Description
This study examines the sentimental correlation of lottery prizes with household consumption via Grey
relational analysis. An approximate correlation with sequential order rankings is identified. Results
demonstrate that all top five lottery prizes are strongly correlated with rational addictive consumption
and income categories. These lottery prizes show a relatively strong correlation with entertainment
consumption and a negligible correlation with desperation consumption. Although jackpot exhibits an
approximate strong correlation with alcohol consumption, other prizes show an approximate strong
correlation with tobacco consumption. The top five prizes demonstrate a relatively strong correlation
with restaurant, recreation, and traveling consumption, as well as a negligible correlation with food and
education consumption. Lottery prizes are negligibly correlated with salary with the least sentiment.
Sentimental relationships between lottery participation and household
consumption
Ann Shawing Yang
Institute of International Management, National Cheng Kung University, ROC
a r t i c l e i n f o
Article history:
Received 11 March 2015
Accepted 9 July 2015
Available online xxx
Keywords:
Lottery prize
Rational addiction
Entertainment
Desperation
Sentiments
a b s t r a c t
This study examines the sentimental correlation of lottery prizes with household consumption via Grey
relational analysis. An approximate correlation with sequential order rankings is identi?ed. Results
demonstrate that all top ?ve lottery prizes are strongly correlated with rational addictive consumption
and income categories. These lottery prizes show a relatively strong correlation with entertainment
consumption and a negligible correlation with desperation consumption. Although jackpot exhibits an
approximate strong correlation with alcohol consumption, other prizes show an approximate strong
correlation with tobacco consumption. The top ?ve prizes demonstrate a relatively strong correlation
with restaurant, recreation, and traveling consumption, as well as a negligible correlation with food and
education consumption. Lottery prizes are negligibly correlated with salary with the least sentiment.
© 2015 College of Management, National Cheng Kung University. Production and hosting by Elsevier
Taiwan LLC. All rights reserved.
1. Introduction
Lottery prizes often attract considerable public interest with
increased and extended participation (Haruvy, Erev, & Sonsino,
2001; Rogers & Webley, 2001; Sharpira & Venezia, 1992; Thaler &
Ziemba, 1988). Consumer participation in lottery is in?uenced not
only by jackpot prizes for lifetime winnings, but also by medium
prizes to extend participation duration (Haruvy et al., 2001; Thaler
& Ziemba, 1988). In particular, lottery participation increased from
26.6% with a single prize to 37.7% with multiple prizes (Haruvy
et al., 2001). Consumers increase lottery participation for large
jackpot prize opportunities, but also use small prize winnings to
continue toward jackpot prize winnings (Rogers & Webley, 2001;
Sharpira & Venezia, 1992). Therefore, consumers voluntarily
contribute to lottery prizes in which lottery sales determine the
prize structures (Dale, 2004).
Nevertheless, consumers may develop irrational or rational
decision making via lottery prize structures with unknown prob-
abilities of winning toward jackpot, rollover, or low-tier prizes (Lin,
Kang, & Chan, 2005; Lin & Wang, 2004; Matheson & Grote, 2004).
Thus, consumers exhibit rational addictive behavior toward large
jackpot prizes with increased participation (Doran, Jiang, &
Peterson, 2012). Moreover, the accumulations of rollovers
encourage the development of lotto mania behavior among
increased numbers of participants (Beenstock & Haitovsky, 2001;
Harley & Lanot, 2006; Peel, 2010). Therefore, lottery games assist
in developing sentimental reactions for hope and fear via regret
aversion decision making for extended participation (Statman,
2002).
Additionally, consumers determine lottery participation and
duration based on prize payout rates (P erez & Humphreys, 2011).
However, consumers may determine lottery participation based on
income and consumption behavior changes (Kuhn, Kooreman,
Soetevent, & Kapteyn, 2011; P erez & Humphreys, 2011). Increases
in income encourage existing consumers to purchase more national
lottery tickets instead of attracting new potential consumers (P erez
& Humphreys, 2011). Consumers with lottery prize winnings
signi?cantly show ownership of newly purchased cars as well as
spend more on food away from home and durables excluding cars;
by contrast, their counterparts signi?cantly exhibit greater monthly
expenditures, including food away from home and other expendi-
tures, renovation expenditures, durables, and more donations to
charity (Kuhn et al., 2011). From the perspective of household
consumption behavior, consumer sentiment reactions may relate
closely to speci?c expenditures for addictive, recreation, or daily
necessity purchases. Addictive research hypothesis indicates that
tobacco and alcohol expenditures re?ect rational addiction
E-mail address: [email protected].
Peer review under responsibility of College of Management, National Cheng
Kung University.
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Asia Paci?c Management Review xxx (2015) 1e10
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
sentiment (Balabanis, 2002; Kearney, 2005; Lin & Lin, 2007).
Entertainment research hypothesis states that restaurant, recrea-
tion, and traveling expenditures signify entertainment sentiment
(Farrell & Forrest, 2008; Garrett & Marsh, 2002). Daily necessity
research hypothesis posits that food and education expenditures
(i.e., basic family consumption) represent desperation sentiment in
which such expenditures are necessary for maintaining basic living
standards (Landry & Price, 2007; Lee & Chang, 2005).
Thus, our empirical study is motivated by rational addictive
theory (Becker & Murphy, 1988), accompanied by the various
household consumption research hypotheses to identify senti-
ment reactions from lottery participation. We further expand
lottery sentiment reaction analysis from jackpot prize to low-tier
prizes. We analyze the in?uence of multiple prize structures for
lottery games toward consumer decision making and behavior.
This study aims to bridge the gap between higher and lower tier
prizes by identifying the likely sentiments regarding each prize
amount.
Despite existing studies on the demographic and socioeconomic
analysis of lottery participation (Farrell & Walker, 1999; Garrett &
Marsh, 2002; Ghent & Grant, 2007; Harley & Lanot, 2006; Ho,
Lee, & Lin, 2006; Kearney, 2005; Lin & Lin, 2007; Lin & Wu,
2007; Matheson & Grote, 2004), the relationship between lottery
prize structures and sentimental consumption has not been
established. In contrast to previous studies focusing on the causal
relationship between lottery demand and demographic back-
ground (Farrell & Walker, 1999; Garrett & Marsh, 2002; Ghent &
Grant, 2007; Harley & Lanot, 2006; Ho et al., 2006; Kearney,
2005; Lin & Lin, 2007; Lin & Wu, 2007; Matheson & Grote,
2004), we propose Grey relational analysis (GRA) (Deng, 1982) to
identify the approximate correlation between consumption senti-
ment and lottery prizes for the order rankings of sequence in-
?uences for households. A sequential relationship, ranked by orders
of Grey relational grades, is identi?ed for individual and category
sentiment indices comprising rational addiction, entertainment,
and desperation behavior for various prize returns. The application
of GRA builds on other models in identifying the in?uences on
lottery consumption. GRA not only provides an order relation of
variables by rankings of Grey relational grades, but also identi?es
the latent in?uences of variables that are less likely to be detectable
using other methods. The government and authorities may refer to
the empirical results in considering the formation of strategic al-
liances, formulation of promotional campaigns, and designing of
lottery games. Meanwhile, lottery players may refer to the empir-
ical results in determining the sentiment indicators on lottery
purchases.
2. Literature review and theory
Rational addictive behavior generally in?uences lottery con-
sumption by individual players, and lotteries possess addictive
characteristics (Chang, 2004; Moore, 1997). The total prize amount
strongly affects participation in lottery consumption, whereas the
increased consumption of tobacco and alcohol is associated with
increased consumption demand in lotteries (Lin & Lin, 2007; Zeng,
2006). Heavier smokers also tend to purchase more lottery tickets
as an addictive and compulsive behavior (Balabanis, 2002). Thus,
bounded rationality exists in lottery games in which most players
react more to jackpots and respond less to smaller games with
higher returns (Grote & Matheson, 2006). The level of rational
addiction is the major in?uence on lottery consumption (Chang,
2004; Harley & Lanot, 2006; Lin & Lin, 2007). Addictive products,
such as tobacco, alcohol, and betel nuts, strongly in?uence lottery
consumption (Chang, 2004; Kearney, 2005; Landry & Price, 2007).
Low ticket prices similarly encourage lottery players to assume a
higher risk than they otherwise would (Haisley, Mostafa, &
Loewenstein, 2008).
Households may reduce their expenditure on non-addictive
purchases, such as education, grocery, mortgage, rent, and other
bills, to participate in lotteries (Kearney, 2005; Lee & Chang,
2005). The allocation of lottery proceeds to fund education en-
courages lottery sales (Landry & Price, 2007). Household expen-
diture on groceries and entertainment is most likely to be
replaced by consumption needs in lotteries to improve the eco-
nomic situation (Kearney, 2005; Lee & Chang, 2005). Therefore,
restaurant expenditure negatively and signi?cantly in?uences
lottery sales; by contrast, tourism in?uences lottery sales because
players seeking lottery prizes are willing to travel to increase
their probability of winning (Farrell & Forrest, 2008; Garrett &
Marsh, 2002).
Household income also in?uences lottery participation to
improve economic conditions or seek entertainment (Garrett &
Marsh, 2002; Ghent & Grant, 2007). Higher income households
participate in lottery games for entertainment, whereas lower in-
come households do so to improve their economic conditions
(Ghent & Grant, 2007). However, income is also insigni?cantly
related to lottery sales (Chen, Chie, Fan, & Yu, 2009). Nevertheless,
income level and employment status may affect lottery consump-
tion (Lin & Lin, 2007). A decrease in economic ability tends to in-
crease lottery purchases and thus improve the quality of life and
economic conditions (Blalock, Just, & Simon, 2007; Garrett &
Marsh, 2002; Ghent & Grant, 2007).
2.1. Theory
Rational addictive theory, proposed by Becker and Murphy
(1988), focuses on products with the potential to be addictive,
including cigarettes. When making purchasing decisions, con-
sumers consider and transform purchase price, product usage, and
added value as their needs. Factors affecting the need for addictive
products may include stress and income. Particularly, purchase
prices are deterministic in encouraging addictive purchase
behavior (Becker & Murphy, 1988). Therefore, rational addictive
consumer behavior is more likely to develop predictive consump-
tion behavior that is in?uenced by purchase price, product func-
tion, and product added value (Harris & Harris, 1996). Consumers
with an addictive behavior toward products are more likely to be
in?uenced by personal preferences and engage in long-term and
regular consumption of addictive products (Miljkovic, Nganje, & de
Chastenet, 2008).
National lottery games not only encourage consumers to dou-
ble their consumption, but also induce a four-fold increase in the
excessive consumption toward addiction among households (Grun
& McKeigue, 2000). Lottery games with frequent advertisements
are also often viewed as an acceptable gamble with accessible
stores and affordable ticket prices, thus engendering the addiction
behavior of consumers in which they participate in lottery games
via past experiences to exert an illusion of control over their daily
lives (Hardoon, Baboushkin, Derevensky, & Gupta, 2001). In the
case of lottery participation, addictive consumption is common in
less educated households (Grun & McKeigue, 2000; Shepherd,
Ghodse, & London, 1998). Thus, lottery games induce addictive
consumption in which less educated households spend more than
their counterparts at an average of ?2.42 per week on scratch
cards or lottery tickets compared with ?1.84 per week, particularly
for households with an annual income of less than ?20,000
(Shepherd et al., 1998). Low-income households also exhibit the
highest percentage in spending more than 10% of income on lot-
tery tickets, thus spurring addictive consumption (Grun &
McKeigue, 2000).
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 2
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
3. Method
This study uses GRA, proposed by Deng (1982), to solve prob-
lems involving incomplete information systems or missing statis-
tics. Based on Grey system theory, GRA can effectively deal with
small sets of data containing indeterminate values, having multiple
inputs, or are incomplete (Deng, 2000). Contrary to probability and
statistical theories that are used in treating large samples of un-
certain data, Grey system theory can treat uncertain acknowledged
sets (Lui & Hsu, 1996).
Grey relational analysis identi?es a sequential relationship
among factors according to Grey relational grades that systemati-
cally rank the degrees of in?uence (Fu, 1992; Tzeng & Tsaur, 1994).
Grey relational grades pertain to the relationship between two
series of systems or factors, including howthey are affected by time
or other elements (Huang & Jane, 2007). Order relation, the key
feature of GRA, can be used to identify the relationship between
two sequences (Wang, 2008). An approximate correlation is thus
identi?ed using GRA between an objective factor and several
affecting factors in a system characterized by limited data, simple
calculations, and lack of statistical distribution (Chen & Tzeng,
2004; Lu, Lin, & Lewis, 2008). The advantages of GRA include the
avoidance of defects common in conventional, large sample sta-
tistical methods, simple calculation, minimal data requirements,
and quanti?ed results that do not con?ict with those of qualitative
analysis (Li, Yamaguchi, Nagai, & Masuda, 2008; Lin & Chang,
2008). Thus, GRA potentially offers a reliable extension of existing
methodologies.
3.1. Procedure
This study uses GRA to examine the relative value of nine in-
dividual sentiment indices and ultimately identify the variable that
exerts the strongest in?uence on lottery returns using Grey rela-
tional software. Individual sentiment indices are compared based
on the orders of Grey relational grades and evaluated according to
the values of individual series indices. First, this investigation ver-
i?es the monthly data using Grey data processing to normalize and
transform data expressed using different measurement units into a
single numerical order (Chang & Lin, 1999). The direct application
of raw data is also permitted if they meet the requirements of
comparability, namely non-dimensionality, scaling, and polariza-
tion (Wang, 2008).
x
i
ðkÞ ¼
x
ð0Þ
i
ðkÞ Àmin
k
x
ð0Þ
i
ðkÞ
max
k
x
ð0Þ
i
ðkÞ Àmin
k
x
ð0Þ
i
ðkÞ
; (1)
where x is the index variable, i represents the various prize returns
obtained during the ith month, and k denotes the variable values of
the sentiment index during the ith month.
