The Effect of Tour Leaders’ Emotional Intelligence on Tourists’ Consequences

Abstract

There has been little discussion on the impact of tour leaders’ emotional intelligence on tourists’ consequences although the study of emotional intelligence has gained attention in the tourism industry. Empirical data to assess emotional intelligence, affect, rapport, and customer satisfaction were collected from 54 tour leaders and 526 tour members participating in group package tours in Taiwan. Cross-level analysis with hierarchical linear models revealed that a tour leaders’ emotional intelligence could cultivate tour members’ positive affect and tour leader–member rapport, and lead to tourists’ satisfaction. Furthermore, the study discusses management implications and suggestions for future research.

Keywords

emotional intelligence positive affect rapport satisfaction tour leader

Introduction

Multiple encounters and considerable interaction with customers are distinctive characteristics of the tourism industry. It is especially critical for tour service providers to have the ability to manage, regulate, and control their own emotions to interact effectively with customers (T. Kim et al. 2012; Min 2014). Emotional intelligence is defined as the ability to monitor one’s own and others’ feelings and emotions, to discriminate among them, and to use this information to guide one’s thinking and actions (Salovey and Mayer 1990). It can be utilized in jobs that normally contain high levels of emotional demands and involve many interactions with customers (Carvelzani et al. 2003; Glomb, Kammeyer-Mueller, and Rotundo 2004; Min 2014). Undoubtedly, tour leaders are among those who need high emotional intelligence to both manage her or his own performance and regulate tour members’ emotions to most appropriately and effectively interact with them (Min 2012, 2014). Although empirical research about tour leaders’ emotional intelligence has emerged in recent years (e.g., Min 2012, 2014; Min and Peng 2012), most of these studies have focused on the impact of emotional intelligence on tour leaders. There is little evidence to support the relationship between tour leaders’ emotional intelligence and tour members’ emotions or service assessment (e.g., positive affect, rapport, and satisfaction with tour leader).

Individuals with high emotional intelligence are able to create pleasant feelings, as well as enhance a positive affective state (Goleman 1998; Mayer and Salovey 1997). According to the emotional contagion theory (Schoenewolf 1990), emotional states can be transmitted from one person to another, with the receiver catching the emotions that the sender displays. However, prior research has failed to examine whether the tour leaders’ emotional intelligence can influence tour members’ positive affect. Furthermore, service providers with good emotional intelligence are better at managing relationships, building networks, and getting positive responses from the customers with whom they interact (K. Kim, Cundiff, and Choi 2014; Min 2012). There is a lack of empirical evidence to show that the tour leaders’ emotional intelligence can induce tour members’ rapport perception and satisfaction.

Previous studies have been conducted on the effect of the service provider’s emotional displays on customers (Barger and Grandey 2006; Groth, Hennig-Thurau, and Walsh 2009; Hennig-Thurau et al. 2006). However, most empirical studies measured service providers’ emotion displays from the customer’s perspectives with only a few studies measuring from the service provider’s perspective (Van Dijk, Smith, and Cooper 2011). Furthermore, Morgeson and Hofmann (1999) indicated that the aggregation of variables from different levels may change the variables’ meaning as well as the meaning of the relationships. The complex phenomena occurring at differing levels can be comprehensively investigated by conducting a cross-level analysis (Mathieu and Taylor 2007). Cross-level analysis means investigating the influence of both lower- and higher-level influences on a lower-level outcome variable (Hofmann 1997). Therefore, this study proposes establishing a causal relationship from the aspects of both tour leader and tour members, and applies the hierarchical linear model (HLM) to discuss how a tour leader’s emotional intelligence induces tour members’ emotions and service assessment.

Furthermore, according to the affect-as-information framework (Schwarz and Clore 1996), people use their emotional states as their basis for making judgments. Previous studies show that customers’ emotions affect their satisfaction (Deng, Yeh, and Sung 2013; J.-S. C. Lin and Liang 2011), rapport perception (Hennig-Thurau et al. 2006), and behavior intentions (J.-S. C. Lin and Liang 2011). Thus, changes in customers’ emotions in the service context affect their assessments of the service.

The current research draws on literature to offer two objectives. The first objective of this study was to integrate variables on both levels of tour leader and tour member and to investigate whether the emotional intelligence of tour leaders exerts an effect on tour members’ positive affect, rapport perception, and their satisfaction with the tour leader. Based on the affect-as-information framework, the second objective of this study was to investigate the relationships among tour members’ positive affect, the rapport between a tour leader and tour members, and their satisfaction with the tour leader. Figure 1 illustrates the research framework.

Literature Review and Hypotheses Development

Tour Leader

Having the most distinctive role in the group package tour (GPT), the tour leader provides various services for the tour members and has the opportunity to develop long-term ties with them (Luoh and Tsaur 2014; Wang, Hsieh, and Chen 2002). In practice, the tour leader greets and meets tour members on arrival. After all the tour members have arrived at the destination, the local guide participates in the group by providing travel information and taking charge of local tours (Tsaur and Lin 2014). If no local guides have been arranged, tour leaders are called full-trip guides because they take on the dual responsibilities of running the entire tour as tour leader and local guide (J.-C. Chang 2009). In Taiwan, tour leaders of long-distance trips usually also serve as tour guides. Likewise, tour leaders of short-distance trips also need to handle some of the tour guides’ work (Luoh and Tsaur 2014). However, Min and Peng (2012) intentionally did not differentiate between tour leaders and full-trip guides when investigating the training needs of emotional intelligence for tour leaders. This may mean that regardless of the type of tour leader designation, it is necessary for these leaders to strengthen their emotional intelligence to be able to deal with various conditions and to interact appropriately and effectively with tour members. For the purpose of this study, the tour leader takes on both roles of leader and guide.

