Online consumer review and group-buying participation: The mediating effects of consumer beliefs

Online consumer review and group-buying participation: The mediating effects of consumer beliefs

Accepted Manuscript Online consumer review and group-buying participation: The mediating effects of consumer beliefs Xinping Shi, Ziqi Liao PII: DOI: ...

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Accepted Manuscript Online consumer review and group-buying participation: The mediating effects of consumer beliefs Xinping Shi, Ziqi Liao PII: DOI: Reference:

S0736-5853(16)30453-1 http://dx.doi.org/10.1016/j.tele.2016.12.001 TELE 893

To appear in:

Telematics and Informatics

Received Date: Revised Date: Accepted Date:

15 September 2016 15 November 2016 6 December 2016

Please cite this article as: Shi, X., Liao, Z., Online consumer review and group-buying participation: The mediating effects of consumer beliefs, Telematics and Informatics (2016), doi: http://dx.doi.org/10.1016/j.tele.2016.12.001

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Title page

Online consumer review and group-buying participation: The mediating effects of consumer beliefs

Authors:

Xinping Shi, Ziqi Liao School of Business Hong Kong Baptist University

Corresponding author: Ziqi Liao Ph.D. School of Business Hong Kong Baptist University Kowloon, Hong Kong Tel: +852 34115227 E-mail: [email protected]

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Online consumer review and group-buying participation: The mediating effects of consumer beliefs and satisfaction

Abstract This paper aims to examining the extent to which online consumer review (OCR) influences consumer beliefs and participation in online group-buying. We design a conceptual model and propose several hypotheses to articulate the causal relationships in line with the social exchange theory and the theory of institution-based trust. The empirical results unveil that OCR significantly influences consumer perceptions of effectiveness, perceived structure assurance, and familiarity with intermediary, while consumer satisfaction and trust in intermediary significantly mediate the relationships between consumer perceptions and continuance use of online group-buying. The present study advances the theoretical understanding of the impact of consumer review and the mediating effects of consumer beliefs in the context of online group-buying. The findings make contributions to research and practice with managerial implications for the application of social media in e-commerce.

Keywords: Online consumer review Social media Consumer beliefs Continuance use Group-buying participation

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1. Introduction As a consumer-oriented social media, online consumer review (OCR) becomes increasingly popular on the websites of different intermediaries. Many online intermediaries host OCR, through which consumers can participate in online social exchange and information sharing. The existing studies indicate that OCR may serve as a communication channel that enables consumers to express their opinions and views on products and services that may influence other consumers’ beliefs and buying behavior, facilitates interactions between the online intermediary and consumers, and motivates consumers to participate in online exchanges. In addition, the presence of online review is helpful to the online intermediary as it may play a role in attracting consumers to visit the intermediary’s websites, communicating with consumers, appreciating the products and services needed by consumers, building up a sense of community, and influencing consumers’ perceptions and beliefs of the online intermediary (Chen and Xie, 2008; Mudambi and Schuff, 2010; Jing and Xie, 2011; Rishika et al., 2013; Rese et al., 2014; Engler et al., 2015). In the context of online group-buying, deal-of-the-day offered by an online intermediary might become a popular shopping activity if could be extensively accepted by consumers. The online group-buying intermediary should provide institutional mechanisms that enable transactions and exchanges between consumers and suppliers. In particular, it should possess the following distinctive characteristics. First, it should add values for consumers in the ways of pooling consumer preferences, reducing transaction costs, and offering volume discounts and price discovery mechanisms (Datta and Chatterjee, 2008). Second, it should have institutional mechanisms with structural assurance consisting of policies, regulations, and operation norms, which not only coordinate transactions and mitigate risks in relation to consumer privacy and transaction security, but also foster institution-based trust and sustainable relationships with consumers (Datta and Chatterjee, 2008; Jing and Xie, 2011). Third, it may host a social media through which consumers can participate in information sharing and social exchange, through which consumers can express views and comments on different products and share shopping information and experiences (Pavlou and Dimoka, 2006; Mudambi and Schuff, 2010; Shiau and Luo, 2012). In particular, an online intermediary should establish mechanisms to 3

