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It is wellestablished that tourism induced by film and television (TV) (screen tourism) is a phenomenon of global significance, and a number of studies since the 1990s have explored its impacts on specific destinations and communities. While some research provides insights into motivations of screen tourists, understanding of the experiences of screen tourists in film and TV locations remains an emerging area of inquiry. Consequently, the aim of this paper is to explore the interface between the screen tourist and the destination. The results of empirical research with screen tourists to the Isle of Mull (Scotland) to view the filming location for the children’s TV show Balamory are discussed. First, the degree to which people are attracted to a location through film connections and the types of visits are explored. Second, the nature of visit experiences is analysed, allowing some consideration of emerging issues for both visitors and the destination. Third, the visitor propensity to return for a future visit is examined. The paper identifies that the lower the influence of Balamory for the visit, the higher the level of adult satisfaction, and that a return visit was more likely if visitors were satisfied with their trip, especially if Balamory was not the only reason for the visit. A structural equation modelling approach is adopted to explore some of the issues induced by an evaluation of visit experiences and the perceived likelihood of repeat visits, generating a range of widely applicable implications for screen tourism destination management and development.
Tourism Management 40 (2014) 372e381 Contents lists available at ScienceDirect Tourism Management journal homepage: www.elsevier.com/locate/tourman Social interactions and intentions to revisit for agritourism service encounters Hyungsuk Choo a, *, James F Petrick b,1 a b School of Human Movement, Sports, and Leisure Studies, Bowling Green State University, Bowling Green, OH 43402, USA Department of Recreation, Park, and Tourism Sciences, Texas A&M University, 2261 TAMU College Station, TX 77843, USA h i g h l i g h t s The study suggests a model integrating agritourists’ interactions with service providers, companions, and other customers Interactions with service providers and those with companions positively affected satisfaction with the farm visit Interactions with companions influenced satisfaction more than those with other customers a r t i c l e i n f o a b s t r a c t Article history: Received March 2012 Accepted 18 July 2013 This study addresses how agritourists’ social interactions affect their satisfaction and, in turn, revisit intentions Adopting social exchange theory and resource theory, the study proposes that social interactions with service providers, local residents, companion tourists, and other customers influence satisfaction, which in turn affects revisit intentions For this, an onsite survey was conducted to examine the proposed model and test the hypotheses Subjects (N ¼ 266) were tourists who visited farms All, but one of the hypotheses were supported or partially supported by the data and the proposed model also had an acceptable fit Results provide direction for the development of a theoretical framework to understand revisit intentions by seeking to improve the social exchange relationships with agritourists In addition, the results call for the incorporation of social interactions as a component of the agritourism servicescape Ó 2013 Elsevier Ltd All rights reserved Keywords: Social interactions Satisfaction Revisit intentions Agritourism Introduction Agritourism has long been a phenomenon in many countries, but its popularity has only recently increased for farmers, tourists and consumers of agricultural products and services (Sharpley & Vass, 2006) On the supply side, as traditional methods of agriculture production system are becoming less viable, farming communities have experienced economic and social challenges, including decreased farm incomes (Busby & Rendle, 2000) Thus, farmers have looked for alternatives to help diversify traditional farm operations, hoping to reverse the steady erosion of net farm incomes (Fleischer & Pizam, 1997) Farm diversification into tourism, in general, presents a potential to generate additional income, diversify the farming economy, lower risks and uncertainties * Corresponding author Tel.: þ1 419 372 7862; fax: þ1 419 372 0383 E-mail addresses: hchoo@bgsu.edu, hyungsuk.choo@gmail.com (H Choo), jpetrick@tamu.edu (J.F Petrick) Tel.: þ1 979 845 8806; fax: þ1 979 845 0446 0261-5177/$ e see front matter Ó 2013 Elsevier Ltd All rights reserved http://dx.doi.org/10.1016/j.tourman.2013.07.011 and form a symbiotic relationship with agriculture for farming communities (Clarke, 1999) Agritourism also provides benefits to tourists and consumers Since the majority of the general population may have little or no contact with agriculture, agritourism could also be a mechanism by which urbanites can enjoy nature and culture, learn about agriculture and purchase locally grown farm products (Sonnino, 2004) In sum, agritourism has been commonly guided and motivated by a vision for a thriving, diverse, small-scale farm that remains profitable, enhances the environment, enriches the indigenous culture, and improves the quality of life for farmers and consumers While a growing body of literature related to agritourism exists, the vast majority has dealt with tourism from the supply side (Jolly & Reynolds, 2005; McIntosh & Bonnemann, 2006) To date, little attention has been given to farm tourists and their relationships with farmers even though the recent growth in agritourism has been driven by both demand and supply (Tew & Barbieri, 2012) There are considerable opportunities for growth of the demand for agritourism as an increasing number of farmers are diversifying into tourism businesses (Lobo et al., 1999) Therefore, it is believed H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 that research should be conducted to understand the factors affecting consumers’ perspectives for agritourism activities in order to fill this gap Like other forms of tourism, agritourism involves much service This creates a need to focus on service encounters in which a customer interacts with staff and/or other customers (Bitner, Booms, & Tetreault, 1990) Service encounters