Second, prior to obtaining the Grey relational coef?cient from
Equation (2), this investigation applies Equation (3) to identify the
absolute difference between two sequences and thus demonstrate
their relationship with the entire system (Lu et al., 2008). Term z is
an identi?cation coef?cient that is used in adjusting the difference
between relational coef?cients (Lu et al., 2008). For stability and
clarity, a value of 0.5 is widely applied (Fu, Zheng, & Zhao, 2001; Lu
et al., 2008; Wang, 2008). In this case, x
0
(k) denotes the reference
value of Grey relational calculation, x
i
(k) represents the compared
value of sentiment index k on the ith month, zD
max
is the value of
the distinguishing coef?cient multiplied by the maximum differ-
ence between the compared series x
i
and reference series x
0
, and
D
0i
(k) represents the difference between the collection of compared
series and the reference series of Grey relational factors.
gðx
0
ðkÞ; x
i
ðkÞÞ ¼
D
min
þzD
max
D
0i
ðkÞ þzD
max
; (2)
where:
1: D
0i
ðkÞ ¼ jx
0
ðkÞ À x
i
ðkÞj (3)
Equation (3) expresses the absolute difference between the
compared and reference series.
2: D
min
¼ min
i
min
k
jx
0
ðkÞ À x
i
ðkÞj (4)
3: D
max
¼ max
i
max
k
jx
0
ðkÞ À x
i
ðkÞj (5)
Equations (4) and (5) are subsequently used to determine the
minimum and maximum distances in all of the compared se-
quences (Chang & Lin, 1999; Lu et al., 2008). D
min
and D
max
should
be respectively de?ned as the minimum and maximum difference
between the compared series x
i
and reference series x
0
, where k
represents the value of sentiment index.
4: z ¼ identification coefficient z2½0; 1? (6)
Equation (6) is also applied, where z is a distinguished identi-
?cation coef?cient, with z2[0, 1] used in adjusting the difference
between D
0i
and D
max
(Fu et al., 2001; Wang, 2008). The Grey
relational coef?cient is subsequently calculated using Equation (2).
Grey relational grade is calculated using Equation (7). Grey
relational grade g (x
0
, x
i
) represents the in?uence between the
measured elements that are de?ned using Equation (7).
gðx
0
; x
i
Þ ¼
X
n
k¼1
b
k
gðx
0
ðkÞ; x
i
ðkÞÞ; (7)
where b
k
denotes k normweight and
P
n
k¼1
b
k
¼ 1 (Ho & Lin, 2003).
This study ranks the sequences according to the Grey relational
order, from the most related to the least related. The relationship
between investor sentiment indices and price volatility is ranked
and termed the Grey relational rank (g). A Grey relational rank
value exceeding 0.9 indicates a strong in?uence, a value between
0.8 and 0.9 connotes a relatively strong in?uence, a value between
0.7 and 0.8 denotes a signi?cant in?uence, and a value between 0.6
and 0.7 shows a negligible in?uence (Fu et al., 2001).
3.2. GRA example
We illustrate an example of the application of GRA. We obtain
monthly jackpot prize returns and tobacco expenditures from
January to December 2002. Columns 1 and 2 present the raw data
for jackpot prize returns (x
01
) and tobacco expenditures (in ln form)
(x
21
), respectively. In the ?rst step, data normalization is conducted
by taking the monthly values divided by the January value for both
jackpot prize returns in Column 3 and tobacco expenditures in
Column 4. Considering that January is determined as the base
month, data normalization for January will become 1.0 for both
jackpot prize returns and tobacco expenditures. In the second step,
the absolute difference values are computed by the difference be-
tween Columns 3 and 4; we take Column 3 minus Column 4 and
obtain the absolute value on a monthly basis (corresponding to
Equation (3)). In step three, we identify the minimum and
maximum values from Column 5 (corresponding to Equations (4)
and (5)). In step four, we take 0.5 multiplied by the maximum
value from Column 7 to adjust the difference between D
0i
(k) and
Dmax and derive an adjusted value zDmax (corresponding to
Equation (6)). In step ?ve, Grey relational coef?cients are calculated
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 3
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
according to Equation (2). In step six, we sum up all of the Grey
relational coef?cients and take the average value to identify the
Grey relational grade (corresponding to Equation (7)). The obtained
Grey relational grade is compared for correlational relationship to
identify the importance order and sequential order with other
variables Table 1.
4. Research design
4.1. Selection of variables
This study follows Doran et al. (2012), Lin and Wu (2007), and
Kearney (2005) in selecting and categorizing variables. Variables
representing lottery returns are segmented into high- and low-tier
prizes. Variables representing household consumption are classi-
?ed into different groups based on whether they are used for the
rational addiction hypothesis, desperation hypothesis, or enter-
tainment hypothesis. Table 2 lists the categories of variable selec-
tions. Three categories are studied, namely, lottery purchase,
household consumption, and income.
4.2. Lottery returns
Lottery returns from a jackpot are frequently viewed as the
primary motivation in lottery consumption (Garrett & Sobel, 2004).
Although low-tier prizes from smaller lottery games may also yield
high returns, they are frequently ignored owing to the prizes
offered through jackpots (Grote & Matheson, 2006). Prize sizes,
ranging from a jackpot win to various smaller prizes, represent the
various probabilities of winning the lottery (Maeda, 2008). The
current study selected jackpot (Jackpt), second prize (2nd Pz), third
prize (3rd Pz), fourth prize (4th Pz), and ?fth prize (5th Pz) returns
to identify the relationship between different prize sizes and
household consumption. The ratio of prize sizes to lottery sales is
calculated using each prize.
4.3. Household expenditures
Household expenditure variables are classi?ed into desperation
hypothesis, rational addiction hypothesis, and entertainment hy-
pothesis. This study refers to Landry and Price (2007), Balabanis
(2002), Kearney (2005), and Garrett and Marsh (2002) for the se-
lection of variables to indicate household consumption. Food ex-
penditures (Fd) and education expenditures (Edu) are selected to
represent expenditures for the desperation hypothesis. Tobacco
expenditures (Toba) and alcohol expenditures (Alcho) are selected
to represent expenditures for the rational addiction hypothesis.
Restaurant expenditures (Resto), recreation expenditures (Rec), and
traveling expenditures (Trvl) are selected to represent expenditures
for the entertainment hypothesis.
4.4. Income
According to Garrett and Sobel (2004), income is a signi?cant
indicator of lottery sales. Ghent and Grant (2007) report that a
higher income encourages greater lottery participation. Salary
(Salry) is thus adjusted to identify the relationship between prize
size and income for lottery purchases.
4.5. Study period and data sources
This study uses monthly data for 2002e2010 to identify the
relationship between lottery prize returns and household con-
sumption. Eight sentiment indices are selected for each of the ?ve
types of lottery prize returns for each month of the year. A total of T
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A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 4
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
108 observations consist of 12 monthly values from January to
December for 9 years; 8 sentiment indices multiplied by 108
months result in 864 entries. Statistical lottery data are obtained
from the Taiwan Lottery Company. The Taiwan Lottery Company,
which is the only government-authorized sales agent for national
lottery tickets, is located in Taipei, the capital of Taiwan. House-
hold expenditure statistics are obtained from the Directorate
General of Budget, Accounting and Statistics of the Taipei City
Government. Data on average monthly salary are obtained from
the Directorate General of Budget, Accounting and Statistics, Ex-
ecutive Yuan.
5. Results and analysis
This study analyzes the in?uences of ?ve different lottery prize
returns on household consumption in Taipei. Each lottery prize
return, including those for the jackpot, second, third, fourth, and
?fth prizes, is individually analyzed for the period 2002e2010. For
each type of prize return, eight individual sentiment indices are
selected and compared among four sentiment categories
throughout the study period. Table 3 lists the results for various
lottery returns and category sentiment indices, whereas Table 4
lists the results for various lottery returns and individual senti-
ment indices.
5.1. Category sentiment indices and lottery returns
Table 3 lists the four categories of sentiment indices, namely
desperation category, rational addiction category, entertainment
category, and income category, and ranks them according to Grey
relational grades for all prize returns throughout all study periods.
Rational addiction category indices consistently show an approxi-
mate strong correlation of various prize returns with household
consumptions, with Grey relational grades ranging between 0.9497
(for jackpot return in 2005) and 0.9887 (for ?fth prize return in
2006). Jackpot returns on rational addiction category exhibit an
approximate strong correlation, with Grey relational grades
ranging from 0.9497 to 0.9850 throughout the study period; by
contrast, smaller prizes show Grey relational grade values between
0.9686 and 0.9862 (second prize return), 0.9693 and 0.9853 (third
prize return), 0.9686 and 0.9857 (fourth prize return), and 0.9686
and 0.9887 (?fth prize return), respectively.
The sentiment indices of the income category also display an
approximate strong correlation with all prize returns throughout
the study period, with Grey relational grades between 0.9242 (for
jackpot return in 2005) and 0.9834 (for ?fth prize return in 2006).
Jackpot returns are strongly correlated with income category, with
Grey relational grades between 0.9242 and 0.9794, and the ranking
in terms of strength of correlation subsequently follows this order:
smaller prize returns between 0.9562 and 0.9808 (second prize
return), between 0.9585 and 0.9808 (third prize return), between
0.9563 and 0.9810 (fourth prize return), and between 0.9562 and
0.9834 (?fth prize return).
The sentiment indices of the desperation category show an
approximate signi?cant correlation with all prize returns
throughout the study period, with Grey relational grades between
0.6321 (for jackpot return in 2005; negligible in?uence) and 0.7270
(for ?fth prize return in 2006). Jackpot returns are signi?cantly
correlated with desperation category sentiment indices, with Grey
relational grades between 0.6321 and 0.7216. In 2005, jackpot
returns are only negligibly correlated with desperation category
sentiment indices, with a Grey relational grade value of 0.6321.
Furthermore, the correlation of smaller prizes with household
consumption classi?ed as desperation category is signi?cant, with
Grey relational grades between 0.7097 and 0.7267 (second prize
return), between 0.7095 and 0.7269 (third prize return), between
0.7084 and 0.7266 (fourth prize return), and between 0.7091 and
0.7270 (?fth prize return).
The sentiment indices of the entertainment category, ranked
with the least correlation according to Grey relational grades,
display a negligible correlation with all prize returns for all study
periods, with Grey relational grades between 0.6200 (for jackpot
return in 2005) and 0.6651 (for ?fth prize return in 2006). The
various Grey relational grades for all prizes range from 0.6200 to
0.6594 for jackpot return, from 0.6465 to 0.6643 for second prize
return, from 0.6466 to 0.6642 for third prize return, from 0.6526 to
0.6642 for fourth prize return, and from 0.6524 to 0.6651 for ?fth
prize return.
Jackpot returns display the largest volatility in correlation with
various category sentiment indices. Thus, jackpot returns display a
range of Grey relational grades from 0.9497 to 0.9850 for the
rational addiction category; from 0.9242 to 0.9794 for the income
category; from 0.6321 to 0.7216 for the desperation category; and
from 0.6200 to 0.6594 for the entertainment category. However,
smaller prize returns display relatively stable Grey relational grade
values throughout the study period from 2002 to 2010 for all
category sentiment indices. Although lottery prizes are consistently
strongly correlated with the income category, with Grey relational
grades exceeding 0.9, rational addiction category sentiment indices
display a stronger correlation. Therefore, the category sequence of
Grey relational grades is as follows: rational addiction, income,
desperation, and entertainment.
Table 2
Category and individual factors affecting lottery sentiment.
Segmentation Category sentiment indices Individual sentiment indices Symbols De?nition
a
Lottery x
0
Lottery returns x
01
Jackpot returns Pz
jack
Jackpot amount
t
/Sales amount
t
x
02
Second Prize returns Pz
2
Second Prize amount
t
/Sales amount
t
x
03
Third Prize returns Pz
3
Third Prize amount
t
/Sales amount
t
x
04
Fourth Prize returns Pz
4
Fourth Prize amount
t
/Sales amount
t
x
05
Fifth Prize returns Pz
5
Fifth Prize amount
t
/Sales amount
t
Household consumption x
1
Desperation x
11
Food Fd Ln(Food
t
)
x
12
Education Edu ln(Edu
t
)
x
2
Rational Addiction x
21
Tobacco Toba Ln(Tobac)
x
22
Alcohol Alcoh ln(Alcol
t
)
x
3
Entertainment x
31
Restaurant Resto Ln(Resto
t
)
X
32
Recreation Recre ln(Recre
t
)
x
33
Traveling Trvl Ln(Travl
t
)r
Income x
4
Income x
41
Salary Salry ln(Salary
t
)
a
Note: Lotto represents lottery sales, Food represents food consumption, Edu represents educational consumption, Tobac represents tobacco consumption, Alcol represents
alcohol consumption, Recre represents recreational consumption, Resto represents restaurant dinning consumption, Trvl represents traveling consumption, and Salry rep-
resents salary received.
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 5
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
Table 3
Grey relation coef?cients and relational grade ranking 2002e2010 e category indices.
