1. Introduction
In recent years, the number of sharing economy business models has increased dramatically and great interest has been raised in the potential of these models to create sustainable value [1]. To study the motivation of sustainable value creation in the sharing economy, we need to consider its value creation mode. Essentially different from the traditional economy, the sharing economy is about the value co-creation between users [2], Benoit et al. believe that the sharing economy tend to have more value co-creation than the traditional economy [3]. Breidbach and Brodie point out that sharing economy model is a process in which enterprises promote and coordinate value co-creation among interdependent economic actors by participating in platform activities [4]. Customer’s sustainable value co-creation behavior is an important driving force for the sustainable development of the sharing economy. At the same time, with the new model of the sharing economy, the mechanism of value co-creation under the traditional economic background has changed, and customers want to take control of their own value co-creation activities [5]. Therefore, it is of great significance to study the factors that affect customers’ value co-creation behavior in the sharing economy model to explore the motivation for sustainable value creation in the sharing economy.
Value co-creation is a process of interaction among economic actors [6]. Value co-creation of the sharing economy is different from that of the traditional economy. It includes the value co-creation of customers, service providers and sharing platforms, namely the enterprises [7]. At present, for the study of value co-creation of the sharing economy, one group of researchers refer to the traditional model, and divide the participants of value co-creation into providers and customers. The providers include platform providers and peer service providers [8,9]. Another group of researchers divide customers of the sharing economy into Supplier Customers and Demander Customers [10]. According to the “Customer Independent Value Creation” theory proposed by Grönroos and Voima in 2013 [6], the value co-creation of the sharing economy is the value co-creation of both Supplier customers and Demander customers, namely created by customers [7,11]. In their study, both groups of researchers take Demander customers as one side of the sharing economy and other actors as the other, and then study the value co-creation based on the interactions between the two sides of product and service transactions, but this model is insufficient for the multilateral relationship of the sharing economy.
In addition to transactional relationships, the sharing economy differs from traditional economies in mutual relations within its system [12]. Platform operators are the intermediaries and organizers in the sharing economy system, while customers are the participants [10]. The customers include Supplier customers, or Peer Service Providers, and Demander customers. The differences between this paper and previous literature are mainly reflected in two aspects: firstly, the two subjects of the sharing relationship, the organizer, namely the enterprise, and the participant, namely the customer, are distinguished by the relationship between the organizer and the participant, rather than the buyer-seller relationship. Secondly, this paper pays more attention to the influence of social attributes rather than economic attributes on customer participation in value co-creation behavior.
This paper studies how the identity of the enterprise as the intermediary between buyers and sellers affects the value co-creation behavior of consumers in the sharing economy model. Secondly, in this study, Suppliers of products or services in the sharing economy are also regarded as the consumers of the platform. Similar to Demanders, the subject of consumer value co-creation in the sharing economy is affected by other factors.
This study is mainly carried out from the following contents: sorting out the important theories of the sharing economy and value co-creation; detailing the research methods, analysis process and results of this paper; putting forward the research significance and suggestions of this paper.
2. Previous Literature
2.1. The Sharing Economy
The “sharing economy” was first proposed as a phenomenon by American scholars in Social Structure and Collaborative Consumption [13]. In 2008, with the development of information technology, “sharing economy” was first mentioned as a term, meaning “collaborative consumption formed by sharing, exchanging and renting resources without owning them” [14]. In recent years, with the rapid development of cloud computing, big data, the Internet of Things and mobile internet, the efficiency of market information transfer and the speed of resource circulation have increased dramatically, and the ownership and use of products are increasingly separated [15]. As a new economic model, the sharing economy integrates a large number of idle resources of suppliers through Internet technology to meet the diversified demands of the market [16]. Botsman proposed that the sharing economy in the Internet era could be divided into three stages [17]. The first phase is the code sharing, such as Linus, etc. The second stage is the online sharing of life information, such as YouTube or Facebook. The third stage is the sharing of offline assets, such as Uber’s ride sharing and Airbnb’s home stay sharing.
The sharing economy is based on individuals sharing [18], and relies on a platform [19] where the right of domination is separated from the right of use [15]. Compared to the traditional economic model where there are two subjects: the enterprise and the customer, the subjects of the sharing economy have become three: the platform provider, the provider (peer service provider), and the customer (consumer) [3]. In this paper, which is based on Ranjbari M, et al.’s views, the sharing economy is divided into two subjects: the enterprise, namely the platform operator, and the consumer, which includes the Supplier consumer and the Demander consumer [10]. The sharing economy is usually associated with sustainability, which is one of the motivations for customers to use the sharing economy [20].
2.2. Value Co-Creation
Modern value co-creation theory can mainly be divided into two schools; one is the value co-creation model proposed by Prahalad and Ramaswamy [21], based on customer experience value, and its basic views can be summarized as follows: 1. joint creation of consumption experience is the core of customers and enterprises’ value creation; 2. the interaction of participants is the basic way to realize such value co-creation. The other school is the value co-creation model based on the ‘service-led logic’ proposed by Vargo and Lusch [22]. Its basic viewpoints are as follows: 1. value co-created no longer focuses on value exchange but on value-in-use; 2. value-in-use is the value created by the interaction between customers and producers during the consumption of products or services; 3. as resource integrators, customers create value by integrating and utilizing various resources, and value is continuously and dynamically formed with customers’ consumption and interaction activities.
Both of the two theories mentioned above are based on the traditional economic model and contain the following characteristics: 1. value co-creation is based on the binary relationship between enterprises and customers; 2. ownership of products or services is transferred between the two; 3. participants of value co-creation are either the providers or demanders of products or services. However, in the sharing economy, the ownership of products or services is usually not transferred between the main participants: enterprises and customers. Instead, they play the role as ecological organizers and participants with more social attributes.
As for the specific behaviors of value co-creation, Yi and Gong divided the value co-creation behavior into customer engagement behavior and customer citizenship behavior. Customer engagement refers to customers’ behaviors such as information seeking, information sharing, responsible behaviors and personal interaction. Customer citizenship behavior includes four parts: feedback, advocacy, helping and tolerance [23]. Yoon, S.J. divided value co-creation behavior into helping, engagement and advocacy in terms of customer-oriented, enterprise-oriented and interactive behaviors [24]. Yoon, S.M., Lee, Y. and Kim, I. classifies engagement as a leading factor of value co-creation behavior [25,26].
This paper studies the value co-creation behavior in the corporates-customer relationship. In the sharing economy, enterprises usually act as platforms and intermediaries instead of actual offline service providers. Therefore, based on the above literature, the customer value co-creation behavior studied in this paper includes feedback, advocacy and helping. Advocacy refers to recommending the business, whether conducted by the enterprises or the employees, to others, such as friends or family. Feedback includes solicited and unsolicited information that customers provide to the employee, which helps employees and the firm to improve the service-creation process in the long run. Helping refers to customer behavior aimed at assisting other customers [23].
