Description
Study on Competitive Choice Dimensions of Golf Destinations: A Multivariate Perceptual Mapping Analysis:- Analysis is the process of breaking a complex topic or substance into smaller parts to gain a better understanding of it. The technique has been applied in the study of mathematics and logic since before Aristotle (384–322 B.C.), though analysis as a formal concept is a relatively recent development.
Study on Competitive Choice Dimensions of Golf Destinations: A Multivariate Perceptual Mapping Analysis
AbstrAct: The central objective of this study is to determine the main factors influencing
the choice of a golf destination. This paper explores the use of multivariate statistical techniques, in particular the use of factor analysis, to derive perceptual maps of few choice dimensions, and multiple regression analysis, to determine the importance of the various choice dimensions identified. The three main perceptual dimensions identified are the "Golf ", the "Hospitality and Value" and the "Entertainment and Leisure" dimensions. Perceptual maps show the competitive positions, as perceived by golf tourists, of the six main golf destinations of Portugal and Spain. The results of this research suggest the existence of two well-defined types of golfers, with different preferences. The analysis is carried out for these main segments of golf tourists identified in the literature, namely the "holiday golfers" and the "dedicated golfers", and the results are compared. Finally, how the present methodology can be used to support strategic decisions concerning the management of golf destinations is illustrated. Keywords: Golf tourism, strategic marketing, multivariate analysis, competitive positioning, perceptual mapping,
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Introduction In the last fifty years the popularity of golf has grown enormously. As a result, the flow of foreign visitors to international golf destinations has increased as well as the competition among international golf destinations (Hutchinson, Lai, & Wang, 2009). Golf tourists are a desired segment of the tourism market (Yun, Macdonald, & Hennessey, 2010), in particular for their ability to "generate significantly above-average per capita revenues for the destinations they frequent" (Mintel, 2006; Watson, davies & Thilmany, 2008). In this context, it is therefore increasingly important for political and managerial decision makers to identify the factors that attract and retain golf customers (Hennessey, Macdonald, & MacEachern, 2008; Hutchinson et al., 2009; Petrick, 2002). Where these choice factors are properly identified decision makers can use this knowledge to enhance the performance and competitiveness of a golf destination. The central objective of this study is to determine the main factors influencing the choice of a golf destination. To achieve this goal, the main perceptual dimensions that golf tourists use when comparing a set of golf destinations are determined, as well as the relative importance of those dimensions of choice. based on the derived dimensions, perceptual maps showing the competitive positions of the six main golf destinations situated in Portugal and Spain are built. This would broaden the literature on perceptual mapping and on strategic marketing/competitive positioning. This paper is structured as follows. Firstly, a review of relevant literature on quantitative perceptual mapping and its relation with competitive positioning is presented. Secondly, the details of how data were obtained are described. Thirdly, in the analysis and results section, the data themselves are described, factor analysis is used to reveal the major perceptual dimensions that underpin the choice of a golf destination, perceptual maps that show the competitive positions of the six golf destinations under analysis are built, and multiple regression analysis
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is used to determine the relative importance of the choice dimensions. The preceding analysis is performed for two main segments of golf tourists - the "holiday golfers" and the "dedicated golfers", and the results are compared. How this methodology can be used to support strategic marketing decisions of golf destinations is also illustrated. Finally, the last section presents the main findings and limitations of this research as well as suggestions for future investigation. LITERATuRE REVIEW In an increasingly competitive sector such as tourism, a major challenge for destination marketers is to devise effective competitive strategies in order to attract the attention of consumers-tourists (Crouch & Ritchie, 1999; Gross & brown, 2006; Pike & Ryan, 2004). This has become increasingly important because of the explosive increase in the supply of reachable destinations and due to the vast array of strategies used in the promotion of destinations. Not surprisingly, research on the competitiveness of destinations has as one of its main objectives the strengthening, or the creation, of a positive and differentiated image of a destination in the minds of consumers (e.g., buhalis, 2000; dwyer & Kim, 2003; Morgan, Pritchard, & Pride, 2002; Ritchie & Crouch, 2003; Mossberg & Kleppe, 2005). due to its importance in the process of building the image of an offer, positioning plays a crucial role in improving the attractiveness of a destination (Chacko, 1997; uysal, Chen, & Williams, 2000; Lopes &Silva, 2011). In fact, the purpose of destination positioning is to cre-ate a distinct and differentiated place in the minds of consumers (day, Skidmore, & Koller, 2002; Merrilees, Miller, & Herington, 2009). The positioning of a destination, which involves the definition, and the ef- fective communication, of the competitive advantage(s) to be associ- ated with a destination, helps to distinguish the destination from oth- er similar ones, and therefore, helps consumers to choose it as being more attractive (Kotler, Haider, & Rein, 1993). An analytical technique frequently used in other industries to support positioning decision making is perceptual mapping. Perceptual maps showing the competitive position of various types of products, built with quantitative multivariate techniques, have been widely used since the sixties with the aim of supporting strategic marketing planning (e.g., Green, Johnson, & Neal, 2003; Myers, 1992). And, according to Green et al. (2003), this type of methodology is set to play an important role in marketing research in this new century. Perceptual maps are based on the assessment that consumers make of products, brands and/or competing services and seek to find out the position of these offers in the minds of consumers. They are, therefore, a very valuable tool to (re)position an offer, to measure the success of (re)
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positioning exercises, or to follow the evolution of the position of competing offers over time (Neal, 1980). Additional information on perceptual mapping techniques, including information on studies that have created perceptual maps for various types of industries, can be found in Monteiro, dibb and Almeida (2010). The use of perceptual maps for the positioning of destinations, and territories in general, is relatively recent. Studies mentioned in the literature include the work by Chen and uysal (2002), dolnicar and Grabler (2004), dolnicar, Grabler, and Mazanec (1999), Kim (1998 & 1996), Kim, Guo, and Agrusa (2005), MacKay and Fesenmaier (2000), Murphy (1999), Orth and Tureckova (2002), Prayag (2007), Pyke (2006), Pyke and Ryan (2004), and uysal et al. (2000). Few additional prior studies are reported in Kim, Chun, and Petrick (2005). Most of these studies use multidimensional scaling techniques (MdS). Studies involving the positioning of golf destinations using perceptual maps are rare in the literature. Such studies include Kim, Chun, and Petrick (2005) and Mendes (2004). Kim, Chun, and Petrick (2005) use multidimensional scaling techniques to identify the relative positions of golf destinations in Southeast Asia, as perceived by Korean golfers. The work by Mendes (2004) centers on the competitive positioning of the Algarve, in Portugal, although the author draws perceptual maps based on the original variables and not based on multi-attribute perceptual dimensions. The research here is the first that uses factor analysis to derive perceptual maps to establish the competitive positions of golf destinations. The knowledge of the main dimensions that golf tourists use to evaluate competitive golf destinations, their relative importance, and the position of the various golf destinations under analysis along each of the key derived perceptual dimensions, is vital to support destination managers to make better decisions aimed at capturing the golf tourists' preference and choice of the golf destinations under their command. METHOd Sampling and data collection The data used in this research were obtained through a survey of golfers who used the golf course of Praia del Rey, located in Óbidos the Oeste region of Portugal during 2007. Owing to time limitations, a non-probability sampling method - quota sampling - was used to select the respondents. The sample was stratified by nationality, according to the data on the distribution of rounds of golf provided by the management of the golf course Praia del Rey. The surveys were conducted through a personal interview, since this enables a greater response rate
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and greater intelligibility of the questions, due to the face-to-face contact of the researcher. One hundred and twenty four responses were obtained and considered valid. Measurement As regards the selection of attributes included in the questionnaire the following procedure was used. In the first stage, it was ascertained that the attributes could be grouped into two sets: those relating to the characteristics of the destination and those relating to the characteristics of the golf courses and the game itself (Amorós, 2003; beerli &Martin, 2004; Correia & Pintassilgo, 2006; Golf and Tourism Consult- ing, 2001; Kim & Ritchie, 2010; Mendes, 2004; Mintel, 2006; Nation- al Golf Foundation, 2005; Paniza, 2005; Petrick & backman, 2002). In the second stage, in order to reduce the 39 attributes identified in the first stage into a more actionable number, interviews with sixteen golfers were carried out, in which they rated the importance of each attribute using a 7 - point importance scale. Then, the 22 most impor- tant attributes mentioned by these golfers, 11 related to the character- istics of the destination and 11 related to the characteristics of the golf courses, were selected to be included in the questionnaire (Table 1). The first part of the questionnaire designed for this study refers to socio-demographic and behavioral characteristics of the golf tourists. The second part of the questionnaire captures, through a seven-point Likert scale (from 1 - "strongly disagree" to 7 - "strongly agree"), the perceptions of golf tourists on selected competitive golf destinations, using the attributes shown in Table 1. The last part of the questionnaire measures the reported frequency of use of the golf courses, and the intention to recommend them to other people, both measured on a seven-point Likert scale (from 1 - "strongly disagree" to 7 - "strongly agree"). With regard to the selection of the main golf destinations to be analyzed in this research, the Portuguese destinations Costa de Lisboa, the Algarve and the Oeste were chosen in accordance with the definition of priority products for each of the Portuguese regions, as established in the national strategic tourism plan of Portugal (Ministério da Economia e Inovação, 2006). In Spain, a set of main golf destinations according to the information provided by the Real Federación Española de Golf (2006) was initially selected. This set was then submitted to the same refinement process used in the choice of attributes resulting in the final selection of Costa del Sol, Costa brava and Costa blanca as the main Spanish destination competitors. Figure 1 shows the locations of the six major golf destinations in Portugal and Spain included in the analysis.