Category
sentiment
indices
Jackpot e Relational grades and rankings Second prize e Relational grades and ranking
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Desperation 0.7168 (3) 0.7087 (3) 0.7216 (3) 0.6321 (3) 0.7201 (3) 0.7156 (3) 0.7074 (3) 0.7196 (3) 0.7203 (3) 0.7178 (3) 0.7097 (3) 0.7267 (3) 0.7192 (3) 0.7258 (3) 0.7217 (3) 0.7113 (3) 0.7236 (3) 0.7246 (3)
Rational
addiction
0.9844 (1) 0.9773 (1) 0.9801 (1) 0.9497 (1) 0.9850 (1) 0.9792 (1) 0.9696 (1) 0.9806 (1) 0.9753 (1) 0.9841 (1) 0.9768 (1) 0.9849 (1) 0.9851 (1) 0.9862 (1) 0.9850 (1) 0.9686 (1) 0.9831 (1) 0.9790 (1)
Entertainment 0.6576 (4) 0.6559 (4) 0.6555 (4) 0.6200 (4) 0.6594 (4) 0.6464 (4) 0.6488 (4) 0.6524 (4) 0.6496 (4) 0.6587 (4) 0.6570 (4) 0.6606 (4) 0.6465 (4) 0.6643 (4) 0.6532 (4) 0.6523 (4) 0.6566 (4) 0.6535 (4)
Income 0.9721 (2) 0.9586 (2) 0.9747 (2) 0.9242 (2) 0.9794 (2) 0.9674 (2) 0.9550 (2) 0.9705 (2) 0.9550 (2) 0.9719 (2) 0.9582 (2) 0.9796 (2) 0.9590 (2) 0.9808 (2) 0.9733 (2) 0.9562 (2) 0.9732 (2) 0.9587 (2)
Category sent-
iment indices
Third prize e Relational grades and ranking Fourth prize e Relational grades and ranking
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Desperation 0.7180 (3) 0.7095 (3) 0.7269 (3) 0.7192 (3) 0.7257 (3) 0.7168 (3) 0.7119 (3) 0.7239 (3) 0.7245 (3) 0.7174 (3) 0.7084 (3) 0.7266 (3) 0.7192 (3) 0.7257 (3) 0.7215 (3) 0.7116 (3) 0.7239 (3) 0.7246 (3)
Rational
addiction
0.9846 (1) 0.9768 (1) 0.9853 (1) 0.9853 (1) 0.9861 (1) 0.9847 (1) 0.9693 (1) 0.9834 (1) 0.9788 (1) 0.9855 (1) 0.9764 (1) 0.9852 (1) 0.9857 (1) 0.9864 (1) 0.9849 (1) 0.9686 (1) 0.9834 (1) 0.9788 (1)
Entertainment 0.6588 (4) 0.6569 (4) 0.6607 (4) 0.6466 (4) 0.6642 (4) 0.6477 (4) 0.6528 (4) 0.6569 (4) 0.6534 (4) 0.6581 (4) 0.6557 (4) 0.6604 (4) 0.6465 (4) 0.6642 (4) 0.6531 (4) 0.6526 (4) 0.6569 (4) 0.6535 (4)
Income 0.9724 (2) 0.9583 (2) 0.9800 (2) 0.9592 (2) 0.9808 (2) 0.9727 (2) 0.9569 (2) 0.9734 (2) 0.9585 (2) 0.9732 (2) 0.9578 (2) 0.9798 (2) 0.9595 (2) 0.9810 (2) 0.9732 (2) 0.9563 (2) 0.9735 (2) 0.9585 (2)
Category
sentiment
indices
Fifth prize e Relational grades and ranking
2002 2003 2004 2005 2006 2007 2008 2009 2010
Desperation 0.7174 (3) 0.7091 (3) 0.7267 (3) 0.7193 (3) 0.7270 (3) 0.7217 (3) 0.7115 (3) 0.7237 (3) 0.7244 (3)
Rational Addiction 0.9842 (1) 0.9767 (1) 0.9850 (1) 0.9855 (1) 0.9887 (1) 0.9852 (1) 0.9686 (1) 0.9834 (1) 0.9788 (1)
Entertainment 0.6582 (4) 0.6564 (4) 0.6606 (4) 0.6466 (4) 0.6651 (4) 0.6531 (4) 0.6524 (4) 0.6567 (4) 0.6533 (4)
Income 0.9720 (2) 0.9582 (2) 0.9796 (2) 0.9594 (2) 0.9834 (2) 0.9735 (2) 0.9562 (2) 0.9734 (2) 0.9585 (2)
Note: Grey relational category indices are presented by sentiment categories for all prizes for the period from 2002 to 2010. Lottery prize categories include jackpot, second, third, fourth, and ?fth prizes, which are ranked
according to sentiment on desperation, rational addiction, and entertainment, plus income. Rational addiction sentiment shows a strong sentimental correlation with lottery participation, with Grey relational grades (GRA
grades
)
above 0.9, followed by income with a relatively strong correlation (GRA
grades
between 0.8 and 0.9), desperation with a signi?cant correlation (GRA
grades
between 0.7 and 0.8), and entertainment with a negligible correlation
(GRA
grades
between 0.6 and 0.7) for all prizes.
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Table 4
Grey relation coef?cients and relational grade rankingseindividual sentiment indices.
Indiv. Sentmt
Indice
Jackpot e Relational grades and rankings Second prize e Relational grades and rankings
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Fd 0.6852 (7) 0.6805 (7) 0.6891 (7) 0.6156 (7) 0.7016 (7) 0.6931 (7) 0.6532 (7) 0.6764 (7) 0.6897 (7) 0.6868 (7) 0.6794 (7) 0.7002 (7) 0.6673 (7) 0.6944 (7) 0.6889 (7) 0.6567 (7) 0.6845 (7) 0.6983 (7)
Edu 0.7341 (6) 0.7291 (6) 0.7444 (6) 0.6743 (6) 0.7529 (6) 0.7467 (6) 0.7172 (6) 0.7471 (6) 0.7333 (6) 0.7353 (6) 0.7275 (6) 0.7552 (6) 0.7297 (6) 0.7446 (6) 0.7412 (6) 0.7205 (6) 0.7547 (6) 0.7419 (6)
Tobac 0.9635 (2) 0.9520 (2) 0.9555 (2) 0.8553 (2) 0.9690 (2) 0.9625 (2) 0.9302 (2) 0.9569 (2) 0.9538 (2) 0.9791 (1) 0.9806 (1) 0.9867 (1) 0.9842 (1) 0.9880 (1) 0.9884 (1) 0.9264 (2) 0.9779 (1) 0.9681 (2)
Alcho 0.9708 (1) 0.9557 (1) 0.9649 (1) 0.8741 (1) 0.9733 (1) 0.9698 (1) 0.9374 (1) 0.9620 (1) 0.9609 (1) 0.9689 (2) 0.9500 (2) 0.9738 (2) 0.9386 (2) 0.9588 (2) 0.9585 (2) 0.9391 (1) 0.9673 (2) 0.9683 (1)
Recre 0.8444 (4) 0.8343 (4) 0.8486 (4) 0.7633 (3) 0.8601 (4) 0.8514 (4) 0.8078 (4) 0.8379 (4) 0.8212 (4) 0.8443 (4) 0.8310 (4) 0.8589 (4) 0.8224 (3) 0.8490 (4) 0.8435 (4) 0.8106 (4) 0.8448 (4) 0.8296 (4)
Resto 0.8513 (3) 0.8514 (3) 0.8594 (3) 0.7518 (4) 0.8826 (3) 0.8585 (3) 0.8334 (3) 0.8563 (3) 0.8411 (3) 0.8511 (3) 0.8478 (3) 0.8696 (3) 0.8106 (4) 0.8708 (3) 0.8504 (3) 0.8359 (3) 0.8632 (3) 0.8494 (3)
Trvl 0.8092 (5) 0.8158 (5) 0.7996 (5) 0.7204 (5) 0.8143 (5) 0.7974 (5) 0.7689 (5) 0.7875 (5) 0.8023 (5) 0.8095 (5) 0.8128 (5) 0.8100 (5) 0.7774 (5) 0.8043 (5) 0.7907 (5) 0.7717 (5) 0.7950 (5) 0.8108 (5)
Salry 0.6414 (8) 0.6364 (8) 0.6441 (8) 0.5743 (8) 0.6573 (8) 0.6496 (8) 0.6139 (8) 0.6382 (8) 0.6273 (8) 0.6433 (8) 0.6358 (8) 0.6552 (8) 0.6238 (8) 0.6511 (8) 0.6462 (8) 0.6176 (8) 0.6463 (8) 0.6357 (8)
Indiv. Sentmt
Indice
Third prize e Relational grades and rankings Fourth prize e Relational grades and rankings
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Fd 0.6869 (7) 0.6811 (7) 0.7005 (7) 0.6674 (7) 0.6944 (7) 0.6889 (7) 0.6577 (7) 0.6734 (7) 0.6981 (7) 0.6850 (7) 0.6776 (7) 0.6996 (7) 0.6623 (7) 0.6937 (7) 0.6891 (7) 0.6572 (7) 0.6852 (7) 0.6983 (7)
Edu 0.7354 (6) 0.7293 (6) 0.7557 (6) 0.7299 (6) 0.7446 (6) 0.7412 (6) 0.7215 (6) 0.7454 (6) 0.7417 (6) 0.7336 (6) 0.7259 (6) 0.7547 (6) 0.7244 (6) 0.7440 (6) 0.7414 (6) 0.7209 (6) 0.7555 (6) 0.7419 (6)
Tobac 0.9797 (1) 0.9834 (1) 0.9875 (1) 0.9847 (1) 0.9881 (1) 0.9884 (1) 0.9279 (2) 0.9773 (1) 0.9677 (2) 0.9803 (1) 0.9814 (1) 0.9872 (1) 0.9783 (1) 0.9877 (1) 0.9887 (1) 0.9266 (2) 0.9785 (1) 0.9677 (2)
Alcho 0.9694 (2) 0.9527 (2) 0.9745 (2) 0.9390 (2) 0.9588 (2) 0.9585 (2) 0.9404 (1) 0.9662 (2) 0.9680 (1) 0.9700 (2) 0.9504 (2) 0.9742 (2) 0.9327 (2) 0.9584 (2) 0.9588 (2) 0.9392 (1) 0.9679 (2) 0.9680 (1)
Recre 0.8446 (4) 0.8332 (4) 0.8595 (4) 0.8227 (3) 0.8490 (4) 0.8435 (4) 0.8119 (4) 0.8384 (4) 0.8293 (4) 0.8438 (4) 0.8302 (4) 0.8588 (4) 0.8169 (3) 0.8484 (4) 0.8437 (4) 0.8110 (4) 0.8456 (4) 0.8294 (4)
Resto 0.8514 (3) 0.8501 (3) 0.8701 (3) 0.8109 (4) 0.8708 (3) 0.8504 (3) 0.8372 (3) 0.8574 (3) 0.8491 (3) 0.8507 (3) 0.8471 (3) 0.8695 (3) 0.8051 (4) 0.8703 (3) 0.8506 (3) 0.8362 (3) 0.8639 (3) 0.8492 (3)
Trvl 0.8097 (5) 0.8149 (5) 0.8105 (5) 0.7776 (5) 0.8043 (5) 0.7908 (5) 0.7729 (5) 0.7869 (5) 0.8105 (5) 0.8086 (5) 0.8118 (5) 0.8097 (5) 0.7720 (5) 0.8037 (5) 0.7909 (5) 0.7721 (5) 0.7958 (5) 0.8106 (5)
Salry 0.6426 (8) 0.6369 (8) 0.6549 (8) 0.6235 (8) 0.6508 (8) 0.6461 (8) 0.6183 (8) 0.6350 (8) 0.6358 (8) 0.6413 (8) 0.6338 (8) 0.6544 (8) 0.6189 (8) 0.6504 (8) 0.6463 (8) 0.6180 (8) 0.6471 (8) 0.6358 (8)
Indiv. Sentmt Indice Fifth prize e Relational grades and rankings
2002 2003 2004 2005 2006 2007 2008 2009 2010
Fd 0.6849 (7) 0.6794 (7) 0.7003 (7) 0.6675 (7) 0.6527 (7) 0.6884 (7) 0.6567 (7) 0.6847 (7) 0.6979 (7)
Edu 0.7335 (6) 0.7277 (6) 0.7553 (6) 0.7300 (6) 0.7014 (6) 0.7408 (6) 0.7205 (6) 0.7550 (6) 0.7415 (6)
Tobac 0.9787 (1) 0.9827 (1) 0.9868 (1) 0.9850 (1) 0.9404 (1) 0.9882 (1) 0.9264 (2) 0.9784 (1) 0.9677 (2)
Alcho 0.9684 (2) 0.9518 (2) 0.9739 (2) 0.9393 (2) 0.9108 (2) 0.9583 (2) 0.9390 (1) 0.9678 (2) 0.9680 (1)
Recre 0.8430 (4) 0.8319 (4) 0.8590 (4) 0.8229 (3) 0.8033 (4) 0.8431 (4) 0.8106 (4) 0.8452 (4) 0.8292 (4)
Resto 0.8498 (3) 0.8488 (3) 0.8697 (3) 0.8111 (4) 0.8242 (3) 0.8501 (3) 0.8359 (3) 0.8636 (3) 0.8490 (3)
Trvl 0.8080 (5) 0.8136 (5) 0.8101 (5) 0.7778 (5) 0.7594 (5) 0.7903 (5) 0.7718 (5) 0.7954 (5) 0.8104 (5)
Salry 0.6413 (8) 0.6357 (8) 0.6553 (8) 0.6239 (8) 0.6107 (8) 0.6457 (8) 0.6176 (8) 0.6466 (8) 0.6353 (8)
Note: Grey relational category indices are presented by sentiment indices for all prizes for the period from2002 to 2010. Lottery prize categories include jackpot, second, third, fourth, and ?fth prizes, which are ranked according
to individual sentiment indices on household consumption related to food, education, tobacco, alcohol, recreation, restaurant, and travel, plus salary. For all prize categories, tobacco consumption shows a strong sentimental
correlation with lottery participation, with Grey relational grades above 0.9. Alcohol consumption, restaurant consumption, and recreation consumption demonstrate a relatively strong correlation (GRA
grades
between 0.8 and
0.9). Travel consumption and education consumption exhibit a signi?cant correlation (GRA
grades
between 0.7 and 0.8). Food consumption and salary show a negligible correlation (GRA
grades
between 0.6 and 0.7).
