Cocreation of the hospitality brand experience: A triadic interaction model

Abstract

Although dyadic interactions among customers have widely been acknowledged to impact customer experience, the interdependence between customers and the service provider may form a symbiotic force that attenuates how an experience is cocreated. This study focuses on triadic interactions among casino patrons by modeling employee-to-customer (E2C) interactions as a boundary condition that may moderate the effect of customer-to-customer interactions (C2C) and customer-to-companion (Cu2Co) interaction quality on brand experience. Data were collected among patrons from 30 casino establishments using a two-step sampling approach. Findings suggest that E2C interaction moderates the relationship between customer interactions and the brand experience, such that the C2C interaction quality effect is more salient under the high E2C interaction condition. Implications for both practice and theory as well as limitations and future directions are further discussed.

Keywords

Brand experience casino customer interactions employee-to-customer interaction triadic interactions value cocreation

Introduction

Service firms today are compelled to meticulously formulate their offerings while attempting to engage their customers by staging memorable experiences (Pine and Gilmore, 1998; Wong, 2013). To this end, there is an increasing need to understand how customer experience can be improved. Meanwhile, the gaming industry in Asia, such as that of Macau, has developed rapidly over the years. For example, casinos in Macau compete intensely on a diverse assortment of offerings in order to attract, please, and retain valuable players. Such a practice is particularly prevalent for its premium gaming market—a market that makes up a great portion of the industry’s revenue (Gaming Inspection and Coordination Bureau, 2019). As a result, while complimentary services (e.g., free drinks, food, and shuttle services) are still considered important to casino players, they are becoming less influential to sustain one’s positive perceptions of the tourist experience in such a competitive environment (Prentice and Wong, 2015). Furthermore, given today’s competitive experience-driven services (e.g., gaming) business, both scholars and decision makers have recognized that the service encounter is undeniably the fundamental component in delivering a memorable experience, which can serve as an advantage for firms (Lai et al., 2014; Prentice et al., 2017). Yet, questions remain as to how a brand’s experience can best be manifested and attained in the service encounter. This study seeks to answer this question through an investigation of interaction qualities (or interactions, for short, hereafter) among customers and employees in the casino setting.

Brand experience is conceptualized as a moment of truth when customers’ responses are evoked by brand-related stimuli that differentiate one brand from another (King, 2017). Although brand experience can be derived from marketing communications and brand design, the service encounter is also a rich source for such an experience (Ahn et al., 2019; Wu and Cheng, 2019). The service encounter encompasses a constellation of service elements that consumers interact with at various consumption stages including interactions with employees, other customers, and companions (Patrício et al., 2011). Yet, in comparison with other customers who are strangers, companions can be family members, friends, or commercial acquaintances who have an established relationship with the focal customer. In many cases, such customer interactions are considered as a key component of the service encounter because, for example, gamblers might share their gambling experiences or tactics with others, which implies putting more emphasis on gambling pleasure and care during a gambler’s journey (Lam, 2007). Yet, although the literature has acknowledged the role of customer-to-customer (C2C) interaction in value cocreation, several limitations remain including a lack of research on (1) customer-to-companion (Cu2Co) interactions, (2) an interplay among E2C, C2C, and Cu2Co, and (3) a possible moderating role of E2C in interaction qualities among customers.

It is important to note that research to date has accentuated empirical evidence showing how human interaction could ultimately nurture customer satisfaction and delightful experience. For example, Chang and Horng (2010) propose a set of human elements in relation to staging customers’ experiences including frontline service employees and the presence of other customers. Meanwhile, a remarkably increasing body of research has paid heed to the role of customers in the cooperation of service offerings development as well as delivery process—the role of value cocreator / service coproducer (e.g., Chen et al., 2015; Prentice et al., 2017). For example, studies conducted in hospitality settings demonstrate that consumers are vital to a cocreated service experience; such effect is prevalent since consumers commonly consume services together in hospitality service settings (Luo et al., 2019; Yang, 2016). More importantly, hospitality practitioners such as casino operators are becoming more aware of the importance of embedding gamblers in their marketing strategy to sell an interaction-based gambling image (Wong and Wu, 2013). For example, Macau Galaxy—a local integrated resort, promoted on its website an image of people talking and sharing laughter inside its elegant venue. Indeed, customers’ roles today are increasingly appreciated as each customer is not merely a value recipient (Wong et al., 2018), but he/she plays a significant role in either cocreating better quality of services or co-destroying them (Eisingerich et al., 2014). Service scholars have further identified a set of specific roles consumers may enact in the service settings (e.g., partial employees and consultants, Bettencourt, 1997), along with subsequent beneficial outcomes (e.g., cared and respected by others, Rosenbaum and Massiah, 2007). In general, encouraging customers to mingle with one another during the service encounter could enable them to cherish the service consumption experience (Kim and Choi, 2016). Accordingly, it is broadly believed that each type of human interaction could directly contribute to improving customer experience to a great extent (Kim and Choi, 2016; Zhang et al., 2010).

