Description
Motivation is a psychological feature that arouses an organism to act towards a desired goal and elicits, controls, and sustains certain goal-directed behaviors. It can be considered a driving force; a psychological one that compels or reinforces an action toward a desired goal. For example, hunger is a motivation that elicits a desire to eat. Motivation is the purpose or psychological cause of an action.
HOW TO MOTIVATE FEMALES TO PLAY POKER ONLINE?
(Business study of Swedish women)
Abstract:The aim of this study is to investigate the main motives behind Swedish females' propensity to play poker online by means of hypotheses testing through regression analysis. Method includes collection of the information on definitions, theories and models about gambling, online gambling (precisely online poker) and motivations to gamble. Five hypotheses have been constructed based on the collected information and the survey have been created and conducted among 397 Swedish female online poker players. Further, based on gathered data, hypotheses have been tested by means of simple linear and multiple regressions. Regression analysis revealed that emotional and material motivations together with accessibility of the game and surrounding atmosphere play a significant role in the reason why Swedish females play online poker for money. It was also found that emotional motivation was a fundamental factor that triggers Swedish women to gamble. Furthermore, research revealed the hypothetical target segment of female Swedish online poker players. Average Swedish woman is between 30-40 years old single woman without children, who live high speed, active life (either studying or working) and who spends around 30.3 hours per months on playing online poker.
ACKNOWLEDGMENT
We would like to express gratitude to our supervisor Mikael Holmgren for the guidance and support during our working process. We also appreciate the help of our opponents and we would like to thank them for their advice and valuable tips. We would like to dedicate this paper to our parents: Svetlana Bochkareva and Viktor Bochkarev; Zhanna Petrova and Viktor Petrov. We would like to express additional appreciation to the respondents in Sweden, who spent their time to help us and fill in the survey. We would like to thank our friends and relatives for their encouragement, care and support.
____________________ Karina Petrova
____________________ Anastasiya Bochkareva
Västerås, May 31st , 2011
TABLE OF CONTENT
ABSTRACT ........................................................................................................................................... ACKNOWLEDGMENT ........................................................................................................................ 1. INTRODUCTION......................................................................................................................... 1 1.1 1.2 1.3 1.4 2. Problem Background .................................................................................................................. 1 Problem Specification................................................................................................................. 3 Research Question ...................................................................................................................... 5 Aim of the Paper ......................................................................................................................... 5
THEORETICAL FRAMEWORK ................................................................................................ 6 2.1 2.1.1 2.1.2 2.1.3 2.2 2.2.1 2.3 2.3.1 2.3.2 2.4 Definitions ................................................................................................................................... 6 Defining Gambling /Gambling routs and Characteristics .............................................. 6 Defining Online Gambling ............................................................................................. 6 Defining Online Poker.................................................................................................... 7 Market Segmentation Process.................................................................................................... 8 Segmenting the Internet.................................................................................................. 9 Motivational Models................................................................................................................... 9 Theory of Intrinsic and Extrinsic Motivation ............................................................... 10 Motivation to Gamble/Play Poker ................................................................................ 11 Formulating Hypotheses........................................................................................................... 13
3.
METHODOLOGY...................................................................................................................... 15 3.1 3.1.1 3.2 3.3 3.4 3.4.1 3.4.2 3.4.3 Scientific Methodology ............................................................................................................ 15 Conceptual Framework................................................................................................. 15 Literature Review ..................................................................................................................... 16 Choice of Theories.................................................................................................................... 17 Survey........................................................................................................................................ 18 Choice of Respondents ................................................................................................. 18 Data Collection ............................................................................................................. 18 Data Analysis................................................................................................................ 21
3.4.4 3.4.5 3.5 3.6 4.
Interpreting Regression Statistics ................................................................................. 24 Descriptive statistics ..................................................................................................... 25 Methodological Issues .............................................................................................................. 25 Validity and Reliability ............................................................................................................ 26
EMPIRICAL DATA ................................................................................................................... 28 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 Emotional Motivation............................................................................................................... 28 Atmosphere ............................................................................................................................... 29 Accessibility.............................................................................................................................. 30 Material Motivation .................................................................................................................. 30 Hours Spend Playing Online Poker ......................................................................................... 31 Occupation ................................................................................................................................ 32 Educational Level ..................................................................................................................... 33 Relationship Status and Children............................................................................................. 33 Age............................................................................................................................................. 34
5.
ANALYSIS ................................................................................................................................. 35 5.1 5.2 5.3 Demographic characteristics .................................................................................................... 35 The Model ................................................................................................................................. 36 The Hypotheses Testing ........................................................................................................... 37
6.
CONCLUSION AND DISSCUSSION....................................................................................... 40
REFERENCES ................................................................................................................................... 44 APPENDIX ...........................................................................................................................................I Appendix A - Estimating Sample Size.................................................................................................. I Appendix B - Survey............................................................................................................................. II Appendix C - Decode and Measurement for Each Survey Question ................................................ IV Appendix D - Homoscedasticity Tests and Residuals Analysis ........................................................ VI Appendix E - Regression Data.............................................................................................................. X
Table of Figures
Figure 1: Estimated internet gambling revenues .................................................................................. 2 Figure 2: Demographic comparison of gambling behavior by gender................................................. 2 Figure 3: Motivation summary........................................................................................................... 10 Figure 4: The hierarchical model ...................................................................................................... 12 Figure 5: Five-factor gambling motivation model ........................................................................... 12 Figure 6: Parallel five-factor model.................................................................................................... 13 Figure 7: Conceptual Framework....................................................................................................... 16 Figure 8: Emotional Motivation ......................................................................................................... 28 Figure 9: Atmosphere ......................................................................................................................... 29 Figure 10: Accessibility...................................................................................................................... 30 Figure 11: Material Motivation .......................................................................................................... 31 Figure 12: Hours Spend Playing Poker .............................................................................................. 32 Figure 13: Occupation ........................................................................................................................ 32 Figure 14: Educational Level ............................................................................................................. 33 Figure 15: Relationship Status and Children...................................................................................... 33 Figure 16: Age .................................................................................................................................... 34 Figure 17: The Hypothesized Model .................................................................................................. 39
Table of Formulas
Formula 1: General Regression Equation........................................................................................... 22
Table of Tables
Table 1: Summary Table of Regression Analysis .............................................................................. 37
1. INTRODUCTION
The first chapter introduces the reader to the field of interest and topic for the study. Moreover, it presents the problem background, develops further into the problem specification and ends with the statement of the research question and the research aim.
1.1
Problem Background
Starting from the ancient times with the primitive betting games and until our times, where gambling takes different forms (from casino games to horse races and lotteries) this is one of the oldest activities of the mankind, which has grown into the enormous business sector. (Carey & Carey, 1984) For some people gambling is seen primarily as an addiction; for others it is just one of the many forms of entertainment, while the third group of people can include those who see gambling as an illegal way of making people spend money. But in spite of all critiques and arguments around gambling, it has proven to be a very successful, huge and rapid growing industry worldwide. (Drozd, 2010) Just about ten years ago casinos, slot-machines and hippodromes were the physical/land-based locations, where people could place their odds and win/lose money. Nowadays technological progress contributed to the development of gambling practices transforming it into digital services. Digital gambling is becoming more popular and spread among people all over the world. It is now on the growing pace of replacing the land-based gambling. (Lloyd et. al., 2010; King et al., 2009; Griffiths, 2003) The start of public and commercial internet exploitation in 1990s has made it possible to evolve the land-based gambling services into the online ones. As a result, in 1995 online gambling opportunities have been introduced to the public (Manzin & Biloslavo, 2008; Wood & Williams, 2009). Online gambling industry in recent years has significantly grown in popularity. This growth is characterized by the increasing number of the online gambling web sites; types of the services available; and relatively relaxed regulations towards gambling activities in the majority of the countries worldwide. Now online gambling has developed into strong industry that generates sufficient and growing revenues. (Wood & Williams, 2009; Griffiths, 2003; King et al., 2010) Since 2001 the estimated internet gambling revenues have grown from about 3.1 billions of dollars to nearly 24.5 billion:
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Figure 1: Estimated internet gambling revenues (Christian Capital Advisory Ltd., 2011)
According to Drozd (2010) online poker is now listed as the second popular gambling activity in the internet space after betting. Nowadays this is one of the fastest growing online gambling forms (Griffiths et al. 2006). The first online poker room - www.planetpoker.com - was implemented in 1998 while the major expansion took place in 2003 (Wood & Williams, 2009). In 2010 poker generated $5.06 billion, which is nearly 21% out of the whole online gambling industry (Murray, 2011). And if betting online is popular among both male and female segments, online poker is by now only man dominated activity (Drozd, 2010; Wood et al., 2007; Griffiths et al., 2010). This could be illustrated by the below figure, where demographic comparison of gambling behavior by gender is presented. Precisely for poker sector, represented by partypoker.com website, men's dominance is evident.
Figure 2: Demographic comparison of gambling behavior by gender (Drozd, 2010)
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As the industry is relatively young, there have been done very little research in the online poker field. Consequently, the full-market potential has not been fully realized and investigated (Meyer et al. 2009; Griffiths et. al. in 2010; King et al. 2010; Wood et al., 2007). The existing researches don't provide the in-depth focuse on the online poker patterns, but rather aggregate and analyze all the different types of gambling in tandem; e.g. by Manzin & Biloslavo (2008); LaBrie et al. (2007); Mowen et al. (2009); Griffiths & Barnes (2008); Lee et al. (2007); Corney & Davis (2010); and some studies with small and representative population samples like Ialomiteanu and Adlaf research in 2001 of 1,254 Ontario adults and Meyer et al. (2009). Described studies have been attempting to explore the online gambling industry and online poker within this industry from different angles, where most of the effort was put into the investigation of the problem-gamblers and the male-customers dominance in the industry and precisely in the poker world (Griffiths et al., 2009; Ialomiteanu & Adlaf, 2001; LaBrie et al., 2007; LaPlante et al., 2009; Griffiths et. al., 2010; Meyer et.al., 2009) However the rapid growth of the online gambling and as a part of it, online poker industries has signed that there are new opportunities and a great potential for the further development. The underestimated and poorly investigated women's segment market might be a great revenue stream for the providers striving to attract the broad customer base especially now, when the competition is tough. (Drozd, 2010) In order to attract, acquire and retain the female segment, online poker providers need to understand the woman's behavior and motivations that make her risking money in order to win more (Drozd, 2010; Perse et al., 2005). As it turned out there has been done a very limited research about just females' motives to gamble (Davis & Avery, 2004); gamble online (Corney & Davis, 2010); and no separate research of women's motivations to play poker online.
1.2
Problem Specification
Swedish market with its strict monopoly on both land-based and online gambling is of great interest for investigation. Country has only one major gambling operator - Svenska Spel that owns 53 percent of market share. At first, the company was in charge for the land-based gambling facilities, such as four casinos. However, 8 years ago it broadened its power to the Internet gambling (Svenska Spel, 2011; Young & Todd, 2008; Jonsson & Rönnberg, 2009, p.300). In spite of receiving a lot of critiques from the EU and accusations in breaking the fair trade laws, Sweden is still insisting on the monopoly in the gambling industry and legally prohibits all other providers within the country. However it does not stop Swedish people to use services of the international providers and actively participate in the poker tournaments and other kinds of gambling entertainment outside the Swedish legislative boarders. There are currently around 265 websites available in Swedish language (i.e. Bettson, Party Poker, Bwin, etc.). (Young & Todd, 2008; Online Gambling Sites in Sweden, 2011)
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Online poker tables were launched in Sweden by Svenska Spel just in 2006 (Young & Todd, 2008). Consequently, this activity is relatively new and poorly researched within the Swedish boarders. From the demographic perspective the market segment of online poker players might be very broad in Sweden. Since anyone aged at least 18 years old (Jonsson & Rönnberg, 2009, p.302) is legally allowed to participate in the game, there are nearly 7,5 million Swedish people (SCB, 2010) who can be targeted by provides for a great fraction of the potential revenue stream. However, traditionally poker was predominantly men's activity. Back in time, women were not supposed to participate in any kind of gambling due to social, cultural and religious aspects (Carey & Carey, 1984). At the present time, the demographic situation in the online poker market is changing, but the typical stereotype that a gambler is a "dashing male figure" does still exist all over the world (Davis & Avery, 2004). The fact that women were not considered as the target segment, contributed to the high opportunity costs for the providers of missing the potential huge customer segment and therefore not gaining profits. (Wood & Griffiths, 2008; Corney & Davis, 2010). Nevertheless, during the last decade the social perceptions towards poker have changed and became more relaxed. According to recent findings the online poker is evidently gaining more and more attention among women. It was estimated that 33% of the poker playing population are women, who at least once a month play for real money stakes. In Sweden this percentage is second only to Austrian women. Swedish online poker playing females account for the 3% of the whole adult population, meaning that among overall 9 million inhabitants over one hundred thousand women played poker online in 2010. (Zupko, 2010) A study by Woods & Griffiths (2008) investigated the reasons why Swedish people play online poker and factors influencing trust in poker web-sites. The qualitative research has been done on twenty-four respondents, of which a majority (16 respondents) has been males. It was found that the possibility to play poker online (but not in the land-based casino) has contributed even more to the Swedish women involvement in the game. Woods and Griffith's (2008) research has revealed that a lot of women tend to swap their genders and register under the men's names, which was obviously impossible in the land-based casinos. Therefore, women became more confident and eager to participate in the online poker where no one would under evaluate their skills. This rise in the women's participation in the online poker games is certainly favorable for the providers striving to attract and retain as much players as possible (Drozd, 2010). The new segment (women) involvement in this industry means that providers should think of new marketing tactics in order to generate the appealing and attractive space for women in the internet poker world. However, as in any business sphere, in order to win the competitive advantage the most essential issue is to understand customers "behavior, drivers and motivations that make them feel like purchasing the product/service". (Montgomery, 2008)
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Although, there are several studies that attempt to investigate women's motivations to gamble online (Lee et al. 2007; Corney & Davis, 2010), it was hardly possible to find any sources concerning the motivations of Swedish women to play internet poker. The only study of Wood & Griffiths (2008) of Swedish people playing online poker does not make emphasis on women separately. Moreover, it is restricted to only 24 online poker players, which, taking into account the Swedish population can't be considered comprehensive in attempt to understand female's motivations to play poker online. So, despite the fact that providers worldwide have started to investigate women's behavior, majority of the existing researches are about online gambling as the whole without distinguishing online poker and female segment, and it seems that there is still a gap in this investigation in Sweden.
1.3
Research Question
The research question is as follows: 'What motivates Swedish women to play poker online for money?'
1.4
Aim of the Paper
It is important to understand the new developing segment in the online gambling industry, so service providers could manage to develop appropriate tactics and campaigns to reach this segment and to make it profitable. Therefore, this came as the first and most important goal for the online poker providers - to understand women's motivations, i.e. what demographic characteristics combined with the external and internal motivational factors make them play the game. (Drozd, 2010; Wiebe, 2008) Consequently the aim of this study is to investigate the main motives behind Swedish females' propensity to play poker online by means of hypotheses testing through regression analysis.
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2. THEORETICAL FRAMEWORK
The second chapter presents the theories, models and definitions that has been the basis for the study and has been constructed through literature review.
2.1
Definitions
Further understanding and definitions of main terms and notations used for current study are presented and explained.
2.1.1 Defining Gambling /Gambling routs and Characteristics
According to Cabot (1999), the attorney with the practice in gaming law and internet gaming, gambling can be defined in the following way: .. any activity in which a person risks something of value on the outcome of an uncertain event, in which the bettor does not exercise any control or is determined predominantly by chance . (Dewar, 2001) Gambling has a long prehistory that has started already in the ancient times. The activity that started as an entertainment has grown up into a huge - multibillion business nowadays with lots of casinos, slotmachines, lotteries and various locations where one can bet on horse races, sports and all the possible activities with the unknown outcome. The aim of any gambling activity is to win prize, or more precisely money. (Dewar, 2001) Drozd (2010) suggests the following classification of gambling types: The games of skill where outcome is not only fortune-driven, but the level of gamblers' knowledge, experience and professionalism play the most crucial role. Such activities include sports betting, cards games (poker) horse racing. The games of chance. Here the outcome is not controlled by people and cannot be managed by means of any knowledge, but rather odds and probability are the main linkage to the possible success or failure. These are bingo, casino games, i.e. roulette, lottery.
2.1.2 Defining Online Gambling
With the growth of technological advances the means by which gambling activities can be delivered to the potential customers is becoming even broader. Drozd (2010) suggested dividing the global gambling market into two broad parts, i.e. land-based gambling and digital gambling. The gambling market nowadays is one of the most profitable segments when it comes to the overall media and entertainment industry. The market offers a broad range of products and services which can be brought up to the consumers by means of various platforms. (Drozd, 2010; Wood et al. 2007)
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Gambling industry inculcated the advances of information and communication technologies and knowledge about virtual business. About ten years ago it started offering services online. In order to make any online gambling portal or casino to function, a complex technological solution has to be implemented. At the same time from the customer perspective everything is need is the access to the internet and a certain amount of money. (Manzin & Biloslavo, 2008) In various literature several notions could be found that refer to gambling through Internet: 'online gambling', 'internet gambling', 'cyber gambling', 'casino gaming on the internet', etc. Internet gambling consist of two types of activities. First, gaming meaning casino type games online e.g. poker, blackjack, roulette. Second, betting or wagering referring to various racing (e.g. horse, dogs) and sport events (e.g. football, hockey, basketball) betting. (Manzin & Biloslavo, 2008) Online gambling opened up opportunities for people to gamble anytime from anywhere, therefore expending gambling market and transforming many potential players (e.g. who didn't have landbased casino in the area) into real ones. People are no longer dependant on being geographically restricted to countries or regions. (Manzin & Biloslavo, 2008; Layton & Worthington, 1999)
2.1.3 Defining Online Poker
Online poker is one of the forms of online casino entertainment possibilities and at the same time the game of skills (see 2.1.1) that requires certain talent, intelligence and constant practices. There are three types on online poker services available at the present moment: Web-based poker, which can be played directly in the internet without any need to download additional software. This is the most popular form of online poker and the possibility to play in the internet for real money Download-based poker where the software needs to be downloaded in order to be able to play. After downloading there is no requirement to be connected to the browser. Live dealer poker service. This kind of online poker has not yet reached so much popularity as the two previously described ones but it is an existing development that combines both reality and web space. Users are able to see and interact with dealers by means of video links. (Drozd, 2010) Nowadays it is possible to play online poker for real money as well as without any kind of investment. There exists a significant difference between online poker and traditional in-person one. First, the rate of the play online is much faster, since no time is wasted on shuffling and dealing cards. Second, players are not able to see each other, therefore regular means for predicting the behavior like watching mimics and facial reactions are not usable any longer. Players now are
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analyzing each other by other factors such as betting patterns, reaction time, speed of play and so on. (Monaghan & MacCallum, 2006; Wood et al., 2007)
2.2
Market Segmentation Process
Market segmentation process consists of three stages: segmentation, targeting and positioning. The segmentation is essential for strategic marketing. It involves defining market segments, choosing suitable market target and deciding on how and where position the product/service. (Baines et al., 2008, p. 216) Market segmentation is "the division of a mass market into identifiable and distinct groups or segments, each of which have common characteristics and needs and display similar responses to marketing actions" (Baines et al., 2008, p. 217). For consumer goods/services' markets, certain segmentations are used for groups of customers with similar needs and wants. Most common bases are classified as Geographic, Demographic, Psychographic and Product-related. (Kurtz et al, 2009, pp. 261)
•
Geographic segmentation means dividing consumers into segments by their location. Variables here could be regions; countries; areas; population size; climate; job growth and so on. The main idea behind it is to identify core regions where certain product/service could be distributed.
• •
Demographic segmentation - customer groups are defined by demographic variables such as age; gender; ethnic group(nationality); education level; income attributes; occupation; social class belonging; household type and life stage. Psychographic segmentation is intended to provide deeper insights into consumer behavior. It is based on dividing people into groups with similar interests; opinions; characteristics; values and lifestyles. Psychographic segmentation is the most efficient when applied together with demographic and geographic ones.
•
Product-Related segmentation helps to identify customer segments by their connection to product/service. This segmentation is based on benefits that customers seek from the particular product/service. Other variables are for example usage rates - the amounts that customers purchase and how often product/service is used; brand loyalty, etc.
(Baines et al., 2008, pp. 223-239; Kurtz et al, 2009, pp. 261-278). After dividing markets into segments the next step is to decide which of these segments to target. This could be done by evaluating market segments by effectiveness or attractiveness factors. The third part of segmentation process - positioning - starts when segments have been defined and specific market targets have been identified. Positioning has two important elements - physical
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attributes of product or service and how those are communicated and perceived by customer. (Baines et al., 2008, pp. 246-251)
2.2.1 Segmenting the Internet
With the increasing importance of Internet and online sales it became important for companies and marketers to understand web users and shoppers (Donthu and Garcia, 1999). Internet has eliminated geographical borders and boundaries between companies and its customers and has initiated firms to offer more standardized products/services. Those products and services are offered internationally, which may cause companies to face problems associated with different characteristics and behaviors of customers from all over the world. (Barnes et al., 2007) Kau et al (2003) study of topology of online shoppers indicated that it is essential to understand different customer segments involved into online activities in order to be able to develop effective strategies and tactics for attracting and keeping those customers. It was found that online and traditional customer segments significantly vary in terms of importance to convenience, risk aversion, impulsiveness as well as more typical dimensions such as age, gender, patterns, social group, etc. Miller (1999) highlighted another criterion for segmenting Internet users - by manner in which they use it: for academic purposes and studying; for personal use (e.g. entertainment, shopping, communication, etc); for business; etc. The life stage during which people are introduced to Internet is also important and has a lot to do with what people want and need from Internet. The understanding of characteristics of different segments and how they use the Web is crucial for companies that are operating online businesses.
2.3
Motivational Models
"Consumer research looks into the motivations and personalities of an individual in terms of consuming or buying a particular product or service, later turning this information into strategies geared at gaining a particular segment of the market that the company targets or centers on" (Montgomery, 2008). The theory of consumer behavior is based upon the three major categories - motivation, cognition, and learning. The motivation can be said to be the fundament in the sequence of the three components. Motivation in other words is the aggregate of drivers, wishes, urges and desires which lie at the roots of consumer behavior. Cognition and learning are products of mental phenomena and can change over time in response to the external factors. (Bayton, 1958) The important thing about motivation and its nature is that it can be hardly classified as the unitary phenomenon. People have different amounts as well as kinds of motivations, i.e. it is not only stage of motivation but also the kind. (Ryan & Deci, 2000)
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2.3.1
Theory of Intrinsic and Extrinsic Motivation
From the psychological perspective motivation is the combination of external and internal factors that build up people's behavior. In the business environment motivation plays a vital role as it influences consumers' behaviors. So, it is of a great importance for the companies providing a service or selling a product to understand factors that motivate people to spend their money. This knowledge will consequently help providers to come to the decision how those factors can be manipulated in the most favorable for the company way. According to several studies in the field of gambling and the motives behind it, intrinsic motivational factors are more common for those poker players and other gamblers who are seeking for socializing and entertainment and are not commonly associated with the problem-gambling. At the same time extrinsic factors are the materialistic needs that make people desperate to winning and are more commonly seen among poker players with problematic addiction. (Lee et al., 2007) Intrinsic motivational motives are in other words the internal, i.e. based on personal needs, cognitions and emotions, factors. Person does some kind of activity not for some "separable consequence" but for the self-esteem and inner satisfaction. While extrinsic factors are those external triggers that are caused by environmental, social and cultural surroundings of a consumer. (Ryan & Derci, 2000) Ryan & Derci (2000) summarized the main theoretical concepts of both kinds of motivations in one graph (Figure 3):
Figure 3: Motivation summary (Ryan & Derci, 2000)
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This theoretical presentation subdivides the motivation into three groups, where the extrinsic motivation is stated to be the largest. Two other types of motives, i.e . amotivation and intrinsic motivation, are smaller and of an equal size without any additional subdivisions. In addition to this vertical division, there is a three-row horizontal division: regulatory styles, i.e. the theoretical names of the concepts; associated processes, i.e. the explanation/real-life description of the motivations; and perceived locus of causality, i.e. how the motivations are perceived in reality. This third row of perceived locus of causality explains the broad specter of the extrinsic motivation group, pointing out that the theoretical view on the motivation does not strictly corresponds with the real perceptions. The sector is therefore also subdivided into extrinsic and intrinsic traits with the more incline to the right towards the perceived nature of the motivation. (Ryan & Derci, 2000)
2.3.2 Motivation to Gamble/Play Poker
Understanding gambling behavior and motives of gamblers is the primary goal for marketers who strive to create the persuasive messages for each target group (Mowen et al., 2009). The theory of market segmentation suggests that depending on features possessed by different groups (i.e. national peculiarities, age differences, economic factors, genders, etc.) there do exist different approaches for targeting the particular segment due to the variations in their perceptions, attitudes and motivations when purchasing product/service (Hong & Jang, 2004; Davis & Avery, 2004; Laplante et al., 2009; Griffiths at al., 2010). The motives and reasons to gamble/play poker are different depending on the perspective from which to consider the results. Obviously the most common reason to gamble is "to win" or "to win money". Still even both motives sound to be very related they include a wide spectrum of personal traits and primary factors. The Swedish National Institute of Public Health applied three different approaches in the investigation of gambling motivation and involvement; those are sociological approaches, economic and cultural aspects of gambling behavior. (Binde, 2009) In their investigation of trait antecedents of gambling, Mowen et al. (2009) applied a hierarchical model of personality to make the assumptions of correlations between traits and propensity to gamble and build up hypotheses of positive/negative correlations. They applied a rather psychological approach to determine the traits of gamblers and their motives in different forms of gambling including online facilities. For example, it was found that financial conservatism is negatively related to the online forms of gambling placing the role of money and saving over the insecure possibility to earn more. At the same time introversion was found to be positively related to online gambling stressing the solitary nature of presence online. The openness to experience was also considered to be important characteristic of the online gamblers. Figure 4 below represents the division of motivational traits to gamble/play online poker in the hierarchical model proposed by Mowen et al. (2009):
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Figure 4: The hierarchical model (Mowen et al., 2009)
Both Mowen et al. (2009) and Hong & Jung (2004) studies suggested the importance of impulsiveness and emotional instability of the major gamblers' group stressing the inevitable role of emotional motivations when playing for money. Interestingly it was found out that sensation seeking was not statistically significant determinant of the potential gambler. In their study of problem gambling and psychological motivations Lee et al. (2007) have proposed two Five-factor gambling motivation model. The first one, presented in Figure 5, makes the emphasis on the monetary impact and the implications of gambling severity:
Figure 5: Five-factor gambling motivation model (Lee et al., 2007)
The model (where M stands for 'motive') places a great importance of the psychological/emotional features that stand behind the economic factor, i.e. monetary motive. This monetary/extrinsic motivation emphasis corresponds with the above Ryan & Derci (2000) three groups of motivational model, where the middle row "Extrinsic motivation" merges both external and internal motives stressing out their interconnection when it comes to the perceptions.
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The second model in Figure 6 is the parallel five-factor model and discuses the independent influence of the 5 factors in gambling severity:
Figure 6: Parallel five-factor model (Lee et al., 2007)
The parallel model emphasizes the independence of all the factors on gambling intensity. According to the results of the five-factor model investigation, it was found out that monetary motivation does have the direct effect on the gambling severity, while such factors as excitement and avoidance affect gambling behavior only through money motive. Various other factors could become incentives for people to gamble. Jonsson and Rönnberg (2009) in their article 'Gambling in Sweden' discussed such factors as positive and negative emotional state of the person; various events on gambling market and wrong believes and expectations from gambling.
2.4
Formulating Hypotheses
According to Mowen et al. (2009) and their research based on the 3M model discussed in the theoretical background of this study paper, emotional drivers impact positively on the intensity of gambling/online poker gambling. At the same time Lee et al. (2007) stressed out that women were more than men driven by the emotional triggers to be involved in the gambling activities. The positive relationship was also found by Wood & Griffiths (2008) and Corney & Davis (2010). Thus the first hypothesis is: H1: There is a positive statistically significant relationship between Swedish women propensity to play online poker and emotional motivation, i.e. self-enjoyment, impulsiveness and excitement all together. Previous investigations of the gambling/online poker propensity among both men and women found out the significant and positively directed relationship between involvement into the game and economic trigger. Lee et al. (2007) stated that monetary motive is the only one that has the direct impact on gambling severity while all the other motivations (see five-factor model in the theoretical
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background) affect gambling behavior indirectly through money motive. What is more, the existing researches stress out that the money motive is more common among men players. (Mowen et al., 2009; Layton & Worthington, 1999; Lee et al. 2007) Thus the second hypothesis is: H2: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and material motivations. One of the earliest studies of the gambling and socio-economic implications stressed out the importance of ease and convenience when it comes to the accessibility of the gambling service (Layton & Worthington, 1999). Moreover, Wood et al. (2007) found that accessibility and distance from casino were some of the top reasons to gamble online. Corney & Davis (2010) have discovered that around 90% of interviewed women admitted that accessibility of the internet influenced their propensity and frequency to gamble. The positive involvement in the online gambling activities due to the easy and comfortable accessibility, i.e. from home, work, etc. was also found by Wood &Griffiths (2008). H3: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and level of accessibility of the game. The positive relationship was also found between the private and relaxed atmosphere the online access gives to women and their frequency and comfort to play online gambling games (Corney &Davis, 2010; Wood & Griffiths, 2008). In their investigation of the reasons to gamble online versus land-based casinos, Wood et al. (2007) found that privacy issues and negative attitudes to the crowdie surroundings were among the most popular motivations to choose the internet gambling services. H4: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and the surrounding atmosphere As it was stated earlier, women were traditionally considered to be motivated by the set of the emotions that trigger them to play online poker or are other gambling activity. Lee et al. (2007) found that the amount of women admitting emotional motivation was around 70%. Also Corney & Davis (2010) stressed out this fact in their investigation of females' attractions towards online gambling. Thus the 5th hypothesis is: H5: Emotional incentive, i.e. excitement, enjoyment, adrenaline, has the largest/the most important impact on Swedish women's propensity to play poker online.