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5.2. Individual sentiment indices and lottery returns
Table 4 lists eight sentiment indices, comprising household
consumption on food, education, tobacco, alcohol, restaurant, rec-
reation, and traveling, plus salary, which are analyzed and ranked
according to Grey relational grades for various prizes throughout
the study period. Alcohol and tobacco consumption consistently
shows approximate strong correlations with various prize returns.
Jackpot returns are most strongly correlated with alcohol con-
sumption, given the Grey relational grades between 0.8741 in 2005
and 0.9733 in 2006. However, smaller prize returns display an
approximate stronger correlation with tobacco consumption, with
Grey relational grades ranging between 0.9404 for ?fth prize in
2006 and 0.9887 for fourth prize in 2007; with most of study period
being between 2002 and 2007, plus 2009. For the study periods
2008 and 2010, alcohol consumption is more in?uenced by smaller
prize returns compared with tobacco consumption.
Restaurant consumption consistently shows a relatively strong
correlation for all prize returns during all study periods, with Grey
relational grades between 0.7518 for jackpot return in 2005 and
0.8708 for third prize return in 2006. For 2005, restaurant con-
sumption consistently exhibits less correlation than recreation
consumption for all prize returns. Meanwhile, traveling con-
sumption displays a cyclical change in in?uence for all prize
returns during all study periods. Furthermore, jackpot returns are
signi?cantly correlated with traveling consumption, with Grey
relational grades exceeding 0.80 in 2002 and 2003, after which
their correlation becomes negligible in 2005 and 2005, with Grey
relational grades of 0.7996 and 0.7204, respectively. For later study
periods, the correlation of jackpot returns with traveling con-
sumption remains signi?cant, with Grey relational grades of
0.8143 in 2006; the in?uence of Grey relational grade gradually
decreases to become negligible between 2007 and 2009, after
which the correlation of Grey relational grade becomes signi?cant.
Smaller prize returns experience similar changes in Grey relational
grades and correlation levels. For the period between 2002 and
2004, in 2006, and in 2010, second, third, and fourth prize returns
are signi?cantly correlated with traveling consumption. Compared
with the periods 2005 and between 2007 and 2009, Grey rela-
tional grades indicate a negligible correlation. However, ?fth prize
returns are signi?cantly correlated with traveling consumption
between 2002 and 2004, and during 2010. Fifth prize returns are
also negligibly correlated with traveling consumption between
2005 and 2009, with Grey relational grades between 0.7594 and
0.7954.
Education consumption displays an approximate signi?cant
correlation with all prize returns for all study periods, with Grey
relational grades between 0.6743 for the jackpot in 2005 and
0.7555 for fourth prize in 2009. In 2005, jackpot returns are only
negligibly correlated with education consumption. Food con-
sumption shows an approximate negligible correlation with all
prize returns for all study periods, and exhibits Grey relational
grades between 0.6156 for the jackpot in 2005 and 0.7016 for the
jackpot in 2006. Jackpot returns are signi?cantly correlated with
food consumption, with a Grey relational grade of 0.7016 in 2006.
In 2004, second, third, and ?fth prizes are signi?cantly correlated
with food consumption, with Grey relational grades of 0.7002,
0.7005, and 0.7003, respectively. However, fourth prize return is
consistently and negatively correlated with food consumption for
all study periods.
Salary sentiment index consistently shows an approximate
negligible correlation with all prize returns throughout the study
period, with the exception of jackpot returns in 2005, when a Grey
relational grade of 0.5743 indicates less than negligible correlation.
Correlations of various prize returns on salary throughout the
period indicate Grey relational grades between 0.5743 for a jackpot
return in 2005 and 0.6553 for a ?fth prize return in 2004.
Thus, jackpot returns display the largest volatility in correlation
with individual sentiment indices, particularly for the study period
2005 for all individual sentiment indices. Consistent correlation
levels are shown for most individual sentiment indices, except for
traveling consumption with alternating levels of in?uences during
the study period. Although jackpot returns are correlated with
alcohol consumption more strongly than tobacco consumption, for
smaller prize returns, including second, third, fourth, and ?fth
prizes, the relationship of the above sentiment indices is reversed.
Restaurant consumption is more strongly correlated with prize
amounts, and is ranked as the third index of sentiment when
compared to the correlations of prize amounts with recreation
consumption. Prize size shows an approximate signi?cant corre-
lationwith education consumption, whereas the correlation of food
consumption with salary is negligible. The Grey relational order,
based on the rankings of Grey relational grades, for individual
sentiment indices, follows this order: tobacco consumption, alcohol
consumption, restaurant consumption, recreation consumption,
traveling consumption, education consumption, food consumption,
and salary.
6. Conclusion
This study attempts to identify the relationship between various
lottery prize returns and household consumption. The degrees of
correlation are identi?ed and ranked sequentially to identify the
correlation of prize returns with consumption patterns. In contrast
to previous investigations focusing on the regression analysis of
household lottery consumption and demographic analysis of lot-
tery participants, this investigation clari?es the interactions of
household consumption with lottery prizes. This investigation at-
tempts to establish reference consumption indices as sentiment
indicators closely related to lottery returns that in?uence house-
hold consumption.
This study includes various lottery prize returns and explores
their approximate correlation with household consumption in
relation to the rational addiction, desperation, and entertainment
hypotheses. This investigation differs from previous investigations
on lottery demand in that lottery prize returns are analyzed ac-
cording to prize size to identify their in?uences on household
consumption. Sentiment indicators for household consumption
items are identi?ed and ranked according to their relationship with
lottery returns.
This investigation demonstrates that lottery prize returns are
strongly correlated with rational addiction category sentiment
indices, which comprise the individual sentiment indices of to-
bacco and alcohol consumption. The ?ndings correspond to those
of Ghent and Grant (2007), Kearney (2005), Lee and Chang (2005),
and Lin and Lin (2007), who indicate that lottery consumption may
be driven by prize designs to encourage rational addictive behavior.
Lottery prizes are also strongly correlated with income category
sentiment index, but their correlation becomes negligible
compared with individual sentiment indices. This ?nding corre-
sponds to Chen et al. (2009) and Haisley et al. (2008), but contra-
dicts Garrett and Sobel (2004). Moreover, lottery prizes are
signi?cantly correlated with the sentiment indices of the desper-
ation category and negligibly correlated with individual sentiment
indices that comprise education and food consumption. This
?nding contradicts that of Landry and Price (2007) due to the likely
lower costs for food and education consumption. Negligible cor-
relations with lottery prizes are demonstrated for the sentiment
indices of the entertainment category and become relatively strong
for individual sentiment indices related to restaurant, recreation,
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 8
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
and traveling consumption. These ?ndings correspond to those of
Blalock et al. (2007), Garrett and Marsh (2002), and Ghent and
Grant (2007), who reveal that households view lottery consump-
tion as a form of entertainment, including travel.
This investigation applies GRA to analyze the relationship be-
tween lottery returns from prizes, household consumption, and
income. It builds on previous studies regarding lotteries by
grouping factors, such as household consumption and macroeco-
nomic conditions, to observe their in?uences on lottery prize
returns. The results indicate that the Taiwanese lottery market is
characterized by a strong correlation with rational addictive con-
sumption, followed by mixed correlations among relatively strong,
signi?cant, and negligible correlations with desperate and enter-
taining consumption. These results differ from those in the previ-
ous literature demonstrating that most desperation or
entertainment consumption behaviors are directed toward lottery
purchases.
7. Contributions of the study
7.1. Theoretical contributions
This investigation contributes to the literature by applying GRA
(Deng, 1982) to extend existing methodologies, including a ques-
tionnaire survey on the demographic analysis of lottery players,
regression analysis of secondary statistical data on the lottery de-
mands of various socioeconomic groups, and lottery game experi-
ments to assess risk behavior among lottery game players (see
Farrell & Walker, 1999; Garrett & Marsh, 2002; Ghent & Grant,
2007; Harley & Lanot, 2006; Ho et al., 2006; Kearney, 2005; Lin &
Lin, 2007; Lin & Wu, 2007; Matheson & Grote, 2004). The GRA
method adopts secondary statistical data to identify factors asso-
ciated with lottery prize returns and household consumption. An
approximate correlation with sequential order rankings by Grey
relational grades is identi?ed via minimal dataset, simple calcula-
tion, and lack of statistical distribution. Therefore, our empirical
research contributes to the application of GRA to identify the de-
gree of correlation among variables, which differs from traditional
regression analysis, survey, or experiment for identifying a causal
relationship.
This study applies GRA to analyze the in?uence of lottery con-
sumption on household expenditure by identifying the theoretical
support for lottery consumption based on rational addiction theory
(corresponding to Balabanis, 2002; Kearney, 2005; Lin &Lin, 2007),
desperation hypothesis (corresponding to Garrett & Marsh, 2002;
Farrell & Forrest, 2008), and entertainment hypothesis (corre-
sponding to Landry & Price, 2007; Lee & Chang, 2005). The indi-
vidual sentiment indices of household consumption are identi?ed
in relation to lottery prizes to explain changes in consumption
priority that occur for lottery prize winners. Additionally, category
sentiment indices are examined in relation to lottery prize returns
and ranked sequentially.
7.2. Applied contributions
This investigation contributes to the literature by examining
the long-term relationship between lottery prizes and household
consumption. Based on theoretical foundations, household con-
sumption expenditures are analyzed in categories and individual
sentiment indices corresponding to lottery prizes ranging from
jackpot to low-tier prizes. Contrary to the previous literature on
causal relationships in lottery demand (Kearney, 2005; Lee &
Chang, 2005), the current study establishes the indicators of
lottery prizes in relation to household consumption with latent
emotional reactions. Sentiments related to rational addiction,
desperation, and entertainment are tested based on their in?u-
ence in providing potential directions for research on lottery
games. Lottery prizes, ranging from jackpot to low-tier prizes, are
successfully demonstrated to contain sentiments to exhibit lot-
tery player behavior as a potential direction for research on
designing lottery prize structures. Thus, our empirical study
successfully applies rational addictive theory (Becker & Murphy,
1988) with household consumption hypotheses to identify the
latent correlation of consumer consumption behavior with lot-
tery prizes.
Our ?ndings clarify the major in?uences on household con-
sumption for lottery prize returns. Sentiment indices are ranked
based on Grey relational grades to identify their importance and
in?uences. The ?ndings indicate that lottery players may not be
desperate to participate in lottery games, which are contrary to
those of Kearney (2005) and Lee and Chang (2005). However,
rational addiction motivations strongly correlate lottery prize
returns and likely consumption items representing motivations
in seeking to win lottery prizes; this ?nding corresponds to those
of Dale (2004) and Doran et al. (2012). Leading category senti-
ment and individual sentiment indicators of lottery consump-
tions are identi?ed to assist lottery development and strategic
positioning for lottery promotions. Contrary to lottery pro-
motions that deal with social welfare (Lee & Chang, 2005), the
lottery market in Taiwan is characterized by more dominant risk-
seeking behavior among lottery players. Furthermore, our
empirical research contributes to policy making by exploring the
possible household consumption alternations induced by lottery
prizes.
7.3. Implications
For implications, we suggest that authorities could permit
strategic alliances between lottery tickets and various business
entities. For example, tobacco or alcohol discount coupons could be
issued, which are accepted at government-owned tobacco and
alcohol stores, for lottery ticket purchases. Similarly, the govern-
ment tourism bureau could authorize the issuances of restaurant,
recreation, and tourism-related discount coupons for each lottery
ticket purchase. Furthermore, government could provide more
medium and small prizes with better payout probabilities to
encourage extended participation duration. Consumers could
participate more in lottery ticket purchases via discount coupons
and lottery prizes.
8. Limitation and future research
This investigation analyzes the relationship between lottery
prize returns and household expenditures in Taipei. A question-
naire survey on lottery player segmentation and lottery demand
model analyses complemented the use of sentiment indices in this
investigation to identify consumption behavior in relation to lot-
tery prizes. Future studies can also analyze the effects of other
lottery products such as scratch cards on consumption sentiment
indices.
Acknowledgments
The author is grateful to the Editor-in-Chief and anonymous
referees for their helpful comments and suggestions that have
signi?cantly improved this paper. The author thanks the Ministry of
Science and Technology (formerly National Science Council) of
Taiwan, ROC, for ?nancially supporting this research under the
grant NSC98-2410-H-006-121.