This study seeks to address the aforementioned gaps in the literature regarding how a brand’s experience can best be attained through social components of the casino service setting. It views interactions among customers and providers as symbiotic and builds a triadic model of customer interaction quality by taking into account E2C, C2C, and Cu2Co in assessing customer evaluations of brand experience and brand attachment, which is defined as an emotional bond linking patrons and the brand; meanwhile it is crucial to drive a firm’s performance outcomes (King, 2017). In addition, by introducing the moderating role of E2C interaction quality, this study aims to fill the current research gap regarding an interplay of the triadic interactions among customers and employees. Our study therefore is orchestrated first with discussions of relevant theoretical background, which is followed by empirically assessing the relationships of interest. Further, we conclude with a discussion of the theoretical and managerial implications, as well as explicating limitations and future directions.

Theoretical background

Employee-to-customer Interaction

The preeminence of frontline employees has widely been appraised by both practitioners and scholars as a crucial means to deliver superior quality of services (e.g., Evanschitzky et al., 2011; Moore et al., 2005; Muskat et al., 2019; Wong, 2013). E2C interaction is commonly conceptualized as the quality of an experiential transactional-oriented interface between a customer and one or multiple frontline employees in a hospitality setting, in that resources are exchanged to facilitate the organizational purpose on one hand, along with emotional and functional experiences obtained by the customer on the other hand (Buonincontri et al., 2017). Evanshitzky et al. (2011) suggest that managers should not underestimate the power of service employees in creating a delightful experience. For instance, casino frontline employees not only are instrumental to the advancement of player–brand relationships, but they are also important as a means to foster casino brands’ competitiveness (Moore et al., 2005; Prentice and Wong, 2016). Indeed, research on service quality affirms that employee services count largely on the perceptions of customers regarding the overall service performance (Parasuraman et al., 1988).

Moreover, a gaming service transaction is characterized as inseparable in nature in that production and consumption of a gaming service often entails the cooperation from the gambler side (Fong et al., 2017). Therefore, gamblers are commonly compelled to exert efforts to assist casino employees, such as conveying their specific needs in exchange for a desirable level of customization and intimacy (Wong, 2013). Meanwhile, patrons may engage in friendly conversations with employees, which provides a means for casino employees to establish a relationship with them (Prentice and Wong, 2015). Rosenbaum (2006) further contends that customers may exhibit an urge to obtain support from employees in order to obtain more empathic services. Employees, however, may act as ‘coaches’ by assisting customers on service usage; or, in a less common situation, they may enact the role of ‘police officers’ by taking control of the service encounter when consumers demonstrate misbehavior (Fong et al., 2017; Pranter and Martin, 1991). That is, positive E2C interaction could not only elevate service quality, but it could also heighten customer satisfaction and ensure customer loyalty, resulting in advantage over competitors (Buonincontri et al., 2017; Moore et al., 2005).

Customer-to-customer interaction and customer-to-companion interaction

This study defines customer-to-customer (C2C) interaction as the quality of interactions among customers during the consumption stage, resulting in a cocreated or co-destroyed consumption experience (Luo et al., 2019; Yang, 2016). It is important to note that customers in the C2C definition refer to strangers who are initially unknown to one another (Huang and Hsu, 2010). Customers’ roles today are expanding from merely value recipients to value coproducers. This shift of customers’ roles is able to help expand ways in which they could better enjoy the customer journey through enhanced experiences (Huang and Hsu, 2010; Kim and Choi, 2016). In fact, customers are not merely consuming a service, but they are also sharing a range of resources to others (Martin and Pranter, 1989) and hence, cocreating experiences for a given brand (Ji et al., 2018; Makkonen and Olkkonen, 2017). That is, consumers are indeed a critical part of the service delivery process as they often act as ‘partial employees’ who assist and express care for one another in a way that even goes beyond service staff (Bettencourt, 1997; Kim and Choi, 2016).

Researchers further contend that in a service setting, interactions among patrons are a frequent phenomenon, ranging from making eye contact to helping one another and forming social camaraderie (e.g., Rosenbaum and Massiah, 2007; Sundaram and Webster, 2000). For example, conversations among gamblers often occur (Lam, 2007) as they share a common gaming premises, while the gaming service itself often allows them to network with one another (Fang and Mowen, 2009). Rosenbaum (2006) further suggests that customers may desire supportive resources from other customers, inhibiting their negative emotions while fulfilling their social–emotional desires. Customers may also exchange technical/functional support to one another by leveraging their knowledge and skills to facilitate their decision-making ability (Bettencourt, 1997). Broadly speaking, customer interactions may also occur in an indirect way when other consumers merely constitute the social environment, such as an energetic crowding effect during a sporting event (Martin and Pranter, 1989; Moore et al., 2005). This situation is also prevalent in the casino context, in which gamblers often provide some support to each other in the wagering process through cheering for each other and sharing information (Lam, 2007). Furthermore, although players are crucial in facilitating a pleasant gambling experience, their misbehaviors are also very common, especially when they are not familiar with gaming transactions and thus liable to impact others’ gambling experience negatively (Fong et al., 2017).

