Characterization of Profiles as Management Strategies Based on the Importance and Valuation That Users Give to the Elements of the Golf Courses

sustainability Article Characterization of Profiles as Management Strategies Based on the Importance and Valuation That Users Give to the Elements of the Golf Courses Virginia Serrano-Gómez 1,*, Óscar García-García1, Vicente Gambau i Pinasa 2 and Antonio Rial-Boubeta 3 1Faculty of Educational Sciences and Sports, University of Vigo, 36005 Pontevedra, Spain; oscargar[email protected] 2Faculty of Sport Sciences and Physical Education, University of Coruña, 15179 Oleiros, Spain; [email protected] 3Faculty of Psychology, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain; [email protected] *Correspondence: [email protected] Received: 16 May 2020; Accepted: 9 June 2020; Published: 11 June 2020   Abstract: The main objective of this study was to characterize golfers’ profiles based on the importance and valuation that users give to the elements of golf courses, considering the segmentation as key to making strategic decisions. This was done using a priori segmentation of the traditional style against a post hoc segmentation based on the importance that users concede to variability of elements of golf courses. Moreover, the relationship between the quality attributed to the service dimensions and the golf course global performance was examined for each of the obtained segments. The results have established certain specific characteristics of the typical golf user and two large segments of golfers were identified from Cluster Analysis (Competitives and Socials), they were made up of the following subgroups: Regular-leisure and business and matures-familiar. The causal analysis of covariance structures for each segment revealed partially different interests. This study provides useful information for managers to design management strategies that address the different characteristics, interests, and priorities of their customers and potential customers in order to win them, keep them, satisfy them, and build their loyalty, ensuring the development and sustainability of the entity. Keywords: strategic management; consumer psychology; cluster analysis; sport consumer loyalty; golf industry; segmentation 1. Introduction Nowadays, understanding consumer behavior and the identification of the main features of a product and services, which play an important role in the consumer’s decision-making, constitute the main concern of the marketing programs of any organization [1,2]. Market segmentation is a key tool in marketing management [ 3 ]. According to Miquel et al. [4] (p.30) , segmentation is differentiation of the total market of a product or service, in a certain number of elements, people, or organizations, homogeneous among them and different from others in terms of habits, needs, and tastes of their components, which are called segments, obtained by different statistical procedures, in order to apply to each segment the most appropriate marketing strategies to achieve the objectives established a priori by the company. To assume that the market is not uniform and that there are different groups of consumers with different profiles and particular needs, attitudes, motivations, experiences, and behaviors, enabling organizations to better understand the markets in which they are inserted and be more competitive. Sustainability 2020,12, 4781; doi:10.3390/su12114781 www.mdpi.com/journal/sustainability Sustainability 2020,12, 4781 2 of 15 In practice, diverse strategies and procedures have been proposed to try to segment a market [ 5 ]. Socio-demographic criteria have been used to categorize subjects depending on age, gender, occupation, professional status, level of education, or income. These criteria have been shown to have a high explanatory capacity, but they have been losing importance in mature markets. Different authors [ 6 – 8 ] have noted the increasing relevance of subjective variables, such as lifestyle, motivations, attitudes, preferences, or importance [ 9 , 10 ], as referents more powerful in characterizing of consumers. Nowadays, it is common to opt for strategies capable of integrating both types of information, through the use of advanced multivariate methods, such as Cluster Analysis [ 11 ] or the CHAID procedure [12,13]. In the case of sports services of which nature is intangible, the market segmentation is essential [14–16] . Several studies [ 17 – 19 ] suggest that the way to achieve the satisfaction of