Collaborative Innovation or Opportunistic Behavior? Evidence from the Relational Governance of Tourism Enterprises

Abstract

Relational norms are often used to govern interfirm relationships. However, an emerging stream of work has identified their potential “dark sides.” This study examines why and when the benefits or drawbacks occur. Based on a survey of tourism enterprises in China, an integrative model composed of relational norms, commitment, relationship performance (including collaborative innovation and opportunistic behavior), and substitutability is confirmed. The results show that the effectiveness of relational norms depends on the partner’s commitment types and the contexts in which those norms are embedded. Although relational norms promote collaborative innovation through both the calculative and affective commitment, they are likely to foster the partner’s opportunistic behavior through calculative commitment. The substitutability of a tourism enterprise is found to influence the strength of the relationships between relational norms and the two types of commitment. These findings offer important implications for tourism businesses.

Keywords

collaborative innovation opportunistic behavior relational norms relationship commitment substitutability

Introduction

Relational norms, which are defined as “expectations about behaviors that are at least partially shared by a group of decision makers” (Heide and John 1992, 34), are often used to govern interfirm collaborative relationships. The “bright sides” of relational norms have a long research focus (e.g., Palmatier, Dant, and Grewal 2007; Poppo and Zenger 2002). Studies indicate that relational norms help promote a long-term orientation in the exchange, direct firms and their partners to bilaterally beneficial strategies (Heide and John 1992), lower transaction costs (Poppo, Zhou, and Zenger 2008), and reduce conflict (Jap and Ganesan 2000). Relational norms help to safeguard working relationships against deviant behaviors (Zhou et al. 2015), thus positively influencing both the financial and the relational outcomes of interfirm collaborative activities (Cannon, Achrol, and Gundlach 2000).

However, an emerging stream of research has indicated that relational norms are not always beneficial (e.g., Huang and Chiu 2018; Poppo, Zhou, and Zenger 2008); they may involve dysfunctions or have “dark sides.” Several studies have reported an insignificant effect of relational norms on a firm’s performance (e.g., Cai, Yang, and Jun 2011). Relational norms may increase the likelihood of opportunism (Carson, Madhok, and Wu 2006), cause firms to overlook better options, and harm firm profitability (Holloway and Parmigiani 2014). These findings suggest a somewhat contradictory relationship between relational norms and relationship performance. Thus, the effects of relational norms need further investigation. In this study, we contribute to this topic by presenting answers to the key questions of why and when the benefits or drawbacks of relational norms occur. Specifically, we use relational norms as a predictor and relationship performance as an outcome variable in an integrative model that considers relational norms, commitment, relationship performance, and substitutability. In doing so, we attempt to bridge the separating research on the effects of relational norms and build a consensus among the divergent findings.

We mainly focus on the relational governance of tourism enterprises and take into account two possible consequences of relational norms: collaborative innovation and tourism partners’ opportunistic behavior. So far, there is a dearth of empirical insights into relationship governance in the tourism sector, despite the fact that interfirm collaboration is central to tourism-related economic activities (Zhang, Song, and Huang 2009). Because of the unique characteristics of tourism products and the tourism industry, a number of important issues must be dealt with regarding relationship governance in the tourism context. First, services are intangible, and thus the inputs and outputs of tourism enterprises and their partners are difficult to define or evaluate. Relational norms play a vital role in in these kinds of interfirm partnership, because such norms are particularly useful in dealing with performance ambiguity and behavior that cannot be observed or controlled directly (Heide and John 1992). A second issue is that tourism is a coordination-intensive industry, in which various product/service providers are bundled together to provide customers with a holistic tourism experience (Song, Liu, and Chen 2013). This interdependence requires that equal attention be paid to the improvement of collaborative quality and to the reduction of exchange costs in the governance of tourism interfirm relationships. Though, as suggested by scholars, collaborative exercises are often challenging and need to be addressed from a long-term perspective (Novelli, Schmitz, and Spencer 2006), a change of models may still be needed for tourism research (Hjalager 2010).

This study applies social exchange theory (SET) to explore the effects of relational norms. SET is a conceptual framework that has been widely used in management research (Cropanzano et al. 2017). The central tenet of SET is that relationships are maintained through a process of reciprocity, whereby one party tends to reward the good (or sometimes bad) activities of another party (Cropanzano and Mitchell 2005). Commitment reflects a reciprocal response to relational norms, which in turn engenders certain behavioral outcomes (Cropanzano et al. 2017). Thus, a partner’s sense of commitment is identified as a variable potentially mediating the effects of relational norms. We examine two components of commitment: calculative commitment (which is based on rational economic calculations) and affective commitment (which is based on emotional attachments or social sentiments) (Gilliland and Bello 2002). This study also considers the substitutability of tourism enterprises. Because of low entry barriers (Lee, Hallak, and Sardeshmukh 2016), the tourism sector is dominated by homogeneous small- and medium-sized enterprises (SMEs) (Novelli, Schmitz, and Spencer 2006). The relatively high degree of substitutability and low levels of bargaining power present major challenges for SMEs as they seek to manage the interfirm relationships (Carlisle et al. 2013). Overcoming such challenges through relational governance is important for SMEs. We posit that the association between relational norms and the partners’ commitment is contingent on the substitutability of tourism enterprises.