As for the factors influencing customer value co-creation behavior in the traditional economic mode, there have been a number of research papers on the participants of value co-creation: customers and corporates. Corporate brand symbolic values [27], customer factors, customer social capital [28] and customer citizenship [29] are both considered to have an impact on customer value co-creation activities. The above study shows that customer value co-creation, as an activity with social attributes, is not only related to economic interests, but also related to the social characteristics of the relevant economic actors, namely corporates and customers. However, most of the existing research is based on the traditional economic model, and there is little research focusing on the factors influencing the value co-creation of the sharing economy.
2.3. Corporate Ethical Management
“Ethics” refers to the standard system that judges right and wrong, good and evil, moral and immoral behaviors [30], and “ethical management” refers to the application of ethical standards to corporates’ decision-making and implementation [31]. Especially when matching people with the help of artificial intelligence, the ethics of the platform operator can have a direct impact on the matching results [32]. A corporation’s ethical attitude refers to a corporation following the legal and ethical principals of right, good and just in its business activities [33]. It means that the members of an enterprise, as kindhearted citizens, attach importance to the relationship with customers, employees, and the core stakeholders of the community, and comply with relevant laws in their business activities.
Generally, ethical management can be evaluated from five aspects, including ethical leadership of managers, operation of dedicated organizations for ethical management, establishment and education of ethical management norms, ethical management practice, and contribution to the community [34]. Operation of dedicated organizations for ethical management, establishment and education of ethical management norms are the pre-factors of ethical management achievements and also the internal factor of a corporate. These theories are relevant to our study, which aims to analyze the impact of customers’ perception of corporate ethical management on their value co-creation. Therefore, the ethical management referred to in this study includes leadership, practice and contribution.
2.4. Corporate Authenticity
Authenticity refers to showing the true self that is not hidden; it means being factual, true, sincere, original and consistent with words and deeds [35], and consistent with the appearance. It is a credible character and an important component of corporate governance [36]. Corporate authenticity is related to product authenticity [37], business legitimacy [38], and apparent authenticity of various corporate behaviors [39]. At present, the academic circle has regarded corporate authenticity as a positive factor of enterprise management and an important variable of customer relationship management, and has carried out plenty of research on its importance [40]. In this study, corporate authenticity refers not only to satisfaction with commercial motives, but also the pursuit of the continuous value of customers [41], including consistency, customer orientation and consistency [42], as well as truth and integrity [43]. In particular, service customer orientation is an important factor for the sustainable development of enterprises [44].
2.5. Corporate Image
The concept of corporate image was put forward in western developed countries at the beginning of the last century and has been widely recognized. There is not much dispute between the academic and business circles on the core definition, and both agree that corporate image refers to the comprehensive feeling brought by an enterprise [45]. At the same time, it believes that corporate image has a broad impact on customer behavior [46]. The corporate image in this study is composed of reputation [47] and credibility [48] according to the views of Pina, J.M., Martinez, E., Chernatony, L.D. and Drury, S. [49].
2.6. Customer Citizenship
Customer citizenship originally refers to the national rights and qualifications demanded by individuals and the national responsibilities and obligations demanded by individuals [50]. However, with the development of society, the integration of social economic and political issues, and the gradual rise in private consumption to the level of public issues, the social requirements of customers has also increased the level of social responsibility. Customers not only have significance for the transaction of funds and the use of products and services, but they also have significance for their feedback on the results after use as well as the social impact and indirect economic value brought by the results [51]. Citizenship includes the sense of autonomy, community, and participation. The sense of autonomy refers to the ability or qualification to choose what is meaningful to the individual. The sense of community refers to alleviating contradictions and blind competition among members and maintaining the collective centrality of the community. The sense of participation refers to participatory action through mutual dialogue and collective action [52,53].
2.7. Customer Social Capital
Social capital refers to the social network, norms, and mutual trust that enable the members of a social community to cooperate and interact with each other [54]. In 2002, the Performance and Innovation Unit of the British Cabinet Office classified social capital into two categories: bonding and bridging [55]. Bonding social capital can be considered as the social networks between members of homogeneous groups, while bridging social capital can be considered as the networks between members of heterogeneous groups. Social capital is a source that promotes individual or collective action and an asset that a person can obtain from his social network [56]. Customer social capital reflects both individual and collective interests of customers [57]. General resources are consumed, while social capital is continuously formed through the interaction and relationship between social members. With the complexity of society and the differentiation of social relations, people pay more attention to social capital [58]. The formation of the sharing economy system cannot depend only on a certain customer or a few customers. Only the continuous participation of a large number of customers can ensure the continuous operation of the sharing economy system. Social capital is an important factor affecting customer citizenship behavior in the sharing economy [59], and social capital could explain intrinsic motivation, which includes enjoyment and sustainability motivation [60].
2.8. Customer Self-Monitoring
Self-monitoring refers to the idea that individuals differ in the extent to which their behaviors are influenced by situational cues rather than their inner states [61]. In order to gain recognition from others in interpersonal relationships, people observe, control and manage their own images and their impressions on others [62]. Snyder believed that people with high self-monitoring and those with low self-monitoring could be divided according to different situations [63]. People with high self-surveillance are more concerned about how others look at them and are sensitive to how they are accepted by others, while those with low self-surveillance are not determined by others but by their own attitudes, feelings and personalities. Since the 1980s, there have been many studies on self-monitoring as a variable that can predict customers’ attitudes and behaviors. Under the traditional economic model, scholars mainly studied the influence of self-surveillance on customers’ behaviors. For example, studies have found that customers with high self-monitoring tend to buy products for social reasons rather than practical ones [64]. Customers with a high capacity for self-monitoring are more conscious of the brands of products than those with low self-monitoring [65]. The degree of self-monitoring determines whether customers pay more attention to product internality or brand image [66]. In online communities, customers with high self-monitoring are more willing to manage their own image and behavior [67]. As for the value co-creation under the traditional economic model, customers’ self-monitoring has a positive influence on the process of value co-creation promoted by enterprise factors and customers’ personal factors [53].
2.9. Hypothesis Development
As mentioned above, this paper studies the factors that affect the value co-creation behavior in the corporate-customer relationship under sharing economy. Referring to relevant research, this paper divides the influencing factors into corporate characteristics and customer characteristics for analysis, and puts forward several hypotheses.
2.9.1. The Influence of Corporate Characteristics on Customer Value Co-Creation Behavior
In the sharing economy system, enterprises do not directly provide offline services, and their impact on customer behavior depends more on the characteristics of the enterprises. Among others factors, corporate ethical management can positively contribute to the growth of customers [34], improve the customers’ perception of the corporate image, and thus enhance their trust in the enterprises [68]. The integrity behaviors of enterprises are an important influencing factor in promoting customer engagement in related activities [69]. On the technology platform provided by the enterprise, the combination of dialogue, access and transparency enable customers to assess the risk and benefits of being active co-creators [70]. Technology enterprises can, within the platform, use IT to enable or prevent social interaction and resource integration, which are important components of value co-creation behavior [71]. Enterprise authorities can increase customers’ liking for the brands and positively promote the customers’ evaluation of enterprises [72,73]. A good corporate image will positively promote customer behavior, by which customers can achieve value co-creation through further influencing other customers’ perception of the brand [74]. Unlike the traditional economic models, in the sharing economy, the characteristics of enterprises inherently have a greater impact on customers’ participation in the sharing system as well as on the value co-creation [2]. Therefore, the following hypotheses are proposed in this paper:
Corporate ethical management has a significant positive impact on customer value co-creation activities.