often occur in the presence of multiple customers and service providers who share the servicescape with each other, involving a series of interactions and/or relationships In this sense, it would appear to be important to integrate the types of interactions at service encounters to understand how those influence customers’ service experiences In the service marketing literature, service encounters have typically represented social encounters in which employees’ interpersonal skills affect customer satisfaction and behavior (Bitner, Booms, & Mohr, 1994; Bowers, Martin, & Luker, 1990) and where customers influence one another indirectly as a part of the environment or directly through interpersonal encounters (Bitner et al., 1994; Martin, 1996) Similarly, tourism scholars have examined the dyadic interface between tourists and employees (Solnet, 2007) and customer-to-customer interactions (Huang & Hsu, 2010; Wu, 2007) Additionally, interactions with tourists’ companions and with local residents might also be critical parts of tourists’ tourism experiences This study therefore sets out to examine an integrated social interaction in agritourism service encounters including four distinctive relationships including: 1) agritourist-to-service provider, 2) agritourist-to-local resident, 3) agritourist-to-companion tourist, and 4) agritourist-to-other customer Taking findings related to social exchange theory (Homans, 1958) and affect theory of social exchange (Lawler, 2001), this study will examine the link between agritourists’ social interactions and satisfaction with their service experience Moreover, these four types of social interactions will be compared to see how these interactions can individually or in combination, positively influence post-purchase behaviors It is hoped that this study will provide marketing implications for developing tourism businesses on farms by seeking to understand the social exchange relationships that agritourists have Literature review 2.1 Agritourism and service encounters The primary reason for the recent emergence of tourism as an important rural economic activity can be found from the supply side Farm-based tourism has increasingly given farmers an opportunity to generate additional income (Knowd, 2006), to be an avenue for direct marketing to consumers (Sonnino, 2004; Tew & Barbieri, 2012; Veeck, Che, & Veeck, 2006) and as a way to counteract social and economic problemsdloss of income, increased expenses, globalization, and othersdassociated with the decline of traditional agriculture industries (McGehee, 2007) In general, farmers diversify into tourism services for significant and steady retail sales of farming products, but opportunities for educating agritourists and consumers about the farming and farming resources and offering entertainment/recreation services are useful side benefits of these activities While these potential benefits have attracted many farmers into agritourism, farmers should keep in mind that this activity requires them to have extended marketing practices Compared to long supply chains of traditional agricultural systems as a part of the production system, agritourism involves much service, including direct interactions with agritourists and consumers This suggests attention needs to be paid to service encounters in both agritourism research and practice 373 In the service marketing literature, service encounters are defined as any period of time during which a customer interacts with a service (Bitner, 1990; Shostack, 1985) This definition includes discrete, separate, and distinct events and behaviors, as well as customers’ interactions with all the dimensions of a service However, a majority of service encounter scholars believe that interpersonal interactions between customers and service providers are typically important because it is during this time when customers judge the services provided to them and most services involve at least one human being interacting with another (Czepiel, 1990; Shostack, 1985) Hence, such an encounter has been the focus of service marketing research While different scholars have paid attention to specific types of interactions during service encounters, an integrated model explaining three discrete relationships has been identified in general service environments: customer-to-organization, customer-toservice provider, and customer-to-customer interactions (Yi & Gong, 2009) All of these interactions seem relevant to general tourism service encounters, but they are not necessarily the same for small-scale operations which predominate in agritourism Agritourists seem not to distinguish their interactions with organizations or employees because farm owners themselves are service providers in many cases (Wilson, 2007) Therefore, out of the three types of interactions, this study will not consider customerto-organization interactions Agritourists encounter local residents, although not on a regular basis Local residents’ behavior toward tourists can influence whether the experience of agritourists is pleasant Tourist-toother customer interactions have received scholarly attention in that the presence of other customers can affect the nature of the service outcome and process Lastly, as the indigenous presence of social groups has been recognized in the tourism literature (Crompton, 1981), travel companions might also influence the tourism experience A vast majority of leisure tourists not travel solo and most tourism statistics indicate an average travel party over two Although the phenomenon of tourists’ interaction with their companions has not been identified well in the tourism literature, this specific interaction, afforded by families and friends in shared leisure activities, has been explored through the concept of leisure companionship in other fields (Iso-Ahola & Park, 1996; McCormick, 1999) In sum, this study suggests that at least four types of social interactions exist in agritourismdwith service providers, companion tourists, other customers, and local residents This study will further examine how these interactions influence revisit intentions through satisfaction 2.2 Satisfaction and social exchange theory Satisfaction is one of the most heavily researched topics in consumer behavior and marketing The importance of understanding satisfaction is primarily based on its potential outcomes, such as: loyalty and commitment (Cronin & Taylor, 1992), word-ofmouth (Huia, Wan, & Ho, 2006), complaining behavior (Landon, 1977), and repurchase intentions (Hu, 2003; Petrick, 2004; Petrick & Backman, 2001, 2002; Petrick, Morais, & Norman, 2001; Petrick, Tonner, & Quinn, 2006) Customer satisfaction has generally been conceptualized as a post-purchase evaluative judgment concerning a specific purchase choice (Westbrook & Oliver, 1999) Satisfaction is created more from feelings-based criteria than cognitive criteria, yet it tends to relate as much to perceptions of the intermediate steps of personal exchange during the process of service delivery as to its actual outputs (Nowak & Washburn, 1998) Satisfaction is further complicated by the influence of personal and social variables such as needs, disposition, traveling companions and previous 374 H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 experience (Crompton & Love, 1995; Kozak, 2001) This suggests that the importance of examining various antecedents of satisfaction (Cronin & Taylor, 1992) According to social exchange theory, interpersonal interaction includes exchanges of resources and satisfaction is primarily influenced by the social and economic outcomes of those exchanges (Homans, 1958) On the contrary, the expectancydisconfirmation paradigm, which is arguably a dominant satisfaction framework, focuses on internal processing which involves comparison of the actual and expected performance of a product or service (Oliver, 1977) Therefore, a key advantage of social exchange theory is that it considers the interpersonal variables influencing satisfaction Successful relationships are characterized by reciprocity (Gouldner, 1960), and it is likely that they are the keys to positive feelings about sustained social relationships Social exchange theory was originally built upon rational choice assumption of human behavior, but Lawler and his colleagues connected rates of social exchanges and positive emotions (Lawler, Thye, & Yoon, 2000; Lawler & Yoon, 1993) The theory takes its specific form as an affect theory of social exchange, which conceives of the importance of emotion as an outcome of social exchanges for relational commitment (Lawler, 2001; Lawler & Thye, 2006) This theory accordingly supports the affective outcome (i.e., satisfaction) resulted from social interactions that this study asserts Social exchange relationships evolve when an individual who supplies rewarding services to another obligates them To discharge this obligation, the second must in turn furnish benefits to the first (Blau, 1964) To the extent that both parties apply the reciprocity norm to their relationships, favorable treatment by either party is reciprocated, leading to mutually beneficial outcomes (Rhoades & Eisenberger, 2002) Similar to above reasoning, the four types of interactions suggested in this study have been recognized Of these, the interactions with service providers (Morais, Dorsch, & Backman, 2004; Sierra & McQuitty, 2005) or other customers (Huang & Hsu, 2010; Rosenbaum & Massiah, 2007; Wu, 2007) have been identified both in the general service and tourism literatures with respect to positive post-purchase behaviors In addition to these two parities, some tourism scholars have suggested that direct and indirect interactions with local residents can play a role in creating positive tourist experiences (Carmichael, 2006; Fick & Ritchie, 1991) Within a travel group, Kozak and Duman (2012) recently investigated the role of other members in a family affect a spouse’ (or partner’)s vacation satisfaction, concluding the postpurchase evaluation is part of a joint-decision making process Combining these prior evidences, the following four hypotheses were derived Hypothesis Interactions with service providers will have a positive effect on satisfaction Hypothesis Interactions with local residents will have a positive effect on satisfaction Hypothesis Interactions with companion tourists will have a positive effect on satisfaction Hypothesis Interactions with other customers will have a positive effect on satisfaction 2.3 Satisfaction and resource theory Resource theory is a social psychological framework for understanding social interactions and relationships It is closely related to social exchange theory, which very broadly refers to any conceptual model or theoretical approach that focuses on the exchange of resources between or among people In this way, social interactions are seen as providing the means by which persons can obtain needed resources from others and, thus, gain satisfaction as a result of the effect these transactions have on them (Rettig & Bubolz, 1983) Consequently, resource theory represents a broad conceptual framework that helps us to understand interpersonal behavior and the relationships between individuals in everyday life In particular, this theory posits that the resources exchanged by those having relationships are expected to be qualitatively different as well as engaging in a greater quantity of exchanges (Foa & Foa, 1976) Within the resource theory framework, resources can be broadly defined as “any item, concrete or symbolic, which can become the object of exchange among people” (Foa & Foa 1980, p 78) Resources can be classified into six classes: (1) Lovedan expression of affectionate regard, warmth, or comfort; (2) Statusdan evaluative judgment conveying high or low prestige, regard, or esteem; (3) Information eany advice, knowledge, opinions, or suggestions; (4) Moneydany coin or token that has some standard of exchange value; (5) Goodsdany tangible items that are exchanged; and (6) Servicesdactivities provided to or by an individual According to Foa and Foa (1980), individuals satisfy personal needs through resource exchanges with others Incorporating the material and nonmaterial needs of an individual with another, resource theory has the potential to assist in understanding satisfaction in an agritourism context where both material and nonmaterial exchanges are necessarily common According to some relationship scholars (Buunk & Verhoeven, 1991; Miller & Berg, 1982), the type of relationship is an influential factor in social exchanges, as previous research in social psychology has indicated that different types of social interaction have distinct effects on life satisfaction Among them, Rook (1987a, 1987b) compared the role of companionship and other social relationships on