This study makes three contributions. First, it represents one of the few attempts to address interfirm governance and collaborative innovation issues in the tourism context. Although the tourism literature has highlighted the importance of collaborative innovation (e.g., Divisekera and Nguyen 2018; Zach 2016), few studies have provided details on how to actually promote it. Our research advances the literature by providing a relational governance framework for assessing collaborative innovation among tourism enterprises. Second, we shed light on the mechanisms and boundary conditions for relational norms. Thus, we enrich the literature on interfirm relationship governance, and provide an opportunity for dialogue between tourism research and the wider field of research on general management. The mediating roles of calculative and affective commitment help to identify the mechanism that links relational norms with collaborative performance. The moderating effect of substitutability indicates the boundary conditions of relational norms. Third, we suggest that the effect of relational norms is a double-edged sword. The “bright side” and “dark side” of relational norms coexist in interfirm governance. Relational norms is positively related to collaborative innovation. However, this kind of governance may also bring costs for enterprises by promoting partner opportunism. Thus, from a practical standpoint, this study provides a more nuanced understanding of these mixed effects and can help enterprises, especially tourism enterprises, decide how to leverage the positive outcomes of relational norms while minimizing the negative impacts in collaborative relationships.

Theoretical Background

Collaborative Innovation and Opportunism in Tourism

Many researchers have emphasized the value of collaborative innovation in the tourism context (e.g., Divisekera and Nguyen 2018; Kallmuenzer and Peters 2018). In a rapidly changing market, innovation across firm boundaries through the sharing of ideas, expertise, and opportunities (R. E. Miles, Miles, and Snow 2005) is often the essence of competitive advantage (Lee, Hallak, and Sardeshmukh 2016; Smirnova, Rebiazina, and Khomich 2018). By collaborating with partners, enterprises can maintain flexibility while leveraging external resources and can thus close the gap between their current levels of innovation and the levels they need to attain (Ketchen, Ireland, and Snow 2007). For SMEs in less economically developed countries, collaborative innovation is particularly useful for achieving greater performance and sustainability (Carlisle et al. 2013; Zach 2012). Several researchers have investigated the antecedents of tourism-based collaborative innovation. For example, Hoarau and Kline (2014) found that increased social capital could lead to knowledge sharing and contribute to collaborative innovation. The choice of partners was associated with collaboration and knowledge sharing (Zach and Hill 2017). These studies have enhanced our understanding of collaborative innovation in tourism. However, to our knowledge, few attempts have been made to empirically explore collaborative innovation from the perspective of relational governance.

Because of information asymmetry, bounded rationality, and the profit motive, opportunistic behavior is a constant concern for firms involved in collective activities (Williamson 1975). Opportunistic behavior, or opportunism, is defined as “a lack of candor or honesty in transactions, [including] self-interest seeking with guile” (Williamson 1975, p. 9). Such behavior can take both active and passive forms, which involve breaches of contract, expropriation, free riding, the withholding of effort, and the evasion of obligations (Wathne and Heide 2000). Either type of opportunistic behavior can cause uncertainty and may have detrimental effects on interfirm relationships (Zhou et al. 2015). When firms behave opportunistically, their gains come at the expense of the partners (Wathne and Heide 2000). Studies have suggested that opportunism tends to increase one party’s short-term unilateral gains but erode the long-term gains that could benefit both parties (N. A. Morgan, Kaleka, and Gooner 2007). In recent years, a number of online travel agencies (OTAs) have complained about or even sued hotels and airlines for violating cooperation unilaterally, by offering lower rates on their own websites to increase direct bookings (Schaal 2016). These examples indicate the opportunism of tourism partners. Given the ubiquitous nature and the negative associations of opportunistic behavior, it is clear that tourism enterprise need to govern the relations through a collaborative process (Paswan, Hirunyawipada, and Iyer 2017).

Social Exchange Theory and Governance Based on Relational Norms

Both collaborative innovation and opportunistic behavior can be governed through the deployment of appropriate mechanisms. Governance mechanisms are the safeguards or tools that firms implement to establish and structure their business relationships (Brown, Dev, and Lee 2000). For enterprises engaged in collaboration, interfirm exchanges are not one-shot transactions in a market context but instead exchanges immersed in social relationships and involve a series of social interactions (Poppo and Zenger 2002). Thus, SET offers a useful framework for examining the governance of interfirm relationships. SET posits that social interaction is an exchange process (Blau 1964). The underlying premise is that “all relationships have give and take” (Kaynak and Marandu 2006, 229). As for relational norms, they express the enterprise’s promise of fair play, and signal a long-term mutual beneficial orientation (Palmatier, Dant, and Grewal 2007). Consistent with SET, exchange partners may perceive the attitudes and beliefs of the enterprise and feel obligated to reciprocate such treatments. Thus, relational norms may operate as a self-enforcing safeguard that motivates the partners to behave in expected ways (Tangpong, Huang, and Ro 2010).

Relational norms usually have three dimensions: flexibility, information exchange, and solidarity (Jap and Ganesan 2000). Flexibility is the willingness to adapt to changes in circumstance. Information exchange is the bilateral expectation that each party will provide its partner with the information it needs. Solidarity means that problems in the relationship are treated as common concerns for all of the parties involved (Poppo and Zenger 2002). Flexibility, information exchange, and solidarity remind the parties how they are expected to behave (Dev, Grzeskowiak, and Brown 2011). However, as mentioned previously, relational norms are not always effective. Although such norms represent a form of “moral control” (Larson 1992, p. 96), they cannot predict behavior (Jap and Ganesan 2000). Norms have the potential to generate high-quality relationships, but only under certain circumstances (Cropanzano and Mitchell 2005). Williamson (1996) expressed skepticism about the efficiency of relational norms and proposed that in actuality, clear calculation determines the degree of cooperation and performance in relational exchanges. Therefore, the effectiveness of relational norms require further empirical investigation.