In addition, it is important to distinguish the differences between customer-to-customer (C2C) and customer-to-companion (Cu2Co) interactions. In contrast to the aforementioned C2C interaction, Cu2Co interaction refers to the quality of interactions among customers who are already friends, family members, or to a lesser extent, social acquaintances in a service setting. Although Cu2Co interaction is commonly considered as a form of C2C interaction, as a large portion of similar customer interactive behaviors are shared among customers’ companions and other customers (Moore et al., 2005), customers may intend to better sustain their social bonds with companions. Therefore, customers are expected to be more comfortable with their companions rather than strangers and hence, engage more frequently in Cu2Co interactions, such as exhibiting companionship support (Rosenbaum and Massiah, 2007). Furthermore, Kim and Choi (2016) suggest that customers’ companions play a paramount role during service exchanges by heightening the focal customers’ confidence in the service setting. Indeed, casino marketers are increasingly capitalizing on this phenomenon by constantly launching loyalty incentive programs to motivate gamblers to visit the property with their companions.

Brand experience

The customer experience has taken center stage in the literature on the hospitality industry since competing on product and service attributes may not be sufficient in ensuring customer loyalty (Ji et al., 2018; Morosan and DeFranco, 2019). As customers experience a brand, they are exposed to various brand attributes such as brand design, service setting, employees, and customers they interact with (Brakus et al., 2009; Ding and Tseng, 2015). While researchers have recognized the holistic and subjective nature of the brand experience, consumers may engage in a variety of experiential responses toward the brand (Brakus et al., 2009). For example, a brand that supplies enticing sensory cues through its facilities may further foster consumers’ behavioral responses by exhibiting approach behaviors toward the brand (Moore et al., 2005; Wong et al., 2019b). Other researchers have stated that emotional experiences are a key determinant of maintaining a mutual beneficial bond between a service provider and its patrons (Thomson et al., 2005). Hence, a brand experience in this study is defined as consumers’ evoked responses toward a brand and its elements when they are encountering the brand’s diverse components (Brakus et al., 2009).

The above discussions highlight the crucial need for service firms to meticulously formulate their service offerings to supplying patrons with a unique experience cultivated from a brand (Chang and Horng, 2010). As mentioned above, such an experience may not only be engendered by the tangible artifacts provided by the brand, but it can also be enriched through camaraderie and other social exchange opportunities among customers (Rosenbaum, 2006). That is, consumers are often deemed as a key driver of the unique service experience, which can hardly be replicated from the provider side of the experience (Kim and Choi, 2016; Yang, 2016). Fostering consumers’ propensities to positively engage in interactions with others could promote a set of countable benefits to each individual (Rosenbaum and Massiah, 2007). For example, promoting friendly dialog could be particularly beneficial for enabling customers to relish a service while waiting for the service together (Harris and Baron, 2004). Moreover, patrons may fulfill their emotional experiential needs by receiving care, or inhibiting worries when they exchange supportive resources in the service establishment (Rosenbaum and Massiah, 2007; Wei et al., 2017). In summary, customers’ experiences with a brand are cocreated, in that quality interactions with companions and other patrons serve as a conduit in complementing services crafted by providers (Kim and Choi, 2016; Nysveen and Pedersen, 2014). Hence, this study proposed the following hypotheses:

Hypothesis 1: Customer-to-customer (C2C) interaction has an impact on customers’ brand experiences.

Hypothesis 2: Customer-to-companion (Cu2Co) interaction has an impact on customers’ brand experiences.

The moderating role of employee-to-customer (E2C) interaction

To date, a large body of research has constrained its scope to the dyadic interactions between employees and customers (e.g., Chang and Horng, 2010; Harris and Baron, 2004; Kim and Choi, 2016). Although a multitude of elements may have an impact on the brand, a customer’s brand experience essentially rests upon the interactions between frontline staff and patrons (Jeong and Jang, 2011; Wong and Wu, 2013). Scholars concur that frontline employees can best foster the quality of an oasis in the service encounter (King, 2017; Tse and Ho, 2009). Whether service employees display attentiveness and responsiveness to patrons’ needs, or reliable services are delivered while exhibiting empathetic concerns, occupy customers’ judgment of what a quality service is (Parasuraman et al., 1988). Hospitality research on service quality further affirms this stance, in that consumers’ experiential assessment primarily rests on the quality of E2C interaction (Chen, 2013).

