Measuring Sport Tourist Motivation: Implications for Sport Tourism Distribution

Abstract

Purpose - The purpose of this study was to develop a motivation scale for participation sport tourism and to produce implications of potential use of MSPST for sport tourism distribution emphasizing the needs of sport tourists and the functions required to satisfy those needs. Research design, data, and methodology - The Motivation Scale for Participation Sport Tourism (MSPST) was developed in three stages. A literature review generated 8 dimensions with 42-items in the first stage. Second, an expert review phase refined the initial item pool, which resulted in 35 items. Result - Exploratory factor analysis was employed to produce an 8-factor, 28 item pool. The reduced version was confirmed via structural equation modeling, indicating an acceptable model of fit. The final MSPST consisted of 8 dimensions of motivation, including friendship, family, solitude, challenges, intrinsic, achievement, nature, and competition. Conclusions - The MSPST is a valid and reliable scale of tourists' motives for participating in sports. The results supported the suggested measures of motives associated with participation sport tourism regarding construct, convergent and discriminant validity. A body of knowledge about motives provides insights for policy-makers seeking to support distributional industries for sport tourism and finally to promote economy on both regional and national levels.

1. Introduction

Due to rapid advancement of communication technology and changing consumer preferences, the range of channels that tourism providers might use to distribute their products and services has been expanded (Pearce, 2009). To effectively reach target segments in tourism and to shape the tailored channels, it is crucial to explore and identify their specific needs (Albayrak & Caber, 2018; Buckley, 2012; Lee & Syah, 2018; Shin, 2018).

Within the travel segments, the sport tourism market has gained the most attention from tourism practitioners and researchers (Buning & Gibson, 2015; Faulks, Ritche, & Dodd, 2008). Participation sport tourism is defined as travel to participate in sport (Gibson, 1998a). Its primary aim is for participants to travel to other destinations for the purpose of taking part in physical activities such as golf, skiing, scuba diving, cycling, hiking/trekking, biking, canoeing, sailing, horse riding and so forth (Buning & Gibson, 2016; Tomik, 2013).

Since the 1990s, studies on sport tourism have been conducted on various aspects associated with this conceptual definition (Gibson, 1998a; Gibson, 1998b; Gibson, 2003; Gibson, Willming, & Holdnak, 2003; Han, Seo, & Moon, 2018). Specifically, several authors have called for more empirical research systematically examining travelers’ perspective on the reason why they travel to participate in sport (Faulks et al., 2008; Gillett & Kelly, 2006; Kim & Ritchie, 2012; Ritchie, 1998; Ritchie, Tkaczynski, & Faulks, 2010; Tomik, Gorska, Staszkiewicz, & Polechonski, 2014). Motivation is understood as a process which produces a particular action or behavior (Franken, 2007; Singh, 2014), also, an activation, drive and/or reason to engage in certain behavior and to maintain those behaviors (Mannell & Kleiber, 1997).

Sport tourists’ motivations are a function of a sport tourist’s perceived needs and become the drivers through the decision-making process, which ultimately lead to purchase or participation intentions (Collier, 1999). Understanding why individuals travel to participate in sport is an essential first step to develop a theoretical understanding of how to capitalize on the growth of the sport tourism industry (Han et al., 2018; Hemmatinezhad, Kalar, & Nia, 2010). As a multidisciplinary field, participation sport tourism is a unique area of study which combines sport and travel. Therefore, the reason for a sporting holiday is not only affected by sport participation itself but also influenced by other travel motives (Weed & Bull, 2004). In short, sport tourists’ reasons for traveling can include a combination of both sport and tourism motives (Gammon & Robinson, 1997). Simply providing an organized environment to compete in sport may not fully optimize tourists’ needs and wants (Harrison-Hill & Chalip, 2005). It is clear that understanding the motives of sport tourists will provide sport tourism distributors and policy-makers with a basis for connecting with target markets and developing marketcentered policies.

