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Moderator And Mediator Effects In Hospitality Research Paper

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Against the background of Fishbein and Ajzen’s (1975) Behavioural Intentions Model (Cognition → Affect → Intention → Behaviour), Swart and Roodt (2008, 2009) investigated how scores on a SQSC (cognition) are related to Retention (intention) scores, and how this relationship is meditated by Satisfaction (affect) scores and moderated by market segmentation variables. This resulted in a Business Tourist SQSC Prediction Model (Swart 2013). This paper aims to investigate the moderating relationship of the market segmentation variables between either the SQSC and Retention or Satisfaction and Retention.

According to research done by Ryan and Bonfield (1975), a market segmentation variable is an antecedent variable which has an influence on, but does not explain the relationships between independent (such as the SQSC) and dependent (such as Retention) variables. Furthermore, Chen et al. (2013) state service quality may influence the evaluation of service quality and satisfaction. It also clarifies the influences that precede these relationships. The weightings associated with the normative and attitudinal components of the model are different across the market segments and, therefore, it is expected that the market segmentation variables, as moderating variables, have an effect on the SQSC (independent variable) and Retention (dependent variable) (Baron and Kenny 1986; Frazier et al. 2004).

Targeting the right customers for a specific customer retention campaign is a high priority (Coussement and Van den Poel 2009). According to Seo et al. (2008), age and gender as market segmentation variables indirectly impact whether a customer will return to an organisation to experience the same product or service. However, they also indicate that more research is needed on other demographics such as education level, and area code (indicating the geographical area or province to which the business tourist travels) to better understand customer retention. Customers’ age groups and levels of education contribute to the explanation of their tendency to return to an organisation (Cohen et al. 2007). Although it has been postulated that Satisfaction facilitates Retention at a destination, is it also important to identify which market segmentation variables will moderate the results of the SQSC. Identifying such variables will potentially contribute to a more favourable experience, leading to Retention. Thus for the purpose of this study, market segmentation variables are defined as the division of the business tourism market into smaller groups of delegates according to their gender, age, ethnic group, educational qualifications, province visited, and needs and characteristics when they are exposed to a business tourism product (as informed by George 2011; Moore et al. 2008).

Researchers have found that demographic variables (such as age and gender) play an important role in product adoption behaviours (Im et al. 2003) and in tourism (Han and Ryu 2006; Li et al. 2013). According to Hudson (1999), psychological forces do not operate in isolation. Mediating and moderating effects have been established in hospitality (Ro 2012), but not in a business tourism context before. Baron and Kenny (1986, p. 1181) are of the opinion that appropriate procedures need to be applied to make the most effective use of the moderator and mediator distinction (in the context of a ‘wide range of phenomena’, which can include attitude and personality traits) in a causal relationship. Moderators and mediators function on three levels, namely from a conceptual (explanations for differences in peoples’ behaviour), strategic (moderators are introduced when there is an inconsistent relationship between the dependent and independents variables), and statistical (indicates the moderating effect of the dependant variable on the independent variable). Moderators may contain either manipulations or assessments, which can be either personal or situational variables. Thus, a moderator is defined as ‘… a qualitative (e.g. gender, ethnic group) or quantitative (e.g. level of reward) variable that affects the direction and/or strength of the relationship between an independent or predictor variable and a dependent or criterion variable’ (Baron and Kenny 1986, p. 1174). Furthermore, multiple regression can be used to examine whether the effects of the predictor or moderator variables are continuous (e.g. as in the case of age) or categorical (e.g. as in the case of gender or ethnic group) (Frazier et al. 2004).

Service quality has a significant relationship with gender (Lee et al. 2011). However, age does not have a significant effect on the link between customer satisfaction and repeat visit intention (Han and Ryu 2006), while educational qualification has a significant relationship with customer satisfaction and perceived quality (Forgas-Coll et al. 2013; Severt et al. 2007). Aguinis (2004) further recommend the inclusion of gender and ethnicity as a best practice in the testing of moderation effects. Based on these findings, Chen et al. (2013) and Seo et al. (2008) recommend further research into the moderation effects of market segmentation variables. Supported by literature, specifically Seo et al. (2008), there is a need to further investigate these moderating relationships in the business tourism industry.