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3. METHODOLOGY
3.1 Scientific Methodology
Current research reflected the concept of positivism, where authors prefer 'working with the observable social reality and the end product of such research can be law-like generalizations similar to those produced by the physical and natural scientists' (Remenyi et al. 1988 as citied in Saunders et al., 2009, pp.113). The phenomena/topic authors observed lead to generation of a credible data and research strategy based on existing theories and models as well as hypotheses. Authors attempted to carry out the research in a value-free way, meaning that authors were not influenced by the subject of the investigation and didn't influence it themselves. This was achieved by carefully designing the research process and using highly structured methodology. (Saunders et al., 2009, pp.113-114) There are two possibilities to decide what is true or false and draw fair and relevant conclusions deduction and induction; the first one is based on logic, while second - on empirical evidence (Ghauri & Grønhaug, 2010, p. 15). Current research was based on deductive approach, meaning that the theories and hypotheses were build first, before collecting empirical data. Authors performed detailed literature review on the selected research topic and, based on this literature review, built up the theoretical framework and the rest of the research process. Authors deducted five hypotheses from the existing literature and tested those using existing concepts in statistical analysis: H1: There is a positive statistically significant relationship between Swedish women propensity to play online poker and emotional motivation, i.e. self-enjoyment, impulsiveness and excitement all together. H2: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and material motivations. H3: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and level of accessibility of the game. H4: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and the surrounding atmosphere H5: Emotional incentive, i.e. excitement, enjoyment, adrenaline, has the largest/the most important impact on Swedish women's propensity to play poker online.
3.1.1 Conceptual Framework
In order to study the research topic, answer research question and achieve the aim of the study, authors developed a conceptual framework based on the performed literature review:
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Figure 7: Conceptual Framework (own illustration)
Quantitative research method was chosen in association with deductive approach. Quantitative research involves measurements and is focused on testing and verification. Therefore for current study, where hypotheses have been constructed, quantitative method was the most suitable since it allowed accepting or rejecting these hypotheses in a logical and consistent way. Authors chose to conduct the pre-structured survey on a sample of respondents that was taken from overall female population of Sweden over 18 years old. Conceptual framework, summarized in figure 7 included theoretical background about Segmentation/Demography as well as Motivational models - Hierarchy of Traits and 5-factor Models (from which extrinsic motivation factors such as accessibility and material needs and intrinsic motivation factors - emotional and atmospheric have been identified). Based on those theories; distinguished factors; literature review and hypotheses, survey for testing those hypotheses has been constructed. With help of statistical analysis, precisely multiple and single regressions as well as descriptive statistics, data collected from the survey have been accessed, analyzed and interpreted. By testing the hypotheses and identifying which are accepted and/or rejected, authors achieved the research aim and answered the stated research question. The idea of the research was not only to identify motivations of some hypothetical Swedish woman to play online poker for money. It was also relevant to understand the general characteristics of the typical female Swedish online gambler in order to get the picture of the potential profitable segment among Swedish female poker players.
3.2
Literature Review
Authors began the study by collecting relevant ideas; theories; models and previous researches about gambling, online gambling industry, online poker and motives behind people playing games for money in the Internet. Key academic theories within research area have been identified and their
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overview was presented as theoretical framework and also used in introduction. Authors started out by retrieving more general information about gambling industry and motivation and then narrowed it down to online gambling, online poker and females playing it and therefore came up with limited field of study and precise research question. Several types of sources have been used for retrieving the information for the research. Both secondary and primary sources have been located with help of tertiary sources. Those 'search tools' included search engines such as Google -http://www.google.se/ and Google Scholarhttp://scholar.google.se/; subject directories - Yahoo! -http://www.yahoo.com/. Moreover, several databases have been used - EMERALD (http://ep.bib.mdh.se:2086/); ABI/INFORM Global (ProQuest); LibHub (http://ep.bib.mdh.se:3655/libhub). (Saunders et al., 2009, pp. 86-87) Due to the fact that most of the information has been accessed online, certain parameters of the search have been defined. Language of publications was English since the report had to be written in English as well; search area as has been mentioned was within gambling and online gambling industry as well as people's motives for gambling online; geographical area of search was not limited, documents from all over the world written in English and within subject area have been reviewed. Certain ''key words' such as 'gambling'; 'online gambling'; 'Internet gambling'; 'online poker'; 'motivation theories'; 'segmentation'; 'women gambling', etc. have been defined and used for searching both primary and secondary sources through tertiary sources. (Saunders et al., 2009, pp. 75-76) Primary sources, which are first occurrences of documents that were used for literature review and theoretical framework, included several reports and studies connected to gambling and online gambling research, published by Swedish National Institute of Public Health and European Parliament's committee on Internal Market and Consumer Protection (IMCO). Secondary sources included books and journal articles retrieved with help of described tertiary sources. Various article on chosen topic have been found in 'European Journal of Marketing'; 'Journal of Marketing'; 'Journal of Gambling Issues'; 'Journal of Advertising Research'; 'Journal of Consumer Marketing'; 'Journal of Business Research'; etc. Books such as 'Marketing'; 'Contemporary Marketing'; 'Gambling in Sweden', etc. have been found in Mälardalen University and Västerås city libraries.
3.3
Choice of Theories
The theories applied in this paper were chosen after the careful and detailed literature review. The theoretical base attained from the specific scientific studies and books served as the fundament for creation of the conceptual framework for this research. As the incline of this study paper is on characteristics of women playing online poker and their motivations, the theoretical framework was subdivided into three parts.
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First, it was important to get the background on overall gambling characteristics, i.e. industry with its opportunities, and precisely online poker, in order for authors to get deeper knowledge and exact picture of chosen business sector. Then, the insight on the marketing segmentation was needed in order to find out the main characteristics, i.e. marital status, occupational and educational levels etc., of the potential online poker playing women. These theories were mainly needed in order to make up the second part of the survey, where the aim was to receive the personal features of the women market segment. And for the last and the most important part of this research, the deep investigation of the motivational theories and models was made. These theories were essential in order to build up the likert-scales of the survey and according to the attained responses apply the statistical analysis, i.e. multiple regressions. This was supposed to identify the significance of the theoretically suggested motivations to play poker online for the women in Sweden and come to conclusion which drivers are the most important.
3.4
Su r v e y
3.4.1 Choice of Respondents
As have been mention, the current study was focused on women in Sweden who play poker online for real money. The total population of the country for 31th of December, 2010 was 9,415,570 people of age from 0 to 111, where 4,725,326 people were women (SCB, 2010). Out of 4,725,326 women 3,729,091 are older than 18 years old, which is the legal age from which people are allowed to gamble (SCB, 2010). According to Fisher (2007, p. 189) and Saunders et al. (2009, pp. 218-219), the suitable sample size for the research depends on the size of the margin of error researchers are prepared to accept and the size of the population from which the sample is going to be drawn. For current research the authors accepted 95% confidence/certainty level and the margin of error/confidence interval of +/- 5%, in other words for example if 53 % of sample prefer category A, authors were 95% sure that the same estimate for the whole population within the same category A was going to be 53% +/- 5%, between 48 and 58%. Taking into account confidence level; margin of error and the total size of the population from which the sample was taken - 3,729,091 (SCB, 2010) women in Sweden who play online poker, by using table in appendix A, authors estimated the required amount of completed questionnaires, which equaled to 384 surveys. (Fisher, 2007, p. 190; Saunders et al., 2009, p. 219)
3.4.2 Data Collection
Primary data for the research was collected through a survey. Authors used analytical type of questionnaire, because with this type, it is possible to understand the relationships and identify
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independent, dependent and extraneous variables which is the aim of the research (Ghauri & Grønhaug, 2010, p. 119). Moreover, in analytical surveys performed literature review and constructed theories are of great importance while structuring the overall research that is exactly the case with current study, where a lot of emphasis was put on existing literature, theory and researches. Furthermore, employing analytical type of questionnaire gave authors possibility to manage independent, dependent and extraneous variables with help of statistical techniques and analysis, such as multiple and single regression analysis. The survey was logically structured: starting with similar general questions and moving on to more specific personal ones in the end of the survey. Pre-structured survey is shown in Appendix B. Authors attempted to construct relatively short survey, so respondents wouldn't get tired and loose interest while filling it in. The language used is simple; easy to understand and straight forward. Authors made sure to use words that don't have double meaning and that overall language is easy to understand for people with different background (education, knowledge, etc) In addition all questions and explanations were formulated in polite and soft nature, so not to offend, annoy or provoke the respondents. (Ghauri& Grønhaug, 2010, pp. 123-124) Questions were formulated so there was no escape route for respondents to avoid answering the question. Authors didn't provide answer option such as 'no comment', therefore ensured respondents to choose one of the answers. (Ghauri & Grønhaug, 2010, pp. 122, 124) Each question in the survey was aimed to measure only one variable/ dimension, so respondents and authors wouldn't get confused, moreover, each question has been carefully coded in order for authors to be able to perform statistical analysis of the data. A detailed explanation of what each survey question was intended to measure and decode for each question is presented in Appendix C. Types of primary data included status and state of affairs data, which data on demographics and socio- economic nature. For current research authors were interested in retrieving information about age, marital status, education level, occupation and amount of time respondents spend playing poker. Questions were based on the segmentation theory and its implications. Six questions were constructed based on segmentation theory in order to collect status and state of affairs data. Two questions about the age of the respondents and amount of time spend playing poker were of open- ended nature, so respondents were able to fill in their exact age and their own estimate of time spend playing poker and not tick a box with suitable range. That was done in order to be able to identify the exact average age of the respondents and exact number of hours they play poker online. Other four questions were closed questions, where respondents were offered to choose one of the provided answers: two dichotomous questions which had just two alternatives to choose from and two multiple-choice questions were employed. (Fisher, 2007, pp. 193-199; Ghauri & Grønhaug, 2010, p. 100)
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Second type of primary data gathered was data on motivation. Collected data helped to understand motives and stimuli behind woman playing online poker. Twelve likert-scales one of the forms of rating scales were constructed in order to find such factors as driving forces and motives that influence respondents' behavior and are behind them choosing to play online poker for money. Likertscales were based on motivation theories and models chosen as theoretical framework for the research. Respondents were asked to choose a number from one to seven that best represents the extent to which provided statements correspond to the reasons why they play poker online. The spread of answers was between 'does not correspond at all' - one to 'corresponds exactly' - seven. (Fisher, 2007, pp. 195-196; Ghauri & Grønhaug, 2010, p. 101) Pre-structured survey have been spread among the female customers of Casino 'Cosmopol' in Stockholm city by authors and their friend who works in the casino and have access to the potential respondents. It was assumed that women, who gamble in land-based location, were possibly gambling online as well. Survey was designed, so the first question identified the respondents who play online poker, moreover, when author were in the casino on 15th of March and 27th of April, 2011 between 14.00 - 19.00 pm they were first directly asking potential female respondents if they play poker online and in case of positive reply asked them to fill in the survey; in total during the first visit authors collected 47 completed questionnaires and during the second visit 84. Friends of authors have been giving out surveys to female customers, who agreed to fill it in during 4 days between 11.04.2011-14.04.2011 and during 4 more days between 25.04.2011-27.04.2011 and on 29.04.2011. The total amount of given out surveys for both time periods exceeded 650, where just 230 have been fully completed. Besides casino 'Cosmopol' authors have spend time in 'ATG' - Swedish Horse Racing Totalisator Board locations trying to reach potential respondents with the same technique. On 14 th of March, 2011 both authors have been in 'ATG' locations in their home-towns in Västerås and Märsta, between approximately 12.00 and 17.00 pm. Both authors together collected 36 completed surveys. Even though that 'ATG' have nothing to do with poker, it is the place where people place bets on horse racing, which is one of the form of gambling, therefore the audience visiting 'ATG' gambles and possibly plays online poker (ATG the Company, 2011). Authors were asking any female 'ATG' visitors if the play online poker and if the answer was positive asked them to complete the survey. Coverage of respondents from three different cities in Sweden - Stockholm, Västerås and Märsta provided authors with wide sample of the population not located in one place/city in other words geographical area, and therefore generalization of the result on this sample is possible. As calculated above the amount of completed surveys that was required for the study based on total population size, confidence interval and level was 384, where total number of completed survey that authors manage to collect equaled to 397, which is more than enough in order to achieve representative results and make conclusions general for overall population. The rate of response is
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calculated by dividing the total amount of collected surveys (397) with total number of given out surveys (?820) and multiplying by 100%. The respond rate equaled 48,4% for current study.
3.4.3 Data Analysis
For testing the deducted hypothesis, using data collected from the survey, authors decided to perform regression analysis. In order to investigate the important and significant relations between dependent and explanatory variables in business statistics or economic research, the regression analysis can be applied (Ghauri & Grønhaug pp.177-184). Barrow (1996, p.220) stressed out the applicability of regression analysis as a tool to measure the impact of the exogenous, i.e. explanatory, factors on the endogenous one, i.e. dependent variable. By entering step-by-step the variables into simple linear regression one can assess the change of the explanatory power of the new model (multiple) and see whether the power rises, remains unchanged or diminishes. If the power rises then this means that the additional explanatory variables were needed; if the modelweakens in its explanatory power then the extra variables ruin the main regression principles/assumption: Linearity of the relationship between predictors and dependent variable Homoscedasticity/ homogeneity of variance Independence of the error terms Normal distribution of errors
The violation of the main assumptions can be checked, which was done in this particular study. The violations of linearity were detected with the help of observed residuals versus fits in Minitab, where the points have been symmetrically distributed around the line. Independence of the error terms was detected by checking if there is a presence of autocorrelation. Graph residuals versus order can provide the visual evidence of presence or absence of the autocorrelation: the cluster of residuals with the same sign told about the existence of positive autocorrelation, a negative autocorrelation was indicated by rapid changes in the signs of sequential residuals. The normal probability plot provides the evidence of normality or non-normality otherwise. If the distribution is normal, then the residuals have to be proportionally placed close to the diagonal line. According to homoscedasticity assumption the dependent variable has to exhibit similar variances across the range of predictor variable. There is a graphical method called boxplot to check this assumption of the regression analysis. All the assumptions were checked (see Appendix D). Obviously it is hardly possible to get perfect matches with the theory because of the data specification/encoding, broad sample and probably sometimes random answers. However, taking into account that the original data is coded with theequal intervals, the regression can be considered as the appropriate tool to make the particular
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analysis since even with the few violations of the regression assumption, the overall trend towards the proposed theoretically rules is held in the précis model. (Cottrell, 2003) Multiple regression analysis Multiple regression analysis is a procedure to create the linear equation that shows the statistical correlations between Y and X variables:
Formula 1: General Regression Equation
Y - Dependent or endogenous variable. In this research that was the proxy of the online poker playing affection among women, i.e. hours spent on the game per month. X1, X2, X3, X4 - Explanatory/predictor/exogenous variables. In the regression analysis the direction of the causality is assumed to be directed from the explanatory, i.e. exogenous, variables towards the dependent variable. Here these were the kinds of extrinsic and intrinsic motivations that were theoretically assumed to cause the involvement into online poker among women, and have the statistically significant impact on the dependent variable. As it is evident from the survey (Appendix B), there are four types of motives behind the women's involvement into the online poker games. All those types were investigated by means of three likertscale statements for each type of motivations and then divided into two major groups, extrinsic and intrinsic motivations. In order to run the regression analysis with four potential predictors, i.e. emotional motivation, atmosphere, accessibility, and material motivations, the likert-scale answers from 1 to 7 in out of each three questions group were aggregated and the average was found, that represented each motive (Appendix E). ?1,?2,?3,?4 - The coefficient shows the elasticity, i.e. the amount of change in the endogenous variable due to change in the exogenous variables. The sign of the coefficient indicates the direction of the relationship, either positive, plus sign, or negative, i.e. minus sign. ? - The constant. Considering that there is zero relationship between explanatory variables and the dependent one this is going to be the intercept of the x-axis with the y-axis, if presenting the results in the graphic way. ? - The error term. In other words it represents all other variables that have the probable impact on the dependent variable but were not included for some reasons. (Barrow, 1996, pp.241-265) Regression analysis with the non-numeric variables If regression analysis is done with non-numeric explanatory variables, i.e. different kinds of motives as in this particular research, then the implementation of the codes is essential. This is called
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"dummy coding" if one uses binary choice variables, i.e. male/female, and is coded by means of '0' or '1' to show the different categories, or if this is the case of using likert-scales results, i.e. more than two possibilities, the digits from 1 to 7, for example, are used as the codes to demonstrate the levels/intensity. In other words, one assigns numbers to the non-numeric data in order to apply the regression analysis. (Winship & Mare, 1984) The data, that is non-numeric, can be of the different types: Categorical variables: These variables have two or more categories but those are not directed by some intrinsic order. The gender, i.e. male and female, can be an example of the categorical variable and can be coded by means of two different digits, for example 0-male and 1-female, and like that presented as the ready data for statistical analysis. This is also called dummy-coding. Ordinal variables: The difference between categorical and ordinal variables is that there is a clear sequence/levels of the variables. For, example if there are different opinions when filling in the survey towards online poker, i.e. "I play poker online because I want to earn a lot of money easily and quickly" and variants of answers "does not correspond at all", "corresponds a little", "corresponds moderately", "corresponds a lot", "corresponds exactly", then those variants of answers can the categorized by order with the help of numbers from 1 to 7 or some other final digit and investigated by means of the regression analysis. Interval variables: These variables are nearly the same as the ordinal variables in the sense of sequential ordering but the intervals between the values are evenly spaced. (G.-Martin, 2009) Likert-scale results as Explanatory Variables in Regression analysis There are no notions about the distribution of the explanatory variables in that kind of the regression analysis. Nevertheless, parameter estimates generally are only interpretable for nominal categories or numerical data. The coefficient is decoded as the difference in the mean of dependent variable, Y, for each unit change in the independent variable, X. If X, the predictor, is categorical, so a unit change simply postulates switching from one category to another. Ordinal independent variables are regarded as either nominal unordered categories or numerical. In the case of nominal unordered categories, the assumption about the order is neglected. In the second case, one is making assumptions about the variations between the scale items. If the distances can be reasonably considered equal and meaningful, then it is rational to consider the exogenous factors as numerical (a unit change from 1 to 2 is equivalent to a unit change from 3 to 4). (High, n/d) Likert-scale independent data in the analysis can be considered as the ordinal predictors, which are categorical explanatory variables where the categories have a natural ordering. One may choose to investigate the particular data as if it were continuous, nominal or categorical variables. The most common and therefore applied in this research way to treat ordinal predictors is as if it was a continuous data. (Winship & Mare, 1984)
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So, qualitative predictor data can be also analyzed by means of statistical/econometric tools traditionally applied for the numeric data. Regression analysis is one of these tools. After coding data (in case of likert-scale the rank of answers from 1 to 7 for example) the regression can be easily run if the data approves several important assumptions: 1. It must be a full likert-scale data, i.e. the composition of several questions with the multiple likert-scale answers. 2. The intervals between the answers must be reasonably considered equal (at least nearly equal) in order to treat the data as continuous and run the regression analysis. 3. Change in categorical predictor is interpreted as switch from one category to another and the consequence impact on the dependent variable. (Winship & Mare, 1958) Consequently, in this paper the likert-scale answers from 1 to 7 were considered as the coded ordinal predictors with the equal intervals.
3.4.4 Interpreting Regression Statistics
The regression analysis, in other words is rejection or acceptance of the null hypothesis (H 0). The regression output helps to determine whether the coefficients of the desired results are equal to zero, i.e. statistically insignificant (H0 is accepted). Consequently, in this study paper the H0 is desired to be rejected and that the tested hypotheses are statistically significant. All the regressions have been run in the statistical software Minitab. In this research the regression results and the overall model was considered to be significant within 95% confidence interval. Meaning that probability values p less than 0.05 (5%) indicate the significance of the achieved results and implied on the acceptance of the hypotheses tested in this paper. The regression analysis provides different measures of the significance of the tested models and the relationships within the models. However, this study paper was concentrated on the most important ones for this research, precisely, R2 , R2adjusted, F, t-statistic, p values and? coefficients. (Barrow, 1996, pp. 241-265)
T-statistic/? coefficients/p-values
T-statistic's p-value provides the information about the significance of the? coefficient. Minitab software computes the probability values directly. So, taking into consideration that in this research all the results are significant at the 95% confidence level, the p values under 0.05 will indicate the statistical significance of the? coefficients. (Minitab, 2011)
R2 (R squared)
R2 is also called the coefficient of determination. This is the measure of the correlation of the dependent and predictor variables in the tested model. In other words this coefficient shows how
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well the chosen exogenous factors explain the variations on the endogenous variable. The higher the coefficient, the better the model fit. However, it is worth to remember that too high coefficient is more often the result of biases (violations of the regression assumptions) in the model. At the same time, too low coefficient will tell that the chosen explanatory factors are insufficient to explain the alterations in the dependent variable and the additional predictors are needed.(Minitab, 2011)
R2 adj. (adjusted R squared)
In the multiple regression analysis R2adj. is a goodness-of-feet measure that is similar to the simple R2 but it allows for the other variables to be entered into the model, which therefore lessens the degrees of freedom. R2 adj. increases only if the new potential predictor would improve the model, meaning that the present model is incomplete. (Minitab, 2011)
F-test
The F-test is the other goodness-of-feet test that identifies whether the whole model works. F-test is significance and therefore statistical applicability of the model is checked by looking at the p value as in the case with the t-statistic. (Minitab, 2011)
3.4.5 Descriptive statistics
Pie and bar charts were the main ways of displaying the empirical data. Moreover, in addition to regression analysis, descriptive statistics was employed while describing the basic features of the data in the research and to provide summary of the sample demographics and measures. (Ghauri & Grønhaug, 2010, pp. 154-156)
3.5
Methodological Issues
There were several methodological problems that occurred during the research. Different factors might have affected/influenced the results:
•
Literature review and, therefore, applied theories: it is possible that with the different theoretical background and additional or other literature sources the research and drawn conclusions could be vary. Authors tried to search for the most relevant; reliable and up-todate publications and documents within the scope of the research while doing literature review. To achieve that research parameters as well as 'key words' for informational retrieval have been identified and implemented.
•
Survey: if, for example, the survey questions were constructed differently or changed in general, collected data could have been different and obtained results might have been different. However, the authors attempted to construct the research in such a way, so that to receive the most precise and only possible information, and avoid biases. It was done by closely relating and basing survey development on the created theoretical framework. Moreover, the survey was pre-tested on a small group of authors' friends in order to make
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sure that language is simple, respectful and clear; correct terminology is used and overall survey presentation is attractive. Furthermore, such factors as respondents' random or possible wrong answers have been taken into account. To attempt to eliminate this kind of biases authors collected more survey that have required, 397 fully complete questionnaires instead of 384 have been gathered.
•
The sample itself could be criticized since respondents have been not chosen randomly. Even though, authors attempted to collect various sample by spreading the survey in three Swedish cities - Västerås, Märsta and Stockholm. Moreover, Stockholm is a capital of Sweden and holds one of only four country casinos, therefore it was assumed that people who are visiting the casino are most likely not only Stockholm residents, but also came to gamble and participate in the Poker Tournaments from different parts of the country.
•
Statistical problems, such as connected with regression analysis. Authors made sure to verify the assumptions of the regression analysis as well as to check various models in order to find the best fit of data and variables. Moreover, none of the other statistical techniques for data analysis besides descriptive statistics and regression analysis have been implemented since those were considered to be enough in order to answer the research question.
3.6
Validity and Reliability
The design quality of each research could be reviewed and criticized since it is supposed to represent a logical set of statements and arguments. Several criteria of the research merit attention while creating the conceptual framework, gathering and analyzing the empirical data. (Ghauri & Grønhaug, 2010, p. 79; Fisher, 2007, pp. 290-294) The information provided in the research should be meaningful, which is a focus of validity. Concepts and theories employed in particular research represent research material; moreover, conclusions and interpretations of the results were drawn carefully and logically from the research empirical data together with corresponding theories and models. Appropriate research technique such as survey with representative for the overall population sample was employed, so that readers and authors were sure that results and conclusions reliably and fairly represent subject being explored. (Fisher, 2007, pp. 294-295) In order to improve measurements in the research and examine potential relationships between variables (hours spent playing poker online; emotional motivation; material motivation; accessibility and atmosphere) authors pursued the following steps suggested by Ghauri & Grønhaug, (2010, pp. 8485). First in introduction, the problem that there exists a research gap in the female motivation to gamble online, in particular play online poker, has been explained and stated. From the problem, the research question has been developed. It was decided to investigate the problem by means of quantitative research, specifically by developing hypotheses and testing them with data collected
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from the survey with help of regression analysis and descriptive statistics. Four constructs/factors have been defined and survey has been designed to be closely connected with those constructs. Therefore, authors were sure that they have collected just needed information strongly related to the field of the interest. There are three types of validity: construct, internal and external and certain tactics to improve them. For current research, since it employs questionnaire as a research technique, the construct or measurement validity is of great importance. It deals with the constructs and focuses on issue whether those constructs in fact measure what they are said to measure. In other words, researchers have to be sure that they measure the right thing. Current study aims to measure four main constructs (factors) - emotional motivation, material motivation, accessibility and atmosphere. In order to make sure that those factors are measured correctly and accurately, authors asked external public to asses if those constructs correspond to what was intended to be measured. A pre-test of the survey have been done on five volunteer respondents and slight changes in the survey have been made to improve construct validity. (Ghauri& Grønhaug, 2010, pp. 81-82; Fisher, 2007, p. 295) Internal validity faces the concern about the existence of the casual relationships between various variables. To be able to confirm a casual relationship between four factors (constructs) and the dependant variable (hours spend playing poker), authors made sure to check assumptions of the simple and multiple regressions (see Appendix D) and, what is more important, proved the statistical significance of the overall model (p-values are less than 0.05). The statistical significance and applicability of all tested models means that there is an explanatory power and a good fit among variables. (Ghauri& Grønhaug, 2010, p. 83) External validity deals with generalization of the findings. The sample size for the survey (397 respondents) is representative for population within chosen, limited geographical area (Sweden). Moreover, simple probability sampling procedures have been applied. (Ghauri& Grønhaug, 2010, p. 84; Fisher, 2007, pp. 297-298) The main idea of reliability is to minimize the errors and biases and provide the stability of measures in the research. Any other researcher should be able to get the same results if he/she followed the same method and if he/she applied the same procedures as original authors. To make that possible, authors of the study documented the steps that they followed during the research process. The research protocol was not created, but authors were clear on all the stages of the research process, which were presented in the foregoing parts. (Ghauri& Grønhaug, 2010, p. 79)
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4. EMPIRICAL DATA
Chapter four represents the empirical data collected from the survey with 397 respondents. Data is presented by means of pie and bar charts and was grouped first according to the motivation factors - emotional, atmosphere, accessibility and material and the rest of the questions were presented separately.
4.1
Emotional Motivation
Figure 8 reveals results for the emotional motives of women playing online poker. Questions 2, 3 and 10 which were the likert-scales aimed to measure intrinsic motivation behind the reason why respondents play online poker for money:
• • •
Question 2 - Because it allows me to enjoy myself enormously. Question 3 - Because it is exciting to play for money. Question 10 - Because when I play I feel thrill and adrenaline.
Emotional Motivation
70 126137 Question 2 4 18 42 Corresponds exactly(7) 60 134 9 Question 3 3 19 42 64 Question 10 4 0 16 44 13 135 134 Corresponds a lot(6) Corresponds a lot(5) Corresponds moderately(4) Corresponds a little(3) Corresponds a little(2) Does not correspond at all(1) 50 100 150
Number Of Respondents
Figure 8: Emotional Motivation
Majority of respondents (approximately 130 people for each question and category) for all three questions indicated that such emotions as 'excitement', 'enjoyment' and 'thrill and adrenaline' correspond a lot (5,6) to why do they play online poker. 'Corresponds exactly' (7) was the third popular answer among respondents for all three likert-scales - 70, 60, 64 women consequently. 'Corresponds moderately' (4) was the next accepted category - around 40 people for each question
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chose (4). 'Corresponds a little' got the least answers among 397 respondents - around 20 women ticked (3) and 4 respondents - (2). 'Does not correspond at all' (1) was not chosen by any respondents.
4.2
Atmosphere
Figure 9 shows respondents' opinion towards atmosphere being reason for women to play poker online. Questions 4, 7 and 13 which were also likert-scales aimed to measure intrinsic motivation behind respondents playing online poker for money:
• • •
Question 4 - Because the atmosphere of the game is relaxed. Question 7 - Because I don't want to reveal my identity (like in table poker). Question 13 - Because I feel more self-confident in the familiar surrounding.
Atmosphere
16 Question 4 5 17 Question 7 5 18 Question 13 3 0 20 34 40 60 434 8 55 69 107 1 11 80 100 120 Number Of Respondents 140 31 74 677 7 67 127 Corresponds exactly(7) Corresponds a lot(6) 108 109 Corresponds a lot(5) Corresponds moderately(4) Corresponds a little(3) Corresponds a little(2) Does not correspond at all(1)
Figure 9: Atmosphere
'Corresponds moderately' (4) was the most chosen answer for how atmosphere influences respondents to play online poker for money for all three questions (127, 109, 111 respondents). 'Correspond a lot' (5, 6) was the second popular category, while 'Corresponds a little' (2.3) the third: Question 4 received 77 (5)th ; 74 (6)th; 67 (3)th and 31 (2) th; Question 7 received 108 (5)th ; 67 (6)th; 48 (3)th and 43 (2) th ; Question 13 received 107 (5)th ; 55 (6)th; 69 (3)th and 34 (2) th. The two extreme categories 'Corresponds exactly' (7) and 'Does not correspond at all' (1) got the least of respondents answers - 16, 17, 18 and 5, 5, 3 consequently.
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4.3
Accessibility
Respondents' answers on how accessibility influences them to play online poker are revealed in Figure 10. Likert-scales 5, 9 and 11 which were designed to measure extrinsic motivation behind respondents playing online poker for money:
• • •
Question 5 - Because I can play at any place with Internet access. Question 9 - Because I can play at any time I want. Question 11 - Because it is convenient to play
Accessibility
40 Question 5 0 Question 9 0 Question 11 2 0 16 20 40 19 35 47 17 44 44 53 93 90 101 Corresponds exactly(7) 89 89 Corresponds a lot(6) 112 Corresponds a lot(5) Corresponds moderately(4) 95 1 01 0 7 1 60 80 100 120 Corresponds a little(3) Corresponds a little(2) Does not correspond at all(1)
Number Of Respondents
Figure 10: Accessibility
'Corresponds a lot' (5) was the most preferred category - 101, 112, 107 respondents. At the same time 'Corresponds a lot' (6) with 'Corresponds moderately' (4) and 'Corresponds exactly' (7) with 'Corresponds a little' (3) had nearly the same amount of answers: for the first pair the average amount for all three questions was 95, while for the second approximately 40. 'Does not correspond at all' (1) category was chosen only by 2 respondents for question 11.