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Table 1. Attributes used to evaluate a golf destination Code Name of the variable Attributes related to the destination A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 beautiful Scenery Pleasant Climate Good variety of tourist attractions Good hospitality and friendliness of local people Good safety and security Good quality of the gastronomy Good value for money diversity of shopping facilities Good accessibilities Pleasant nightlife and entertainment Suitable number of golf courses Attributes related to the golf courses b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 International airport proximity (1 hour or less travelling time) Ease of obtaining tee-times Suitable course fees Course design and competitiveness Good course upkeep Championship golf course Course rating in international ranking Good pro shop Good Club House Good practice and training facilities Good quality of the facilities
Selection of the competitive golf destinations
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Figure 1. The six main golf destinations under analysis
RESuLTS Sample profile Concerning the characterization of the golfers in the sample, Table 2 indicates that the majority of respondents are from the united Kingdom (49.2%), with Portuguese being the second group in terms of size (22.6%), followed by Scandinavians (10.5%), and Irish (8.1%), while other nationalities represent 9.7% of the respondents. These values are similar to the shares of occupation of the golf course in 2005 that, according to the management of the Praia del Rey golf course, were 43% for those from the united Kingdom, 16% for Portuguese, 12% for Scandinavians, 6 % for Irish and 13% for other nationalities. The vast majority of players are male (79.8%); almost half of respondents are between 46 and 60 years old (45.2%), while the great majority are between 31 and 60 (78.3%); 41.9% of respondents have a college degree. Most respondents (61%), which from now on will be called "holiday golfers", did not choose golf as the main reason for travel, whereas those who did choose golf as the main reason for travel, which from now on will be named "dedicated golfers", represent a very appreciable slice of sample (39%). The literature often mentions these two main categories of golf tourists (Readman, 2003). As for the accommodation used, two main types were mentioned, representing around 80% of the total of respondents in the sample. While 40.3% of all respondents chose to stay at a hotel, 38.7% of respondents have their own residence in Praia del Rey. For other forms of accommodation, 10.5% chose to stay at a friend's or relative's house and 8.9% opted for renting a house.
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The period of stay most represented is the 4-to-7 day period (42.7%), which corresponds to the golf package which is most sold by tour operators, according to the report of the International Association of Golf Tour Operators (IAGTO, 2005). The period of stay reported in second place is the 2-to-3 day period (26.6%). Again, this is in line with the IAGTO (2005) report, which mentions that weekend golf tours packages, which have been increasing in recent years, represent about 30% of the total of golf packages. It should also be noted that the average period of stay corresponds to the good figure of 5.5 days, rising to 6.5 days when Portuguese golfers are excluded. According to the Instituto Nacional de Estatística of Portugal (2005), the average stay in the registered accommodation facilities in 2004 was 2.5 days for the Oeste region and 4.2 days for Portugal.
Table 2. Characteristics of golfers in the sample
Characteristics Country of residence united Kingdom Portugal Scandinavia Ireland Other Gender Male Female Age structure (years) 15-30 31-45 46-60 >60 Level of Education College graduate Other Golf as the motivation for travel Main motivation Secondary motivation No motivation Type of accommodation Hotel Own residence Rented residence Friend's/relative's house Other Length of stay 1 day 2-3 days 47 days 8-15 days Total Frequencies 61 28 13 10 12 99 25 10 41 56 17 52 72 48 60 16 50 48 11 13 2 13 33 53 25 124 Percentage 49.2 22.6 10.5 8.1 9.7 79.8 20.2 8.1 33.1 45.2 13.7 41.9 58.1 38.7 48.4 12.9 40.3 38.7 8.9 10.5 1.6 10.5 26.6 42.7 20.2 100.0
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Finding the main perceptual dimensions with factor analysis T he main perce ptual dimensions that g olf tourists use when com paring the various golf destinations under consideration will be determined using factor analysis. These dimensions are then used to build perceptual maps that show the competitive positions of the various golf destinations under analysis. Then, multiple regression analysis will be used to determine the relative importance of each dimension in the choice of a golf destination. Exploratory factor analysis is a multivariate technique often used to reduce the information contained in a set of original variables into a small number of factors, or dimensions, with minimal loss of information (Gorsuch, 1983). Since it can handle any type of distribution of the original data, the principal components method was the extraction technique chosen to identify the main perceptual dimensions that explain a substantial amount of the variance contained in the original perceptual data. The statistical software package used to process the data was SPSS. Factor analysis (R type) was performed on a table whose rows record the perce ptions of all respondents for all destinations and whose columns correspond to the 22 perceptual attributes, according to the following procedure (Hair, black, babin, Anderson, & Tatham, 2006). Firstly, the correlation matrix was examined to check whether the variables were sufficiently correlated with one another. Secondly, the number of factors to be extracted was determined, and the degree of adjustment of the factor model to the original data was evaluated. Thirdly, the extracted factors were subjected to a Varimax rotation to obtain more easily interpretable factors. Finally, factor scores for each golf destination were computed to be used in further analysis, par ticularly in the building of perce ptual maps and in deter mining the relative importance of each perceptual dimension. To verify whether the variables were sufficiently correlated with one another, a visual inspection of the correlation matrix was carried out; bartlett's test of sphericity (1950) and the Kaiser-MeyerOlkin (KMO) measure of sampling adequacy were also computed. The correlation matrix, in Table 3, shows that nearly all variables have at least one correlation coefficient greater than, or equal to, 0.5 except for three variables where this figure is 0.4. This means that all variables are sufficiently correlated with each other to be included in the analysis. In addition, bartlett's test of sphericity (1950) is statistically significant at the 0.001 level, which allows rejecting the null hypothesis that the correlation matrix is an identity matrix. Finally, the value of the KMO measure was 0.93, a figure which belongs to the range of values that Kaiser (1974) considers to be "wonderful". For these three reasons it is concluded that these data are adequate to be subjected to factor analysis.
Table 3. Correlation matrix
A10 A11 B1 B10 B11 B 2 B 3 B 4 B 5 B 6 B 7 B 8 B 9
A 1 A
A 1 1.
A 2
A 3
A 4
A 5
A 6
A 7
A 8
A 9
2 A 3 A
00 0.39 1.00 0.16 0.40
4 A 5 A
1.00 0.56 0.38 0.04 1.00 0.54 0.41 0.04 0.66 1.00
0.50 0.35 0.07 0.59 0.59 1.00
6 A 7 A
0.55 0.42 0.03 0.64 0.65 0.70 1.00
0.10 0.37 0.43 0.16 0.12 0.18 0.17 1.00 8 A 0.34 0.56 0.50 0.28 0.37 0.34 0.35 0.46 1.00 9 A10 0.10 0.47 0.47 -0.03 0.03 0.14 0.08 0.50 0.45 1.00
A11 -0.09 0.36 0.48 -0.20 -0.18 -0.07 -0.17 0.45 0.41 0.66 1.00 B 0.17 0.40 0.35 0.03 0.13 0.08 0.12 0.28 0.48 0.43 0.41 1.00
1 B 2 B
0.53 0.50 0.06 0.54 0.61 0.48 0.60 0.14 0.39 0.12 -0.08 0.41 1.00
0.46 0.36 0.06 0.52 0.52 0.63 0.62 0.18 0.33 0.07 -0.08 0.17 0.59 1.00
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3 B 4 b
0.44 0.51 0.18 0.45 0.47 0.52 0.54 0.20 0.38 0.27 0.14 0.28 0.65 0.60 1.00
0.53 0.46 0.04 0.54 0.55 0.52 0.56 0.13 0.32 0.19 -0.06 0.23 0.69 0.60 0.68 1.00
5 B 6 B
0.30 0.42 0.10 0.33 0.41 0.37 0.36 0.10 0.29 0.19 0.12 0.27 0.58 0.44 0.62 0.54 1.00
0.41 0.44 0.09 0.41 0.43 0.40 0.46 0.18 0.31 0.19 0.10 0.24 0.55 0.55 0.65 0.62 0.72 1.00
7 B 8 B
0.31 0.49 0.29 0.33 0.39 0.41 0.37 0.33 0.41 0.38 0.25 0.42 0.61 0.49 0.59 0.56 0.57 0.56 1.00
0.40 0.52 0.14 0.43 0.49 0.50 0.48 0.21 0.42 0.22 0.11 0.27 0.63 0.65 0.64 0.61 0.60 0.67 0.63 1.00 9 B10 0.24 0.58 0.33 0.34 0.31 0.37 0.37 0.30 0.36 0.35 0.21 0.30 0.42 0.37 0.57 0.50 0.43 0.51 0.60 0.50 1.00
With regard to the number of factors to retain, the eigenvalue criterion, which considers that all factors whose eigenvalues are greater than one should be retained, indicates that three factors should be selected see Table 4. The extraction of three factors is also supported by the Scree Test (Cattell, 1966), since the eigenvalues decrease very little from the third factor onwards. Furthermore, the three factors solution explains more than 60% of the total variance of the original variables, percentage which is considered satisfactory in social sciences (Hair et al., 2006). Finally, this solution is also a good solution from the interpretative point of view, which is a very relevant practical criterion for researchers (Hair et al., 2006; Lattin, Carrol, & Green, 2003).
