Mediating roles of emotion and experience in the stimulus-organism-response framework in higher education institutions

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1 Journal of Marketing for Higher Education ISSN: (Print) (Online) Journal homepage: Mediating roles of emotion and experience in the stimulus-organism-response framework in higher education institutions Mei-Teh Goi, Vigneswari Kalidas & Norzita Yunus To cite this article: Mei-Teh Goi, Vigneswari Kalidas & Norzita Yunus (2018) Mediating roles of emotion and experience in the stimulus-organism-response framework in higher education institutions, Journal of Marketing for Higher Education, 28:1, , DOI: / To link to this article: Published online: 20 Jan Submit your article to this journal Article views: 167 View Crossmark data Full Terms & Conditions of access and use can be found at

2 JOURNAL OF MARKETING FOR HIGHER EDUCATION 2018, VOL. 28, NO. 1, Mediating roles of emotion and experience in the stimulus-organism-response framework in higher education institutions Mei-Teh Goi a, Vigneswari Kalidas a and Norzita Yunus a,b a Faculty of Business and Accounting, Infrastructure University Kuala Lumpur (IUKL), Kajang, Malaysia; b Faculty of Arts, Communication, and Education, Infrastructure University Kuala Lumpur (IUKL), Kajang, Malaysia ABSTRACT This study aims to examine the Stimulus-Organism-Response (SOR) model in the context of Higher Education Institutions (HEIs). Unlike previous studies, this study tested two organism variables, namely emotion and experience, as mediators in the relationship between seven dimensions of stimulus and response. Self-administered questionnaires were distributed to students in public and private HEIs. A total of 424 questionnaires were used in the data analysis. Using structural equation modeling, this study shows that emotion significantly mediated the relationship between three dimensions of stimulus (layout and facilities, fellow students, and employees) and response. This study also found that experience significantly mediated the relationship between two dimensions of stimulus (layout and facilities, and students fellows) and response. The findings suggest that emotion and experience play an important role as mediators in the relationship between stimulus and response. ARTICLE HISTORY Received 25 April 2017 Accepted 25 July 2017 KEYWORDS Stimulus-organism-response (SOR); higher education institutions (HEIs); emotion; experience Introduction As higher education institutions (HEIs) are individually unique, they may fail to distinguish themselves by using a common marketing strategy. The growing participation of the private sector and international universities in the higher education industry in Malaysia has made it increasingly difficult for marketing practitioners to compete in the industry. Specifically, in retaining students, HEIs need more effort to remain competitive (Dennis, Papgiannidis, Alamanos, & Bourlakis, 2016). With a huge number of HEIs, consumers decisions to remain in the same university are driven by various factors. However, a review of the current literature suggests that not all stimulations would influence consumer behavior. No general agreement on these stimulations exists in the service marketing literature despite the fact that different service strategies should be applied to different types of service. As a result, marketing practitioners have blindly adopted any available strategies to stimulate consumers. Some HEIs practice similar strategies to compete effectively in the market (Rauschnabel, Krey, Babin, & Ivens, 2016). Although HEIs have attempted to invest millions of dollars in building and designing attractive campuses CONTACT Mei-Teh Goi goimt@iukl.edu.my 2018 Informa UK Limited, trading as Taylor & Francis Group

3 JOURNAL OF MARKETING FOR HIGHER EDUCATION 91 (Bernama, 2008), this strategy seems to have been ineffective in retaining students. For example, a private university indicated that from the year 2013 to 2016, an average of 6.27% students withdrew from the university. In the USA, according to Shah, Nair, and Bennett (2013), the enrollments in private institutions had sharply increased by 225% from 1998 to However, in Malaysia, the enrollments in private institutions showed an increase of only 2% from 531,479 in 2000 to 541,629 in 2010 (Ministry of Higher Education, 2017). In order to compete in an increasingly complex and competitive business environment, Pucciarelli and Kaplan (2016) urged that HEIs apply a pure marketing theory that suits a university setting. However, past literature on students as customers focuses heavily on academic quality rather than pure marketing concepts (e.g. Abdullah, Wasiuzzaman, & Musa, 2015; Shah et al., 2013). Guilbault (2017) supported the need for marketing in HEIs because students can be viewed as the customer, and education as a service system. Pucciarelli and Kaplan (2016) further explained the need for an appropriate strategy for HEIs, thus called for research on strategy within HEIs. Since students are customers, the adaptation of consumer behavior theory and the study of consumers behavior is crucial for future sustainability. A number of models have been adopted in the study of consumer behavior. Within environmental psychology, the SOR model has been widely used in understanding how external stimulus influences consumer behavior (Turley & Milliman, 2000). In order to understand students as customers, the SOR model was developed intensively to help researchers understand consumer behavior (Turley & Milliman, 2000). Marketing researchers have suggested that the SOR model needs to be modified across time because consumers change over time (Yoo, Park, & MacInnis, 1998). Consequently, there has been a lot of research on the SOR model within the physical store or bricks-and-mortar retailing (e.g. Turley & Milliman, 2000; Walsh, Shiu, Hassan, Michaelidou, & Beatty, 2011; Yoo et al., 1998). Yet, only a limited number of studies have adopted the model for unique retailers such as tourism (Kim & Moon, 2009), hospitality (Daunt & Harris, 2012), and theme parks (Dong & Siu, 2013). Furthermore, Chang (2016) clarified that the relationship between stimulus, organism, and response is different within the service industry depending on the types of services and the level of employee engagement with the customers. Thus, it is crucial for an empirical SOR model to be developed within the higher education industry. A number of mixed models related to consumer behavior have been introduced within the service industry (Turley & Milliman, 2000). Though theoretically informed or empirically tested, a number of limitations were found in the studies. First, the operational definition of stimulus, organism, and response was inconsistent, and subject to the industry in which the model was tested. Harris and Ezeh (2006) explained that most past studies tended to focus on only one of the dimensions of the variables tested; very few studies incorporated the influence of more than one dimension of the variable. Second, two different types of model were found in the literature: a model with a mediator between stimulus and response (Spies, Hesse, & Loesch, 1997; Turley & Milliman, 2000; Vieira, 2013; Yoo et al., 1998); and a model without a mediating variable between stimulus and response (Daunt & Harris, 2012; Lin, 2004; Wong, Osman, Jamaluddin, & Chan, 2012). Third, Wakefield and Blodgett (1996) claimed that services research to date has heavily focused on service encounters of relatively short duration,