Given the significance of uncovering motives embedded in participation sport tourism and of producing implications for sport tourism distribution and related policies, the purpose of this study has two folds. First, the study sought to explore motives for traveling to a destination to participate in sport by developing a comprehensive measurement instrument that equally weighs both sport and tourism motives. Both academic and industrial sectors that are seeking to reach sport tourism markets will benefit by having access to a functional and valid scale with which to analyze their consumer segments (Hungenberg, Gray, Gould, & Stoltlar, 2016). Second, the study sought to discuss industrial implications of use of MSPST for sport tourism providers to effectively communicate with sport travelers via distribution channels.

This study composed three phases: a qualitative phase, a quantitative phase and discussion section. Potential measures were generated in the qualitative stage and statistically purified into coherent scales in the quantitative stage. Implications of use of MSPST for sport tourism were discussed.

2. Qualitative Phase

2.1. Item Generation

According to Gibson (2003), participation sport tourism refers to travels that people move to particular destinations to participate in sport activities. Given the conceptual framework, participation sport tourism represents two distinct foundations which are sport activities and tourism activities. This provides the motivation for the study to identify motivational variables and related items from both sport and tourism literature. In a qualitative phase, thus, the study reviewed the literature and identified potential factors by reviewing the prior research in the field of physical exercise, participation sport, event sport, cultural tourism, nature tourism, domestic and international tourism.

The qualitative phase identified 13 dimensions(87 items) underlying motives for both sport participation and tourism. The preliminary item pool included items from existing scales gauging competence-mastery, stimulus avoidance, intellectual, friendship, esteem from self and others, family, solitude, exploration, challenge, education, intrinsic factor, social recognition, social identity, achievement, nature, stimulation, and nostalgia. These factor and items were refined and saturated through the item evaluation process.

2.2. Item Evaluation

The primary purpose of the study was to develop a comprehensive measurement instrument that equally weighs both sport and tourism motives. For this, it is necessary to generate the initial items from the preliminary item pool, representing motivation scale for participation sport tourism (MSPST). To ensure content validity, this study employed two processes. First, the preliminary items were screened by the research team members to identify duplicate or ambiguous factors and items. In this step, the research team members categorized some similar factors and removed some items that are deemed vague. Furthermore, several items were modified to mirror their use as a measure of motivation for participation sport tourism. Second, to enhance content validity of the items, the items were further assessed and refined by three experts in either sport or tourism industries (Netemeyer, Bearder, & Sharma, 2003). They thoroughly examined the remaining potential items, suggested additional modifications and some rewording of items. Finally, the initial item pool, containing an eight factor potential 35-item pool, was generated (Table 2): Family (Kim & Ritchie, 2012; Ritche et al., 2010), solitude (Pearce & Lee, 2005; Ritche, 1998), challenge (Frederick & Ryan, 1993; Ritche, 1998), achievement (Trail & James, 2001), nature (Andreu, Kozak, Ayci, & Cifter, 2006; Pearce & Lee, 2005), competition (Milne & McDonald, 1999), Friendship (Faulks et al., 2008), and intrinsic motives (Frederick & Ryan, 1993).

Table 1: Operational definition of 8 constructs of participation sport tourist’s motives

Note: This source is produced by consensus of researchers throughout the literature review.

Table 2: Initial MSPST with factor loading and scale reliability

3. Quantitative Phase

3.1. Participants

The sample consisted of 243 respondents who reported experiences of travel for the purpose of participating in a variety of sports, ranging from cycling to skiing. The original sample was recruited from a pool of sports club members in the United States. Participants were given access to an online survey link. A total of 252 completed surveys were received. Of these, 243 valid responses were analyzed. The sample consisted of more male (52.7%) than female (47.3%), participants, with a majority of them being married (57.4%), college educated (74.5%), and white/Caucasian (74.1%). Participants ranged in age from 18 to 69 (M=40.06, SD=12.74) and they participated in a variety of sports ranging from outdoor running (13.6%) to rock climbing (0.4%). The majority of the sample reported an annual household income between $25,000 and $125,000 (USD) (n= 215), while only 8.6% reported an income greater than $125,000 (n=21).

3.2. Measurement

In order to identify and confirm the constructs of participation sport tourism motives, we examined the initial version of the motivation scale for participation sport tourism (MSPST), made up of 8 dimensions (35-item pool), which were refined in the item generation stage. The item statements were measured on a 7-point scale indicating level of agreement ranging from 1 (strongly disagree) to 7 (strongly agree). Cronbach’s alpha ranged from .93 for the challenge motive, to .97 for the nature motive.