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 9
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
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A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 10
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Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
doc_991385096.pdf
This study examines the sentimental correlation of lottery prizes with household consumption via Grey
relational analysis. An approximate correlation with sequential order rankings is identified. Results
demonstrate that all top five lottery prizes are strongly correlated with rational addictive consumption
and income categories. These lottery prizes show a relatively strong correlation with entertainment
consumption and a negligible correlation with desperation consumption. Although jackpot exhibits an
approximate strong correlation with alcohol consumption, other prizes show an approximate strong
correlation with tobacco consumption. The top five prizes demonstrate a relatively strong correlation
with restaurant, recreation, and traveling consumption, as well as a negligible correlation with food and
education consumption. Lottery prizes are negligibly correlated with salary with the least sentiment.
Sentimental relationships between lottery participation and household
consumption
Ann Shawing Yang
Institute of International Management, National Cheng Kung University, ROC
a r t i c l e i n f o
Article history:
Received 11 March 2015
Accepted 9 July 2015
Available online xxx
Keywords:
Lottery prize
Rational addiction
Entertainment
Desperation
Sentiments
a b s t r a c t
This study examines the sentimental correlation of lottery prizes with household consumption via Grey
relational analysis. An approximate correlation with sequential order rankings is identi?ed. Results
demonstrate that all top ?ve lottery prizes are strongly correlated with rational addictive consumption
and income categories. These lottery prizes show a relatively strong correlation with entertainment
consumption and a negligible correlation with desperation consumption. Although jackpot exhibits an
approximate strong correlation with alcohol consumption, other prizes show an approximate strong
correlation with tobacco consumption. The top ?ve prizes demonstrate a relatively strong correlation
with restaurant, recreation, and traveling consumption, as well as a negligible correlation with food and
education consumption. Lottery prizes are negligibly correlated with salary with the least sentiment.
© 2015 College of Management, National Cheng Kung University. Production and hosting by Elsevier
Taiwan LLC. All rights reserved.
1. Introduction
Lottery prizes often attract considerable public interest with
increased and extended participation (Haruvy, Erev, & Sonsino,
2001; Rogers & Webley, 2001; Sharpira & Venezia, 1992; Thaler &
Ziemba, 1988). Consumer participation in lottery is in?uenced not
only by jackpot prizes for lifetime winnings, but also by medium
prizes to extend participation duration (Haruvy et al., 2001; Thaler
& Ziemba, 1988). In particular, lottery participation increased from
26.6% with a single prize to 37.7% with multiple prizes (Haruvy
et al., 2001). Consumers increase lottery participation for large
jackpot prize opportunities, but also use small prize winnings to
continue toward jackpot prize winnings (Rogers & Webley, 2001;
Sharpira & Venezia, 1992). Therefore, consumers voluntarily
contribute to lottery prizes in which lottery sales determine the
prize structures (Dale, 2004).
Nevertheless, consumers may develop irrational or rational
decision making via lottery prize structures with unknown prob-
abilities of winning toward jackpot, rollover, or low-tier prizes (Lin,
Kang, & Chan, 2005; Lin & Wang, 2004; Matheson & Grote, 2004).
Thus, consumers exhibit rational addictive behavior toward large
jackpot prizes with increased participation (Doran, Jiang, &
Peterson, 2012). Moreover, the accumulations of rollovers
encourage the development of lotto mania behavior among
increased numbers of participants (Beenstock & Haitovsky, 2001;
Harley & Lanot, 2006; Peel, 2010). Therefore, lottery games assist
in developing sentimental reactions for hope and fear via regret
aversion decision making for extended participation (Statman,
2002).
Additionally, consumers determine lottery participation and
duration based on prize payout rates (P erez & Humphreys, 2011).
However, consumers may determine lottery participation based on
income and consumption behavior changes (Kuhn, Kooreman,
Soetevent, & Kapteyn, 2011; P erez & Humphreys, 2011). Increases
in income encourage existing consumers to purchase more national
lottery tickets instead of attracting new potential consumers (P erez
& Humphreys, 2011). Consumers with lottery prize winnings
signi?cantly show ownership of newly purchased cars as well as
spend more on food away from home and durables excluding cars;
by contrast, their counterparts signi?cantly exhibit greater monthly
expenditures, including food away from home and other expendi-
tures, renovation expenditures, durables, and more donations to
charity (Kuhn et al., 2011). From the perspective of household
consumption behavior, consumer sentiment reactions may relate
closely to speci?c expenditures for addictive, recreation, or daily
necessity purchases. Addictive research hypothesis indicates that
tobacco and alcohol expenditures re?ect rational addiction
E-mail address: [email protected].
Peer review under responsibility of College of Management, National Cheng
Kung University.
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Asia Paci?c Management Review xxx (2015) 1e10
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Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
sentiment (Balabanis, 2002; Kearney, 2005; Lin & Lin, 2007).
Entertainment research hypothesis states that restaurant, recrea-
tion, and traveling expenditures signify entertainment sentiment
(Farrell & Forrest, 2008; Garrett & Marsh, 2002). Daily necessity
research hypothesis posits that food and education expenditures
(i.e., basic family consumption) represent desperation sentiment in
which such expenditures are necessary for maintaining basic living
standards (Landry & Price, 2007; Lee & Chang, 2005).
Thus, our empirical study is motivated by rational addictive
theory (Becker & Murphy, 1988), accompanied by the various
household consumption research hypotheses to identify senti-
ment reactions from lottery participation. We further expand
lottery sentiment reaction analysis from jackpot prize to low-tier
prizes. We analyze the in?uence of multiple prize structures for
lottery games toward consumer decision making and behavior.
This study aims to bridge the gap between higher and lower tier
prizes by identifying the likely sentiments regarding each prize
amount.
Despite existing studies on the demographic and socioeconomic
analysis of lottery participation (Farrell & Walker, 1999; Garrett &
Marsh, 2002; Ghent & Grant, 2007; Harley & Lanot, 2006; Ho,
Lee, & Lin, 2006; Kearney, 2005; Lin & Lin, 2007; Lin & Wu,
2007; Matheson & Grote, 2004), the relationship between lottery
prize structures and sentimental consumption has not been
established. In contrast to previous studies focusing on the causal
relationship between lottery demand and demographic back-
ground (Farrell & Walker, 1999; Garrett & Marsh, 2002; Ghent &
Grant, 2007; Harley & Lanot, 2006; Ho et al., 2006; Kearney,
2005; Lin & Lin, 2007; Lin & Wu, 2007; Matheson & Grote,
2004), we propose Grey relational analysis (GRA) (Deng, 1982) to
identify the approximate correlation between consumption senti-
ment and lottery prizes for the order rankings of sequence in-
?uences for households. A sequential relationship, ranked by orders
of Grey relational grades, is identi?ed for individual and category
sentiment indices comprising rational addiction, entertainment,
and desperation behavior for various prize returns. The application
of GRA builds on other models in identifying the in?uences on
lottery consumption. GRA not only provides an order relation of
variables by rankings of Grey relational grades, but also identi?es
the latent in?uences of variables that are less likely to be detectable
using other methods. The government and authorities may refer to
the empirical results in considering the formation of strategic al-
liances, formulation of promotional campaigns, and designing of
lottery games. Meanwhile, lottery players may refer to the empir-
ical results in determining the sentiment indicators on lottery
purchases.
2. Literature review and theory
Rational addictive behavior generally in?uences lottery con-
sumption by individual players, and lotteries possess addictive
characteristics (Chang, 2004; Moore, 1997). The total prize amount
strongly affects participation in lottery consumption, whereas the
increased consumption of tobacco and alcohol is associated with
increased consumption demand in lotteries (Lin & Lin, 2007; Zeng,
2006). Heavier smokers also tend to purchase more lottery tickets
as an addictive and compulsive behavior (Balabanis, 2002). Thus,
bounded rationality exists in lottery games in which most players
react more to jackpots and respond less to smaller games with
higher returns (Grote & Matheson, 2006). The level of rational
addiction is the major in?uence on lottery consumption (Chang,
2004; Harley & Lanot, 2006; Lin & Lin, 2007). Addictive products,
such as tobacco, alcohol, and betel nuts, strongly in?uence lottery
consumption (Chang, 2004; Kearney, 2005; Landry & Price, 2007).
Low ticket prices similarly encourage lottery players to assume a
higher risk than they otherwise would (Haisley, Mostafa, &
Loewenstein, 2008).
Households may reduce their expenditure on non-addictive
purchases, such as education, grocery, mortgage, rent, and other
bills, to participate in lotteries (Kearney, 2005; Lee & Chang,
2005). The allocation of lottery proceeds to fund education en-
courages lottery sales (Landry & Price, 2007). Household expen-
diture on groceries and entertainment is most likely to be
replaced by consumption needs in lotteries to improve the eco-
nomic situation (Kearney, 2005; Lee & Chang, 2005). Therefore,
restaurant expenditure negatively and signi?cantly in?uences
lottery sales; by contrast, tourism in?uences lottery sales because
players seeking lottery prizes are willing to travel to increase
their probability of winning (Farrell & Forrest, 2008; Garrett &
Marsh, 2002).
Household income also in?uences lottery participation to
improve economic conditions or seek entertainment (Garrett &
Marsh, 2002; Ghent & Grant, 2007). Higher income households
participate in lottery games for entertainment, whereas lower in-
come households do so to improve their economic conditions
(Ghent & Grant, 2007). However, income is also insigni?cantly
related to lottery sales (Chen, Chie, Fan, & Yu, 2009). Nevertheless,
income level and employment status may affect lottery consump-
tion (Lin & Lin, 2007). A decrease in economic ability tends to in-
crease lottery purchases and thus improve the quality of life and
economic conditions (Blalock, Just, & Simon, 2007; Garrett &
Marsh, 2002; Ghent & Grant, 2007).
2.1. Theory
Rational addictive theory, proposed by Becker and Murphy
(1988), focuses on products with the potential to be addictive,
including cigarettes. When making purchasing decisions, con-
sumers consider and transform purchase price, product usage, and
added value as their needs. Factors affecting the need for addictive
products may include stress and income. Particularly, purchase
prices are deterministic in encouraging addictive purchase
behavior (Becker & Murphy, 1988). Therefore, rational addictive
consumer behavior is more likely to develop predictive consump-
tion behavior that is in?uenced by purchase price, product func-
tion, and product added value (Harris & Harris, 1996). Consumers
with an addictive behavior toward products are more likely to be
in?uenced by personal preferences and engage in long-term and
regular consumption of addictive products (Miljkovic, Nganje, & de
Chastenet, 2008).
National lottery games not only encourage consumers to dou-
ble their consumption, but also induce a four-fold increase in the
excessive consumption toward addiction among households (Grun
& McKeigue, 2000). Lottery games with frequent advertisements
are also often viewed as an acceptable gamble with accessible
stores and affordable ticket prices, thus engendering the addiction
behavior of consumers in which they participate in lottery games
via past experiences to exert an illusion of control over their daily
lives (Hardoon, Baboushkin, Derevensky, & Gupta, 2001). In the
case of lottery participation, addictive consumption is common in
less educated households (Grun & McKeigue, 2000; Shepherd,
Ghodse, & London, 1998). Thus, lottery games induce addictive
consumption in which less educated households spend more than
their counterparts at an average of ?2.42 per week on scratch
cards or lottery tickets compared with ?1.84 per week, particularly
for households with an annual income of less than ?20,000
(Shepherd et al., 1998). Low-income households also exhibit the
highest percentage in spending more than 10% of income on lot-
tery tickets, thus spurring addictive consumption (Grun &
McKeigue, 2000).
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 2
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
3. Method
This study uses GRA, proposed by Deng (1982), to solve prob-
lems involving incomplete information systems or missing statis-
tics. Based on Grey system theory, GRA can effectively deal with
small sets of data containing indeterminate values, having multiple
inputs, or are incomplete (Deng, 2000). Contrary to probability and
statistical theories that are used in treating large samples of un-
certain data, Grey system theory can treat uncertain acknowledged
sets (Lui & Hsu, 1996).
Grey relational analysis identi?es a sequential relationship
among factors according to Grey relational grades that systemati-
cally rank the degrees of in?uence (Fu, 1992; Tzeng & Tsaur, 1994).
Grey relational grades pertain to the relationship between two
series of systems or factors, including howthey are affected by time
or other elements (Huang & Jane, 2007). Order relation, the key
feature of GRA, can be used to identify the relationship between
two sequences (Wang, 2008). An approximate correlation is thus
identi?ed using GRA between an objective factor and several
affecting factors in a system characterized by limited data, simple
calculations, and lack of statistical distribution (Chen & Tzeng,
2004; Lu, Lin, & Lewis, 2008). The advantages of GRA include the
avoidance of defects common in conventional, large sample sta-
tistical methods, simple calculation, minimal data requirements,
and quanti?ed results that do not con?ict with those of qualitative
analysis (Li, Yamaguchi, Nagai, & Masuda, 2008; Lin & Chang,
2008). Thus, GRA potentially offers a reliable extension of existing
methodologies.
3.1. Procedure
This study uses GRA to examine the relative value of nine in-
dividual sentiment indices and ultimately identify the variable that
exerts the strongest in?uence on lottery returns using Grey rela-
tional software. Individual sentiment indices are compared based
on the orders of Grey relational grades and evaluated according to
the values of individual series indices. First, this investigation ver-
i?es the monthly data using Grey data processing to normalize and
transform data expressed using different measurement units into a
single numerical order (Chang & Lin, 1999). The direct application
of raw data is also permitted if they meet the requirements of
comparability, namely non-dimensionality, scaling, and polariza-
tion (Wang, 2008).
x
i
ðkÞ ¼
x
ð0Þ
i
ðkÞ Àmin
k
x
ð0Þ
i
ðkÞ
max
k
x
ð0Þ
i
ðkÞ Àmin
k
x
ð0Þ
i
ðkÞ
; (1)
where x is the index variable, i represents the various prize returns
obtained during the ith month, and k denotes the variable values of
the sentiment index during the ith month.