life satisfaction, emphasizing the important nature of shared experiences and activities associated with companionships Accordingly, when the tourist-to-companion tourist interaction is compared with the tourist-to-other customers interaction on satisfaction judgment, the effect of the former may be more significant than the latter in agritourism encounters In a similar vein, how tourists interact with service providers is hypothesized to be more prominent in their satisfaction judgment than their interaction with other local residents (i.e., other local farmers) This does not mean that interactions with local residents are not important, but rather to understand how tourists’ interactions with service providers and local residents both influence agritourism encounters Therefore, the specific hypotheses regarding the type of relationship are: Hypothesis The effect of agritourists’ interactions with their own companions on satisfaction will be stronger than the effect of agritourists’ interactions with other customers on satisfaction Hypothesis The effect of agritourists’ interactions with service providers on satisfaction will be stronger than the effect of agritourists’ interactions with local residents on satisfaction 2.4 Revisit intentions Many tourism scholars have increasingly discussed the concept of revisit intentions and its antecedents by examining their beneficial rewards; creating positive word-of-mouth, achieving better cost-effectiveness by repeat visitors, and increasing economic profit (Shoemaker & Lewis, 1999) In agritourism, as seasonal changes are part of the farming environment, this also creates the importance of attracting a high portion of repeat tourists The concept of revisit intentions is adopted and modified from both social psychology and marketing perspectives In social H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 psychology, the intention to continue/to stay in a relationship is referred to as relationship maintenance by social exchange theory (Thibaut & Kelley, 1959) Consistent with this conceptualization of revisit intentions as an extension of the relationship framework, this study examines the relationship between agritourists’ interactions at agritourism experiences and their revisit intentions, mediated by satisfaction A number of tourism researchers in this domain have suggested several other key antecedents of revisit intentions, though theoretical and empirical findings are quite consistent in suggesting satisfaction positively related to revisit intentions (Chen & Tsai, 2007; Kozak, 2001; Petrick, 2004; Yuksel, 2001) This study thus postulates that satisfaction will ultimately influence agritourists’ intention to revisit the farm in the following: Hypothesis There will be a positive relationship between satisfaction and revisit intentions Methodology 3.1 Survey development Following resource theory’s suggestion that social interactions include as many as six different resources, a preliminary 18 items (Table 2) were included to measure the concept of interaction with service providers In addition to 14 items suggested in the previous literature (Morais, Backman, & Dorsch, 2003), additional items Table Demographic characteristics of the sample Demographic characteristics Gender Male Female Age 18e39 40e59 60þ Income (Average) Less than 19,999 $20,000 to less than $40,000 $40,000 to less than $60,000 $60,000 to less than $80,000 $80,000 to less than $100,000 $100,000þ Marital status Single Married Single parent w/child(ren) Married w/child(ren) Other Employment status Employed full-time Employed part-time Self-employed Full-time homemaker Student Retired Not currently employed Education background Less than high school Completed high school Some college, not completed Completed college Post graduate work started/completed Ethnic background Caucasian Hispanic or Mexican American African American Asian Native American Other Percentage (N ¼ 266) 40.6% 59.4% 63.1% 27.6% 9.2% $69,000 6.4% 12.7% 16.8% 31.9% 15.0% 17.3% 30.7% 28.1% 19.7% 19.9% 1.5% 35.2% 23.1% 5.3% 11.5% 13.02% 7.4% 4.4% 3% 12.7% 4.3% 50.6% 32.2% 79.8% 5.5% 1.0% 10.3% 5% 2.8% 375 relevant to agritourism context were included For agritourists’ interactions with local residents, companions, and other customers, the same items were used excluding six irrelevant items (three items each of interactions through product and money exchange e.g., local residents/companions/other customers offered discounts) All variables were measured on five-point Likert-type scales ranging from (strongly disagree) to (Strongly agree) In addition, four sets of polar items on a five-point modified semantic differential summation scale for satisfaction and the two items on a 5-point scale for revisit intentions were adopted from Baker and Crompton (2000) and Grewal, Monroe, & Krishnan (1998) respectively 3.2 Data collection Texas was selected for the study site due to its significant contribution of agriculture to the whole country Although data is unavailable for the total number of farms involved in tourism in Texas, according to the National Agriculture Statistics Service (NASS) in 2008, Texas led the nation in number of farms (229,000), total land in farms (129 million acres), and livestock and product commodity sales ($9.3 billion) in 2008 Word-of-mouth recommendations obtained from agricultural professionals in practice, academics, and the government resulted in the identification of 19 Texas farms engaged with tourism activity Among those, five relevant agritourism farms located in central Texas, were chosen based on the distance and year-round availability They were contacted for possible participation and three farms agreed to participate in study The data were collected from February to March 2009 via onsite surveys Every 5th visitor was systematically approached (Dillman, 2000) and informed about the purpose of the survey in advance before they were given the questionnaire During an 8-week period, a total of 307 surveys were returned Of those, 21 incomplete or duplicate responses were identified and removed In addition, responses from those who stated that they routinely visited the farm almost every week (20 responses) were also removed as they were identified as local customers who purchase farm products Thus, 266 were kept in the final sample for analysis, and the response rate was 82.6% As shown in Table 1, the majority of