B11 0.27 0.48 0.34 0.32 0.29 0.30 0.34 0.28 0.41 0.31 0.15 0.38 0.53 0.36 0.59 0.46 0.46 0.42 0.62 0.45 0.65 1.00
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Table 4. Factors extracted with the principal components method Factor
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Eigenvalue
9.25 3.29 1.44 0.88 0.85 0.68 0.60 0.57 0.53 0.46 0.42 0.40 0.35 0.34 0.34 0.29 0.26 0.26 0.25 0.20 0.20 0.17
Variance (%)
42.02 14.96 6.55 3.99 3.87 3.08 2.72 2.60 2.40 2.10 1.90 1.79 1.60 1.55 1.55 1.30 1.19 1.17 1.12 0.91 0.89 0.77
Cumulative Variance (%)
42.02 56.98 63.53 67.52 71.39 74.47 77.18 79.78 82.17 84.27 86.17 87.96 89.56 91.11 92.66 93.96 95.15 96.32 97.43 98.35 99.23 100.00
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Table 5. Solution obtained with the principal components method and Varimax rotation Variable
b6 Championship golf course b7 Course rating in international ranking b8 Good pro shop b4 Course design and competitiveness b9 Good Club House b5 Good course upkeep b2 Ease of obtaining tee-times b11 Good quality of the facilities b10 Good practice and training facilities A7 Good value for money A4 Good hospitality and friendliness of local people A5 Good safety and security A6 Good quality of the gastronomy A1 beautiful Scenery b3 Suitable course fees Pleasant nightlife and entertainment A11 Suitable number of golf courses A3 Good variety of tourism attractions A8 diversity of shopping facilities A9 Good accessibilities A2 Pleasant Climate b1 International airport proximity
Factor Factor Factor Commu1
0.80 0.77 0.73 0.72 0.70 0.64 0.64 0.64 0.63 0.81 0.80 0.78 0.76 0.71 0.62 0.78 0.68 A10 0.77 0.77 0.76 0.70 0.69 0.56 0.55 0.70 0.68 0.76 0.79 0.69 0.83 0.52 0.53 0.71 0.75 0.81 0.72 0.76 0.65 0.62
2
3
nality
0.63 0.69 0.73 0.69 0.69 0.68 0.70
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The solution with 3 factors obtained with Varimax rotation is shown in Table 5. To facilitate the reading of this table, only the factor loadings whose absolute values are greater than 0.50 are shown. This solution is good for a number of reasons. Firstly, almost all variables have factor loadings exceeding 0.60, except two of them which have factor loadings greater than 0.50, a value that is considered significant by Hair et al. (2006). Secondly, nearly all variables are strongly correlated with one factor only. Finally, looking at the values of the communalities, the factor solution explains between 62% and 84% of the variance of the original variables. With regard to the interpretation of the resulting factors, Table 5 shows that the three factors are related to three categories of attributes. Factor 1 is clearly linked to the attributes of golf courses, the most highly correlated being b6 - "Championship golf course", followed by b7 - "Course rating in international ranking", b8 - "Good pro-shop", and b4 "Course design and competitiveness", with factor loadings of 0.80, 0.77, 0.73 and 0.72, respectively. Thus, this factor will be called "Golf ", and reflects the interest in the prestige and competitiveness of the golf courses. Factor 2 is associated with attributes of the golf destination, particularly with variables A7 - "Good value for money", A4 - "Good hospitality and friendliness of local people", A5 - "Good safety and security", A6 - "Good quality of the gastronomy", and A1 - "beauti- ful scenery", with factor loadings of 0.81, 0.80, 0.78, 0.76 and 0.71 respectively. Thus, Factor 2 will be designated "Hospitality and Value", and reflects the interest in the relationship between quality and price, and in the hospitality and security of the golf destination. Factor 3 is strongly correlated with the attributes A10 - "Pleasant nightlife and entertainment", A11 - "Suitable number of golf courses", A3 - "Good variety of tourism attractions", and A8 - "diversity of shopping facilities", with factor loadings of 0.78, 0.77, 0.76 and 0.70 respectively. Therefore, Factor 3 will be called "Entertainment and Leisure", since it reflects the interest in the complementary activi- ties in a golf destination related to tourism entertainment and leisure. Perceptual maps showing the competitive positions of the golf destinations In order to empirically establish the perceived competitive positions of the six golf destinations of Portugal and Spain under analysis, perceptual maps were built, using all respondents, where each golf destination is represented by its mean factor score along each of the three factors - see Figure 2 and Figure 3. These perceptual maps are an excellent way to confront the image of the various objects, simplifying a huge amount of information (Pike & Ryan, 2004). Through this meth-
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odology it is possible to view the relative positions of the various golf destinations along the three derived perceptual dimensions, as well as the main differences between these destinations. Figure 2 shows the perceptual map revealing the competitive position of the destinations under analysis in relation to dimensions F1 "Golf " and F2 - "Hospitality and Value". Figure 2 reveals that the Oeste region is very well positioned along both dimensions F1 and F2. On the other hand, the Costa de Lisboa region appears well positioned in relation to the "Hospitality and Value" dimension but it is the least well perceived destination on the "Golf " dimension. The Algarve has a slightly above average position along the first two perceptual dimensions, whereas the group of Spanish destinations is relatively poorly positioned regarding F2 - "Hospitality and Value". In fact, the second dimension separates the Spanish golf destinations from the Portuguese ones, with the latter being perceived as offering higher levels of "Hospitality and Value" than their Spanish competitors. Finally, both Costa blanca and Costa brava have below average perceived relative positions on the first two perceptual dimensions, while Costa del Sol is well positioned on the "Golf " dimension.
Figure 2. Perceptual map "Golf "/"Hospitality and Value" (all participants)
Figure 3 shows the perceptual map based on dimensions F1 - "Golf " and F3 - "Entertainment and Leisure". The third dimension separates the Oeste destination from all other destinations, and reveals that Oeste is perceived as the worst destination in terms of "Entertainment and Leisure". The destinations better positioned alongside F3 are the Cos-
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ta brava and the Costa de Lisboa, followed by the Costa del Sol. The Costa blanca and the Algarve display average values as regards dimension F3 - "Entertainment and Leisure".
Figure 3. Perceptual map "Golf "/"Entertainment and Leisure" (all participants)
Determining the importance of the choice dimensions with multiple regression analysis Multiple regression analysis was the technique used to identify the relative importance of each perceptual dimension in the choice of a golf destination. The "recommendation of the golf destination" was used as the dependent variable, since the "choice of the golf destination" was not directly measured, and the independent variables were the factor scores obtained for dimensions F1 - "Golf ", F2 - "Hospi tality and Value" and F3 - "Entertainment and Leisure". The results of the multiple regression analysis are shown in Table 6, in the part referring to "all golfers". Equation (1) shows the linear regression model with the three factors, explaining 43% of the total variation of the variable "recommendation of the golf destination". (1) Recommendation of the golf destination = 4.65 + 0.53 F1 + 0.51 F2 - 0.16 F3; R2= 0 . 4 3 (107.24) (12.57) (5.34) (-7.55) As expected, the "recommendation of the g olf destination" in creases with the increase of dimensions F1 - "Golf " and F2 - "Hos -
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pitality and Value". Surprisingly, the "recommendation of the golf destination" decreases as dimension F3 - "En ter tainment and Lei sure" increases. The beta values, in Table 6, indicate that the dimensions F1 and F2, whose values are 0.44 and 0.42 respectively, have basically the same importance, and are much more important in the reg ression model than the perce ptual dimension F3, whose absolute value is 0.13. This means that the "recommendation of the golf destination" depends mainly on the perceptions that tourists have of that destination along dimensions F1 - "Golf " and F2 - "Hospitality and Value". The regression model also indicates that the golf destinations that are better perceived in terms of the dimension F3 - "Entertainment and Leisure" have lower levels of recommendation, for equal values of F1 and F2. Investigating differences between "holiday golfers" and "dedicated golfers" The preceding analysis will now be repeated for two segments of tourists mentioned in the literature (Readman, 2003), the "holiday golfers" and the "dedicated golfers", in order to investigate the differences between these two groups of golf tourists. In this part of the analysis only the responses of golfers who do not own a residence in the Praia del Rey resort will be considered - 61.3% of the sample, so as not to include this subjective component in the analysis. It must be pointed out here the fact that 68.7% of the "dedicated g olfers" stated they knew at least four of the six golf destinations under analysis, and 47.2% at least five of these destinations; these figures are 36.2% and 22.4%, respectively, for the "holiday golfers" segment. This means that th e segmen t o f "dedica ted g o lfer s" h a s sup er io r p er so n a l in fo r ma tio n and experience regarding the set of golf destinations under analysis. T he factor analysis car ried out for both segments of g olf tourists showed a factor structure similar to that previously obtained where all respondents were considered. The perceptual maps based on the dimensions F1 - "Golf " and F2 - "Hospitality and Value", prepared for the "holiday golfers" and "dedicated golfers" segments are shown in Figure 4 and Figure 5, respectively. The perceptual map for "holiday golfers", shown in Figure 4, is similar to that obtained where all respondents were considered - see Figure 2. However, the position of the "Costa brava" is perceived by the "holiday golfers" segment to be closer to that of the "Costa del Sol", whereas its position was closer to that of the "Costa blanca" when the perceptions of all golfers were analyzed. In addition, as shown in Figure 4, the Algarve has a less favorable perceived position in relation to dimension F1 - "Golf ".
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Figure 4. Perceptual map "Golf "/"Hospitality and Value" ("holiday golfers")
On the other hand, the perceptual map for the "dedicated golfers" segment, in Figure 5, is quite different, reflecting the better knowledge that this segment has of the several golf destinations under analysis. T h e "dedi ca ted g o lfer s" co n si der th a t th e b est p o si ti o n ed desti n a tions jointly in terms of the dimensions F1 and F2 are the Oeste, the Algarve and the Costa del Sol, with the Costa del Sol slightly exceeding the Oeste on dimension F1 - "Golf ". The Algarve noticeably improves its position along the first perceptual dimension compared to that obtained where all respondents were considered. Turning to dimension F2 - "Hospitality and Value", the three Portuguese golf destinations are valued higher than the Spanish golf destinations, but the Costa del Sol substantially improves its perceived position, compared to that shown in Figure 2. The Costa de Lisboa region, although well positioned along the second dimension, continues to have a less favorable perceived position regarding the "Golf " dimension.
Figure 5. Perceptual map "Golf "/"Hospitality and Value" ("dedicated golfers")
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Following the same procedure as before, multiple regression analysis was used to determine the relative importance of each perceptual dimension, taking "recommendation of the golf destination", Y, as the dependent variable and the three factors as the independent variables. The multiple regression equations obtained for the "holiday golfers" and the "dedicated golfers" segments are identified below with the numbers (2) and (3), respectively. To facilitate the comparison, the regression model obtained for all respondents is presented again - equation (1). The results of multiple regression analysis for the various segments of golf tourists are shown in Table 6. (1) Y (all participants) = 4.65 + 0.53 F1 + 0.51 F2 - 0.16 F3; R2= 0.43 (107.24) (12.57) (5.34) (-7.55) (2) Y (holiday golfers) = 4.41 + 0.45 F1 + 0.66 F2 - 0.15 F3; R2= 0.47 (20.90) (9.96) (7.68) (-4.56) (3) Y (dedicated golfers) = 4.84 + 0.53 F1 + 0.42 F2 - 0.29 F3; R2= 0.49 (21.65) (9.45) (2.17) (-3.40) The comparison of the various regression models leads to the following conclusions. Firstly, the most important perceptual dimensions are F1 and F2 for the three sets of participants; dimension F3 is considerably less important than the other two dimensions. However, for the "holiday golfers" segment, equation (2) reveals that is the "Hospitality and Value" dimension, F2, which assumes greater importance on the recommendation of the golf course to other people - Table 6 shows a beta value of 0.51. The "Golf " dimension, F1, also presents an appreciable relative importance, with a beta figure of 0.40. On the contrary, regarding the "dedicated golfers" segment, equation (3) reveals that is the "Golf " dimension which assumes greater importance on the recommendation of the golf course to other people - its beta value is 0.45. For this segment the dimension "Hospitality and Value" is the second most important, with a beta figure of 0.39. These results are in line with what one would expected, with "holiday golfers" putting more emphasis on the "Hospitality and Value" of the golf destination and the "dedicated golfers" preferring firstly the aspects related to the practice of "Golf ". The "dedicated golfers" also have the particularity of weighing the dimension F3 - "Entertain- ment and Leisure" more negatively than the "holiday golfers"; their beta values in Table 6 are -0.25 and -0.12, respectively.