4 92 M.-T. GOI ET AL. thus there is a lack of studies on customers with a long duration within the service. The short duration service includes those in travel, banking, and restaurants. The long duration service requires customers to spend an extended period of time, such as in leisure facilities, hotels, and resorts (Wakefield & Blodgett, 1996). Chang (2016) explained that the longer the periods spent by a customer, the more robustly the stimulus will influence the customer s attitude. Angulo-Ruiz, Pergelova, Cheben, and Angulo-Altamirano (2016) agreed that research in higher education marketing is slow as compared to the growth of the education sector itself. In the case of HEIs, customers are generally required to spend at least two to three years within the physical surrounding of the service; therefore, is the consumer behavior model applicable to other service industries? In order to investigate this, this study aims to examine the relationship between stimulus, organism, and response in the context of HEIs. Building on the existing activities of HEIs, this study strives to provide a theoretical foundation for the HEI consumer research effort. This study s contribution to knowledge is embedded in the development of a theoretical model that explains how each dimension of stimulus influences customers responses specifically in the higher education industry. In addition, this study contributes to the body of knowledge by enriching the evidence of the mediating role of emotion and experience in the SOR model. Since prior literature has over-depended on customers emotion in developing the SOR model, this study attempts to introduce customer experience in the SOR model that can distinguish between the service industry and the retailing theory. SOR theory The SOR model was developed many years ago to help researchers understand consumer behavior (Turley & Milliman, 2000). The SOR model has been extensively adopted for understanding consumer behavior and experiences (Luqman, Cao, Ali, Masood, & Yu, 2017), but is rarely adopted for understanding consumers in the higher education industry. Research on the SOR model in service marketing has been consistently growing (Table 1). Within the literature of the SOR model in service marketing, several related perspectives are uncovered. First, a basic consumer behavior model which consists of stimulus as an independent variable, organism as a mediator, and response as the dependent variable (Spies et al., 1997; Turley & Milliman, 2000; Vieira, 2013; Yoo et al., 1998). Most past literature agrees on the interrelationship between stimulus, organism, and response as the basis of a consumer behavior model. However, Daunt and Harris (2012) study focused on the relationship between stimulus and consumer response, neglecting the role of a mediator. Lin (2004), on the other hand, proposed that customers are unable to provide a direct behavioral response to the stimulus without passing through three processes starting from cognitive to affective and from affective to cognitive. Turley and Milliman (2000) had reviewed the literature on the effect of atmosphere on buying behavior from the year 1975 to They argued that the current consumer behavior model is unable to explain, predict, and control the behavior of consumers. This study further reviewed past literature that relates to the adaptation of the consumer behavior model in service industries. Although a number of studies have been conducted on the adaptation of the SOR model within the service industry, the variation of the dimensions introduced had raised doubts. Daunt and Harris (2012) found that there are significant differences

5 JOURNAL OF MARKETING FOR HIGHER EDUCATION 93 Table 1. Summary of SOR model within service industry. No. Citation Service industry Stimulus Organism Response 1. Lin (2004) Hospitality Visual cues Auditory cues Olfactory cues 2. Harris and Ezeh (2006) 3. Kim and Moon (2009) 4. Jang and Namkung (2009) 5. Bruggen et al. (2011) 6. Lam et al. (2011) 7. Walsh et al. (2011) 8. Daunt and Harris (2012) 9. Siu et al. (2012) 10. Dong and Siu (2013) 11. Durna et al. (2015) Restaurant Restaurant Restaurant Fast-food Chain Casino Coffee Shops Hospitality Convention and exhibition center Theme park visitors Hospitality Ambient conditions, Design factors, Staff behavior, Staff image Facility Aesthetics, Layout, Electrical equipment, Seating comfort, Ambient conditions Product quality, Atmospherics, Service quality Lighting, Color, Layout, Furnishing, Paintings Ambience, Navigation, Seating comfort, Interior décor, Cleanliness In-store music, In-store aroma, Merchandise quality, Service quality, Price Physical, Social Ambient conditions, Spatial layout, Functionality, Signs, Symbols, Artifacts, Cleanliness Substantive staging (background, functional), Communicative Staging (Employee behavior, employee image, cultural, atmospherics) Substantive staging of servicescape, Communicative staging of servicescape 12. Jani and Han (2015) 13. Chang (2016) Hospitality Substantive staging, Communicative staging Cognitive Behavior Affective Cognitive process Loyalty intentions Emotion (Pleasurefeeling & Perceived Service Quality) Emotion Revisit Intention Behavioral intentions Cognitive Affective Behavioral Satisfaction (cognitive and affective) Emotions (Arousal & Pleasure) Desire to Stay Intention to revisit Marketing outcomes (Store satisfaction & Store loyalty) Customer disaffection (Inequity, Dissatisfaction) Affect Satisfaction Desire to Stay Service experience evaluation Corporate image Hospitality Ambience Emotional Loyalty Customer emotions Experience (intensification & extension) Revisiting intention Word-of-Mouth Behavioral intentions in consumers responses across different service environments. An inspection of the current literature suggests that not all consumer behavior models may appropriate for all services because service itself is unique in nature. Therefore, there is a need to combine various variables from past literature on the service industry and further examine these variables within the HEI setting.