In light of the above literature, we argue that the quality of E2C interactions may moderate the role of interactions among customers in coloring their experiences with a brand. This logic rests on the fact that employees are obligated to manage customer behaviors and may intervene in these behaviors in due course. Such an intervention if viewed positively could elevate C2C and Cu2Co interaction qualities, hence improving one’s experience with a brand (Luo et al., 2019). For example, if casino staff offers guidance and empathy while managing the misbehaviors of others present, the experience of the disgruntled gamblers may be alleviated (Fong et al., 2017). On the contrary, if the intervention is deemed inappropriate, it could hamper the quality of customer interactions and ultimately translate to an unpleasant service experience (Pranter and Martin, 1991). Moreover, the customer’s profile also plays a role in influencing employee intervention strategies such that the serving staff might show a greater tolerance and even accommodate the premium players who are particularly aggressive and demanding (Fong et al., 2017). In addition, a study conducted in the hospitality service setting proposes that consumers are more compelled to exert efforts to cocreate an experience with others when they perceive service staffs have displayed extra-role behaviors (Im and Qu, 2017). In other words, the quality of C2C and Cu2Co interactions are contingent upon E2C interactions, in that favorable interactions between the server and the recipient act as a buffer. On one hand, such a buffer promotes positive customer experience either through remedying negative interactions or further enhancing positive interactions among customers; on the other hand it lessens the impact of customer interactions on such an experience when E2C interactions are perceived as unfavorable (Moore et al., 2005; Zhang et al., 2010).

Furthermore, drawing on social exchange theory, actors who benefit from such an exchange may arouse a diffuse obligation in other actors and hence, reciprocate with resources and benefits (Bettencourt, 1997; Evanschitzky et al., 2011). Therefore, when service performance has met gamblers’ expectations and beyond, satisfied gamblers are inclined to express reciprocation by supporting and helping other actors in the service setting (Bettencourt, 1997). In other words, since customer experience primarily rests on quality of E2C interactions, such a successful interaction/exchange provides a foundation in driving customers to devote more efforts and time to other actors by helping those in need, engaging in pleasant conversations, and/or exhibiting emotional support (Im and Qu, 2017). As a result, the quality of C2C and Cu2Co interactions could be enhanced under the condition of satisfactory E2C interactions (Luo et al., 2019). Accordingly, the following hypotheses were posited:

Hypothesis 3: E2C interaction moderates the relationship between C2C interaction and brand experience whereby negative E2C interaction may weaken this relationship while positive E2C interaction may strengthen this relationship.

Hypothesis 4: E2C interaction moderates the relationship between Cu2Co interaction and brand experience whereby negative E2C interaction may weaken this relationship while positive E2C interaction may strengthen this relationship.

Brand attachment

Brand attachment is gaining traction in the literature due to its prominent role in cultivating customer loyalty and ultimately firm success (Bahri-Ammari et al., 2016; Prentice and Wong, 2016). Brand attachment is deemed an emotion-dominated customer–brand bond and measures the strength of such a bond (King, 2017). Once patrons are firmly attached to a brand, they would exercise high emotional commitment to it (Malär et al., 2011). In turn, brand attachment often serves as an indicator of reinforced customer–firm connection, engaging patrons’ minds in ways that promote favorably emotional and behavioral responses to the brand (Thomson et al., 2005). Such responses, ranging from word-of-mouth expressions and revisit intentions (Prentice and Wong, 2016) to increased time staying and spending in the focal casino (Hwang et al., 2019). Hence, patrons’ strong attachment to the brand renders reciprocal behaviors that may ultimately drive business success (Prentice and Wong, 2016). Research on brand attachment has revealed that pleasurable encounters in the service delivery process may further promote customers’ attachment to the brand (Iglesias et al., 2011). Brand experiences are a more powerful driver in building customer–brand connection, as such connection is mainly developed through emotional traits (Brakus et al., 2009; Iglesias et al., 2011). Delightful experience therefore manifests as a means of brand connection, and hence brand attachment (Iglesias et al., 2011; Prentice and Wong, 2016). Indeed, the casino service encounter offers gamblers ample opportunity for social interactions (Lam, 2007); hence, such experience derived from the casino brand is crucial to the development of gamblers’ attachment to the brand (Prentice and Wong, 2016). Thus, the following hypothesis was proposed:

Hypothesis 5: Brand experience is positively related to brand attachment.

Methods

Data collection and sample

Data collection was undertaken in the casino industry in Macau, the gambling capital of the world. There were 41 casinos in 2019 ranging from smaller size casinos with a limited number of slot machines and gaming tables to larger and more popular ones such as Venetian and Galaxy. The gaming revenue of 2019 was around USD $37 billion (Gaming Inspection and Coordination Bureau, 2019), with the major contribution coming from Chinese gamblers. Furthermore, casino services are appropriate for this investigation as intense competition has compelled operators to cultivate a more intimate customer experience (Wan, 2013). We further defined our sample frame to incorporate tourist gamblers because Macau is renowned as a casino tourism destination with an influx of tourists flocking to casinos for gambling, shopping, sightseeing, dinning, and more (Wong and Rosenbaum, 2012). The sample included these gamblers from both large integrated and small traditional casinos. Measurement items on the questionnaire were first composed in English. They were then translated to Chinese and polished with assistance from two bilinguals in order to improve language precision for the main clientele (e.g., Chinese gamblers). Both simplified and traditional Chinese versions of the questionnaire were made available to the respondents. A pilot test with 11 respondents was conducted to further improve the wording of the questionnaire (e.g., Chinese translation of the questionnaire was revised based on respondents’ feedback).