Gender, age, ethnic group, educational qualifications and province most frequently visited are identified as market segmentation variables in this study. Research on these variables is reported below.

2.1 Gender

Gender is one of the most popular segmentation strategies used to understand customers’ attitudes, behaviours and choices (Crouch et al. 2009; Wakefield and Baker 1998) from a multi-channel context (Lin 2011). Gender is defined as the applicable characteristics, such as attitudes, behaviours, roles and values chosen by the male or female respondent (as informed by George (2011); Palan (2001)). Studies found that gender is a moderator in the relationship between quality and loyalty (Costa et al. 2001, Mittal and Kamakura 2001; Sanchez-Franco et al. 2009), but also between perceived quality and satisfaction (Forgas-Coll et al. 2013) in a service environment. Furthermore, a significant difference in the evaluation of service quality between male and female customers is observed, with female customers showing a tendency to rate service quality lower than males do (Lee et al. 2011; Snipes and Thomson 2006). From a tourism perspective, studies have been conducted on the influence of gender segmentation strategy (Lee et al. 2011); the effects of gender within a restaurant environment (Kim et al. 2009b) and the moderating effect of gender on airline website loyalty formation (Forgas-Coll et al. 2013). According to Kim et al. (2009b), gender is one of the most influential demographic variables associated with consumer purchase behaviour within a tourism-related environment. However, of all the identified studies, only the one conducted by Lee et al. (2011) support the moderating effect of gender and perceived service quality within a tourism environment, where a significant relationship is reported between men’s perceptions of service quality and women’s perceptions of service quality. All the other studies acknowledge the effect of gender, but only indicate the descriptive statistics. On the basis of the literature referenced it is clear that there is a literature gap regarding the moderating effect of gender in the prediction of tourist retention either via the SQSC or Satisfaction. Based on the above discussion, the following hypothesis is proposed:

H1.1

Gender group moderates the relationship between SQSC and Retention.

H1.2

Gender group moderates the relationship between Satisfaction and Retention.

2.2 Age

Customers’ age usually plays an important role in their choice to return to a specific service provider (Cohen et al. 2007; Crouch et al. 2009; Kim et al. 2009a). Age has been used as a market segmentation variable by ‘Dividing a market into different age and lifecycle groups’ (George 2011, p. 551). Therefore, age is defined as a generational market segment that represents a group of business tourists of a similar age who were born during the same time in history (as adapted from George 2011, p. 551; Wiersma 2009, p. 240). In a study on the tourism industry, Kim et al. (2009b) report that age is the most influential demographic variable associated with tourist purchase behaviour. It was further found that older tourists tend to show a higher repeat patronage than their younger counterparts (Kim et al. 2009b). Empirical evidence indicates that age is a moderator in the relationship between customer satisfaction and behavioural intention (Homburg and Giering 2001). Han and Ryu (2006) investigate the moderating effect of age in the relationship between tourist satisfaction and tourist repurchase intention, and have found that it is not significant. This finding should be further investigated in a business tourism context. No studies could be found on the moderating effect of age in the prediction of Retention. Based on the literature discussion, there is sufficient theoretical evidence to formulate the hypothesis:

H2.1

Age groups moderate the relationship between SQSC and Retention.

H2.2

Age groups moderate the relationship between Satisfaction and Retention.