4.4
Material Motivation
Answers about how material motivation corresponds to why women pay online poker are displayed in Figure 11 Likert-scales 6, 8 and 12 which were designed to measure extrinsic motivation behind respondents playing online poker for money:
•
Question 6 - Because it allows me to make money quickly and easily.
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• •
Question 8 - Because it allows me to make a lot of money. Question 12 - Because I feel a need of more money.
Material Motivation
15 Question 6 23 19 Question 8 28 10 Question 12 27 0 20 40 67 1 7 57 64 60 80 100 120 101 Corresponds a little(2) Does not correspond at all(1) 61 61 48 53 73 70 102 Corresponds exactly(7) Corresponds a lot(6) 77 74 90 Corresponds a lot(5) Corresponds moderately(4) Corresponds a little(3)
Number Of Respondents
Figure 11: Material Motivation
'Corresponds moderately' (4) received majority of the answers for all three likert-scales (102, 90, 101 respondents). 'Corresponds a lot' (5) was the second most chosen with 73, 77 and 71 respondents. "Corresponds a little' (3) was the third popular answer for questions 6 -70 respondents and question 8 74 respondents, while for question 12 'Corresponds a lot' (6) was third with 67 respondents and "Corresponds a little' (3) had 64 women. Corresponds a lot' (6) was chosen by 53 women for question 6 and by 48 for question 8. 'Corresponds a little' (2) received 61 answers for question 6 and question 8 and 57 fro question 12. 'Does not correspond at all' (1) was on the last but one choice with 23, 27 and 27 respondents and on 'Corresponds exactly' (7) had 15, 19 and 10 answers.
4.5
Hours Spend Playing Online Poker
Question 14 had an open-answer nature where respondents were asked to estimate how many hours per month do they play online poker. The spread of answers was between 2 and 150 hours. The most popular written amounts of numbers included 5 hours - 40 respondents; 10 hours - 39 respondents; 15 hours - 52 respondents; 20 hours - 43 respondents and 30 hours - 32 respondents. 23 women said that they play online poker for about 25 hours per month; 21 women - 35 hours per month; 45 and 50 hours have been written down by 25 and 22 respondents respectively; 14 women spend 40 hours in front of the computer playing poker and 13 respondents - 60 hours. The rest of the hours
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categories include less than 10 respondents per each, e. g. 3 hours - 8 respondents; 90 hours - 5 respondents, etc. Figure 12 shows all the respondents answers.
Hours Playing Online Poker
60 52 50 40 Number of Respondents 30 20 10 1 0 2 3 4 5 6 7 8 9 1 1 0 1 2 1 3 1 5 1 6 1 7 2 8 2 0 3 5 3 0 3 4 3 5 4 7 4 0 5 5 5 0 6 5 6 0 6 5 7 8 7 0 8 5 8 0 9 5 9 0 10 5 12 0 13 0 15 0 0 Number of Hours (per month) Figure 12: Hours Spend Playing Poker 8 1 1 6 11 11 211 2 2 40 43 39 32 23 21 25 22 14 5 13 7 1 8 242 43111 5
4.6
Occupation
Question 14 was aimed to measure the occupation of the respondents. 139 (35%) out of al 397 women were a full-time employees, while 132 (33%) were students. 81(21%) people were working part-time and the minority - 45 (11%) of respondents were staying at home.
Occupation
45 11%
132 33 %
139 35%
Full-time employee Half-time employee Student Staying at home
81 21% Figure 13: Occupation
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4.7
Educational Level
Figure 14 shows results of Question 17 which measured the education level of respondents. In total 4 women chose two of answers categories 'none of the above' and 'high-school diploma' -3 of which said that they had only a high-school diploma and 1 ticked none of the provided above answers. 264 (67%) out of 397 women had completed university education and 129 (32%) were in the process of achieving one.
1 0 %
3 1 %
Education Level
High-school diploma 129 32 % 264 67 % University degree/diploma In process of achieving University degree None of the above
Figure 14: Educational Level
4.8
Relationship Status and Children
Figures 15 display the relationship status and presence of children among 397 female respondents. Majority of respondents were single - 275(69%) and without children - 324 (59%). 122(31%) women were either married or cohabiting and 163 (41%) had children.
Relationship Status
122 31 % Single Married/Cohabiting 275 69 %
Children
163 41 % Yes No
234 59 %
Figure 15: Relationship Status and Children
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4.9
Age
Figure 16 below presents the age of the respondents that have filled in the survey. The age categories are presented on the vertical axis and vary between 19 and 63 years old. Number of respondents in each age category is shown on the vertical axis.
Age
63 years old 57 years old 51 years old 45 years old 44 years old 42 years old 41 years old 40 years old 39 years old 38 years old 37 years old 35 years old 34 years old 33 years old 32 years old 31 years old 30 years old 29 years old 27 years old 26 years old 25 years old 24 years old 22 years old 21 years old 19 years old
1 4 2 23 19 8 12 6 13 39 15 36 28 25 16 17 34 17 21 8 16 14 13 7 3 0 5 10 15 20 25 30 35 40 45
Number of Respondents
Figure 16: Age
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5. ANALYSIS
The fifth chapter is the analysis of empirical data with the use of presented theoretical framework
5.1
Demographic characteristics
The research has been carried out among 397 respondents. All respondents were women who play online poker for money. Due to the fact that service - poker game was offered to the customers by means of Internet, it became more standardized for most of the users. Since Swedish gamblers also have an opportunity to play on other international web-sites, the motivations and characteristics of the potential profitable customer segment among Swedish women are of the interest not only for the Swedish monopoly provider- Svenska Spel but also for the international providers. (Barnes et al., 2007; Donthu & Garcia, 1999). Survey revealed the general bases/segments of the women engaged into the research. From the beginning it was assumed to conduct the study of female players in Sweden, therefore geographic segment was women who play online poker in Sweden. Pie charts and histograms presented as empirical data show the certain demographic characteristics that illustrate the average female online poker player in Sweden. The importance of understanding not only traditional customers, but also the general demographic characteristics of those who are involved into online activities have been noted by Kau et al (2003). Knowing better target customers' personal characteristics is a root to predict and assess the possible motivations and overall behavior. According to the received answers from the 397 Swedish women playing poker online, the mode of the hours spent as the proxy of the propensity to be involved into the game during the period of one month was 15 (n = 52) hours. The other popular answers were 20 (n = 43), 5 (n = 40), 10 (n = 39), and 30 (n = 32). Consequently the average amount of hours out of all responses was estimated to be 30.3. That is nearly 1 hour per day or 7 hours per week indicating the daily/frequent involvement into the game. Age as the bases for demographic segmentation disclosed that the majority of women who play online poker were above 30 years old (30, 35, 38 years old), where the age spread was between 19 and 63 years old. This finding is comparable with the previous findings in various geographic markets where the age of the potential female online poker players was estimated to be in a rank of 32-50 years old (Davis & Avery, 2004; LaPlante et al. 2009; Wood & Griffiths, 2008) Second demographic variable that has been investigated was occupation. Main fraction of respondents (56%) was employed either part- or full- time, where 33% have been studying and 11% staying at home. This numbers indicate that women that play poker online in Sweden mainly belong to the highly active and engaged segment such as work or studying. The similar level of occupation
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was found by Davis & Avery (2004) and Corney & Davis (2010) in their investigations of the US and UK markets respectively, where the majority of female respondents stated being professionals, clerical staff or managers. When it comes to the educational level, it was previously found that the major fraction of the online poker players, both men and women, have higher education or are in the process of achieving one (college, bachelor or master degree) stressing the importance of the higher level of intelligence required for the games of skills (Davis & Avery, 2004; Griffiths et al. 2010). In terms of educational segments, the dominating majority (67%) were women who have already completed university/college degree, while 32% were currently in the process of achieving high education. Swedish poker gamblers were mostly high-educated women. Relationship status and presence of children has been analyzed in tandem as the proxy of occupation with family activities and the role of family as a whole. In Sweden the main female group was found to be single predominantly (69% single/living alone vs. 31% married/co-habiting) and without children. Though the difference between those with children and without was not significantly large, i.e. 18%. These findings are in variance with the previous findings of Corney & Davis (2010) and Davis & Avery (2004), where the majority of women involved into the online gambling activities of all kinds are either married or cohabiting. Now, after the hypothetical target segment was figured out by means of demographic characteristics investigation (i.e. woman aged 30-40, single, predominately without children, either working or studying and spending around 30.3 hours per month on online poker for money) it is time for revealing the most important aspect for marketers- behavior, i.e. motivations to play poker online (Montgomery, 2008).
5.2
The Model
Both types of regressions, multiple and single (separately with each predictor variable) were conducted in attempt to find the better fit of the data. The analysis revealed that all four investigated explanatory variables, i.e. emotional context, accessibility, atmosphere and monetary motives, do play a significant role in forming the online poker playing women's behavior and therefore must be entered into one multiple model. The correlation coefficient R2 was found to be more than twice higher in case of the multiple regression model. (see Table 1) In addition, the R2 adj. coefficient was found to be smaller but nearly the same as the simple R2 coefficient. This supported the statistical significance and applicability of the model, suggesting that there is a good fit between variables. The other goodness-of-fit test, F- test, also indicated the significance of the model and the overall fit with the probability value p equal to zero, which consequently rejected the H0 of the absence of the significant relations of the dependent and the predictor factors.
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Nevertheless, it was also obvious that though the multiple model provides more precise estimates and data fit it still misses to explain nearly 40% of propensity of women to play poker online which can be explained by the restricted choice of explanatory variables to test the hypotheses due to theoretical gap in the field of investigation and various types of motivations among Swedish women.
Time = - 67,5 + 7,44 Emotions + 2,74 Atmosphere + 3,64 Access + 7,06 Money T-statistics F-test em 128,48* Time vs Emotions Time vs Atmosphere Time vs Access Time vs Money 7,66* At m 3,30* acc 4,06* mon 13,26* R2 and/ R2 adj. (%) 56,7/ 56,3 ? coefficient em At m acc mon
7,44 2,74 3,64 7,06
157,51* 12,55*
-
-
-
28,5/28,3
12,7
-
-
-
113,28* 149,63* 143,24*
-
10,64* -
12,23* -
11,97*
22,3/22,1 27,5/27,3 26,6/26,4
-
8,82 -
9,86 -
8,19
(**) [*] the significance at the (5%) [1%] level
Table 1: Summary Table of Regression Analysis (own)
5.3
The Hypotheses Testing
As it was discussed in the theoretical background the consumers' (in this paper consumers are Swedish women playing online poker) behavior is driven by two broad groups of motivations, extrinsic and intrinsic. Digging deeper into the online poker world and the motivations that drive people to gamble online, it was found that theory suggests four main motives to play online poker that could be applicable explanations why Swedish women play online poker. According to the previous studies, women tend to be more driven by their emotions when making the decision to gamble online. Davis & Corney (2010) stressed out the importance of the emotional relief seeking among women when they decided to gamble online. Lee et al. (2007) found out that excitement seeking as the emotional driver was predominant among gambling women. Relying on those researches and findings the two hypotheses concerning emotional motivations to play online poker among Swedish people were formed and tested. First hypothesis stated the positive relationship between propensity to play online poker and the emotional motivation. The last, fifth
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hypothesis, emphasized the role of emotions as the dominant trigger to play poker online among Swedish women. H1: According the regression analysis output there was a positive statistically significant relationship between emotional motives and the level of involvement into the online poker games. The t-statistic (7,66) was significantly positively related with the p value equal to zero and?coefficient with the plus sign. H5: The fifth hypothesis was also accepted. With the largest? coefficient, 7.44, the emotional motivation was proved to be the most important trigger among Swedish people to play online poker. Moreover, according to the answers presented by choice of likert-scale numbers, statements aimed to discover the emotional motivation received the largest amount of the strongest agreements, i.e. '7' in the scale of "corresponds a lot". The second hypothesis tested in this study stressed out the role of material motivation to play online poker among Swedish women. Nearly every scientific research of the gambling/online gambling propensity stressed out the role of material motivation. (Drozd, 2010, Mowen et. Al, 2009, Hong & Jung, 2004) The only studies that investigated the women's propensity to gamble or play poker online minimized the role of money when making the decision to gamble. (Lee et al. 2007, Corney&Davis, 2010) H2: According to the findings in this precise analysis, the material motivation does positively correlates to the propensity to play online poker among Swedish women with the ? coefficient second large, 7,06 and the t-statistic (13,26) with the zero probability that this predictor might be insignificant. The next hypothesis tested the positive relationship between the accessibility and the propensity to play online poker. Layton & Worthington stressed the importance of the convenience and accessibility when it comes to the gambling already in 1999 (Layton& Worthinngton, 1999) Further, Corney & Davis (2010) and Wood et al. (2007) found that accessibility factor was mentioned as the dominant motive to gamble online by nearly every questioned woman. The convenience brought by the internet for the gamblers was also discussed by Wood &Griffiths (2008). H3: Thus the hypothesis of the positive impact of the easy and convenient online poker access was tested in this research. The results approved the theoretical background: the accessibility of the online poker was found to be in a positive relationship with the level of involvement into the game among Swedish women with the? coefficient equal to 3,64 and the p value of the t-statistic (4,06) equal to zero.
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The last major motivation suggested by the previous research was found to be the atmosphere. The sense of privacy and self-confidence in the familiar surroundings were proposed to trigger internally people's propensity to gamble and therefore have the positive relationship. (Corney & Davis, 2010; Wood & Griffiths, 2008; Wood et al., 2007) H4: As in all the previous hypothesis testing cases, the acceptance of the hypothesis was approved by this analysis. The atmosphere motivator was found the be statistically significant and positively related to the dependent variable with the? coefficient equal to 2,74 and t-statistic (3,30) with the p value of 0,001. After all, the t-statistics were found to be significant at 1% level stressing the importance of all the four motivational aggregates in the model. The analysis also indicated the set of outliers, i.e. the unusual observation that are supposed to influence the statistical significance of the results. But, as it was discussed, the statistical significance of the whole model as well as each coefficient separately was proved and therefore those outliers were not supposed to significantly affect the model, which once again approved the positive results of this analysis. The complete hypothesized model is summarized and presented in the figure 17 below, it shows the relationship between variables used in constructing hypotheses.
Figure 17: The Hypothesized Model (own)
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6. CONCLUSION AND DISSCUSSION
Last chapter summarizes the research results. In addition it presents the discussion of those results from different perspectives and aspects Current research was focused on Swedish market that is characterized by strict monopoly on landbased and online gambling as well as relatively recent introduction of the online poker activity (Svenska Spel, 2011; Young & Todd, 2008; Jonsson & Rönnberg, 2009, p.300). Traditionally women's role in online gambling and precisely online poker have been underestimated and uninvestigated (Manzin & Biloslavo, 2008; LaBrie et al., 2007; Mowen et al., 2009; Griffiths &Barnes, 2008; Lee et al., 2007; Corney & Davis, 2010). In Sweden women account for the significant fraction of the overall eligible (18+) for gambling population, who also participate in online poker (SCB, 2010). Therefore, it was of a vast interest to understand what drives those women to get involved into online poker world and bet their money. The research attempted to understand Swedish women's motivation to play online poker with the help of existing theoretical models and previous studies by means of hypotheses testing through multiple and simple regression analyses. The results showed that emotional and material motivations as well as accessibility and atmosphere factors do have the negligible direct impact on the Swedish women's level of involvement into the online poker for real money. The deep investigation of the existing studies (gambling, online gambling, online poker and women in the gambling world) and theoretical models (extrinsic/extrinsic motivations, 3M model, 5-factor model) was conducted as the inspirational base for testing hypotheses on the Swedish females' sample (Ryan & Derci, 2000; Mowen et al., 2009; Lee et al., 2007). The study attempted to find out whether the chosen motivation that have been previously investigated and theoretically suggested are applicable in case of women in Sweden who play poker online for money. According to previous studies and findings, the most popular motivations to gamble online or play poker by means of internet among both men and women were: - Emotional motivation (i.e. excitement, enjoyment, thrill and adrenaline seeking) - Material motivation (i.e. to win money) - Accessibility (i.e. ease and comfort of access by means of internet) - Atmosphere (i.e. familiar surrounding and privacy while gambling/playing poker with own PC) If considering the above triggers to gamble from the theoretical and psychological perspectives, then those can be divided into two groups - extrinsic and intrinsic motivations. Where emotional motives and atmosphere are the internal/intrinsic factors, while money seeking and accessibilityexternal/extrinsic ones (Ryan & Derci, 200).
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The analysis revealed that reality within the Swedish market and female segment is comparable to what was found previously by various authors within different geographic and demographic markets. Given, the previous findings and results achieved in this concrete research, one can state that intrinsic, i.e. emotional, motivations are fundamental factors that form Swedish women's behavior when it comes to the decision to play poker online. This probably comes from the psychological distinguishing characteristics of women, where women tend to be more often driven by their emotional state when making decisions. The second in line was material motivation such as making money easily and quickly or general need of money. The third factor was accessibility of the game, meaning that Swedish respondents appreciated that it is convenient to play online and moreover they can gamble at any time at any place. And the last one was atmosphere of the game and its surroundings. Even though according to the results it was not the most important reason to play poker online, feeling of the self-confidence in the familiar surrounding, relaxed atmosphere and no need to reveal the true identity are still considered to be significant motives for Swedish women propensity to play the game. As stated above the material motivation was on the second place, which also stresses the significance of this factor when making the decision to dedicate time on the online poker among Swedish women. Obviously, when playing for money, material factor can't be neglected, otherwise why even to choose this type of game. The main aspect here is placement of the priorities on both factors, emotional and material, which comes from the gender differences and demographic characteristics. The first issue (i.e. gender differences) was previously investigated and it was found that when it comes to male samples, the weights on the emotional and material motivations to gamble/play poker online were placed vice versa (i.e. first place - material trigger, second - the emotional motivations). The other demographic characteristics such as age, occupation, education and family status do also have the impact on the motives to play poker online. (Lee et al., 2007; Lloyd et al., 2010; Wood & Griffiths, 2008) This study did not attempt to investigate cross-correlations of the demographic variables and various motives as it would have lead to several conclusions, additional use of theory and go beyond one research question. However, as it was stated at the beginning of this paper, the attempt was to investigate the potential target segment for the online poker providers and mainly see the motivations of the particular sample. For the marketing and costs reducing purposes all the information is essential in order to make the efficient campaign and attract as much customers as possible. The quantitative researches are aimed to receive vast amount of responses in order to make the aggregation after all (Ghauri & Grønhaug, 2010, p. 138). The same intention was in this particular research - to understand the motivations that drive this aggregated potential customer base (consisting of Swedish women) to play online poker for money. As it turned out, the collective image of the Swedish woman who is prone to play poker online is- woman who is around 35, with
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high education and professionally occupied, without serious relationships and mainly without children and she is more driven by emotional motivations when deciding to play poker online for money. Given the results of the Swedish females investigation in this study paper and the previous findings about online gambling overall, one can indicate that those go in line and very much comparable among all the gambling services all over the world. This indicates that one can generalize all the online gambling activities when considering the motivations that make females to gamble in every part of the world where this activity is legalized. However, from the statistical perspective, the tested model, that incorporated the four motivational factors, was found to be incomplete, meaning that there probably are some other important factors that make Swedish women to play poker online but were not taken into consideration in this particular research. The other explanation might be the aggregation of the likert-scale answers that represent one motivational group. As each group consisted of three statements, probably this limited the spread of choices and consequently influenced the whole model. Moreover, it is accepted that there might be some portion of bias in the results due to the nature of dependent variable - amount of hours dedicated to the game. It is hardly possible to give the exact number of hours per month. So, the predicted factor is only nearly correct from the statistical perspective, though precise enough for this research's purpose. As it was already mentioned before, this study paper looks at the online poker and the whole gambling as at the huge business where providers should attract, acquire and retain as many customers as possible in order to generate profits (Baines et al., 2008, pp. 246-251; Barnes et al., 2007; Kau et al., 2003). Therefore, the findings in this paper can be applicable for the online poker providers both within and outside Sweden as Swedish people are actively using the international websites due to strict monopolistic regulations in the country. As, nowadays online poker is becoming more and more popular among women segment whole over the world and Sweden is not an exception, it is necessary for providers to distinguish the main motivations among various demographic groups. From the psychological point of view, the results of this paper can be useful for the medical institutions that fight against such issues as problem- and pathological gambling. Knowing the potential player among women can contribute to the existing investigations of the roots of the addictive behavior. This knowledge is essential when attempting to come up with the means to prevent or cure the addiction. For further researches Continuing with the problem-gambling, the further research of the Swedish female poker players can be concentrated around the pathological behavior, i.e. addiction that makes people lose all their
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money and estate being unable to stop without the outside help. Probably in this research there was a portion of problem-gamblers who answered the survey. However, as that was not of the interest and purpose to investigate the problem-gambling patterns, this study neglected this fact as it was out of the scope of the particular research. Moreover, the further studies can evaluate each motivation separately and show cross-correlations with the demographic factors which will lead to several additional conclusions in this particular field of study. Additionally, other researchers could investigate other gambling activities, besides online poker as well as try to identify other motivations and variables that influence gambling behavior and motivate people to gamble, since model in current research resulted to be incomplete.
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REFERENCES
Baines, P., Fill, C., Page, K. (2008) Marketing, Oxford University Press Barnes, S. T., Bauer, H. H., Neumann, M. M., Huber, F. (2007) "Segmenting cyberspace: a customer typology for the internet", European Journal of Marketing, 41(1/2), pp.71 - 93 Barrow, M. (1996) Statistics for Economics, Accounting and Business Studies (2d ed) LONGMAN: London and New-York Bayton J.A., (1958) Motivation, cognition, learning - basic factors in consumer behavior. Journal of Marketing 22(3) Carey A.E., Carey K.R. (1984) Gambling. Reference Services Review, pp.49-61 Corney R., Davis J. (2010) The attractions and risks of internet gambling for women: A qualitative study. Journal of Gambling Issues 24, pp. 121-139 Cottrell, A. (2003) Regression Analysis: Basic concepts Davis, D. R. & Avery, L. (2004) Women Who Have Taken Their Lives Back From Compulsive Gambling: Results from an online survey. Journal of Social Work Practice in the Addictions 4(1), pp. 61-80 Davis, D. R., Avery, L.(2004) Women who have taken their lives back from compulsive gambling: results from an online survey. Journal of Social Work Practice in the Addictions, 4(1), pp.61-79 Dewar L. (2001) Regulating Internet gambling: the net tightens on online casinos and bookmakers. Asib Proceedings, 53(9), pp. 353-367 Donthu, N., Garcia, A. (1999) The internet shopper. Journal of Advertising Research, 39(3), pp. 5258. Drozd A. (2010) The future of digital gambling. Business insights Fisher, C. (2007) Researching and Writing a Dissertation for Business Students. (2th ed) Pearson Education Limited Ghauri, P., Gronhaug, K. (2010) Research Methods in Business Studies (4th Edition) Pearson Education Limited Griffiths, M. D. (2003). Internet gambling: CyberPsychology & Behavior, 6, pp. 557-568. Griffiths, M. D., Barnes, A. (2008). Internet gambling: An online empirical study among student gamblers. International Journal of Mental Health and Addiction, 6, pp. 194-204. Issues, concerns, and recommendations.
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Griffiths, M. D., Parke, A., Wood, R. T. A., & Parke, J. (2006). Internet gambling: An overview of psychosocial impacts. Gaming Research and Review Journal, 27(1), pp. 27-39. Griffiths, M. D., Parke, A., Wood, R. T. A., & Parke, J. (2010). Online Poker Gambling in University Students: Further Findings from an Online Survey. International Journal of Mental Health and Addiction , 8, pp. 82-89 Griffiths, M. D., Wardle, J., Orford J., Sproston, K., & Erens, B. (2009). Socio-demographic correlates of internet gambling: findings from the 2007 British Gambling Prevalence Survey. CyberPsychology and Behavior. Griffiths, M. et al (2010) Online Poker Gambling in University students: Further Findings from an Online Survey. Int J Health Addiction 8, pp. 82-89 Hong S.-K., Jang H. (2004) Segmentation of early casino markets: an exploratory study. Tourism Management 25, pp. 801-805 Jonsson, J., Rönnberg, S. (2009). Gambling in Sweden. In G. Meyer, T. Hayer & M.D. Griffiths (Eds.), Problem Gaming in Europe: Challenges, Prevention, and Interventions. New York: Springer. Kau, A.K., Tang, Y.E., Ghose, S. (2003) Typology of online shoppers. Journal of consumer Marketing, Vol. 20 No. 2, pp. 139-56. King, D., Delfabbro, P., Griffiths, M. (2010) The Convergence of Gambling and Digital Media: Implications for Gambling in Young People. Journal of Gambling Studies, 26/2, pp. 175-187 Kurtz, D. L., MacKenzie, H. F., Kim Snow, K. (2009) Contemporary Marketing, Cengage Learning LaPlante, D.A. , Kleschinskyb, J. H., LaBriea, R. A., Nelsona, S. E., Shaffera, H. J. (2009) Sitting at the virtual poker table: A prospective epidemiological study of actual Internet poker gambling behavior. Computers in Human Behavior Layton, A. & Worthington, A. (1999) The impact of socio-economic factors on gambling expenditure. International Journal of Social Economics 26 (1/2/3), pp. 430-440 Lee H.P., Chae P.K., Lee H.S., Kim Y.K. (2007) The five- factor gambling motivation model. Psychiatry Research 150(1), pp. 21-32 Lloyd, J., Doll, H., Hawton, K., Dutton, W.H., Geddes, J. R. Goodwin, G.M., Rogers, R.D. (2010) Internet Gamblers: A Latent Class Analysis of Their Behaviours and Health Experiences. Journal Of Gambling Studies, 26(3), pp. 387-39 Manzin, M., Biloslavo, R. (2008) Online Gambling: Today's Possibilities and Tomorrow's Opportunities. Managing Global Transitions 6 (1), pp. 95-110
45 | P a g e
Meyer, G., Hayer, T., & Griffiths, M. D. (2009). Problem gaming in Europe: Challenges, prevention, and interventions. New York: Springer. Miller, T.E. (1996), "Segmenting the internet", American Demographics, 18(7), pp. 48-52. Monaghan, S. MacCallum, B. (2006) Internet and Wireless Gambling - A Current Profile . Australasian Gaming Council Montgomery, J. (2008) The role that personality and motivation play in consumer behavior: a case study on HSBC. Business intelligence Journal. Case study 3 Mowen J.C., Fang, X., Scott, K. (2009) A hierarchical model approach for identifying the trait antecedents of general gambling propensity and of four gambling-related genres. Journal of Business Research, 62, pp. 1262-1268 Perse, L. Bellringer, M., Abbott, M. (2005) Literature review to inform social marketing objectives and approaches, and behavior change indicators, to prevent and minimize gambling harm. Gambling research center Romild U. (2009) SWELOGS- a longitudinal study on Gambling and Health. Swedish National Institute of Public Health Ryan R.M., Deci E.L. (2000) Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemporary Educational Psychology 25, pp.54-67 Saunders, M. N. K., Thornhill, A., Lewis, P. (2009) Research Methods for Business Students (5th Edition) Pearson Education Limited Wiebe J. (2008) Internet Gambling: Strategies to Recruit and Retain Gamblers. Ontario Problem Gambling Research Centre Winship C., Mare R.D (1984) Regression models with ordinal variables. American Sociological Review 49, pp. 512-525 Wood, R. T. A., Griffiths, M. D., & Parke, J. (2007). The acquisition, development, and maintenance of online poker playing in a student sample. Cyberpsychology and Behavior, 10, pp. 354361. Wood, R.T, Williams R.J. (2009) Internet gambling: Prevalence, Patterns, Problems, And Policy Options. Ontario Problem Gambling Research Centre Wood, R.T. et al. (2007) Why do Internet gamblers prefer online versus land-based venues? Some preliminary findings and implications. Journal of Gambling, 20, pp. 235-252
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Wood, R.T.A., Griffiths M. D (2008) Why Swedish people play online poker and factors that can increase or decrease trust in Web sites: A qualitative investigation. Journal of Gambling Issues 21, pp. 80-97 Young, R., Todd, J. (2008) ONLINE GAMBLING: focusing on integrity and a code of conduct for gambling. Policy Department Economic and Scientific Policy. European Parliament's committee on Internal Market and Consumer Protection (IMCO)
Internet Sources
ATG the Company (2011) Retrieved on 16th of April, 2011 from thehttp://www02.atg.se/cm/english/aboutatg Christian Capital Advisory Ltd. (2011) Retrieved on 10th of April, 2011 fromhttp://www.ccai.com/primary navigation/online data store/internet_gambling_data.htm G-.Martin K. (2009) Can likert-scale data ever be continuous? Retrieved on the 13th of April, 2011 from:http://www.ideamarketers.com/?Can_Likert_Scale_Data_ever_be_Continuous&articleid=424733 High, R. (n/d) Date coding issues with logistic regression. Retrieved on 13th of April from:http://rfd.uoregon.edu/files/rfd/StatisticalResources/est_logistic.txt Ialomiteanu, A., & Adlaf, E. (2001). Internet gambling among Ontario adults. Electronic Journal of Gambling, 5. Retrieved Aprril 21st, 2011 fromhttp://www.camh.net/egambling/issue5/research/ialomiteanu_adlaf_article.html Minitab. Retrieved 2nd of May, 2011 fromhttp://www.minitab.com/enSE/products/minitab/default.aspx Murray, B (2011) Online Poker Grew 7.1 Percent In 2010. Retrieved April 14th , 2011 fromhttp://www.cardplayer.com/poker-news/10494-online-poker-grew-7-1-percent-in-2010 Online Gambling Sites in Sweden (2011). Retrieved March 26th, 2011 fromhttp://gamingzion.com/sweden SCB (2010) Sweden's Population by sex and age on 31/12/2010. Retrieved 6th April, 2011 fromhttp://www.scb.se/Pages/TableAndChart____264373.aspx Svenska Spel (2011). Retrieved March 28th , 2011 fromhttp://svenskaspel.se/p4.aspx?pageid=527 Zupko A. (2010) Woman populating the online poker world. Retrieved March 31st , 2011 fromhttp://www.womanpokerplayer.com/pokernews/598-women-populating-the-online-pokerworld.html
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APPENDIX Appendix A - Estimating Sample Size
Margin of error Population
50 100 150 20 250 300 400 500 750 1000 2000 5000 10000 100000 1000000 10000000 5% 44 79 108 132 151 168 196 217 254 278 322 357 370 383 384 384 3% 48 91 132 168 203 234 291 340 440 516 696 879 964 1056 1066 1067 2% 49 96 141 185 226 267 343 414 571 706 1091 1622 1936 2345 2395 2400 1% 50 99 148 19 244 291 364 475 696 906 1655 3288 4899 8762 9513 9595
(Fisher, 2007, p. 190; Saunders et al., 2009, p. 219)
I|P age
Appendix B - Survey
"WHY DO YOU PLAY ONLINE POKER FOR MONEY?"