3.3. Data Analysis

In order to look at the demographic information of the sample, the study examined the frequencies and descriptive characteristics of the data. In order to verify the factor structure of the initial MSPST, exploratory factor analysis (EFA) assessed the unidimentionality of constructs by forcing items to load on factors with loadings over .50(Floyd & Widaman, 1995; Segars, 1997). Items with factor loadings in the range of .40 and above were considered to be substantial (Floyd & Widaman, 1995). Additionally, the total variance for each latent variable-greater-than-50% rule was employed. Furthermore, the EFA assessed the validity of the initial MSPST scale by examining whether they were measuring what they have to measure (John & BenetMartinez, 2000). Following the EFA, confirmatory factor analysis (CFA) was conducted on the reduced MSPST to evaluate and identify its hierarchical model. The cutoff criteria for fit indices reported by Hu and Bentler (1999) were utilized. Cronbach’s alpha was computed for each subscale to test the internal consistency.

4. Results

4.1. Exploratory factor analysis

Exploratory factor analysis(EFA) should be employed before confirmatory factor analysis (CFA) because EFA can disclose that certain items load poorly in terms of magnitude on an intended factor or load highly on more than one factor (Netemeyer et al., 2003). Hence, before CFA, EFA was conducted to explore the dimensionality of the initial MSPST version (e.g., Seo & Green, 2008).

Again, EFA was employed to determine the number of factors, and the items to be included in each factor, and finally to further purify the initial MSPST (Table 2). Items with factor loadings in the range of .40 and above were considered substantial (Floyd & Widaman, 1995). Given the above criteria, principle component factor analysis (PCA) produced an eight-factor MSPST model that removed 7 items from the original model. Internal consistency for each of the eight dimensions was assessed with Cronbach’s alpha. An eight-factor MSPST model showed 81.1% of the explained variance.

Subsequent analysis was to determine whether the 8 latent factors were significantly correlated with each other. Highly correlated latent factors indicate the need to explore the probability of a second-order structure for the MSPST (Seo & Green, 2008). All structures were significantly correlated with each other (see Table 3). Hence, it seems that the intial eight-factors explain the second order-factor, motivation for participation sport tourism.

Table 3: Correlations among latent factors

Note. ^*p < .05. ^**p < .01.

FD: Friendship, FM: Family, ST: Solitude, CH: Challenge, IT: Intrinsic Factor, ACH: Achievement, Na: Nature, CP: Competition

4.2. Confirmatory factor analysis and evaluation of validity

Confirmatory factor analysis (CFA) was conducted to confirm and examine the eight-factor MSPST’s latent constructs and items which were identified from the EFA results. At 35-items, and eight constructs, the hypothesized CFA model was estimated using AMOS 4.0. The purpose of the model testing was to further reduce, identify, and validate the suggested eight-factor MSPST, and finally retain the optimal number of items per factor (Hungenberg et al., 2016). Fit indices of chi-square, comparative fit index (CFI), normed fit index (NFI), and standardized root mean square residual (SRMR) were assessed to evaluated overall fit of MSPST. The cutoff criteria for fit indices recommended by Hu and Bentler (1999) were used in the model evaluation (Seo & Green, 2008).

The CFA results indicated that the 35-item, eight factor, MSPST needed more modification by producing the following model fit: χ²= 1353.831, df = 552, CFI = .92, NFI = .88, and SRMR = .72. To validate the hypothesized MSPST, one item that did not clearly explain solitude motive, and another item that was not clearly related to intrinsic motive, were removed from the model. One item, indicating low item to total loading, was also eliminated. Additionally, three items were removed from the nature motive, and one item was removed from the competition motive, due to lack of conceptual validity. The final model consists of 28 items measuring 8 dimensions of sport participation tourism.

The final 28-item, 8 factor, MSPST indicated an acceptable model fit: χ²=861.828, df=342, CFI=.93, NFI=.90, and SRMR=.50. All items loaded significantly on their respective factors (p<.001), ranging from .80 for challenge (CH4) to .95 for competition (CP2) and friendship (FD2). All first-order factors were significantly loaded to the second-order factor-motivation for participation sport tourism (p<.001), ranging from .67 for the nature motive to .86 for the challenge motive.