Data were obtained by following a two-step sampling approach in order to improve representativeness of the population of interest. In the first step, we randomly chose 10 large integrated casinos and 20 small traditional casinos to represent the casino industry in the city. This selection decision was guided by the information (e.g., full casino list and corresponding websites) provided by the local gaming authority (Gaming Inspection and Coordination Bureau, 2019). We then checked each casino website to determine whether or not the casino offers a wide range of services beyond gambling (e.g., shopping, entertaining events, fine dining and accommodation options), and then categorized it as an integrated or small traditional casino. Next, a quota sampling approach was employed whereby 30 participants were recruited from large casinos while 10 participants were recruited from small establishments. We further used a systematic sampling method in that we intercepted every third casino patron at the outside of the exit door of each selected casino through a person-administered survey approach. Two filter questions were raised to ensure that participants were tourists who had gambled in the corresponding casinos. Each participant received a gift of a pack of paper towels upon completion of the survey.

We collected a total of 542 responses, which corresponded to a 54% response rate. The sample encompassed demographic distributions that resonate closely with the gambler profiles: 73% were male gamblers; 42% were aged between 40 and 59; 49% had a gaming budget over 10,000 Hong Kong dollars (HKD); 15% were first-time visitors to the selected casinos (see Table 1 for details).

Table 1.

Characteristics of respondents.

Variable	Percentage	Variable	Percentage
Gender		Total budget
Male	72.9	<5,000	26.4
Female	27.1	5,000–10,000	24.9
Age		10,001–25,000	12.5
21–29	19.0	25,001–50,000	16.5
30–39	31.0	50,001–100,000	10.7
40–49	27.7	Above 100,000	9.0
50–59	14.6	Frequency before the current trip
60 or above	7.7	0 time	15.3
Place of origin		1–5 times	39.5
Mainland China	85.4	6–10 times	12.4
Hong Kong	6.3	11–20 times	11.6
Taiwan	2.2	Above 20 times	21.2
Other places	6.1	With companions
		Yes	73.4
		No	26.6

Measures

Customer interactions

Both C2C interaction and Cu2Co interaction were assessed using four items. Both scales were adopted based on Arnould and Price (1993) and Moore et al. (2005). Each item was assessed on a 7-point Likert scale where 7 indicated ‘strongly agree’ and 1 indicated ‘strongly disagree’. Both scales were reliable, with Cronbach’s alpha equal to 0.86 and 0.90, respectively (see Table 2).

Table 2.

Scale items for the study constructs.

Scale items	Factor loadings	Cronbach’s alpha	CR	AVE
C2C interaction		0.86	0.89	0.67
I interacted well with other customers at this casino.	0.68
I developed friendships with other customers whom I met at this casino.	0.64
I felt satisfied with being there with other customers at this casino.	0.95
Other customers made my time there more enjoyable.	0.96
Cu2Co interaction		0.90	0.90	0.70
I felt closer to my companions at this casino.	0.65
I interacted well with my companions at this casino.	0.83
I felt satisfied with being part of my companions at this casino.	0.92
My companions made my time there more enjoyable.	0.93
E2C interaction		0.91	0.92	0.79
Interacting with employees of this casino made me feel comfortable.	0.91
I interacted well with employees of this casino.	0.96
I enjoyed interacting with employees of this casino.	0.79
Brand experience (sensory)		0.78	0.78	0.54
This casino brand makes a strong impression on my visual sense or other senses.	0.65
I find this casino brand interesting in a sensory way.	0.75
This casino brand appeals to my senses.	0.81
Brand experience (emotional)		0.85	0.85	0.65
This casino brand induces my feelings.	0.86
I have strong emotions for this casino brand.	0.84
This casino brand is an emotional casino brand.	0.72
Brand attachment		0.91	0.91	0.72
I really love this casino.	0.80
I would really miss this casino if I went away.	0.82
This casino is special to me.	0.89
This casino is more than a product/service to me.	0.88

Note: All factor loadings were standardized and were significant at the 0.001 level.

CR = composite reliability.

AVE = average variance extracted.

Comparative fit index [CFI] = 0.96, Tucker–Lewis index [TLI] = 0.95,

Root mean square error of approximation [RMSEA] = 0.06, and Normed fit index [NFI] = 0.94

E2C interaction

E2C interaction was a three-item scale adopted from Gremler and Gwinner (2000) and Arnould and Price (1993). It was measured using a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The scale demonstrated strong internal consistency with a Cronbach’s alpha of 0.91.