facilitate online transactions and social exchange, mitigate the intrinsic risk of online privacy and security, and create institution-based trust for sustainable online operations (Jing and Xie, 2011). A social media hosted by an online intermediary may play a role in encouraging consumer interactions and motivating consumers to participate in online group-buying activities. Recent studies suggest that it is imperative to examine consumer beliefs and continuance intention (Chang, 2013; Chang et al., 2015; Tan et al., 2015; Ramayah et al., 2016). Therefore, it is meaningful to empirically articulate the causal relationships of consumer review and continuous participation in online group-buying. The objective of this paper is to unveil the effects of OCR and the mediating effects of consumer beliefs on continuance use of online group-buying. In particular, we formulate a conceptual model and propose several hypotheses to examine the causal relationships of consumer satisfaction, trust in intermediary, and continuance use of online group-buying in line with the underpinnings of the social exchange theory and the theory of institution-based trust. In addition, we carry out a survey to obtain data from experienced consumers and empirically test the conceptual model and hypotheses using structural equation modeling. The present work makes contributions to research and practice. The empirical findings to be presented in the following sections indicate that OCR significantly influences consumer perceptions with regard to perceived effectiveness, perceived structural assurance, and familiarity with intermediary, while consumer satisfaction and trust in intermediary positively mediate the relationships between consumer perceptions and continuance use of online group-buying. This paper is structured as follows. The next section begins with theoretical foundation of the conceptual model and hypotheses. It then describes our research method and presents the results of empirical analysis. Moreover, it discusses the empirical results together with theoretical contributions and practical insights. Finally, it summarizes our research findings and highlights the directions for future research.

2. Conceptual Model and Hypotheses As a premier theoretical origin for examining social phenomena and economic exchanges, the social exchange theory postulates that consumers are socially interdependent (Emerson, 1976; Homans, 1958). With OCR, consumers may develop a sense of online community through mutually sharing 4

product information and exchanging shopping experiences (Rese et al., 2014). They may also obtain product and service information that is useful for participating in online group-buying. However, online group-buying transactions involve risks that are intrinsically embedded in virtual environments, because of information asymmetry and potential opportunistic behavior of counterparts (Shiau and Luo, 2012). The social exchange theory advocates that information sharing and trust of online community are relational bonds between exchange parties to cope with risks and opportunistic behaviors. OCR may therefore foster consumers’ trust in online group-buying intermediary. The theory of institution-based trust underpins online social exchanges and group-buying transactions with an intermediary. Institution-based trust may be developed on the basis of institutional mechanisms that govern online transactions (Pavlou and Gefen, 2004). In line with the theoretical underpinnings, the institutional mechanisms of an online intermediary can alleviate risk and uncertainty, strengthen consumer privacy and security protection, and coordinate transactions with assurance for reliable and successful online transactions. When consumers perceive the goodness of the mechanism and recognize an intermediary as a trustworthy partner, they are willing to depend on it in conducting online exchanges. Thus, institution-based trust refers to consumers’ psychological beliefs of an online intermediary, which indicates that consumers are willing to depend on the intermediary, since they have confidence in the intermediary in terms of reliability and predictability (Pavlou and Gefen, 2004; Sha, 2008). Actually, the social exchange theory and the theory of institution-based trust lay a theoretical foundation for examining OCR with regard to consumer perceptions, psychological state, and continuance use. We design a conceptual model to elucidate the extent to which OCR affects consumer perceptions, psychological beliefs, and continuance use of online group-buying. As depicted in Fig. 1, OCR acts as an exogenous construct, which is proposed to affect consumer perceptions in terms of perceived effectiveness, structural assurance, and familiarity. At the same time, consumer satisfaction with and trust in intermediary are assumed to mediate the relationships between consumer perceptions and continuance use of online group-buying. ~ Insert Fig. 1 ~

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2.1. Online consumer review In the present work, OCR refers to the consumer-created online information posted on the website hosted by an intermediary, which may include opinions and recommendations about different products and services. It fosters communication and information sharing of different consumers and enables individuals to obtain information from others, in which different consumers may express views based on their experiences, enjoyments, and benefits from using the relevant products or services delivered by the intermediary (Chen and Xie, 2008; Mudambi and Schuff, 2010; Schindler and Bickart, 2012). It also enables the intermediary to communicate with consumers and learn about the feedback from different consumers, while the online intermediary should provide consumers with guidelines for posting their reviews. In line with the definition aforementioned, consumer review is the information created and posted by consumers on an intermediary hosted website, which may draw other consumers’ attention, provoke their response, and facilitate them to make purchase decisions and appreciate the economic and social value of a product or service (Park et al., 2007). It plays a role in influencing consumer perceptions of products and service offerings. Pavlou and Dimoka (2006) explore the effect of consumers’ feedback through eBay on building buyers’ trust in a seller’s benevolence and credibility, which suggest that online comments and opinions may help develop consumers’ trust and facilitate them to particulate in e-commerce activities. OCR may serve as a free sales assistant to help a consumer make a purchase decision, while a seller may also adjust its marketing strategy in the light of consumer-created information (Chen and Xie, 2008). In addition, online review may influence individual perceptions of goods such as wine, food, and cosmetics, because novice buyers may rely on other experienced consumers’ recommendations to reduce search cost, evaluate alternatives, comprehend the value of a wanted product, and make purchase decision (Mudambi and Schuff 2010; Baber et al., 2016). Some customers may consider the opinions from online review to evaluate product alternatives and confirm their purchase decisions. They may also deliver comments on the intermediary’s social media to help other prospective customers, which may affect perceived effectiveness of online group-buying in terms of volume discounts of products and services as well as