Conceptual Model and Hypotheses

We apply our conceptual model (Figure 1) to business partnerships in the tourism sector. This model helps to examine the effects of relational norms on collaborative innovation, and on each partner’s opportunistic behavior, via the kinds of the partner’s commitment. In addition, we investigate the moderating effect of a tourism enterprise’s substitutability on the association between relational norms and commitment.

Figure 1.

The conceptual model.

Relational Norms and Relationship Commitment

Commitment refers to one party’s ongoing desire to maintain a relationship with others (Jokela and Söderman 2017; Jap and Ganesan 2000). For tourism enterprises, a committed partner is “forward looking” and wants “the relationship to endure indefinitely” (R. M. Morgan and Hunt 1994, p. 23). However, commitment can take different forms, and the two main types of relationship commitment are calculative commitment and affective commitment (Gilliland and Bello 2002). Calculative commitment is a state of attachment that results from a rational calculation of the benefits and costs (Dwyer, Schurr, and Oh 1987). This type of commitment reflects an instrumental link between an enterprise and its partners (Geyskens et al. 1996). In contrast, affective commitment is based on an emotional attachment or a social sentiment regarding the business relationship (Gilliland and Bello 2002; Kim, Hibbard, and Swain 2011). Although these two types of commitment may coexist (Gilliland and Bello 2002), they involve quite different motivations for continuing a relationship, and thus may have differing effects on the partner’s forms of subsequent behavior. Therefore, it is necessary to examine the effects of relational norms on various types of commitment, and the potential consequences of each kind of commitment.

In line with SET, we propose that the fair and moral treatment displayed by tourism enterprises through relational norms help to boost the partners’ relationship commitment. In that case, commitment represents a reciprocal response of the partners toward the relational norms. We note that “the reciprocating responses will match the valance of the respective positive and negative actions” (Cropanzano et al. 2017, p. 22). Therefore, relational norms are likely to induce different types of commitment, based on the perceived “valences” of the relational norms. For partners in business, the norms of flexibility, solidarity, and information exchange are displayed in accordance with the logic of appropriateness. This sort of logic indicates how certain aspects of the relationship will be modified under changing circumstances and treats the partners as friends (Grayson 2007; Heide and Wathne 2006). Thus, we expect that the use of relational norms will enhance a partner’s affective commitment. However, tourism enterprises are not individuals with fixed predispositions, but collections of different roles (Heide and Wathne 2006). As a businessperson, enterprises are inherently motivated by profit-seeking and utility maximization (Heide and Wathne 2006). The norms for solidarity and flexibility and the necessity of information exchange also align with an enterprise’s economic incentives to engage in cooperation and collaboration. Thus, the partners tend to show a calculative form of commitment to relational norms, in response to the enterprise’s economic expectations. Hence, we propose the following hypotheses.

Hypothesis 1a: Relational norms positively affect the calculative commitment of partners.

Hypothesis 1b: Relational norms positively affect the affective commitment of partners.

Relationship Commitment and Opportunistic Behavior

Calculative commitment is a utilitarian, rational commitment generated by economic interest (Gilliland and Bello 2002). Thus, calculatively committed partners are likely to act according to a logic of consequences, and to adopt unethical behavior if doing so enhances their self-interest. Although calculative commitment suggests an element of continuance, some scholars have argued that calculative commitment actually reflects a negative motivation to maintain a relationship (Geyskens et al. 1996). Typically, calculative commitment tends to result in an unstable relationship (Devece, Palacios-Marqués, and Alguacil 2016). Ties between tourism enterprises and their partners that are based on calculative commitment are commonly weak and easily broken (Liu et al. 2010). Thus, the exchange partners’ calculative commitment is proposed to be positively associated with their opportunistic behavior and a search for alternatives (Gilliland and Bello 2002).

In contrast, the underlying motivation of affective commitment involves a generalized sense of emotional regard for and attachment to the enterprise (Geyskens et al. 1996). Unlike the extrinsic economic motivation of calculative commitment, affective commitment is intrinsically motivated. A partner with affective commitment to the relationship appreciates the enterprise, values the partnership, and experiences feelings of faithfulness and allegiance to the joint enterprise (Gilliland and Bello 2002). In such a case, an affectively committed partner will consider opportunism as a deceitful violation of the appropriate or required role behavior and will actively seek to reduce opportunism (R. M. Morgan and Hunt 1994; N. A. Morgan, Kaleka, and Gooner 2007). A relationship based on positive affect may actually be more sustainable than a relationship focused on economic transactions (Fullerton 2005). We therefore propose the following additional hypotheses.

Hypothesis 2a: The calculative commitment of partners positively affects their opportunistic behavior.

Hypothesis 2b: The affective commitment of partners negatively affects their opportunistic behavior.

Relationship Commitment and Collaborative Innovation

Interorganizational collaboration is the process through which two or more parties work closely together to achieve common interests (Ketchen, Ireland, and Snow 2007). In such collaboration, the partner’s commitment to the relationship is particularly important (Garnes and Mathisen 2014). As mentioned previously, both affective and calculative commitment indicate a long-term orientation and an intention to continue the relationship.

A partner committed to the business relationship will participate in collaborative innovation out of a desire to make the relationship work (R. M. Morgan and Hunt 1994). Various studies have shown that affective commitment is positively associated with co-productive forms of behavior such as collaborative innovation, exchange participation, and citizen behavior (Kim, Hibbard, and Swain 2011). Enterprises with a high degree of affective commitment are more motivated to actively participate in behavior that is beneficial to the achievement of common goals and even helps the other party to achieve its own goals (Mayer and Schoorman 1992). As collaborative innovation provides economic benefits for both a tourism enterprise and its partners, a calculatively committed partner may also actively participate in collaborative innovation. Thus, the following hypotheses are formulated.