Second, prior to obtaining the Grey relational coef?cient from
Equation (2), this investigation applies Equation (3) to identify the
absolute difference between two sequences and thus demonstrate
their relationship with the entire system (Lu et al., 2008). Term z is
an identi?cation coef?cient that is used in adjusting the difference
between relational coef?cients (Lu et al., 2008). For stability and
clarity, a value of 0.5 is widely applied (Fu, Zheng, & Zhao, 2001; Lu
et al., 2008; Wang, 2008). In this case, x
0
(k) denotes the reference
value of Grey relational calculation, x
i
(k) represents the compared
value of sentiment index k on the ith month, zD
max
is the value of
the distinguishing coef?cient multiplied by the maximum differ-
ence between the compared series x
i
and reference series x
0
, and
D
0i
(k) represents the difference between the collection of compared
series and the reference series of Grey relational factors.
gðx
0
ðkÞ; x
i
ðkÞÞ ¼
D
min
þzD
max
D
0i
ðkÞ þzD
max
; (2)
where:
1: D
0i
ðkÞ ¼ jx
0
ðkÞ À x
i
ðkÞj (3)
Equation (3) expresses the absolute difference between the
compared and reference series.
2: D
min
¼ min
i
min
k
jx
0
ðkÞ À x
i
ðkÞj (4)
3: D
max
¼ max
i
max
k
jx
0
ðkÞ À x
i
ðkÞj (5)
Equations (4) and (5) are subsequently used to determine the
minimum and maximum distances in all of the compared se-
quences (Chang & Lin, 1999; Lu et al., 2008). D
min
and D
max
should
be respectively de?ned as the minimum and maximum difference
between the compared series x
i
and reference series x
0
, where k
represents the value of sentiment index.
4: z ¼ identification coefficient z2½0; 1? (6)
Equation (6) is also applied, where z is a distinguished identi-
?cation coef?cient, with z2[0, 1] used in adjusting the difference
between D
0i
and D
max
(Fu et al., 2001; Wang, 2008). The Grey
relational coef?cient is subsequently calculated using Equation (2).
Grey relational grade is calculated using Equation (7). Grey
relational grade g (x
0
, x
i
) represents the in?uence between the
measured elements that are de?ned using Equation (7).
gðx
0
; x
i
Þ ¼
X
n
k¼1
b
k
gðx
0
ðkÞ; x
i
ðkÞÞ; (7)
where b
k
denotes k normweight and
P
n
k¼1
b
k
¼ 1 (Ho & Lin, 2003).
This study ranks the sequences according to the Grey relational
order, from the most related to the least related. The relationship
between investor sentiment indices and price volatility is ranked
and termed the Grey relational rank (g). A Grey relational rank
value exceeding 0.9 indicates a strong in?uence, a value between
0.8 and 0.9 connotes a relatively strong in?uence, a value between
0.7 and 0.8 denotes a signi?cant in?uence, and a value between 0.6
and 0.7 shows a negligible in?uence (Fu et al., 2001).
3.2. GRA example
We illustrate an example of the application of GRA. We obtain
monthly jackpot prize returns and tobacco expenditures from
January to December 2002. Columns 1 and 2 present the raw data
for jackpot prize returns (x
01
) and tobacco expenditures (in ln form)
(x
21
), respectively. In the ?rst step, data normalization is conducted
by taking the monthly values divided by the January value for both
jackpot prize returns in Column 3 and tobacco expenditures in
Column 4. Considering that January is determined as the base
month, data normalization for January will become 1.0 for both
jackpot prize returns and tobacco expenditures. In the second step,
the absolute difference values are computed by the difference be-
tween Columns 3 and 4; we take Column 3 minus Column 4 and
obtain the absolute value on a monthly basis (corresponding to
Equation (3)). In step three, we identify the minimum and
maximum values from Column 5 (corresponding to Equations (4)
and (5)). In step four, we take 0.5 multiplied by the maximum
value from Column 7 to adjust the difference between D
0i
(k) and
Dmax and derive an adjusted value zDmax (corresponding to
Equation (6)). In step ?ve, Grey relational coef?cients are calculated
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 3
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
according to Equation (2). In step six, we sum up all of the Grey
relational coef?cients and take the average value to identify the
Grey relational grade (corresponding to Equation (7)). The obtained
Grey relational grade is compared for correlational relationship to
identify the importance order and sequential order with other
variables Table 1.
4. Research design
4.1. Selection of variables
This study follows Doran et al. (2012), Lin and Wu (2007), and
Kearney (2005) in selecting and categorizing variables. Variables
representing lottery returns are segmented into high- and low-tier
prizes. Variables representing household consumption are classi-
?ed into different groups based on whether they are used for the
rational addiction hypothesis, desperation hypothesis, or enter-
tainment hypothesis. Table 2 lists the categories of variable selec-
tions. Three categories are studied, namely, lottery purchase,
household consumption, and income.
4.2. Lottery returns
Lottery returns from a jackpot are frequently viewed as the
primary motivation in lottery consumption (Garrett & Sobel, 2004).
Although low-tier prizes from smaller lottery games may also yield
high returns, they are frequently ignored owing to the prizes
offered through jackpots (Grote & Matheson, 2006). Prize sizes,
ranging from a jackpot win to various smaller prizes, represent the
various probabilities of winning the lottery (Maeda, 2008). The
current study selected jackpot (Jackpt), second prize (2nd Pz), third
prize (3rd Pz), fourth prize (4th Pz), and ?fth prize (5th Pz) returns
to identify the relationship between different prize sizes and
household consumption. The ratio of prize sizes to lottery sales is
calculated using each prize.
4.3. Household expenditures
Household expenditure variables are classi?ed into desperation
hypothesis, rational addiction hypothesis, and entertainment hy-
pothesis. This study refers to Landry and Price (2007), Balabanis
(2002), Kearney (2005), and Garrett and Marsh (2002) for the se-
lection of variables to indicate household consumption. Food ex-
penditures (Fd) and education expenditures (Edu) are selected to
represent expenditures for the desperation hypothesis. Tobacco
expenditures (Toba) and alcohol expenditures (Alcho) are selected
to represent expenditures for the rational addiction hypothesis.
Restaurant expenditures (Resto), recreation expenditures (Rec), and
traveling expenditures (Trvl) are selected to represent expenditures
for the entertainment hypothesis.
4.4. Income
According to Garrett and Sobel (2004), income is a signi?cant
indicator of lottery sales. Ghent and Grant (2007) report that a
higher income encourages greater lottery participation. Salary
(Salry) is thus adjusted to identify the relationship between prize
size and income for lottery purchases.
4.5. Study period and data sources
This study uses monthly data for 2002e2010 to identify the
relationship between lottery prize returns and household con-
sumption. Eight sentiment indices are selected for each of the ?ve
types of lottery prize returns for each month of the year. A total of T
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A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 4
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
108 observations consist of 12 monthly values from January to
December for 9 years; 8 sentiment indices multiplied by 108
months result in 864 entries. Statistical lottery data are obtained
from the Taiwan Lottery Company. The Taiwan Lottery Company,
which is the only government-authorized sales agent for national
lottery tickets, is located in Taipei, the capital of Taiwan. House-
hold expenditure statistics are obtained from the Directorate
General of Budget, Accounting and Statistics of the Taipei City
Government. Data on average monthly salary are obtained from
the Directorate General of Budget, Accounting and Statistics, Ex-
ecutive Yuan.
5. Results and analysis
This study analyzes the in?uences of ?ve different lottery prize
returns on household consumption in Taipei. Each lottery prize
return, including those for the jackpot, second, third, fourth, and
?fth prizes, is individually analyzed for the period 2002e2010. For
each type of prize return, eight individual sentiment indices are
selected and compared among four sentiment categories
throughout the study period. Table 3 lists the results for various
lottery returns and category sentiment indices, whereas Table 4
lists the results for various lottery returns and individual senti-
ment indices.
5.1. Category sentiment indices and lottery returns
Table 3 lists the four categories of sentiment indices, namely
desperation category, rational addiction category, entertainment
category, and income category, and ranks them according to Grey
relational grades for all prize returns throughout all study periods.
Rational addiction category indices consistently show an approxi-
mate strong correlation of various prize returns with household
consumptions, with Grey relational grades ranging between 0.9497
(for jackpot return in 2005) and 0.9887 (for ?fth prize return in
2006). Jackpot returns on rational addiction category exhibit an
approximate strong correlation, with Grey relational grades
ranging from 0.9497 to 0.9850 throughout the study period; by
contrast, smaller prizes show Grey relational grade values between
0.9686 and 0.9862 (second prize return), 0.9693 and 0.9853 (third
prize return), 0.9686 and 0.9857 (fourth prize return), and 0.9686
and 0.9887 (?fth prize return), respectively.
The sentiment indices of the income category also display an
approximate strong correlation with all prize returns throughout
the study period, with Grey relational grades between 0.9242 (for
jackpot return in 2005) and 0.9834 (for ?fth prize return in 2006).
Jackpot returns are strongly correlated with income category, with
Grey relational grades between 0.9242 and 0.9794, and the ranking
in terms of strength of correlation subsequently follows this order:
smaller prize returns between 0.9562 and 0.9808 (second prize
return), between 0.9585 and 0.9808 (third prize return), between
0.9563 and 0.9810 (fourth prize return), and between 0.9562 and
0.9834 (?fth prize return).
The sentiment indices of the desperation category show an
approximate signi?cant correlation with all prize returns
throughout the study period, with Grey relational grades between
0.6321 (for jackpot return in 2005; negligible in?uence) and 0.7270
(for ?fth prize return in 2006). Jackpot returns are signi?cantly
correlated with desperation category sentiment indices, with Grey
relational grades between 0.6321 and 0.7216. In 2005, jackpot
returns are only negligibly correlated with desperation category
sentiment indices, with a Grey relational grade value of 0.6321.
Furthermore, the correlation of smaller prizes with household
consumption classi?ed as desperation category is signi?cant, with
Grey relational grades between 0.7097 and 0.7267 (second prize
return), between 0.7095 and 0.7269 (third prize return), between
0.7084 and 0.7266 (fourth prize return), and between 0.7091 and
0.7270 (?fth prize return).
The sentiment indices of the entertainment category, ranked
with the least correlation according to Grey relational grades,
display a negligible correlation with all prize returns for all study
periods, with Grey relational grades between 0.6200 (for jackpot
return in 2005) and 0.6651 (for ?fth prize return in 2006). The
various Grey relational grades for all prizes range from 0.6200 to
0.6594 for jackpot return, from 0.6465 to 0.6643 for second prize
return, from 0.6466 to 0.6642 for third prize return, from 0.6526 to
0.6642 for fourth prize return, and from 0.6524 to 0.6651 for ?fth
prize return.
Jackpot returns display the largest volatility in correlation with
various category sentiment indices. Thus, jackpot returns display a
range of Grey relational grades from 0.9497 to 0.9850 for the
rational addiction category; from 0.9242 to 0.9794 for the income
category; from 0.6321 to 0.7216 for the desperation category; and
from 0.6200 to 0.6594 for the entertainment category. However,
smaller prize returns display relatively stable Grey relational grade
values throughout the study period from 2002 to 2010 for all
category sentiment indices. Although lottery prizes are consistently
strongly correlated with the income category, with Grey relational
grades exceeding 0.9, rational addiction category sentiment indices
display a stronger correlation. Therefore, the category sequence of
Grey relational grades is as follows: rational addiction, income,
desperation, and entertainment.
Table 2
Category and individual factors affecting lottery sentiment.
Segmentation Category sentiment indices Individual sentiment indices Symbols De?nition
a
Lottery x
0
Lottery returns x
01
Jackpot returns Pz
jack
Jackpot amount
t
/Sales amount
t
x
02
Second Prize returns Pz
2
Second Prize amount
t
/Sales amount
t
x
03
Third Prize returns Pz
3
Third Prize amount
t
/Sales amount
t
x
04
Fourth Prize returns Pz
4
Fourth Prize amount
t
/Sales amount
t
x
05
Fifth Prize returns Pz
5
Fifth Prize amount
t
/Sales amount
t
Household consumption x
1
Desperation x
11
Food Fd Ln(Food
t
)
x
12
Education Edu ln(Edu
t
)
x
2
Rational Addiction x
21
Tobacco Toba Ln(Tobac)
x
22
Alcohol Alcoh ln(Alcol
t
)
x
3
Entertainment x
31
Restaurant Resto Ln(Resto
t
)
X
32
Recreation Recre ln(Recre
t
)
x
33
Traveling Trvl Ln(Travl
t
)r
Income x
4
Income x
41
Salary Salry ln(Salary
t
)
a
Note: Lotto represents lottery sales, Food represents food consumption, Edu represents educational consumption, Tobac represents tobacco consumption, Alcol represents
alcohol consumption, Recre represents recreational consumption, Resto represents restaurant dinning consumption, Trvl represents traveling consumption, and Salry rep-
resents salary received.
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 5
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
Table 3
Grey relation coef?cients and relational grade ranking 2002e2010 e category indices.