respondents were women (59.4%) and in the 18 to 39 age cohort (63.1%) Agritourists tended to be highly educated with 82.8 percent having completed college and the average income being $69,000 Among the respondents, 58.3 percent were employed either full-time or part-time Among them, 29.5% were repeaters and the average number of visits among the repeaters was 2.9 times Of the respondents, 255 (95.9%) accompanied companions The average party size was 2.6 ranging from to 19, and their visit/s was/were mainly with their families (60.8%) or friends (34.0%) Results 4.1 Measures The measurement models of all constructs (i.e., social interactions with service providers, companions, and other customers, satisfaction, and revisit intentions) except social interactions with local residents were identified In this step, social interactions with local residents was dropped from the final structural model due to its low reliability (Hair, Anderson, Tatham, & Black, 1998) (Cronbach’s alpha ¼ 402) and too many missing values (35.1% nonresponse rate for this construct) (Raymond & Roberts, 1987) Factor analyses were preliminarily conducted (Mulaik, 2004) in order to reduce the number of variables for the three social interactions scales and unidimensionality of satisfaction and revisit intentions scales The social interaction scale had not been 376 H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 Table Result of exploratory factor analyses Factors & items Love_S: Interactions with service providers through love Fondness_S: Service providers were very fond of me Importance_S: Service providers treated me important Personal_S: Service providers treated me personally Care_S: Service providers cared about me Money_S: Interactions with service providers through money Discount_S: Service providers offered discounts Money_S: Service providers provided monetary benefits Free_S: Service providers provided or share a free stuff Souvenirs_S: Service providers provided or shared souvenirs Service_S: Interactions with service providers through service Equipment_S: Service providers provided or shared good quality equipment to use in this visit (basket, bag, etc) Advantage_S: I took advantage of service providers’ help Love_C: Interactions with companions through love Fondness_C: My companions were very fond of me during the visit Importance_C: My companions treated me as an important person Personal _C: My companions treated me personally Care_C: My companions cared about me Information_C: Interactions with companions through information Attraction_C: My companion(s) provided me with information on attraction, lodging, or restaurant around the farm Problem_C: My companion(s) provided me with information about the problems Education_C: My companion(s) educated me about a farm Advantage_C: I took advantage of my companion(s) ’s help Status_O: Interactions with other customers through status Fondness_O: Other customers were very fond of me Personal_O: Other customers treated me personally Esteem_O: Other customers treated me with high esteem Care_O: Other customers cared about me Special_O: Other customers treated me special Information_O: Interactions with other customers through information Attraction_O: Other customers provided me with information on attraction, lodging, or restaurant around the farm Problem_O: Other customers provided me with information about the problems Satisfaction (SA) I was satisfied with the farm and its experience I was pleased with the farm and its experience My experience at the farm was favorable My overall feeling about the farm was positive Revisit Intentions (RI) If I were to visit a farm again, the probability that it would be this farm again The likelihood that I’d consider visiting this farm again is FC EV VE (%) RC 7.26 42.17 93 2.63 15.49 70 1.02 6.00 73 7.19 59.88 93 1.07 8.88 82 6.49 54.11 93 1.02 8.46 78 3.71 92.38 92 1.83 91.54 90 86 88 87 86 81 80 80 85 68 80 84 83 84 73 64 83 76 74 82 81 80 58 85 63 96 97 95 97 96 96 Note: FC: Factor loadings, EV: Eigen value, VE: Variance extracted, RC: Reliability Coefficient, S, C, and O indicate Service providers, Companion tourists, and Other customers respectively sufficiently tested since its development in a tourism setting (Morais et al., 2003) Hence, it was determined that it would be more appropriate to conduct a multi-step process for examining and refining each scale Exploratory Factor Analysis (EFA) to examine the dimensional structure and properties of the measure relevant to the study context was chosen as suggested by Churchill (1979) Kaiser-Meyer-Olkin (KMO) measure with 79e.91 (Kaiser, 1970) and Bartlett’s test of sphericity (Bartlett, 1950) of 10,211 (p < 001) found that the data were appropriate for factor analysis Various cutoff criteria were used to determine the number of factors derived, such as eigenvalues, scree plot, percentage of variance, item communalities, and factor loadings (Hair et al., 1998) Items with loadings lower than and with loadings higher than on more than one factor were eliminated For social interactions with service providers, output of the EFA with a Varimax rotation using SPSS 15.0 suggested three factors (social interactions through love, money, and service), which explained 64.2% of the variance Two latent factors were identified for social interactions with companions (social interactions through love and information) and explained 68.8% of the variance Analysis of social interactions with other customers revealed two factors (social interactions through status and information), explaining 68.7% of the variance In total, 17 items were removed in this preliminary step due to low factor loadings or dual factor loadings and details of the results of the EFA are shown in Table The reliability coefficients of factors identified for the three social interactions ranged from 70 to 93, which exceeded the minimum standard for reliability of 70 recommended by Nunnally and Bernstein (1994) For the satisfaction and revisit intentions constructs, factor analyses confirmed one factor each, accounting for 92.4% and 91.5% of the total variance, respectively Reliability coefficients of 92 and 90 respectively, indicated acceptable reliability (Nunnally & Bernstein, 1994) 4.2 The hypothesized structural models AMOS 17.0 was employed to examine the structural models For this, Skewness and Kurtosis tests were preliminary performed to evaluate