Corporate authenticity has a significant positive impact on customer value co-creation activities.
Corporate image has a significant positive impact on customer value co-creation activities.
2.9.2. The Influence of Customer Characteristics on Customer Value Co-Creation Behavior
In the sharing economy model, operators attract customers including Supplier customers and Demander customers through the construction of platforms, forming an online sharing community. Enterprises are the makers and initiators of the rules of the online community, and customers are the members of the online community. On the one hand, between enterprises and customers, citizenship determines customers’ attitude towards corporate activities [29]. Social capital can induce customers’ enthusiasm to participate in activities [75]. On the other hand, among members, social capital can promote the self-value awakening of customers in the community and enhance the belief that they can make contributions to the community [57]. Common values and goals make members connected and more likely to cooperate actively [76]. In online communities, social capital can promote customers’ behaviors such as content sharing, communication and interaction [77]. Therefore, the following hypotheses are proposed in this paper:
Customer citizenship has a significant positive impact on value co-creation activities.
Customer social capital has a significant positive impact on value co-creation activities.
2.9.3. The Moderating Role of Customer Self-Monitoring
As a moderating variable, self-monitoring has been widely applied in various customer behavior studies [78]. The higher self-monitoring customers have, the more sensitive they are to social norms, and the more they will make decisions on their own behaviors based on the surrounding situation [79]. On the contrary, the lower the self-monitoring, the more they will make such decisions according to their own hearts [80]. Therefore, people with low self-monitoring have a higher consistency between their own attitudes and behaviors than those with high self-monitoring [81]. Under the sharing economy model, customers with a low sense of ownership will relax their constraints, while customers with high self-monitoring will adjust themselves to meet the needs of the sharing community [82]. Therefore, the following hypotheses are proposed in this paper:
Customer self-monitoring plays a moderating role in the influence of corporate characteristics and customer characteristics on value co-creation behavior. The stronger the customer self-monitoring is, the greater the influence of corporate ethical management, corporate authenticity, corporate image, customer citizenship and social capital on customer value co-creation.
Based on the hypotheses presented in Section 2.9, we present a research model as shown in Figure 1 to analyze the influencing factors between variables. The model in Figure 1 applies equally to both Supplier customers and Demander customers of sharing economy services. In Section 4, we show how the two models can be linked through an integrated model.
3. Method
3.1. Development of Measurement Tools
In this study, we select appropriate research variables through the analysis of previous literature. In order to ensure the content validity of variable measurement items, only the measurement items verified in previous literature were selected. At the same time, in order to ensure the applicability of the measurement project in Malaysia, we conducted a structured interview with eight Malaysian Airbnb users. These users are mainly college graduate students and recommended peripheral friends, including two Airbnb landlords and six Airbnb tenants. The interview contents of the two types of objects are the same. During the interview, we first introduced the research background, relevant concepts and the exact meaning of the questions in the questionnaire, and then listened to their understandings and answers to the questionnaire. Based on the opinions of the interviewees, the questionnaire was modified and the final questionnaire was formed, as shown in Table 1.
3.2. Data Collection and Sample Characteristics
Affected by the epidemic, the final questionnaire survey was commissioned to be completed online from March to May 2022. The survey agency randomly released a screening questionnaire, in which respondents filled in whether they had used Airbnb, both as a landlord and a tenant, without knowing the screening conditions. Respondents who met the condition of ‘have used Airbnb’ could continue to complete the formal questionnaire. When the number of respondents which met the conditions reached 700, the random distribution of online questionnaires would be stopped. Then, 700 questionnaires were screened for the rationality of completion time and completion situation, and 587 valid questionnaires were obtained.
4. Results
4.1. Survey Sample Properties
Table 2 shows the descriptive statistics of Airbnb consumers. Tenant proportion (62.5%) was higher than that of landlord (37.50%). The majority (69.3%) of consumers are female. The ethnic backgrounds of the participants included Malay (34.4%), Chinese (41.4%), Indian (8%) and Other (16.2%).
4.2. Measurement
The Cronbach’α coefficient of the EM scale is 0.858. The Cronbach’α coefficient of the CA scale is 0.914. The Cronbach’α coefficient of the CI scale is 0.906. The Cronbach’α coefficient of the CC scale is 0.883. The Cronbach’α coefficient of the CSC scale is 0.895. The Cronbach’α coefficient of CSM is 0.891. The Cronbach’α coefficient of the VVC scale is 0.854. See Table 3 for details.
4.3. Confirmatory Factor Analysis
In this study, the discriminant validity of EM, CA, CI, CC, CSC, VVC and CSM is tested by confirmatory factor analysis. Since the EM, CC and VVC scales are composed of three dimensions, and the CSC scales are composed of two dimensions, in order to reduce errors, improve the degree of commonality, stability and fitting index of parameter estimation, and avoid excessive complexity of the overall measurement model, this study adopts the internal consistency item packaging method, and applies the mean values of EM, CC, CSC and VVC as measurement indexes. Based on the seven-factor model, six alternative models are proposed. For the seven-factor model, 2/df = 1.845, RMSEA = 0.038, SRMR = 0.033, CFI = 0.955, TLI = 0.950, the model fitting degree reaches the judgment standard, and is better than the other models, which indicates that the discriminating validity among variables is better. See Table 4 for details.
4.4. Common Method Deviation Bias Test
Common method bias is tested by Harman single factor method. The results show that the explained variance ratio of the first common factor obtained by unrotated exploratory factor analysis is 19.024%, which is lower than 40%, and the model fitting by confirmatory factor single factor is 2/df = 11.704, RMSEA = 0.135, SRMR = 0.152, CFI = 0.402, TLI = 0.362. The model fitting is far lower than the judgment criteria, so the common method bias has little influence on the research results.
4.5. Correlation Analysis
Table 5 shows the mean value, standard deviation and correlation of EM, CA, CI, CC, CSC, CSM and VVC. EM is significantly positively correlated with VVC (r = 0.403, p < 0.05), CA is significantly positively correlated with VVC (r = 0.438, p < 0.05), CI is significantly positively correlated with VVC (r = 0.354, p < 0.05), CC is significantly positively correlated with VVC (r = 0.474, p < 0.05), CA is significantly positively correlated with VVC (r = 0.438, p < 0.05). CSC is positively correlated with VVC (r = 0.286, p < 0.05). So, the hypothesis is tentatively supported.
4.6. Structural Model Testing
In this study, the structural equation model is applied to test the hypotheses. As is shown from Table 6 and Figure 2, the structural equation model fits well (2/df = 2.174, RMSEA = 0.045, SRMR = 0.035, CFI = 0.946, TLI = 0.939), EM has a significant positive effect on VVC (β= 0.252, p < 0.001). CA has a significant positive effect on VVC (β = 0.271, p < 0.001). CC has a significant positive effect on VVC (β = 0.366, p < 0.001). CI has a significant positive effect on VVC (β = 0.201, p < 0.001). CSC has a significant positive effect on VVC (β = 0.160, p < 0.01).