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Table 6. Multiple regression results for the various segments of respondents
dependent variable: Recommendation of the golf destination
B
All golfers Constant F1 F2 F3 Holiday golfers Constant F1 F2 F3 dedicated golfers Constant F1 F2 F3 4.84 0.53 0.42 -0.29 4.41 0.45 0.66 -0.15 4.65 0.53 0.51 -0.16
Beta
t
107.24
Multiple R
0.65
R Square
0.43
0.44 0.42 -0.13
12.57 5.34 -7.55
20.90 0.40 0.51 -0.12 9.96 7.68 -4.56
0.69
0.47
21.65 0.45 0.39 -0.25 9.45 2.17 -3.40
0.70
0.49
Managerial implications The results obtained in the previous section suggest the existence of two well-defined types of golfers, and confirm the difficulties of managing a golf destination mentioned in the literature (e.g., Amorós, 2003; Petrick & backman, 2002). Important factors for golfers are not only the level of quality of the products and services offered, crucial for developing the loyalty of consumers and the competitiveness of a golf destination, but also other, more difficult to control, such as the hospitality and security of the golf destination, which also depend on the residents and local authorities.
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The multivariate method in this research can be useful for managers of golf destinations to support policies and practices aiming at capturing the preferences of these two segments of golfers and, consequently, to improve the competitive position of the golf destinations under their command. Taking the region Oeste of Portugal as an example, its position in all the derived perceptual maps indicates the possibility of using consumers as "ambassadors" of this destination. Thus, the excellent competitive position of the Oeste golf destination should be included in its communication policy, aimed at both the final consumers and the distribution channels. The Oeste region could develop and implement relational marketing strategies aimed at developing the golfers' loyalty, and policies that intensify the "word of mouth". It could also offer familiarization trips for specialist journalists and tour operators. Turning to the Algarve, the quality of its "Golf " is recognized by the experts, the "dedicated golfers" segment, but the "holiday golfers" segment does not perceive this golf destination in such a positive way in fact, Figure 4 shows that the Algarve is perceived below the average along the "Golf " dimension. One reason for this might be that the Algarve is not effective in the way it communicates the excellence of its golf courses to the less connoisseur, "holiday golfers" segment. To improve the competitive position of the Algarve along the "Golf " dimension, concerning the "holiday golfers" segment, managers should focus on improving the scores of this destination on the original variables which load highly on this dimension, and where the Algarve is at a competitive disadvantage. The inspection of the mean of the original variables shows that managers should pay particular attention to variables b6 - Championship golf course and b7 - Course rating ininternational ranking. dISCuSSION The central objective of this study is to determine the main factors influencing the choice of a golf destination. This research aims to expand the literature on perceptual mapping and on strategic marketing by being the first which uses factor analysis to derive perceptual maps that establish the perceived competitive positions of golf destinations. Factor analysis revealed that golfers use three main perceptual dimensions when they evaluate the golf destinations under analysis. These are the dimension F1 - "Golf ", which is clearly associated with the attributes of the golf courses, the dimension F2 - "Hospitality and Value", which reflects the interest in the price-quality ratio and in the hospitality and security of the golf destination, and the dimension F3 - "Entertainment and Leisure", which mirrors the interest in the complementary activities offered by a tourism destination, namely in
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the entertainment and leisure tourism activities. The perceived competitive positions of the six main golf destinations of Portugal and Spain were then empirically established through the construction of perceptual maps, where each golf destination is represented by its average factor score. Multiple regression analysis, where the "recommendation of the golf destination" was the dependent variable and the independent variables were the three factors, F1 - "Golf ", F2 - "Hospitality and Value" and F3 "Entertainment and Leisure", revealed that, where all respondents were considered, the dimensions "Golf " and "Hospitality and Value" have basically the same importance, and are much more important than the dimension "Entertainment and Leisure" in the choice of a golf destination. This analysis also showed, as expected, that the "recommendation of the golf destination" increases with the increase of the dimensions F1 - "Golf " and F2 - "Hospitality and Value". This corroborates research results reported by Silvestre et al. (2007) where a factor representing the characteristics of the golf course was found to positively affect the intentions of golfers to recommend the Algarve's golf courses. Surprisingly, the "recommendation of the golf destination" decreases with the increase of the dimension F3 - "Entertainment and Leisure", which is a result that could be studied in future research. This regression model explains 43% of the total variation of the variable "recommendation of the golf destination". The preceding methodology was repeated for two segments of golfers - "holiday golfers" and "dedicated golfers", revealing different perceptual maps for these two segments. The "holiday golfers" clearly set the Oeste region apart from the competition, while the "dedicated golfers", more knowledgeable of the various golf destinations under analysis, do highlight a competitive cluster that includes the Oeste, the Algarve and the Costa del Sol. Regarding the relative importance of the perceptual dimensions, for "holiday golfers" the most important dimension influencing the "recommendation of the golf destination" to other people is the dimension F2 - "Hospitality and Value", followed by dimension F1 - "Golf ". On the contrary, for the "dedicated golfers" segment, the importance of these two perceptual dimensions is reversed. In addition, the "dedicated golfers" segment attributes far greater importance to the dimension F3 - "Entertainment and Leisure" than the "holiday golfers", a dimension which is considered undesirable by both segments. This finding, however, is not in line with the "avid golfer" segment of the typology of golf tourists suggested by Tassiopoulos and Haydam (2008). This segment, which shares with the "dedicated golfers" segment the fact of having golf as the primary focus of the travel, prefers (along with other variables) the existence or availability of night life, which is a variable highly correlated with the undesirable "Entertainment and Leisure" dimension.
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The results of this research suggest the existence of two well defined types of golfers, with different preferences, and corroborate the difficulties of managing a golf destination mentioned in the literature (e.g., Amorós, 2003; Petrick & backman, 2002). However, unlike some studies (Silvestre, Correia, & barros, 2007) which claim that golf tourism is a focused activity not connected to the tourism destination, this study suggests that the attributes of the destination play a relevant role in the choice of a golf destination. On the other hand, the present results partially confirm the findings obtained by Hutchinson et al. (2009) in the sense that the perceived value, a variable which is highly correlated with the "Hospitality and Value" dimension, has a positive influence on word-of-mouth/recommendation of the golf destination. The reported results should be appraised with regards to the limitations of this research. One of these is the type of sampling method used; a non-probabilistic sampling method was used, namely a quota sample, which precludes the generalization of the results of this research. Another limitation of this study is the period during which the data was collected, throughout december 2006 and January 2007, which does not cover the entire annual spectrum and the associated seasonality. A third important limitation stems from having compared six golf destinations using data collected on only one of them - the Oeste destination. If, on the one hand, this is not a problem in terms of the application of the multivariate methodology explored in this study which can be used with other research designs, on the other hand, the excellent results of the Oeste region, compared with other more mature and consolidated destinations, might have been influenced by the positive perceptions that the respondents were experiencing at the Oeste at the moment of the data collection. Indeed, the Praia del Rey golf course is located in a unique spot in terms of natural landscape. The resort won the prize of Golf Resort of the Year - Europe 2007, awarded by the International Association of Golf Tourist Operators (IAGTO), and the golf course has won several international awards for its location, design and competitiveness. Some methodological issues for discussion and future research are also suggested. definitely, it would be of interest to analyze how the results obtained might differ depending on the golf destination where the data are collected. but, what should be the optimal design for this type of study regarding the selection of the respondents? Should the sample contain golfers who are actually playing in each of the golf destinations under analysis? Or would it be better to survey golfers who have recently played in the golf courses under analysis, but who are in their houses, in their home countries? A result of this research that might trigger further investigation on attributes or dimensions that are unwanted by golf tourists is the find-
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ing that dimension F3 - "Entertainment and Leisure" is considered undesirable by both segments of golfers. In fact, another recent research the study by barros, butler and Correia (2010) - has also found an attribute which is not wanted by golf tourists. These researchers analyzed the length of stay of golf tourists in the Algarve, via survival models, and found that the "length of stay decreases with (the attribute) beach, signifying that golf tourists are not sea oriented tourists". Finally, the methodology used in this research could be useful at different periods of the year to observe the changing perceptions of the golf tourists, and to research other segments of golf tourists such as golfers from specific countries, or segments derived through the use of multivariate clustering techniques. A comparison of the results would be possible. REFERENCES
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Lattin, J., Carrol, J. d., & Green, P.E. (2003). Analysing multivariate data. duxbury: Thompson Learning. Lopes, S. & Silva, J. (2011). Image and positioning of the European tourism market from the perspective of Spanish Tourists. European Journal of Tourism, Hospitality and Recreation, 2(2), 71-89. MacKay, K., & Fesenmaier, d. (2000). An exploration of cross-cultural destination image assessment. Journal of Travel Research, 38, 417-423. Merrilees b., Miller d., & Herington C. (2009). Antecedents of residents' city brand attitudes. Journal of Business Research, 62(3), 362-367. Mendes, J. (2004). O Posicionamento competitivo do golfe: o caso de Almancil. Dissertação de Mestrado, Faculdade de Economia da universidade do Algarve. Ministério da Economia e Inovação (2006). Plano Estratégico Nacional do Turismo. Lisboa: Ministério da Economia e Inovação. Mintel (2006). Golf tourism international report. Retrieved May, 14, 2009, from http://reports.mintel.com/ Monteiro C., dibb S., & Almeida L.T. (2010). Revealing doctors' prescrib- ing choice dimensions with multivariate tools: a perceptual mapping approach. European Journal of Operational Research, 201(3), 909-920. Morgan, N., Pritchard, A., & Pride, R. (2002). Destination branding: creating the unique destination proposition. Oxford: butterworth-Heinemann. Mossberg, L. & Kleppe, I. (2005). Country and destination image - different or similar image concepts? The Service Industries Journal, 25(4), 493-503. Myers, J. (1992). Positioning products/services in attitude space. Marketing Research, 4(March), 46-51. Murphy, L. (1999). Australia's image as a holiday destination: perceptions of backpacker visitors. Journal of Travel and Tourism Marketing, 8(3), 21-45. National Golf Foundation (2005). Golf industry report: golf participation issue. Retrieved May, 14, 2009, from http://www.ngf.org/cgi/researchreports.asp Neal, W. (1980). Strategic product positioning: a step-by-step guide. Business, May-June, 34-42. Orth, u. R., & Tureckova, J. (2002). Segmenting the tourist market using perceptual and attitudinal mapping. Agricultural Economics, 48(1), 36-48. Paniza, J. (2005). La percepción social del golf en Andalucía. Sevilla: Consejería de Turismo, Comercio y deporte. Petrick, J. (2002). Experience use history as a segmentation tool to examine golf travellers' satisfaction, perceived value and repurchase intentions. Journal of Vacation Marketing, 8(4), 332-342. Petrick, J., & backman, S. (2002). An examination of the determinants of golf travellers satisfaction. Journal of Travel Research, 40, 252-258. Prayag G. (2007). Positioning the city product as an international tourist destination: evidence from South Africa. Tourism - An International Interdisciplinary Journal, 55(2), 139-155.