normality of the data The absolute value for univariate skewness and kurtosis ranged from 03 to 2.09 and from 01 to 3.79 respectively and fell within conventional criteria of normality (Kline, 2005) H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 Table Comparison of overall fit indices for the hypothesized and alternative models (N ¼ 266) Model c2 (df) RMSEA CFI GFI NNFI IFI RFI Hypothesized structural model Alternative model 426.01 (162) 07 91 90 90 94 93 413.21 (155) 07 90 90 89 93 93 Dc2 12.8* Note: RMSEA: Root mean square error of approximation, CFI: Comparative Fit Index, GFI: goodness-of-fit index, NNFI: Non-normed Fit Index, IFI: Incremental Fit Index, RFI: Relative Fit Index *p < 05 The nine constructs were incorporated into the structural model to examine the hypothesized relationships among the latent factors Since some of the factors were measured by more than four items, a parceling procedure (Bagozzi & Heatherton, 1994) was adopted This procedure, by combining items randomly into composites, can help reduce random errors, increase the stability of the parameter estimates, improve the variable to sample size ratio, remedy small sample sizes, and simultaneously maintain the properties of multiple indicators (Bagozzi & Edward, 1998; Hallak, Brown, & Lindsay, 2012) In addition, a structural model that is based on parceled items is more “parsimonious” than a model with individual items (Little, Cunningham, Shahar, & Widaman, 2002), and parameter estimates calculated when item parcels are used are more stable and therefore, more generalizable (Cunningham, 2007) Researchers often recommend the use of item parceling strategies, particularly when the underlying research questions involve relationships between the constructs rather than the functioning of individual items (Labouvie & Ruetsch, 1995; Rocha & Chelladurai, 2012) For this study, a total of ten parcels were created for the five social interaction dimensions having more than four items Maximum likelihood model estimation was used to test the fit the hypothesized structural model In the hypothesized structural model, the seven social interaction constructs were exogenous, and predicted satisfaction, which in turn predicted revisit intentions The results of the SEM showed that the proposed model provided a good fit to the data (Table 3) (c2 (162) ¼ 426.01 p < 001, CFI ¼ 91; NNFI ¼ 90; GFI ¼ 90; IFI ¼ 94; RFI ¼ 93; and RMSEA ¼ 07) These fit indices appropriately met the cutoff requirements of suggested model fit indices by Kline (2005) and Bollen (1989) The hypothesized structural model indicated that all standard factor loadings were greater than 50 (Kline, 2005) and no variable has modification indices (MI) scores greater than 100 Moreover, the present MI results were fairly complex, and did not present a theoretically meaningful solution to improve the model fit further In the hypothesized model, all the indicators loaded significantly and substantively on their factors (p < 05), suggesting convergent 377 validity (Bagozzi & Yi,1988) As shown in Table 4, the average variance extracted (AVE) exceeded 5, further supporting convergent validity (Fornell & Larcker, 1981) The correlations among factors were not higher than 85 (Kenny, 2012) In addition, the most conservative method using AVE also confirmed the discriminant validity because the AVE for each construct was greater than the squared correlation coefficients for the corresponding inter-constructs and this confirms discriminant validity (Fornell & Larcker, 1981) (Table 4) The items included in the hypothesized model are identified in Fig.1, which also shows the standard path coefficients and standard deviations 4.3 Alternative model In order to validate the hypothesized model and the mediating role of satisfaction, an alternative model which included direct paths between the social interaction constructs and revisit intentions was also examined The c2 difference test examined the null hypotheses of no significant difference with a nested structured model If the null hypothesis is sustained, the more constrained model would be tentatively accepted A set of fit statistics indicated that the alternative model moderately fit the data (c2 (155) ¼ 413.21, p < 001, CFI ¼ 90; NNFI ¼ 89; GFI ¼ 90; IFI ¼ 93; RFI ¼ 93; and RMSEA ¼ 07) The change in chisquare indicated that the fit of the alternative model did not perform better than the hypothesized structural model (Dc2 ¼ 12.8, df ¼ 7, p < 01) Examination of the individual path coefficients indicated that three paths were found to be positive and statistically significant (baMoneyeService Providers ¼ 08, p < 05, baServiceeService Providers ¼ 12, p < 01, baInformationeCompanion ¼ 09, p < 05) Although three of the seven direct paths from the seven social interaction constructs to revisit intentions were statistically significant (p < 05), all three path coefficients indicated only weak direct relationships, whereas the paths between the six social interaction constructs and satisfaction and those between satisfaction and revisit intentions remained relatively strong and significant (Fig 2) Although these results technically indicated partial mediation (Baron & Kenny, 1986), given the fact that the more parsimonious hypothesized model fit the data better and only three paths from social interaction to revisit intentions were statistically significant with the relatively weaker path loadings, it was concluded that the hypothesized structural model fit the data better than the alternative model 4.4 Hypotheses testing Path coefficients estimated by SEM and the results of hypotheses to are presented in Fig The path coefficient from social interactions with service providers to satisfaction was significant at the 01 level, indicating a positive relationship (bLoveeService Providers ¼ 31, p < 01, bServiceeService Providers ¼ 25, p < 01, bMoneyeService Providers ¼ 11, Table Correlation (squared correlation), average variance extracted (AVE), and mean of the hypothesized model 1 Love_S Money_S Service_S Love_C Information_C Status_O Information_O SA RI AVE Standard deviation Mean 172 762 597 549 012 103 568 447 793 1.34 3.95 (.030) (.566) (.356) (.301) (.000) (.011) (.323) (.200) All correlations are significant at p < 05 476 172 485 032 160 315 251 611 1.38 2.75 (.228) (.030) (.235) (.001) (.026) (.099) (.063) 631 643 018 158 665 451 569 1.37 3.55 (.398) (.413) (.000) (.025) (.442) (.203) 