users of sports services may be different depending on the segment or profile in question. The golf industry has not escaped the need for a detailed analysis of user ´ s profile, which, in recent years, has gone from being an expensive game of riches to a mass hobby [ 20 , 21 ]. This assessment seems essential when its social projection has achieved in recent years more than 60 million players across the world [ 22 ] and it is currently considered as the primary sport in the world in terms of financial expenses [23,24]. These figures allow describing it as a massive sport, and every year, more women and children begin to play golf, to emphasize the social importance of this activity. In addition, golf constitutes a business area of rising importance, not only linked to touristic services, but also associated with the amount of employment which this activity generates in different organizations [22,25]. Golf Around the World [ 26 ] shows more than one-third (36%) of the U.S. population played, watched, or read about golf in 2018. Europe has the second largest regional share with 23% of the world’s total. England is the number one golfing country in Europe with 2270 golf courses and 31,620 golf holes. Spain takes sixth place in Europe with 497 golf courses, 7071 holes, 471 facilities and 269.853 federative licenses (71.73% males/28.26% females), of which 10.452 are licenses from Galicia (72.4% males/27.6% females) [27]. As a result, the typology of golfers has been progressively diversifying from socio-demographic, attitudinal, and motivational the point of view. Besides, the concept of golf club itself has evolved into something complex and multidimensional, which has attracted the interest of recent studies. Most of these studies focus on the segmentation of golf market as promotion strategy, linking the golfers’ perception of quality of service with satisfaction, the perceived value and other different variables of interest, such as gender [ 28 , 29 ], age [ 30 ], the player ´ s limitations and experience, motivation [ 31 ], participation [ 32 ], or exercise adherence intention [ 21 ]. However, most related publications are focused on the perspective of golf tourist and intention to return to destination [ 33 – 35 ], rather than making a comprehensive segmentation of golfers in a community or in a particular country. In the latter case, it would be possible to identify and characterize the different existing profiles and typologies, also considering the different types of golf courses and management methods as a form of strategy that allows the improvement and sustainability of these sports clubs. In this sense, sustainability must be an element in the long-term planning of golf organizations, from a social, economic, and environmental point of view. For all the above, the purpose of this study will be to characterize golfers ´ profiles based on the importance and valuation that users give to the elements of golf courses, considering the segmentation as key to making strategic decisions. To identify the existence of different users ´ profiles, two complementary strategies will be used. On the one hand, a priori segmentation of the traditional style based on socio-demographic data, motivational, sports practice aspects, and habits linked to playing golf. On the other hand, a post hoc segmentation to identify profile subtypes from Cluster Analysis using different stages. Sustainability 2020,12, 4781 3 of 15 In addition, the relationship between the quality attributed to the dimensions referred to service and the golf course global performance for each of the main segments previously obtained from Cluster Analysis will be examined. In this way, an attempt will be made to verify to what extent the ways to achieve the approval of golf users may vary depending on the type of golfer, since if so, it will be necessary to implement different recruitment and/or loyalty strategies that allow the sustainability of these sports entities, through the continuous adaptation of the service to such a changing society and market. 