Hypothesis 3a: The calculative commitment of partners positively affects collaborative innovation.

Hypothesis 3b: The affective commitment of partners positively affects collaborative innovation.

Mediating Effect of Relationship Commitment

Commitment is a key construct explaining the behavior of different members in a partnership (Gao, Ghosh, and Qian 2018; Gilliland and Bello 2002). Some researchers have argued that “relationships are built on the foundation of mutual commitment” (Berry and Parasuraman 1991, p. 139). R. M. Morgan and Hunt (1994) proposed a commitment–trust theory, proposing that commitment plays a critical role in linking an array of relationship sources and outcomes. In line with these suggestions, we position the two types of commitment as mediators between relational norms and relationship performance.

Relational norms cannot directly predict a partner’s behavior, which is best viewed as an outcome of the partner’s attitude (Fishbein and Ajzen 1975). Relational norms usually enhance relational responses such as commitment, which in turn cause certain types of behavior among the partners (Cropanzano et al. 2017). Some studies have noted that a partner’s commitment can affect the quality of governance and the relational behavior (Gundlach, Achrol, and Mentzer 1995). In a collaborative process, commitment leads directly to behavior that furthers the success of the relationship (Jeong and Oh 2017). Specifically, relational norms affect relationship performance via both calculative and affective commitment. This observation is consistent with the suggestion that the mechanisms through which relational governance attenuates hazards and promotes performance are both economic and sociological (Poppo and Zenger 2002). To examine the mediating effect of relationship commitment, we propose the following hypotheses.

Hypothesis 4: The relationship commitment of tourism partners mediates the relationship between relational norms and opportunistic behavior.

Hypothesis 4a: The calculative commitment of tourism partners mediates the relationship between relational norms and opportunistic behavior.

Hypothesis 4b: The affective commitment of tourism partners mediates the relationship between relational norms and opportunistic behavior.

Hypothesis 5: The relationship commitment of tourism partners mediates the relationship between relational norms and collaborative innovation.

Hypothesis 5a: The calculative commitment of tourism partners mediates the relationship between relational norms and collaborative innovation.

Hypothesis 5b: The affective commitment of tourism partners mediates the relationship between relational norms and collaborative innovation.

Moderating Effect of Substitutability

Substitutability is a major variable that determines the dependence structure and power allocation in a relationship (Kumar, Scheer, and Steenkamp 1995; Xia 2011). In the tourism context, substitutability reflects the degree of difficulty for a partner to find a substitute tourism enterprise in the market (Mwesiumo, Halpern, and Buvik 2019). The more difficult it is to find a substitute for an enterprise, the lower its substitutability, and the greater a partner’s dependence on the enterprise will be (Geyskens et al. 1996).

We investigate the moderating effect of substitutability from the perspective of a tourism enterprise that is implementing relational governance, rather than by taking its partner’s point of view. It is necessary to examine substitutability in social exchanges, because it influences the partners’ perceptions toward the interactions involved in the relationship (Nunkoo 2016). For tourism enterprises with higher substitutability, it is easier for their partners to find comparable resources elsewhere (Bae and Gargiulo 2004; Molm 1994). In such cases, the association between relational norms and the partner’s calculative commitment tends to be weaker, as the relationship is less economically attractive for the partner. We posit that under such circumstances, the link between relational norms and the partner’s affective commitment will be strengthened. The relational norms used by enterprises with higher substitutability are more likely to be perceived positively by their partners, and such perceptions can contribute to a more emotion-based set of social exchanges (Chang et al. 2012). When an enterprise has higher substitutability, its partners perceive less risk or vulnerability in making an affective commitment (Kumar, Scheer, and Steenkamp 1995). That is, even though substitutability does not directly stimulate affective commitment, it does create an environment in which affective commitment can be cultivated and can flourish (Kumar, Scheer, and Steenkamp 1995). Thus, we propose the following further hypotheses.

Hypothesis 6: The substitutability of the tourism enterprise moderates the relationship between the relational norms and commitment of the partners.

Hypothesis 6a: The substitutability of the tourism enterprise weakens the positive relationship between the relational norms and calculative commitment of the partners.

Hypothesis 6b: The substitutability of the tourism enterprise strengthens the positive relationship between relational norms and affective commitment of the partners.

Research Methods

Data Collection Sites

The proposed model was tested using a quantitative approach. A questionnaire survey of tourism enterprises in China was conducted to collect data. The questionnaires were distributed at the Beijing International Tourism Expo, the Central China Travel Expo (in Wuhan), and the Guangdong International Tourism Industry Expo. These three expos were selected for a number of reasons. First, they are very popular in China and attract representatives of tourism enterprises from all over the country. Second, the managers in charge of external cooperation often participate in these expos. Third, it is reasonable to infer that the tourism enterprises attending these expos are more actively to engage in collaborative innovation with partners. Fourth, these expos are cost-effective locations at which to obtain a sample of tourism enterprises, as more than 1,000 tourism enterprises attend the Beijing International Tourism Expo and the Central China Travel Expo, and over 2,000 tourism enterprises attend the Guangdong International Tourism Industry Expo each year.