2.3 Ethnic group

Many scholars have conducted research on ethnicity in tourism (Ishii 2012; Sabiote et al. 2013), but the moderating effect of ethnicity in the relationships between satisfaction, retention and service quality is limited. There is a close relationship between culture and ethnic group, since ethnic group represents the multiple traits of people of which culture can be one. Kong and Jogaratnam (2007, p. 278) state that ‘Different cultures imply different mental programming that governs activities, motivations, and values’. In general nationality has been used to measure ethnicity in customer studies (Tsoukatos and Rand 2007), but only in descriptive statistics to characterise the population. From a tourism perspective, different studies (Hsieh and Tsai 2009; Liu and Jang 2009; Pizam 1999; Sabiote et al. 2013) have identified the influence of ethnicity on satisfaction and intention to return. Results from these studies demonstrated that local residents and tourism employees perceive tourists’ behaviour to be affected by their national culture. More specifically the moderating effect of ethnicity on the relationship between satisfaction and perceived quality is significant (Hsieh and Tsai 2009; Sabiote et al. 2013). However, none of the consulted studies indicate the moderating effect of an ethnic group on the relationship between the SQSC and the prediction of Retention. Therefore, the hypothesis below will be tested:

H3.1

Ethnic groups moderate the relationship between SQSC and Retention.

H3.2

Ethnic groups moderate the relationship between Satisfaction and Retention.

2.4 Educational qualification

The impact of education is one of the most influential demographic variables associated with consumer purchase behaviour within a tourism-related environment (Kim et al. 2009b). Thus, consumers with formal education are likely to be better educated as consumers, and also likely to engage in a detailed information search process before making a purchase decision (Crouch et al. 2009). In tourism research, Forgas-Coll et al. (2013) as well as Pakdil and Aydin (2007) indicate that tourists’ education level tends to have a significant influence on their expectations of, and satisfaction with, an airline service. Hye-Rin et al. (2009) and Severt et al. (2007) are of the opinion that there is a significant relationship between educational activities, overall satisfaction, word-of-mouth (WOM) communication, and the intent to return to a specific conference. Therefore, Severt et al. (2007) support the moderating effect of education on satisfaction amongst convention attendees. In the airline industry the moderating effect of education in the relationship between perceived quality and satisfaction is supported (Forgas-Coll et al. 2013). However, none of these studies investigate the moderating effect of educational qualification in predicting Retention through the SQSC. This study also aims to address the suggestion made by Seo et al. (2008) to test education as a moderating variable in order to create a better understanding of customer retention, especially in a business tourism context. There is thus sufficient theoretical evidence to formulate the hypothesis below:

H4.1

Educational qualification categories moderate the relationship between SQSC and Retention.

H4.2

Educational qualification categories moderate the relationship between Satisfaction and Retention.

2.5 Province (geographical region) visited

Studies related to a government’s geographical area have been done (Ishikawa and Fukushige 2007). Results from the identified studies focus only on local governments and municipalities and not on provinces per se. Furthermore, only the descriptive results and weights allocated in the balanced scorecard (BSC) survey were considered by Chan (2004), while Sullivan and Estes (2007) recommend the modification of the SERVQUAL model, and warn that private-sector models are not designed for public decision-making. It is evident from these studies that information on the application of the BSC, service quality dimensions, customer satisfaction and customer retention is limited within a business tourism context. However, due to the high ranking of some of South Africa’s business tourist destinations, such as Gauteng and KwaZulu Natal, it is important to investigate whether a specific province’s SQSC has an influence on the prediction of Retention. Hence, to create a better understanding of customer retention, Seo et al. (2008) suggest the investigation of a destination’s geographical location as a dimension. Therefore, this study aims to investigate whether province most frequently visited (hereafter mostly referred to a province) moderates the relationship between the SQSC and Satisfaction, as well as between SQSC and Retention in a business tourism context. Thus, the following hypothesis is formulated:

H5.1

Provinces visited moderate the relationship between SQSC and Retention.

H5.2

Provinces visited moderate the relationship between Satisfaction and Retention.

Figure 1 is proposed as theoretical model for this study. This model is based on the review of the literature and the relationships between the constructs in the hypotheses with the moderating effects of gender (H1), age (H2), ethnic group (H3), educational qualification (H4) and province (H5), as shown below.