2. Materials and Methods 2.1. Participants Participants were 968 golf users of Galicia—Northwest of Spain—belonging to 13 different clubs with different types of installations (golf courses of 9 and 18 holes, and pitch and putt) and management forms (private, public, commercial, and mixed). Of these, 796 were men (82.2%) and 172 women (17.8%). Their ages were between 16 and 79 years old (x =47.58; Sx =12.51), more than half (57.75%) between 41 and 60. Most of them were club members (59.7%) and had a moderate level of golf with handicaps between 11.6 and 18.4 (Table 1). Table 1. Distribution of practitioners according to gender, age, and handicap. Gender Men (82.2%) Women (17.8%) Age Average: 47.58 age; Typical deviation: 12.51 <30 (11.1%) 31–40 (15.6%) 41–50 (29.4%) 51–60 (28.3%) >60 (15.6%) Handicap (Better players are those with the lowest handicaps) Category 1 Category 2 Category 3 Category 4 Category 5 Category 6 ≤4.4 (3.8%) 4.5 to 11.5 (19.2%) 11.6 to 18.4 (31.8%) 18.5 to 26.4 (17.7%) 26.5 to 36.4 (25.9%) >36.4 (1.7%) Without handicap (4.02%)/(Beginners) 2.2. Process The selective methodology was used. Data were collected from a closed structured interview conducted by interviewers unconnected with the club and trained specifically for this (supervised by the person responsible for the study and authorized by the manager). To collect information, interviewers used an ad hoc questionnaire. Participants were selected accidentally, voluntarily and, following the advice of golf course managers, during the busiest months of the year (spring and summer seasons). In addition, to try to make up for the lack of randomness in the selection of the sample units, the data from each club were collected on different days and time zones, to try to achieve the highest possible degree of sample representativeness. The interviews had an approximate duration of 15 min. Participation in the study was completely voluntary, making special emphasis on the guarantee of confidentiality and anonymity referred to the answers. Written informed consent was obtained from all individual participants included in the study. The research protocol followed the principles of the Declaration of Helsinki regarding research involving human subjects—64th World Medical Assembly 2013. The study was approved by the management board of the golf courses, as well as by the Ethics local Committee. Sustainability 2020,12, 4781 4 of 15 2.3. Instrument The ad hoc questionnaire used was structured and closed, composed of a section of segmentation where socio-demographic, motivational, attitudinal and sport practice information (Figure 1) appeared, and on the other hand (Figure 2), a section of assessment of the importance-valuation of elements that make a golf club, with a general assessment section that included three additional items as performance indicators: Global assessment, degree of fulfillment of expectations, and general user satisfaction. The scale used was based on previous studies [ 36 , 37 ], obtained from Confirmatory Factor Analysis (CFA) (Table 2), with high internal consistency both globally ( α Global =0.91) and for each of the dimensions ( α Personal =0.87; α Facilities =0.86; y α Course/Play zone =0.76 ( α =0.92) and high ability to explain user satisfaction (R2=0.724). 2.3. Instrument The ad hoc questionnaire used was structured and closed, composed of a section of segmentation where socio-demographic, motivational, attitudinal and sport practice information (Figure 1) appeared, and on the other hand (Figure 2), a section of assessment of the importancevaluation of elements that make a golf club, with a general assessment section that included three additional items as performance indicators: Global assessment, degree of fulfillment of expectations, and general user satisfaction. The scale used was based on previous studies [36,37], obtained from Confirmatory Factor Analysis (CFA) (Table 2), with high internal consistency both globally (αGlobal = 0.91) and for each of the dimensions (αPersonal = 0.87; αFacilities = 0.86; y αCourse/Play zone = 0.76 (α = 0.92) and high ability to explain user satisfaction (R 2 = 0.724). Figure 1. Segmentation questionnaire for users of golf clubs (first part). SEGMENTATION QUESTIONNAIRE FOR USERS OF GOLF CLUBS Gender: (point with an X) M W Age: Handicap: At what age did you start playing: Respect to the club is: (point with an X) Member Subscriber Guest Correspondece Free use Other Which: Your usual frequency of play is: (point with an X) Weekly Monthly Occasionally (Once every 3-6 months) Sporadic (once a year) Only on holidays Almost never /never The day you pla, how much time you spend: Practice motivations: (Indicate with nº up to 3 in order) Fun To do physical activity Socialize Enjoy nature Release stress Business Compete Other Other. Which? Barriers that impede you playing golf more often: ( Indicate with nº up to 3 in order ) Lack of time Family responsabilities Distance Travel/outside the area Climatology Little motivated Work Price Other. Which? ( Indicate with nº up to 3 in order ) Who do you usually play golf with? Alone Family Friends Couple Mate Other Which? Have you used the services of other golf clubs? (Point with an X) No Yes ¿In how many different clubs? (Indicate the nº) Do you travel to golf tourist destinations? (Point with an X) No Yes Where? ( Indicate 3+frequent) 1. 