4.7. Moderating Effect Test of CSM
In this study, hierarchical regression analysis is used to test the moderating effect of CSM. First, all variables are standardized; second, demographic variables to VVC regression analysis; third, demographic variables, independent variables to VVC regression analysis; fourth, demographic variables, independent variables, moderating variables to VVC regression analysis; finally, the interaction term of independent variable and moderating variable is introduced into the regression equation, and the value of R² and p are observed. If R² becomes significantly larger or the interaction term p value reaches the significance level, the moderating effect of the variable is proven.
As is shown in Table 7, compared with model 3, the R² of model 4 significantly increases after the interaction term of EM, CA, CI, CC, CSC and CSM (△R² = 0.050, p < 0.001), and the interaction term of EM and CSM has a significant positive effect on VVC (β = 0.089, p < 0.01). The interaction term of CA and CSM has a significant positive effect on VVC (β = 0.082, p < 0.05), the interaction term of CI and CSM has a significant positive effect on VVC (β = 0.082, p < 0.05), the interaction term of CC and CSM has a significant positive effect on VVC (β = 0.044, p > 0.05). The interaction term of CSC and CSM has a significant positive effect on VVC (β = 0.097, p < 0.01). Therefore, CSM has a positive moderating effect between EM, CA, CI, CSC and VVC, but not between CC and VVC.
In order to further explain the moderating effect of CSM on EM, CA, CI, CSC and VVC, this paper conducts a simple slope analysis and draws the regulatory map through PROCESS3.3 to show the direction and intensity of the regulating effect in a more intuitive way. As is shown in Table 8 and Figure 3, Figure 4, Figure 5 and Figure 6, the results of simple slope analysis show that when CSM value is higher, EM has a stronger positive effect on VVC (simple slope = 0.266, t = 6.010, p < 0.001), and CA has a stronger positive effect on VVC (simple slope = 0.287, t = 6.289, p < 0.001). CI has a stronger positive effect on VVC (simple slope = 0.234, t = 5.172, p < 0.001), while CSC has a stronger positive effect on VVC (simple slope = 0.204, t = 4.686, p < 0.001); when the CSM value is low, EM has no significant positive effect on VVC (simple slope = 0.087, t = 1.893, p > 0.05), CA has a weak positive effect on VVC (simple slope = 0.123, t = 2.693, p < 0.01). CI has no significant positive effect on VVC (simple slope = 0.071, t = 1.618, p > 0.05), and CSC has no significant positive effect on VVC (simple slope = 0.010, t = 0.815, p > 0.05). So, the hypotheses are proven again.
5. Conclusions and Discussion
5.1. Theoretical Implications
Under the background of multilateral participation in the sharing economy, this study regards both Supplier customers and Demander customers as customers, and analyzes the factors influencing the value co-creation of customers in the relationship between the organizers, namely the enterprises, and the participants, namely the customers of the sharing economy system and then establishes the relevant research model. By doing so, it fills up the deficiency of the previous research on the factors that affect the value co-creation of customers in the sharing economy model. At the same time, considering the different roles played by enterprises and service providers in the sharing economy system, this study focuses on the social characteristics of enterprises and customers, rather than the economic characteristics of products and services.
The following specific conclusions can be drawn from the empirical study:
In the sharing economy model, the platform operators no longer directly provide physical products or services. The ways in which they influence consumer participation in value co-creation are partially the same as in the traditional economic model, that is, the ethical business management, corporate authenticity, and corporate image all positively influence customer participation in value co-creation activities. This also confirms that the previous research findings [39,53] in the traditional economic model are also applicable to the sharing economy;
In the sharing economy model, Supplier consumers, similar to Demander consumers, will participate in value co-creation activities to various degrees under the influence of enterprise factors and its own factors in the interactions with the companies operating the sharing economy platforms. This is a change from the traditional economic model where only the Demander consumers participates in value co-creation activities.
When any Supplier participates in value co-creation activities as consumer, its civic awareness, social capital and self-monitoring also play an active role.
Consumer self-monitoring has a significant positive moderating effect on the process of corporate ethics, corporate authenticity, corporate image and customer social capital influencing customer value co-creation behavior.
5.2. Practical Implication
Most sharing economy platforms, including Airbnb, provide services to customers through mobile Internet apps. However, these platforms are different from other e-commerce APPs, because in addition to the quality of software products and offline services, which can be directly experienced by customers, the enterprises which operate the sharing platforms and the characteristic of customers themselves also have an important impact on the sustainable development of these sharing platforms. Therefore, in order to ensure such sustainable development, on one hand, enterprises need to pay more attention to their own business behaviors and images; and on the other hand, they need to establish certain mechanisms which lead to customers’ participation in the interaction with the enterprises.
5.3. Limitation Future Research Directions
This study has some limitations, and it is expected to be improved in future research. First of all, the samples collected from the questionnaire survey include different races such as Malay, Chinese, Indian, and they have different cultural backgrounds. However, this study does not take these background differences into consideration. Therefore, it is hoped that the analysis of different races will be included in the future research. Secondly, the measurement of enterprise factors in this study is based on customers’ perceptions rather than information provided by enterprises, so deviations between such perceptions and the real situation may exist. In future research, it is expected that more direct information will be added as supplementary material. In addition, further research from other perspectives will be carried out using the data obtained in this study.
Conceptualization: J.Z. Writing—original draft: J.Z. Data curation: Y.S. Writing—review & editing: Y.S. All authors have read and agreed to the published version of the manuscript.
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The authors declare no conflict of interest.
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Survey instruments.
| Variate | Measuring Item | N | Provenance | ||
|---|---|---|---|---|---|
| Ethical Management | Leadership | EML | Managements will to drive strong; support what is needed; ethical behavior on their own | 8 | [ |
| Practice | EMP | Transparency of business activities; fairness in external activities; responsible management | |||
| Contribution | EMC | Active in community service activities; active in donation and donation activities | |||
| Corporate Authenticity | CA | Adhere to core values; long-lasting; continuous operating results; use meaningful logos; historical heritage and spirit; genuine; distinct from other brands; unique products; attempted innovation | 9 | [ |
|
| Corporate Image | CI | Regarded; professionally successful; well-established; stable; trustworthy; dependable; concerned about customers | 8 | [ |
|
| Customer Citizenship | Autonomy | CCA | Make own plans; responsibility for action; judging by values | 3 | [ |
| Commonality | CCC | Sorry for the mistake; intent to help; compliance with basic order; cooperation in group activities | 4 | ||
| Engagement | CCE | Propose improvements; compliance with multiple decisions; participation in the election; tendency to run for a representative | 4 | ||
| Customer Social Capital | Bonding | CBO | Interested in a variety of activities; try new; interested in other people’s thoughts; a sense of community affiliation; everyone’s connection perception | 10 | [ |
| Bridging | CBR | Someone to trust; mentor presence; dialog object presence; referees presence; financial backers’ presence | |||
| Customer Self-monitoring | CSM | Easy to understand the feelings of others; consideration of others; sensitive to changes in others; it is easy to recognize other people’s faces; get along well with others | 5 | [ |
|
| Value co-creation | Feedback | VCCF | Provide useful information; comment to the provider of great service | 2 | [ |
| Advocacy | VCCA | Consider products when purchasing; product preferential selection; recommend products to others | 3 | ||
| Helping | VCCH | Willingness to cooperate; willingness to support policy; intention to provide continuous help; give suggestions | 4 | ||
Customer demographic information (n = 587).