6 94 M.-T. GOI ET AL. Second, the focus of past literature within the service industry can be divided into three categories: the restaurant sector (Bruggen et al., 2011; Harris & Ezeh, 2006; Jang & Namkung, 2009; Kim & Moon, 2009; Walsh et al., 2011), hospitality (Chang, 2016; Daunt & Harris, 2012; Jani & Han, 2015; Lin, 2004), and leisure (Dong & Siu, 2013; Lam et al., 2011). Most past literature focused on services directed at people s bodies such as restaurants and hospitality. Education is known as a service directed at people s minds, and the nature of the service is intangible actions (Lovelock & Wirtz, 2011). The consumer needs to invest a lot of time and a degree of mental effort in the education service, thus the consumer behavior model may vary as compared to other types of services. When differences occur in the nature of services, the conceptualization of the variables may vary. To date, no agreement exists within the marketing literature on the dimensions of stimulus, organism, and response. For example, ambience has been widely used as a dimension of stimulus (Harris & Ezeh, 2006; Jani & Han, 2015; Kim & Moon, 2009; Lam et al., 2011; Siu et al., 2012), but the other dimensions vary within the literature. Customer satisfaction has been used as a dimension for both organisms (Lam et al., 2011; Siu et al., 2012) and response (Daunt & Harris, 2012; Walsh et al., 2011). Third, there has not been an acceptable and consistent variable of organism examined in past literature. Based on the review of the literature on the service industry, five different variables of organism emerge, namely emotion, affect, experience, corporate image, and cognitive. Within the service industry, the most extensively used variable as organism is emotion or affective (Chang, 2016; Jani & Han, 2015; Kim & Moon, 2009; Walsh et al., 2011). The second most widely used is experience (Dong & Siu, 2013). Further, the study by Dong and Siu (2013) explained that to differentiate the service industry and traditional service, experience is essential. The third variable is corporate image. Corporate image was examined by Durna et al. (2015) as organism in hospitality industry. Durna et al. (2015) explained that corporate image is used because customers in other regions cannot experience the product. Therefore, corporate image is not appropriate for this study. The fourth variable introduced in past literature is cognitive. Lin (2004) suggested that cognitive came directly after stimulus rather than emotion. Lin (2004) explained that many studies ignored the cognitive process because the interrelationship between cognitive and emotion is arguable. Since cognitive has not been empirically tested (Lin, 2004), it has been eliminated from this study. Furthermore, Bruggen et al. (2011) had included cognitive in measuring customer response. In order to fill the gaps in past literature, emotion and experience were addressed in this study. Stimulus Stimulus refers to the design of physical environments that are outlined by a firm to enhance the action of their employees and customers (Kim & Moon, 2009; Lin, 2004), and it is a manmade tangible environment (Kim & Moon, 2009). From Table 1, various dimensions of stimulus had been introduced in the service industry. Studies had investigated stimulus in the same service industry, yet the conceptualization of stimulus varies. For example, Chang (2016), Daunt and Harris (2012), Durna et al. (2015), and Jani and Han (2015) had examined the SOR model within the hospitality industry, but none of the dimensions was identical. Due to the unclear conceptualization of stimulus, Fiore and Kim (2007) had reviewed past literature and concluded that the dimensions of