Brand experience

This 12-item four-dimension scale was adopted based on Brakus et al. (2009). However, the results from our preliminary analysis suggested that both the cognitive and behavioral dimensions exercised low convergent validity and reliability; as a result, they were removed from the study. The resulting two dimensions (six items) corresponded to affective and sensory aspects of brand experience. Each item of the scale was evaluated using a 9-point Likert scale ranging from 1 (completely disagree) to 9 (completely agree). This study followed Brakus et al. (2009) to operationalize the construct as a second-order measure. The two dimensions exhibited acceptable measurement consistency, as evidenced by Cronbach’s alpha values of 0.85 and 0.78, respectively.

Brand attachment

The brand attachment scale was adopted from Prentice and Wong (2016). The scale contained four items and each item was evaluated on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The scale demonstrated satisfactory reliability, with a Cronbach’s alpha of 0.91.

We further tested construct validity, in which all constructs’ average variance extracted (AVE) values exceeded 0.50 while in excess of the squared correlations of constructs of interest; hence, achieving convergent and discriminant validity. For diagnosing common method bias, Harman’s single factor test (Podsakoff et al., 2003) was used to demonstrate that around 41% of the variance (lower than the maximum threshold of 50%) was explained by the first factor, suggesting that such bias may not be an issue in the study. Further, we performed confirmatory factor analysis and the results suggested an acceptable measurement model fit (comparative fit index [CFI] = 0.96, Tucker–Lewis index [TLI] = 0.95, root mean square error of approximation [RMSEA] = 0.06, and normed fit index [NFI] = 0.94).

Findings

Results from Table 3 indicate that each construct of interest is significantly correlated. We further conducted hypothesis testing based on the structural equation modeling (SEM) using AMOS version 26. Overall, results from Table 4 demonstrate a satisfactory overall model fit (CFI = 0.94, TLI = 0.93, RMSEA = 0.07, and NFI = 0.92).

Table 3.

Descriptive statistics and correlations.

	Mean	S.D.	1	2	3	4	5	6
E2C interaction	4.83	1.29	0.91
C2C interaction	4.57	1.12	0.41	0.86
Cu2Co interaction	5.77	0.87	0.38	0.44	0.90
Brand experience (sensory)	6.12	1.61	0.47	0.31	0.37	0.78
Brand experience (affective)	5.24	1.90	0.48	0.36	0.37	0.74	0.85
Brand attachment	3.31	1.07	0.50	0.36	0.39	0.73	0.79	0.91

Note: Correlations were all statistically significant at the 0.01 level.

Table 4.

Results of path estimates.

	Model 1	Model 2
	Brand experience	Brand attachment
Control Variables
Casino type	0.33***	0.29***
Frequency to the selected casino	0.01 ^n.s.	0.03 ^n.s.
Main Effects
C2C	0.31***	0.34***
Cu2Co	0.29***	0.31***
Brand experience		0.92***
R ² (brand experience)	0.29	0.30
R ² (brand attachment)		0.84

Note: *** p < .001, n.s. denotes not significant.

Parameters are standardized.

Fit statistics for Model 2: CFI = 0.94, TLI = 0.93, RMSEA = 0.07, and NFI = 0.92

Hypotheses 1 and 2 posit that both C2C interaction and Cu2Co interaction have a direct effect on brand experience. Findings indicate that both interaction qualities are significantly associated with brand experience (H1: β_C2C = 0.34, p < 0.001 and H2: β_Cu2Co = 0.31, p < 0.001). Also, these interaction qualities have an approximately equal contribution to the focal customers’ brand experiences.

Hypotheses 3 and 4 propose that E2C interaction moderates the relationships between customer interactions and the brand experience, such that negative E2C interaction may weaken the proposed direct relationships. To assess for moderation, measurement invariance and group invariance analyses were employed. Based on the sample median, we split E2C interaction into two groups: high quality (N = 296) and low quality (N = 246) of interaction. Table 5 provides support (Δ χ ² ₍₁₃₎ = 27.23, p > 0.01) for measurement invariance (Han, 2015). Our findings (see Table 6) also provide evidence for group invariance such that E2C interaction quality conditions the relationship between C2C interaction and brand experience (Δ χ ² ₍₁₎ = 5.86, p < 0.05). On the other hand, we find that E2C interaction quality does not moderate the relationship between Cu2Co interaction and brand experience (Δ χ ² ₍₁₎ = 0.26, not significant) and hence, it fails to support Hypothesis 4. Our findings further suggest that the C2C–brand experience relationship remains significant for the high E2C interaction quality group (β = 0.34, p < 0.001), but not for its low E2C interaction counterpart (β = 0.12, n.s.). In other words, low quality of E2C interaction weakens the relationship between C2C interaction and brand experience but not for Cu2Co interaction. Hence, in support of Hypothesis 3.

Table 5.

Results of measurement invariance test.