2. 3. Services most used in the club (Up to 3 in order. Ex.Restaurant, room of clubs…) Practice course Specialized shop Putting-green Golf school Room of clubs/batteries Sports services Rental equipment Restaurant Rental buggies Coffee shop Other. Which? 1. 2. 3. Other usual sports: (Indicate up 3 in order) Academic training: (Point with an X) No studies Elementary Secondary Baccalaureate Vocational training University Occupation: (Point with an X) Civil servant Security forces Entrepreneur Retired Professional Pensioner Self employed Student Senior manager Unemployed Middle manager Home care Employee Another occupation Habitual residence in: Zip code: Figure 1. Segmentation questionnaire for users of golf clubs (first part). Sustainability 2020,12, 4781 5 of 15 Figure 2. Questionnaire second part, level of global importance and valuation of each element, and overall valuation. Adapted from Serrano-Gómez et al. [29]. Table 2. CFA. Goodness-of-fit indices for the causal covariance structure models. χ 2 gl p χ 2 /gl GFI AGF I CFI NFI TLI RMSEA [IC] * Final Casual Model 274.84 73 < 0.001 3.76 0.96 0.95 0.97 0.96 0.96 0.053 (0.047–0.060) QUESTIONARY IMPORTANCE Level of global Importance – Valuation of each elements of golf clubs. (Point with an X the level from 1 to 5) VALUATION None Litle Some Pretty Much Very bad Bad Avera ge Good Very Good 1 2 3 4 5 1 2 3 4 5 Importance STAFF PROFESSIONALISM Valuation 1 2 3 4 5 Management professionalism 1 2 3 4 5 1 2 3 4 5 Receptionist professionalism 1 2 3 4 5 1 2 3 4 5 Greenkeeper’s professionalism 1 2 3 4 5 1 2 3 4 5 Master Caddie’s professionalis m 1 2 3 4 5 1 2 3 4 5 Golf’s Teachers professionalism 1 2 3 4 5 1 2 3 4 5 Management involvement 1 2 3 4 5 1 2 3 4 5 Management professionalism 1 2 3 4 5 Importance MANAGEMENT Valuation 1 2 3 4 5 Management involvement 1 2 3 4 5 1 2 3 4 5 Organization and management of resources 1 2 3 4 5 1 2 3 4 5 Information management 1 2 3 4 5 1 2 3 4 5 Complaints and suggestions management 1 2 3 4 5 1 2 3 4 5 Safety and risk prevention 1 2 3 4 5 1 2 3 4 5 Environmental management 1 2 3 4 5 1 2 3 4 5 Championship organization in the club 1 2 3 4 5 Importance FACILITIES Valuation 1 2 3 4 5 Cleaning and general sanitation 1 2 3 4 5 1 2 3 4 5 State of club facilities 1 2 3 4 5 1 2 3 4 5 State of furnishings and materials 1 2 3 4 5 1 2 3 4 5 Club-House/ Social roo m 1 2 3 4 5 1 2 3 4 5 Changing rooms 1 2 3 4 5 Importance COURSE Valuation 1 2 3 4 5 Course state 1 2 3 4 5 1 2 3 4 5 Game control/ Rules 1 2 3 4 5 1 2 3 4 5 Course design 1 2 3 4 5 1 2 3 4 5 Course safety 1 2 3 4 5 1 2 3 4 5 Practice area 1 2 3 4 5 1 2 3 4 5 Course state 1 2 3 4 5 Considering together all services, staff and club facilities, y ou would sa y that……….. Complete with an X The overall assessment about the club is… Very Bad Bad Average Good Very Good NA The degree of confirmations of your expectations has been… Much worst than expected Worse than expected As expected Better than expected Much better than expected NA From 0 to 10, your Overall Satisfaction level is… 0 1 2 3 4 5 6 7 8 9 10 Figure 2. Questionnaire second part, level of global importance and valuation of each element, and overall valuation. Adapted from Serrano-Gómez et al. [29]. Table 2. CFA. Goodness-of-fit indices for the causal covariance structure models. χ2gl p χ2/gl GFI AGFI CFI NFI TLI RMSEA [IC] * Final Casual Model 274.84 73 <0.001 3.76 0.96 0.95 0.97 0.96 0.96 0.053 (0.047–0.060) * 90% confidence interval for the Root Mean Square Error of Approximation (RMSEA) Sustainability 2020,12, 4781 6 of 15 2.4. Analysis of Data To identify the existence of different users’ profiles, two complementary strategies were used: (1) We proceeded to a descriptive and univariate analysis of the various questions of the questionnaire referred to socio-demographic, motivational, and sports practice aspects. (2) We carried out a two-stage Cluster Analysis [ 38 , 39 ] to identify profile subtypes performing a hierarchical Cluster Analysis in the first, exploratory stage, and an iterative Cluster Analysis in the second stage to obtain the final solution. On the hierarchical