7 JOURNAL OF MARKETING FOR HIGHER EDUCATION 95 stimulus can be divided into two factors: design and social. Some past literature concurred with the suggestion and included human elements in their studies (Chang, 2016; Daunt & Harris, 2012; Dong & Siu, 2013; Durna et al., 2015; Harris & Ezeh, 2006). However, in examining the impact of stimulus, some studies only focused on the physical elements (Bruggen et al., 2011; Kim & Moon, 2009; Lam et al., 2011) whereas others have found that stimulus is a multidimensional variable. Goi and Kalidas (2015) had examined all the dimensions and found that stimulus was a multidimensional concept within HEI contexts, consisting of interior, wellbeing, location, exterior, layout and facilities, fellow students, and employees. Goi and Kalidas (2015) study only focused on the dimensions of stimulus and did not relate the dimensions to other variables. Stimulus and response The atmosphere is the stimulus that influences customers evaluation and response (Turley & Milliman, 2000). Vieira (2013) claimed that many findings related to stimuli are insufficient in providing a detailed understanding of which of atmosphere s cues affect consumer response. Although research on stimuli within the service industry has long been acknowledged, the results are irreconcilable. Based on a review of the literature, two types of relationship between stimulus and customer response have been introduced. First, the direct relationship between stimulus and customer response (Daunt & Harris, 2012; Lin, 2004; Wong et al., 2012). In the service industry, Daunt and Harris (2012) concurred that stimulus is an important preliminary factor in influencing customer response, positively or negatively. Past studies have shown inconsistent results on the impact of the dimensions of stimulus on customer response. For example, Harris and Ezeh (2006) found six dimensions (aroma, cleanliness, implicit communicators, furnishing, customer orientation, and physical attractiveness) from the nine dimensions of stimulus significantly influencing customer response in a restaurant setting. Bruggen et al. (2011) also found mixed results on the impact of the dimensions of stimulus toward cognitive, behavioral, and affective outcomes. Chang (2016) examined different dimensions of stimulus as compared to Bruggen et al. (2011) and Harris and Ezeh (2006). Chang (2016) found a significant relationship between employee engagement and behavioral intentions. Findings from Carter and Yeo s (2015) study on business students in Malaysian HEIs suggested five dimensions of stimulus academic experience, faculty quality, campus life, facilities, and placement support related to students intention to continue their higher degree. However, the study found that only academic experience was significantly related to student persistence. The second type of relationship is a mediated relationship between stimulus and response (Chang, 2016; Dong & Siu, 2013; Jang & Namkung, 2009; Lam et al., 2011; Walsh et al., 2011). Literature in the non-service industry also indicated that stimulus can influence customer organism before customer response (Dong & Siu, 2013; Fiore & Kim, 2007; Kaltcheva & Weitz, 2006; Kim & Moon, 2009 ; Lam et al., 2011; Turley & Milliman, 2000; Vieira, 2013; Walsh et al., 2011; Yoo et al., 1998). Fiore and Kim (2007) explained that response is the final result or outcome of the internal processes of organism. Although most past literature had focused on the influence of stimulus on organism and organism on response, there is no consistency in the elements of organism or the mediator. Dong and Siu (2013), Jang and Namkung (2009), Kim and Moon (2009), Lam et al. (2011), and

8 96 M.-T. GOI ET AL. Walsh et al. (2011) had adopted the three variables of the consumer behavior model in the service industry and also introduced mediators. Organism Organism refers to the internal and the intervening process which consists of perceptual, physiological, feeling, and thinking activities (Kumar & Kim, 2014). Based on Lam et al. s (2011) study, organism was designated as satisfaction and divided into cognitive and affective satisfaction. Kim and Moon (2009) divided organism into emotion and perceived service. Although the SOR model has been widely studied, many of the dimensions in an organism are not uniform. An interesting study by Lin (2004) suggested three organisms: cognitive, affective, and cognitive process. However, Lin (2016) used different variables of organism, namely, experience, pleasure, and arousal. Based on a review of past literature, seven out of 13 studies used emotion in their study (Table 1). Three additional dimensions suggested or adopted in past literature are experience, cognitive, and corporate image. Yet, Lam et al. (2011) explained that cognitive satisfaction is similar to customer experience. Verhoef, Lemon, Parasuraman, Roggeveen, Tsiros & Schlesinger (2009) stated that experience has not been considered as a variable in past studies because the operationalization of the variable is misleading. For example, consumption, search, purchase, and after-sale phases had been used to describe experience in retailing studies (Verhoef et al., 2009). Chang (2016) found that stimulus is likely to influence customer service experiences and emotions. For the purpose of this study, two mediators were adopted based on Chang (2016), namely, emotion (Chang, 2016; Jang & Namkung, 2009; Jani & Han, 2015; Kim & Moon, 2009; Walsh et al., 2011), and experience (Dong & Siu, 2013). The two mediators are appropriate for this study for two reasons. First, emotion has been extensively used in previous studies on consumer behavior (Kim & Moon, 2009; Ladhari, Souiden, & Dufour, 2017). Second, experience is the central objective in the service industry (Verhoef et al., 2009), and is used widely in the study of service marketing (Dong & Siu, 2013; Olsson, Friman, Pareigis, & Edvardsson, 2012). Emotion and affection are the most significant psychological variables adopted by retailing researchers. Emotion and affection are used interchangeably by researchers (Hsu & Liu, 1998). For the purpose of this study, emotion was adopted. Abdullah et al. (2015) explained that emotion has been newly adopted within the HEI setting and it is more important than satisfaction for long-term relationship services such as HEIs. However, the conceptualization of emotion within HEIs has not been much discussed. Within the retailing industry, emotion refers to the subjective state of feeling within consumers (Fiore & Kim, 2007). According to Yoo et al. (1998), emotion can be defined as a set of discrete and phenomenologically distinct affective states. Past literature had operationalized emotion in different ways. For example, Kaltcheva and Weitz (2006), and Walsh et al. (2011) had referred to emotion as pleasure and arousal. Kim and Moon (2009) had operationalized emotion as pleasure and perceived service quality. Though Lam et al. (2011) equated organism with satisfaction, the study actually referred to customers satisfaction level based on their emotional states. Walsh et al. (2011) conceptualized emotion as arousal and pleasure occurring during a service. For the purpose of this study, the operational definition was adopted from Kim and Moon (2009), which refers to emotion as pleasure experienced during study in an HEI.