Category
sentiment
indices
Jackpot e Relational grades and rankings Second prize e Relational grades and ranking
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Desperation 0.7168 (3) 0.7087 (3) 0.7216 (3) 0.6321 (3) 0.7201 (3) 0.7156 (3) 0.7074 (3) 0.7196 (3) 0.7203 (3) 0.7178 (3) 0.7097 (3) 0.7267 (3) 0.7192 (3) 0.7258 (3) 0.7217 (3) 0.7113 (3) 0.7236 (3) 0.7246 (3)
Rational
addiction
0.9844 (1) 0.9773 (1) 0.9801 (1) 0.9497 (1) 0.9850 (1) 0.9792 (1) 0.9696 (1) 0.9806 (1) 0.9753 (1) 0.9841 (1) 0.9768 (1) 0.9849 (1) 0.9851 (1) 0.9862 (1) 0.9850 (1) 0.9686 (1) 0.9831 (1) 0.9790 (1)
Entertainment 0.6576 (4) 0.6559 (4) 0.6555 (4) 0.6200 (4) 0.6594 (4) 0.6464 (4) 0.6488 (4) 0.6524 (4) 0.6496 (4) 0.6587 (4) 0.6570 (4) 0.6606 (4) 0.6465 (4) 0.6643 (4) 0.6532 (4) 0.6523 (4) 0.6566 (4) 0.6535 (4)
Income 0.9721 (2) 0.9586 (2) 0.9747 (2) 0.9242 (2) 0.9794 (2) 0.9674 (2) 0.9550 (2) 0.9705 (2) 0.9550 (2) 0.9719 (2) 0.9582 (2) 0.9796 (2) 0.9590 (2) 0.9808 (2) 0.9733 (2) 0.9562 (2) 0.9732 (2) 0.9587 (2)
Category sent-
iment indices
Third prize e Relational grades and ranking Fourth prize e Relational grades and ranking
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Desperation 0.7180 (3) 0.7095 (3) 0.7269 (3) 0.7192 (3) 0.7257 (3) 0.7168 (3) 0.7119 (3) 0.7239 (3) 0.7245 (3) 0.7174 (3) 0.7084 (3) 0.7266 (3) 0.7192 (3) 0.7257 (3) 0.7215 (3) 0.7116 (3) 0.7239 (3) 0.7246 (3)
Rational
addiction
0.9846 (1) 0.9768 (1) 0.9853 (1) 0.9853 (1) 0.9861 (1) 0.9847 (1) 0.9693 (1) 0.9834 (1) 0.9788 (1) 0.9855 (1) 0.9764 (1) 0.9852 (1) 0.9857 (1) 0.9864 (1) 0.9849 (1) 0.9686 (1) 0.9834 (1) 0.9788 (1)
Entertainment 0.6588 (4) 0.6569 (4) 0.6607 (4) 0.6466 (4) 0.6642 (4) 0.6477 (4) 0.6528 (4) 0.6569 (4) 0.6534 (4) 0.6581 (4) 0.6557 (4) 0.6604 (4) 0.6465 (4) 0.6642 (4) 0.6531 (4) 0.6526 (4) 0.6569 (4) 0.6535 (4)
Income 0.9724 (2) 0.9583 (2) 0.9800 (2) 0.9592 (2) 0.9808 (2) 0.9727 (2) 0.9569 (2) 0.9734 (2) 0.9585 (2) 0.9732 (2) 0.9578 (2) 0.9798 (2) 0.9595 (2) 0.9810 (2) 0.9732 (2) 0.9563 (2) 0.9735 (2) 0.9585 (2)
Category
sentiment
indices
Fifth prize e Relational grades and ranking
2002 2003 2004 2005 2006 2007 2008 2009 2010
Desperation 0.7174 (3) 0.7091 (3) 0.7267 (3) 0.7193 (3) 0.7270 (3) 0.7217 (3) 0.7115 (3) 0.7237 (3) 0.7244 (3)
Rational Addiction 0.9842 (1) 0.9767 (1) 0.9850 (1) 0.9855 (1) 0.9887 (1) 0.9852 (1) 0.9686 (1) 0.9834 (1) 0.9788 (1)
Entertainment 0.6582 (4) 0.6564 (4) 0.6606 (4) 0.6466 (4) 0.6651 (4) 0.6531 (4) 0.6524 (4) 0.6567 (4) 0.6533 (4)
Income 0.9720 (2) 0.9582 (2) 0.9796 (2) 0.9594 (2) 0.9834 (2) 0.9735 (2) 0.9562 (2) 0.9734 (2) 0.9585 (2)
Note: Grey relational category indices are presented by sentiment categories for all prizes for the period from 2002 to 2010. Lottery prize categories include jackpot, second, third, fourth, and ?fth prizes, which are ranked
according to sentiment on desperation, rational addiction, and entertainment, plus income. Rational addiction sentiment shows a strong sentimental correlation with lottery participation, with Grey relational grades (GRA
grades
)
above 0.9, followed by income with a relatively strong correlation (GRA
grades
between 0.8 and 0.9), desperation with a signi?cant correlation (GRA
grades
between 0.7 and 0.8), and entertainment with a negligible correlation
(GRA
grades
between 0.6 and 0.7) for all prizes.
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Table 4
Grey relation coef?cients and relational grade rankingseindividual sentiment indices.
Indiv. Sentmt
Indice
Jackpot e Relational grades and rankings Second prize e Relational grades and rankings
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Fd 0.6852 (7) 0.6805 (7) 0.6891 (7) 0.6156 (7) 0.7016 (7) 0.6931 (7) 0.6532 (7) 0.6764 (7) 0.6897 (7) 0.6868 (7) 0.6794 (7) 0.7002 (7) 0.6673 (7) 0.6944 (7) 0.6889 (7) 0.6567 (7) 0.6845 (7) 0.6983 (7)
Edu 0.7341 (6) 0.7291 (6) 0.7444 (6) 0.6743 (6) 0.7529 (6) 0.7467 (6) 0.7172 (6) 0.7471 (6) 0.7333 (6) 0.7353 (6) 0.7275 (6) 0.7552 (6) 0.7297 (6) 0.7446 (6) 0.7412 (6) 0.7205 (6) 0.7547 (6) 0.7419 (6)
Tobac 0.9635 (2) 0.9520 (2) 0.9555 (2) 0.8553 (2) 0.9690 (2) 0.9625 (2) 0.9302 (2) 0.9569 (2) 0.9538 (2) 0.9791 (1) 0.9806 (1) 0.9867 (1) 0.9842 (1) 0.9880 (1) 0.9884 (1) 0.9264 (2) 0.9779 (1) 0.9681 (2)
Alcho 0.9708 (1) 0.9557 (1) 0.9649 (1) 0.8741 (1) 0.9733 (1) 0.9698 (1) 0.9374 (1) 0.9620 (1) 0.9609 (1) 0.9689 (2) 0.9500 (2) 0.9738 (2) 0.9386 (2) 0.9588 (2) 0.9585 (2) 0.9391 (1) 0.9673 (2) 0.9683 (1)
Recre 0.8444 (4) 0.8343 (4) 0.8486 (4) 0.7633 (3) 0.8601 (4) 0.8514 (4) 0.8078 (4) 0.8379 (4) 0.8212 (4) 0.8443 (4) 0.8310 (4) 0.8589 (4) 0.8224 (3) 0.8490 (4) 0.8435 (4) 0.8106 (4) 0.8448 (4) 0.8296 (4)
Resto 0.8513 (3) 0.8514 (3) 0.8594 (3) 0.7518 (4) 0.8826 (3) 0.8585 (3) 0.8334 (3) 0.8563 (3) 0.8411 (3) 0.8511 (3) 0.8478 (3) 0.8696 (3) 0.8106 (4) 0.8708 (3) 0.8504 (3) 0.8359 (3) 0.8632 (3) 0.8494 (3)
Trvl 0.8092 (5) 0.8158 (5) 0.7996 (5) 0.7204 (5) 0.8143 (5) 0.7974 (5) 0.7689 (5) 0.7875 (5) 0.8023 (5) 0.8095 (5) 0.8128 (5) 0.8100 (5) 0.7774 (5) 0.8043 (5) 0.7907 (5) 0.7717 (5) 0.7950 (5) 0.8108 (5)
Salry 0.6414 (8) 0.6364 (8) 0.6441 (8) 0.5743 (8) 0.6573 (8) 0.6496 (8) 0.6139 (8) 0.6382 (8) 0.6273 (8) 0.6433 (8) 0.6358 (8) 0.6552 (8) 0.6238 (8) 0.6511 (8) 0.6462 (8) 0.6176 (8) 0.6463 (8) 0.6357 (8)
Indiv. Sentmt
Indice
Third prize e Relational grades and rankings Fourth prize e Relational grades and rankings
2002 2003 2004 2005 2006 2007 2008 2009 2010 2002 2003 2004 2005 2006 2007 2008 2009 2010
Fd 0.6869 (7) 0.6811 (7) 0.7005 (7) 0.6674 (7) 0.6944 (7) 0.6889 (7) 0.6577 (7) 0.6734 (7) 0.6981 (7) 0.6850 (7) 0.6776 (7) 0.6996 (7) 0.6623 (7) 0.6937 (7) 0.6891 (7) 0.6572 (7) 0.6852 (7) 0.6983 (7)
Edu 0.7354 (6) 0.7293 (6) 0.7557 (6) 0.7299 (6) 0.7446 (6) 0.7412 (6) 0.7215 (6) 0.7454 (6) 0.7417 (6) 0.7336 (6) 0.7259 (6) 0.7547 (6) 0.7244 (6) 0.7440 (6) 0.7414 (6) 0.7209 (6) 0.7555 (6) 0.7419 (6)
Tobac 0.9797 (1) 0.9834 (1) 0.9875 (1) 0.9847 (1) 0.9881 (1) 0.9884 (1) 0.9279 (2) 0.9773 (1) 0.9677 (2) 0.9803 (1) 0.9814 (1) 0.9872 (1) 0.9783 (1) 0.9877 (1) 0.9887 (1) 0.9266 (2) 0.9785 (1) 0.9677 (2)
Alcho 0.9694 (2) 0.9527 (2) 0.9745 (2) 0.9390 (2) 0.9588 (2) 0.9585 (2) 0.9404 (1) 0.9662 (2) 0.9680 (1) 0.9700 (2) 0.9504 (2) 0.9742 (2) 0.9327 (2) 0.9584 (2) 0.9588 (2) 0.9392 (1) 0.9679 (2) 0.9680 (1)
Recre 0.8446 (4) 0.8332 (4) 0.8595 (4) 0.8227 (3) 0.8490 (4) 0.8435 (4) 0.8119 (4) 0.8384 (4) 0.8293 (4) 0.8438 (4) 0.8302 (4) 0.8588 (4) 0.8169 (3) 0.8484 (4) 0.8437 (4) 0.8110 (4) 0.8456 (4) 0.8294 (4)
Resto 0.8514 (3) 0.8501 (3) 0.8701 (3) 0.8109 (4) 0.8708 (3) 0.8504 (3) 0.8372 (3) 0.8574 (3) 0.8491 (3) 0.8507 (3) 0.8471 (3) 0.8695 (3) 0.8051 (4) 0.8703 (3) 0.8506 (3) 0.8362 (3) 0.8639 (3) 0.8492 (3)
Trvl 0.8097 (5) 0.8149 (5) 0.8105 (5) 0.7776 (5) 0.8043 (5) 0.7908 (5) 0.7729 (5) 0.7869 (5) 0.8105 (5) 0.8086 (5) 0.8118 (5) 0.8097 (5) 0.7720 (5) 0.8037 (5) 0.7909 (5) 0.7721 (5) 0.7958 (5) 0.8106 (5)
Salry 0.6426 (8) 0.6369 (8) 0.6549 (8) 0.6235 (8) 0.6508 (8) 0.6461 (8) 0.6183 (8) 0.6350 (8) 0.6358 (8) 0.6413 (8) 0.6338 (8) 0.6544 (8) 0.6189 (8) 0.6504 (8) 0.6463 (8) 0.6180 (8) 0.6471 (8) 0.6358 (8)
Indiv. Sentmt Indice Fifth prize e Relational grades and rankings
2002 2003 2004 2005 2006 2007 2008 2009 2010
Fd 0.6849 (7) 0.6794 (7) 0.7003 (7) 0.6675 (7) 0.6527 (7) 0.6884 (7) 0.6567 (7) 0.6847 (7) 0.6979 (7)
Edu 0.7335 (6) 0.7277 (6) 0.7553 (6) 0.7300 (6) 0.7014 (6) 0.7408 (6) 0.7205 (6) 0.7550 (6) 0.7415 (6)
Tobac 0.9787 (1) 0.9827 (1) 0.9868 (1) 0.9850 (1) 0.9404 (1) 0.9882 (1) 0.9264 (2) 0.9784 (1) 0.9677 (2)
Alcho 0.9684 (2) 0.9518 (2) 0.9739 (2) 0.9393 (2) 0.9108 (2) 0.9583 (2) 0.9390 (1) 0.9678 (2) 0.9680 (1)
Recre 0.8430 (4) 0.8319 (4) 0.8590 (4) 0.8229 (3) 0.8033 (4) 0.8431 (4) 0.8106 (4) 0.8452 (4) 0.8292 (4)
Resto 0.8498 (3) 0.8488 (3) 0.8697 (3) 0.8111 (4) 0.8242 (3) 0.8501 (3) 0.8359 (3) 0.8636 (3) 0.8490 (3)
Trvl 0.8080 (5) 0.8136 (5) 0.8101 (5) 0.7778 (5) 0.7594 (5) 0.7903 (5) 0.7718 (5) 0.7954 (5) 0.8104 (5)
Salry 0.6413 (8) 0.6357 (8) 0.6553 (8) 0.6239 (8) 0.6107 (8) 0.6457 (8) 0.6176 (8) 0.6466 (8) 0.6353 (8)
Note: Grey relational category indices are presented by sentiment indices for all prizes for the period from2002 to 2010. Lottery prize categories include jackpot, second, third, fourth, and ?fth prizes, which are ranked according
to individual sentiment indices on household consumption related to food, education, tobacco, alcohol, recreation, restaurant, and travel, plus salary. For all prize categories, tobacco consumption shows a strong sentimental
correlation with lottery participation, with Grey relational grades above 0.9. Alcohol consumption, restaurant consumption, and recreation consumption demonstrate a relatively strong correlation (GRA
grades
between 0.8 and
0.9). Travel consumption and education consumption exhibit a signi?cant correlation (GRA
grades
between 0.7 and 0.8). Food consumption and salary show a negligible correlation (GRA
grades
between 0.6 and 0.7).