Because of the wide range of interpersonal interactions, tour leaders are required to perform emotional labor (Black and Weiler 2015; J.-Y. Wong and Wang 2009). Extensive research has been conducted on emotional labor with different types of tour leaders or guides, such as adventure guides (Sharpe 2005), heritage interpretive guides (Van Dijk and Kirk 2007), tour leaders of outbound tours (J.-Y. Wong and Wang 2009), and rafting guides (Carnicelli-Filho 2010). According to Joseph and Newman (2010), occupations with high emotional labor require more emotional intelligence than others. Carvelzani et al. (2003) conducted in-depth interviews with tour operators and found that those with high emotional intelligence have a better capacity to manage interpersonal relationship and interaction, and it also can help to assess and understand the tourists’ needs and expectations to organize a trip better suited to them and therefore provide greater satisfaction. Therefore, we consider that emotional intelligence may be an important ability for tour leaders.

There are some studies in tourism literature that recognize the emotional intelligence of tour leaders. For example, Min (2012) developed a short-form instrument to assess tour leaders’ emotional intelligence. Min and Peng (2012) adopted the TOPSIS approach to ranking emotional intelligence training needs for tour leaders. Min (2014) was the first one to test the causal relations of tour leaders’ emotional intelligence. She indicated that tour leaders with higher emotional intelligence were more aware of their emotions and had more effectively dealt with job stress and enhanced their quality of life. However, little research has been conducted on the influence of tour leaders’ emotional intelligence on tour members’ consequences.

Emotional Intelligence

In reviewing the literature related to emotional intelligence, there are some differences in the conceptualizations of emotional intelligence because of its varying definitions. However, although the definitions of emotional intelligence often varied for different researchers, they tend to be complementary rather than contradictory (Ciarrochi, Chan, and Caputi 2000). Among these studies, there are two general approaches to emotional intelligence in the literature: the ability model and the mixed-based model (Mayer, Salovey, and Caruso 2000). Salovey and Mayer (1990), the first scholars to propose the emotional intelligence concept, defined emotional intelligence as the ability that one uses to monitor and control her or his own and others’ emotions and feelings, discern these emotions, and apply them to guide an individual’s thinking and behavior. Mayer and Salovey (1997) conceptualized emotional intelligence as an individual’s ability encompassing four distinct dimensions: self-emotion appraisal, others’ emotion appraisal, regulation of emotion, and use of emotion. Individuals with high emotional intelligence are capable of understanding and expressing their own emotions, recognizing emotions in others, regulating affect, and using emotions to engage in adaptive behaviors (Salovey and Mayer 1990; C.-S. Wong and Law 2002).

In contrast, the mixed-base model was endorsed by Bar-On (1997) and Goleman (1998). Bar-On (1997) placed emotional intelligence in the context of personality theory. He conceptualized emotional intelligence as noncognitive capabilities, competencies, and skills that help an individual become more efficient in coping with environmental demands and pressures. Goleman (1998) indicated that emotional intelligence was a mixed intelligence consisting of cognitive ability and personality. Joseph and Newman (2010) adopted meta-analysis and found that mixed emotional intelligence offers stronger predictive power in job performance than the ability model of emotional intelligence. The mixed-based model treats emotional intelligence as an umbrella term for a broad array of traits and abilities; however, it suffers extreme theoretical underdevelopment (Joseph and Newman, 2010). Mayer, Salovey, and Caruso (2000) indicated that the individual aspects of the mixed-based model overlap considerably with the specific areas of the Big Five personality dimensions (e.g., Costa and McCrae 1985): extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience. The result of Joseph and Newman’s (2010) research shows high correlations between the mixed emotional intelligence and the Big Five personality traits. It appears to support critics’ claims that mixed emotional intelligence exhibits a great overlap with the Big Five personality traits. However, Law, Wong, and Song (2004) reviewed the definition of emotional intelligence and argued that emotional intelligence is conceptually distinct from personality.

Joseph and Newman (2010) indicated that ability-based emotional intelligence cannot predict job performance across all types of jobs, but it can positively predict performance for high emotional labor jobs. Furthermore, ability-based emotional intelligence was specified with strong theoretical propositions drawing upon decades of research in social and personality psychology. Therefore, this study is based on the ability model and defines tour leaders’ emotional intelligence as the ability of tour leaders to identify, regulate, and use their own and tour members’ emotions to enhance positive affective states and complete service activities.

In the tourism literature, a handful research has examined the relationship between employees’ emotional intelligence and their performance. It is already well known that emotional intelligence plays an important role in emotional labor (Jung and Yoon 2014; T. Kim et al. 2012; Yadisaputra 2015), service performance (Jung and Yoon 2014; T. Kim et al. 2012; Prentice and King 2011), creativity (Tsai and Lee 2014), and emotional dissonance and emotional effort (J.H. Lee and Ok 2012). Jung and Yoon (2012) also indicated that emotional intelligence can partially influence employees’ counterproductive work behaviors and organizational citizen behaviors. Furthermore, Sy and O’Hara (2006) indicated that food service managers with higher emotional intelligence can facilitate the performance of their employees by managing employees’ emotions. It implies that one’s emotional intelligence may influence the other’s affective state during the service encounter.

Impact of the Tour Leaders’ Emotional Intelligence on Tourists

In psychology, affect is often viewed as emotional states, which are the results of one’s assessment of the meaning, causes, and implication of a specific stimulus (Westbrook 1987). Affect can be categorized into positive affect and negative affect. However, positive affect and negative affect are distinct concepts (Russell and Carroll 1999). During a tour, positive affect appears far more frequently than negative affect (Nawijn 2011), and is related to outcome variables such as future intention (Jang et al. 2009) and satisfaction (Y. K. Lee, Back, and Kim 2009). Therefore, this study focuses on the exploration of positive affect. Positive affect is used to reflect a level of pleasurable engagement with an activity, such as happiness, joy, excitement, enthusiasm, and contentment (Clark, Watson, and Leeka 1989).

According to the emotional contagion theory, the expression of an individual’s positive affect can facilitate corresponding affective states in others (Hatfield, Cacioppo, and Rapson 1994). Previous studies indicated that employees’ positive emotional displays (e.g., smiling or extending greetings) could trigger customers’ positive affective states (Hennig-Thurau et al. 2006; Yuksel 2008). People with high emotional intelligence tend to behave in ways that encourage positive emotional experiences, so they attempt to express emotions that please others (Modassir and Singh 2008). To conduct a trip successfully, a tour leader who interacts with tour members needs to display various emotions to affect tour members’ emotions (J.-Y. Wong and Wang 2009). Thus, this study proposes that tour leaders with high emotional intelligence understand how to regulate their own emotions and use positive emotions to interact with tour members, which is beneficial for producing the positive affect (e.g., happiness and enthusiasm) in tour members.