9 JOURNAL OF MARKETING FOR HIGHER EDUCATION 97 The second variable used as an organism in past literature is experience. Past literature had focused on the impact of experience toward customer responses such as customer satisfaction, loyalty, and intentions (Jain, Aagja, & Bagdare, 2017). However, Dong and Siu (2013) introduced experience as a mediator. Srivastava and Kaul (2014) found that customer experience mediated the relationship between stimulus and customer response. They focused on convenience and social interaction as stimulus. Since Guilbault (2017) indicated that higher education is a service system, experience may play an important role as a mediator in an HEI setting. Thus, customer experience is adopted in this study to clarify the relationship between stimulus, experience as an organism, and response. According to Abdullah et al. (2015), students experience occurs when students interact with employees as well as when they engage with facilities provided by the HEIs. Past literature claimed that the operationalization of experience was parallel with cognitive perspective. In the retailing industry, Dong and Siu (2013) also recommended service experience as one of the important elements in service industries. Customer experience is a relatively new research topic within the last three decades, and has received extensive focus in recent studies (Jain et al., 2017). Customer experience includes every point of contact at which customers interact with services (Grewal, Levy, & Kumar, 2009). Esbjerg et al. (2012) indicated that the concept of experience remains undefined and is without empirical support in the literature. Jain et al. (2017) supported the position that there is no agreement within past literature on the variable and its definitions. Although there is no widely accepted definition of experience, most definitions associated experience with customers psychological construct (Rose, Clark, Samouel, & Hair, 2012). For example, Olsson et al. (2012, p. 413) defined experience as cognitive and affective response to any direct or indirect contact with the company or its resources. According to Rose et al. (2012), customer experience can be defined as a psychological state manifested as a subjective response to the service provider. Based on Jain et al. (2017, p. 658), customer experience is described as a holistic concept, representing sum total of feelings, perceptions and attitudes created during successive stages of consumption process as a result of interactive process. This study adopted Rose et al. s (2012) view which defined consumer experience as affect, consisting of sensorial, emotional, cognitive, pragmatic, lifestyle, and relational elements. Response The most important purpose of developing an SOR model is that changes in stimulus and organism can bring a significant change in response. Fiore and Kim (2007) explained that response is the result of organism, expressed as approach or avoidance behaviors, intentions, choice, and decision. A number of past studies have examined single response elements such as behavior (Chang, 2016; Harris & Ezeh, 2006; Jang & Namkung, 2009; Jani & Han, 2015; Kim & Moon, 2009; Lam et al., 2011; Siu et al., 2012) or affect (Daunt & Harris, 2012; Walsh et al., 2011). Within service marketing literature, behavioral reactions have been mostly accepted in measuring consumers response. The behavioral perspective measures consumers response in terms of loyalty (Harris & Ezeh, 2006; Jani & Han, 2015; Walsh et al., 2011), and patronage intention (Chang, 2016; Kim & Moon, 2009; Lam et al., 2011). From the affective perspective, Daunt and Harris (2012), Siu et al. (2012), and Walsh et al. (2011) introduced satisfaction. Dong and Siu (2013) explained

10 98 M.-T. GOI ET AL. that customer response cannot only focus on long-term outcomes, but also immediate outcomes which include affective and cognitive outcomes. Thus, Dong and Siu (2013) measured consumer response from a cognitive perspective. Bruggen et al. (2011) agreed and suggested that customer response should include behavioral, affective and cognitive reactions. The elements include perceived value, perceived service quality, store image, overall satisfaction, encounter satisfaction, and attitude. Based on Bruggen et al. s (2011) explanation, the three dimensions of response are considered in the operationalization of customer response. Hypothesis development Interior Interior refers to visual elements related to aesthetic appeal or known as décor (Harris & Ezeh, 2006). Lam et al. (2011) explained that interior includes signs, symbols, and artifacts. Jang and Namkung (2009) adopted the term atmospherics for describing restaurant facility layout, interior design, colors, lighting, and background music. On the other hand, Goi and Kalidas (2015) found that interior within an HEI consists of a clean environment, air quality, temperature, and lighting in the classroom. Interior has been studied widely in examining the facets of the stimulus in the SOR model (Turley & Milliman, 2000). Harris and Ezeh (2006) and Lam et al. (2011) found that interior was significantly related to customer response. Harris and Ezeh (2006) examined the impact of interior (implicit communicators and furnishing) with loyalty intention in a restaurant and found that interior significantly related to intention of loyalty. Therefore: Hypothesis 1(a): Interior has an influence on customer response. Lam et al. (2011) found that emotion mediates the relationship between interior and customer response. Customer response has been operationalized as customers intention to stay and revisit (Lam et al., 2011). Jang and Namkung (2009) clarified that interior is significantly related to positive emotion, but is not significantly related to negative emotion. Based on the finding, this study hypothesized: Hypothesis 1(b): Interior has an influence on customer emotion. To date, limited studies have aimed to examine the impact of interior on experience. Lee and Jeong (2012) suggested that the design of a website can influence customer experience. However, Lam et al. (2011) found that experience does not significantly mediate the relationship between interior and response of consumers in a casino. Based on the argument above, this study hypothesized: Hypothesis 1(c): Interior has an influence on customer experience. Wellbeing Wellbeing of an HEI refers to an environment that is safe, secure, calm, and provides ample parking spaces (Goi & Kalidas, 2015). The concern with creating a crime-free environment has recently gained importance due to the threat of terrorism, bomb attacks, shoplifting, shrinkage, and vandalism (Kajalo & Lindblom, 2015). The facet of safety and security has