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doc_209672632.docx
Study on Competitive Choice Dimensions of Golf Destinations: A Multivariate Perceptual Mapping Analysis:- Analysis is the process of breaking a complex topic or substance into smaller parts to gain a better understanding of it. The technique has been applied in the study of mathematics and logic since before Aristotle (384–322 B.C.), though analysis as a formal concept is a relatively recent development.
Study on Competitive Choice Dimensions of Golf Destinations: A Multivariate Perceptual Mapping Analysis
AbstrAct: The central objective of this study is to determine the main factors influencing
the choice of a golf destination. This paper explores the use of multivariate statistical techniques, in particular the use of factor analysis, to derive perceptual maps of few choice dimensions, and multiple regression analysis, to determine the importance of the various choice dimensions identified. The three main perceptual dimensions identified are the "Golf ", the "Hospitality and Value" and the "Entertainment and Leisure" dimensions. Perceptual maps show the competitive positions, as perceived by golf tourists, of the six main golf destinations of Portugal and Spain. The results of this research suggest the existence of two well-defined types of golfers, with different preferences. The analysis is carried out for these main segments of golf tourists identified in the literature, namely the "holiday golfers" and the "dedicated golfers", and the results are compared. Finally, how the present methodology can be used to support strategic decisions concerning the management of golf destinations is illustrated. Keywords: Golf tourism, strategic marketing, multivariate analysis, competitive positioning, perceptual mapping,
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Introduction In the last fifty years the popularity of golf has grown enormously. As a result, the flow of foreign visitors to international golf destinations has increased as well as the competition among international golf destinations (Hutchinson, Lai, & Wang, 2009). Golf tourists are a desired segment of the tourism market (Yun, Macdonald, & Hennessey, 2010), in particular for their ability to "generate significantly above-average per capita revenues for the destinations they frequent" (Mintel, 2006; Watson, davies & Thilmany, 2008). In this context, it is therefore increasingly important for political and managerial decision makers to identify the factors that attract and retain golf customers (Hennessey, Macdonald, & MacEachern, 2008; Hutchinson et al., 2009; Petrick, 2002). Where these choice factors are properly identified decision makers can use this knowledge to enhance the performance and competitiveness of a golf destination. The central objective of this study is to determine the main factors influencing the choice of a golf destination. To achieve this goal, the main perceptual dimensions that golf tourists use when comparing a set of golf destinations are determined, as well as the relative importance of those dimensions of choice. based on the derived dimensions, perceptual maps showing the competitive positions of the six main golf destinations situated in Portugal and Spain are built. This would broaden the literature on perceptual mapping and on strategic marketing/competitive positioning. This paper is structured as follows. Firstly, a review of relevant literature on quantitative perceptual mapping and its relation with competitive positioning is presented. Secondly, the details of how data were obtained are described. Thirdly, in the analysis and results section, the data themselves are described, factor analysis is used to reveal the major perceptual dimensions that underpin the choice of a golf destination, perceptual maps that show the competitive positions of the six golf destinations under analysis are built, and multiple regression analysis
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is used to determine the relative importance of the choice dimensions. The preceding analysis is performed for two main segments of golf tourists - the "holiday golfers" and the "dedicated golfers", and the results are compared. How this methodology can be used to support strategic marketing decisions of golf destinations is also illustrated. Finally, the last section presents the main findings and limitations of this research as well as suggestions for future investigation. LITERATuRE REVIEW In an increasingly competitive sector such as tourism, a major challenge for destination marketers is to devise effective competitive strategies in order to attract the attention of consumers-tourists (Crouch & Ritchie, 1999; Gross & brown, 2006; Pike & Ryan, 2004). This has become increasingly important because of the explosive increase in the supply of reachable destinations and due to the vast array of strategies used in the promotion of destinations. Not surprisingly, research on the competitiveness of destinations has as one of its main objectives the strengthening, or the creation, of a positive and differentiated image of a destination in the minds of consumers (e.g., buhalis, 2000; dwyer & Kim, 2003; Morgan, Pritchard, & Pride, 2002; Ritchie & Crouch, 2003; Mossberg & Kleppe, 2005). due to its importance in the process of building the image of an offer, positioning plays a crucial role in improving the attractiveness of a destination (Chacko, 1997; uysal, Chen, & Williams, 2000; Lopes &Silva, 2011). In fact, the purpose of destination positioning is to cre-ate a distinct and differentiated place in the minds of consumers (day, Skidmore, & Koller, 2002; Merrilees, Miller, & Herington, 2009). The positioning of a destination, which involves the definition, and the ef- fective communication, of the competitive advantage(s) to be associ- ated with a destination, helps to distinguish the destination from oth- er similar ones, and therefore, helps consumers to choose it as being more attractive (Kotler, Haider, & Rein, 1993). An analytical technique frequently used in other industries to support positioning decision making is perceptual mapping. Perceptual maps showing the competitive position of various types of products, built with quantitative multivariate techniques, have been widely used since the sixties with the aim of supporting strategic marketing planning (e.g., Green, Johnson, & Neal, 2003; Myers, 1992). And, according to Green et al. (2003), this type of methodology is set to play an important role in marketing research in this new century. Perceptual maps are based on the assessment that consumers make of products, brands and/or competing services and seek to find out the position of these offers in the minds of consumers. They are, therefore, a very valuable tool to (re)position an offer, to measure the success of (re)
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positioning exercises, or to follow the evolution of the position of competing offers over time (Neal, 1980). Additional information on perceptual mapping techniques, including information on studies that have created perceptual maps for various types of industries, can be found in Monteiro, dibb and Almeida (2010). The use of perceptual maps for the positioning of destinations, and territories in general, is relatively recent. Studies mentioned in the literature include the work by Chen and uysal (2002), dolnicar and Grabler (2004), dolnicar, Grabler, and Mazanec (1999), Kim (1998 & 1996), Kim, Guo, and Agrusa (2005), MacKay and Fesenmaier (2000), Murphy (1999), Orth and Tureckova (2002), Prayag (2007), Pyke (2006), Pyke and Ryan (2004), and uysal et al. (2000). Few additional prior studies are reported in Kim, Chun, and Petrick (2005). Most of these studies use multidimensional scaling techniques (MdS). Studies involving the positioning of golf destinations using perceptual maps are rare in the literature. Such studies include Kim, Chun, and Petrick (2005) and Mendes (2004). Kim, Chun, and Petrick (2005) use multidimensional scaling techniques to identify the relative positions of golf destinations in Southeast Asia, as perceived by Korean golfers. The work by Mendes (2004) centers on the competitive positioning of the Algarve, in Portugal, although the author draws perceptual maps based on the original variables and not based on multi-attribute perceptual dimensions. The research here is the first that uses factor analysis to derive perceptual maps to establish the competitive positions of golf destinations. The knowledge of the main dimensions that golf tourists use to evaluate competitive golf destinations, their relative importance, and the position of the various golf destinations under analysis along each of the key derived perceptual dimensions, is vital to support destination managers to make better decisions aimed at capturing the golf tourists' preference and choice of the golf destinations under their command. METHOd Sampling and data collection The data used in this research were obtained through a survey of golfers who used the golf course of Praia del Rey, located in Óbidos the Oeste region of Portugal during 2007. Owing to time limitations, a non-probability sampling method - quota sampling - was used to select the respondents. The sample was stratified by nationality, according to the data on the distribution of rounds of golf provided by the management of the golf course Praia del Rey. The surveys were conducted through a personal interview, since this enables a greater response rate
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and greater intelligibility of the questions, due to the face-to-face contact of the researcher. One hundred and twenty four responses were obtained and considered valid. Measurement As regards the selection of attributes included in the questionnaire the following procedure was used. In the first stage, it was ascertained that the attributes could be grouped into two sets: those relating to the characteristics of the destination and those relating to the characteristics of the golf courses and the game itself (Amorós, 2003; beerli &Martin, 2004; Correia & Pintassilgo, 2006; Golf and Tourism Consult- ing, 2001; Kim & Ritchie, 2010; Mendes, 2004; Mintel, 2006; Nation- al Golf Foundation, 2005; Paniza, 2005; Petrick & backman, 2002). In the second stage, in order to reduce the 39 attributes identified in the first stage into a more actionable number, interviews with sixteen golfers were carried out, in which they rated the importance of each attribute using a 7 - point importance scale. Then, the 22 most impor- tant attributes mentioned by these golfers, 11 related to the character- istics of the destination and 11 related to the characteristics of the golf courses, were selected to be included in the questionnaire (Table 1). The first part of the questionnaire designed for this study refers to socio-demographic and behavioral characteristics of the golf tourists. The second part of the questionnaire captures, through a seven-point Likert scale (from 1 - "strongly disagree" to 7 - "strongly agree"), the perceptions of golf tourists on selected competitive golf destinations, using the attributes shown in Table 1. The last part of the questionnaire measures the reported frequency of use of the golf courses, and the intention to recommend them to other people, both measured on a seven-point Likert scale (from 1 - "strongly disagree" to 7 - "strongly agree"). With regard to the selection of the main golf destinations to be analyzed in this research, the Portuguese destinations Costa de Lisboa, the Algarve and the Oeste were chosen in accordance with the definition of priority products for each of the Portuguese regions, as established in the national strategic tourism plan of Portugal (Ministério da Economia e Inovação, 2006). In Spain, a set of main golf destinations according to the information provided by the Real Federación Española de Golf (2006) was initially selected. This set was then submitted to the same refinement process used in the choice of attributes resulting in the final selection of Costa del Sol, Costa brava and Costa blanca as the main Spanish destination competitors. Figure 1 shows the locations of the six major golf destinations in Portugal and Spain included in the analysis.