| Item | Details | Frequency | Importance (%) |
|---|---|---|---|
| Gender | Male | 180 | 30.7 |
| Female | 407 | 69.3 | |
| Age (years) | Under 20 | 52 | 8.9 |
| 20–29 | 208 | 35.4 | |
| 30–39 | 229 | 39 | |
| 40–49 | 88 | 15 | |
| Over 50 | 10 | 1.7 | |
| Number of uses of Airbnb | Under 5 | 353 | 60.1 |
| 5–10 | 203 | 34.6 | |
| Over 10 | 31 | 5.3 | |
| Race | Malay | 202 | 34.4 |
| Chinese | 243 | 41.4 | |
| Indian | 47 | 8 | |
| Other | 95 | 16.2 | |
| Monthly income | Below 1000 RM | 120 | 20.4 |
| 1001–2000 RM | 76 | 12.9 | |
| 2001–3000 RM | 108 | 18.4 | |
| 3001–4000 RM | 127 | 21.6 | |
| 4001–5000 RM | 60 | 10.2 | |
| Above 5000 RM | 96 | 16.4 | |
| Role | Tenant | 367 | 62.5 |
| Landlord | 220 | 37.5 |
Reliability analysis.
| Variable | Dimension | Cronbach’α | Cronbach’α |
|---|---|---|---|
| EM | EML | 0.853 | 0.858 |
| EMP | 0.847 | ||
| EMC | 0.727 | ||
| CA | 0.914 | ||
| CI | 0.906 | ||
| CC | CCA | 0.831 | 0.883 |
| CCC | 0.848 | ||
| CCE | 0.841 | ||
| CSC | CBO | 0.891 | 0.895 |
| CBR | 0.881 | ||
| CSM | 0.891 | ||
| VVC | VVCF | 0.788 | 0.854 |
| VVCA | 0.775 | ||
| VVCH | 0.856 |
Discriminant validity of variables.
| Model |
|
df | △ |
CFI | TLI | RMSEA | SRMR | |
|---|---|---|---|---|---|---|---|---|
| judgement standards | <3 | >0.9 | >0.9 | <0.8 | <0.8 | |||
| seven-factor model |
874.708 | 474 | 1.845 | 0.955 | 0.950 | 0.038 | 0.033 | |
| six-factor model EM + CA; CI; CC; CSC; VVC; CSM | 1301.573 | 480 | 2.712 | 426.865(6) | 0.907 | 0.898 | 0.054 | 0.059 |
| five-factor model |
3558.745 | 485 | 7.338 | 2684.037(11) | 0.653 | 0.622 | 0.104 | 0.125 |
| four-factor model |
3936.986 | 489 | 8.051 | 3062.278(15) | 0.611 | 0.580 | 0.110 | 0.128 |
| three-factor model |
4114.120 | 492 | 8.362 | 3239.412(18) | 0.591 | 0.561 | 0.112 | 0.130 |
| two-factor model EM + CA + CI + CC + CSC + VVC; CSM | 4282.154 | 494 | 8.668 | 3407.446(20) | 0.572 | 0.543 | 0.114 | 0.130 |
| one-factor model |
5793.439 | 495 | 11.704 | 4918.731(21) | 0.402 | 0.362 | 0.135 | 0.152 |
“+” indicates that two elements are combined into one element; and all Δ
Correlations of latent variables and average variance extracted (AVES).
| EM | CA | CI | CC | CSC | CSM | VVC | |
|---|---|---|---|---|---|---|---|
| EM | 1 | ||||||
| CA | 0.174 ** | 1 | |||||
| CI | 0.186 ** | 0.217 ** | 1 | ||||
| CC | 0.291 ** | 0.303 ** | 0.191 ** | 1 | |||
| CSC | 0.206 ** | 0.155 ** | 0.160 ** | 0.147 ** | 1 | ||
| CSM | 0.064 | 0.117 ** | 0.066 | 0.104 * | 0.018 | 1 | |
| VVC | 0.403 ** | 0.438 ** | 0.354 ** | 0.474 ** | 0.286 ** | 0.222 ** | 1 |
| Mean | 3.537 | 3.471 | 3.507 | 3.574 | 3.461 | 3.620 | 3.585 |
| SD | 0.758 | 0.865 | 0.882 | 0.722 | 0.776 | 0.889 | 0.730 |
* p < 0.05, ** p < 0.01.
Results of testing.
| Hypothesis | Standardized Coefficient | S.E. | C.R. | P | Supported |
|---|---|---|---|---|---|
| H1 EM→VVC | 0.252 | 0.043 | 4.486 | *** | Yes |
| H2 CA→VVC | 0.271 | 0.027 | 5.629 | *** | Yes |
| H3 CC→VVC | 0.366 | 0.05 | 5.873 | *** | Yes |
| H4 CI→VVC | 0.201 | 0.028 | 4.45 | *** | Yes |
| H5 CSC→VVC | 0.16 | 0.039 | 2.975 | 0.003 | Yes |
*** p < 0.001.
Analysis of the regulatory effect of CSM.
| Variables | VVC | ||
|---|---|---|---|
| Model 1 | Model 2 | Model 3 | |
| EM | 0.216 *** | 0.212 *** | 0.177 *** |
| CA | 0.256 *** | 0.244 *** | 0.205 *** |
| CI | 0.184 *** | 0.179 *** | 0.152 *** |
| CC | 0.279 *** | 0.270 *** | 0.255 *** |
| CSC | 0.131 *** | 0.133 *** | 0.107 *** |
| CSM | 0.137 *** | 0.123 *** | |
| EM × CSM | 0.089 ** | ||
| CA × CSM | 0.082 * | ||
| CI × CSM | 0.082 * | ||
| CC × CSM | 0.044 | ||
| CSC × CSM | 0.097 ** | ||
| R2 | 0.434 | 0.452 | 0.502 |
| Adjusted R2 | 0.429 | 0.446 | 0.492 |
| △R2 | 0.434 | 0.018 *** | 0.050 *** |
| F | 88.924 *** | 79.735 *** | 52.694 *** |
* p < 0.05, ** p < 0.01, *** p < 0.001.