11 JOURNAL OF MARKETING FOR HIGHER EDUCATION 99 not been much investigated in past literature. Wong et al. s(2012) study among Malaysian customers introduced the facet of safety and security in describing the quality of a mall. Additionally, Turley and Milliman (2000), Yoo et al. (1998), and Wong et al. (2012) introduced parking facilities as an important facet in stimulus. The impact of wellbeing has not received much attention in SOR studies. According to the logic of the SOR model, this study proposes the following: Hypothesis 2(a): Wellbeing has an influence on customer response. The issue of security has been thoroughly examined in online shopping, but not in retailing or service marketing. Kim and Lennon (2013) adopted the SOR model in online shopping and found that security had a significant positive effect on customers emotions. According to this logic, this study proposes that increased wellbeing will lead to a more positive emotion: Hypothesis 2(b): Wellbeing has an influence on customer emotion. The online shopping literature has extensively examined the link between security and experience (e.g. Chang, Chih, Liou, & Yang, 2016), but such a link is not clear within the retail or service industry. Kajalo and Lindblom (2015) explained that a safe and pleasant shopping environment is important for retailers ability to offer both consumer and social experiences. However, the investigation only focused on retailers and not consumers. Therefore: Hypothesis 2(c): Wellbeing has an influence on customer experience. Location Location is operationalized as the convenience of the location, availability of transportation, and access road to the HEI (Goi & Kalidas, 2015). The impact of location is frequently adopted in studies on retail and shopping malls. Location is crucial in developing the SOR model (Yoo et al., 1998). Yoo et al. (1998) have established a link between product assortment, value of merchandise, salesperson service, after sales service, facilities, and atmosphere with emotion. Location, as one of the independent variables, is not linked with emotion, but is directly linked to customer response. This present study extends Yoo et al. s (1998) study on the link between location and emotion. Therefore: Hypothesis 3(a): Location has an influence on customer response. Srivastava and Kaul s (2014) study found that the location of department stores significantly influences customer emotion. They selected customers from department stores in India. Kent (2003) discovered that studies conducted in different geographical areas offer different kinds of outcomes. Therefore, further study is needed to examine the relationship: Hypothesis 3(b): Location has an influence on customer emotion. Location is rarely suggested as a factor influencing customer experience (Grewal et al., 2009). According to Srivastava and Kaul (2014), a good location of a department store has a stronger impact on customer experience than customer emotion. This is because customer emotion is influenced by various other dimensions, whereas customer experience is only

12 100 M.-T. GOI ET AL. influenced by the tangible and intangible factors offered by a firm (Srivastava & Kaul, 2014). Therefore, this study hypothesizes that location will have an effect on experience. Hypothesis 3(c): Location has an influence on customer experience. Exterior Exterior refers to external variables which include the store front, marquee, entrances, display windows, building architecture, and surrounding area (Turley & Milliman, 2000). The exterior of an HEI refers to the entrance gate, building architecture, gardens and landscape, building size, and decoration (Goi & Kalidas, 2015). Mower, Kim, and Childs (2012) claimed that exteriors are what customers first encounter as they enter into a retail outlet, and it is particularly important for brands which are unknown. Turley and Milliman (2000), based on a body of work on the SOR model, found exterior to be the antecedents of the model. Past literature has focused intensely on the impact of internal factors of retail on customer response (e.g. Harris & Ezeh, 2006; Walsh et al., 2011), but neglected the external factors. Turley and Milliman (2000) suggested that exterior has an influence on the behavior of retail consumers. Therefore: Hypothesis 4(a): Exterior has an influence on customer response. Mower et al. (2012) operationalized mood as pleasure and arousal, but Lucia-Palacios, Perez-Lopez, and Polo-Redondo (2016) considered pleasure and arousal as emotion. Mower et al. (2012) has examined the impact of exterior on emotion in a small apparel boutique. Mower et al. s (2012) study had suggested that exterior leads to customer s mood, but the study empirically found that exterior was not significantly related to mood. Based on the suggestion, this study hypothesizes: Hypothesis 4(b): Exterior has an influence on customer emotion. Little is known about the influence of exterior on customer experience from past literature. Exterior, which was introduced by Turley and Milliman (2000) after a comprehensive review of past literature, has not been linked to experience. Kent (2003) explained that during the 1980s, the external design of a store was equally as important as the interior design in enhancing customer experience in shopping environments. Based on the suggestion, the following hypothesis is developed: Hypothesis 4(c): Exterior has an influence on customer experience. Layout and facilities The layout and facilities of an HEI consist of well-maintained and up-to-date facilities, café, rest and leisure facilities, library, computer, furniture, and interior design (Goi & Kalidas, 2015). The dimension is related to what Lam et al. (2011) referred to as navigation of service in the casino. Navigation refers to sight lines, aisle width, signs/directions, ease of locating, number of facilities, and ceiling height. Siu et al. (2012) used spatial layout as the term to describe the facilities provided by convention and exhibition centers. Harris and Ezeh (2006) indicated layout and facilities as visual elements that enhance the intrinsic cue on an organization s effectiveness. Layout and facilities