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Table 1. Attributes used to evaluate a golf destination Code Name of the variable Attributes related to the destination A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 beautiful Scenery Pleasant Climate Good variety of tourist attractions Good hospitality and friendliness of local people Good safety and security Good quality of the gastronomy Good value for money diversity of shopping facilities Good accessibilities Pleasant nightlife and entertainment Suitable number of golf courses Attributes related to the golf courses b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 International airport proximity (1 hour or less travelling time) Ease of obtaining tee-times Suitable course fees Course design and competitiveness Good course upkeep Championship golf course Course rating in international ranking Good pro shop Good Club House Good practice and training facilities Good quality of the facilities
Selection of the competitive golf destinations
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Figure 1. The six main golf destinations under analysis
RESuLTS Sample profile Concerning the characterization of the golfers in the sample, Table 2 indicates that the majority of respondents are from the united Kingdom (49.2%), with Portuguese being the second group in terms of size (22.6%), followed by Scandinavians (10.5%), and Irish (8.1%), while other nationalities represent 9.7% of the respondents. These values are similar to the shares of occupation of the golf course in 2005 that, according to the management of the Praia del Rey golf course, were 43% for those from the united Kingdom, 16% for Portuguese, 12% for Scandinavians, 6 % for Irish and 13% for other nationalities. The vast majority of players are male (79.8%); almost half of respondents are between 46 and 60 years old (45.2%), while the great majority are between 31 and 60 (78.3%); 41.9% of respondents have a college degree. Most respondents (61%), which from now on will be called "holiday golfers", did not choose golf as the main reason for travel, whereas those who did choose golf as the main reason for travel, which from now on will be named "dedicated golfers", represent a very appreciable slice of sample (39%). The literature often mentions these two main categories of golf tourists (Readman, 2003). As for the accommodation used, two main types were mentioned, representing around 80% of the total of respondents in the sample. While 40.3% of all respondents chose to stay at a hotel, 38.7% of respondents have their own residence in Praia del Rey. For other forms of accommodation, 10.5% chose to stay at a friend's or relative's house and 8.9% opted for renting a house.
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COMPETITIVE CHOICE OF GOLF dESTINATIONS
The period of stay most represented is the 4-to-7 day period (42.7%), which corresponds to the golf package which is most sold by tour operators, according to the report of the International Association of Golf Tour Operators (IAGTO, 2005). The period of stay reported in second place is the 2-to-3 day period (26.6%). Again, this is in line with the IAGTO (2005) report, which mentions that weekend golf tours packages, which have been increasing in recent years, represent about 30% of the total of golf packages. It should also be noted that the average period of stay corresponds to the good figure of 5.5 days, rising to 6.5 days when Portuguese golfers are excluded. According to the Instituto Nacional de Estatística of Portugal (2005), the average stay in the registered accommodation facilities in 2004 was 2.5 days for the Oeste region and 4.2 days for Portugal.
Table 2. Characteristics of golfers in the sample
Characteristics Country of residence united Kingdom Portugal Scandinavia Ireland Other Gender Male Female Age structure (years) 15-30 31-45 46-60 >60 Level of Education College graduate Other Golf as the motivation for travel Main motivation Secondary motivation No motivation Type of accommodation Hotel Own residence Rented residence Friend's/relative's house Other Length of stay 1 day 2-3 days 47 days 8-15 days Total Frequencies 61 28 13 10 12 99 25 10 41 56 17 52 72 48 60 16 50 48 11 13 2 13 33 53 25 124 Percentage 49.2 22.6 10.5 8.1 9.7 79.8 20.2 8.1 33.1 45.2 13.7 41.9 58.1 38.7 48.4 12.9 40.3 38.7 8.9 10.5 1.6 10.5 26.6 42.7 20.2 100.0
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Finding the main perceptual dimensions with factor analysis T he main perce ptual dimensions that g olf tourists use when com paring the various golf destinations under consideration will be determined using factor analysis. These dimensions are then used to build perceptual maps that show the competitive positions of the various golf destinations under analysis. Then, multiple regression analysis will be used to determine the relative importance of each dimension in the choice of a golf destination. Exploratory factor analysis is a multivariate technique often used to reduce the information contained in a set of original variables into a small number of factors, or dimensions, with minimal loss of information (Gorsuch, 1983). Since it can handle any type of distribution of the original data, the principal components method was the extraction technique chosen to identify the main perceptual dimensions that explain a substantial amount of the variance contained in the original perceptual data. The statistical software package used to process the data was SPSS. Factor analysis (R type) was performed on a table whose rows record the perce ptions of all respondents for all destinations and whose columns correspond to the 22 perceptual attributes, according to the following procedure (Hair, black, babin, Anderson, & Tatham, 2006). Firstly, the correlation matrix was examined to check whether the variables were sufficiently correlated with one another. Secondly, the number of factors to be extracted was determined, and the degree of adjustment of the factor model to the original data was evaluated. Thirdly, the extracted factors were subjected to a Varimax rotation to obtain more easily interpretable factors. Finally, factor scores for each golf destination were computed to be used in further analysis, par ticularly in the building of perce ptual maps and in deter mining the relative importance of each perceptual dimension. To verify whether the variables were sufficiently correlated with one another, a visual inspection of the correlation matrix was carried out; bartlett's test of sphericity (1950) and the Kaiser-MeyerOlkin (KMO) measure of sampling adequacy were also computed. The correlation matrix, in Table 3, shows that nearly all variables have at least one correlation coefficient greater than, or equal to, 0.5 except for three variables where this figure is 0.4. This means that all variables are sufficiently correlated with each other to be included in the analysis. In addition, bartlett's test of sphericity (1950) is statistically significant at the 0.001 level, which allows rejecting the null hypothesis that the correlation matrix is an identity matrix. Finally, the value of the KMO measure was 0.93, a figure which belongs to the range of values that Kaiser (1974) considers to be "wonderful". For these three reasons it is concluded that these data are adequate to be subjected to factor analysis.
Table 3. Correlation matrix
A10 A11 B1 B10 B11 B 2 B 3 B 4 B 5 B 6 B 7 B 8 B 9
A 1 A
A 1 1.
A 2
A 3
A 4
A 5
A 6
A 7
A 8
A 9
2 A 3 A
00 0.39 1.00 0.16 0.40
4 A 5 A
1.00 0.56 0.38 0.04 1.00 0.54 0.41 0.04 0.66 1.00
0.50 0.35 0.07 0.59 0.59 1.00
6 A 7 A
0.55 0.42 0.03 0.64 0.65 0.70 1.00
0.10 0.37 0.43 0.16 0.12 0.18 0.17 1.00 8 A 0.34 0.56 0.50 0.28 0.37 0.34 0.35 0.46 1.00 9 A10 0.10 0.47 0.47 -0.03 0.03 0.14 0.08 0.50 0.45 1.00
A11 -0.09 0.36 0.48 -0.20 -0.18 -0.07 -0.17 0.45 0.41 0.66 1.00 B 0.17 0.40 0.35 0.03 0.13 0.08 0.12 0.28 0.48 0.43 0.41 1.00
1 B 2 B
0.53 0.50 0.06 0.54 0.61 0.48 0.60 0.14 0.39 0.12 -0.08 0.41 1.00
0.46 0.36 0.06 0.52 0.52 0.63 0.62 0.18 0.33 0.07 -0.08 0.17 0.59 1.00
38 COMPETITIVE CHOICE OF GOLF dESTINATIONS
3 B 4 b
0.44 0.51 0.18 0.45 0.47 0.52 0.54 0.20 0.38 0.27 0.14 0.28 0.65 0.60 1.00
0.53 0.46 0.04 0.54 0.55 0.52 0.56 0.13 0.32 0.19 -0.06 0.23 0.69 0.60 0.68 1.00
5 B 6 B
0.30 0.42 0.10 0.33 0.41 0.37 0.36 0.10 0.29 0.19 0.12 0.27 0.58 0.44 0.62 0.54 1.00
0.41 0.44 0.09 0.41 0.43 0.40 0.46 0.18 0.31 0.19 0.10 0.24 0.55 0.55 0.65 0.62 0.72 1.00
7 B 8 B
0.31 0.49 0.29 0.33 0.39 0.41 0.37 0.33 0.41 0.38 0.25 0.42 0.61 0.49 0.59 0.56 0.57 0.56 1.00
0.40 0.52 0.14 0.43 0.49 0.50 0.48 0.21 0.42 0.22 0.11 0.27 0.63 0.65 0.64 0.61 0.60 0.67 0.63 1.00 9 B10 0.24 0.58 0.33 0.34 0.31 0.37 0.37 0.30 0.36 0.35 0.21 0.30 0.42 0.37 0.57 0.50 0.43 0.51 0.60 0.50 1.00
With regard to the number of factors to retain, the eigenvalue criterion, which considers that all factors whose eigenvalues are greater than one should be retained, indicates that three factors should be selected see Table 4. The extraction of three factors is also supported by the Scree Test (Cattell, 1966), since the eigenvalues decrease very little from the third factor onwards. Furthermore, the three factors solution explains more than 60% of the total variance of the original variables, percentage which is considered satisfactory in social sciences (Hair et al., 2006). Finally, this solution is also a good solution from the interpretative point of view, which is a very relevant practical criterion for researchers (Hair et al., 2006; Lattin, Carrol, & Green, 2003).