Cluster Analysis—cluster procedure of the IBM SPSS Statistics 24.0, Euclidian distances were chosen as the similarity measures and Ward’s algorithm was used as the most statistically powerful method compared to other agglomerative clustering techniques because of its use of F values to maximize differences among clusters [ 40 , 41 ]. The resulting dendrogram was examined, checking the distance of each subject to his/her merged cluster and the size of each cluster, finding the four-cluster solution as the optimal one. In the second stage of the two-stage clustering procedure, k-means clustering was conducted using the means of the four-cluster solution as the starting seed points. This k-means procedure was used to improve the initial assignment of subjects to clusters and obtain the final solution. Iterative procedures, such as this one, are more powerful and reliable than hierarchical ones but need previous specification of the number of clusters and its initial centers. The resulting groups or subtypes were compared on socio-demographic, motivational, and behavioral variables not included in the original clustering process in order to validate and adequately characterize each of the clusters. These qualitative variables were analyzed with cross-tables using chi-square analyses to assess the global significance and corrected standardized residuals [ 42 ] to know the specific associated categories. In addition, in order to examine the relationship between the quality attributed to the dimensions referred to service and the club’s global performance, for each of the segments obtained from Cluster Analysis. Structural analysis of covariance was carried out using the dimensions concerning the perceived quality as predictors and three performance indicators as criteria. 3. Results 3.1. Distribution of Practitioners According to Socio-Demographic Variables Socio-demographic variables show that most are men (82.2%), the average age is 47.5 years old, 68.5% have a university education, and occupations are mostly entrepreneurs (17.9%) and civil servants (16.9%). 3.2. Distribution of Practitioners Based on Motivation and Sports Practice The main reason (62.2%) for playing golf is its recreational character, followed by improving physical condition (12.2%) and competing (8.2%). The main barrier is the lack of time in general (44%), followed by work (28%) and climatology (11.7%). Sixty percent of golfers also practice other sports (tennis 11.5%, fitness 10.8%, paddle and football 10.7%, swimming 10.5%) and 51.7% do golf tourist travels. 3.3. Distribution of Practitioner According to the Type of Practice of Play More than half of users (59.7%) are members of a club, have handicap between 11.6 and 26.4 (third category), play golf once or twice a week (87.5%), in the company of friends (66.7%), alone (11.2%), or in family (7.1%), for nearly four hours. The age at which they started is very variable, but on average it is 39 years old. The most commonly used services in the club are essentially the practice course (58.4%), coffee shop (14.8%), the putting green (8.1%), and room of clubs (7.1%). In addition, 86.2% have used the facilities and courses of other golf clubs. Sustainability 2020,12, 4781 7 of 15 3.4. Importance of Different Elements of Golf Club It is indicated below (Table 3) the importance that users give to each of the 25 elements of a golf club considered by Serrano-G ó mez et al. [ 29 ]. Although all the elements obtained high averages, five of them stand out with averages higher than 4.50: Maintenance–course condition (4.70), cleaning-hygiene (4.65), treatment and care (4.58), professionalism of teachers (4.55) and physical state–maintenance of facilities (4.54). Table 3. Importance of different elements of golf club (Scale of 1–5). ELEMENTS OF GOLF CLUB IMPORTANCE Average Typical Deviation Involvement of Directive 4.34 0.86 Professionalism management 4.41 0.80 Professionalism reception 4.31 0.78 Professionalism green keeper 4.46 0.71 Professionalism master caddie 4.42 0.73 Professionalism golf teacher 4.55 0.71 Treatment and care provided 4.58 0.67 Organization and management of club resources 4.39 0.73 Information/communication management 4.17 0.82 Complaints and suggestions management, fast and efficient 4.12 0.87 Safety and risk prevention 4.30 0.86 Environmental management 4.35 0.73 Organization of tournaments in club 4.43 0.73 Correspondence with other clubs 4.34 0.81 Cleaning and general hygiene 4.65 0.56 Physical state–maintenance of club facilities 4.54 