13 JOURNAL OF MARKETING FOR HIGHER EDUCATION 101 were found to be significantly related to customer response (Harris & Ezeh, 2006; Kim& Moon, 2009). Consistent with the SOR model in the food and beverage industry, this study proposes: Hypothesis 5(a): Layout and facilities have an influence on customer responses. Kim and Moon (2009) investigated two mediators between stimulus and customer response, namely emotion and perceived service quality. Kim and Moon (2009) found that layout and facilities have a significant effect on emotion. Similarly, Lam et al. (2011) discovered that layout and facilities were related to emotion. Both Kim and Moon (2009) and Lam et al. (2011) have focused their study on intention behavior rather than a wider response from customers. In order to understand customer response from a broader perspective, this study hypothesizes: Hypothesis 5(b): Layout and facilities have an influence on customer emotion. Lam et al. (2011) found that experience significantly mediated the relationship between navigation and intention to revisit and desire to stay. Based on qualitative analysis, Pareigis, Echeverri, and Edvardsson (2012) suggested that navigation forms customer service experience. Another study, by Lucia-Palacios et al. (2016), also proposed a relationship between physical design and experience. They also proposed that malls pay attention to a non-confusing and well-organized layout for customers efficiency during their shopping experience. In a private HEI setting, Abdullah et al. (2015) found that facilities are significantly related to experience. Therefore, this study proposes: Hypothesis 5(c): Layout and facilities have an influence on customer experience. Fellow students Daunt and Harris (2012, p. 134) defined fellow customers as the extent to which patrons within the service environment behave in a manner that is deemed appropriate by other customers present. Since this study is within the context of HEIs, the dimension is termed as fellow students. A few facets have been identified under fellow students: students crowd, students behavior, enjoyment with other students, and students manners (Goi & Kalidas, 2015). Based on a conceptual paper, Verhoef et al. (2009) indicated that customers can also affect other customers, directly or indirectly. From all the facets introduced, crowding has been frequently used in prior studies. For example, Turley and Milliman (2000) explained that consumer crowding influences customer perceptions within the retail atmospheric. Therefore, Hypothesis 6(a): Fellow students have an influence on customer response. Fiore and Kim (2007) reviewed past literature and proposed that fellow customers have an impact on emotion. However, the relationship has not been extensively examined by researchers. The relationship between crowding and customer emotions also suggested by Hwang, Yoon, and Bendle (2012) within a restaurant setting. Hwang et al. (2012) found that crowding significantly influences customer emotion. Therefore, this study hypothesizes that: Hypothesis 6(b): Fellow students have an influence on customer emotion.

14 102 M.-T. GOI ET AL. Verhoef et al. (2009) suggested the need to study the impact of social environment on customer experience. The direct impact of fellow students on customer experience depends on the nature of the theory adopted by the researcher (Fiore & Kim, 2007). Fiore and Kim (2007) explained that when the competing cognitive theory of emotion model is adopted, fellow customers have a direct influence on experience followed by emotion. However, if the SOR model is used in environmental psychology, fellow customers have indirect influence on experience mediate by emotion. However, Lucia-Palacios et al. (2016) proposed that crowding only has an impact on customer experience. Taken together, these two streams of studies introduced the idea that there is a relationship between fellow students and experience. Therefore, this study proposes: Hypothesis 6(c): Fellow students have an influence on customer experience. Employees Employees refers to employee service, characteristics, and image (Goi & Kalidas, 2015; Harris & Ezeh, 2006; Turley & Milliman, 2000). The employees of HEIs include the academic and non-academic staff who provide services to customers. Turley and Milliman (2000) indicated that less attention has been given to studies on the impact of employees in the SOR model. Chang (2016) refers to employee as a communicative staging of servicescape to demonstrate employee characteristics that include employees who are helpful, polite and friendly, give personal attention, and are passionate. Daunt and Harris (2012) found that different types of customer perceive differences in employee service in the hospitality industry. Harris and Ezeh (2006) discovered that not all of the employee facets significantly related to customer response in a restaurant. Therefore: Hypothesis 7(a): Employees have an influence on customer response. Although most of the past literature has suggested the relationship of employees with customer experience and not with emotion, Chang (2016) claimed that his/her study differs compared to that by Dong and Siu (2013) which links employees with emotion rather than experience. The study confirmed that employees positively affect customer emotion in the hospitality industry. Therefore, this study hypothesizes the following: Hypothesis 7(b): Employees have an influence on customer emotion. Verhoef et al. (2009) suggested that the impact of employees, known as service interface, is related to customer experience. Dong and Siu (2013) also discovered that employees positively affect customer experience in a theme park. However, Abdullah et al. (2015) found that the quality of the academic and administrative staff was not significantly related to students experience. Since Abdullah et al. s (2015) study focused only on a private HEI, the impact of employees on customers experience needs to be further examined. Thus, the following hypothesis is developed: Hypothesis 7(c): Employees have an influence on customer experience. Emotion as mediator Based on the hypotheses above, this study further examined the role of emotion and experience as mediators between all the dimensions of stimulus and customer response.