702 075 175 614 487 782 1.49 3.86 (.491) (.006) (.031) (.377) (.237) 051 223 642 458 923 1.34 3.02 (.003) (.050) (.412) (.210) 482 (.232) 080 (.006) 240 (.058) 566 1.28 3.00 254 (.065) 160 (.026) 490 1.28 3.34 756 (.572) 899 1.30 4.22 911 1.40 3.94 378 H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 Fig Estimation of the hypothesized structural model p < 05) The path coefficients from the two factors of social interactions with companions to satisfaction were also significant, indicating a positive relationship (bLoveeCompanions ¼ 28, p < 01, bInformationeCompanions ¼ 15, p < 05) Yet, for the path coefficients between the two factors of social interactions with other customers and satisfaction, only the path coefficient from the Status_O factor to satisfaction was positive and statistically significant (bStatuseOther customers ¼ 12, p < 05) The path coefficient from the Information_O factor to satisfaction was negative, yet statistically insignificant (bInformationeOther Customers ¼ À.09, p > 10) The relationship between satisfaction and revisit intentions showed a positive relationship, significant at the 01 level (bSatisfaction ¼ 68, p < 01) Therefore, while hypothesis and were supported, hypothesis was only partially supported Fig Estimation of the alternative model H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 Hypothesis was not able to be examined due to removal of social interaction with local residents But, the Love_S factor for social interaction with service providers had the highest explanatory power for satisfaction among all types of social interactions, based on the relative values of the path coefficients shown in Fig For hypothesis 6, the effect of social interactions with companions on satisfaction was higher than that of social interactions with other customers (bLoveeCompanions ¼ 28, p < 01, bInformationeCompanions ¼ 15, p < 05); bStatuseOther customers ¼ 12, p < 05, bInformationeOther Customers ¼ À.09, p > 05) Therefore, hypothesis was supported Discussion and implications The purposes of this study were to: (1) integrate observable interpersonal interactions between service providers, local residents, companions, and other customers in small-scale farms involved in tourism; and (2) examine the relationships between the interactions and revisit intentions mediated by satisfaction The proposed model examined integrated social interactions that have been observed in tourism contexts particularly for smallscale tourism operations on farms, and extends Yi and Gong’s work regarding service encounters as an exchange process (2009) By examining agritourism service encounters from a social exchange perspective, this study suggests that agritourism operators need to consider a tourist’s interpersonal interactions and how those interactions influence his/her tourism experiences Providing an opportunity for positive and supportive interactions using agritourism programs and services could help improve tourists’ satisfaction with their tourism experience As important as a person perceives the process and outcome of the relationship, he/she will most likely devote him/herself to it Thus, it is believed to be an important part of functional social exchange because it ensures that partners will put forth the effort necessary to produce mutually desirable outcomes However, it should be noted that all social interactions make important, but complementary contributions to tourists’ satisfaction judgment The results of this study supported Hypothesis to 6, except hypotheses and 5, which included social interactions with local residents The integrated model indicated that social interactions with service providers through love, money, and service exchange and those with companions through love and information exchange positively affected satisfaction with the farm visit For the effect of interactions with other customers, exchange of status resources was positive, but the link between interactions through exchange of information resources was neither positive nor statistically significant Additionally, this study demonstrated that the types of relationships were also important indicators in comparing the effects of interactions on satisfaction, as interactions with companions influenced satisfaction more than those with other customers Although the tourism literature has not paid attention to the relationships between tourists’ and their companions associated with service experiences, this study revealed an important role of travel companions on agitourists’ overall experience 5.1 Theoretical implications This study contributed to the repeat visit and satisfaction literatures because it examined an alternative theoretical explanation focusing on social interactions To the best of the authors’ knowledge, this is the first study in tourism to examine social interactions with service providers, companions, and other customers simultaneously in the visitors’ domain Although there are different types of social interactions that can play critical roles in tourism service encounters, previous research has focused mainly on those interactions respectively with service providers and customers By 379 integrating observable social interactions at agritourism encounters, this study provides a framework for understanding the contributions of different types of social interactions to satisfaction and revisit intention that are grounded in social exchange theory and resource theory In general, relationships between customers and tourism operations are based on repetitive interactions over time, which provide opportunities for customers to develop an enduring, positive relationship with service providers, companions, and other customers This implies the importance of examining the role of social interactions from a customer perspective drawn from social exchange theory, which has only been applied to local residents in the tourism literature (Gursoy, Chi, & Dyer, 2009; Perdue, Long, & Kang, 1999) Additionally, the study provided empirical support to the hypothesized influence of social interactions on satisfaction and to the usefulness of resource theory as an alternative theoretical framework to explain satisfaction and revisit intentions Different from previous studies on customers’ social interactions with service providers (Solnet, 2007) and other customers (Huang & Hsu, 2010), this study adopted resource