0.64 Physical state of furniture–equipment–club equipment 4.35 0.74 Social hall-Clubhouse 4.24 0.81 Changing room 4.41 0.74 Golf Academy/School 4.40 0.75 Maintenance/Course condition 4.70 0.55 Control of play/Compliance with regulation in the course 4.38 0.83 Design and round of the course 4.44 0.69 Course security 4.42 0.77 Practice zone 4.38 0.72 3.5. Analysis of Simple Variance for the Comparison of the Four Groups The results of the two-stage Cluster Analysis revealed four reliable subtypes that were differentiated by the importance they concede to various elements that shape the perception of a golf course, as well as their demographic, motivational, and usage profile (Table 4). 3.6. Contingency Tables Crossing the Cluster of Membership with Different Variables of Interest The results of contingency tables crossing the cluster of membership with different variables of interest are shown in Table 5. The contrast value of independence χ2 and its statistical significance are collected. Sustainability 2020,12, 4781 8 of 15 Table 4. Analysis of simple variance for the comparison of the four groups. Dependent Variables F gl Sig. G1 G2 G3 G4 Involvement of directive 14.274 967 <0.001 4.13 2.86 4.38 4.76 Professionalism management 182.98 967 <0.001 4.18 2.90 4.49 4.80 Professionalism reception 145.69 967 <0.001 3.85 3.36 4.36 4.79 Professionalism green keeper 142.06 967 <0.001 4.13 3.50 4.46 4.89 Professionalism master caddie 113.63 967 <0.001 4.06 3.67 4.39 4.87 Professionalism golf teacher 82.94 967 <0.001 4.12 4.10 4.56 4.92 Treatment and care provided 125.92 967 <0.001 4.19 3.73 4.69 4.90 Organization and management of club resources 202.54 967 <0.001 4.03 3.14 4.49 4.81 Information/communication management 189.55 967 <0.001 3.64 3.25 4.13 4.78 Complaints and suggestions management, fast and efficient 219.95 967 <0.001 3.42 3.23 4.16 4.74 Safety and risk prevention (emergencies) 215.07 967 <0.001 3.67 3.06 4.50 4.78 Environmental management 117.38 967 <0.001 3.79 3.82 4.46 4.72 Organization of tournaments in club 72.54 967 <0.001 4.16 3.77 4.39 4.82 Correspondence with other clubs 62.14 967 <0.001 3.95 3.72 4.38 4.69 Cleaning and general hygiene 124.57 967 <0.001 4.32 3.99 4.70 4.96 Physical state–maintenance of club facilities 166.67 967 <0.001 4.14 3.74 4.57 4.97 Physical state of furniture–equipment–club equipment 250.61 967 <0.001 3.84 3.35 4.35 4.92 Social hall–Clubhouse 154.78 967 <0.001 3.75 3.49 4.17 4.83 Changing room 178.97 967 <0.001 3.92 3.53 4.43 4.92 Golf Academy/School 119.10 967 <0.001 3.97 3.65 4.42 4.85 Maintenance/Course condition 122.20 967 <0.001 4.43 3.95 4.76 4.98 Control of play/Compliance with regulation in the course 162.54 967 <0.001 3.97 3.09 4.47 4.83 Design and round of the course 78.50 967 <0.001 4.11 3.96 4.39 4.83 Course security 217.88 967 <0.001 3.90 3.25 4.56 4.89 Practice zone 136.34 967 <0.001 3.96 3.71 4.33 4.88 Table 5. Contingency tables crossing the cluster of membership with different variables of interest. VARIABLES χ2p Type of Installation (Course vs. Pitch & Putt) 13.29 <0.01 N◦of Holes 24.74 <0.001 Gender 11.17 <0.05 Handicap 17.20 <0.05 Relationship with the club 42.86 <0.001 Frequency of play 34.47 <0.01 Hours that play 31.70 <0.001 Main motivations 45.15 <0.05 Main barriers 57.16 <0.01 Who do you usually play with 55.98 <0.001 Travels to golf destination 7.85 <0.05 More used services 68.76 <0.001 Other practiced sports 180.68 <0.001 Academic training 30.92 <0.01 Occupation 95.92 <0.001 3.7. Cluster Analysis The results of the Cluster Analysis identify 4 subgroups of golf club users: (1) Regular, (2) leisure and business, (3) matures, (4) familiar. However, the proximity between the subgroups (Figure 3) makes the first two join in a conglomerate or cluster of second level (Competitives), while subgroups 3 and 4 make up second macro-cluster (Socials). Sustainability 2020,12, 4781 9 of 15 Figure 3. Segments and subgroups obtained from Cluster Analysis. Although it is important to note that, in any case, profiles or types are pure, the analysis carried out allows to establish some characterization of each of them: 3.7.1. CLUSTER 1. Competitive Regular The members of this subgroup (22.8%) give importance, especially to (1) the maintenance and course condition, (2) cleaning and hygiene of facilities, (3) the treatment and care of staff, and (4) the professionalism of management. Here, are mainly concentrated users of 18 holes golf courses, it is where there are more men and young people under 30 years, and a higher