Hypothesis 1: The tour leader’s emotional intelligence is positively associated with tour members’ positive affect.

Customer–employee rapport, characterized by a personal connection between two parties (Gremler and Gwinner 2000), refers to a customer’s perception of having an enjoyable interaction with a service provider. Enjoyable interaction and personal connection are two important aspects of rapport. In this, an enjoyable interaction is an affect-laden relationship produced between the customer and the service provider. In service relationships, the personal connection, derived from a sense of identity or mutual care, refers to a strong affiliation between customers and service providers. Customer–employee rapport is a cognitive assessment of an affective state after customers interact with employees. It can be cultivated over long periods, or formed through a single service interaction (Hennig-Thurau et al. 2006). Gremler and Gwinner (2000) indicated that customer–employee rapport has been identified as a salient issue because rapport exerts a strong influence on customer perceptions of service delivery and service organizations.

The keys to facilitate rapport include caring for customers’ needs and service results, as well as using humor to make customers feel at ease (Gremler and Gwinner 2000). Individuals with higher emotional intelligence are also sensitive to others’ emotions, and can understand their feelings and needs. This helps employees to connect with others and implement effective adaptive strategies to read and engage with customers (Prentice and King 2013). Meanwhile, individuals with higher emotional intelligence are generally more adept at regulating their own emotions and affecting others’ emotions to foster positive interactions and establish close relationships with others (T. Kim et al. 2012; Yadisaputra 2015). During the tour, tour leaders with higher emotional intelligence can better perceive and understand the emotions that tour members disclose in their speech and behaviors. A tour leader with higher emotional intelligence can use appropriate emotions and strategies to respond to tour members, understand their needs, and facilitate a feeling of enjoyment for them. On the basis of these findings, the following hypothesis is proposed:

Hypothesis 2: The tour leader’s emotional intelligence is positively associated with the tour members’ rapport with the tour leader.

Customer satisfaction is generally the consumers’ postpurchase evaluations of the respective product or service (Churchill and Surprenant 1982), or their cognitive assessment of an emotional experience (Hunt 1993). In tourism research, tourist satisfaction is often defined as the experience quality and the psychological outcome of the interaction between the tourist and the tour services at a tourist destination (Baker and Crompton 2000; Huang, Hsu, and Chan 2010). The tour leader’s service is the foundation of tourists’ overall travel satisfaction toward a packaged tour (Huang , Hsu, and Chan 2010). It is clear that the tour leader is a critical factor in affecting tourists’ satisfaction. Thus, this study focuses on the tour members’ satisfaction toward tour leaders.

Emotionally intelligent people can regulate their own emotions effectively, help others regulate their emotions successfully, and evoke positive responses from those with whom they interact (J. H. Lee and Ok 2012). Delcourt et al. (2013) suggested that once customers’ positive affective states are induced by a service employee, they are less critical and, thus, more satisfied with the service encounter. Moreover, employees with high levels of emotional intelligence spontaneously show positive emotions to customers (J. H. Lee and Ok 2012). Customers also hold expectations about service providers’ displays of positive emotions, such as smiling, that influence their levels of satisfaction (W.-C. Tsai 2001). Hence, displays of higher emotional intelligence by the service provider may lead to greater customer satisfaction with the services. Thus, this study proposes that it is easier for tour leaders with high emotional intelligence to manage and regulate their own emotions, use appropriate emotions to serve tour members, and respond to tour members’ requirements. Their performances motivate tour members to evaluate their satisfaction with the tour leaders positively. Thus, the following hypothesis is proposed:

Hypothesis 3: The tour leader’s emotional intelligence is positively associated with the tour members’ satisfaction with the tour leader.

Relationships among Tour Members’ Positive Affect, Tour Leader–Member Rapport, and Satisfaction with the Tour Leader

Rapport is the perception of customers’ own feelings and emotional states after they interact with service providers. Hennig-Thurau et al. (2006) suggested that customers influenced by a service provider’s positive emotions through the service interaction will enjoy the interaction with the service provider. This enjoyable interaction is one of the main characteristics of rapport (Gremler and Gwinner 2000). Previous studies showed that customers experiencing positive emotions in a service encounter are likely to return to enjoy the same positive experience (W.-C. Tsai and Huang 2002). In other words, when a customer experiences a positive emotion, she or he establishes a relationship with the service provider, an important factor in building rapport. Therefore, this study proposes that positive emotions experienced by tour members in the tour strengthen the rapport between the tour members and the tour leader.

Hypothesis 4: Tour members’ positive affect is positively associated with their rapport with the tour leader.

Schwarz and Clore (1996) considered that people often rely on their emotions as a source of information in judgment and decision making. In tourism settings, emotion is one of the core elements of customer satisfaction (Deng, Yeh, and Sung 2013; C.-K. Lee, Lee, and Lee 2005). Customers’ satisfaction toward services is strongly influenced by their own emotional states (Deng, Yeh, and Sung 2013). The more positive affect of tourists, the more they are satisfied (C.-K. Lee, Lee, and Lee 2005). Thus, this study proposes that a tour member in a positive affective state may attribute her or his state to the success of the service interaction and, consequently, may evaluate the tour leader positively.

Hypothesis 5: Tour members’ positive affect is positively associated with their satisfaction with the tour leader.

In the service industry, customers’ evaluation of the service experience is largely determined by the interaction between service providers and customers (W. Kim, Ok, and Gwinner 2010). Empirical research indicates that rapport between service providers and customers greatly affects customer satisfaction (Gremler and Gwinner 2000; W. Kim and Ok 2010). Furthermore, customer–employee rapport during the interaction with the service provider provides the customers with enjoyment and comfort (Gremler and Gwinner 2000). Tour members’ satisfaction is perceived as the level of pleasure or happiness that they feel when participating in a package tour (Song and Cheung 2010). Therefore, this study expects that rapport exists between tour members and their tour leader, and tour members’ perception of happiness and enjoyment during this interaction leads to their satisfaction with the tour leader. This study subsequently proposes the sixth hypothesis:

Hypothesis 6: Tour members’ rapport is positively associated with their satisfaction with the tour leader.