theory, which suggests multidimensional constructs of social interactions The usefulness of resource theory in measuring customers’ social interactions is manifest in important contributions to the research (Berg, Piner, & Frank, 1993) This study could also contribute to developing a servicescape framework specific to agritourism or possibly relevant to general tourism The servicescape concept builds upon well-established research traditions in environmental psychology and marketing that the design of the physical environment can be an extremely important element in influencing consumption patterns and practices by emphasizing the co-creation of experience between service providers and customers The servicescape is typically comprised of three dimensions: ambient conditions, spatial layout and signs/ symbols/artifacts and the concept (Bitner, 1992) It has been argued that these dimensions remain invaluable to tourism marketing (Abubakar, 2002) However, many servicescape researchers have increasingly moved beyond a consumption setting’s physical dimension to less palpable dimensions, including social dimensions which are also housed within the servicescape (Hightower, 2010; Rosenbaum & Massiah, 2011; Tombs & McColl-Kennedy, 2003) The importance of social dimensions is particularly evident in tourism as tourists fulfill not only their utilitarian needs but also their social and psychological needs Therefore, an integrated model of the three interactions during agritourism encounters can serve as a basis for the social elements framework that are encapsulated in the tourism servicescape A servicescape framework embracing three types of interactions into three dimensions of the physical elements advocates that the service setting is not only physically appealing and symbolically welcoming, but also socially supportive and engaging (Rosenbaum & Massiash, 2011) 5.2 Managerial implications Regarding social interactions with service providers, steps should be taken to encourage customereservice provider interactions, as the current research suggested that these benefit customers In particular, in terms of the dimensions of social interactions with service providers, an important tenet can be suggested As the theoretical framework suggested that particularistic resources exchanged may help increase customers’ satisfaction with their experience, this study provides evidence that providers who wish for their customers to return should exchange love and services For example, providers could create personalized interactions to let their customers know how they are cared for and how important they are On the other hand, monetary benefits such as price discounts did not sustain customer satisfaction as highly as care and personal relationships did The value associated with a price discount can be 380 H Choo, J.F Petrick / Tourism Management 40 (2014) 372e381 perceived as just a cheaper price that is applicable to all customers, which might be why offering a price discount was the least valuable resource that customers were looking for In order to provide universal resources more effectively, results of this study suggest they need to be designed to convey personal care and attention towards individual tourists rather than monetary benefits Regarding interactions between unacquainted customers, status exchanges were found to be important aspects Thus, educating customers on the types of behavior expected of them might be important As in some other service contexts, sharing the environment with unacquainted people and standing in line at the farmer’s market, which are common aspects of agritourism, are possible serious challenges However, agritourism environments that convey high prestige and regard among unacquainted customers could be managed as a satisfying experience through proper customer education For farm tourists, it was found that families, friends, and relatives play important roles as travel companions who exchange care and warmth through shared experience as well as being a source of information related to farm visits Accordingly, when developing marketing programs, operators should emphasize the wants and needs of travel groups as well as those of individual tourists Although interaction with companions is not directly controllable, agritourism services could provide a context for mutual enjoyment and shared experience, leading to couple-, family-, and groupfriendly environments As a vast majority of respondents were accompanied by their family to the farms, service providers should emphasize in their advertising family-friendly environmental characteristics that could enhance satisfaction for the travel party with whom agritourists will travel 5.3 Limitations and further research Additional efforts in scale development need to be done to ensure the validity and reliability of the social interactions scales used as the process of developing the social interactions scale adopting resource theory in the tourism field is fairly new In particular, due to dual factor loading and insufficient factor loading scores, all items belonging to the product dimension of social interactions with service providers were not included in the final model Therefore, the influence of product exchange could not be tested in this study, although at face value it appears to be theoretically and practically important Subsequent efforts in scale formation addressing this dimension should be made for more theoretical completeness Additionally, a high item nonresponse rate of social interactions with local residents resulted in the deletion of this concept from the final model for this study The characteristics of study farms (i.e., standalone farms without near farms or many neighbors) and the lack of a concrete definition of “local residents” from the various agritourists’ perspectives (i.e., local visitors, out-of-state visitors) are potential reasons for the high item nonresponse rate A more specific definition of “local resident” relevant to the various types of agritourists needs to be determined for future research In addition, the data collection for this study relied on survey informant gathered at only three farms in Texas, so the result of the study likely should not be generalized beyond the study population Finally, this study suggests that the success of tourism business on farms can be 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