1. Do you play online poker?
? Yes ? No If you answered YES, then for each of the following statements, please circle the number that best represents the extent to which the statement corresponds to the reasons why you play poker online.
Does not correspond at all 1 2 3 Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly
4
5
6
7
For example, if the statement doesn't correspond at all, circle number 1; if it corresponds moderately, circle number 4; if it corresponds exactly, circle number 7. WHY DO YOU PLAY ONLINE POKER FOR MONEY? 2. Because it is exciting to play for money. 3. Because it allows me to enjoy myself enormously. 4. Because the atmosphere of the game is relaxed. 5. Because I can play at any place with Internet access. 6. Because it allows me to make money quickly and easily. 7. Because I don't want to reveal my identity (like in table poker). 8. Because it allows me to make a lot of money. 9. Because I can play at any time I want. 10. Because when I play I feel thrill and adrenaline. 11. Because it is convenient to play . 12. Because I feel a need of more money. 13. Because I feel more self-confident in the familiar surrounding. 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567
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14. How old are you? 15. How many hours per month do you spend playing poker online? Please, provide your own estimation For the following questions, please, choose one of the provided answers. 16. Your occupation is:
? Full-time employee ? Halftime employee ? Student ? Staying at home
17. Your education level is:
? High-school diploma ? University degree/diploma ? In process of achieving University degree ? None of the above
18. What is your relationship status?
? Single ? Married/Co-habiting
19. Do you have children?
? Yes ? No
~ THANK YOU FOR YOUR PARTICIPATION AND HELP ~
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Appendix C - Decode and Measurement for Each Survey Question
Question 1
Decode Yes No Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Aim to Measure
Question 2
Question 3
Question 4
Question 5
Question 6
Question 7
Question 8
Question 9
Question 10
Question 11
1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7
Intrinsic Motivations: Emotional motives
Intrinsic Motivations: Emotional motives
Intrinsic Motivations: Atmosphere
Extrinsic Motivations: Accessibility
Extrinsic Motivations: Material motives
Intrinsic Motivations: Atmosphere
Extrinsic Motivations: Material motives
Extrinsic Motivations: Accessibility
Intrinsic Motivations: Emotional motives
Extrinsic Motivations: Accessibility
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Question 12 Does not correspond at all
Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Respondents were asked to fill in a number themselves
Question 13
1 2,3 4 5,6 7 1 2,3 4 5,6 7
Extrinsic Motivations: Material motives
Intrinsic Motivations: Atmosphere
Question 14
Age of respondents Time spend playing poker online Occupation
Question 15 Respondents were asked to fill in a number themselves Question 16 Full-time employee
Half-time employee Student Staying at home High-school diploma University degree/diploma In process of achieving University degree None of the above Single Married/Co-habiting Yes No
Question 17
Level of Education
Question 18 Question 19
Relationship Status Existence of Children
V|Page
Appendix D - Homoscedasticity Tests and Residuals Analysis
Homoscedasticity Tests:
1. BoxPlot: Time versus Emotions
Boxplot of Time
160 140 120 100 Time 80 60 40 20 0 0 00 3 33 7 66 0 00 3 33 7 66 0 00 3 33 7 66 0 00 3 33 7 66 0 00 3 33 7 0 66 00
2 00 2,33 2,66 3,00 3,33 3,66 4,00 4,33 4,66 5,00 5,33 5,66 6,00 6,33 6,66 7,00 , Emotions
2. BoxPlot: Time versus Atmosphere
Boxplot of Time
160 140 120 100 Time 80 60 40 20 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 1 33 1,66 2,00 2,33 2,66 3,00 3,33 3,66 4,00 4,33 4,66 5,00 5,33 5,66 6,00 6,33 6,66 7,00 , A tmosphere 0
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3. BoxPlot: Time versus Access
Boxplot of Time
160 140 120 100 Time 80 60 40 20 0 67 00 3 3 67 00 3 3 67 00 3 3 67 00 3 3 67 00 3 3 67 00
1, 6 2 66 ,000 ,333 ,666 ,000 ,333 ,666 ,000 ,333 ,666 ,000 ,333 ,666 ,000 ,333 ,666 ,000 2 2 3 3 3 4 4 4 5 A cc e s s 5 5 6 6 6 7
4. BoxPlot: Time versus Money
Boxplot of Time
Time 160 140 120 100 80 60 40 20 0 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 00 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 1 00 1,33 1,66 2,00 2,33 2,66 3,00 3,33 3,66 4,00 4,33 4,66 5,00 5,33 5,66 6,00 6,33 6,66 7,00 , Money 0
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Residuals Analysis:
1. Versus Order
Versus Order
(response is Time) 100
75
50 Residual
25
0
-25
-50 1 50 100 150 200 250 Observation Order 300 350
2. Versus Fits
Versus Fits
(response is Time) 100
75
50 Residual
25
0
-25 -50 0 25 Fitted Value 50 75
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3. Normal Probability Plot
Normal Probability Plot
(response is Time)
99,9
99 95 90 80
Percent
70 60 50 40 30 20 10 5 1 0,1
-50
-25
0
25 Residual
50
75
100
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Appendix E - Regression Data
Hours 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Emotional Motivation Atmosphere Accessibility Material Motivation Q2 Q3 Q10 Average Q4 Q7 Q13 Average Q5 Q9 Q11 Average Q6 Q8 Q12 Average 25 65 6 5,666667 4 4 4 443 3 3,333333 4 4 3 3,666667 40 44 5 4,333333 4 5 4 4,333333 2 2 2 244 4 4 55 55 5 533 4 3,333333 3 2 3 2,666667 7 6 6 6,333333 20 45 5 4,666667 3 2 3 2,666667 4 3 3 3,333333 4 4 4 4 25 56 5 5,333333 2 2 3 2,333333 4 5 4 4,333333 4 5 4 4,333333 45 44 5 4,333333 4 5 5 4,666667 5 5 4 4,666667 5 5 6 5,333333 30 65 6 5,666667 2 3 2 2,333333 4 4 4 434 4 3,666667 5 33 4 3,333333 3 2 3 2,666667 3 4 3 3,333333 1 2 2 1,666667 10 34 4 3,666667 4 4 4 433 2 2,666667 3 4 4 3,666667 15 54 5 4,666667 4 4 4 422 2 244 5 4,333333 68 67 7 6,666667 3 2 3 2,666667 4 4 4 477 6 6,666667 10 54 3 422 2 232 3 2,666667 4 3 4 3,666667 20 55 5 522 1 1,666667 4 3 4 3,666667 5 4 5 4,666667 35 55 6 5,333333 3 3 2 2,666667 5 5 5 556 6 5,666667 10 56 6 5,666667 4 4 4 465 4 533 4 3,333333 15 55 4 4,666667 4 4 5 4,333333 5 4 4 4,333333 4 3 4 3,666667 60 66 7 6,333333 4 4 5 4,333333 4 4 4 466 6 6 15 55 6 5,333333 3 3 3 365 5 5,333333 4 4 5 4,333333 15 56 6 5,666667 2 1 1 1,333333 2 2 1 1,666667 3 4 4 3,666667 20 54 5 4,666667 2 2 3 2,333333 3 2 2 2,333333 4 4 3 3,666667 5 56 5 5,333333 4 4 4 444 4 433 3 3 7 44 4 433 3 333 3 333 3 3 5 34 3 3,333333 5 5 5 555 6 5,333333 2 1 1 1,333333 5 56 5 5,333333 6 6 6 655 4 4,666667 1 1 1 1 9 66 6 666 6 666 6 633 3 3 16 55 5 534 3 3,333333 6 6 6 643 4 3,666667 30 76 6 6,333333 5 4 4 4,333333 5 5 5 567 6 6,333333 60 66 6 644 4 466 6 677 7 7 566 6 623 2 2,333333 3 3 3 322 2 230 15 66 6 645 4 4,333333 6 6 6 644 4 4 15 55 5 555 5 523 3 2,666667 3 3 3 3 45 67 6 6,333333 4 5 4 4,333333 5 5 5 555 5 5 30 66 6 666 6 666 6 633 3 3 30 76 5 645 5 4,666667 4 4 4 444 4 4 30 77 7 721 2 1,666667 2 3 3 2,666667 2 2 2 2 30 55 5 555 4 4,666667 5 4 5 4,666667 4 4 5 4,333333 25 55 5 534 3 3,333333 4 4 4 444 3 3,666667 18 66 6 666 6 666 6 622 2 2 3 55 5 523 3 2,666667 4 4 4 423 3 2,666667 X|Page
31 32 33 34 35 36 37 38 39
40 41
58 59 60
71
76 77
3 5 5 5 5 6 6 5 5,666667 6 6 6 6 2 1 1 1,333333 35 5 5 5 4 4 4 4 4 5 4 4,333333 3 3 3 342 10 7 66 6,333333 6 6 5 5,666667 6 6 6 6 4 3 4 3,666667 43 70 7 67 6,666667 4 5 4 4,333333 6 6 6 6 5 6 5 5,333333 44 45 7 65 6 4 4 4 4 5 5 4 4,666667 5 6 7 645 35 7 6 7 6,666667 55 5 5 6 6 6 6 3 3 2 2,666667 46 25 6 6 6 6 3 4 33,333333 5 5 5 5 5 4 5 4,666667 47 50 7 7 6 6,666667 7 6 7 6,666667 7 7 6 6,666667 2 1 2 1,666667 48 50 5 5 5 5 5 5 55 4 5 5 4,666667 6 4 5 549 50 4 3 5 4 6 6 6 6 5 6 55,333333 5 5 5 550 45 5 6 6 5,666667 5 5 4 4,666667 2 2 2 25 4 4 4,333333 51 15 5 5 6 5,333333 4 4 4 4 3 2 3 2,666667 4 4 5 4,333333 52 10 4 4 4 4 4 4 4 4 4 4 4 45 4 4 4,333333 53 20 4 5 4 4,333333 4 4 4 4 6 6 5 5,666667 4 3 3 3,333333 54 25 4 5 5 4,666667 3 3 2 2,666667 4 44 4 3 3 3 355 30 5 6 6 5,666667 4 4 3 3,666667 4 5 5 4,666667 6 5 5 5,333333 56 37 6 6 5 5,666667 5 5 6 5,333333 4 33 3,333333 4 4 5 4,333333 57 20 4 3 3 3,333333 4 5 4 4,333333 4 44 4 4 5 5 4,666667 15 5 5 5 5 4 4 4 4 3 3 4 3,333333 3 2 3 2,666667 40 7 6 6 6,333333 2 2 3 2,333333 4 5 4 4,333333 5 5 6 5,333333 56 5 5 5,333333 1 2 2 1,666667 2 2 2 2 4 3 3 3,333333 61 5 33 2 2,666667 4 5 5 4,666667 3 3 2 2,666667 5 5 5 562 10 6 5 5 5,333333 4 4 4 4 3 3 3 3 3 2 2 2,333333 63 5 54 5 4,666667 3 2 3 2,666667 4 4 4 4 5 4 4 4,333333 64 15 5 4 4 4,333333 4 4 5 4,333333 4 5 4 4,333333 4 4 4 465 20 5 5 5 5 3 4 4 3,666667 3 4 4 3,666667 5 4 4 4,333333 66 25 4 3 3 3,333333 4 4 5 4,333333 3 4 3 3,333333 5 5 5 567 50 7 6 7 6,666667 6 5 5 5,333333 4 4 4 4 6 5 6 5,666667 68 35 6 5 5 5,333333 5 5 5 5 3 4 4 3,666667 5 5 6 5,333333 69 40 7 6 5 6 4 4 4 4 5 4 4 4,333333 7 6 6 6,333333 70 10 5 4 5 4,666667 2 2 3 2,333333 3 4 3 3,333333 4 4 5 4,333333 56 6 6 6 2 2 3 2,333333 3 2 4 3 2 2 2 272 15 2 33 2,666667 5 5 6 5,333333 3 3 3 3 2 3 3 2,666667 73 20 5 56 5,333333 4 4 4 4 5 4 4 4,333333 5 4 4 4,333333 74 45 3 44 3,666667 4 4 4 4 5 4 4 4,333333 6 6 6 675 70 7 76 6,666667 5 5 6 5,333333 4 5 4 4,333333 7 6 6 6,333333 45 6 6 7 6,333333 5 5 5 5 5 5 4 4,666667 6 6 6 6 20 5 5 5 5 3 4 4 3,666667 5 5 5 5 5 4 4 4,333333 78 10 4 4 4 4 5 5 4 4,666667 2 2 3 2,333333 4 4 4 479 15 4 4 4 4 4 4 4 4 3 3 3 3 4 4 4 480 5 5 5 65,333333 2 3 2 2,333333 3 4 4 3,666667 3 2 3 2,666667 81 25 6 56 5,666667 3 2 2 2,333333 3 4 4 3,666667 4 5 5 4,666667 82 25 3 44 3,666667 5 5 4 4,666667 4 4 4 4 5 5 5 5 XI | P a g e
83 84
90
101 102
105
110 111 112 114 115 116 118 119 120
124
10 3 3 4 3,333333 2 1 20 6 6 5 5,666667 2 2 10 5 5 5 5 4 4 3 15 4 4 4 4 3 2 3 40 6 6 7 6,333333 3 4 50 6 7 7 6,666667 4 4 10 5 4 5 4,666667 4 5 52 3 3 2,666667 5 4 4 60 7 6 7 6,666667 5 5 66 6 6 6 6 6 7 7 6,666667 3 4 3 3,333333 5,666667 4 4 3 3,666667 63 4 5 4 5 5 5 5 33 3 3 4 3 3,333333 66 6 7 7 6 6,666667 5,666667 6 6 5 5,666667 77 7 7 2 2 2 2100 65,333333 7 7 6 6,666667 50 5 6 6 5,666667 4 4 15 5 5 5 5 4 4 4 20 6 5 4 5 4 3 3 20 5 5 5 5 5 5 5 20 5 5 5 5 4 4 4 66 6,333333 4 4 4 4 4 15 5 5 5 5 5 5 5 45 6 7 6 6,333333 4 5 15 4 4 4 4 3 2 3 40 6 6 7 6,333333 3 4 35 5 5 6 5,333333 3 3 15 6 7 7 6,666667 3 4 55 6 5,333333 2 3 2 40 6 6 6 6 6 6 6 25 6 5 6 5,666667 3 2 16 5 5 5 5 3 4 3 30 7 6 6 6,333333 5 4 20 6 5 4 5 4 3 3 20 5 5 5 5 5 5 10 6 5 5 5,333333 4 4 54 5 4,666667 3 2 3 15 5 4 4 4,333333 4 4 45 5 5 5 5 3 2 3 35 6 6 6 6 6 6 5 45 7 7 7 7 7 7 7
2 1,666667 2 2 2 3,666667 5 2,666667 4 4 3,666667 4 4 5 5 4,666667 4,333333 4 5 5 5 6 6,666667 3 3 3 5 5 5 1 1 2 2 2 1 4 3 5 4 4 4 65 6
3 3 2 2,666667 4 2 2 2 2 3 3 5 4 4,666667 5 4 4 5 4,333333 4 3 5 5 5 5 6 6 6 6 5,666667 5 5 3 3 4 3,333333 6 4 3 3,666667 5 6 5 5 5 6 6 6 5 5 4 4,666667 93 15 3 3 3 3 394 5 2 2 2 295 1,333333 96 8 4 5 1,666667 97 50 6 7 498 35 6 6 6 6 499 45 7 7 7 7 5 6 5,666667 6 6
3 3 3,333333 2,666667 85 4 4,333333 86 4 3,666667 87 5 5,666667 88 6 5,333333 89 5 6 5,666667 6 5,666667 91 692 40 6 6 7 7 5 6 6 5 4 6 6 6 5 4,666667 3 7 6,666667 6 6 6 5 7 7 7 7 6 6 5 5
5 4,333333 4 5 5 4,666667 4 4 5 4 4,333333 3 3,333333 3 3 3 3 4 5 5 5 5 4 4,666667 3 4 4 4 4 4 4 4 4 4 5 4,333333 4 6 6 5 2 3 3 2,666667 3 4 4,333333 5 5 5 5 5 2,666667 4 4 5 4,333333 4 4 3,666667 5 5 5 5 6 2 2,666667 5 5 5 5 5 3 3,333333 3 3 3 3 3 2,333333 3 4 4 3,666667 3 6 7 7 6 6,666667 5 2 2,333333 3 4 4 3,666667 3,333333 6 6 6 6 4 3 4 4,333333 5 5 5 5 6 3,333333 3 3 3 3 4 5 5 5 5 5 4 4,666667 4 4 3 3 3 3 3 2 2,666667 4 4 4 4 5 4 5 4,333333 4 5 4 4,333333 2,666667 3 2 3 2,666667 5 5,666667 6 6 5 5,666667 4 7 7 7 7 7 2 2 2
5 6 6 5,666667 5 4 4103 4 4,333333 104 4 3 3,333333 4106 30 7 5,333333 107 3 3 3108 5 5 5109 3 4 3,666667 6 5 5,666667 6 6 5,666667 3 3 3113 5 2 3 2,666667 5 4 4,666667 4 5 5 4,666667 4 3,666667 117 7 6 6,333333 4 4,333333 3 4 3 3,333333 2 2,333333 121 5 4 4,333333 122 4 4 4 4123 5 6 5,333333 4 4 4125 2 XII | P a g e
126 127
131 132 133
144 145
149 150 152
155 156
160 161 162 163
167
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doc_939506108.docx
Motivation is a psychological feature that arouses an organism to act towards a desired goal and elicits, controls, and sustains certain goal-directed behaviors. It can be considered a driving force; a psychological one that compels or reinforces an action toward a desired goal. For example, hunger is a motivation that elicits a desire to eat. Motivation is the purpose or psychological cause of an action.
HOW TO MOTIVATE FEMALES TO PLAY POKER ONLINE?
(Business study of Swedish women)
Abstract:The aim of this study is to investigate the main motives behind Swedish females' propensity to play poker online by means of hypotheses testing through regression analysis. Method includes collection of the information on definitions, theories and models about gambling, online gambling (precisely online poker) and motivations to gamble. Five hypotheses have been constructed based on the collected information and the survey have been created and conducted among 397 Swedish female online poker players. Further, based on gathered data, hypotheses have been tested by means of simple linear and multiple regressions. Regression analysis revealed that emotional and material motivations together with accessibility of the game and surrounding atmosphere play a significant role in the reason why Swedish females play online poker for money. It was also found that emotional motivation was a fundamental factor that triggers Swedish women to gamble. Furthermore, research revealed the hypothetical target segment of female Swedish online poker players. Average Swedish woman is between 30-40 years old single woman without children, who live high speed, active life (either studying or working) and who spends around 30.3 hours per months on playing online poker.
ACKNOWLEDGMENT
We would like to express gratitude to our supervisor Mikael Holmgren for the guidance and support during our working process. We also appreciate the help of our opponents and we would like to thank them for their advice and valuable tips. We would like to dedicate this paper to our parents: Svetlana Bochkareva and Viktor Bochkarev; Zhanna Petrova and Viktor Petrov. We would like to express additional appreciation to the respondents in Sweden, who spent their time to help us and fill in the survey. We would like to thank our friends and relatives for their encouragement, care and support.
____________________ Karina Petrova
____________________ Anastasiya Bochkareva
Västerås, May 31st , 2011
TABLE OF CONTENT
ABSTRACT ........................................................................................................................................... ACKNOWLEDGMENT ........................................................................................................................ 1. INTRODUCTION......................................................................................................................... 1 1.1 1.2 1.3 1.4 2. Problem Background .................................................................................................................. 1 Problem Specification................................................................................................................. 3 Research Question ...................................................................................................................... 5 Aim of the Paper ......................................................................................................................... 5
THEORETICAL FRAMEWORK ................................................................................................ 6 2.1 2.1.1 2.1.2 2.1.3 2.2 2.2.1 2.3 2.3.1 2.3.2 2.4 Definitions ................................................................................................................................... 6 Defining Gambling /Gambling routs and Characteristics .............................................. 6 Defining Online Gambling ............................................................................................. 6 Defining Online Poker.................................................................................................... 7 Market Segmentation Process.................................................................................................... 8 Segmenting the Internet.................................................................................................. 9 Motivational Models................................................................................................................... 9 Theory of Intrinsic and Extrinsic Motivation ............................................................... 10 Motivation to Gamble/Play Poker ................................................................................ 11 Formulating Hypotheses........................................................................................................... 13
3.
METHODOLOGY...................................................................................................................... 15 3.1 3.1.1 3.2 3.3 3.4 3.4.1 3.4.2 3.4.3 Scientific Methodology ............................................................................................................ 15 Conceptual Framework................................................................................................. 15 Literature Review ..................................................................................................................... 16 Choice of Theories.................................................................................................................... 17 Survey........................................................................................................................................ 18 Choice of Respondents ................................................................................................. 18 Data Collection ............................................................................................................. 18 Data Analysis................................................................................................................ 21
3.4.4 3.4.5 3.5 3.6 4.
Interpreting Regression Statistics ................................................................................. 24 Descriptive statistics ..................................................................................................... 25 Methodological Issues .............................................................................................................. 25 Validity and Reliability ............................................................................................................ 26
EMPIRICAL DATA ................................................................................................................... 28 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 Emotional Motivation............................................................................................................... 28 Atmosphere ............................................................................................................................... 29 Accessibility.............................................................................................................................. 30 Material Motivation .................................................................................................................. 30 Hours Spend Playing Online Poker ......................................................................................... 31 Occupation ................................................................................................................................ 32 Educational Level ..................................................................................................................... 33 Relationship Status and Children............................................................................................. 33 Age............................................................................................................................................. 34
5.
ANALYSIS ................................................................................................................................. 35 5.1 5.2 5.3 Demographic characteristics .................................................................................................... 35 The Model ................................................................................................................................. 36 The Hypotheses Testing ........................................................................................................... 37
6.
CONCLUSION AND DISSCUSSION....................................................................................... 40
REFERENCES ................................................................................................................................... 44 APPENDIX ...........................................................................................................................................I Appendix A - Estimating Sample Size.................................................................................................. I Appendix B - Survey............................................................................................................................. II Appendix C - Decode and Measurement for Each Survey Question ................................................ IV Appendix D - Homoscedasticity Tests and Residuals Analysis ........................................................ VI Appendix E - Regression Data.............................................................................................................. X
Table of Figures
Figure 1: Estimated internet gambling revenues .................................................................................. 2 Figure 2: Demographic comparison of gambling behavior by gender................................................. 2 Figure 3: Motivation summary........................................................................................................... 10 Figure 4: The hierarchical model ...................................................................................................... 12 Figure 5: Five-factor gambling motivation model ........................................................................... 12 Figure 6: Parallel five-factor model.................................................................................................... 13 Figure 7: Conceptual Framework....................................................................................................... 16 Figure 8: Emotional Motivation ......................................................................................................... 28 Figure 9: Atmosphere ......................................................................................................................... 29 Figure 10: Accessibility...................................................................................................................... 30 Figure 11: Material Motivation .......................................................................................................... 31 Figure 12: Hours Spend Playing Poker .............................................................................................. 32 Figure 13: Occupation ........................................................................................................................ 32 Figure 14: Educational Level ............................................................................................................. 33 Figure 15: Relationship Status and Children...................................................................................... 33 Figure 16: Age .................................................................................................................................... 34 Figure 17: The Hypothesized Model .................................................................................................. 39
Table of Formulas
Formula 1: General Regression Equation........................................................................................... 22
Table of Tables
Table 1: Summary Table of Regression Analysis .............................................................................. 37
1. INTRODUCTION
The first chapter introduces the reader to the field of interest and topic for the study. Moreover, it presents the problem background, develops further into the problem specification and ends with the statement of the research question and the research aim.
1.1
Problem Background
Starting from the ancient times with the primitive betting games and until our times, where gambling takes different forms (from casino games to horse races and lotteries) this is one of the oldest activities of the mankind, which has grown into the enormous business sector. (Carey & Carey, 1984) For some people gambling is seen primarily as an addiction; for others it is just one of the many forms of entertainment, while the third group of people can include those who see gambling as an illegal way of making people spend money. But in spite of all critiques and arguments around gambling, it has proven to be a very successful, huge and rapid growing industry worldwide. (Drozd, 2010) Just about ten years ago casinos, slot-machines and hippodromes were the physical/land-based locations, where people could place their odds and win/lose money. Nowadays technological progress contributed to the development of gambling practices transforming it into digital services. Digital gambling is becoming more popular and spread among people all over the world. It is now on the growing pace of replacing the land-based gambling. (Lloyd et. al., 2010; King et al., 2009; Griffiths, 2003) The start of public and commercial internet exploitation in 1990s has made it possible to evolve the land-based gambling services into the online ones. As a result, in 1995 online gambling opportunities have been introduced to the public (Manzin & Biloslavo, 2008; Wood & Williams, 2009). Online gambling industry in recent years has significantly grown in popularity. This growth is characterized by the increasing number of the online gambling web sites; types of the services available; and relatively relaxed regulations towards gambling activities in the majority of the countries worldwide. Now online gambling has developed into strong industry that generates sufficient and growing revenues. (Wood & Williams, 2009; Griffiths, 2003; King et al., 2010) Since 2001 the estimated internet gambling revenues have grown from about 3.1 billions of dollars to nearly 24.5 billion:
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Figure 1: Estimated internet gambling revenues (Christian Capital Advisory Ltd., 2011)
According to Drozd (2010) online poker is now listed as the second popular gambling activity in the internet space after betting. Nowadays this is one of the fastest growing online gambling forms (Griffiths et al. 2006). The first online poker room - www.planetpoker.com - was implemented in 1998 while the major expansion took place in 2003 (Wood & Williams, 2009). In 2010 poker generated $5.06 billion, which is nearly 21% out of the whole online gambling industry (Murray, 2011). And if betting online is popular among both male and female segments, online poker is by now only man dominated activity (Drozd, 2010; Wood et al., 2007; Griffiths et al., 2010). This could be illustrated by the below figure, where demographic comparison of gambling behavior by gender is presented. Precisely for poker sector, represented by partypoker.com website, men's dominance is evident.
Figure 2: Demographic comparison of gambling behavior by gender (Drozd, 2010)
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As the industry is relatively young, there have been done very little research in the online poker field. Consequently, the full-market potential has not been fully realized and investigated (Meyer et al. 2009; Griffiths et. al. in 2010; King et al. 2010; Wood et al., 2007). The existing researches don't provide the in-depth focuse on the online poker patterns, but rather aggregate and analyze all the different types of gambling in tandem; e.g. by Manzin & Biloslavo (2008); LaBrie et al. (2007); Mowen et al. (2009); Griffiths & Barnes (2008); Lee et al. (2007); Corney & Davis (2010); and some studies with small and representative population samples like Ialomiteanu and Adlaf research in 2001 of 1,254 Ontario adults and Meyer et al. (2009). Described studies have been attempting to explore the online gambling industry and online poker within this industry from different angles, where most of the effort was put into the investigation of the problem-gamblers and the male-customers dominance in the industry and precisely in the poker world (Griffiths et al., 2009; Ialomiteanu & Adlaf, 2001; LaBrie et al., 2007; LaPlante et al., 2009; Griffiths et. al., 2010; Meyer et.al., 2009) However the rapid growth of the online gambling and as a part of it, online poker industries has signed that there are new opportunities and a great potential for the further development. The underestimated and poorly investigated women's segment market might be a great revenue stream for the providers striving to attract the broad customer base especially now, when the competition is tough. (Drozd, 2010) In order to attract, acquire and retain the female segment, online poker providers need to understand the woman's behavior and motivations that make her risking money in order to win more (Drozd, 2010; Perse et al., 2005). As it turned out there has been done a very limited research about just females' motives to gamble (Davis & Avery, 2004); gamble online (Corney & Davis, 2010); and no separate research of women's motivations to play poker online.