Sampling and Data Collection

We employed a team of 15 research assistants to conduct the survey. These research assistants were trained to ensure that they understood the survey’s procedures and methods. To identify potential respondents, we used a purposive sampling procedure. First, we included only tourism enterprises that had experience in collaborative innovation with external partners. Second, we considered only managers in charge of cooperating with external companies (e.g., marketing managers) as qualified respondents, because these people had extensive knowledge of the relevant activities.

The data were collected face to face from managers of tourism enterprises at the aforementioned tourism expos. We went to each exhibition booth, explained the study’s purpose to the target manager, and asked whether he or she was willing to participate. If the manager answered yes, we gave him or her the questionnaire to complete. Each respondent was instructed to answer the questions with reference to collaborative innovation experiences with one business partner of his or her choice. If the tourism enterprise did not qualify as an effective sample, or if the manager was not willing to participate in the survey, we moved on to the next exhibition booth.

At the three expos, we distributed 450 questionnaires, and 391 respondents completed the surveys, resulting in a response rate of 87%. Subsequently, 22 surveys were omitted because of missing data, which left a final total of 369 valid questionnaires for analysis. This total satisfied the minimum sample size requirement (Hair et al. 2013). Of the 369 respondents, 49% were female and 51% were male. The respondents were mainly well educated; 87% had college degrees or above.

Measurement Scales

The constructs in the proposed model were measured using multi-item scales adapted from the literature (Table 1). The items were developed in English and then translated into Chinese. To ensure that the translated versions reflected the meanings and intent of the original text, a two-step process was used. First, the researchers applied back-translation, and then a translator proficient in both English and Chinese checked the translated questionnaire and made the necessary modifications. Five academic experts from universities were invited to read, edit, and improve the items to enhance the content validity, clarity, and readability. To estimate the reliability and construct validity of the items, a pilot study was conducted with 30 marketing/purchasing managers from CITS International Travel Service Group, Nanhu International Travel Service Company, and GZL International Travel Service Company, based in Guangdong Province, China. Minor changes were made to the formal questionnaire according to the results of the pilot test.

Table 1.

Assessment of the Measurement Model: Reliability and Validity.

Items	Standardized Loadings	t Value	Cronbach’s α / CR	AVE
Relational Norms (RN) (Second-order factor)			0.84/0.75	0.50
Flexibility Norms (FN)	0.69		0.74
FN1: We willingly set aside the contractual terms in order to work through difficult situations with the partner.	0.71
FN2: We gladly make adjustments to help out the partner when faced with special problems.	0.70	10.74***
FN3: We expect the transaction method adapts to the changing environment.	0.67	10.41***
Information Exchange Norms (IEN)	0.72	11.36***	0.73
IEN1: It is expected that any information that might help the other party will be provided to them.	0.73
IEN2: Exchange of information in this relationship takes place frequently.	0.61	9.93***
IEN3: It is expected that we keep each other informed about events or changes that may affect the other party.	0.72	11.21***
Solidarity Norms (SN)	0.72	11.39***	0.77
SN1: Problems that arise in this relationship are treated as joint rather than individual responsibilities.	0.62
SN2: Both firms are committed to improvements that may benefit the relationship as a whole and not only individual parties.	0.83	11.17***
SN3: The parties have a sense of responsibility to ensure that the transaction relationship promotes common interests.	0.77	10.89***

Calculative Commitment (CC)			0.75/0.76	0.51
CC1: This company has advantages compared to other companies.	0.64
CC2: I would suffer economically if the relationship were damaged.	0.68	10.00***
CC3: We cooperate with this company because of economic benefits gained from the relationship.	0.81	10.71***

Affective Commitment (AC)			0.78/0.79	0.55
AC1: It is pleasant working with this company.	0.73
AC2: We like this company.	0.83	13.51***
AC3: We intend to continue cooperation with this company even if other companies offer better conditions.	0.66	11.43***

Opportunistic Behavior (OB)			0.87/0.87	0.69
OB1: we do not always act in accordance with the contractual conditions agreed with this company.	0.87
OB2: we sometimes breach agreements to maximize our own benefit.	0.82	17.93***
OB3: we will take advantage of “holes” in the contract to further our own interests.	0.80	17.48***

Collaborative Innovation (CI)			0.85/0.85	0.66
CI1: Both firms have developed new ideas during the cooperation process.	0.77
CI2: Both firms have cooperatively created many new and useful solutions to problems that have arisen during the cooperation process.	0.86	15.96***
CI3: Both firms have cooperatively promoted the innovation of tourism products.	0.80	15.22***

Substitutability (S)			0.84/0.85	0.66
S1: Other companies could provide what we get from this company.	0.65
S2: This company possesses a near monopoly over our sales.	0.89	13.37***
S3: This company is one of the few options that we possess.	0.88	13.36***

Note: AVE = average variance extracted. In AMOS, one loading has to be fixed to 1, therefore no t value can be computed for this item.

***

p < .001.

The formal questionnaire was made up of five sections. Section one included nine items from Heide and John (1992) to measure the three factors involved in relational norms (i.e., flexibility norms, information exchange, and solidarity norms). Section two included six items adapted from Gustafsson, Johnson, and Roos (2005) and from Palmatier, Dant, and Grewal (2007). These items measured calculative commitment and affective commitment. In section three, the two dependent variables, opportunistic behavior and collaborative innovation, were measured by using items adapted from Heide, Wathne, and Rokkan (2007) and from Wang et al. (2008). Section four was made up of three items derived from Cannon and Homburg (2001) to measure substitutability. All of the items in the questionnaire used a 7-point Likert-type scale (1 = strongly disagree to 7 = strongly agree). The measurement items for the key constructs are presented in Table 1. To estimate the quality of the information provided by the respondents, several items were added in the last section of the questionnaire to provide a post hoc check of the respondents’ knowledge concerning relational governance of their tourism partners.