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5.2. Individual sentiment indices and lottery returns
Table 4 lists eight sentiment indices, comprising household
consumption on food, education, tobacco, alcohol, restaurant, rec-
reation, and traveling, plus salary, which are analyzed and ranked
according to Grey relational grades for various prizes throughout
the study period. Alcohol and tobacco consumption consistently
shows approximate strong correlations with various prize returns.
Jackpot returns are most strongly correlated with alcohol con-
sumption, given the Grey relational grades between 0.8741 in 2005
and 0.9733 in 2006. However, smaller prize returns display an
approximate stronger correlation with tobacco consumption, with
Grey relational grades ranging between 0.9404 for ?fth prize in
2006 and 0.9887 for fourth prize in 2007; with most of study period
being between 2002 and 2007, plus 2009. For the study periods
2008 and 2010, alcohol consumption is more in?uenced by smaller
prize returns compared with tobacco consumption.
Restaurant consumption consistently shows a relatively strong
correlation for all prize returns during all study periods, with Grey
relational grades between 0.7518 for jackpot return in 2005 and
0.8708 for third prize return in 2006. For 2005, restaurant con-
sumption consistently exhibits less correlation than recreation
consumption for all prize returns. Meanwhile, traveling con-
sumption displays a cyclical change in in?uence for all prize
returns during all study periods. Furthermore, jackpot returns are
signi?cantly correlated with traveling consumption, with Grey
relational grades exceeding 0.80 in 2002 and 2003, after which
their correlation becomes negligible in 2005 and 2005, with Grey
relational grades of 0.7996 and 0.7204, respectively. For later study
periods, the correlation of jackpot returns with traveling con-
sumption remains signi?cant, with Grey relational grades of
0.8143 in 2006; the in?uence of Grey relational grade gradually
decreases to become negligible between 2007 and 2009, after
which the correlation of Grey relational grade becomes signi?cant.
Smaller prize returns experience similar changes in Grey relational
grades and correlation levels. For the period between 2002 and
2004, in 2006, and in 2010, second, third, and fourth prize returns
are signi?cantly correlated with traveling consumption. Compared
with the periods 2005 and between 2007 and 2009, Grey rela-
tional grades indicate a negligible correlation. However, ?fth prize
returns are signi?cantly correlated with traveling consumption
between 2002 and 2004, and during 2010. Fifth prize returns are
also negligibly correlated with traveling consumption between
2005 and 2009, with Grey relational grades between 0.7594 and
0.7954.
Education consumption displays an approximate signi?cant
correlation with all prize returns for all study periods, with Grey
relational grades between 0.6743 for the jackpot in 2005 and
0.7555 for fourth prize in 2009. In 2005, jackpot returns are only
negligibly correlated with education consumption. Food con-
sumption shows an approximate negligible correlation with all
prize returns for all study periods, and exhibits Grey relational
grades between 0.6156 for the jackpot in 2005 and 0.7016 for the
jackpot in 2006. Jackpot returns are signi?cantly correlated with
food consumption, with a Grey relational grade of 0.7016 in 2006.
In 2004, second, third, and ?fth prizes are signi?cantly correlated
with food consumption, with Grey relational grades of 0.7002,
0.7005, and 0.7003, respectively. However, fourth prize return is
consistently and negatively correlated with food consumption for
all study periods.
Salary sentiment index consistently shows an approximate
negligible correlation with all prize returns throughout the study
period, with the exception of jackpot returns in 2005, when a Grey
relational grade of 0.5743 indicates less than negligible correlation.
Correlations of various prize returns on salary throughout the
period indicate Grey relational grades between 0.5743 for a jackpot
return in 2005 and 0.6553 for a ?fth prize return in 2004.
Thus, jackpot returns display the largest volatility in correlation
with individual sentiment indices, particularly for the study period
2005 for all individual sentiment indices. Consistent correlation
levels are shown for most individual sentiment indices, except for
traveling consumption with alternating levels of in?uences during
the study period. Although jackpot returns are correlated with
alcohol consumption more strongly than tobacco consumption, for
smaller prize returns, including second, third, fourth, and ?fth
prizes, the relationship of the above sentiment indices is reversed.
Restaurant consumption is more strongly correlated with prize
amounts, and is ranked as the third index of sentiment when
compared to the correlations of prize amounts with recreation
consumption. Prize size shows an approximate signi?cant corre-
lationwith education consumption, whereas the correlation of food
consumption with salary is negligible. The Grey relational order,
based on the rankings of Grey relational grades, for individual
sentiment indices, follows this order: tobacco consumption, alcohol
consumption, restaurant consumption, recreation consumption,
traveling consumption, education consumption, food consumption,
and salary.
6. Conclusion
This study attempts to identify the relationship between various
lottery prize returns and household consumption. The degrees of
correlation are identi?ed and ranked sequentially to identify the
correlation of prize returns with consumption patterns. In contrast
to previous investigations focusing on the regression analysis of
household lottery consumption and demographic analysis of lot-
tery participants, this investigation clari?es the interactions of
household consumption with lottery prizes. This investigation at-
tempts to establish reference consumption indices as sentiment
indicators closely related to lottery returns that in?uence house-
hold consumption.
This study includes various lottery prize returns and explores
their approximate correlation with household consumption in
relation to the rational addiction, desperation, and entertainment
hypotheses. This investigation differs from previous investigations
on lottery demand in that lottery prize returns are analyzed ac-
cording to prize size to identify their in?uences on household
consumption. Sentiment indicators for household consumption
items are identi?ed and ranked according to their relationship with
lottery returns.
This investigation demonstrates that lottery prize returns are
strongly correlated with rational addiction category sentiment
indices, which comprise the individual sentiment indices of to-
bacco and alcohol consumption. The ?ndings correspond to those
of Ghent and Grant (2007), Kearney (2005), Lee and Chang (2005),
and Lin and Lin (2007), who indicate that lottery consumption may
be driven by prize designs to encourage rational addictive behavior.
Lottery prizes are also strongly correlated with income category
sentiment index, but their correlation becomes negligible
compared with individual sentiment indices. This ?nding corre-
sponds to Chen et al. (2009) and Haisley et al. (2008), but contra-
dicts Garrett and Sobel (2004). Moreover, lottery prizes are
signi?cantly correlated with the sentiment indices of the desper-
ation category and negligibly correlated with individual sentiment
indices that comprise education and food consumption. This
?nding contradicts that of Landry and Price (2007) due to the likely
lower costs for food and education consumption. Negligible cor-
relations with lottery prizes are demonstrated for the sentiment
indices of the entertainment category and become relatively strong
for individual sentiment indices related to restaurant, recreation,
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 8
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
and traveling consumption. These ?ndings correspond to those of
Blalock et al. (2007), Garrett and Marsh (2002), and Ghent and
Grant (2007), who reveal that households view lottery consump-
tion as a form of entertainment, including travel.
This investigation applies GRA to analyze the relationship be-
tween lottery returns from prizes, household consumption, and
income. It builds on previous studies regarding lotteries by
grouping factors, such as household consumption and macroeco-
nomic conditions, to observe their in?uences on lottery prize
returns. The results indicate that the Taiwanese lottery market is
characterized by a strong correlation with rational addictive con-
sumption, followed by mixed correlations among relatively strong,
signi?cant, and negligible correlations with desperate and enter-
taining consumption. These results differ from those in the previ-
ous literature demonstrating that most desperation or
entertainment consumption behaviors are directed toward lottery
purchases.
7. Contributions of the study
7.1. Theoretical contributions
This investigation contributes to the literature by applying GRA
(Deng, 1982) to extend existing methodologies, including a ques-
tionnaire survey on the demographic analysis of lottery players,
regression analysis of secondary statistical data on the lottery de-
mands of various socioeconomic groups, and lottery game experi-
ments to assess risk behavior among lottery game players (see
Farrell & Walker, 1999; Garrett & Marsh, 2002; Ghent & Grant,
2007; Harley & Lanot, 2006; Ho et al., 2006; Kearney, 2005; Lin &
Lin, 2007; Lin & Wu, 2007; Matheson & Grote, 2004). The GRA
method adopts secondary statistical data to identify factors asso-
ciated with lottery prize returns and household consumption. An
approximate correlation with sequential order rankings by Grey
relational grades is identi?ed via minimal dataset, simple calcula-
tion, and lack of statistical distribution. Therefore, our empirical
research contributes to the application of GRA to identify the de-
gree of correlation among variables, which differs from traditional
regression analysis, survey, or experiment for identifying a causal
relationship.
This study applies GRA to analyze the in?uence of lottery con-
sumption on household expenditure by identifying the theoretical
support for lottery consumption based on rational addiction theory
(corresponding to Balabanis, 2002; Kearney, 2005; Lin &Lin, 2007),
desperation hypothesis (corresponding to Garrett & Marsh, 2002;
Farrell & Forrest, 2008), and entertainment hypothesis (corre-
sponding to Landry & Price, 2007; Lee & Chang, 2005). The indi-
vidual sentiment indices of household consumption are identi?ed
in relation to lottery prizes to explain changes in consumption
priority that occur for lottery prize winners. Additionally, category
sentiment indices are examined in relation to lottery prize returns
and ranked sequentially.
7.2. Applied contributions
This investigation contributes to the literature by examining
the long-term relationship between lottery prizes and household
consumption. Based on theoretical foundations, household con-
sumption expenditures are analyzed in categories and individual
sentiment indices corresponding to lottery prizes ranging from
jackpot to low-tier prizes. Contrary to the previous literature on
causal relationships in lottery demand (Kearney, 2005; Lee &
Chang, 2005), the current study establishes the indicators of
lottery prizes in relation to household consumption with latent
emotional reactions. Sentiments related to rational addiction,
desperation, and entertainment are tested based on their in?u-
ence in providing potential directions for research on lottery
games. Lottery prizes, ranging from jackpot to low-tier prizes, are
successfully demonstrated to contain sentiments to exhibit lot-
tery player behavior as a potential direction for research on
designing lottery prize structures. Thus, our empirical study
successfully applies rational addictive theory (Becker & Murphy,
1988) with household consumption hypotheses to identify the
latent correlation of consumer consumption behavior with lot-
tery prizes.
Our ?ndings clarify the major in?uences on household con-
sumption for lottery prize returns. Sentiment indices are ranked
based on Grey relational grades to identify their importance and
in?uences. The ?ndings indicate that lottery players may not be
desperate to participate in lottery games, which are contrary to
those of Kearney (2005) and Lee and Chang (2005). However,
rational addiction motivations strongly correlate lottery prize
returns and likely consumption items representing motivations
in seeking to win lottery prizes; this ?nding corresponds to those
of Dale (2004) and Doran et al. (2012). Leading category senti-
ment and individual sentiment indicators of lottery consump-
tions are identi?ed to assist lottery development and strategic
positioning for lottery promotions. Contrary to lottery pro-
motions that deal with social welfare (Lee & Chang, 2005), the
lottery market in Taiwan is characterized by more dominant risk-
seeking behavior among lottery players. Furthermore, our
empirical research contributes to policy making by exploring the
possible household consumption alternations induced by lottery
prizes.
7.3. Implications
For implications, we suggest that authorities could permit
strategic alliances between lottery tickets and various business
entities. For example, tobacco or alcohol discount coupons could be
issued, which are accepted at government-owned tobacco and
alcohol stores, for lottery ticket purchases. Similarly, the govern-
ment tourism bureau could authorize the issuances of restaurant,
recreation, and tourism-related discount coupons for each lottery
ticket purchase. Furthermore, government could provide more
medium and small prizes with better payout probabilities to
encourage extended participation duration. Consumers could
participate more in lottery ticket purchases via discount coupons
and lottery prizes.
8. Limitation and future research
This investigation analyzes the relationship between lottery
prize returns and household expenditures in Taipei. A question-
naire survey on lottery player segmentation and lottery demand
model analyses complemented the use of sentiment indices in this
investigation to identify consumption behavior in relation to lot-
tery prizes. Future studies can also analyze the effects of other
lottery products such as scratch cards on consumption sentiment
indices.
Acknowledgments
The author is grateful to the Editor-in-Chief and anonymous
referees for their helpful comments and suggestions that have
signi?cantly improved this paper. The author thanks the Ministry of
Science and Technology (formerly National Science Council) of
Taiwan, ROC, for ?nancially supporting this research under the
grant NSC98-2410-H-006-121.
A.S. Yang / Asia Paci?c Management Review xxx (2015) 1e10 9
Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
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Please cite this article in press as: Yang, A. S., Sentimental relationships between lottery participation and household consumption, Asia Paci?c
Management Review (2015),http://dx.doi.org/10.1016/j.apmrv.2015.07.001
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