B11 0.27 0.48 0.34 0.32 0.29 0.30 0.34 0.28 0.41 0.31 0.15 0.38 0.53 0.36 0.59 0.46 0.46 0.42 0.62 0.45 0.65 1.00
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Table 4. Factors extracted with the principal components method Factor
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Eigenvalue
9.25 3.29 1.44 0.88 0.85 0.68 0.60 0.57 0.53 0.46 0.42 0.40 0.35 0.34 0.34 0.29 0.26 0.26 0.25 0.20 0.20 0.17
Variance (%)
42.02 14.96 6.55 3.99 3.87 3.08 2.72 2.60 2.40 2.10 1.90 1.79 1.60 1.55 1.55 1.30 1.19 1.17 1.12 0.91 0.89 0.77
Cumulative Variance (%)
42.02 56.98 63.53 67.52 71.39 74.47 77.18 79.78 82.17 84.27 86.17 87.96 89.56 91.11 92.66 93.96 95.15 96.32 97.43 98.35 99.23 100.00
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Table 5. Solution obtained with the principal components method and Varimax rotation Variable
b6 Championship golf course b7 Course rating in international ranking b8 Good pro shop b4 Course design and competitiveness b9 Good Club House b5 Good course upkeep b2 Ease of obtaining tee-times b11 Good quality of the facilities b10 Good practice and training facilities A7 Good value for money A4 Good hospitality and friendliness of local people A5 Good safety and security A6 Good quality of the gastronomy A1 beautiful Scenery b3 Suitable course fees Pleasant nightlife and entertainment A11 Suitable number of golf courses A3 Good variety of tourism attractions A8 diversity of shopping facilities A9 Good accessibilities A2 Pleasant Climate b1 International airport proximity
Factor Factor Factor Commu1
0.80 0.77 0.73 0.72 0.70 0.64 0.64 0.64 0.63 0.81 0.80 0.78 0.76 0.71 0.62 0.78 0.68 A10 0.77 0.77 0.76 0.70 0.69 0.56 0.55 0.70 0.68 0.76 0.79 0.69 0.83 0.52 0.53 0.71 0.75 0.81 0.72 0.76 0.65 0.62
2
3
nality
0.63 0.69 0.73 0.69 0.69 0.68 0.70
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The solution with 3 factors obtained with Varimax rotation is shown in Table 5. To facilitate the reading of this table, only the factor loadings whose absolute values are greater than 0.50 are shown. This solution is good for a number of reasons. Firstly, almost all variables have factor loadings exceeding 0.60, except two of them which have factor loadings greater than 0.50, a value that is considered significant by Hair et al. (2006). Secondly, nearly all variables are strongly correlated with one factor only. Finally, looking at the values of the communalities, the factor solution explains between 62% and 84% of the variance of the original variables. With regard to the interpretation of the resulting factors, Table 5 shows that the three factors are related to three categories of attributes. Factor 1 is clearly linked to the attributes of golf courses, the most highly correlated being b6 - "Championship golf course", followed by b7 - "Course rating in international ranking", b8 - "Good pro-shop", and b4 "Course design and competitiveness", with factor loadings of 0.80, 0.77, 0.73 and 0.72, respectively. Thus, this factor will be called "Golf ", and reflects the interest in the prestige and competitiveness of the golf courses. Factor 2 is associated with attributes of the golf destination, particularly with variables A7 - "Good value for money", A4 - "Good hospitality and friendliness of local people", A5 - "Good safety and security", A6 - "Good quality of the gastronomy", and A1 - "beauti- ful scenery", with factor loadings of 0.81, 0.80, 0.78, 0.76 and 0.71 respectively. Thus, Factor 2 will be designated "Hospitality and Value", and reflects the interest in the relationship between quality and price, and in the hospitality and security of the golf destination. Factor 3 is strongly correlated with the attributes A10 - "Pleasant nightlife and entertainment", A11 - "Suitable number of golf courses", A3 - "Good variety of tourism attractions", and A8 - "diversity of shopping facilities", with factor loadings of 0.78, 0.77, 0.76 and 0.70 respectively. Therefore, Factor 3 will be called "Entertainment and Leisure", since it reflects the interest in the complementary activi- ties in a golf destination related to tourism entertainment and leisure. Perceptual maps showing the competitive positions of the golf destinations In order to empirically establish the perceived competitive positions of the six golf destinations of Portugal and Spain under analysis, perceptual maps were built, using all respondents, where each golf destination is represented by its mean factor score along each of the three factors - see Figure 2 and Figure 3. These perceptual maps are an excellent way to confront the image of the various objects, simplifying a huge amount of information (Pike & Ryan, 2004). Through this meth-
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COMPETITIVE CHOICE OF GOLF dESTINATIONS
odology it is possible to view the relative positions of the various golf destinations along the three derived perceptual dimensions, as well as the main differences between these destinations. Figure 2 shows the perceptual map revealing the competitive position of the destinations under analysis in relation to dimensions F1 "Golf " and F2 - "Hospitality and Value". Figure 2 reveals that the Oeste region is very well positioned along both dimensions F1 and F2. On the other hand, the Costa de Lisboa region appears well positioned in relation to the "Hospitality and Value" dimension but it is the least well perceived destination on the "Golf " dimension. The Algarve has a slightly above average position along the first two perceptual dimensions, whereas the group of Spanish destinations is relatively poorly positioned regarding F2 - "Hospitality and Value". In fact, the second dimension separates the Spanish golf destinations from the Portuguese ones, with the latter being perceived as offering higher levels of "Hospitality and Value" than their Spanish competitors. Finally, both Costa blanca and Costa brava have below average perceived relative positions on the first two perceptual dimensions, while Costa del Sol is well positioned on the "Golf " dimension.
Figure 2. Perceptual map "Golf "/"Hospitality and Value" (all participants)
Figure 3 shows the perceptual map based on dimensions F1 - "Golf " and F3 - "Entertainment and Leisure". The third dimension separates the Oeste destination from all other destinations, and reveals that Oeste is perceived as the worst destination in terms of "Entertainment and Leisure". The destinations better positioned alongside F3 are the Cos-
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ta brava and the Costa de Lisboa, followed by the Costa del Sol. The Costa blanca and the Algarve display average values as regards dimension F3 - "Entertainment and Leisure".
Figure 3. Perceptual map "Golf "/"Entertainment and Leisure" (all participants)
Determining the importance of the choice dimensions with multiple regression analysis Multiple regression analysis was the technique used to identify the relative importance of each perceptual dimension in the choice of a golf destination. The "recommendation of the golf destination" was used as the dependent variable, since the "choice of the golf destination" was not directly measured, and the independent variables were the factor scores obtained for dimensions F1 - "Golf ", F2 - "Hospi tality and Value" and F3 - "Entertainment and Leisure". The results of the multiple regression analysis are shown in Table 6, in the part referring to "all golfers". Equation (1) shows the linear regression model with the three factors, explaining 43% of the total variation of the variable "recommendation of the golf destination". (1) Recommendation of the golf destination = 4.65 + 0.53 F1 + 0.51 F2 - 0.16 F3; R2= 0 . 4 3 (107.24) (12.57) (5.34) (-7.55) As expected, the "recommendation of the g olf destination" in creases with the increase of dimensions F1 - "Golf " and F2 - "Hos -
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COMPETITIVE CHOICE OF GOLF dESTINATIONS
pitality and Value". Surprisingly, the "recommendation of the golf destination" decreases as dimension F3 - "En ter tainment and Lei sure" increases. The beta values, in Table 6, indicate that the dimensions F1 and F2, whose values are 0.44 and 0.42 respectively, have basically the same importance, and are much more important in the reg ression model than the perce ptual dimension F3, whose absolute value is 0.13. This means that the "recommendation of the golf destination" depends mainly on the perceptions that tourists have of that destination along dimensions F1 - "Golf " and F2 - "Hospitality and Value". The regression model also indicates that the golf destinations that are better perceived in terms of the dimension F3 - "Entertainment and Leisure" have lower levels of recommendation, for equal values of F1 and F2. Investigating differences between "holiday golfers" and "dedicated golfers" The preceding analysis will now be repeated for two segments of tourists mentioned in the literature (Readman, 2003), the "holiday golfers" and the "dedicated golfers", in order to investigate the differences between these two groups of golf tourists. In this part of the analysis only the responses of golfers who do not own a residence in the Praia del Rey resort will be considered - 61.3% of the sample, so as not to include this subjective component in the analysis. It must be pointed out here the fact that 68.7% of the "dedicated g olfers" stated they knew at least four of the six golf destinations under analysis, and 47.2% at least five of these destinations; these figures are 36.2% and 22.4%, respectively, for the "holiday golfers" segment. This means that th e segmen t o f "dedica ted g o lfer s" h a s sup er io r p er so n a l in fo r ma tio n and experience regarding the set of golf destinations under analysis. T he factor analysis car ried out for both segments of g olf tourists showed a factor structure similar to that previously obtained where all respondents were considered. The perceptual maps based on the dimensions F1 - "Golf " and F2 - "Hospitality and Value", prepared for the "holiday golfers" and "dedicated golfers" segments are shown in Figure 4 and Figure 5, respectively. The perceptual map for "holiday golfers", shown in Figure 4, is similar to that obtained where all respondents were considered - see Figure 2. However, the position of the "Costa brava" is perceived by the "holiday golfers" segment to be closer to that of the "Costa del Sol", whereas its position was closer to that of the "Costa blanca" when the perceptions of all golfers were analyzed. In addition, as shown in Figure 4, the Algarve has a less favorable perceived position in relation to dimension F1 - "Golf ".
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Figure 4. Perceptual map "Golf "/"Hospitality and Value" ("holiday golfers")
On the other hand, the perceptual map for the "dedicated golfers" segment, in Figure 5, is quite different, reflecting the better knowledge that this segment has of the several golf destinations under analysis. T h e "dedi ca ted g o lfer s" co n si der th a t th e b est p o si ti o n ed desti n a tions jointly in terms of the dimensions F1 and F2 are the Oeste, the Algarve and the Costa del Sol, with the Costa del Sol slightly exceeding the Oeste on dimension F1 - "Golf ". The Algarve noticeably improves its position along the first perceptual dimension compared to that obtained where all respondents were considered. Turning to dimension F2 - "Hospitality and Value", the three Portuguese golf destinations are valued higher than the Spanish golf destinations, but the Costa del Sol substantially improves its perceived position, compared to that shown in Figure 2. The Costa de Lisboa region, although well positioned along the second dimension, continues to have a less favorable perceived position regarding the "Golf " dimension.