Research Methodology

Survey Instruments

Because the measurement scales were developed in English and the surveys were administered in Chinese, back-translation was adopted to ensure accuracy of translation (Brislin 1970). A 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) was used for all of the measures. Two experts, one an academic and one a practitioner in the tourism field, reviewed the instrument for content validity (Hair et al. 2010) and verified that the items were related to the GPT context. All items (including means, standard deviation, skewness, and kurtosis) are listed in the appendix.

The 16-item emotional intelligence scale from C.-S. Wong and Law (2002) was adapted to measure tour leaders’ emotional intelligence. Based on Mayer and Salovey’s (1997) definition of emotional intelligence, C.-S. Wong and Law’s (2002) scale consists of four dimensions: others’ emotion appraisal, use of emotion, self-emotion appraisal, and regulation of emotion. Many researchers have used this scale across various cultures and diverse ethnic and gender groups, thus producing greater reliability and validity (Jeon 2016; Perez, Petrides, and Furham 2005; Law, Wong, and Song 2004). In our study, the Cronbach’s alpha for this scale was 0.968. The three items with highest scores are as follows: (1) I am sensitive to the feelings and emotions of tour members (4.11); (2) When I am leading a tour, I always tell myself I am a competent tour leader (4.11); (3) When I’m leading a tour, I have a good understanding of my own emotions (4.11). High-score items reflect that the tour leader is good at observing tour members’ emotions and emotional self-awareness.

With regard to tour members’ positive affect, we adapted a positive affect scale (four items) from Hennig-Thurau et al. (2006): their scale is used to measure postencounter customer positive affect. In addition, we added three items: (1) During the tour, I feel pleasure; (2) During the tour, I feel relaxed; and (3) During the tour, I feel entertained. The Cronbach’s alpha for this scale was 0.960. The three items with highest scores were the following: (1) During the tour, I feel pleasure (4.00); (2) During the tour, I feel elated (3.98); and (3) During the tour, I feel relaxed (3.98). These items reflect that under the leadership of their tour leader, tour members were pleasurably engaged with the tour.

As for tour leader–member rapport, this study adapted the 11-item rapport measure scale developed by Gremler and Gwinner (2000). This scale is used across various customer-to-employee relationships (Hwang, Kim, and Hyun 2013; W. Kim, Ok, and Gwinner 2010; Tsaur, Dai, and Liu 2015); thus, this scale is applicable in this study. The rapport includes two dimensions of enjoyable interaction and personal connection. The Cronbach’s alpha for the measure of tour leader–member rapport was 0.960. The three items with the highest scores were as follows: (1) This tour leader has a good sense of humor (3.92); (2) I am comfortable interacting with this tour leader (3.92); and (3) This tour leader creates a feeling of “warmth” in our relationship (3.89). These items reflect that under the leadership of their tour leader, tour members were pleasurably engaged with the tour. These three items were all used to measure the dimension of enjoyable interaction. This clearly shows that the performance of the tour leader influences the tour members’ perception of their interaction with the tour leader.

The three-item satisfaction from the salesperson scale from Crosby, Evans, and Cowles (1990) was adapted and modified to measure satisfaction with the tour leader. They consider satisfaction to be an emotional state that occurs in response to an evaluation of the interaction experiences between the customer and salesperson. The concept is similar to tour members’ satisfaction toward tour leaders in our study. The scores of three items are all higher than 4. This reflects that the performance of tour leaders had achieved or exceeded tour members’ expectations. The Cronbach’s alpha for this scale was 0.945.

Previous research studies noted that emotional contagion may have potential effects on the perception of customer service quality (e.g., Hennig-Thurau et al. 2006; Pugh 2001). Therefore, this study uses emotional contagion as a control variable to reduce the potential confounding effects on tour member variables and maximize statistical power. The four-item emotional contagion scale from Omdahl and O’Donnel (1999) was adapted to measure tour members’ emotional contagion. This scale has been widely adopted and has been suggested as a valid scale measuring emotional contagion with good reliability (García-Izquierdo, Moreno, and García-Izquierdo 2010; Omdahl and O’Donnell 1999). The highest item scores of this scale are as follows: (1) I become nervous if others around me seem to be nervous (3.30); (2) I tend to lose control when I am bringing bad news to people (3.21). This reflects that tour members’ emotions are not easily affected by others. Cronbach’s alpha for this scale was 0.914.

Common Method Variance

To mitigate the concern of common method bias, survey respondents did not know what was being tested, and the name of variables and dimensions were excluded in the survey (Peng, Gao, and Lin 2006). Furthermore, the survey was conducted in two phases for a tour to minimize the possible threat of common method bias (Podsakoff et al. 2003). In the first phase of a survey, a tour leader filled out her or his emotional intelligence questionnaire on the first day of the tour. In the second phase, 10 tour members were invited to assess positive affect, tour leader–member rapport, and satisfaction with the tour leader on the last day of the tour. Completing the questionnaires at different time points reduced the possibility of the tour leader and tour members knowing what was being tested, and prevented response bias.

To assess the possible problem of common method variance, Harman’s one-factor test was adopted for all the self-reported variables (Podsakoff and Organ 1986). Principal component factor analysis was conducted on question items for tour member variables: positive affect, tour leader–member rapport, satisfaction with the tour leader, and emotional contagion. The result of the factor analysis indicated three factors with eigenvalues greater than 1, explaining 76.21% of the total variance. Of the three factors extracted, factor 1 accounted for only 33.40% (less than 50%) of the total variance, which did not explain most of the variance (Podsakoff and Organ 1986). Therefore, the common method bias was not a major concern in the present study.