Model	Description	χ ²	df	Δ χ ²	p	CFI	RMSEA
1	Baseline model for low and High E2C interactions	584.10	260	—	—	0.95	0.05
2	All factor loadings constrained equal	611.33	273	27.23₍₁₃₎	p > 0.01 (insignificant)	0.94	0.05

Note: Model 1 is the baseline model for Δ χ ² of the constrained model.

Table 6.

Results of group invariance test.

	Brand experience
	High E2C interaction	Low E2C interaction	Interaction effect	Δ χ2(1)
C2C interaction	0.34***	0.12^n.s.	0.27*	5.86*
Cu2Co interaction	0.24***	0.27***	0.21^n.s.	0.26^n.s.

Note: Parameters are all standardized.

*** p < .001, * p < .05, n.s. denotes not significant.

Hypothesis 5 assesses the relationship between the brand experience and brand attachment. The results show that enticing brand experiences can foster customers’ attachment to a brand (β = 0.92, p < 0.001), thus, supporting the hypothesis. Meanwhile, 84% of the variance of brand attachment is explained by brand experience, suggesting that offering customers with a high level of brand experience could ultimately help promote strong connections between a firm and the customers.

Discussion

The service encounter is imperative in staging experiences that customers desire (Chang and Horng, 2010). Contemporary research has acknowledged the impact of human touches on customers’ experience journey (e.g., Kim and Choi, 2016; Lloyd and Luk, 2011). However, in the hospitality literature little has been researched regarding the triadic interactions among factors. This research gap calls for a need to investigate the interplay of interactions among employees, companions, and other customers in the service setting. Furthermore, scholars concur that employee services are salient to staging a satisfying experience, whereas the impact of customer interactions on each individual’s experience varies significantly (Wong, 2013; Zhang et al., 2010). This study therefore examines how the association between customer interactions and the brand experience varies with the E2C interaction quality. The findings advance our understanding toward the interplay of the service encounter such that low E2C interaction quality may weaken the value cocreation process through C2C interactions. Theoretical and practical implications of the findings are presented as follows.

Theoretical implications

Although the literature has reported the role of customers in cocreating value in the service setting, such as parks (Grove and Fisk, 1997), gyms (Rosenbaum and Massiah, 2007), and hair salons (Moore et al., 2005), such customer-driven value cocreation inquiry through customer interaction remains sparse in hospitality studies. Despite the fact gambling is a social endeavor, as patrons often share gaming tables while remaining physically adjacent to each other, the literature rarely investigates how interactions among customers may help nurture a better casino brand experience. To this end, it is rather unclear whether or not gamblers may in turn help cocreate favorable brand experience with others. This study thus fills the void in the literature by showcasing that beyond C2C interaction quality as commonly reported in the literature, Cu2Co interactions play an equally important role, ceteris paribus. In other words, this study offers a new perspective in understanding interactions among customers that goes beyond the conventional C2C domain.

More specifically, prior research has focused on dyadic interactions of the service encounter (e.g., Kim and Choi, 2016; Harris and Baron, 2004). However, the service encounter goes beyond the dyadic interactions in which each service component is interdependent in the experience cocreation process (Bitner, 1992; Martin and Pranter, 1989). This study therefore fills the current research gap by exploring a triadic interaction model with respect to how C2C, Cu2Co, and E2C could cultivate brand experience and ultimately brand attachment. In essence, the proposed Cu-Co-E triadic interaction model presented in Figure 1 illustrates an intricate relationship among four parties with influences of interactions between oneself and others (e.g., customer, companion, and employee). This model thus highlights a novel means to assess interactions between the self and a triadic web of others as a conduit to obtain better customer experience.

Figure 1.

Proposed Model of Cu-Co-E Triadic Interaction.

Specific findings of this study further illustrate this intricate web of interactions. For example, a low quality of E2C interaction during the service encounter could hamper the C2C interaction quality effect on customer experience; but such E2C interaction quality does not have any major negative impact on the role of Cu2Co interaction. These counterintuitive results suggest that E2C interaction is a boundary condition for C2C interaction, in that it could facilitate cocreation of experience on one hand, and debase experience cocreation on the other hand. This buffering mechanism thus demonstrates how the customer side of interactions is contingent upon the provider’s endeavor. In addition, it is plausible that during an unpleasant E2C exchange, customers may rely more on Cu2Co interactions, as companions can provide more reliable exchanges and hence, rescue one’s experience.

Looking through a broader theoretical lens, this study draws on the social exchange theory (Bettencourt, 1997) to assess customer interactions from three different aspects: employees, stranger customers, and companions. It adds to the existing understanding on social exchange, which is often viewed as dyadic, by illustrating how complex interactions among various types of actors could ultimately influence customer responses to a commercial setting and the focal brand. Putting these findings together, this investigation contributes to a new research direction by delving into symbiotic triadic interactions between the self and others in the cocreation of experience.