Figure 5. Perceptual map "Golf "/"Hospitality and Value" ("dedicated golfers")
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COMPETITIVE CHOICE OF GOLF dESTINATIONS
Following the same procedure as before, multiple regression analysis was used to determine the relative importance of each perceptual dimension, taking "recommendation of the golf destination", Y, as the dependent variable and the three factors as the independent variables. The multiple regression equations obtained for the "holiday golfers" and the "dedicated golfers" segments are identified below with the numbers (2) and (3), respectively. To facilitate the comparison, the regression model obtained for all respondents is presented again - equation (1). The results of multiple regression analysis for the various segments of golf tourists are shown in Table 6. (1) Y (all participants) = 4.65 + 0.53 F1 + 0.51 F2 - 0.16 F3; R2= 0.43 (107.24) (12.57) (5.34) (-7.55) (2) Y (holiday golfers) = 4.41 + 0.45 F1 + 0.66 F2 - 0.15 F3; R2= 0.47 (20.90) (9.96) (7.68) (-4.56) (3) Y (dedicated golfers) = 4.84 + 0.53 F1 + 0.42 F2 - 0.29 F3; R2= 0.49 (21.65) (9.45) (2.17) (-3.40) The comparison of the various regression models leads to the following conclusions. Firstly, the most important perceptual dimensions are F1 and F2 for the three sets of participants; dimension F3 is considerably less important than the other two dimensions. However, for the "holiday golfers" segment, equation (2) reveals that is the "Hospitality and Value" dimension, F2, which assumes greater importance on the recommendation of the golf course to other people - Table 6 shows a beta value of 0.51. The "Golf " dimension, F1, also presents an appreciable relative importance, with a beta figure of 0.40. On the contrary, regarding the "dedicated golfers" segment, equation (3) reveals that is the "Golf " dimension which assumes greater importance on the recommendation of the golf course to other people - its beta value is 0.45. For this segment the dimension "Hospitality and Value" is the second most important, with a beta figure of 0.39. These results are in line with what one would expected, with "holiday golfers" putting more emphasis on the "Hospitality and Value" of the golf destination and the "dedicated golfers" preferring firstly the aspects related to the practice of "Golf ". The "dedicated golfers" also have the particularity of weighing the dimension F3 - "Entertain- ment and Leisure" more negatively than the "holiday golfers"; their beta values in Table 6 are -0.25 and -0.12, respectively.
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Table 6. Multiple regression results for the various segments of respondents
dependent variable: Recommendation of the golf destination
B
All golfers Constant F1 F2 F3 Holiday golfers Constant F1 F2 F3 dedicated golfers Constant F1 F2 F3 4.84 0.53 0.42 -0.29 4.41 0.45 0.66 -0.15 4.65 0.53 0.51 -0.16
Beta
t
107.24
Multiple R
0.65
R Square
0.43
0.44 0.42 -0.13
12.57 5.34 -7.55
20.90 0.40 0.51 -0.12 9.96 7.68 -4.56
0.69
0.47
21.65 0.45 0.39 -0.25 9.45 2.17 -3.40
0.70
0.49
Managerial implications The results obtained in the previous section suggest the existence of two well-defined types of golfers, and confirm the difficulties of managing a golf destination mentioned in the literature (e.g., Amorós, 2003; Petrick & backman, 2002). Important factors for golfers are not only the level of quality of the products and services offered, crucial for developing the loyalty of consumers and the competitiveness of a golf destination, but also other, more difficult to control, such as the hospitality and security of the golf destination, which also depend on the residents and local authorities.
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COMPETITIVE CHOICE OF GOLF dESTINATIONS
The multivariate method in this research can be useful for managers of golf destinations to support policies and practices aiming at capturing the preferences of these two segments of golfers and, consequently, to improve the competitive position of the golf destinations under their command. Taking the region Oeste of Portugal as an example, its position in all the derived perceptual maps indicates the possibility of using consumers as "ambassadors" of this destination. Thus, the excellent competitive position of the Oeste golf destination should be included in its communication policy, aimed at both the final consumers and the distribution channels. The Oeste region could develop and implement relational marketing strategies aimed at developing the golfers' loyalty, and policies that intensify the "word of mouth". It could also offer familiarization trips for specialist journalists and tour operators. Turning to the Algarve, the quality of its "Golf " is recognized by the experts, the "dedicated golfers" segment, but the "holiday golfers" segment does not perceive this golf destination in such a positive way in fact, Figure 4 shows that the Algarve is perceived below the average along the "Golf " dimension. One reason for this might be that the Algarve is not effective in the way it communicates the excellence of its golf courses to the less connoisseur, "holiday golfers" segment. To improve the competitive position of the Algarve along the "Golf " dimension, concerning the "holiday golfers" segment, managers should focus on improving the scores of this destination on the original variables which load highly on this dimension, and where the Algarve is at a competitive disadvantage. The inspection of the mean of the original variables shows that managers should pay particular attention to variables b6 - Championship golf course and b7 - Course rating ininternational ranking. dISCuSSION The central objective of this study is to determine the main factors influencing the choice of a golf destination. This research aims to expand the literature on perceptual mapping and on strategic marketing by being the first which uses factor analysis to derive perceptual maps that establish the perceived competitive positions of golf destinations. Factor analysis revealed that golfers use three main perceptual dimensions when they evaluate the golf destinations under analysis. These are the dimension F1 - "Golf ", which is clearly associated with the attributes of the golf courses, the dimension F2 - "Hospitality and Value", which reflects the interest in the price-quality ratio and in the hospitality and security of the golf destination, and the dimension F3 - "Entertainment and Leisure", which mirrors the interest in the complementary activities offered by a tourism destination, namely in
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the entertainment and leisure tourism activities. The perceived competitive positions of the six main golf destinations of Portugal and Spain were then empirically established through the construction of perceptual maps, where each golf destination is represented by its average factor score. Multiple regression analysis, where the "recommendation of the golf destination" was the dependent variable and the independent variables were the three factors, F1 - "Golf ", F2 - "Hospitality and Value" and F3 "Entertainment and Leisure", revealed that, where all respondents were considered, the dimensions "Golf " and "Hospitality and Value" have basically the same importance, and are much more important than the dimension "Entertainment and Leisure" in the choice of a golf destination. This analysis also showed, as expected, that the "recommendation of the golf destination" increases with the increase of the dimensions F1 - "Golf " and F2 - "Hospitality and Value". This corroborates research results reported by Silvestre et al. (2007) where a factor representing the characteristics of the golf course was found to positively affect the intentions of golfers to recommend the Algarve's golf courses. Surprisingly, the "recommendation of the golf destination" decreases with the increase of the dimension F3 - "Entertainment and Leisure", which is a result that could be studied in future research. This regression model explains 43% of the total variation of the variable "recommendation of the golf destination". The preceding methodology was repeated for two segments of golfers - "holiday golfers" and "dedicated golfers", revealing different perceptual maps for these two segments. The "holiday golfers" clearly set the Oeste region apart from the competition, while the "dedicated golfers", more knowledgeable of the various golf destinations under analysis, do highlight a competitive cluster that includes the Oeste, the Algarve and the Costa del Sol. Regarding the relative importance of the perceptual dimensions, for "holiday golfers" the most important dimension influencing the "recommendation of the golf destination" to other people is the dimension F2 - "Hospitality and Value", followed by dimension F1 - "Golf ". On the contrary, for the "dedicated golfers" segment, the importance of these two perceptual dimensions is reversed. In addition, the "dedicated golfers" segment attributes far greater importance to the dimension F3 - "Entertainment and Leisure" than the "holiday golfers", a dimension which is considered undesirable by both segments. This finding, however, is not in line with the "avid golfer" segment of the typology of golf tourists suggested by Tassiopoulos and Haydam (2008). This segment, which shares with the "dedicated golfers" segment the fact of having golf as the primary focus of the travel, prefers (along with other variables) the existence or availability of night life, which is a variable highly correlated with the undesirable "Entertainment and Leisure" dimension.
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The results of this research suggest the existence of two well defined types of golfers, with different preferences, and corroborate the difficulties of managing a golf destination mentioned in the literature (e.g., Amorós, 2003; Petrick & backman, 2002). However, unlike some studies (Silvestre, Correia, & barros, 2007) which claim that golf tourism is a focused activity not connected to the tourism destination, this study suggests that the attributes of the destination play a relevant role in the choice of a golf destination. On the other hand, the present results partially confirm the findings obtained by Hutchinson et al. (2009) in the sense that the perceived value, a variable which is highly correlated with the "Hospitality and Value" dimension, has a positive influence on word-of-mouth/recommendation of the golf destination. The reported results should be appraised with regards to the limitations of this research. One of these is the type of sampling method used; a non-probabilistic sampling method was used, namely a quota sample, which precludes the generalization of the results of this research. Another limitation of this study is the period during which the data was collected, throughout december 2006 and January 2007, which does not cover the entire annual spectrum and the associated seasonality. A third important limitation stems from having compared six golf destinations using data collected on only one of them - the Oeste destination. If, on the one hand, this is not a problem in terms of the application of the multivariate methodology explored in this study which can be used with other research designs, on the other hand, the excellent results of the Oeste region, compared with other more mature and consolidated destinations, might have been influenced by the positive perceptions that the respondents were experiencing at the Oeste at the moment of the data collection. Indeed, the Praia del Rey golf course is located in a unique spot in terms of natural landscape. The resort won the prize of Golf Resort of the Year - Europe 2007, awarded by the International Association of Golf Tourist Operators (IAGTO), and the golf course has won several international awards for its location, design and competitiveness. Some methodological issues for discussion and future research are also suggested. definitely, it would be of interest to analyze how the results obtained might differ depending on the golf destination where the data are collected. but, what should be the optimal design for this type of study regarding the selection of the respondents? Should the sample contain golfers who are actually playing in each of the golf destinations under analysis? Or would it be better to survey golfers who have recently played in the golf courses under analysis, but who are in their houses, in their home countries? A result of this research that might trigger further investigation on attributes or dimensions that are unwanted by golf tourists is the find-
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ing that dimension F3 - "Entertainment and Leisure" is considered undesirable by both segments of golfers. In fact, another recent research the study by barros, butler and Correia (2010) - has also found an attribute which is not wanted by golf tourists. These researchers analyzed the length of stay of golf tourists in the Algarve, via survival models, and found that the "length of stay decreases with (the attribute) beach, signifying that golf tourists are not sea oriented tourists". Finally, the methodology used in this research could be useful at different periods of the year to observe the changing perceptions of the golf tourists, and to research other segments of golf tourists such as golfers from specific countries, or segments derived through the use of multivariate clustering techniques. A comparison of the results would be possible. REFERENCES
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