1.2
Problem Specification
Swedish market with its strict monopoly on both land-based and online gambling is of great interest for investigation. Country has only one major gambling operator - Svenska Spel that owns 53 percent of market share. At first, the company was in charge for the land-based gambling facilities, such as four casinos. However, 8 years ago it broadened its power to the Internet gambling (Svenska Spel, 2011; Young & Todd, 2008; Jonsson & Rönnberg, 2009, p.300). In spite of receiving a lot of critiques from the EU and accusations in breaking the fair trade laws, Sweden is still insisting on the monopoly in the gambling industry and legally prohibits all other providers within the country. However it does not stop Swedish people to use services of the international providers and actively participate in the poker tournaments and other kinds of gambling entertainment outside the Swedish legislative boarders. There are currently around 265 websites available in Swedish language (i.e. Bettson, Party Poker, Bwin, etc.). (Young & Todd, 2008; Online Gambling Sites in Sweden, 2011)
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Online poker tables were launched in Sweden by Svenska Spel just in 2006 (Young & Todd, 2008). Consequently, this activity is relatively new and poorly researched within the Swedish boarders. From the demographic perspective the market segment of online poker players might be very broad in Sweden. Since anyone aged at least 18 years old (Jonsson & Rönnberg, 2009, p.302) is legally allowed to participate in the game, there are nearly 7,5 million Swedish people (SCB, 2010) who can be targeted by provides for a great fraction of the potential revenue stream. However, traditionally poker was predominantly men's activity. Back in time, women were not supposed to participate in any kind of gambling due to social, cultural and religious aspects (Carey & Carey, 1984). At the present time, the demographic situation in the online poker market is changing, but the typical stereotype that a gambler is a "dashing male figure" does still exist all over the world (Davis & Avery, 2004). The fact that women were not considered as the target segment, contributed to the high opportunity costs for the providers of missing the potential huge customer segment and therefore not gaining profits. (Wood & Griffiths, 2008; Corney & Davis, 2010). Nevertheless, during the last decade the social perceptions towards poker have changed and became more relaxed. According to recent findings the online poker is evidently gaining more and more attention among women. It was estimated that 33% of the poker playing population are women, who at least once a month play for real money stakes. In Sweden this percentage is second only to Austrian women. Swedish online poker playing females account for the 3% of the whole adult population, meaning that among overall 9 million inhabitants over one hundred thousand women played poker online in 2010. (Zupko, 2010) A study by Woods & Griffiths (2008) investigated the reasons why Swedish people play online poker and factors influencing trust in poker web-sites. The qualitative research has been done on twenty-four respondents, of which a majority (16 respondents) has been males. It was found that the possibility to play poker online (but not in the land-based casino) has contributed even more to the Swedish women involvement in the game. Woods and Griffith's (2008) research has revealed that a lot of women tend to swap their genders and register under the men's names, which was obviously impossible in the land-based casinos. Therefore, women became more confident and eager to participate in the online poker where no one would under evaluate their skills. This rise in the women's participation in the online poker games is certainly favorable for the providers striving to attract and retain as much players as possible (Drozd, 2010). The new segment (women) involvement in this industry means that providers should think of new marketing tactics in order to generate the appealing and attractive space for women in the internet poker world. However, as in any business sphere, in order to win the competitive advantage the most essential issue is to understand customers "behavior, drivers and motivations that make them feel like purchasing the product/service". (Montgomery, 2008)
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Although, there are several studies that attempt to investigate women's motivations to gamble online (Lee et al. 2007; Corney & Davis, 2010), it was hardly possible to find any sources concerning the motivations of Swedish women to play internet poker. The only study of Wood & Griffiths (2008) of Swedish people playing online poker does not make emphasis on women separately. Moreover, it is restricted to only 24 online poker players, which, taking into account the Swedish population can't be considered comprehensive in attempt to understand female's motivations to play poker online. So, despite the fact that providers worldwide have started to investigate women's behavior, majority of the existing researches are about online gambling as the whole without distinguishing online poker and female segment, and it seems that there is still a gap in this investigation in Sweden.
1.3
Research Question
The research question is as follows: 'What motivates Swedish women to play poker online for money?'
1.4
Aim of the Paper
It is important to understand the new developing segment in the online gambling industry, so service providers could manage to develop appropriate tactics and campaigns to reach this segment and to make it profitable. Therefore, this came as the first and most important goal for the online poker providers - to understand women's motivations, i.e. what demographic characteristics combined with the external and internal motivational factors make them play the game. (Drozd, 2010; Wiebe, 2008) Consequently the aim of this study is to investigate the main motives behind Swedish females' propensity to play poker online by means of hypotheses testing through regression analysis.
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2. THEORETICAL FRAMEWORK
The second chapter presents the theories, models and definitions that has been the basis for the study and has been constructed through literature review.
2.1
Definitions
Further understanding and definitions of main terms and notations used for current study are presented and explained.
2.1.1 Defining Gambling /Gambling routs and Characteristics
According to Cabot (1999), the attorney with the practice in gaming law and internet gaming, gambling can be defined in the following way: .. any activity in which a person risks something of value on the outcome of an uncertain event, in which the bettor does not exercise any control or is determined predominantly by chance . (Dewar, 2001) Gambling has a long prehistory that has started already in the ancient times. The activity that started as an entertainment has grown up into a huge - multibillion business nowadays with lots of casinos, slotmachines, lotteries and various locations where one can bet on horse races, sports and all the possible activities with the unknown outcome. The aim of any gambling activity is to win prize, or more precisely money. (Dewar, 2001) Drozd (2010) suggests the following classification of gambling types: The games of skill where outcome is not only fortune-driven, but the level of gamblers' knowledge, experience and professionalism play the most crucial role. Such activities include sports betting, cards games (poker) horse racing. The games of chance. Here the outcome is not controlled by people and cannot be managed by means of any knowledge, but rather odds and probability are the main linkage to the possible success or failure. These are bingo, casino games, i.e. roulette, lottery.
2.1.2 Defining Online Gambling
With the growth of technological advances the means by which gambling activities can be delivered to the potential customers is becoming even broader. Drozd (2010) suggested dividing the global gambling market into two broad parts, i.e. land-based gambling and digital gambling. The gambling market nowadays is one of the most profitable segments when it comes to the overall media and entertainment industry. The market offers a broad range of products and services which can be brought up to the consumers by means of various platforms. (Drozd, 2010; Wood et al. 2007)
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Gambling industry inculcated the advances of information and communication technologies and knowledge about virtual business. About ten years ago it started offering services online. In order to make any online gambling portal or casino to function, a complex technological solution has to be implemented. At the same time from the customer perspective everything is need is the access to the internet and a certain amount of money. (Manzin & Biloslavo, 2008) In various literature several notions could be found that refer to gambling through Internet: 'online gambling', 'internet gambling', 'cyber gambling', 'casino gaming on the internet', etc. Internet gambling consist of two types of activities. First, gaming meaning casino type games online e.g. poker, blackjack, roulette. Second, betting or wagering referring to various racing (e.g. horse, dogs) and sport events (e.g. football, hockey, basketball) betting. (Manzin & Biloslavo, 2008) Online gambling opened up opportunities for people to gamble anytime from anywhere, therefore expending gambling market and transforming many potential players (e.g. who didn't have landbased casino in the area) into real ones. People are no longer dependant on being geographically restricted to countries or regions. (Manzin & Biloslavo, 2008; Layton & Worthington, 1999)
2.1.3 Defining Online Poker
Online poker is one of the forms of online casino entertainment possibilities and at the same time the game of skills (see 2.1.1) that requires certain talent, intelligence and constant practices. There are three types on online poker services available at the present moment: Web-based poker, which can be played directly in the internet without any need to download additional software. This is the most popular form of online poker and the possibility to play in the internet for real money Download-based poker where the software needs to be downloaded in order to be able to play. After downloading there is no requirement to be connected to the browser. Live dealer poker service. This kind of online poker has not yet reached so much popularity as the two previously described ones but it is an existing development that combines both reality and web space. Users are able to see and interact with dealers by means of video links. (Drozd, 2010) Nowadays it is possible to play online poker for real money as well as without any kind of investment. There exists a significant difference between online poker and traditional in-person one. First, the rate of the play online is much faster, since no time is wasted on shuffling and dealing cards. Second, players are not able to see each other, therefore regular means for predicting the behavior like watching mimics and facial reactions are not usable any longer. Players now are
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analyzing each other by other factors such as betting patterns, reaction time, speed of play and so on. (Monaghan & MacCallum, 2006; Wood et al., 2007)
2.2
Market Segmentation Process
Market segmentation process consists of three stages: segmentation, targeting and positioning. The segmentation is essential for strategic marketing. It involves defining market segments, choosing suitable market target and deciding on how and where position the product/service. (Baines et al., 2008, p. 216) Market segmentation is "the division of a mass market into identifiable and distinct groups or segments, each of which have common characteristics and needs and display similar responses to marketing actions" (Baines et al., 2008, p. 217). For consumer goods/services' markets, certain segmentations are used for groups of customers with similar needs and wants. Most common bases are classified as Geographic, Demographic, Psychographic and Product-related. (Kurtz et al, 2009, pp. 261)
•
Geographic segmentation means dividing consumers into segments by their location. Variables here could be regions; countries; areas; population size; climate; job growth and so on. The main idea behind it is to identify core regions where certain product/service could be distributed.
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Demographic segmentation - customer groups are defined by demographic variables such as age; gender; ethnic group(nationality); education level; income attributes; occupation; social class belonging; household type and life stage. Psychographic segmentation is intended to provide deeper insights into consumer behavior. It is based on dividing people into groups with similar interests; opinions; characteristics; values and lifestyles. Psychographic segmentation is the most efficient when applied together with demographic and geographic ones.
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Product-Related segmentation helps to identify customer segments by their connection to product/service. This segmentation is based on benefits that customers seek from the particular product/service. Other variables are for example usage rates - the amounts that customers purchase and how often product/service is used; brand loyalty, etc.
(Baines et al., 2008, pp. 223-239; Kurtz et al, 2009, pp. 261-278). After dividing markets into segments the next step is to decide which of these segments to target. This could be done by evaluating market segments by effectiveness or attractiveness factors. The third part of segmentation process - positioning - starts when segments have been defined and specific market targets have been identified. Positioning has two important elements - physical
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attributes of product or service and how those are communicated and perceived by customer. (Baines et al., 2008, pp. 246-251)
2.2.1 Segmenting the Internet
With the increasing importance of Internet and online sales it became important for companies and marketers to understand web users and shoppers (Donthu and Garcia, 1999). Internet has eliminated geographical borders and boundaries between companies and its customers and has initiated firms to offer more standardized products/services. Those products and services are offered internationally, which may cause companies to face problems associated with different characteristics and behaviors of customers from all over the world. (Barnes et al., 2007) Kau et al (2003) study of topology of online shoppers indicated that it is essential to understand different customer segments involved into online activities in order to be able to develop effective strategies and tactics for attracting and keeping those customers. It was found that online and traditional customer segments significantly vary in terms of importance to convenience, risk aversion, impulsiveness as well as more typical dimensions such as age, gender, patterns, social group, etc. Miller (1999) highlighted another criterion for segmenting Internet users - by manner in which they use it: for academic purposes and studying; for personal use (e.g. entertainment, shopping, communication, etc); for business; etc. The life stage during which people are introduced to Internet is also important and has a lot to do with what people want and need from Internet. The understanding of characteristics of different segments and how they use the Web is crucial for companies that are operating online businesses.
2.3
Motivational Models
"Consumer research looks into the motivations and personalities of an individual in terms of consuming or buying a particular product or service, later turning this information into strategies geared at gaining a particular segment of the market that the company targets or centers on" (Montgomery, 2008). The theory of consumer behavior is based upon the three major categories - motivation, cognition, and learning. The motivation can be said to be the fundament in the sequence of the three components. Motivation in other words is the aggregate of drivers, wishes, urges and desires which lie at the roots of consumer behavior. Cognition and learning are products of mental phenomena and can change over time in response to the external factors. (Bayton, 1958) The important thing about motivation and its nature is that it can be hardly classified as the unitary phenomenon. People have different amounts as well as kinds of motivations, i.e. it is not only stage of motivation but also the kind. (Ryan & Deci, 2000)
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2.3.1
Theory of Intrinsic and Extrinsic Motivation
From the psychological perspective motivation is the combination of external and internal factors that build up people's behavior. In the business environment motivation plays a vital role as it influences consumers' behaviors. So, it is of a great importance for the companies providing a service or selling a product to understand factors that motivate people to spend their money. This knowledge will consequently help providers to come to the decision how those factors can be manipulated in the most favorable for the company way. According to several studies in the field of gambling and the motives behind it, intrinsic motivational factors are more common for those poker players and other gamblers who are seeking for socializing and entertainment and are not commonly associated with the problem-gambling. At the same time extrinsic factors are the materialistic needs that make people desperate to winning and are more commonly seen among poker players with problematic addiction. (Lee et al., 2007) Intrinsic motivational motives are in other words the internal, i.e. based on personal needs, cognitions and emotions, factors. Person does some kind of activity not for some "separable consequence" but for the self-esteem and inner satisfaction. While extrinsic factors are those external triggers that are caused by environmental, social and cultural surroundings of a consumer. (Ryan & Derci, 2000) Ryan & Derci (2000) summarized the main theoretical concepts of both kinds of motivations in one graph (Figure 3):
Figure 3: Motivation summary (Ryan & Derci, 2000)
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This theoretical presentation subdivides the motivation into three groups, where the extrinsic motivation is stated to be the largest. Two other types of motives, i.e . amotivation and intrinsic motivation, are smaller and of an equal size without any additional subdivisions. In addition to this vertical division, there is a three-row horizontal division: regulatory styles, i.e. the theoretical names of the concepts; associated processes, i.e. the explanation/real-life description of the motivations; and perceived locus of causality, i.e. how the motivations are perceived in reality. This third row of perceived locus of causality explains the broad specter of the extrinsic motivation group, pointing out that the theoretical view on the motivation does not strictly corresponds with the real perceptions. The sector is therefore also subdivided into extrinsic and intrinsic traits with the more incline to the right towards the perceived nature of the motivation. (Ryan & Derci, 2000)
2.3.2 Motivation to Gamble/Play Poker
Understanding gambling behavior and motives of gamblers is the primary goal for marketers who strive to create the persuasive messages for each target group (Mowen et al., 2009). The theory of market segmentation suggests that depending on features possessed by different groups (i.e. national peculiarities, age differences, economic factors, genders, etc.) there do exist different approaches for targeting the particular segment due to the variations in their perceptions, attitudes and motivations when purchasing product/service (Hong & Jang, 2004; Davis & Avery, 2004; Laplante et al., 2009; Griffiths at al., 2010). The motives and reasons to gamble/play poker are different depending on the perspective from which to consider the results. Obviously the most common reason to gamble is "to win" or "to win money". Still even both motives sound to be very related they include a wide spectrum of personal traits and primary factors. The Swedish National Institute of Public Health applied three different approaches in the investigation of gambling motivation and involvement; those are sociological approaches, economic and cultural aspects of gambling behavior. (Binde, 2009) In their investigation of trait antecedents of gambling, Mowen et al. (2009) applied a hierarchical model of personality to make the assumptions of correlations between traits and propensity to gamble and build up hypotheses of positive/negative correlations. They applied a rather psychological approach to determine the traits of gamblers and their motives in different forms of gambling including online facilities. For example, it was found that financial conservatism is negatively related to the online forms of gambling placing the role of money and saving over the insecure possibility to earn more. At the same time introversion was found to be positively related to online gambling stressing the solitary nature of presence online. The openness to experience was also considered to be important characteristic of the online gamblers. Figure 4 below represents the division of motivational traits to gamble/play online poker in the hierarchical model proposed by Mowen et al. (2009):
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Figure 4: The hierarchical model (Mowen et al., 2009)
Both Mowen et al. (2009) and Hong & Jung (2004) studies suggested the importance of impulsiveness and emotional instability of the major gamblers' group stressing the inevitable role of emotional motivations when playing for money. Interestingly it was found out that sensation seeking was not statistically significant determinant of the potential gambler. In their study of problem gambling and psychological motivations Lee et al. (2007) have proposed two Five-factor gambling motivation model. The first one, presented in Figure 5, makes the emphasis on the monetary impact and the implications of gambling severity:
Figure 5: Five-factor gambling motivation model (Lee et al., 2007)
The model (where M stands for 'motive') places a great importance of the psychological/emotional features that stand behind the economic factor, i.e. monetary motive. This monetary/extrinsic motivation emphasis corresponds with the above Ryan & Derci (2000) three groups of motivational model, where the middle row "Extrinsic motivation" merges both external and internal motives stressing out their interconnection when it comes to the perceptions.
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The second model in Figure 6 is the parallel five-factor model and discuses the independent influence of the 5 factors in gambling severity:
Figure 6: Parallel five-factor model (Lee et al., 2007)
The parallel model emphasizes the independence of all the factors on gambling intensity. According to the results of the five-factor model investigation, it was found out that monetary motivation does have the direct effect on the gambling severity, while such factors as excitement and avoidance affect gambling behavior only through money motive. Various other factors could become incentives for people to gamble. Jonsson and Rönnberg (2009) in their article 'Gambling in Sweden' discussed such factors as positive and negative emotional state of the person; various events on gambling market and wrong believes and expectations from gambling.
2.4
Formulating Hypotheses
According to Mowen et al. (2009) and their research based on the 3M model discussed in the theoretical background of this study paper, emotional drivers impact positively on the intensity of gambling/online poker gambling. At the same time Lee et al. (2007) stressed out that women were more than men driven by the emotional triggers to be involved in the gambling activities. The positive relationship was also found by Wood & Griffiths (2008) and Corney & Davis (2010). Thus the first hypothesis is: H1: There is a positive statistically significant relationship between Swedish women propensity to play online poker and emotional motivation, i.e. self-enjoyment, impulsiveness and excitement all together. Previous investigations of the gambling/online poker propensity among both men and women found out the significant and positively directed relationship between involvement into the game and economic trigger. Lee et al. (2007) stated that monetary motive is the only one that has the direct impact on gambling severity while all the other motivations (see five-factor model in the theoretical
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background) affect gambling behavior indirectly through money motive. What is more, the existing researches stress out that the money motive is more common among men players. (Mowen et al., 2009; Layton & Worthington, 1999; Lee et al. 2007) Thus the second hypothesis is: H2: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and material motivations. One of the earliest studies of the gambling and socio-economic implications stressed out the importance of ease and convenience when it comes to the accessibility of the gambling service (Layton & Worthington, 1999). Moreover, Wood et al. (2007) found that accessibility and distance from casino were some of the top reasons to gamble online. Corney & Davis (2010) have discovered that around 90% of interviewed women admitted that accessibility of the internet influenced their propensity and frequency to gamble. The positive involvement in the online gambling activities due to the easy and comfortable accessibility, i.e. from home, work, etc. was also found by Wood &Griffiths (2008). H3: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and level of accessibility of the game. The positive relationship was also found between the private and relaxed atmosphere the online access gives to women and their frequency and comfort to play online gambling games (Corney &Davis, 2010; Wood & Griffiths, 2008). In their investigation of the reasons to gamble online versus land-based casinos, Wood et al. (2007) found that privacy issues and negative attitudes to the crowdie surroundings were among the most popular motivations to choose the internet gambling services. H4: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and the surrounding atmosphere As it was stated earlier, women were traditionally considered to be motivated by the set of the emotions that trigger them to play online poker or are other gambling activity. Lee et al. (2007) found that the amount of women admitting emotional motivation was around 70%. Also Corney & Davis (2010) stressed out this fact in their investigation of females' attractions towards online gambling. Thus the 5th hypothesis is: H5: Emotional incentive, i.e. excitement, enjoyment, adrenaline, has the largest/the most important impact on Swedish women's propensity to play poker online.
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3. METHODOLOGY
3.1 Scientific Methodology
Current research reflected the concept of positivism, where authors prefer 'working with the observable social reality and the end product of such research can be law-like generalizations similar to those produced by the physical and natural scientists' (Remenyi et al. 1988 as citied in Saunders et al., 2009, pp.113). The phenomena/topic authors observed lead to generation of a credible data and research strategy based on existing theories and models as well as hypotheses. Authors attempted to carry out the research in a value-free way, meaning that authors were not influenced by the subject of the investigation and didn't influence it themselves. This was achieved by carefully designing the research process and using highly structured methodology. (Saunders et al., 2009, pp.113-114) There are two possibilities to decide what is true or false and draw fair and relevant conclusions deduction and induction; the first one is based on logic, while second - on empirical evidence (Ghauri & Grønhaug, 2010, p. 15). Current research was based on deductive approach, meaning that the theories and hypotheses were build first, before collecting empirical data. Authors performed detailed literature review on the selected research topic and, based on this literature review, built up the theoretical framework and the rest of the research process. Authors deducted five hypotheses from the existing literature and tested those using existing concepts in statistical analysis: H1: There is a positive statistically significant relationship between Swedish women propensity to play online poker and emotional motivation, i.e. self-enjoyment, impulsiveness and excitement all together. H2: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and material motivations. H3: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and level of accessibility of the game. H4: There is a positive and statistically significant relationship between Swedish women propensity to play online poker and the surrounding atmosphere H5: Emotional incentive, i.e. excitement, enjoyment, adrenaline, has the largest/the most important impact on Swedish women's propensity to play poker online.
3.1.1 Conceptual Framework
In order to study the research topic, answer research question and achieve the aim of the study, authors developed a conceptual framework based on the performed literature review:
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Figure 7: Conceptual Framework (own illustration)
Quantitative research method was chosen in association with deductive approach. Quantitative research involves measurements and is focused on testing and verification. Therefore for current study, where hypotheses have been constructed, quantitative method was the most suitable since it allowed accepting or rejecting these hypotheses in a logical and consistent way. Authors chose to conduct the pre-structured survey on a sample of respondents that was taken from overall female population of Sweden over 18 years old. Conceptual framework, summarized in figure 7 included theoretical background about Segmentation/Demography as well as Motivational models - Hierarchy of Traits and 5-factor Models (from which extrinsic motivation factors such as accessibility and material needs and intrinsic motivation factors - emotional and atmospheric have been identified). Based on those theories; distinguished factors; literature review and hypotheses, survey for testing those hypotheses has been constructed. With help of statistical analysis, precisely multiple and single regressions as well as descriptive statistics, data collected from the survey have been accessed, analyzed and interpreted. By testing the hypotheses and identifying which are accepted and/or rejected, authors achieved the research aim and answered the stated research question. The idea of the research was not only to identify motivations of some hypothetical Swedish woman to play online poker for money. It was also relevant to understand the general characteristics of the typical female Swedish online gambler in order to get the picture of the potential profitable segment among Swedish female poker players.
3.2
Literature Review
Authors began the study by collecting relevant ideas; theories; models and previous researches about gambling, online gambling industry, online poker and motives behind people playing games for money in the Internet. Key academic theories within research area have been identified and their
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overview was presented as theoretical framework and also used in introduction. Authors started out by retrieving more general information about gambling industry and motivation and then narrowed it down to online gambling, online poker and females playing it and therefore came up with limited field of study and precise research question. Several types of sources have been used for retrieving the information for the research. Both secondary and primary sources have been located with help of tertiary sources. Those 'search tools' included search engines such as Google -http://www.google.se/ and Google Scholarhttp://scholar.google.se/; subject directories - Yahoo! -http://www.yahoo.com/. Moreover, several databases have been used - EMERALD (http://ep.bib.mdh.se:2086/); ABI/INFORM Global (ProQuest); LibHub (http://ep.bib.mdh.se:3655/libhub). (Saunders et al., 2009, pp. 86-87) Due to the fact that most of the information has been accessed online, certain parameters of the search have been defined. Language of publications was English since the report had to be written in English as well; search area as has been mentioned was within gambling and online gambling industry as well as people's motives for gambling online; geographical area of search was not limited, documents from all over the world written in English and within subject area have been reviewed. Certain ''key words' such as 'gambling'; 'online gambling'; 'Internet gambling'; 'online poker'; 'motivation theories'; 'segmentation'; 'women gambling', etc. have been defined and used for searching both primary and secondary sources through tertiary sources. (Saunders et al., 2009, pp. 75-76) Primary sources, which are first occurrences of documents that were used for literature review and theoretical framework, included several reports and studies connected to gambling and online gambling research, published by Swedish National Institute of Public Health and European Parliament's committee on Internal Market and Consumer Protection (IMCO). Secondary sources included books and journal articles retrieved with help of described tertiary sources. Various article on chosen topic have been found in 'European Journal of Marketing'; 'Journal of Marketing'; 'Journal of Gambling Issues'; 'Journal of Advertising Research'; 'Journal of Consumer Marketing'; 'Journal of Business Research'; etc. Books such as 'Marketing'; 'Contemporary Marketing'; 'Gambling in Sweden', etc. have been found in Mälardalen University and Västerås city libraries.
3.3
Choice of Theories
The theories applied in this paper were chosen after the careful and detailed literature review. The theoretical base attained from the specific scientific studies and books served as the fundament for creation of the conceptual framework for this research. As the incline of this study paper is on characteristics of women playing online poker and their motivations, the theoretical framework was subdivided into three parts.
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First, it was important to get the background on overall gambling characteristics, i.e. industry with its opportunities, and precisely online poker, in order for authors to get deeper knowledge and exact picture of chosen business sector. Then, the insight on the marketing segmentation was needed in order to find out the main characteristics, i.e. marital status, occupational and educational levels etc., of the potential online poker playing women. These theories were mainly needed in order to make up the second part of the survey, where the aim was to receive the personal features of the women market segment. And for the last and the most important part of this research, the deep investigation of the motivational theories and models was made. These theories were essential in order to build up the likert-scales of the survey and according to the attained responses apply the statistical analysis, i.e. multiple regressions. This was supposed to identify the significance of the theoretically suggested motivations to play poker online for the women in Sweden and come to conclusion which drivers are the most important.
3.4
Su r v e y
3.4.1 Choice of Respondents
As have been mention, the current study was focused on women in Sweden who play poker online for real money. The total population of the country for 31th of December, 2010 was 9,415,570 people of age from 0 to 111, where 4,725,326 people were women (SCB, 2010). Out of 4,725,326 women 3,729,091 are older than 18 years old, which is the legal age from which people are allowed to gamble (SCB, 2010). According to Fisher (2007, p. 189) and Saunders et al. (2009, pp. 218-219), the suitable sample size for the research depends on the size of the margin of error researchers are prepared to accept and the size of the population from which the sample is going to be drawn. For current research the authors accepted 95% confidence/certainty level and the margin of error/confidence interval of +/- 5%, in other words for example if 53 % of sample prefer category A, authors were 95% sure that the same estimate for the whole population within the same category A was going to be 53% +/- 5%, between 48 and 58%. Taking into account confidence level; margin of error and the total size of the population from which the sample was taken - 3,729,091 (SCB, 2010) women in Sweden who play online poker, by using table in appendix A, authors estimated the required amount of completed questionnaires, which equaled to 384 surveys. (Fisher, 2007, p. 190; Saunders et al., 2009, p. 219)
3.4.2 Data Collection
Primary data for the research was collected through a survey. Authors used analytical type of questionnaire, because with this type, it is possible to understand the relationships and identify
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independent, dependent and extraneous variables which is the aim of the research (Ghauri & Grønhaug, 2010, p. 119). Moreover, in analytical surveys performed literature review and constructed theories are of great importance while structuring the overall research that is exactly the case with current study, where a lot of emphasis was put on existing literature, theory and researches. Furthermore, employing analytical type of questionnaire gave authors possibility to manage independent, dependent and extraneous variables with help of statistical techniques and analysis, such as multiple and single regression analysis. The survey was logically structured: starting with similar general questions and moving on to more specific personal ones in the end of the survey. Pre-structured survey is shown in Appendix B. Authors attempted to construct relatively short survey, so respondents wouldn't get tired and loose interest while filling it in. The language used is simple; easy to understand and straight forward. Authors made sure to use words that don't have double meaning and that overall language is easy to understand for people with different background (education, knowledge, etc) In addition all questions and explanations were formulated in polite and soft nature, so not to offend, annoy or provoke the respondents. (Ghauri& Grønhaug, 2010, pp. 123-124) Questions were formulated so there was no escape route for respondents to avoid answering the question. Authors didn't provide answer option such as 'no comment', therefore ensured respondents to choose one of the answers. (Ghauri & Grønhaug, 2010, pp. 122, 124) Each question in the survey was aimed to measure only one variable/ dimension, so respondents and authors wouldn't get confused, moreover, each question has been carefully coded in order for authors to be able to perform statistical analysis of the data. A detailed explanation of what each survey question was intended to measure and decode for each question is presented in Appendix C. Types of primary data included status and state of affairs data, which data on demographics and socio- economic nature. For current research authors were interested in retrieving information about age, marital status, education level, occupation and amount of time respondents spend playing poker. Questions were based on the segmentation theory and its implications. Six questions were constructed based on segmentation theory in order to collect status and state of affairs data. Two questions about the age of the respondents and amount of time spend playing poker were of open- ended nature, so respondents were able to fill in their exact age and their own estimate of time spend playing poker and not tick a box with suitable range. That was done in order to be able to identify the exact average age of the respondents and exact number of hours they play poker online. Other four questions were closed questions, where respondents were offered to choose one of the provided answers: two dichotomous questions which had just two alternatives to choose from and two multiple-choice questions were employed. (Fisher, 2007, pp. 193-199; Ghauri & Grønhaug, 2010, p. 100)
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Second type of primary data gathered was data on motivation. Collected data helped to understand motives and stimuli behind woman playing online poker. Twelve likert-scales one of the forms of rating scales were constructed in order to find such factors as driving forces and motives that influence respondents' behavior and are behind them choosing to play online poker for money. Likertscales were based on motivation theories and models chosen as theoretical framework for the research. Respondents were asked to choose a number from one to seven that best represents the extent to which provided statements correspond to the reasons why they play poker online. The spread of answers was between 'does not correspond at all' - one to 'corresponds exactly' - seven. (Fisher, 2007, pp. 195-196; Ghauri & Grønhaug, 2010, p. 101) Pre-structured survey have been spread among the female customers of Casino 'Cosmopol' in Stockholm city by authors and their friend who works in the casino and have access to the potential respondents. It was assumed that women, who gamble in land-based location, were possibly gambling online as well. Survey was designed, so the first question identified the respondents who play online poker, moreover, when author were in the casino on 15th of March and 27th of April, 2011 between 14.00 - 19.00 pm they were first directly asking potential female respondents if they play poker online and in case of positive reply asked them to fill in the survey; in total during the first visit authors collected 47 completed questionnaires and during the second visit 84. Friends of authors have been giving out surveys to female customers, who agreed to fill it in during 4 days between 11.04.2011-14.04.2011 and during 4 more days between 25.04.2011-27.04.2011 and on 29.04.2011. The total amount of given out surveys for both time periods exceeded 650, where just 230 have been fully completed. Besides casino 'Cosmopol' authors have spend time in 'ATG' - Swedish Horse Racing Totalisator Board locations trying to reach potential respondents with the same technique. On 14 th of March, 2011 both authors have been in 'ATG' locations in their home-towns in Västerås and Märsta, between approximately 12.00 and 17.00 pm. Both authors together collected 36 completed surveys. Even though that 'ATG' have nothing to do with poker, it is the place where people place bets on horse racing, which is one of the form of gambling, therefore the audience visiting 'ATG' gambles and possibly plays online poker (ATG the Company, 2011). Authors were asking any female 'ATG' visitors if the play online poker and if the answer was positive asked them to complete the survey. Coverage of respondents from three different cities in Sweden - Stockholm, Västerås and Märsta provided authors with wide sample of the population not located in one place/city in other words geographical area, and therefore generalization of the result on this sample is possible. As calculated above the amount of completed surveys that was required for the study based on total population size, confidence interval and level was 384, where total number of completed survey that authors manage to collect equaled to 397, which is more than enough in order to achieve representative results and make conclusions general for overall population. The rate of response is
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calculated by dividing the total amount of collected surveys (397) with total number of given out surveys (?820) and multiplying by 100%. The respond rate equaled 48,4% for current study.