Simple slope analysis.
| Path | CSM | β | se | t | p | LLCI | ULCI |
|---|---|---|---|---|---|---|---|
| EM→VVC | Low value(M − SD) | 0.087 | 0.046 | 1.893 | 0.059 | −0.003 | 0.178 |
| High value(M + SD) | 0.266 | 0.044 | 6.010 | 0.000 | 0.179 | 0.353 | |
| CA→VVC | Low value (M − SD) | 0.123 | 0.046 | 2.693 | 0.007 | 0.033 | 0.213 |
| High value (M + SD) | 0.287 | 0.046 | 6.289 | 0.000 | 0.197 | 0.376 | |
| CI→VVC | Low value (M − SD) | 0.071 | 0.044 | 1.618 | 0.106 | −0.015 | 0.156 |
| High value (M + SD) | 0.234 | 0.045 | 5.172 | 0.000 | 0.145 | 0.323 | |
| CSC→VVC | Low value (M − SD) | 0.010 | 0.044 | 0.234 | 0.815 | −0.076 | 0.097 |
| High value (M + SD) | 0.204 | 0.044 | 4.686 | 0.000 | 0.119 | 0.290 |
References
1. Laukkanen, M.; Tura, N. The potential of sharing economy business models for sustainable value creation. J. Clean. Prod.; 2020; 253, 120004. [DOI: https://dx.doi.org/10.1016/j.jclepro.2020.120004]
2. Camilleri, J.; Neuhofer, B. Value Co-creation and Co-destruction in the Airbnb Sharing Economy. Int. J. Contemp. Hosp. Manag.; 2017; 29, pp. 2322-2340. [DOI: https://dx.doi.org/10.1108/IJCHM-09-2016-0492]
3. Benoit, S.; Baker, T.L.; Bolton, R.N.; Gruber, T.; Kandampully, J. A triadic framework for collaborative consumption (CC): Motives, activities and resources & capabilities of actors. J. Bus. Res.; 2017; 79, pp. 219-227.
4. Breidbach, C.F.; Brodie, R.J. Engagement platforms in the sharing economy: Conceptual foundations and research directions. J. Serv. Theory Pract.; 2017; 27, pp. 761-777. [DOI: https://dx.doi.org/10.1108/JSTP-04-2016-0071]
5. Yang, X.C.; Tu, K. Research on the Effect of Platform Support Quality on User Value Co-creation Citizenship Behavior under the Background of Sharing Economy. Econ. Manag. J.; 2018; 3, pp. 128-144.
6. Grönroos, C.; Voima, P. Critical service logic: Making sense of value creation and cocreation. J. Acad. Mark. Sci.; 2013; 41, pp. 133-150. [DOI: https://dx.doi.org/10.1007/s11747-012-0308-3]
7. Meng, T.; Guan, Y.Q.; Dong, Z.; Wang, W. The Mechanism of User Independent Value Creation Under the Sharing Economy —Airbnb & Xianyu as Examples. Sci. Sci. Manag. S.&.T; 2020; 8, pp. 111-130.
8. Akhmedova, A.; Mas-Machuca, M.; Marimon, F. Value co-creation in the sharing economy: The role of quality of service provided by peer. J. Clean. Prod.; 2020; 266, 121736. [DOI: https://dx.doi.org/10.1016/j.jclepro.2020.121736]
9. Nadeem, W.; Juntunen, M.; Hajli, N.; Tajvidi, M. The Role Of Ethical Perceptions In Consumers’ Participation And Value Co-Creation On Sharing Economy Platforms. J. Bus. Ethics; 2021; 3, pp. 421-441. [DOI: https://dx.doi.org/10.1007/s10551-019-04314-5]
10. Ranjbari, M.; Morales-Alonso, G.; Carrasco-Gallego, R. Conceptualizing the Sharing Economy through Presenting a Comprehensive Framework. Sustainability; 2018; 10, 2336. [DOI: https://dx.doi.org/10.3390/su10072336]
11. Li, Y.; Zhou, M.; Wang, X.X. The Study of Customer Independent Value Creation: Review, Analysis and Prospects. Foreign Econ. Manag.; 2016; 3, pp. 73-85.
12. Leung, X.Y.; Xue, L.; Wen, H. Framing the shan ring economy: Toward a sustainable ecosystem. Tour. Manag.; 2019; 71, pp. 44-53. [DOI: https://dx.doi.org/10.1016/j.tourman.2018.09.021]
13. Felson, M.; Spaeth, J.L. Community Structure and Collaborative Consumption: A Routine Activity Approach. Am. Behav. Sci.; 1978; 21, pp. 614-624. [DOI: https://dx.doi.org/10.1177/000276427802100411]
14. Benkler, Y. Remix: Making Art and Commerce Thrive in the Hybrid Economy. Science; 2009; 5925, pp. 337-338. [DOI: https://dx.doi.org/10.1126/science.1172790]
15. Puschmann, T.; Alt, R. Sharing Economy. Bus. Inf. Syst. Eng.; 2016; 58, pp. 93-99. [DOI: https://dx.doi.org/10.1007/s12599-015-0420-2]
16. Zervas, G.; Proserpio, D.; Byers, J.W. The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. J. Mark. Res.; 2017; 54, pp. 687-705. [DOI: https://dx.doi.org/10.1509/jmr.15.0204]
17. Botsman, R.; Rogers, R. What’s Mine Is Yours: The Rise of Collaborative Consumption. Publ. Wkly.; 2010; 257, 42.
18. Bardhi, F.; Eckhardt, G.M. Access-Based Consumption: The Case of Car Sharing. J. Consum. Res.; 2012; 39, pp. 881-898. [DOI: https://dx.doi.org/10.1086/666376]
19. Belk, R. You Are What You Can Access: Sharing and Collaborative Consumption Online. J. Bus. Res.; 2014; 67, pp. 1595-1600. [DOI: https://dx.doi.org/10.1016/j.jbusres.2013.10.001]
20. Boar, A.; Bastida, R.; Marimon, F. A Systematic Literature Review. Relationships Between the Sharing Economy, Sustainability and Sustainable Development Goals. Sustainability; 2020; 12, 6744. [DOI: https://dx.doi.org/10.3390/su12176744]
21. Prahalad, C.K.; Ramaswamy, V. Co-creation experiences: The next practice in value creation. J. Interact. Mark.; 2004; 18, pp. 5-14. [DOI: https://dx.doi.org/10.1002/dir.20015]
22. Vargo, S.L.; Lusch, R.F. Evolving to a new dominant logic for marketing. J. Mark.; 2004; 68, pp. 1-17. [DOI: https://dx.doi.org/10.1509/jmkg.68.1.1.24036]
23. Yi, Y.; Gong, T. Customer value co-creation behavior: Scale development and validation. J. Bus. Res.; 2013; 66, pp. 1279-1284. [DOI: https://dx.doi.org/10.1016/j.jbusres.2012.02.026]
24. Yoon, S.J. Effects of Customer Perception, Ethical Consumption Propensity, and Trust on Value Co-creation Behavior for Social Enterprise. J. Prod. Res.; 2016; 34, pp. 95-105. [DOI: https://dx.doi.org/10.36345/kacst.2016.34.4.010]
25. Yoon, S.M. The Impact of Customer Participation and Expertise on the Co-creation of Value and Customer Trust of Hotel Users. Tour. Res.; 2017; 42, pp. 131-150. [DOI: https://dx.doi.org/10.32780/ktidoi.2017.42.2.131]
26. Lee, Y.; Kim, I. A value co-creation model in brand tribes: The effect of luxury cruise consumers’ power perception. Serv. Bus.; 2019; 1, pp. 129-152. [DOI: https://dx.doi.org/10.1007/s11628-018-0373-x]
27. Li, X.X.; Zhang, Z. Research on the Impact of Brand Symbolic Values on Consumer Value Co-Creation Intention —Moderated Mediation Models. Soft Sci.; 2020; 8, pp. 116-122.