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social benefits such as enjoyable experience, sense of community, and knowledge sharing with other buyers or community members (Jing and Xie, 2011). It may also enhance online social interactions and help consumers appreciate the online group-buying process. Therefore, we propose the following hypothesis: H1: OCR positively affects perceived effectiveness of online group-buying. The information in OCR includes comments on the online intermediary’s structural assurance in relation to its operations and regulations of group-buying (Pavlou and Gefen, 2004). Consumers’ questions, comments, and remarks reflect their concerns about intermediary’s assurance for protections of personal privacy, transaction security, and the reduction of risk and uncertainty inherited in group-buying transactions. Sharing of these viewpoints among consumers and the intermediary’s responses to consumer’s concerns, OCR may enhance consumers’ understanding of the intermediary’s operational procedures such as group-buying process and timing, and strengthen consumers’ comprehension of the intermediary’s benevolent policies and regulations for caring consumers’ interests, benefits, and concerns (Sha, 2008). Hence, online review not only fosters communications between consumers and intermediary, but also makes online group-buying become a reliable outlet through strengthening the intermediary’s structural assurance that is in place and in force to secure private and transactional data of the consumers. Therefore, we propose the following hypothesis: H2: OCR positively affects perceived structural assurance of online group-buying. As a social media for consumers, OCR is distinctive to draw a large number of extant and prospective consumers to visit, post, and interact with other consumers. For example, the OCRs enabled by Amazon.com and eBay receive considerable consumers’ acceptance in online transactions (Pavlou and Dimoka, 2006; Mudambi and Schuff, 2010). An immediate and significant effect of large number of consumers’ participations in OCR may be the enhancement of consumers’ familiarity with an intermediary. Patronizing the viewpoints available on intermediary’s websites, consumers can communicate with the intermediary and other consumers, understand the uniqueness and detailed characteristics of products and services, and differentiate the intermediary from its competitors. It may 7

enhance consumers’ familiarity with and comprehension of the intermediary’s operational norms and benevolent behavior. Thus, consumers become knowledgeable and skillful in group-buying in terms of timing and discounts from the deal-of-the-day group-buying transactions (Park and Kim, 2008; Jing and Xie, 2011; Liu and Sutanto, 2012). Therefore, we propose the following hypothesis: H3: OCR positively affects consumers’ familiarity with intermediary. 2.2. Perceived effectiveness In the present work, perceived effectiveness refers to consumers’ assessment of usability, value, and social benefits offered by an online intermediary as well as products purchased through group-buying. First, usability indicates the functionality of online group-buying. Second, value indicates consumers’ perception of the value for money of the products purchased and the cost occurred in group-buying transactions. Third, social benefits are obtained from online interactions and enjoyments such as sharing of experience, information, and knowledge with other consumers. Actually, perceived effectiveness is a post-adoption or post-usage valuation, which may include consumers’ cognitive and affective judgments formed during transactions, information exchange, and consumption processes, as these cognitive and affective elements may affect consumers’ psychological beliefs (Bolton and Drew, 1991; Cronin et al., 2000; Liao and Cheung, 2001: Liao and Shi, 2009). We employ perceived effectiveness to measure consumer perceptions (Pavlou and Gefen, 2004). The effect of perceived effectiveness can be articulated in two perspectives. First, perceived effectiveness may directly affect consumer satisfaction with the intermediary’s group-buying mechanism and performance including the products and services. In line with the expectation disconfirmation theory (Oliver, 1980), at the post-usage stage consumers usually evaluate their transactions in terms of price, compare the benefit with initial expectation, and develop an emotional response of satisfaction or dissatisfaction. From a cognitive psychology perspective, consumer satisfaction is influenced by expectation and the extent to which the expectation is met after product purchase. In the case of online group-buying, the information on OCR may provide consumers with a baseline reference. Thus, perceived effectiveness may affect consumer satisfaction, as it includes not only economic value such as the discount gained from group-buying in comparison to the price in the 8