3.4.3 Data Analysis
For testing the deducted hypothesis, using data collected from the survey, authors decided to perform regression analysis. In order to investigate the important and significant relations between dependent and explanatory variables in business statistics or economic research, the regression analysis can be applied (Ghauri & Grønhaug pp.177-184). Barrow (1996, p.220) stressed out the applicability of regression analysis as a tool to measure the impact of the exogenous, i.e. explanatory, factors on the endogenous one, i.e. dependent variable. By entering step-by-step the variables into simple linear regression one can assess the change of the explanatory power of the new model (multiple) and see whether the power rises, remains unchanged or diminishes. If the power rises then this means that the additional explanatory variables were needed; if the modelweakens in its explanatory power then the extra variables ruin the main regression principles/assumption: Linearity of the relationship between predictors and dependent variable Homoscedasticity/ homogeneity of variance Independence of the error terms Normal distribution of errors
The violation of the main assumptions can be checked, which was done in this particular study. The violations of linearity were detected with the help of observed residuals versus fits in Minitab, where the points have been symmetrically distributed around the line. Independence of the error terms was detected by checking if there is a presence of autocorrelation. Graph residuals versus order can provide the visual evidence of presence or absence of the autocorrelation: the cluster of residuals with the same sign told about the existence of positive autocorrelation, a negative autocorrelation was indicated by rapid changes in the signs of sequential residuals. The normal probability plot provides the evidence of normality or non-normality otherwise. If the distribution is normal, then the residuals have to be proportionally placed close to the diagonal line. According to homoscedasticity assumption the dependent variable has to exhibit similar variances across the range of predictor variable. There is a graphical method called boxplot to check this assumption of the regression analysis. All the assumptions were checked (see Appendix D). Obviously it is hardly possible to get perfect matches with the theory because of the data specification/encoding, broad sample and probably sometimes random answers. However, taking into account that the original data is coded with theequal intervals, the regression can be considered as the appropriate tool to make the particular
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analysis since even with the few violations of the regression assumption, the overall trend towards the proposed theoretically rules is held in the précis model. (Cottrell, 2003) Multiple regression analysis Multiple regression analysis is a procedure to create the linear equation that shows the statistical correlations between Y and X variables:
Formula 1: General Regression Equation
Y - Dependent or endogenous variable. In this research that was the proxy of the online poker playing affection among women, i.e. hours spent on the game per month. X1, X2, X3, X4 - Explanatory/predictor/exogenous variables. In the regression analysis the direction of the causality is assumed to be directed from the explanatory, i.e. exogenous, variables towards the dependent variable. Here these were the kinds of extrinsic and intrinsic motivations that were theoretically assumed to cause the involvement into online poker among women, and have the statistically significant impact on the dependent variable. As it is evident from the survey (Appendix B), there are four types of motives behind the women's involvement into the online poker games. All those types were investigated by means of three likertscale statements for each type of motivations and then divided into two major groups, extrinsic and intrinsic motivations. In order to run the regression analysis with four potential predictors, i.e. emotional motivation, atmosphere, accessibility, and material motivations, the likert-scale answers from 1 to 7 in out of each three questions group were aggregated and the average was found, that represented each motive (Appendix E). ?1,?2,?3,?4 - The coefficient shows the elasticity, i.e. the amount of change in the endogenous variable due to change in the exogenous variables. The sign of the coefficient indicates the direction of the relationship, either positive, plus sign, or negative, i.e. minus sign. ? - The constant. Considering that there is zero relationship between explanatory variables and the dependent one this is going to be the intercept of the x-axis with the y-axis, if presenting the results in the graphic way. ? - The error term. In other words it represents all other variables that have the probable impact on the dependent variable but were not included for some reasons. (Barrow, 1996, pp.241-265) Regression analysis with the non-numeric variables If regression analysis is done with non-numeric explanatory variables, i.e. different kinds of motives as in this particular research, then the implementation of the codes is essential. This is called
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"dummy coding" if one uses binary choice variables, i.e. male/female, and is coded by means of '0' or '1' to show the different categories, or if this is the case of using likert-scales results, i.e. more than two possibilities, the digits from 1 to 7, for example, are used as the codes to demonstrate the levels/intensity. In other words, one assigns numbers to the non-numeric data in order to apply the regression analysis. (Winship & Mare, 1984) The data, that is non-numeric, can be of the different types: Categorical variables: These variables have two or more categories but those are not directed by some intrinsic order. The gender, i.e. male and female, can be an example of the categorical variable and can be coded by means of two different digits, for example 0-male and 1-female, and like that presented as the ready data for statistical analysis. This is also called dummy-coding. Ordinal variables: The difference between categorical and ordinal variables is that there is a clear sequence/levels of the variables. For, example if there are different opinions when filling in the survey towards online poker, i.e. "I play poker online because I want to earn a lot of money easily and quickly" and variants of answers "does not correspond at all", "corresponds a little", "corresponds moderately", "corresponds a lot", "corresponds exactly", then those variants of answers can the categorized by order with the help of numbers from 1 to 7 or some other final digit and investigated by means of the regression analysis. Interval variables: These variables are nearly the same as the ordinal variables in the sense of sequential ordering but the intervals between the values are evenly spaced. (G.-Martin, 2009) Likert-scale results as Explanatory Variables in Regression analysis There are no notions about the distribution of the explanatory variables in that kind of the regression analysis. Nevertheless, parameter estimates generally are only interpretable for nominal categories or numerical data. The coefficient is decoded as the difference in the mean of dependent variable, Y, for each unit change in the independent variable, X. If X, the predictor, is categorical, so a unit change simply postulates switching from one category to another. Ordinal independent variables are regarded as either nominal unordered categories or numerical. In the case of nominal unordered categories, the assumption about the order is neglected. In the second case, one is making assumptions about the variations between the scale items. If the distances can be reasonably considered equal and meaningful, then it is rational to consider the exogenous factors as numerical (a unit change from 1 to 2 is equivalent to a unit change from 3 to 4). (High, n/d) Likert-scale independent data in the analysis can be considered as the ordinal predictors, which are categorical explanatory variables where the categories have a natural ordering. One may choose to investigate the particular data as if it were continuous, nominal or categorical variables. The most common and therefore applied in this research way to treat ordinal predictors is as if it was a continuous data. (Winship & Mare, 1984)
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So, qualitative predictor data can be also analyzed by means of statistical/econometric tools traditionally applied for the numeric data. Regression analysis is one of these tools. After coding data (in case of likert-scale the rank of answers from 1 to 7 for example) the regression can be easily run if the data approves several important assumptions: 1. It must be a full likert-scale data, i.e. the composition of several questions with the multiple likert-scale answers. 2. The intervals between the answers must be reasonably considered equal (at least nearly equal) in order to treat the data as continuous and run the regression analysis. 3. Change in categorical predictor is interpreted as switch from one category to another and the consequence impact on the dependent variable. (Winship & Mare, 1958) Consequently, in this paper the likert-scale answers from 1 to 7 were considered as the coded ordinal predictors with the equal intervals.
3.4.4 Interpreting Regression Statistics
The regression analysis, in other words is rejection or acceptance of the null hypothesis (H 0). The regression output helps to determine whether the coefficients of the desired results are equal to zero, i.e. statistically insignificant (H0 is accepted). Consequently, in this study paper the H0 is desired to be rejected and that the tested hypotheses are statistically significant. All the regressions have been run in the statistical software Minitab. In this research the regression results and the overall model was considered to be significant within 95% confidence interval. Meaning that probability values p less than 0.05 (5%) indicate the significance of the achieved results and implied on the acceptance of the hypotheses tested in this paper. The regression analysis provides different measures of the significance of the tested models and the relationships within the models. However, this study paper was concentrated on the most important ones for this research, precisely, R2 , R2adjusted, F, t-statistic, p values and? coefficients. (Barrow, 1996, pp. 241-265)
T-statistic/? coefficients/p-values
T-statistic's p-value provides the information about the significance of the? coefficient. Minitab software computes the probability values directly. So, taking into consideration that in this research all the results are significant at the 95% confidence level, the p values under 0.05 will indicate the statistical significance of the? coefficients. (Minitab, 2011)
R2 (R squared)
R2 is also called the coefficient of determination. This is the measure of the correlation of the dependent and predictor variables in the tested model. In other words this coefficient shows how
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well the chosen exogenous factors explain the variations on the endogenous variable. The higher the coefficient, the better the model fit. However, it is worth to remember that too high coefficient is more often the result of biases (violations of the regression assumptions) in the model. At the same time, too low coefficient will tell that the chosen explanatory factors are insufficient to explain the alterations in the dependent variable and the additional predictors are needed.(Minitab, 2011)
R2 adj. (adjusted R squared)
In the multiple regression analysis R2adj. is a goodness-of-feet measure that is similar to the simple R2 but it allows for the other variables to be entered into the model, which therefore lessens the degrees of freedom. R2 adj. increases only if the new potential predictor would improve the model, meaning that the present model is incomplete. (Minitab, 2011)
F-test
The F-test is the other goodness-of-feet test that identifies whether the whole model works. F-test is significance and therefore statistical applicability of the model is checked by looking at the p value as in the case with the t-statistic. (Minitab, 2011)
3.4.5 Descriptive statistics
Pie and bar charts were the main ways of displaying the empirical data. Moreover, in addition to regression analysis, descriptive statistics was employed while describing the basic features of the data in the research and to provide summary of the sample demographics and measures. (Ghauri & Grønhaug, 2010, pp. 154-156)
3.5
Methodological Issues
There were several methodological problems that occurred during the research. Different factors might have affected/influenced the results:
•
Literature review and, therefore, applied theories: it is possible that with the different theoretical background and additional or other literature sources the research and drawn conclusions could be vary. Authors tried to search for the most relevant; reliable and up-todate publications and documents within the scope of the research while doing literature review. To achieve that research parameters as well as 'key words' for informational retrieval have been identified and implemented.
•
Survey: if, for example, the survey questions were constructed differently or changed in general, collected data could have been different and obtained results might have been different. However, the authors attempted to construct the research in such a way, so that to receive the most precise and only possible information, and avoid biases. It was done by closely relating and basing survey development on the created theoretical framework. Moreover, the survey was pre-tested on a small group of authors' friends in order to make
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sure that language is simple, respectful and clear; correct terminology is used and overall survey presentation is attractive. Furthermore, such factors as respondents' random or possible wrong answers have been taken into account. To attempt to eliminate this kind of biases authors collected more survey that have required, 397 fully complete questionnaires instead of 384 have been gathered.
•
The sample itself could be criticized since respondents have been not chosen randomly. Even though, authors attempted to collect various sample by spreading the survey in three Swedish cities - Västerås, Märsta and Stockholm. Moreover, Stockholm is a capital of Sweden and holds one of only four country casinos, therefore it was assumed that people who are visiting the casino are most likely not only Stockholm residents, but also came to gamble and participate in the Poker Tournaments from different parts of the country.
•
Statistical problems, such as connected with regression analysis. Authors made sure to verify the assumptions of the regression analysis as well as to check various models in order to find the best fit of data and variables. Moreover, none of the other statistical techniques for data analysis besides descriptive statistics and regression analysis have been implemented since those were considered to be enough in order to answer the research question.
3.6
Validity and Reliability
The design quality of each research could be reviewed and criticized since it is supposed to represent a logical set of statements and arguments. Several criteria of the research merit attention while creating the conceptual framework, gathering and analyzing the empirical data. (Ghauri & Grønhaug, 2010, p. 79; Fisher, 2007, pp. 290-294) The information provided in the research should be meaningful, which is a focus of validity. Concepts and theories employed in particular research represent research material; moreover, conclusions and interpretations of the results were drawn carefully and logically from the research empirical data together with corresponding theories and models. Appropriate research technique such as survey with representative for the overall population sample was employed, so that readers and authors were sure that results and conclusions reliably and fairly represent subject being explored. (Fisher, 2007, pp. 294-295) In order to improve measurements in the research and examine potential relationships between variables (hours spent playing poker online; emotional motivation; material motivation; accessibility and atmosphere) authors pursued the following steps suggested by Ghauri & Grønhaug, (2010, pp. 8485). First in introduction, the problem that there exists a research gap in the female motivation to gamble online, in particular play online poker, has been explained and stated. From the problem, the research question has been developed. It was decided to investigate the problem by means of quantitative research, specifically by developing hypotheses and testing them with data collected
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from the survey with help of regression analysis and descriptive statistics. Four constructs/factors have been defined and survey has been designed to be closely connected with those constructs. Therefore, authors were sure that they have collected just needed information strongly related to the field of the interest. There are three types of validity: construct, internal and external and certain tactics to improve them. For current research, since it employs questionnaire as a research technique, the construct or measurement validity is of great importance. It deals with the constructs and focuses on issue whether those constructs in fact measure what they are said to measure. In other words, researchers have to be sure that they measure the right thing. Current study aims to measure four main constructs (factors) - emotional motivation, material motivation, accessibility and atmosphere. In order to make sure that those factors are measured correctly and accurately, authors asked external public to asses if those constructs correspond to what was intended to be measured. A pre-test of the survey have been done on five volunteer respondents and slight changes in the survey have been made to improve construct validity. (Ghauri& Grønhaug, 2010, pp. 81-82; Fisher, 2007, p. 295) Internal validity faces the concern about the existence of the casual relationships between various variables. To be able to confirm a casual relationship between four factors (constructs) and the dependant variable (hours spend playing poker), authors made sure to check assumptions of the simple and multiple regressions (see Appendix D) and, what is more important, proved the statistical significance of the overall model (p-values are less than 0.05). The statistical significance and applicability of all tested models means that there is an explanatory power and a good fit among variables. (Ghauri& Grønhaug, 2010, p. 83) External validity deals with generalization of the findings. The sample size for the survey (397 respondents) is representative for population within chosen, limited geographical area (Sweden). Moreover, simple probability sampling procedures have been applied. (Ghauri& Grønhaug, 2010, p. 84; Fisher, 2007, pp. 297-298) The main idea of reliability is to minimize the errors and biases and provide the stability of measures in the research. Any other researcher should be able to get the same results if he/she followed the same method and if he/she applied the same procedures as original authors. To make that possible, authors of the study documented the steps that they followed during the research process. The research protocol was not created, but authors were clear on all the stages of the research process, which were presented in the foregoing parts. (Ghauri& Grønhaug, 2010, p. 79)
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4. EMPIRICAL DATA
Chapter four represents the empirical data collected from the survey with 397 respondents. Data is presented by means of pie and bar charts and was grouped first according to the motivation factors - emotional, atmosphere, accessibility and material and the rest of the questions were presented separately.
4.1
Emotional Motivation
Figure 8 reveals results for the emotional motives of women playing online poker. Questions 2, 3 and 10 which were the likert-scales aimed to measure intrinsic motivation behind the reason why respondents play online poker for money:
• • •
Question 2 - Because it allows me to enjoy myself enormously. Question 3 - Because it is exciting to play for money. Question 10 - Because when I play I feel thrill and adrenaline.
Emotional Motivation
70 126137 Question 2 4 18 42 Corresponds exactly(7) 60 134 9 Question 3 3 19 42 64 Question 10 4 0 16 44 13 135 134 Corresponds a lot(6) Corresponds a lot(5) Corresponds moderately(4) Corresponds a little(3) Corresponds a little(2) Does not correspond at all(1) 50 100 150
Number Of Respondents
Figure 8: Emotional Motivation
Majority of respondents (approximately 130 people for each question and category) for all three questions indicated that such emotions as 'excitement', 'enjoyment' and 'thrill and adrenaline' correspond a lot (5,6) to why do they play online poker. 'Corresponds exactly' (7) was the third popular answer among respondents for all three likert-scales - 70, 60, 64 women consequently. 'Corresponds moderately' (4) was the next accepted category - around 40 people for each question
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chose (4). 'Corresponds a little' got the least answers among 397 respondents - around 20 women ticked (3) and 4 respondents - (2). 'Does not correspond at all' (1) was not chosen by any respondents.
4.2
Atmosphere
Figure 9 shows respondents' opinion towards atmosphere being reason for women to play poker online. Questions 4, 7 and 13 which were also likert-scales aimed to measure intrinsic motivation behind respondents playing online poker for money:
• • •
Question 4 - Because the atmosphere of the game is relaxed. Question 7 - Because I don't want to reveal my identity (like in table poker). Question 13 - Because I feel more self-confident in the familiar surrounding.
Atmosphere
16 Question 4 5 17 Question 7 5 18 Question 13 3 0 20 34 40 60 434 8 55 69 107 1 11 80 100 120 Number Of Respondents 140 31 74 677 7 67 127 Corresponds exactly(7) Corresponds a lot(6) 108 109 Corresponds a lot(5) Corresponds moderately(4) Corresponds a little(3) Corresponds a little(2) Does not correspond at all(1)
Figure 9: Atmosphere
'Corresponds moderately' (4) was the most chosen answer for how atmosphere influences respondents to play online poker for money for all three questions (127, 109, 111 respondents). 'Correspond a lot' (5, 6) was the second popular category, while 'Corresponds a little' (2.3) the third: Question 4 received 77 (5)th ; 74 (6)th; 67 (3)th and 31 (2) th; Question 7 received 108 (5)th ; 67 (6)th; 48 (3)th and 43 (2) th ; Question 13 received 107 (5)th ; 55 (6)th; 69 (3)th and 34 (2) th. The two extreme categories 'Corresponds exactly' (7) and 'Does not correspond at all' (1) got the least of respondents answers - 16, 17, 18 and 5, 5, 3 consequently.
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4.3
Accessibility
Respondents' answers on how accessibility influences them to play online poker are revealed in Figure 10. Likert-scales 5, 9 and 11 which were designed to measure extrinsic motivation behind respondents playing online poker for money:
• • •
Question 5 - Because I can play at any place with Internet access. Question 9 - Because I can play at any time I want. Question 11 - Because it is convenient to play
Accessibility
40 Question 5 0 Question 9 0 Question 11 2 0 16 20 40 19 35 47 17 44 44 53 93 90 101 Corresponds exactly(7) 89 89 Corresponds a lot(6) 112 Corresponds a lot(5) Corresponds moderately(4) 95 1 01 0 7 1 60 80 100 120 Corresponds a little(3) Corresponds a little(2) Does not correspond at all(1)
Number Of Respondents
Figure 10: Accessibility
'Corresponds a lot' (5) was the most preferred category - 101, 112, 107 respondents. At the same time 'Corresponds a lot' (6) with 'Corresponds moderately' (4) and 'Corresponds exactly' (7) with 'Corresponds a little' (3) had nearly the same amount of answers: for the first pair the average amount for all three questions was 95, while for the second approximately 40. 'Does not correspond at all' (1) category was chosen only by 2 respondents for question 11.
4.4
Material Motivation
Answers about how material motivation corresponds to why women pay online poker are displayed in Figure 11 Likert-scales 6, 8 and 12 which were designed to measure extrinsic motivation behind respondents playing online poker for money:
•
Question 6 - Because it allows me to make money quickly and easily.
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• •
Question 8 - Because it allows me to make a lot of money. Question 12 - Because I feel a need of more money.
Material Motivation
15 Question 6 23 19 Question 8 28 10 Question 12 27 0 20 40 67 1 7 57 64 60 80 100 120 101 Corresponds a little(2) Does not correspond at all(1) 61 61 48 53 73 70 102 Corresponds exactly(7) Corresponds a lot(6) 77 74 90 Corresponds a lot(5) Corresponds moderately(4) Corresponds a little(3)
Number Of Respondents
Figure 11: Material Motivation
'Corresponds moderately' (4) received majority of the answers for all three likert-scales (102, 90, 101 respondents). 'Corresponds a lot' (5) was the second most chosen with 73, 77 and 71 respondents. "Corresponds a little' (3) was the third popular answer for questions 6 -70 respondents and question 8 74 respondents, while for question 12 'Corresponds a lot' (6) was third with 67 respondents and "Corresponds a little' (3) had 64 women. Corresponds a lot' (6) was chosen by 53 women for question 6 and by 48 for question 8. 'Corresponds a little' (2) received 61 answers for question 6 and question 8 and 57 fro question 12. 'Does not correspond at all' (1) was on the last but one choice with 23, 27 and 27 respondents and on 'Corresponds exactly' (7) had 15, 19 and 10 answers.
4.5
Hours Spend Playing Online Poker
Question 14 had an open-answer nature where respondents were asked to estimate how many hours per month do they play online poker. The spread of answers was between 2 and 150 hours. The most popular written amounts of numbers included 5 hours - 40 respondents; 10 hours - 39 respondents; 15 hours - 52 respondents; 20 hours - 43 respondents and 30 hours - 32 respondents. 23 women said that they play online poker for about 25 hours per month; 21 women - 35 hours per month; 45 and 50 hours have been written down by 25 and 22 respondents respectively; 14 women spend 40 hours in front of the computer playing poker and 13 respondents - 60 hours. The rest of the hours
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categories include less than 10 respondents per each, e. g. 3 hours - 8 respondents; 90 hours - 5 respondents, etc. Figure 12 shows all the respondents answers.
Hours Playing Online Poker
60 52 50 40 Number of Respondents 30 20 10 1 0 2 3 4 5 6 7 8 9 1 1 0 1 2 1 3 1 5 1 6 1 7 2 8 2 0 3 5 3 0 3 4 3 5 4 7 4 0 5 5 5 0 6 5 6 0 6 5 7 8 7 0 8 5 8 0 9 5 9 0 10 5 12 0 13 0 15 0 0 Number of Hours (per month) Figure 12: Hours Spend Playing Poker 8 1 1 6 11 11 211 2 2 40 43 39 32 23 21 25 22 14 5 13 7 1 8 242 43111 5
4.6
Occupation
Question 14 was aimed to measure the occupation of the respondents. 139 (35%) out of al 397 women were a full-time employees, while 132 (33%) were students. 81(21%) people were working part-time and the minority - 45 (11%) of respondents were staying at home.
Occupation
45 11%
132 33 %
139 35%
Full-time employee Half-time employee Student Staying at home
81 21% Figure 13: Occupation
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4.7
Educational Level
Figure 14 shows results of Question 17 which measured the education level of respondents. In total 4 women chose two of answers categories 'none of the above' and 'high-school diploma' -3 of which said that they had only a high-school diploma and 1 ticked none of the provided above answers. 264 (67%) out of 397 women had completed university education and 129 (32%) were in the process of achieving one.
1 0 %
3 1 %
Education Level
High-school diploma 129 32 % 264 67 % University degree/diploma In process of achieving University degree None of the above
Figure 14: Educational Level
4.8
Relationship Status and Children
Figures 15 display the relationship status and presence of children among 397 female respondents. Majority of respondents were single - 275(69%) and without children - 324 (59%). 122(31%) women were either married or cohabiting and 163 (41%) had children.
Relationship Status
122 31 % Single Married/Cohabiting 275 69 %
Children
163 41 % Yes No
234 59 %
Figure 15: Relationship Status and Children
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4.9
Age
Figure 16 below presents the age of the respondents that have filled in the survey. The age categories are presented on the vertical axis and vary between 19 and 63 years old. Number of respondents in each age category is shown on the vertical axis.
Age
63 years old 57 years old 51 years old 45 years old 44 years old 42 years old 41 years old 40 years old 39 years old 38 years old 37 years old 35 years old 34 years old 33 years old 32 years old 31 years old 30 years old 29 years old 27 years old 26 years old 25 years old 24 years old 22 years old 21 years old 19 years old
1 4 2 23 19 8 12 6 13 39 15 36 28 25 16 17 34 17 21 8 16 14 13 7 3 0 5 10 15 20 25 30 35 40 45
Number of Respondents
Figure 16: Age
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5. ANALYSIS
The fifth chapter is the analysis of empirical data with the use of presented theoretical framework
5.1
Demographic characteristics
The research has been carried out among 397 respondents. All respondents were women who play online poker for money. Due to the fact that service - poker game was offered to the customers by means of Internet, it became more standardized for most of the users. Since Swedish gamblers also have an opportunity to play on other international web-sites, the motivations and characteristics of the potential profitable customer segment among Swedish women are of the interest not only for the Swedish monopoly provider- Svenska Spel but also for the international providers. (Barnes et al., 2007; Donthu & Garcia, 1999). Survey revealed the general bases/segments of the women engaged into the research. From the beginning it was assumed to conduct the study of female players in Sweden, therefore geographic segment was women who play online poker in Sweden. Pie charts and histograms presented as empirical data show the certain demographic characteristics that illustrate the average female online poker player in Sweden. The importance of understanding not only traditional customers, but also the general demographic characteristics of those who are involved into online activities have been noted by Kau et al (2003). Knowing better target customers' personal characteristics is a root to predict and assess the possible motivations and overall behavior. According to the received answers from the 397 Swedish women playing poker online, the mode of the hours spent as the proxy of the propensity to be involved into the game during the period of one month was 15 (n = 52) hours. The other popular answers were 20 (n = 43), 5 (n = 40), 10 (n = 39), and 30 (n = 32). Consequently the average amount of hours out of all responses was estimated to be 30.3. That is nearly 1 hour per day or 7 hours per week indicating the daily/frequent involvement into the game. Age as the bases for demographic segmentation disclosed that the majority of women who play online poker were above 30 years old (30, 35, 38 years old), where the age spread was between 19 and 63 years old. This finding is comparable with the previous findings in various geographic markets where the age of the potential female online poker players was estimated to be in a rank of 32-50 years old (Davis & Avery, 2004; LaPlante et al. 2009; Wood & Griffiths, 2008) Second demographic variable that has been investigated was occupation. Main fraction of respondents (56%) was employed either part- or full- time, where 33% have been studying and 11% staying at home. This numbers indicate that women that play poker online in Sweden mainly belong to the highly active and engaged segment such as work or studying. The similar level of occupation
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was found by Davis & Avery (2004) and Corney & Davis (2010) in their investigations of the US and UK markets respectively, where the majority of female respondents stated being professionals, clerical staff or managers. When it comes to the educational level, it was previously found that the major fraction of the online poker players, both men and women, have higher education or are in the process of achieving one (college, bachelor or master degree) stressing the importance of the higher level of intelligence required for the games of skills (Davis & Avery, 2004; Griffiths et al. 2010). In terms of educational segments, the dominating majority (67%) were women who have already completed university/college degree, while 32% were currently in the process of achieving high education. Swedish poker gamblers were mostly high-educated women. Relationship status and presence of children has been analyzed in tandem as the proxy of occupation with family activities and the role of family as a whole. In Sweden the main female group was found to be single predominantly (69% single/living alone vs. 31% married/co-habiting) and without children. Though the difference between those with children and without was not significantly large, i.e. 18%. These findings are in variance with the previous findings of Corney & Davis (2010) and Davis & Avery (2004), where the majority of women involved into the online gambling activities of all kinds are either married or cohabiting. Now, after the hypothetical target segment was figured out by means of demographic characteristics investigation (i.e. woman aged 30-40, single, predominately without children, either working or studying and spending around 30.3 hours per month on online poker for money) it is time for revealing the most important aspect for marketers- behavior, i.e. motivations to play poker online (Montgomery, 2008).
5.2
The Model
Both types of regressions, multiple and single (separately with each predictor variable) were conducted in attempt to find the better fit of the data. The analysis revealed that all four investigated explanatory variables, i.e. emotional context, accessibility, atmosphere and monetary motives, do play a significant role in forming the online poker playing women's behavior and therefore must be entered into one multiple model. The correlation coefficient R2 was found to be more than twice higher in case of the multiple regression model. (see Table 1) In addition, the R2 adj. coefficient was found to be smaller but nearly the same as the simple R2 coefficient. This supported the statistical significance and applicability of the model, suggesting that there is a good fit between variables. The other goodness-of-fit test, F- test, also indicated the significance of the model and the overall fit with the probability value p equal to zero, which consequently rejected the H0 of the absence of the significant relations of the dependent and the predictor factors.
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Nevertheless, it was also obvious that though the multiple model provides more precise estimates and data fit it still misses to explain nearly 40% of propensity of women to play poker online which can be explained by the restricted choice of explanatory variables to test the hypotheses due to theoretical gap in the field of investigation and various types of motivations among Swedish women.