Harman’s single-factor test was used to assess the common method variance. The test loaded all of the constructs in an exploratory factor analysis (EFA) procedure. Common method variance is considered to be present if a single factor emerges from the data, or if one general factor explains the majority of the variance (Podsakoff et al. 2003). Results indicated that six factors explained 70% of the total variance, with the first factor accounting for only 28.4% of the total variance (<50%), which suggested that common method variance was not a pervasive issue in the data.

Results

Measurement Model

Relational norms were conceptualized as a second-order construct comprising flexibility norms, information exchange, and solidarity norms. To measure the soundness of relational norms, second-order confirmatory factor analysis (CFA) was first conducted (Rindskopf and Rose 1988). The results indicated a three-factor structure with an acceptable fit to the data (χ² = 81.12, df = 24, p < 0.001, comparative fit index [CFI] = 0.95, goodness-of-fit index [GFI] = 0.95, Tucker-Lewis index [TLI] = 0.92, root mean square error of approximation [RMSEA] = 0.07). The average scores of the three first-order factors were used as indicators of relational norms in the measurement and structural models.

Following the guidelines of Anderson and Gerbing (1988), we conducted CFA to examine the reliability and validity of all the main constructs and assess the overall model fit before testing the structural model. The skewness and kurtosis indices for the scale items were within the recommended absolute values of 3 and 8, respectively. Therefore, the normality assumption was not violated, and subsequent analyses could be performed (Kline 2011). The CFA analysis provided the following results: χ² = 290.81, χ²/df = 2.42, p < 0.001, CFI = 0.94, GFI = 0.92, TLI = 0.93, RMSEA = 0.06, indicating that the proposed model displayed a satisfactory fit to the data (Byrne 1998).

The reliability and validity of the constructs were then further assessed. As shown in Table 1, the Cronbach’s alpha values for all of the constructs were between 0.73 and 0.87, exceeding the recommended value of 0.70 (Nunnally 1978). For each construct, the composite reliability estimates were above the recommended threshold of 0.70, indicating that the measures were reliable (Fornell and Larcker 1981). The standardized factor loadings for all of the variables were greater than 0.50 and significant (the t values were between 10.00 and 17.93, p < 0.001). The AVE for each construct was above 0.50. These values offered strong support for the scale’s convergent validity (Fornell and Larcker 1981; Hair et al. 2013). The square-root values of the AVE for each construct were greater than the correlation coefficients between any pair of the latent variables, which provided strong evidence of discriminant validity (Hair et al. 2013).

Structural Model

SEM was performed using SPSS AMOS 20.0 to test the hypothesized relationships between the variables. Overall, the structural model demonstrated a good fit with the data (χ² = 250.00, χ²/df = 2.98, p < 0.001, CFI = 0.93, GFI = 0.91, TLI = 0.91, and RMSEA = 0.07 < 0.08).

As shown in Table 2, the results of the structural model indicated that relational norms had significant positive effects on calculative commitment (β = 0.66, t = 7.91, p < 0.001) and affective commitment (β = 0.80, t = 8.85, p < 0.001). Calculative commitment was found to have significant positive effects on the partners’ opportunistic behavior (β = 0.16, t = 1.98, p < 0.05) and on the collaborative innovation (β = 0.22, t = 3.14, p < 0.01). Affective commitment was found to have a significant negative effect on the partners’ opportunistic behavior (β = −0.24, t = −3.02, p < 0.01) and a significant positive effect on the collaborative innovation (β = 0.50, t = 6.37, p < 0.001). Thus, hypotheses 1a, 1b, 2a, 2b, 3a, and 3b were supported.

Table 2.

Results for the Hypothesized Model.

Hypothesized Path	β	t Value		Results
Hypothesis 1a: RN-CC	0.66	7.91***		Supported
Hypothesis 1b: RN-AC	0.80	8.85***		Supported
Hypothesis 2a: CC-OB	0.16	1.98*		Supported
Hypothesis 2b: AC-OB	−0.24	−3.02**		Supported
Hypothesis 3a: CC-CI	0.22	3.14**		Supported
Hypothesis 3b: AC-CI	0.50	6.37***		Supported
Mediating effect	β	SE_Boot	95%CI
Hypothesis 4a : RN-CC-OB	0.16	0.05	0.07, 0.26	Supported
Hypothesis 4b : RN-AC-OB	0.02	0.07	−0.10, 0.16	Rejected
Hypothesis 5a : RN-CC-CI	0.07	0.04	0.00, 0.15	Supported
Hypothesis 5b : RN-AC-CI	0.12	0.05	0.03, 0.24	Supported

Note: RN = relational norms, CC = calculative commitment, AC = affective commitment, OB = opportunistic behavior, CI = collaborative innovation.

p < 0.05, **p < 0.01, ***p < 0.001.

Mediating Effect of Relationship Commitment

A bootstrapping method with bias-corrected 95% confidence intervals and 5,000 iterations was used to test the mediating effects of relationship commitment (Hayes, Montoya, and Rockwood 2017; Preacher and Hayes 2008). If the confidence interval did not include zero, then the indirect effect was significant, and the mediation effects were established (Zhao, Lynch, and Chen 2010). As shown in Table 2, the indirect effects of relational norms on opportunistic behavior and on collaborative innovation through calculative commitment were significant (β = 0.16, SEboot = 0.05, CI = 0.07 to 0.26; β = 0.07, SEboot = 0.04, CI = 0.01 to 0.15). The indirect effects of relational norms and collaborative innovation through affective commitment were also significant (β = 0.12, SEboot = 0.05, CI = 0.03 to 0.24). These results showed that the direct effects of relational norms on opportunistic behavior and collaborative innovation were significant as well (β = −0.56, p < 0.001; β = 0.54, p < 0.001), which suggested a partial mediating effect. Therefore, hypotheses 4a, 4b, and 5b were supported.