Participants and Procedures

The participants were tour leaders and tour members from various outbound GPTs in Taiwan. This study looked for volunteer tour members from PTT (the ID of the creator) to assist the survey. PTT is the most popular bulletin board system (BBS) in Taiwan. It hosts more than 20,000 discussion boards and has more than 1,000,000 registered users. On average, more than 240,000 individuals visit the site every day. PTT, with users of all ages, is the most influential online community in Taiwan. First, the researcher obtained permission from the PPT administrators to recruit volunteer tour members who would be participating in multiday overseas tours in the next few weeks. If the tour members agreed to assist in this research, we contacted them and informed them of the procedure for the survey by visiting them in person or video-phone calling. Finally, we left/sent questionnaires (1 tour leader questionnaire, 10 tour member questionnaires) and stamped self-addressed envelopes to the volunteer tour members. We returned to collect the surveys after their tours, or instructed volunteer tour members to seal their completed questionnaires in self-addressed stamped envelopes and send them directly to us. Every volunteer tour member was given a gift after completing the survey. However, the nonprobability sampling was used for this study; therefore, no assessment of sampling error was possible.

In total, we distributed 750 pairs of questionnaires (75 tour leaders and 750 tour members). We excluded incomplete questionnaires with any missing data, and had a total of 526 valid tour leader–tour member dyads (54 tour leaders and 526 tour members), yielding a response rate of 70.1%. The participating group size ranged from 7 to 10 members (M = 9.74 members).

Of the tour leaders, 53.7% were female, and almost a third of the respondents were between 41 and 50 years of age (31.5%). More than half (68.5%) of the tour leaders had a bachelor’s degree. The length of service for the majority (37%) of tour leaders was 6–10 years.

Of the tour members, 53.8% were female, and more than a third of the members were between 31 and 40 years of age (37.3%). More than half of the tour members (66%) had college degrees, and business industry jobs were the most highly represented occupation (23.6%). Close to half (40.3%) of the members had 5–10 travel days; more than a fourth of (25.3%) of the tour destinations was Europe. More than half of the tours (56.1%) had between 15 and 30 participants.

Results

Preliminary Analyses

Table 1 presents the means, standard deviations, and correlations among the variables. Before testing the hypothesized model, confirmatory factor analyses (CFAs) were conducted to test the measurement models. First, we adopted a bootstrap approach to test the CFA of the tour leaders’ emotional intelligence. Mooney and Duval (1993) noted that bootstrapped approximations of parameter estimates and confidence intervals are considered relatively high quality when n > 30. That is, n = 30 is recognized as a reasonable minimum sample size for bootstrapped confidence intervals. The model-fit measures of tour leaders’ emotional intelligence were used to assess the emotional intelligence model’s overall goodness of fit: the result shows that χ²/df = 1.78 (value between 1 and 3 is reasonable), goodness-of-fit index (GFI) = 0.91 > 0.9, normed fit index (NFI) = 0.92 > 0.9, adjusted goodness-of-fit index (AGFI) = 0.96 > 0.9, standardized root mean square residual (SRMR) = 0.05 < 0.08, root mean square error of approximation (RMSEA) = 0.07 with a value between 0.05 and 0.08 being reasonable. This showed that the measurement model of emotional intelligence exhibited a close fit with the collected data. Convergent validity of scale items was estimated using reliability, composite reliability, and average variance extracted (Fornell and Larcker 1981). The standardized factor loadings for the scale items exceeded the minimum loading criterion of 0.50 (0.79–0.90), and the composite reliabilities of all factors also exceeded the recommended 0.70 level (0.91–0.94) (Hair et al. 2010). In addition, the average variance-extracted values were above the threshold value of 0.50 (0.72–0.79). Therefore, emotional intelligence scales used in this study had reasonable degrees of reliability and validity.

Table 1.

Descriptive Statistics among Variables.

Variables	M	SD	1	2	3	4
Tour leader level
Emotional intelligence	3.99	0.74
Tour member level
1. Positive affect	3.94	0.85	–
2. Tour leader–member rapport	3.77	0.73	0.85^**	–
3. Satisfaction with the tour leader	4.02	0.86	0.84^**	0.88^**	–
4. Emotional contagion	3.21	0.99	0.25^*	0.24^*	0.24^*	–

Note: For tour member level, n = 526; tour leader level, n = 54. ^*p < 0.05; ^**p < 0.01.

Furthermore, we used LISREL 8.71 to test the measurement model of tourists’ outcomes: the result also exhibited a close fit (χ²/df = 1.63, GFI = 0.94, NFI = 0.99, AGFI = 0.92, SRMR = 0.02, RMSEA = 0.06). The standardized factor loadings for all scale items were between 0.80 and 0.93, and the composite reliabilities of all factors were between 0.91 and 0.96. The average variance-extracted values were between 0.72 and 0.84. All scales of tour members’ outcomes used in this study also had reasonable reliability and validity.

Discriminant validity is used to measure the relationship between variables. CFA was adopted to assess the discriminant validity of the four constructs: positive affect, tour leader–member rapport, satisfaction with the tour leader, and emotional contagion. The results of discriminant validity are presented in Table 2. The four-factor model adequately fits the data, χ²(98, n = 526) = 267.63 (CFI = 0.99; GFI = 0.94; RMSEA = 0.06), meeting the criteria suggested by scholars (Jöreskog and Sörbom 1993). Drawing on the methods suggested by researchers (Farh, Hackett, and Liang 2007), we tested three alternative models and compared them with the baseline (four-factor) model. The results indicated that the four-factor model yielded a more adequate overall fit than did the three-, two-, and one-factor models. The results also indicated that the four variables were distinct constructs.

Table 2.

Discriminant Validity of Tour Members’ Outcomes.

Model		χ²	df	∆χ²	CFI	GFI	RMSEA
Baseline model	4 factors	267.63	98	–	0.99	0.94	0.06
Model 1	3 factors: PA and RA were combined into 1 factor	517	101	249.37^***	0.98	0.89	0.09
Model 2	2 factors: PA, RA, and SA were combined into 1 factor	955.25	103	687.62^***	0.97	0.81	0.13
Model 3	1 factor: All variables were combined into 1 factor	2636.57	104	2368.94^***	0.90	0.61	0.21

Note: PA = positive affect; RA = tour leader–member rapport; SA = satisfaction with the tour leader; CFI = comparative fit index; GFI = goodness-of-fit index; RMSEA = root mean square error of approximation. n = 526. ^***p < 0.001.