Time = - 67,5 + 7,44 Emotions + 2,74 Atmosphere + 3,64 Access + 7,06 Money T-statistics F-test em 128,48* Time vs Emotions Time vs Atmosphere Time vs Access Time vs Money 7,66* At m 3,30* acc 4,06* mon 13,26* R2 and/ R2 adj. (%) 56,7/ 56,3 ? coefficient em At m acc mon
7,44 2,74 3,64 7,06
157,51* 12,55*
-
-
-
28,5/28,3
12,7
-
-
-
113,28* 149,63* 143,24*
-
10,64* -
12,23* -
11,97*
22,3/22,1 27,5/27,3 26,6/26,4
-
8,82 -
9,86 -
8,19
(**) [*] the significance at the (5%) [1%] level
Table 1: Summary Table of Regression Analysis (own)
5.3
The Hypotheses Testing
As it was discussed in the theoretical background the consumers' (in this paper consumers are Swedish women playing online poker) behavior is driven by two broad groups of motivations, extrinsic and intrinsic. Digging deeper into the online poker world and the motivations that drive people to gamble online, it was found that theory suggests four main motives to play online poker that could be applicable explanations why Swedish women play online poker. According to the previous studies, women tend to be more driven by their emotions when making the decision to gamble online. Davis & Corney (2010) stressed out the importance of the emotional relief seeking among women when they decided to gamble online. Lee et al. (2007) found out that excitement seeking as the emotional driver was predominant among gambling women. Relying on those researches and findings the two hypotheses concerning emotional motivations to play online poker among Swedish people were formed and tested. First hypothesis stated the positive relationship between propensity to play online poker and the emotional motivation. The last, fifth
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hypothesis, emphasized the role of emotions as the dominant trigger to play poker online among Swedish women. H1: According the regression analysis output there was a positive statistically significant relationship between emotional motives and the level of involvement into the online poker games. The t-statistic (7,66) was significantly positively related with the p value equal to zero and?coefficient with the plus sign. H5: The fifth hypothesis was also accepted. With the largest? coefficient, 7.44, the emotional motivation was proved to be the most important trigger among Swedish people to play online poker. Moreover, according to the answers presented by choice of likert-scale numbers, statements aimed to discover the emotional motivation received the largest amount of the strongest agreements, i.e. '7' in the scale of "corresponds a lot". The second hypothesis tested in this study stressed out the role of material motivation to play online poker among Swedish women. Nearly every scientific research of the gambling/online gambling propensity stressed out the role of material motivation. (Drozd, 2010, Mowen et. Al, 2009, Hong & Jung, 2004) The only studies that investigated the women's propensity to gamble or play poker online minimized the role of money when making the decision to gamble. (Lee et al. 2007, Corney&Davis, 2010) H2: According to the findings in this precise analysis, the material motivation does positively correlates to the propensity to play online poker among Swedish women with the ? coefficient second large, 7,06 and the t-statistic (13,26) with the zero probability that this predictor might be insignificant. The next hypothesis tested the positive relationship between the accessibility and the propensity to play online poker. Layton & Worthington stressed the importance of the convenience and accessibility when it comes to the gambling already in 1999 (Layton& Worthinngton, 1999) Further, Corney & Davis (2010) and Wood et al. (2007) found that accessibility factor was mentioned as the dominant motive to gamble online by nearly every questioned woman. The convenience brought by the internet for the gamblers was also discussed by Wood &Griffiths (2008). H3: Thus the hypothesis of the positive impact of the easy and convenient online poker access was tested in this research. The results approved the theoretical background: the accessibility of the online poker was found to be in a positive relationship with the level of involvement into the game among Swedish women with the? coefficient equal to 3,64 and the p value of the t-statistic (4,06) equal to zero.
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The last major motivation suggested by the previous research was found to be the atmosphere. The sense of privacy and self-confidence in the familiar surroundings were proposed to trigger internally people's propensity to gamble and therefore have the positive relationship. (Corney & Davis, 2010; Wood & Griffiths, 2008; Wood et al., 2007) H4: As in all the previous hypothesis testing cases, the acceptance of the hypothesis was approved by this analysis. The atmosphere motivator was found the be statistically significant and positively related to the dependent variable with the? coefficient equal to 2,74 and t-statistic (3,30) with the p value of 0,001. After all, the t-statistics were found to be significant at 1% level stressing the importance of all the four motivational aggregates in the model. The analysis also indicated the set of outliers, i.e. the unusual observation that are supposed to influence the statistical significance of the results. But, as it was discussed, the statistical significance of the whole model as well as each coefficient separately was proved and therefore those outliers were not supposed to significantly affect the model, which once again approved the positive results of this analysis. The complete hypothesized model is summarized and presented in the figure 17 below, it shows the relationship between variables used in constructing hypotheses.
Figure 17: The Hypothesized Model (own)
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6. CONCLUSION AND DISSCUSSION
Last chapter summarizes the research results. In addition it presents the discussion of those results from different perspectives and aspects Current research was focused on Swedish market that is characterized by strict monopoly on landbased and online gambling as well as relatively recent introduction of the online poker activity (Svenska Spel, 2011; Young & Todd, 2008; Jonsson & Rönnberg, 2009, p.300). Traditionally women's role in online gambling and precisely online poker have been underestimated and uninvestigated (Manzin & Biloslavo, 2008; LaBrie et al., 2007; Mowen et al., 2009; Griffiths &Barnes, 2008; Lee et al., 2007; Corney & Davis, 2010). In Sweden women account for the significant fraction of the overall eligible (18+) for gambling population, who also participate in online poker (SCB, 2010). Therefore, it was of a vast interest to understand what drives those women to get involved into online poker world and bet their money. The research attempted to understand Swedish women's motivation to play online poker with the help of existing theoretical models and previous studies by means of hypotheses testing through multiple and simple regression analyses. The results showed that emotional and material motivations as well as accessibility and atmosphere factors do have the negligible direct impact on the Swedish women's level of involvement into the online poker for real money. The deep investigation of the existing studies (gambling, online gambling, online poker and women in the gambling world) and theoretical models (extrinsic/extrinsic motivations, 3M model, 5-factor model) was conducted as the inspirational base for testing hypotheses on the Swedish females' sample (Ryan & Derci, 2000; Mowen et al., 2009; Lee et al., 2007). The study attempted to find out whether the chosen motivation that have been previously investigated and theoretically suggested are applicable in case of women in Sweden who play poker online for money. According to previous studies and findings, the most popular motivations to gamble online or play poker by means of internet among both men and women were: - Emotional motivation (i.e. excitement, enjoyment, thrill and adrenaline seeking) - Material motivation (i.e. to win money) - Accessibility (i.e. ease and comfort of access by means of internet) - Atmosphere (i.e. familiar surrounding and privacy while gambling/playing poker with own PC) If considering the above triggers to gamble from the theoretical and psychological perspectives, then those can be divided into two groups - extrinsic and intrinsic motivations. Where emotional motives and atmosphere are the internal/intrinsic factors, while money seeking and accessibilityexternal/extrinsic ones (Ryan & Derci, 200).
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The analysis revealed that reality within the Swedish market and female segment is comparable to what was found previously by various authors within different geographic and demographic markets. Given, the previous findings and results achieved in this concrete research, one can state that intrinsic, i.e. emotional, motivations are fundamental factors that form Swedish women's behavior when it comes to the decision to play poker online. This probably comes from the psychological distinguishing characteristics of women, where women tend to be more often driven by their emotional state when making decisions. The second in line was material motivation such as making money easily and quickly or general need of money. The third factor was accessibility of the game, meaning that Swedish respondents appreciated that it is convenient to play online and moreover they can gamble at any time at any place. And the last one was atmosphere of the game and its surroundings. Even though according to the results it was not the most important reason to play poker online, feeling of the self-confidence in the familiar surrounding, relaxed atmosphere and no need to reveal the true identity are still considered to be significant motives for Swedish women propensity to play the game. As stated above the material motivation was on the second place, which also stresses the significance of this factor when making the decision to dedicate time on the online poker among Swedish women. Obviously, when playing for money, material factor can't be neglected, otherwise why even to choose this type of game. The main aspect here is placement of the priorities on both factors, emotional and material, which comes from the gender differences and demographic characteristics. The first issue (i.e. gender differences) was previously investigated and it was found that when it comes to male samples, the weights on the emotional and material motivations to gamble/play poker online were placed vice versa (i.e. first place - material trigger, second - the emotional motivations). The other demographic characteristics such as age, occupation, education and family status do also have the impact on the motives to play poker online. (Lee et al., 2007; Lloyd et al., 2010; Wood & Griffiths, 2008) This study did not attempt to investigate cross-correlations of the demographic variables and various motives as it would have lead to several conclusions, additional use of theory and go beyond one research question. However, as it was stated at the beginning of this paper, the attempt was to investigate the potential target segment for the online poker providers and mainly see the motivations of the particular sample. For the marketing and costs reducing purposes all the information is essential in order to make the efficient campaign and attract as much customers as possible. The quantitative researches are aimed to receive vast amount of responses in order to make the aggregation after all (Ghauri & Grønhaug, 2010, p. 138). The same intention was in this particular research - to understand the motivations that drive this aggregated potential customer base (consisting of Swedish women) to play online poker for money. As it turned out, the collective image of the Swedish woman who is prone to play poker online is- woman who is around 35, with
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high education and professionally occupied, without serious relationships and mainly without children and she is more driven by emotional motivations when deciding to play poker online for money. Given the results of the Swedish females investigation in this study paper and the previous findings about online gambling overall, one can indicate that those go in line and very much comparable among all the gambling services all over the world. This indicates that one can generalize all the online gambling activities when considering the motivations that make females to gamble in every part of the world where this activity is legalized. However, from the statistical perspective, the tested model, that incorporated the four motivational factors, was found to be incomplete, meaning that there probably are some other important factors that make Swedish women to play poker online but were not taken into consideration in this particular research. The other explanation might be the aggregation of the likert-scale answers that represent one motivational group. As each group consisted of three statements, probably this limited the spread of choices and consequently influenced the whole model. Moreover, it is accepted that there might be some portion of bias in the results due to the nature of dependent variable - amount of hours dedicated to the game. It is hardly possible to give the exact number of hours per month. So, the predicted factor is only nearly correct from the statistical perspective, though precise enough for this research's purpose. As it was already mentioned before, this study paper looks at the online poker and the whole gambling as at the huge business where providers should attract, acquire and retain as many customers as possible in order to generate profits (Baines et al., 2008, pp. 246-251; Barnes et al., 2007; Kau et al., 2003). Therefore, the findings in this paper can be applicable for the online poker providers both within and outside Sweden as Swedish people are actively using the international websites due to strict monopolistic regulations in the country. As, nowadays online poker is becoming more and more popular among women segment whole over the world and Sweden is not an exception, it is necessary for providers to distinguish the main motivations among various demographic groups. From the psychological point of view, the results of this paper can be useful for the medical institutions that fight against such issues as problem- and pathological gambling. Knowing the potential player among women can contribute to the existing investigations of the roots of the addictive behavior. This knowledge is essential when attempting to come up with the means to prevent or cure the addiction. For further researches Continuing with the problem-gambling, the further research of the Swedish female poker players can be concentrated around the pathological behavior, i.e. addiction that makes people lose all their
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money and estate being unable to stop without the outside help. Probably in this research there was a portion of problem-gamblers who answered the survey. However, as that was not of the interest and purpose to investigate the problem-gambling patterns, this study neglected this fact as it was out of the scope of the particular research. Moreover, the further studies can evaluate each motivation separately and show cross-correlations with the demographic factors which will lead to several additional conclusions in this particular field of study. Additionally, other researchers could investigate other gambling activities, besides online poker as well as try to identify other motivations and variables that influence gambling behavior and motivate people to gamble, since model in current research resulted to be incomplete.
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REFERENCES
Baines, P., Fill, C., Page, K. (2008) Marketing, Oxford University Press Barnes, S. T., Bauer, H. H., Neumann, M. M., Huber, F. (2007) "Segmenting cyberspace: a customer typology for the internet", European Journal of Marketing, 41(1/2), pp.71 - 93 Barrow, M. (1996) Statistics for Economics, Accounting and Business Studies (2d ed) LONGMAN: London and New-York Bayton J.A., (1958) Motivation, cognition, learning - basic factors in consumer behavior. Journal of Marketing 22(3) Carey A.E., Carey K.R. (1984) Gambling. Reference Services Review, pp.49-61 Corney R., Davis J. (2010) The attractions and risks of internet gambling for women: A qualitative study. Journal of Gambling Issues 24, pp. 121-139 Cottrell, A. (2003) Regression Analysis: Basic concepts Davis, D. R. & Avery, L. (2004) Women Who Have Taken Their Lives Back From Compulsive Gambling: Results from an online survey. Journal of Social Work Practice in the Addictions 4(1), pp. 61-80 Davis, D. R., Avery, L.(2004) Women who have taken their lives back from compulsive gambling: results from an online survey. Journal of Social Work Practice in the Addictions, 4(1), pp.61-79 Dewar L. (2001) Regulating Internet gambling: the net tightens on online casinos and bookmakers. Asib Proceedings, 53(9), pp. 353-367 Donthu, N., Garcia, A. (1999) The internet shopper. Journal of Advertising Research, 39(3), pp. 5258. Drozd A. (2010) The future of digital gambling. Business insights Fisher, C. (2007) Researching and Writing a Dissertation for Business Students. (2th ed) Pearson Education Limited Ghauri, P., Gronhaug, K. (2010) Research Methods in Business Studies (4th Edition) Pearson Education Limited Griffiths, M. D. (2003). Internet gambling: CyberPsychology & Behavior, 6, pp. 557-568. Griffiths, M. D., Barnes, A. (2008). Internet gambling: An online empirical study among student gamblers. International Journal of Mental Health and Addiction, 6, pp. 194-204. Issues, concerns, and recommendations.
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Griffiths, M. D., Parke, A., Wood, R. T. A., & Parke, J. (2006). Internet gambling: An overview of psychosocial impacts. Gaming Research and Review Journal, 27(1), pp. 27-39. Griffiths, M. D., Parke, A., Wood, R. T. A., & Parke, J. (2010). Online Poker Gambling in University Students: Further Findings from an Online Survey. International Journal of Mental Health and Addiction , 8, pp. 82-89 Griffiths, M. D., Wardle, J., Orford J., Sproston, K., & Erens, B. (2009). Socio-demographic correlates of internet gambling: findings from the 2007 British Gambling Prevalence Survey. CyberPsychology and Behavior. Griffiths, M. et al (2010) Online Poker Gambling in University students: Further Findings from an Online Survey. Int J Health Addiction 8, pp. 82-89 Hong S.-K., Jang H. (2004) Segmentation of early casino markets: an exploratory study. Tourism Management 25, pp. 801-805 Jonsson, J., Rönnberg, S. (2009). Gambling in Sweden. In G. Meyer, T. Hayer & M.D. Griffiths (Eds.), Problem Gaming in Europe: Challenges, Prevention, and Interventions. New York: Springer. Kau, A.K., Tang, Y.E., Ghose, S. (2003) Typology of online shoppers. Journal of consumer Marketing, Vol. 20 No. 2, pp. 139-56. King, D., Delfabbro, P., Griffiths, M. (2010) The Convergence of Gambling and Digital Media: Implications for Gambling in Young People. Journal of Gambling Studies, 26/2, pp. 175-187 Kurtz, D. L., MacKenzie, H. F., Kim Snow, K. (2009) Contemporary Marketing, Cengage Learning LaPlante, D.A. , Kleschinskyb, J. H., LaBriea, R. A., Nelsona, S. E., Shaffera, H. J. (2009) Sitting at the virtual poker table: A prospective epidemiological study of actual Internet poker gambling behavior. Computers in Human Behavior Layton, A. & Worthington, A. (1999) The impact of socio-economic factors on gambling expenditure. International Journal of Social Economics 26 (1/2/3), pp. 430-440 Lee H.P., Chae P.K., Lee H.S., Kim Y.K. (2007) The five- factor gambling motivation model. Psychiatry Research 150(1), pp. 21-32 Lloyd, J., Doll, H., Hawton, K., Dutton, W.H., Geddes, J. R. Goodwin, G.M., Rogers, R.D. (2010) Internet Gamblers: A Latent Class Analysis of Their Behaviours and Health Experiences. Journal Of Gambling Studies, 26(3), pp. 387-39 Manzin, M., Biloslavo, R. (2008) Online Gambling: Today's Possibilities and Tomorrow's Opportunities. Managing Global Transitions 6 (1), pp. 95-110
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Meyer, G., Hayer, T., & Griffiths, M. D. (2009). Problem gaming in Europe: Challenges, prevention, and interventions. New York: Springer. Miller, T.E. (1996), "Segmenting the internet", American Demographics, 18(7), pp. 48-52. Monaghan, S. MacCallum, B. (2006) Internet and Wireless Gambling - A Current Profile . Australasian Gaming Council Montgomery, J. (2008) The role that personality and motivation play in consumer behavior: a case study on HSBC. Business intelligence Journal. Case study 3 Mowen J.C., Fang, X., Scott, K. (2009) A hierarchical model approach for identifying the trait antecedents of general gambling propensity and of four gambling-related genres. Journal of Business Research, 62, pp. 1262-1268 Perse, L. Bellringer, M., Abbott, M. (2005) Literature review to inform social marketing objectives and approaches, and behavior change indicators, to prevent and minimize gambling harm. Gambling research center Romild U. (2009) SWELOGS- a longitudinal study on Gambling and Health. Swedish National Institute of Public Health Ryan R.M., Deci E.L. (2000) Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemporary Educational Psychology 25, pp.54-67 Saunders, M. N. K., Thornhill, A., Lewis, P. (2009) Research Methods for Business Students (5th Edition) Pearson Education Limited Wiebe J. (2008) Internet Gambling: Strategies to Recruit and Retain Gamblers. Ontario Problem Gambling Research Centre Winship C., Mare R.D (1984) Regression models with ordinal variables. American Sociological Review 49, pp. 512-525 Wood, R. T. A., Griffiths, M. D., & Parke, J. (2007). The acquisition, development, and maintenance of online poker playing in a student sample. Cyberpsychology and Behavior, 10, pp. 354361. Wood, R.T, Williams R.J. (2009) Internet gambling: Prevalence, Patterns, Problems, And Policy Options. Ontario Problem Gambling Research Centre Wood, R.T. et al. (2007) Why do Internet gamblers prefer online versus land-based venues? Some preliminary findings and implications. Journal of Gambling, 20, pp. 235-252
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Wood, R.T.A., Griffiths M. D (2008) Why Swedish people play online poker and factors that can increase or decrease trust in Web sites: A qualitative investigation. Journal of Gambling Issues 21, pp. 80-97 Young, R., Todd, J. (2008) ONLINE GAMBLING: focusing on integrity and a code of conduct for gambling. Policy Department Economic and Scientific Policy. European Parliament's committee on Internal Market and Consumer Protection (IMCO)
Internet Sources
ATG the Company (2011) Retrieved on 16th of April, 2011 from thehttp://www02.atg.se/cm/english/aboutatg Christian Capital Advisory Ltd. (2011) Retrieved on 10th of April, 2011 fromhttp://www.ccai.com/primary navigation/online data store/internet_gambling_data.htm G-.Martin K. (2009) Can likert-scale data ever be continuous? Retrieved on the 13th of April, 2011 from:http://www.ideamarketers.com/?Can_Likert_Scale_Data_ever_be_Continuous&articleid=424733 High, R. (n/d) Date coding issues with logistic regression. Retrieved on 13th of April from:http://rfd.uoregon.edu/files/rfd/StatisticalResources/est_logistic.txt Ialomiteanu, A., & Adlaf, E. (2001). Internet gambling among Ontario adults. Electronic Journal of Gambling, 5. Retrieved Aprril 21st, 2011 fromhttp://www.camh.net/egambling/issue5/research/ialomiteanu_adlaf_article.html Minitab. Retrieved 2nd of May, 2011 fromhttp://www.minitab.com/enSE/products/minitab/default.aspx Murray, B (2011) Online Poker Grew 7.1 Percent In 2010. Retrieved April 14th , 2011 fromhttp://www.cardplayer.com/poker-news/10494-online-poker-grew-7-1-percent-in-2010 Online Gambling Sites in Sweden (2011). Retrieved March 26th, 2011 fromhttp://gamingzion.com/sweden SCB (2010) Sweden's Population by sex and age on 31/12/2010. Retrieved 6th April, 2011 fromhttp://www.scb.se/Pages/TableAndChart____264373.aspx Svenska Spel (2011). Retrieved March 28th , 2011 fromhttp://svenskaspel.se/p4.aspx?pageid=527 Zupko A. (2010) Woman populating the online poker world. Retrieved March 31st , 2011 fromhttp://www.womanpokerplayer.com/pokernews/598-women-populating-the-online-pokerworld.html
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APPENDIX Appendix A - Estimating Sample Size
Margin of error Population
50 100 150 20 250 300 400 500 750 1000 2000 5000 10000 100000 1000000 10000000 5% 44 79 108 132 151 168 196 217 254 278 322 357 370 383 384 384 3% 48 91 132 168 203 234 291 340 440 516 696 879 964 1056 1066 1067 2% 49 96 141 185 226 267 343 414 571 706 1091 1622 1936 2345 2395 2400 1% 50 99 148 19 244 291 364 475 696 906 1655 3288 4899 8762 9513 9595
(Fisher, 2007, p. 190; Saunders et al., 2009, p. 219)
I|P age
Appendix B - Survey
"WHY DO YOU PLAY ONLINE POKER FOR MONEY?"
1. Do you play online poker?
? Yes ? No If you answered YES, then for each of the following statements, please circle the number that best represents the extent to which the statement corresponds to the reasons why you play poker online.
Does not correspond at all 1 2 3 Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly
4
5
6
7
For example, if the statement doesn't correspond at all, circle number 1; if it corresponds moderately, circle number 4; if it corresponds exactly, circle number 7. WHY DO YOU PLAY ONLINE POKER FOR MONEY? 2. Because it is exciting to play for money. 3. Because it allows me to enjoy myself enormously. 4. Because the atmosphere of the game is relaxed. 5. Because I can play at any place with Internet access. 6. Because it allows me to make money quickly and easily. 7. Because I don't want to reveal my identity (like in table poker). 8. Because it allows me to make a lot of money. 9. Because I can play at any time I want. 10. Because when I play I feel thrill and adrenaline. 11. Because it is convenient to play . 12. Because I feel a need of more money. 13. Because I feel more self-confident in the familiar surrounding. 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567 1234567
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14. How old are you? 15. How many hours per month do you spend playing poker online? Please, provide your own estimation For the following questions, please, choose one of the provided answers. 16. Your occupation is:
? Full-time employee ? Halftime employee ? Student ? Staying at home
17. Your education level is:
? High-school diploma ? University degree/diploma ? In process of achieving University degree ? None of the above