However, the mediating effect of relational norms on opportunistic behavior through affective commitment was insignificant (β = 0.02, SEboot = 0.07), with a 95% confidence interval based on 5,000 bootstrap samples including zero (−0.10 to 0.16). Thus, hypothesis 5a was rejected. In summary, calculative commitment significantly mediated the effects of relational norms on opportunistic behavior and collaborative innovation, but affective commitment significantly mediated only the effect of relational norms on collaborative innovation.

Moderating Effect of Enterprise Substitutability

Hierarchical regression analysis was conducted using SPSS 16.0 to examine the moderating effects of the tourism enterprises’ levels of substitutability on the relationship between relational norms and the types of commitment. As suggested by Aiken and West (1991), we mean-centered the independent and moderator variables to minimize the possibility of multicollinearity. The results of the hierarchical regression analysis are shown in Table 3. The first model (model 1) included relational norms and calculative commitment variables, and its explained variance was significant (R² = 0.20, p < 0.001). The interaction between relational norms and substitutability was added in model 2, which significantly increased the model’s explanatory power (F change = 5.93, p < 0.05). The third model (model 3) included relational norms and affective commitment variables, and its explained variance was significant (R² = 0.33, p < 0.001). The interaction between relational norms and substitutability was added in model 4, which significantly increased the explanatory power of the model (F change = 4.07, p < 0.001). In each of the regression models, the variance inflation factors (VIFs) were well below 4, which verified that multicollinearity was not a problem in these analyses (J. Miles and Shevlin 2001).

Table 3.

Results of Hierarchical Regression Analysis.

Variables	Calculative Commitment		Affective Commitment
Variables	Model 1	Model 2	Model 3	Model 4
Relational norms	0.52***	0.53***	0.63***	0.62***
Substitutability	−0.11***	−0.09***	−0.32***	−0.34***
Relational Norms × Substitutability		−0.14**		0.11*
R ²	0.20	0.22	0.33	0.34
F change	50.62	5.93*	94.97	4.07*

p < 0.05, **p < 0.01, and ***p < 0.001.

As shown in Table 3, the regression coefficients for the interaction between relational norms and substitutability in models 2 and 4 were significant (b = −0.14, p < 0.01; b = 0.11, p < 0.05). The results suggested that the enterprise’s substitutability had a negative moderating effect on the relationship between relational norms and calculative commitment and a significant positive moderating effect on the relationship between relational norms and affective commitment. Thus, hypotheses 6a and 6b were supported.

To aid interpretation, we used unstandardized regression coefficients from Models 2 and 4 to plot the links between relational norms and commitment at high and low levels of substitutability. The results, as depicted in Figure 2, were consistent with the hypotheses.

Figure 2.

Relational norms and relational commitment at different levels of substitutability.

Discussions and Implications

In response to calls for further investigation into the effects of relational norms, we proposed and tested a model that integrated relational norms, commitment, relationship performance, and substitutability. We found consistent support that relational norms are a mixed blessing. The partner’s types of commitment and the enterprise’s levels of substitutability were found to specify why and when the benefits or costs of relational norms occur. By doing so, this study has provided an important insight regarding the paradox faced by enterprises that engage in relational governance. Below, we discuss the main conclusions of this study and offer several implications for managers of tourism enterprises.

Effects of Relational Norms: Collaborative Innovation versus Opportunism

Although collaborative innovation is critical for the success of tourism enterprises and opportunistic behavior is a concern in tourism-based collaborative relationships, few empirical studies on tourism have investigated the effects of relational governance on opportunistic behavior or on collaborative innovation. In line with previous research, this study confirms that relational governance has both “bright sides” and “dark sides.” Relational norms help to increase both the calculative and affective forms of commitment between tourism business partners, and both of these types of commitment help to promote collaborative innovation. Furthermore, although relational norms tend to reduce opportunistic behavior or tourism partners through affective commitment, relational norms are likely to enhance the opportunistic behavior through calculative commitment.

Whether relational norms promote collaborative innovation, reduce opportunistic behavior, or enhance opportunistic behavior depends on the paths of the linked commitment types of the tourism partners. From the data analysis, we can identify four paths of influence. In the first and second paths, relational norms enhance the calculative commitment of tourism partners and promote collaborative innovation, but they also increase opportunistic behavior. In the third and fourth paths, relational norms enhance the affective commitment of tourism partners, thereby reducing their opportunistic behavior and promoting collaborative innovation. The first two paths explain why relational norms sometimes fail to work, and the latter two paths explain why relational norms function as effective governance mechanisms in collaborative relationships. Williamson has emphasized that “commercial relations are invariably calculative, and the concept of calculated risk should be used to describe commercial transactions” (Williamson 1996, p. 97). When combined with this perspective, our results indicate that in the real business world, opportunism is to be governed by mechanisms other than relational norms. This finding is also consistent with that of Gilliland and Bello (2002), who showed that when tourism partners are committed to a collaborative relationship primarily for economic or instrumental reasons, a keen awareness of the mechanisms for resolving social disputes is necessary for enterprises.