Test of the Hypotheses

We proposed a multilevel model that would show that tour leader–level emotional intelligence has an effect on tour members’ positive affect, tour leader–member rapport, and satisfaction with the tour leader. Therefore, HLM was conducted to test the hypotheses. Before doing so, we needed to investigate the tour member–level properties of the measurement in this study and the appropriateness of the data aggregation. We computed the r_wg to assess within-group agreement, confirming that members of a group tended to agree in their assessments of a given group member’s positive affect, tour leader–member rapport, and satisfaction with the tour leader, with the mean values of 0.935, 0.958, and 0.963, respectively. The r_wg values exceeded the acceptable level of 0.7 (Hofmann 1997). Furthermore, this study calculated the intraclass correlation (ICC (1)) and reliability of the group mean (ICC (2)): 0.485 and 0.514 for positive affect, 0.361 and 0.638 for leader–member rapport, and 0.312 and 0.687 for satisfaction with the tour leader, respectively. The ICC (1) and ICC (2) values also achieved the acceptable level (ICC (1) > 0.12, ICC (2) > 0.7) (Hofmann 1997). These figures indicated that variations of tour members’ perceptions were due to the differences in the groups and signified the need to use cross-level analysis. All predictors were grand-mean centered in this study to avoid the problem of multicollinearity and provide better estimates and interpretability with the models (Hofmann 1997).

Hypotheses 1, 2, and 3 suggest a main effect of tour leaders’ emotional intelligence on the tour members’ positive affect, tour members’ tour leader–member rapport, and satisfaction with the tour leader, respectively. Models 3 and 4 in Table 3 show that tour leaders’ emotional intelligence was significantly and positively related to tour members’ positive affect (γ = 0.579, p < 0.01) and tour leader–member rapport (γ = 0.550, p < 0.01). Thus, hypotheses 1 and 2 were supported. Model 3 in Table 4 also provided significant evidence of the positive relationship between tour leaders’ emotional intelligence and tour members’ satisfaction with the tour leader (γ = 0.413, p < 0.01), which supported hypothesis 3.

Table 3.

HLM Results for Positive Affect and Tour Leader–Member Rapport.

Variable	Tour Leader–Member Rapport			Positive Affect
Variable	Null Model	Model 2	Model 3	Model 4
Tour member level
Intercept	3.768***	3.780***	3.769***	3.942***
Emotional contagion		0.142*	0.154*	0.178*
Positive affect		0.493***	0.451***
Tour leader level
Emotional intelligence			0.550***	0.579***
R ²		0.580	0.323	0.313

Note: HLM = hierarchical linear model. For tour member level, N = 526; tour leader level, N = 54. *p < .05; **p < 0.01; ***p < 0.001.

Table 4.

HLM Results for Satisfaction with Tour Leader.

Variable	Satisfaction with Tour Leader
Variable	Null Model	Model 2	Model 3
Tour member level
Intercept	3.966***	3.966***	3.97***
Emotional contagion		0.150*	0.152*
Positive affect		0.194***	0.199***
Tour leader–member rapport		0.427***	0.428***
Tour leader level
Emotional intelligence			0.413***
R ²		0.548	0.431

HLM = hierarchical linear model. For tour member level, N = 526; tour leader level, N = 54. *p < .05; **p < 0.01; ***p < 0.001.

Hypotheses 4 and 5 proposed that tour members’ positive affect would affect their tour leader–member rapport and satisfaction with the tour leader. The results from Model 2 in Tables 3 and 4 showed that tour members’ positive affect was significantly associated with tour leader–member rapport (γ = 0.493, p < 0.01) and satisfaction with the tour leader (γ = 0.194, p < 0.01). Thus, hypotheses 4 and 5 were supported. Finally, hypothesis 6 predicted that tour leader–member rapport and satisfaction with the tour leader have a positive relationship. Model 2 in Table 3 further demonstrated that tour members’ tour leader–member rapport was significantly related to their satisfaction with the tour leader (γ = 0.428, p < 0.01). Hence, hypothesis 6 was supported.

Discussion and Implications

This research reveals the relationship among the tour leaders’ emotional intelligence and tour members’ positive affect, tour leader–member rapport, and tour members’ satisfaction with tour leader. The results indicate that the leaders’ emotional intelligence has a strong positive effect on tour members’ positive affect, which supports the concept of the emotional contagion theory (Schoenewolf 1990). The theory suggests that an individual’s positive emotions can elicit emotional states of others. A tour leader with higher emotional intelligence could be more adept at exhibiting a positive affective state throughout the entire tour and expressing positive emotions to tour members. Accordingly, these behaviors and performances elicit tour members’ positive emotional states. Moreover, the results also show that the tour leaders’ emotional intelligence directly and positively influence tour members’ rapport. The findings support previous studies (Law, Wong, and Song 2004; C.-S. Wong and Law 2002), indicating that individuals with higher emotional intelligence are adept at reading others’ emotions, which helps develop positive social interactions and establish close relationships with others. This study suggests that a tour leader with higher emotional intelligence could be more sensitive to tour members’ emotions and able to use their emotions as important and useful information to manage the service interaction. When tour members display negative emotions, the tour leader who perceives and understands them takes steps to create a positive climate and interact smoothly. Accordingly, enjoyable interactions between the tour leader and tour members result in tour members perceiving positive tour leader–member rapport.

In addition, this study confirms that tour leaders’ emotional intelligence led to higher levels of tour members’ satisfaction with the tour leader, supporting the findings of previous studies (Kernbach and Schutte 2005). The findings indicated that higher emotional intelligence displayed by the service provider led to greater customer satisfaction. This study suggests that a tour leader with higher emotional intelligence could be more adept at using his or her emotions to facilitate service performance and respond better to tour members in the GPT.