Managerial implications

Hospitality firms that pursue service excellence, such as casinos and hotels, should meticulously manage the service encounter to cultivate an intended brand experience (Wong et al., 2019a). Such an intended experience will not only satisfy patrons in the short term, it will also have a long-run impact by nurturing a strong connection between a firm and the customer (Iglesias et al., 2011). Hence, industry practitioners are encouraged to exert efforts to understand what and how service offerings and processes can engender memorable experiences.

Customers’ roles in the service encounter are the foundation of cocreating a memorable customer experience (Bettencourt, 1997). On one hand they may assist the service exchange by extending experiential values, but on the other hand, they may also decrease others’ experiences by exhibiting misbehaviors (Nicholls, 2010; Zhang et al., 2010). That is, the focal customers may cocreate or co-destroy their experiences in the company of other actors, such as employees, customers who are strangers, and companions (Chang and Horng, 2010; Luo et al., 2019). As proposed by Martin and Pranter (1989), the first step to realize a long-lasting memorable service experience is to deploy effective segmentation to target the most desirable and homogeneous customer mix, thereby fostering firms’ ability to achieve their objectives. One way to do so is to launch marketing programs that attend to customers who consume services with their companions. Indeed, as suggested by our empirical findings, customers’ companions are instrumental to the cocreation process even when service performance is not satisfactory. (Pranter and Martin, 1991) further state that industry practitioners can also realize this by proactively directing customer behaviors in a way that promotes human interaction-based experience cocreation. In other words, hospitality management should not only rely on timely actions that enforce proper customer behaviors, they should also nurture a socially cheerful service environment (Ou et al., 2020). Yet, such a practice is particularly prevalent in casino VIP and premium mass rooms—evidenced by a deluxe servicescape to offer patrons an oasis for dining and tea service, as well as offering lounges to boost social interactions. Casinos have also hosted baccarat tournaments and have provided a list of other socially engaging events for players having high net worth (such as the second or third tier loyalty card holders). Nevertheless, casino operators are suggested to reinforce social interactions among players on the main floor by arranging extra space with more chairs and tables provided for gamblers to engage in conversations with other gamblers. Such proactive management practices could hence not only prohibit or remedy unpleasant customer interactions, they could also encourage favorable interactions among customers (Pranter and Martin, 1991).

More importantly, managers should not underestimate the power of service employees in cocreating an alluring service encounter (Evanschitzky et al., 2011). Frontline employees could help deliver service quality that differentiate one brand from another. Research on the service–profit chain has acknowledged that satisfied and motivated employees are the essence of service excellence (Heskett et al., 2008). That is, frontline employees play an integral role in addressing customer needs; hence, customer satisfaction often rests on employee satisfaction. Industry practitioners should also encourage patrons to actively cocreate their experiences along with service staffs as demonstrated in the present study. A common approach is to solicit from consumers innovative inputs for service improvement; both firms and patrons may in turn benefit from heightened service quality (Bettencourt, 1997). In addition, our results suggest that gamblers’ frequency of trips is not correlated with their perceived E2C interaction quality; this finding proposes a challenge for casino operators because every E2C interaction encounter matters. Hence, one dissatisfying E2C exchange might diminish a frequent customer’s experience with the given brand, thus affecting their brand attachment. Furthermore, many jay-customer incidents in the casino service encounter often are attributed to lack of understanding of gaming procedures and transactions (Fong et al., 2017); hence casino operators are encouraged to train and empower frontline employees to educate gamblers as needed. Thus, managers should not overlook that frontline employees are salient in the interplay of the service encounter.

Limitations and future research

Although this study is among the first to propose a triadic interaction model on customer experience in the hospitality literature, we must acknowledge limitations of the study as follows. First, this study was a cross-sectional inquiry which limits when triadic interactions take place during the service encounter. It is possible that the order of the interaction could alter the magnitude of the interactions of C2C, Cu2Co, and E2C. Second, the study was conducted in the casino industry in Macau. Although the sample may have good representation for the industry, there could be cultural variations that are not encountered in the study. Third, although we modeled E2C interaction as a moderator, there could be other service elements, such as the service environment and brand image, that also play a role in conditioning the association between customer interactions and brand experience. Fourth, we only focused on social interactions in the casino service encounter, while gamblers’ interactions via social media before they arrive and/or after they leave the focal casino were outside the scope of the present research. Given the aforementioned limitations, we encourage future research to (1) take the research context into consideration by modeling the service setting and/or brand attitudes as a higher level boundary conditions, (2) seek intra-cultural discrepancies, (3) assess whether the order of interaction plays a role in the experience cocreation process, and (4) investigate gamblers’ interaction qualities via social media before they arrive and/or after they leave the focal casino.

Footnotes

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) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: This research is partially supported by Guangdong Provincial Department of Education Grant (2019GXJK052).

ORCID iDs

Zhiwei (CJ) Lin

IpKin Anthony Wong

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