proportion of people with university education (64.2%). They started playing at an early age and have a relatively low handicap in comparison with other subgroups (they are better players). Professional occupations are diverse, although it is the subgroup where there is a greater number of senior managers. They play with friends almost every week, about three hours and a half, for fun and exercise. Lack of time and work reasons is the main barrier. They usually use the practice course and putting green. In all, Cluster 1 could be labeled as Competitive regulars, for whom golf is relatively serious and also a chance to play sports and keep fit. 3.7.2. CLUSTER 2. Competitive of Leisure and Business This subgroup (7.2%), although it shares elements of the previous one, clearly gives less importance to all aspects of the service. It only grants importance higher than four to the golf teacher. Like the first cluster, they are mostly golf course users and less of pitch and putt. The age ranges from 45 to 60 years old, they have a handicap medium (slightly worse than subgroup 1) but better than socials. Comparatively, it is the cluster with less university education and where there is greater presence of civil servants and self-employed. Most are members and it is where they most use correspondence between clubs, maybe that is because there are more individuals playing alone. Like the other subgroups, most play weekly, although this is where there is a greater proportion of subjects that play occasionally. They do it mainly to have fun, although comparatively with the rest they indicate more—the opportunity to make contacts and business. On the other hand, they are the ones who participate more in tournaments, their main barrier is the lack of time and the work, adding also as an impediment “the distance to the club”. They like walking, cycling, swimming, and paddle. They Figure 3. Segments and subgroups obtained from Cluster Analysis. Although it is important to note that, in any case, profiles or types are pure, the analysis carried out allows to establish some characterization of each of them: 3.7.1. CLUSTER 1. Competitive Regular The members of this subgroup (22.8%) give importance, especially to (1) the maintenance and course condition, (2) cleaning and hygiene of facilities, (3) the treatment and care of staff, and (4) the professionalism of management. Here, are mainly concentrated users of 18 holes golf courses, it is where there are more men and young people under 30 years, and a higher proportion of people with university education (64.2%). They started playing at an early age and have a relatively low handicap in comparison with other subgroups (they are better players). Professional occupations are diverse, although it is the subgroup where there is a greater number of senior managers. They play with friends almost every week, about three hours and a half, for fun and exercise. Lack of time and work reasons is the main barrier. They usually use the practice course and putting green. In all, Cluster 1 could be labeled as Competitive regulars, for whom golf is relatively serious and also a chance to play sports and keep fit. 3.7.2. CLUSTER 2. Competitive of Leisure and Business This subgroup (7.2%), although it shares elements of the previous one, clearly gives less importance to all aspects of the service. It only grants importance higher than four to the golf teacher. Like the first cluster, they are mostly golf course users and less of pitch and putt. The age ranges from 45 to 60 years old, they have a handicap medium (slightly worse than subgroup 1) but better than socials. Comparatively, it is the cluster with less university education and where there is greater presence of civil servants and self-employed. Most are members and it is where they most use correspondence between clubs, maybe that is because there are more individuals playing alone. Like the other subgroups, most play weekly, although this is where there is a greater proportion of subjects that play occasionally. They do it mainly to have fun, although comparatively with the rest they indicate more—the opportunity to make contacts and business. On the other hand, they are the ones who participate more in tournaments, their main barrier is the lack of time and the work, adding also as an impediment “the distance to the club”. They like walking, cycling, swimming, and paddle. They are the ones who use more the practice course and less the coffee shop. Thus, Cluster 2 could be labeled as