Van Dijk, Smith, and Cooper’s (2011) research based on zoo guides and zoo visitors found no relationship between the zoo guide’s self-reported emotional labor and visitor perceptions of emotional labor. However, our study demonstrates that the tour leaders’ emotional intelligence is positively related to the tour members’ consequences. Emotional labor is the management of feelings to create a publicly observable facial and bodily display (Hochschild 1983), and is a form of self-emotion regulation. However, emotional intelligence is also an ability to manage self-emotion. More importantly, people with higher emotional intelligence know how to understand and regulate others’ feelings and emotions. Therefore, in this study, the tour leaders’ emotional intelligence is related to tour member’s consequences.

The findings of this study provide support for the affect-as-information framework (Schwarz and Clore 1996) that tour members’ positive affect leads to an increase in tour leader–member rapport and their satisfaction with the tour leader. A tour member in a positive affective state obviously enjoys the interaction with the tour leader, thus leading to a higher level of tour leader–member rapport. Similarly, an increase in a tour member’s positive affect also influences her or his satisfaction with the tour leader. A tour member in a positive affective state attributes his or her state to the success of the service interaction and, consequently, evaluates the tour leader positively. In addition, this study also finds that tour leader–member rapport is a driver of tourists’ satisfaction with their tour leader. The result suggests that more enjoyable contacts lead to an increase in the satisfaction with the tour leader. The evaluation of satisfaction with the tour leader is highly determined by the interactions between the tour leader and tour members. This study concurred with the findings of previous scholars who investigated customer emotions (Deng, Yeh, and Sung 2013; C.-K. Lee, Lee, and Lee 2005) and showed that emotion plays a substantial role in the evaluations of satisfaction with the tour leader.

The underlying premises of emotional intelligence indicate that its application can manage both one’s own and others’ emotions. Although much research has been conducted to understand the relationships between service providers’ emotional intelligence and their performance (Jung and Yoon 2012; T. Kim et al. 2012; C.-T. Tsai and Lee 2014), the present study contributes to the knowledge base relating to the effect of a tour leader’s emotional intelligence on her or his tour members by taking a dyadic perspective to test tour members’ emotions and service assessment through the theoretical lens of emotional contagion. As such, this study also adds to the emotional contagion literature by illustrating the process of emotional transmission in motivating similar emotion, particularly in the context of GPT.

Methodological Implications

Past research has used a customer-level (signal-level) model to examine how first-line employee’s emotional labor connects to customer outcomes (e.g., Hennig-Thurau et al. 2006), but this may change the meaning of the variables and undermine the true relationship between them (Morgeson and Hofmann 1999; I. A. Wong 2015). This study overcame this limitation by using HLM and systematically integrated the two levels of tour leader and tour member to develop a holistic framework, identifying and proving the key roles that stimulate tour members’ emotions or service assessment.

Ignoring nesting in a single-level analysis may cause erroneous estimates (e.g., type I errors, indicating overly lax statistical decisions) and inappropriate conclusions (C.-C. Lin and Peng 2006). However, HLM makes it possible for researchers to perceive that individuals are subject to clustering effects at higher levels, such as the tour leader. Moreover, the HLM avoids the ecological fallacy of making inferences about a lower level of analysis based on the characteristics of a higher level of analysis, while also avoiding the individualistic fallacy of making inferences about a higher level of analysis based on the characteristics of a lower level of analysis (K.-C. Chang 2016; C.-C. Lin and Peng 2006). This methodological advancement is important to the research of social behaviors as requirements for analysis on multiple levels of variables often exist. HLM can greatly improve the accuracy of the analysis and the reliability of the results. In a more general sense, this study resolves a common limitation of emotion research in tourism area.

Implications for Practice

This study finds that tour leaders’ emotional intelligence increases tour members’ positive affect, tour leader–member rapport, and satisfaction with the tour leader. The results may improve managers’ understanding of the importance of tour leaders’ emotional intelligence. Specifically, this study has two main implications for travel managers. First, emotional intelligence is known to affect a service provider’s performance (Prentice and King 2011), creativity (C.-T. Tsai and Lee 2014), and job satisfaction (Langhorn 2004), and the results of this study complement these findings. Therefore, by hiring tour leaders with higher emotional intelligence and encouraging tour leaders to develop emotional intelligence behaviors, travel managers can facilitate the development of tour members’ positive affect, rapport, and satisfaction.

Second, it is critical for tour leaders to develop their abilities to regulate emotions, express emotions, and understand the emotions of the tour members with whom they interact. Consequently, travel managers should assist the progress of tour leaders’ emotional intelligence to build effective relationships with tour members. Previous research has suggested that emotional intelligence skills can be learned, improved, and developed (Min 2012). Thus, travel managers may need to assess the tour leaders’ levels of emotional intelligence by using the Mayer–Salovey–Caruso emotional intelligence test (MSCEIT). MSCEIT is the most widely used measure of emotional intelligence. Once this is accomplished, travel managers can plan comprehensive trainings on emotional intelligence to improve tour leaders’ self-understandings and effective interactions with tour members. The six emotional intelligence skills ranked in Min’s (2012) study include motivating by purpose and emotion, establishing personal goals, using effective strategies in solving problems, communicating one’s thoughts and feelings to others, dealing with stressful circumstances, and recognizing the need to change. These are helpful and practical emotional intelligence skills that enable tour leaders to most appropriately and effectively interact with tour members.

Limitations and Further Research

Although our findings expand the extant knowledge on emotional intelligence in tour leader–member service encounters, we recognize limitations that must be taken into account when generalizing our results. First, we measured tour members’ positive affect and tour leader–member rapport, and tourists’ satisfaction in the second phase of the questionnaire survey. This research design limits any inference of causality among the study variables, thus making it impossible to provide irrefutable evidence of causation. A second limitation is that this study instructed the volunteer tour members to hand out the questionnaires to other members; dissatisfied tour members may have refused to oblige and caused the distribution of tour members’ evaluations to be biased to a certain extent. This could result in an overrepresentation of more satisfied tour members. This sample bias could lead to range restrictions (where the range over which variables vary is artificially limited) in some of our variables. However, a range restriction often has underestimated relationships (Nunnally 1978). In this study, the coefficients would be rather conservative estimates, making the results even more compelling.