18. What is your relationship status?
? Single ? Married/Co-habiting
19. Do you have children?
? Yes ? No
~ THANK YOU FOR YOUR PARTICIPATION AND HELP ~
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Appendix C - Decode and Measurement for Each Survey Question
Question 1
Decode Yes No Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Aim to Measure
Question 2
Question 3
Question 4
Question 5
Question 6
Question 7
Question 8
Question 9
Question 10
Question 11
1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7 1 2,3 4 5,6 7
Intrinsic Motivations: Emotional motives
Intrinsic Motivations: Emotional motives
Intrinsic Motivations: Atmosphere
Extrinsic Motivations: Accessibility
Extrinsic Motivations: Material motives
Intrinsic Motivations: Atmosphere
Extrinsic Motivations: Material motives
Extrinsic Motivations: Accessibility
Intrinsic Motivations: Emotional motives
Extrinsic Motivations: Accessibility
IV | P a g e
Question 12 Does not correspond at all
Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Does not correspond at all Corresponds a little Corresponds moderately Corresponds a lot Corresponds exactly Respondents were asked to fill in a number themselves
Question 13
1 2,3 4 5,6 7 1 2,3 4 5,6 7
Extrinsic Motivations: Material motives
Intrinsic Motivations: Atmosphere
Question 14
Age of respondents Time spend playing poker online Occupation
Question 15 Respondents were asked to fill in a number themselves Question 16 Full-time employee
Half-time employee Student Staying at home High-school diploma University degree/diploma In process of achieving University degree None of the above Single Married/Co-habiting Yes No
Question 17
Level of Education
Question 18 Question 19
Relationship Status Existence of Children
V|Page
Appendix D - Homoscedasticity Tests and Residuals Analysis
Homoscedasticity Tests:
1. BoxPlot: Time versus Emotions
Boxplot of Time
160 140 120 100 Time 80 60 40 20 0 0 00 3 33 7 66 0 00 3 33 7 66 0 00 3 33 7 66 0 00 3 33 7 66 0 00 3 33 7 0 66 00
2 00 2,33 2,66 3,00 3,33 3,66 4,00 4,33 4,66 5,00 5,33 5,66 6,00 6,33 6,66 7,00 , Emotions
2. BoxPlot: Time versus Atmosphere
Boxplot of Time
160 140 120 100 Time 80 60 40 20 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 1 33 1,66 2,00 2,33 2,66 3,00 3,33 3,66 4,00 4,33 4,66 5,00 5,33 5,66 6,00 6,33 6,66 7,00 , A tmosphere 0
VI | P a g e
3. BoxPlot: Time versus Access
Boxplot of Time
160 140 120 100 Time 80 60 40 20 0 67 00 3 3 67 00 3 3 67 00 3 3 67 00 3 3 67 00 3 3 67 00
1, 6 2 66 ,000 ,333 ,666 ,000 ,333 ,666 ,000 ,333 ,666 ,000 ,333 ,666 ,000 ,333 ,666 ,000 2 2 3 3 3 4 4 4 5 A cc e s s 5 5 6 6 6 7
4. BoxPlot: Time versus Money
Boxplot of Time
Time 160 140 120 100 80 60 40 20 0 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 0 3 7 00 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 33 66 00 1 00 1,33 1,66 2,00 2,33 2,66 3,00 3,33 3,66 4,00 4,33 4,66 5,00 5,33 5,66 6,00 6,33 6,66 7,00 , Money 0
VII | P a g e
Residuals Analysis:
1. Versus Order
Versus Order
(response is Time) 100
75
50 Residual
25
0
-25
-50 1 50 100 150 200 250 Observation Order 300 350
2. Versus Fits
Versus Fits
(response is Time) 100
75
50 Residual
25
0
-25 -50 0 25 Fitted Value 50 75
VIII | P a g e
3. Normal Probability Plot
Normal Probability Plot
(response is Time)
99,9
99 95 90 80
Percent
70 60 50 40 30 20 10 5 1 0,1
-50
-25
0
25 Residual
50
75
100
IX | P a g e
Appendix E - Regression Data
Hours 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Emotional Motivation Atmosphere Accessibility Material Motivation Q2 Q3 Q10 Average Q4 Q7 Q13 Average Q5 Q9 Q11 Average Q6 Q8 Q12 Average 25 65 6 5,666667 4 4 4 443 3 3,333333 4 4 3 3,666667 40 44 5 4,333333 4 5 4 4,333333 2 2 2 244 4 4 55 55 5 533 4 3,333333 3 2 3 2,666667 7 6 6 6,333333 20 45 5 4,666667 3 2 3 2,666667 4 3 3 3,333333 4 4 4 4 25 56 5 5,333333 2 2 3 2,333333 4 5 4 4,333333 4 5 4 4,333333 45 44 5 4,333333 4 5 5 4,666667 5 5 4 4,666667 5 5 6 5,333333 30 65 6 5,666667 2 3 2 2,333333 4 4 4 434 4 3,666667 5 33 4 3,333333 3 2 3 2,666667 3 4 3 3,333333 1 2 2 1,666667 10 34 4 3,666667 4 4 4 433 2 2,666667 3 4 4 3,666667 15 54 5 4,666667 4 4 4 422 2 244 5 4,333333 68 67 7 6,666667 3 2 3 2,666667 4 4 4 477 6 6,666667 10 54 3 422 2 232 3 2,666667 4 3 4 3,666667 20 55 5 522 1 1,666667 4 3 4 3,666667 5 4 5 4,666667 35 55 6 5,333333 3 3 2 2,666667 5 5 5 556 6 5,666667 10 56 6 5,666667 4 4 4 465 4 533 4 3,333333 15 55 4 4,666667 4 4 5 4,333333 5 4 4 4,333333 4 3 4 3,666667 60 66 7 6,333333 4 4 5 4,333333 4 4 4 466 6 6 15 55 6 5,333333 3 3 3 365 5 5,333333 4 4 5 4,333333 15 56 6 5,666667 2 1 1 1,333333 2 2 1 1,666667 3 4 4 3,666667 20 54 5 4,666667 2 2 3 2,333333 3 2 2 2,333333 4 4 3 3,666667 5 56 5 5,333333 4 4 4 444 4 433 3 3 7 44 4 433 3 333 3 333 3 3 5 34 3 3,333333 5 5 5 555 6 5,333333 2 1 1 1,333333 5 56 5 5,333333 6 6 6 655 4 4,666667 1 1 1 1 9 66 6 666 6 666 6 633 3 3 16 55 5 534 3 3,333333 6 6 6 643 4 3,666667 30 76 6 6,333333 5 4 4 4,333333 5 5 5 567 6 6,333333 60 66 6 644 4 466 6 677 7 7 566 6 623 2 2,333333 3 3 3 322 2 230 15 66 6 645 4 4,333333 6 6 6 644 4 4 15 55 5 555 5 523 3 2,666667 3 3 3 3 45 67 6 6,333333 4 5 4 4,333333 5 5 5 555 5 5 30 66 6 666 6 666 6 633 3 3 30 76 5 645 5 4,666667 4 4 4 444 4 4 30 77 7 721 2 1,666667 2 3 3 2,666667 2 2 2 2 30 55 5 555 4 4,666667 5 4 5 4,666667 4 4 5 4,333333 25 55 5 534 3 3,333333 4 4 4 444 3 3,666667 18 66 6 666 6 666 6 622 2 2 3 55 5 523 3 2,666667 4 4 4 423 3 2,666667 X|Page
31 32 33 34 35 36 37 38 39
40 41
58 59 60
71
76 77
3 5 5 5 5 6 6 5 5,666667 6 6 6 6 2 1 1 1,333333 35 5 5 5 4 4 4 4 4 5 4 4,333333 3 3 3 342 10 7 66 6,333333 6 6 5 5,666667 6 6 6 6 4 3 4 3,666667 43 70 7 67 6,666667 4 5 4 4,333333 6 6 6 6 5 6 5 5,333333 44 45 7 65 6 4 4 4 4 5 5 4 4,666667 5 6 7 645 35 7 6 7 6,666667 55 5 5 6 6 6 6 3 3 2 2,666667 46 25 6 6 6 6 3 4 33,333333 5 5 5 5 5 4 5 4,666667 47 50 7 7 6 6,666667 7 6 7 6,666667 7 7 6 6,666667 2 1 2 1,666667 48 50 5 5 5 5 5 5 55 4 5 5 4,666667 6 4 5 549 50 4 3 5 4 6 6 6 6 5 6 55,333333 5 5 5 550 45 5 6 6 5,666667 5 5 4 4,666667 2 2 2 25 4 4 4,333333 51 15 5 5 6 5,333333 4 4 4 4 3 2 3 2,666667 4 4 5 4,333333 52 10 4 4 4 4 4 4 4 4 4 4 4 45 4 4 4,333333 53 20 4 5 4 4,333333 4 4 4 4 6 6 5 5,666667 4 3 3 3,333333 54 25 4 5 5 4,666667 3 3 2 2,666667 4 44 4 3 3 3 355 30 5 6 6 5,666667 4 4 3 3,666667 4 5 5 4,666667 6 5 5 5,333333 56 37 6 6 5 5,666667 5 5 6 5,333333 4 33 3,333333 4 4 5 4,333333 57 20 4 3 3 3,333333 4 5 4 4,333333 4 44 4 4 5 5 4,666667 15 5 5 5 5 4 4 4 4 3 3 4 3,333333 3 2 3 2,666667 40 7 6 6 6,333333 2 2 3 2,333333 4 5 4 4,333333 5 5 6 5,333333 56 5 5 5,333333 1 2 2 1,666667 2 2 2 2 4 3 3 3,333333 61 5 33 2 2,666667 4 5 5 4,666667 3 3 2 2,666667 5 5 5 562 10 6 5 5 5,333333 4 4 4 4 3 3 3 3 3 2 2 2,333333 63 5 54 5 4,666667 3 2 3 2,666667 4 4 4 4 5 4 4 4,333333 64 15 5 4 4 4,333333 4 4 5 4,333333 4 5 4 4,333333 4 4 4 465 20 5 5 5 5 3 4 4 3,666667 3 4 4 3,666667 5 4 4 4,333333 66 25 4 3 3 3,333333 4 4 5 4,333333 3 4 3 3,333333 5 5 5 567 50 7 6 7 6,666667 6 5 5 5,333333 4 4 4 4 6 5 6 5,666667 68 35 6 5 5 5,333333 5 5 5 5 3 4 4 3,666667 5 5 6 5,333333 69 40 7 6 5 6 4 4 4 4 5 4 4 4,333333 7 6 6 6,333333 70 10 5 4 5 4,666667 2 2 3 2,333333 3 4 3 3,333333 4 4 5 4,333333 56 6 6 6 2 2 3 2,333333 3 2 4 3 2 2 2 272 15 2 33 2,666667 5 5 6 5,333333 3 3 3 3 2 3 3 2,666667 73 20 5 56 5,333333 4 4 4 4 5 4 4 4,333333 5 4 4 4,333333 74 45 3 44 3,666667 4 4 4 4 5 4 4 4,333333 6 6 6 675 70 7 76 6,666667 5 5 6 5,333333 4 5 4 4,333333 7 6 6 6,333333 45 6 6 7 6,333333 5 5 5 5 5 5 4 4,666667 6 6 6 6 20 5 5 5 5 3 4 4 3,666667 5 5 5 5 5 4 4 4,333333 78 10 4 4 4 4 5 5 4 4,666667 2 2 3 2,333333 4 4 4 479 15 4 4 4 4 4 4 4 4 3 3 3 3 4 4 4 480 5 5 5 65,333333 2 3 2 2,333333 3 4 4 3,666667 3 2 3 2,666667 81 25 6 56 5,666667 3 2 2 2,333333 3 4 4 3,666667 4 5 5 4,666667 82 25 3 44 3,666667 5 5 4 4,666667 4 4 4 4 5 5 5 5 XI | P a g e
83 84
90
101 102
105
110 111 112 114 115 116 118 119 120
124
10 3 3 4 3,333333 2 1 20 6 6 5 5,666667 2 2 10 5 5 5 5 4 4 3 15 4 4 4 4 3 2 3 40 6 6 7 6,333333 3 4 50 6 7 7 6,666667 4 4 10 5 4 5 4,666667 4 5 52 3 3 2,666667 5 4 4 60 7 6 7 6,666667 5 5 66 6 6 6 6 6 7 7 6,666667 3 4 3 3,333333 5,666667 4 4 3 3,666667 63 4 5 4 5 5 5 5 33 3 3 4 3 3,333333 66 6 7 7 6 6,666667 5,666667 6 6 5 5,666667 77 7 7 2 2 2 2100 65,333333 7 7 6 6,666667 50 5 6 6 5,666667 4 4 15 5 5 5 5 4 4 4 20 6 5 4 5 4 3 3 20 5 5 5 5 5 5 5 20 5 5 5 5 4 4 4 66 6,333333 4 4 4 4 4 15 5 5 5 5 5 5 5 45 6 7 6 6,333333 4 5 15 4 4 4 4 3 2 3 40 6 6 7 6,333333 3 4 35 5 5 6 5,333333 3 3 15 6 7 7 6,666667 3 4 55 6 5,333333 2 3 2 40 6 6 6 6 6 6 6 25 6 5 6 5,666667 3 2 16 5 5 5 5 3 4 3 30 7 6 6 6,333333 5 4 20 6 5 4 5 4 3 3 20 5 5 5 5 5 5 10 6 5 5 5,333333 4 4 54 5 4,666667 3 2 3 15 5 4 4 4,333333 4 4 45 5 5 5 5 3 2 3 35 6 6 6 6 6 6 5 45 7 7 7 7 7 7 7
2 1,666667 2 2 2 3,666667 5 2,666667 4 4 3,666667 4 4 5 5 4,666667 4,333333 4 5 5 5 6 6,666667 3 3 3 5 5 5 1 1 2 2 2 1 4 3 5 4 4 4 65 6
3 3 2 2,666667 4 2 2 2 2 3 3 5 4 4,666667 5 4 4 5 4,333333 4 3 5 5 5 5 6 6 6 6 5,666667 5 5 3 3 4 3,333333 6 4 3 3,666667 5 6 5 5 5 6 6 6 5 5 4 4,666667 93 15 3 3 3 3 394 5 2 2 2 295 1,333333 96 8 4 5 1,666667 97 50 6 7 498 35 6 6 6 6 499 45 7 7 7 7 5 6 5,666667 6 6
3 3 3,333333 2,666667 85 4 4,333333 86 4 3,666667 87 5 5,666667 88 6 5,333333 89 5 6 5,666667 6 5,666667 91 692 40 6 6 7 7 5 6 6 5 4 6 6 6 5 4,666667 3 7 6,666667 6 6 6 5 7 7 7 7 6 6 5 5
5 4,333333 4 5 5 4,666667 4 4 5 4 4,333333 3 3,333333 3 3 3 3 4 5 5 5 5 4 4,666667 3 4 4 4 4 4 4 4 4 4 5 4,333333 4 6 6 5 2 3 3 2,666667 3 4 4,333333 5 5 5 5 5 2,666667 4 4 5 4,333333 4 4 3,666667 5 5 5 5 6 2 2,666667 5 5 5 5 5 3 3,333333 3 3 3 3 3 2,333333 3 4 4 3,666667 3 6 7 7 6 6,666667 5 2 2,333333 3 4 4 3,666667 3,333333 6 6 6 6 4 3 4 4,333333 5 5 5 5 6 3,333333 3 3 3 3 4 5 5 5 5 5 4 4,666667 4 4 3 3 3 3 3 2 2,666667 4 4 4 4 5 4 5 4,333333 4 5 4 4,333333 2,666667 3 2 3 2,666667 5 5,666667 6 6 5 5,666667 4 7 7 7 7 7 2 2 2
5 6 6 5,666667 5 4 4103 4 4,333333 104 4 3 3,333333 4106 30 7 5,333333 107 3 3 3108 5 5 5109 3 4 3,666667 6 5 5,666667 6 6 5,666667 3 3 3113 5 2 3 2,666667 5 4 4,666667 4 5 5 4,666667 4 3,666667 117 7 6 6,333333 4 4,333333 3 4 3 3,333333 2 2,333333 121 5 4 4,333333 122 4 4 4 4123 5 6 5,333333 4 4 4125 2 XII | P a g e
126 127
131 132 133
144 145
149 150 152
155 156
160 161 162 163
167
5 6 5 5 5,333333 1 2 2 1,666667 2 2 2 2 53 3 2 2,666667 4 5 5 4,666667 3 3 2 2,666667 5 10 6 5 5 5,333333 4 4 4 4 3 3 3 3 3 2 20 4 5 5 4,666667 3 2 3 2,666667 4 3 3 3,333333 25 5 6 5 5,333333 2 2 3 2,333333 4 5 4 4,333333 15 4 4 4 4 3 2 3 2,666667 4 4 5 4,333333 4 40 6 6 7 6,333333 3 4 4 3,666667 5 5 5 5 6 35 5 5 5 6 6 5 5,666667 6 6 6 6 2 1 56 5 5,333333 4 4 4 4 4 4 4 4 3 3 3 44 3 3 3 3 3 3 3 3 3 3 3 3136 35 6 65 5,666667 5 6 5 5,333333 4 3 4 3,666667 137 45 76 7 6,666667 7 6 6 6,333333 2 2 2 2138 20 44 4 4 4 4 4 4 4 4 4 4139 30 6 6 6 3,666667 4 5 5 4,666667 4 6 6 5,333333 140 15 55 5 2 3 3 2,666667 3 3 3 3141 15 5 45 4,333333 4 5 4 4,333333 4 4 4 4142 20 5 43,666667 3 4 4 3,666667 5 4 4 4,333333 143 25 44 5 4,333333 3 4 3 3,333333 5 5 5 5 50 7 6 7 6,666667 6 5 5 5,333333 4 4 4 4 56 5 5 5,333333 1 2 2 1,666667 2 2 2 2 4 3 33 3 3 4 5 5 4,666667 3 2 2 2,333333 5 5 6 10 6 5 5 5,333333 4 4 4 4 3 3 3 3 3 2 15 5 4 5 4,666667 4 5 4 4,333333 4 5 5 4,666667 20 6 5 4 5 4 3 3 3,333333 3 4 3 3,333333 4 10 5 6 6 5,666667 4 4 4 4 6 5 4 5 3 3 15 5 5 5 5 4 5 5 4,666667 5 4 4 4,333333 4 60 6 6 7 6,333333 4 4 5 4,333333 4 4 4 4 6 37 5 5 6 5,333333 3 3 3 3 5 5 5 5 4 4 30 6 5 6 5,666667 2 3 2 2,333333 4 4 4 4 3 53 4 4 3,666667 3 2 3 2,666667 3 4 3 3,333333 1 10 3 3 4 3,333333 4 4 4 4 3 2 2 2,333333 4 56 5 5,333333 4 3 4 3,666667 4 4 4 4 3 2 45 4 4,333333 3 3 3 3 3 4 3 3,333333 3 15 5 5 4 4,666667 4 4 5 4,333333 4 5 4 4,333333 20 5 6 5 5,333333 3 4 4 3,666667 3 4 4 3,666667 25 4 3 3 3,333333 4 5 5 4,666667 3 4 3 3,333333 50 7 6 7 6,666667 6 5 5 5,333333 4 5 4 4,333333 20 6 5 4 5 4 3 4 3,666667 3 3 3 3 4 5 30 5 5 6 5,333333 5 5 5 5 5 5 5 5 3 3 6 5 5,666667 3 3 3 3 5 5 5 5 1 1 2 60 7 7 7 7 5 6 5 5,333333 6 7 7 6,666667 4 50 5 5 5 5 3 4 4 3,666667 5 5 5 5 6 7 55 7 6 7 6,666667 5 5 5 5 6 6 6 6 3 4
4 3 3 3,333333 5 5 5128 2 2,333333 129 4 4 4 4130 4 5 4 4,333333 3 4 3,666667 6 5 5,666667 1 1,333333 134 5 3135 7 4 4 5 6 5,666667 6 7 7 6 6,666667 5 5 6 5,333333 6 4 3 4 5 5 5 5 5 4 4 4,333333 4 5 5 5 3 4 4 3 3 3,333333 6 5 6 5,666667 3 3,333333 146 5 5,333333 147 2 2,333333 148 4 5 4 4,333333 5 5 4,666667 4 3,333333 151 3 4 3,666667 6 6 6153 5 4,333333 154 4 4 3,666667 2 2 1,666667 4 4 4157 5 3 2,666667 158 7 3 3 3159 4 4 3 3,666667 5 4 4 4,333333 5 5 5 5 6 5 6 5,666667 4 4,333333 164 3 3165 10 6 1,333333 166 3 4 3,666667 6 6,333333 168 4 3,666667 XIII | P a g e
169 170
187 188
191 192
197 199
203 205 206
55 6 6 6 6 5 5 70 7 5 6 6 5 5 5 444 4 2 2 3 2,333333 655 5,333333 4 5 5 4,666667 55,333333 6 5 5 5,333333 555 4 4 4,333333 5 4 5 543 4 4 4 4 4 4 2 3,666667 4 4 4 4 2 2 544,666667 2 2 2 2178 15 222,333333 179 35 5 5 4 54,666667 180 20 6 6 7 22,333333 181 20 6 6 6 3,333333 182 20 5 6 6 444183 60 6 6 6 6 6 75 6 6 6 6 6 6 7 776,666667 6 6 5 5,666667 100 7 7 7 7 7 7 7 50 5 5 5 5 4 4 45 6 7 6 6,333333 4 5 35 6 6 6 6 5 5 5 35 6 7 7 6,666667 6 7 35 5 5 6 5,333333 5 4 35 6 6 6 6 6 6 6 5 5 5 3 3 3 3 5 5 6 5,666667 5 5 5 12 4 4 4 4 4 4 4 7 7 6,666667 6 6 6 40 6 6 6 6 5 5 5 6 5 5,333333 5 6 5 10 6 6 5 5,666667 4 5 10 6 6 6 6 4 5 5 25 5 5 6 5,333333 6 6 20 6 7 7 6,666667 6 7 20 6 6 6 6 5 5 5 5 5 5 5 5 5 5 5 40 6 6 6 6 6 5 30 7 7 7 7 6 6 6 30 6 6 6 6 5 5 4 7 7 7 6 6 6 6 6 5,333333 6 6 5 5,666667 6 6 6 5 5 5 5 6 3 4 3 3,333333 4 4 4
4 4,666667 6 6 6 6 5 5 6 5,333333 5 5 5 5 5 6 5 6 5,666667 171 3 4 5 4 4,333333 1 1 2 1,333333 172 5 5 6 6 5,666667 1 3 2 2173 5 6 5 6 6 6 6 2 3 2 2,333333 174 3 5 5 4,666667 3 2 3 2,666667 175 7 5 5 5 5 2 2,666667 176 7 4 5 5 4,666667 4 4 3 2 2177 10 7 6 5 6 3 4 3 3,333333 5 5 5 5 5 5 5 5 5 5 5 5 5 3 4,666667 3 2 2 2,333333 5 5 5 5 4 5 6,333333 5 6 5 5,333333 6 6 6 6 3 2 6 4 4 4 4 5 5 5 5 3 3 4 5,666667 5 5 5 5 5 6 6 5,666667 4 6 6 6 6 6 6 6 6 6 6 6184 6,333333 7 7 7 7 3 3 3 3185 90 6 7 7 6 6,666667 5 4 4 4,333333 186 7 7 7 7 7 7 7 7 7 3 3,666667 4 4 3 3,666667 5 5 4 4,666667 5 4,666667 6 6 6 6 5 5 5 5189 5 5 5 5 5 5 5 4 4,666667 190 6 6,333333 6 6 6 6 4 3 3 3,333333 4 4,333333 6 5 4 5 4 5 4 4,333333 6 6 6 6 6 6 6 6 6193 40 5 5 4 4,666667 6 6 6 6194 15 6 5 6 6 6 6 2 1 2 1,666667 195 4 4 4 4 4 2 2 2 2196 50 6 6 6 7 7 6,666667 3 4 3 3,333333 5 5 5 5 5 6 6 6 6198 10 5 5,333333 5 5 6 5,333333 4 5 5 4,666667 4 4,333333 3 3 3 3 3 3 3 3200 4,666667 6 6 6 6 2 1 2 1,666667 201 5 5,666667 6 6 6 6 5 5 5 5202 7 6,666667 7 7 7 7 2 1 2 1,666667 5 6 6 6 6 6 5 4 5204 15 5 5 5 5 5 5 5 5 5 5,333333 5 6 5 5,333333 6 7 6 6,333333 6 7 7 7 7 2 3 3 2,666667 207 4,666667 6 6 6 6 5 5 5 5208 65 7 6 6 6 2 1 1 1,333333 209 85 5 5 6 6 5 5 5,333333 5 4 3 4210 15 6 6 6 6 5 5 5 5211 10 6 5 5 5,333333 4 2 2 2 2 XIV | P a g e
212 213
217
221
225 226
230 231 232
236 238
247 248 249 251 252
5 4 5 5 4,666667 4 4 4 4 6 6 6 6 3 4 4 3,666667 10 6 6 6 6 3 3 3 3 4 4 4 4 1 1 2 1,333333 214 15 5 6 6 5,666667 4 5 5 4,666667 6 6 6 6 1 1 1 1215 50 5 5 5 5 3 2 3 2,666667 5 4 5 4,666667 4 4 4 4216 45 6 5 6 5,666667 2 2 3 2,333333 5 5 5 5 6 7 6 6,333333 20 4 4 4 4 2 2 2 2 4 5 5 4,666667 4 4 4 4218 10 5 5 5 5 3 2 2 2,333333 4 4 4 4 3 2 2 2,333333 219 40 5 6 6 5,666667 4 4 4 4 5 4 4 4,333333 4 4 4 4220 10 6 5 5 5,333333 2 3 3 2,666667 5 6 5 5,333333 3 2 3 2,666667 20 4 5 4 4,333333 4 4 3 3,666667 5 4 5 4,666667 4 4 4 4222 10 4 3 3 3,333333 3 3 3 3 5 4 6 5 4 5 5 4,666667 223 5 33 3 3 3 2 2 2,333333 4 5 5 4,666667 3 4 4 3,666667 224 17 4 4 4 4 4 4 4 4 4 4 5 4,333333 3 3 4 3,333333 34 4 5 5 4,666667 3 3 3 3 6 5 5 5,333333 3 2 3 2,666667 52 2 3 2,333333 1 2 2 1,666667 3 3 3 3 4 4 4 4227 10 4 33 3,333333 5 5 4 4,666667 4 4 4 4 4 4 4 4228 10 4 4 3 3,666667 4 4 4 4 4 3 4 3,666667 5 4 6 5229 5 4 5 6 5 4 33 3,333333 2 3 3 2,666667 4 4 4 4 20 5 5 6 5,333333 4 4 3 3,666667 5 4 4 4,333333 5 4 5 4,666667 25 6 6 6 6 4 4 4 4 4 5 5 4,666667 5 4 4 4,333333 60 7 7 6 6,666667 6 5 5 5,333333 5 5 6 5,333333 7 6 5 6233 30 5 6 6 5,666667 6 6 4 5,333333 5 4 5 4,666667 4 4 4 4234 30 5 5 5 5 3 2 3 2,666667 4 4 4 4 4 4 3 3,666667 235 20 3 4 4 3,666667 2 2 2 2 5 4 4 4,333333 2 3 3 2,666667 15 3 5 4 4 4 3 4 3,666667 4 4 4 4 6 4 4 4,666667 237 34 6 5 5 5,333333 1 2 2 1,666667 3 3 3 3 5 5 6 5,333333 10 4 4 4 4 3 2 2 2,333333 4 4 4 4 5 5 5 5239 25 4 54 4,333333 3 3 3 3 5 4 4 4,333333 4 7 4 5240 5 3 3 22,666667 5 5 4 4,666667 2 2 1 1,666667 2 2 1 1,666667 241 5 55 5 5 3 3 3 3 2 2 2 2 4 4 5 4,333333 242 10 4 4 4 44 4 4 4 4 5 4 4,333333 2 2 2 2243 35 6 5 5 5,333333 21 2 1,666667 6 5 6 5,666667 6 5 5 5,333333 244 40 6 6 7 6,333333 2 3 2 2,333333 4 4 4 4 2 2 3 2,333333 245 20 3 34 3,333333 2 2 2 2 5 4 4 4,333333 3 3 2 2,666667 246 10 2 2 2 2 3 3 2 2,666667 4 4 6 4,666667 6 5 5 5,333333 15 3 2 3 2,666667 3 4 4 3,666667 5 5 5 5 4 4 5 4,333333 15 4 4 4 4 2 4 3 3 4 4 4 4 5 4 5 4,666667 15 4 5 4 4,333333 2 2 2 2 3 3 4 3,333333 4 4 4 4250 20 6 5 5 5,333333 3 3 2 2,666667 4 5 5 4,666667 4 4 5 4,333333 30 6 6 5 5,666667 2 2 1 1,666667 4 3 4 3,666667 3 3 4 3,333333 50 5 5 5 5 3 2 2 2,333333 6 6 6 6 6 5 5 5,333333 253 10 6 6 7 6,333333 4 4 4 4 4 4 5 4,333333 4 4 4 4254 7 44 5 4,333333 4 4 4 4 4 3 3 3,333333 2 2 2 2 XV | P a g e
255 256
259 260 261 262
273 274
291 292
50 6 7 35 6 5 55 4,666667 15 5 4 20 5 4 20 5 4 30 5 6 55 5 5 55,666667 4 54 4,333333 56 6 6 44 1 2 22 2268 54269 45 6270 60 7 55 5 5 66 6 6 15 5 5 15 5 5 66 6,333333 54 4 3 33 3 3 56 5,333333 4,666667 2 6,333333 6 62 2 2 1283 80 5 90 5 5 95 7 7 95 6 7 56 5,666667 57 5,666667 45 6 5 55 5,333333 5 7 6 57 6 7 56 5,333333 66 5,666667 25 5 5 76 6,333333 77 7 4
7 6,666667 2 1 2 1,666667 5 5 4 4,666667 4 3 4 3,666667 5 5,333333 4 4 4 4 4 4 4 4 3 3 3 3257 20 4 5 4 4 4,333333 2 3 2 2,333333 6 7 6 6,333333 258 5 4,666667 3 3 3 3 4 5 5 4,666667 4 5 4 4,333333 4 4,333333 2 2 2 2 6 5 6 5,666667 5 5 4 4,666667 5 4,666667 4 4 4 4 4 4 5 4,333333 2 3 3 2,666667 6 5,666667 5 4 3 4 3 3 4 3,333333 3 4 4 3,666667 5 3 3 3 3 5 5 5 5 2 1 1 1,333333 263 3 6 6 4 4 4 4 4 4 4 1 1 1 1264 15 6 6 6 6 4 5 5 5 5 2 2 2 2265 65 6 7 7 6,666667 5 5 5 6 5 6 6 5,666667 266 5 4 4 4 4 4 4 4 4 4 4 2 1,666667 267 13 5 5 5 5 3 3 3 3 4 4 4 4 2 50 7 7 6 6,666667 5 5 6 5,333333 6 6 6 6 3 4 6 6 6 6 4 5 4 4,333333 5 6 5 5,333333 6 6 6 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7271 30 5 4 4 4,333333 5 5 5 5 3 4 3 3,333333 272 45 6 6 6 6 7 7 6 6,666667 2 2 3 2,333333 5 5 4 4 4 4 5 5 5 5 1 2 1 1,333333 5 5 4 3 4 3,666667 5 5 5 5 3 3 3 3275 20 7 5 6 5 5,333333 6 6 6 6 4 4 4 4276 20 5 5 5 3,666667 5 6 5 5,333333 3 4 5 4277 20 3 3 3 3 3 3 3 3 2 2 2 2278 20 6 7 6 6,333333 5 5 5 5 5 1 1 1 1279 20 5 5 5 5 3 3 3 3 5 4 5 2 4 2,666667 280 65 7 7 7 7 5 5 5 5 6 7 6 7 6 6,333333 281 15 6 6 6 6 6 6 6 6 6 6 6 2282 75 7 7 7 7 7 7 7 7 7 7 7 7 1 1 1 5 5 5 4 5 6 5 6 6 6 6 6 6 7 6,333333 284 5 5 5 5 5 5 6 7 7 6,666667 6 6 6 6285 7 7 6 7 6 6,333333 7 7 7 7 4 5 4 4,333333 286 7 6,666667 6 6 6 6 6 6 6 6 3 3 3 3287 60 6 6 5 4 5 5 6 5 5,333333 6 6 6 6288 10 5 6 4 5 5 5 5 5 5 4 3 5 4289 3 5 5 6 5,333333 6 6 6 6 2 2 1 1,666667 290 5 6 6 7 6,333333 6 5 6 6 5,666667 2 3 3 2,666667 6 6,333333 6 5 4 5 6 6 6 6 4 3 3 3,333333 6,666667 5 5 6 5,333333 6 6 6 6 3 3 3 3293 10 5 4 5 5 4,666667 5 5 5 5 2 2 3 2,333333 294 10 5 4 4 3 3,666667 4 3 3 3,333333 2 1 1 1,333333 295 5 5 5 5 5 5 5 5 5 5 5 5 5 5296 30 6 6 6 5 5,666667 6 6 5 5,666667 5 5 5 5297 70 7 5 5 4,666667 5 5 5 5 7 6 7 6,666667 X VI | P a g e
298 299
304
316 317
332 334 335
339
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6 5,666667 4300 15 5 90 7 303 2,666667 50 7 5 5 5 6 5,666667 5 4 6 5 5 5 4 6 5 5 6 6 6 6 5 6 6 6 7 6 7 6 6 4 4,333333 5318 50 6 4 4,333333 6 5,333333 3 4 3 3 4 5 4,666667 4 5 5 5 5 5 3,666667 2 6,666667 5 6 5 4 4 4 4 6,666667 30 6 5 4,333333 30 6 30 5 338 2 2,333333 1340 5
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341 342
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371
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15 6 6 6 6 4 4 15 6 6 6 6 4 3 4 15 7 6 7 6,666667 4 4 65 6 6 7 7 6,666667 76 5 6 5,666667 7 7 7 66 6 6 6 2 2 2 2347 66 7 6 6,333333 348 35 5 55 5 5349 25 6 6 5 2,666667 350 30 7 7 6 11,333333 351 45 6 7 7 65 6352 45 5 6 6 4353 45 7 6 6 6,333333 4354 50 7 7 7 7 7 7 45 6 6 6 6 6 6 5 67 6,333333 4 5 4 4,333333 55 5 5 5 5 5 5 5 54 6 5 6 6 4 5,333333 2 7 5 5 5,666667 3 2 564 5 5 4 4 5 4,333333 676 6,333333 6 5 5 5,333333 555 5 4 3 4 3,666667 666 6 5 6 5,666667 6 6 566 5,666667 7 7 6 6,666667 445 4,333333 5 5 5 5 2 555,333333 7 6 5 6 6 6 666 6 6 6368 30 6 6 322,666667 369 30 7 7 7 44370 30 6 5 6 5,666667 60 7 6 5 6 5 6 4 45 6 7 6 6,333333 5 6 70 7 7 7 7 6 7 7 777 6 6 6 6 6 6 6 567 6 7 6 7 6,666667 666,333333 6 6 5 5,666667 25 6 6 6 6 5 6 25 6 6 5 5,666667 4 5 15 7 6 6 6,333333 4 4 15 5 5 5 5 4 4 5 10 6 6 5 5,666667 5 3 66 5 5,666667 4 4 5 70 7 7 7 7 6 7 6
4 4 4 5 5 4,666667 3 4 5 4 3,666667 4 3 3 3,333333 3 3 3 3343 4 4 5 5 5 5 1 2 3 2344 35 7 7 7 7 7 6 6 6 6345 65 7 7 7 7 2 2 2 2346 6 6 6 6 6 6 6 6 70 6 6 6 6 6 6 6 6 6 6 6 6 6 5,666667 5 5 5 5 5 5 5 5 5,666667 5 5 5 5 5 5 5 5 3 3 2 6,666667 7 6 7 6,666667 7 7 7 7 1 2 6,666667 6 6 6 6 6 7 6 6,333333 7 5,666667 5 5 5 5 7 7 7 7 4 3 5 4 5 5 4,666667 6 5 5 5,333333 4 4 4 7 7 7 7 7 7 2 3 2 2,333333 355 5,666667 6 6 6 6 6 6 6 6356 25 6 5 5 5 5 3 3 4 3,333333 357 30 5 5 5 5 5 5 5358 15 6 6 5 5,666667 2 2 1 1,666667 3 2,666667 5 5 5 5 1 1 1 1 5 5 6 5,333333 4 4 5 4,333333 361 5 4 4 5 4,333333 1 2 1 1,333333 362 5 4 5 5 4,666667 2 2 2 2363 35 6 6 6 5 6 6 5,666667 364 55 7 7 7 7 4 5 4 4,333333 365 10 5 6 5 5,333333 1 2 1,666667 366 50 7 6 6 6,333333 6 6 6367 45 6 6 6 6 6 6 6 6 6 6 6 6 5 5 5 5 6 5 5 5,333333 3 7 6 5 5 5,333333 6 6 6 6 4 4 4 4 4 4 7 6 5 6 3 3 4 3,333333 5 4 5 5 4,666667 5 5 5 5372 5 5,333333 6 6 6 6 4 5 6 5373 6,666667 7 7 7 7 1 1 1 1374 90 7 6 6 7 6 6,333333 375 130 7 7 7 7 5 6 6 5,666667 376 35 6 6 6 6 7 3 3 4 3,333333 6 5,666667 5 5 6 5,333333 5 5 5 5 4 4,333333 5 6 6 5,666667 3 3 3 3379 4 4 5 5 5 5 4 3 4 3,666667 380 4,333333 4 5 4 4,333333 2 2 2 2381 4 4 3 3 4 3,333333 3 2 1 2382 5 4,333333 3 3 4 3,333333 1 1 1 1383 6,333333 7 7 7 7 5 6 6 5,666667 XVIII | P a g e
384 385 386 388
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6 6 6,333333 6 7 6,666667 7 7 7 7 7 6 6,333333 5 5 5 5 6 6 6 6 5,666667 5 6 6 6 5 7 6 6,666667 6 6 6,333333 6 5 5,666667 7 6 6,666667 6 7 6,333333 7 7 7
7 6 7 6 5 6 5 4 4 4 6 6 5 7
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5 6 5 5,666667 7 7 7 6 6 6 5 5 5 6 6 6 5 5 4 4,333333 6 5 5 6 4 4 6 4 5,333333 6 5,666667 6 5,666667 7 7
7 6 7 6 6 6 5 7 6 6 6 7 7 7
7 6 6,666667 6 7 6,333333 7 7 6 7 7 6,333333 2 5,333333 5 6 2 2 2 4,666667 1 7 6,666667 4 7 6,333333 6 7 6,333333 6 7 7 6,666667 7 6 6,666667 6 6 6,333333 7 7 7
5 5 3 4 6,666667 3 3 5 5 2390 2 1 5 4 6 6 6 6 6 5 4 5 4 3 5 5
5 5 3 3,333333 387 2,666667 5389 25 6 1,333333 4,333333 6393 6394 6 5,666667 5 4,666667 4 3,666667 5 5
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doc_939506108.docx