To further verify convergent and discriminant validity of the model, average variance extracted (AVE) was assessed. AVE estimates should be greater than .50 to verify that a set of items assumed to represent a construct does converge on that same construct (Fornell & Larcker, 1981; Gounaris & Dimitriadis, 2003). AVE values of all factors in the model exceed .70. To verify discriminant validity, inter-factor correlations were compared with AVE’s square root for each factor. Analysis showed that inter-factor correlations of the model were less than the square root of the AVE belonging to each construct (Fornell & Larcker, 1981). Thus, the final 28-item, 8 factor MSPST has evidence for both convergent and discriminant validity (Table 4).

Table 4: Final MSPST with factor loading, AVE, item-to total correlations and Cronbach’s alpha

All dimensions were also internally consistent. The final MSPST exhibits high item-to-total correlations, ranging from .76 for solitude 4 and intrinsic 3, to .92 for friendship 2. Cronbach’s alphas ranged from .91 for intrinsic to .96 for friendship.

5. Discussion

While some suppliers, especially the larger ones, have a good appreciation of different market needs and have performed a sound marketing mix, this is not always the case, particularly with many of the small- and medium size enterprises that constitute the majority of the country’s tourism businesses (Pearce & Tan, 2006; Stuart, Pearce, & Weaver, 2005). The MSPST is a valid and reliable scale of tourists’ motives for participating in sports. The results supported the suggested measures of motives associated with participation sport tourism regarding construct, convergent and discriminant validity. The MSPST captures a variety of reasons why people travel to participate in sports. The 8 dimensions developed here are consistent with prior motivation studies in the fields of sport and tourism (Andreu et al., 2006; Faulks et al., 2008; Frederick & Ryan, 1993; Kim & Ritchie, 2012; Milne & McDonald, 1999; Pearce & Lee, 2005; Ritche et al., 2010; Trail & James, 2001).

Relationships between sport and tourism are symbiotic (Standeven & Knop, 1998) and they are not separate spheres (Bull, 2006). From this view, MSPST can be used to figure out the socio-psychological benefits sport tourists are seeking and to capture a greater comprehension of sport tourists’ behaviors prior to, and during, sport tourism. Understanding the motivational causes of participation sport tourists is crucial providing implications for practitioners and sport tourism distributors. More specifically, the 8 dimensions can be employed together to obtain insights into sport tourists’ overall motivations and to develop managerial strategies for sport tourism organizations. Alternatively, the dimensions can be used independently to obtain more detailed information regarding sport tourists’ specific behaviors. Further, study of independent dimensions could lead to discovering correlations between certain motivations and subsequent behaviors that are not currently being explored. Practically, sport tourism managers are able to segment travelers on the basis of their motives and to develop customized managerial strategies for their products, services, prices, distributions, and communications. This is because different types of motives induce different behaviors.

In addition, a body of knowledge about motives provides insights for policy-makers seeking to support distributional industries for sport tourism and finally to promote economy on both regional and national levels. For example, tourism policy-makers including tourism managers are able to break sport tourists into segments based on their motives and to figure out socio-demographic profiles for respective motivation segments. Furthermore, they can also analyze socio-psychological constructs including attitudes and images towards destinations, personalities, self-concepts, and life styles, based on motivational groups. Bull (2006) pointed out that the segmentations cover a wide range of different forms and serve to highlight the heterogeneous nature of both the sports tourist and the sports tourism phenomenon. In line with Bull’s suggestions, segmentation analysis would be helpful to develop market-based strategies considering target markets, cultural attractions and infrastructures of destinations, budgets, and so on. Furthermore, with the information about tourists’ motivational segments and their demographic characteristics, managers are able to identify a development path targeting each group and leverage the interconnected nature of the segments, to target the maximum number of people efficiently. The development path would include program and event-based tourism initiatives that align with the motivations of the identified segments. This approach would benefit destinations by offering more customized business models and by leading to an optimal allocation of resources.