A third limitation is that this study focuses on positive emotions because they are most relevant in the process of tour service delivery. However, similar ripple effects may occur for negative affect. For example, anger and unhappy displays by tour members may negatively affect their service experiences. Further research could address this issue by testing whether effects similar to those we found apply equally to the flow of negative emotions in the process of tour service delivery. Future research could also examine the influence of tour leader–level variables (such as passion for work) on affective processes in the tour service delivery. In addition, tour member variables such as citizenship behaviors of tour members (such as discretionary and altruistic behaviors demonstrated by tour members during GPTs that sustain effective functioning of the tour) would be interesting to study. Finally, the differentiated attributes of GPTs, such as the type of tour (mass tourism vs. culture tourism), travel days (one-day tour vs. multiday tour), and the number of tour members, may influence the relationship between tour leader and tour member. Future research could compare the effect of the tour leaders’ emotional intelligence on tour members in GPTs with differentiated attributes.

Furthermore, we confirm the causal relationship between the tour leaders’ emotional intelligence and tour members’ outcomes. Not only does the tour leader have considerable interactions with tour members in multiday overseas tours, but he or she also needs to deal with the requirements of different tour members. Therefore, it is easier for the tour members to observe and perceive the tour leader’s emotional intelligence. This study suggests that some jobs such as flight attendants and first-line employees of hotels and restaurants require high emotional intelligence. However, their interaction may be less frequent than that of a tour leader. Thus, it is necessary to confirm the relationship to other high–emotional labor jobs.

Footnotes

Appendix

Survey Items and Descriptive Analysis.

Factors/Items	Mean	SD	Skewness	Kurtosis
Emotional intelligence
Others’ emotion appraisal
I always know tour members’ emotions from their behaviors.	4.07	0.89	−1.66	4.13
I am a good observer of tour members’ emotions.	4.02	0.94	−1.31	2.39
I am sensitive to the feelings and emotions of tour members.	4.11	0.93	−1.57	3.37
I have a good understanding of the emotions of tour members around me.	4.00	0.93	−1.31	2.49
Use of emotion
When I’m leading a tour, I always set job goals for myself and then try my best to achieve them.	3.93	0.82	−1.77	5.02
When I’m leading a tour, I always tell myself I am a competent tour leader	4.11	0.95	−1.48	2.89
When I’m leading a tour, I am a self-motivated person.	3.93	0.91	−1.26	2.55
When I’m leading a tour, I always encourage myself to try my best.	3.94	0.94	−1.16	2.00
Self-emotion appraisal
When I’m leading a tour, I have a good sense of why I have certain feelings most of the time.	3.93	0.92	−1.32	2.60
When I’m leading a tour, I have a good understanding of my own emotions.	4.11	0.95	−1.23	2.08
When I’m leading a tour, I really understand what I feel.	3.93	0.88	−1.31	2.88
When I’m leading a tour, I always know whether I am happy or not.	3.94	0.91	−1.48	3.22
Regulation of emotion
When I’m leading a tour, I am able to control my temper and handle difficulties rationally.	4.07	0.91	−1.56	3.54
When I’m leading a tour, I am quite capable of controlling my own emotions.	3.91	0.85	−1.53	3.82
When I’m leading a tour, I can always calm down quickly when I am very angry.	3.98	0.88	−1.52	3.64
When I’m leading a tour, I have good control of my own emotions.	3.89	0.84	−1.57	4.07
Positive affect
During the tour, I feel elated.	3.98	0.94	−1.44	2.66
During the tour, I feel happy.	3.90	0.95	−1.26	2.10
During the tour, I feel enthusiastic.	3.91	0.96	−1.23	1.95
During the tour, I feel excited.	3.95	0.97	−1.26	1.96
During the tour, I feel pleasure.	4.00	0.93	−1.53	3.04
During the tour, I feel relaxed.	3.98	0.94	−1.44	2.67
During the tour, I feel entertained.	3.92	0.93	−1.39	2.58

Tour leader–member rapport
Enjoyable interaction
I enjoy interacting with this tour leader.	3.84	0.90	−0.93	1.36
This tour leader creates a feeling of “warmth” in our relationship.	3.89	0.87	−1.15	2.13
This tour leader relates well to me.	3.85	0.89	−0.98	1.56
I have a harmonious relationship with this tour leader.	3.88	0.87	−1.12	2.02
This tour leader has a good sense of humor.	3.92	0.89	−1.10	1.83
I am comfortable interacting with this tour leader.	3.92	0.88	−1.18	2.15
Personal connection
I feel like there is a “bond” between this tour leader and myself.	3.61	0.84	−0.70	1.28
I look forward to seeing this tour leader when I participate in package tours.	3.74	0.87	−0.81	1.28
I strongly care about this tour leader.	3.59	0.84	−0.63	1.17
This tour leader has taken a personal interest in me.	3.59	0.85	−0.57	1.03
I have a close relationship with this tour leader.	3.60	0.84	−0.64	1.16
Satisfaction with tour leader
I am satisfied with the tour leader’s performance.	4.03	0.89	−1.73	4.07
I am pleased with the tour leader’s performance.	4.04	0.91	−1.63	3.55
I am favorable to the tour leader’s performance.	4.00	0.93	−1.47	2.87
Emotional contagion
I often find that I can remain cool in spite of the excitement around me. (R)	2.84	1.01	0.15	1.94
I am able to remain calm even though those around me worry. (R)	2.92	0.87	0.13	1.53
I tend to lose control when I am bringing bad news to people.	3.21	1.10	0.09	1.73
I become nervous if others around me seem to be nervous.	3.30	1.12	0.22	1.01

Note: (R) = reversed items.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Sheng-Hshiung Tsaur Professor, Department of Marketing and Tourism Management, National Chiayi University, Chiayi City, Taiwan. He has published over 40 refereed papers in the areas of tourism, recreation, and hospitality management.

Pi-Shen Ku Ph. D. Candidate, Graduate Institute of Recreation, Tourism and Hospitality Management, National Chiayi University, Chiayi, Taiwan; Special Program Assistant professor, Department of Tourism, Ming Chuan University, Taoyuan, Taiwan. Her research interests include tourism management and hospitality education.

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