15 JOURNAL OF MARKETING FOR HIGHER EDUCATION 103 The literature has shown some support for the mediating role of emotion between stimulus and customer response (Jang & Namkung, 2009; Jani & Han, 2015; Kim & Moon, 2009; Lam et al., 2011; Walsh et al., 2011). Therefore, Hypothesis 8: Emotion mediates the relationship between stimulus and response of consumers. Stimulus consists of (a) interior, (b) wellbeing, (c) location, (d) exterior, (e) layout and facilities, (f) fellow students, and (g) employees. Experience as mediator Research on experience as a mediator in the SOR model is rare and most past literature has not quantitatively examined experience within service marketing. For example, Fiore and Kim (2007) suggested the mediating role of experience between stimulus and customer response based on reviewed past literature. Based on interviews, Lucia-Palacios et al. (2016) proposed the mediating role of experience between stimulus and behavioral responses. Thus, this study hypothesized the following: Hypothesis 8: Experience mediates the relationship between stimulus and response of consumers. Stimulus consists of (a) interior, (b) wellbeing, (c) location, (d) exterior, (e) layout and facilities, (f) fellow students, and (g) employees. Figure 1 illustrates the framework of this study. The proposed research framework aims to investigate each dimension of stimulus toward customer response which consists of three dimensions, namely cognitive, affective, and behavioral. The research framework also comprised two proposed mediators and seven dimensions of stimulus-response relationship. Method Procedure and sample The population consisted of students in public and private HEIs in Malaysia. This study used quota sampling, in which the sample was selected from 10 universities five private and five public. For data collection, 500 sets of questionnaires were distributed equally to the selected HEIs using quota sampling. The questionnaire was distributed to 50 full-time students who were willing to spend their time on this study. A total of 439 were returned and useable. In order to identify the outlier, exploratory data analysis (EDA) was performed to screen the data for violation of assumptions for statistical tests. After EDA was performed, 424 questionnaires were deemed useable for analysis. Table 2 illustrates the descriptive summary of the respondents. The results of the standard deviations (SD) and skewness values did not suggest problems with the assumptions of normality (Table 3). Of the 424 respondents, 55.9% of respondents were male, 39.4% were in their second year of study, and 55.2% studied in public HEIs. Measures Stimulus This study adopted the stimulus scale developed by Goi and Kalidas (2015), which consisted of 44 items. The items were developed from past studies by Daunt and Harris (2012), Dong and Siu (2013), Kim and Moon (2009), Lam et al. (2011), Lin (2004), Turley

16 104 M.-T. GOI ET AL. Figure 1. Research framework. and Milliman (2000), Walsh et al. (2011), Wong et al. (2012), and Yoo et al. (1998). Interior consists of 4 items; there are 3 items for wellbeing, 3 items for location, 5 items for exterior, 13 items for layout and facilities, 5 items for fellow students, and 3 items for employees. A five-point Likert scale ranging from 1 strongly disagree to 5 strongly agree was used. The instrument was pre-tested by deploying a sample of 40 students who did not participate in the final survey administration. Experience and emotion Redundancy of items between experience and emotion measurement derived from Kim and Moon (2009), Walsh et al. (2011) and Rose et al. (2012) was discovered. Therefore, Table 2. Descriptive summary of sample. Variables N Percentage (%) Gender Male Female Classification First-year Second-year Third-year and above Type of HEIs Private Public

17 JOURNAL OF MARKETING FOR HIGHER EDUCATION 105 Table 3. Validity and reliability of the measures. Variables Factor items No. of Items Factor loading Mean SD Skewness AVE CR Stimulus Interior Wellbeing Location Exterior Layout and Facilities Fellow students Employees Organism Experience Emotion Response Cognitive Affective Behavioral Exploratory Factor Analysis (EFA) was used to decide on the items loading. The outcome indicated that experience consisted of 5 items that supported Rose et al. (2012), and emotion consisted of five items from Kim and Moon (2009) and Walsh et al. (2011). Response The customer response scale developed by Bruggen et al. (2011) was adopted. It is a 17- item measure with three dimensions: cognitive, affective, and behavioral. Respondents were asked to indicate the degree of agreement ranging from 1 strongly disagree to 5 strongly agree.. Reliability and validity A Confirmatory Factor Analysis (CFA) was performed to test the reliability and validity of the instrument (Table 3). The model fits well with the data (X 2 /df = 2.44, RMSEA = 0.06, GFI = 0.92), the composite reliability (CR) is above 0.70, and the average variance extracted (AVE) is above 0.50 (Kim & Mattila, 2010). Before the full model was tested, two basic conditions needed to be considered linear relationship and multicollinearity. Curve estimation was used to test the linearity between stimulus and organism, and stimulus and response. The results indicate that the p-value for all relationships is smaller than 0.05, therefore the model is a good fit for the data. Table 4 presents the correlations and square root of AVE. All the correlations between the variables were significant at the 0.01 level. All the coefficients for the correlations between the variables were lower than the square root of AVE for each construct, which indicated that discriminant validity was supported. A Variance Inflation Factor (VIF) was used to test the multicollinearity problems. The results showed that the VIF values were all below 3.00, thus indicating no multicollinearity among the independent variables. Table 4. Correlations between variables. Stimulus Emotion Experience Response VIF Stimulus Emotion Experience Response Notes: Italicized and bolded are square roots of the AVE. The lower-left triangle and the upper-right triangle elements are the correlations between the variables.