Mechanisms Linking Relational Norms to Collaborative Innovation and Opportunism

Although relational governance has been investigated in many studies, constructs such as commitment have been left out and need to be investigated further. The results from our research generally substantiate the importance of commitment as a mediator that links one actor’s treatments and actions of other actors in interfirm relationships (e.g., Palmatier, Dant, and Grewal 2007). The findings of this study further indicate that the affective and calculative forms of commitment should be treated separately, as these types of commitment play different mediating roles. Relational norms tend to increase a partner’s opportunistic behavior and promote collaborative innovation via calculative commitment. However, affective commitment has a significant mediating effect only on the relationship between relational norms and collaborative innovation. Although relational norms are positively related to the partner’s affective commitment and affective commitment has a negative effect on the partner’s opportunistic behavior, affective commitment does not mediate relational norms and opportunistic behavior. These findings indicate the need for further exploration of the underlying mechanisms by which relational norms can reduce opportunistic behavior. As Jap and Ganesan (2000) and R. M. Morgan and Hunt (1994) have already explored the mediating role of commitment in relationship marketing, the results of our study may be seen as an advancement of their findings.

The Boundary Conditions of Relational Norms

To consider the structures of the relationships through which businesses exchange resources (as opposed to just assessing relationship quality), this study investigates the role of substitutability, which is a critical structural element affecting relational governance. The consideration of relationship structures sheds light on the boundary conditions of relational norms, and it helps to specify how tourism enterprises leverage the governance mechanisms to mitigate costs and increase gains in different contexts.

As the findings of this study indicate, the substitutability of a tourism enterprise moderates the relationship between relational norms and commitment. On the one hand, the substitutability of the tourism enterprise strengthens the relationship between relational norms and affective commitment. On the other hand, increased substitutability tends to weaken the relationship between relational norms and calculative commitment. In other words, when a collaborative relationship is governed through relational norms, the substitutability of the tourism enterprise determines the relative prominence of the two types of relationship commitment. Then, the predominance of either the affective or the calculative type of commitment may lead to different behavioral outcomes.

Managerial Implications

The results of this study provide several implications for managers of tourism businesses, especially those who are responsible for partner management.

First, we suggest that tourism enterprises must know and respond to their partners’ attitudes and subsequent actions with regard to specific governance mechanisms. In particular, tourism enterprises that rely on relational norms to govern their interfirm relationships should know that some types of commitment can lead to negative outcomes. If the tourism enterprise makes use of misplaced commitment, collaborative outcomes may be undermined. Specifically, the management strategies adopted by tourism enterprises should encourage their partners to make affective commitments to the relationship and thereby improve the efficiency and effectiveness of the interaction.

Second, this study indicates that a trade-off between potential costs and benefits should be made when designing governance mechanisms. Calculative commitment arising from relationship governance tends to increase rather than curb opportunistic behavior. A tourism partner, even one that is committed to the relationship, may struggle with various aspects of coordination and self-control. Nevertheless, it is still beneficial for a tourism enterprise to implement relational norms in promoting collaborative innovation with external partners.

Another important managerial implication for tourism enterprises concerns the necessity of a match between relational governance and the level of substitutability. For tourism enterprises with higher substitutability, relational norms serve to reduce a partner’s economic motivations and help to develop commitment that is based on emotional ties. Such ties in turn reduces opportunism and promotes collaborative innovation. This insight is especially important for SMEs. In the tourism industry, SMEs constitute the “life blood of the travel and tourism industry world-wide” (Erkkila 2004, p. 23). For tourism SMEs with relatively high substitutability, building and using relational norms may be a good strategy. For tourism enterprises that operate at the center of the power structure and have low substitutability, the risk of opportunism must be taken seriously, as relational norms commonly lead to calculative commitment, which may encourage opportunistic behavior from partners.

Limitations and Future Research

The results of our study should be interpreted with caution, because of a number of potential limitations. First, although the conceptual model proposed in this study has a solid theoretical foundation, the study used a cross-sectional research design, which could only demonstrate correlations between the corresponding variables. The causal relationships between the variables should be further confirmed using longitudinal research designs. Second, only the self-reported opinions of the tourism partners were collected for this study. The roles of the investigated enterprises were defined by their partners, and these subjects may have deliberately concealed facts about their own levels of opportunism and commitment. Although the researchers emphasized the academic use of the survey and provided assurance of anonymity, the participants’ openness may still have been limited. Third, this study used convenience sampling, which can lead to sampling bias and limit the generalizability of the results. Future studies should use a random sampling procedure with a larger sample. Additionally, the survey was conducted in China, and therefore the results may not allow the model to be generalized to other countries. Furthermore, because of the problem of equivalent models, it should be pointed out that the suggested model in this study is only one of several possibilities. Other paths between relational norms, commitment, and collaborative performance, in addition to other variables such as trust and satisfaction, should be considered when exploring the mechanisms of relational norms in future research.

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 paper was supported by the Chinese National Science Foundation (41471467;41801213;41771144).

ORCID iD

Huang Xiang

Author Biographies

Chen Gezhi is an Assistant Professor in the Department of Business Administration, Guangdong University of Finance, China. Her research fields are hospitality management, tourism enterprises management, and tourism sustainable development.

Liu Jingyan is a Professor and the associate dean in the School of Business, Sun Yat-sen University, China. Her research fields are ecotourism, sustainability and tourism, and tourism enterprises management.

Huang Xiang is a Research Professor in the School of Tourism Management and the director of South China Ecological Civilization Research Center, South China Normal University. His research fields are ecotourism, tourism geographies, and tourism enterprises management.

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