28. Tchorek, G.; Brzozowski, M.; Dziewanowska, K.; Allen, A.; Kozioł, W.; Kurtyka, M.; Targowski, F. Social Capital and Value Co-Creation: The Case of a Polish Car Sharing Company. Sustainability; 2020; 11, 4713. [DOI: https://dx.doi.org/10.3390/su12114713]
29. Lee, E.M.; Yoon, S.J. The Effect of Consumer Citizenship on Attitude toward CSR Activities and Consumer Loyalty. J. Prod. Res.; 2016; 34, pp. 93-102.
30. Goodpaster, K.E. The concept of corporate responsibility. J. Bus. Ethics; 1983; 2, pp. 1-22. [DOI: https://dx.doi.org/10.1007/BF00382708]
31. Velasquez, M.G. Business Ethics: Concepts and Cases. J. Bus. Ethics; 1988; 7, pp. 592-604.
32. Rodgers, W.; Murray, J.M.; Stefanidis, A.; Degbey, W.Y.; Tarba, S.Y. An Artificial Intelligence Algorithmic Approach to Ethical Decision-Making in Human Resource Management Processes. Hum. Resour. Manag. Rev.; 2022; 100925.Available online: https://www.sciencedirect.com/science/article/pii/S1053482222000432 (accessed on 10 August 2022). [DOI: https://dx.doi.org/10.1016/j.hrmr.2022.100925]
33. Jeong, B.G. The Effects of Ethical Corporate Attitude on Value Co-Creation in Foodservice Industry-Focused on the Moderating Effects of Employees’ Psychological Well-being in Foodservice Industry. Food Serv. Ind. J.; 2017; 13, pp. 53-66.
34. Sohn, S.H. Influential Factors for the Customer-focused Business Performance of Business Ethics. Ordo Econ. J.; 2009; 12, pp. 19-40.
35. Goffee, R.; Jones, G. Managing authenticity: The paradox of great leadership. Harv. Bus. Rev.; 2005; 83, pp. 86-94.
36. Park, J.C.; Lee, G.O. The effects of the authenticity based on employees’ service characteristics of a hotel enterprise on service quality and customer loyalty. Int. J. Tour. Hosp. Res.; 2016; 30, pp. 135-152. [DOI: https://dx.doi.org/10.21298/IJTHR.2016.06.30.6.135]
37. Gilmore, J.H.; Pine, B.J. Authenticity: What Consumers Really Wan; Harvard Business School Press: Boston, MA, USA, 2007.
38. Kay, M.J. Strong Brands and Corporate Brands. Eur. J. Mark.; 2006; 40, pp. 742-760. [DOI: https://dx.doi.org/10.1108/03090560610669973]
39. Jung, W.S.; Yoon, S.J. A Study on the Effects of Social Capital on Corporate Authenticity and Value Co-Creation: With a focus on differences according to the moderating effects of a brand’s self-monitoring. Korean Corp. Manag. Rev.; 2015; 22, pp. 225-250.
40. Kim, H.J.; Cho, S.H. The Effect of Trust and Authenticity on a Consumer’s Complaining Behavior and Repurchase Intention in a Discount Department Store. J. Prod. Res.; 2017; 35, pp. 117-125.
41. Beverland, M.B. Brand management and the challenge of authenticity. J. Prod. Brand Manag.; 2005; 14, pp. 460-461. [DOI: https://dx.doi.org/10.1108/10610420510633413]
42. Eggers, F.; O’Dwyer, M.; Kraus, S.; Vallaster, C.; Güldenberg, S. The impact of brand authenticity on brand trust and SME growth: A CEO perspective. J. World Bus.; 2013; 48, pp. 340-348. [DOI: https://dx.doi.org/10.1016/j.jwb.2012.07.018]
43. Das, G.; Datta, B.; Guin, K.K. Impact of retailer personality on consumer-based retailer equity. Asia Pac. J. Mark. Logist.; 2012; 24, pp. 619-639. [DOI: https://dx.doi.org/10.1108/13555851211259052]
44. Lee, C.M.J.; Che-Ha, N.; Alwi, S.F.S. Service Customer Orientation and Social Sustainability: The Case of Small Medium Enterprises. J. Bus. Res.; 2021; 122, pp. 751-760. [DOI: https://dx.doi.org/10.1016/j.jbusres.2019.12.048]
45. Liu, H. New Thinking on the Theory and Practice of Corporate Image under the Background of Internet and E-commerce. China Bus. Trade; 2021; 18, pp. 42-45.
46. Nguyen, N.; Leblanc, G. Corporate image and corporate reputation in customers’ retention decisions in services. J. Retail. Consum. Serv.; 2001; 4, pp. 227-236. [DOI: https://dx.doi.org/10.1016/S0969-6989(00)00029-1]
47. Weiss, A.M.; Anderson, E.; MacInnis, D.J. Reputation management as a motivation for sales structure decisions. J. Mark.; 1999; 63, pp. 74-89. [DOI: https://dx.doi.org/10.1177/002224299906300407]
48. Keller, K.L.; Aaker, D.A. The effects of sequential introduction of brand extensions. J. Mark. Res.; 1992; 29, pp. 35-50. [DOI: https://dx.doi.org/10.1177/002224379202900104]
49. Pina, J.M.; Martinez, E.; Chernatony, L.D.; Drury, S. The effect of service brand extensions on corporate image: An empirical model. Eur. J. Mark.; 2006; 40, pp. 174-197. [DOI: https://dx.doi.org/10.1108/03090560610637374]
50. Van Steenbergen, B. The Condition of Citizenship: An Introduction; Sage Publications.: London, UK, 1994.
51. Kim, J.U.; Rhee, K.C. The Conceptualization and the Practical Application of Consumer Citizenship. J. Consum. Stud.; 2008; 19, pp. 47-71.
52. Wade, R.C. Community Service-Learning: A Guide to Including Service in the Public School Curriculum; State University of New York Press: Dulles, VA, USA, 20 August 1997; Available online: https://www.amazon.com/Community-Service-Learning-Including-Curriculum-Democracy/dp/0791431843 (accessed on 10 August 2022).
53. Yoon, S.J.; Oh, J.C. Validation of Antecedent and Outcome Variables Affecting Value Co-creation Behavior of Social Enterprises. Soc. Enterp. Stud.; 2014; 7, pp. 77-104.
54. Putnam, R.D. The Prosperous Community: Social Capital and Public Life. Am. Prospect.; 1993; 13, pp. 35-42.
55. Jung, W.S.; Yoon, S.J. Impact of Social Capital on Value Co-creation: Focused on the Role of Subjective Well-being and Social Identity. J. Prod. Res.; 2015; 33, pp. 33-44.
56. Lin, N. Social Capital: A Theory of Social Structure and Action; Cambridge University Press: New York, NY, USA, 2001.
57. Putnam, R.D. Bowling alone: The collapse and revival of American community. J. Policy Anal. Manag.; 2009; 4, pp. 788-790.
58. Lin, C. Assessing the mediating role of online social capital between social support and instant messaging usage. Electron. Commer. Res. Appl.; 2011; 10, pp. 105-114. [DOI: https://dx.doi.org/10.1016/j.elerap.2010.08.003]
59. Wang, W.B.; Ho, C.W. No Money? No Problem! The Value of Sustainability: Social Capital Drives the Relationship among Customer Identification and Citizenship Behavior in Sharing Economy. Sustainability; 2017; 8, 1400. [DOI: https://dx.doi.org/10.3390/su9081400]
60. Kim, E.K.; Yoon, S.J. Social Capital, User Motivation, and Collaborative Consumption of Online Platform Services. J. Retail. Consum. Serv.; 2021; 62, 102651. [DOI: https://dx.doi.org/10.1016/j.jretconser.2021.102651]
61. Snyder, M.; Gangestad, S. Choosing social situations: Two investigations of self-monitoring processes. J. Personal. Soc. Psychol.; 1982; 1, pp. 123-135. [DOI: https://dx.doi.org/10.1037/0022-3514.43.1.123]
62. Snyder, M. Self-monitoring of expressive behavior. J. Personal. Soc. Psychol.; 1974; 4, pp. 526-537. [DOI: https://dx.doi.org/10.1037/h0037039]
63. Snyder, M. Selling Images Versus Selling Products - Motivational Foundations of Consumer Attitudes And Behavior. Adv. Consum. Res.; 1989; pp. 306-311.
64. Shavitt, S.; Lowrey, T.M.; Han, S.P. Attitude Functions in Advertising: The Interactive Role of Products and Self-monitering. J. Cansumer Psychol.; 1992; 1, pp. 337-364. [DOI: https://dx.doi.org/10.1016/S1057-7408(08)80059-9]
65. Browne, B.A.; Kaldenberg, D.O. Conceptualizing self-monitoring: Links to materialism and product involvement. J. Consum. Mark.; 1997; 14, pp. 31-44. [DOI: https://dx.doi.org/10.1108/07363769710155848]
66. Hogg, M.K.; Cox, A.J.; Keeling, K. The impact of self-monitoring on image congruence and product brand evaluation. Eur. J. Market.; 2013; 5-6, pp. 641-667. [DOI: https://dx.doi.org/10.1108/03090560010321974]
67. Kim, D.H.; Seely, N.K.; Jung, J.H. Do You Prefer, Pinterest or Instagram? The Role of Image-sharing SNSs and Self-monitoring in Enhancing Ad Effectiveness. Comput. Hum. Behav.; 2017; 70, pp. 535-543. [DOI: https://dx.doi.org/10.1016/j.chb.2017.01.022]
68. Cho, E.Y. A Study on Convergence Relation of Corporate Ethical Management, Consumers’ Perceived Trust, and Purchasing Behavior. J. Digit. Converg.; 2015; 8, pp. 113-121. [DOI: https://dx.doi.org/10.14400/JDC.2015.13.8.113]
69. Kotler, P. Marketing Management; Millenniun,
70. Solakis, K.; Katsoni, V.; Mahmoud, A.; Grigoriou, N. Factors affecting value co-creation through artificial intelligence in tourism: A general literature review. J. Tour. Futures; 2022; 5, [DOI: https://dx.doi.org/10.1108/JTF-06-2021-0157]
71. Mengcheng, L.; Tuure, T. Information Technology–Supported value Co-Creation and Co- Destruction via social interaction and resource integration in service systems. J. Strateg. Inf. Syst.; 2022; 31, 101719.
72. Suh, Y.G.; Yoo, H.S.; Kim, H.R. A Study on the Influence on Brand Attachment and Loyalty of Cosmetic Brand Authenticity. J. Channel Retail.; 2014; 19, pp. 87-111.
73. Zang, H.Y.; Moon, Y.H.; Choi, J.H. The Impact of the Fitness and Sincerity of CSR Activities toward Objects on Enterprise Evaluation. J. Prod. Res.; 2020; 38, pp. 37-42.
74. Hong, L.; Huong, T.; Tam, T. Value Co-creation in Branding: A Systematic Review from a Tourism Perspective. Eur. J. Tour. Res.; 2022; 32, 3203.Available online: https://ejtr.vumk.eu/index.php/about/article/view/2597/557 (accessed on 10 August 2022).
75. Lim, M.S. Social Network Induced Stress on Coping Behaviors of Consumers. J. Hum. Resour. Manag. Res.; 2013; 20, pp. 111-136. [DOI: https://dx.doi.org/10.14396/jhrmr.2013.20.4.111]
76. Cohen, D.J.; Prusak, L. Good Company: How Social Capital Makes Organizations Work; M. Harvard Business School Press: BOSTON, MA, USA, 2001.
77. Li, G.X.; Yang, X.; Huang, S. Effects of Social Capital and Community Support on Online Community Members’ Intention to Create User-Generated Content. J. Electron. Commer. Res.; 2014; 3, pp. 190-199.
78. DeBono, K.G. Self-monitoring and consumer psychology. J. Ersonality; 2006; 74, pp. 715-738. [DOI: https://dx.doi.org/10.1111/j.1467-6494.2006.00390.x] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16684251]
79. Snyder, M.; Gangestad, S. On the nature of self-monitoring: Matters of assessment, matters of validity. J. Personal. Soc. Psychol.; 1986; 1, pp. 125-139. [DOI: https://dx.doi.org/10.1037/0022-3514.51.1.125] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/3735063]
80. Lee, S.H.; Lee, S.J. A Study of the Extended Service Norm Constructs Influencing Behavioral Intention and a Moderating Variable in Service Purchasing Situation. Asia Mark. J.; 2009; 11, pp. 1-29. [DOI: https://dx.doi.org/10.53728/2765-6500.1392]
81. Zanna, M.P.; Olson, J.M.; Fazio, R.H. Attitude–behavior consistency: An individual difference perspective. J. Personal. Soc. Psychol.; 1980; 38, pp. 432-440. [DOI: https://dx.doi.org/10.1037/0022-3514.38.3.432]
82. Fan, X.M.; Wang, X.Y. Shared Bicycle Consumption and Unethical Behavior in the Shared Economy Environment ——Based on the Mobility Feature of Liquid Consumption. Collect. Essays Financ. Econ.; 2020; 6, pp. 95-103.
83. Peter, J.P.; Olson, J.C. Consumer Behavior and Marketing Strategy; 8th ed. McGraw-Hill: New York, NY, USA, 2008.
84. Williams, D. On and Off the “Net” Scales for Social Capital in an Online Era. J. Comput. Mediat. Commun.; 2006; 11, pp. 593-628. [DOI: https://dx.doi.org/10.1111/j.1083-6101.2006.00029.x]
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