marketplace, but also affective social value such as pleasure and surprise, especially when it involves experience goods through online group-buying. Therefore, we propose the following hypothesis: H4a: Perceived effectiveness positively affects consumer satisfaction with online group-buying. We posit that perceived effectiveness works as a direct predictor to foster consumers’ institutionbased trust in intermediary, because perceived effectiveness in terms of social benefits gained from group-buying transactions may engender consumers’ social ties or bonds with an intermediary (Bolton and Lemon, 1999; Cronin et al., 2000). Comparing with their expectations, consumers usually get added value in terms of discounted prices through group-buying and affective benefits from the online social exchanges with other consumers. The added value implies that the intermediary together with its institutional mechanism behave benevolently to care consumers’ interests and welfare (Pavlou and Dimoka, 2006). In other words, the added value and benefits reflect the intermediary’s benevolent behavior, which may lead consumers to foster ongoing expectations to and confidence in the intermediary, and form their beliefs that the intermediary is a trustworthy and dependable supplier providing needed products and services ( Mcknight et al., 2002; Pavlou and Gefen, 2004; Collquitt et al., 2007; Shi and Liao, 2013). Therefore, we propose the following hypothesis: H4b: Perceived effectiveness positively affects consumers’ trust in intermediary. 2.3. Perceived structural assurance In the online context, structural assurance refers to the extent to which consumers believe that an online intermediary’s business policies, regulations, guarantees, and legal protections are in place and in force to facilitate exchanges and transactions, minimize risk and uncertainty, and protect the private and transactional data of the consumers (McKnight et al., 2002). In other words, structural assurance is related to consumer perceptions of an intermediary’s institutional mechanism against loss, damage, risk, and opportunistic behavior, which may likely affect consumers’ beliefs and behavior (Sha, 2008). The structural assurance is implemented in the intermediary’s online transaction systems, which works as a safety-net to protect consumers’ interests and provides a worry-free environment for online interactions. It may not disturb or draw consumers’ attention in ordinary online transactions, because

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it is a silent and embedded regulatory mechanism within the intermediary’s information systems. However, when a high level of structure assurance is perceived by consumers and rigorously executed in transactions, consumers may feel that the mechanism is robust, structural, and bothersome, since it may hinder transaction efficiency and consumers’ flexibility to patronize the intermediary’s products and services, though structural assurance may provide better protections to customers and ensure the normality of online operations. Therefore, we propose the following hypothesis: H5a: Perceived structural assurance positively affects consumer satisfaction with online groupbuying. On the other hand, perceived structural assurance may reflect the integrity of an intermediary, which can be defined as the extent to which an intermediary adheres to sound moral principles and commonly accepted rules of commercial conducts (Collquitt and Rodell, 2011). In online transactions, the announcement of policies, regulations, operational procedures, guarantees, and legal protections exhibits the structure assurance of an intermediary and the communication between the intermediary and consumers, which may help enhance consumers’ confidence in the intermediary’s faithfulness and integrity and influence consumers to carry out online transactions with the intermediary. Therefore, we propose the following hypothesis: H5b: Perceived structural assurance positively affects consumers’ trust in intermediary. 2.4. Familiarity with intermediary Familiarity implies that the consumers possess online transaction experiences with an online intermediary at the stage of post usage (Gulati, 1995; Gefen et al., 2003), which refers to the understanding of what, why, when, how to do, and what they want to do based on interactions, experience, and learning. In the present work, we define familiarity with online group-buying as the extent to which a consumer understands an online intermediary’s commercial operations and transaction procedures and has knowledge to purchase desirable products through group-buying. As such, familiarity is more than experience, because it emphasizes consumers’ capability, knowledge, and success (Lee and Kwon, 2011). It may have a considerable impact on consumers’ understanding

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of an intermediary’s group-buying mechanism and performance, because it may result in the reduction of consumers’ concerns of risk, or the alteration of their expectations to the intermediary. When the online intermediary’s performance gives consumers a surprise that is beyond ordinary expectation, familiarity may transform the performance into consumers’ unexpected amazement, which may lead to favorable feelings and satisfaction. An understanding of the online intermediary’s group-buying process may reduce confusions. Therefore, we propose the following hypothesis: H6a: Familiarity with intermediary positively affects consumer satisfaction with online group-buying. According to Luhmann (2000), trust can be achieved within a familiar environment that will have an impact on the possibility of developing trust in human relations. Familiarity may work as a condition that fosters trust development in social and economic exchanges. In addition, the findings of Gefen et al. (2003) on the relationship between familiarity and trust posit that familiarity is a contextual factor, which may have an effect on consumers’ trust (Gulati, 1995). In the case of consumers’ interactions with an intermediary, familiarity with the intermediary can be regarded as an antecedents of institution-based trust (Komiak and Benbasat, 2006), which may increase consumer confidence in the intermediary and its offerings. Therefore, we propose the following hypothesis: H6b: Familiarity with intermediary positively affects consumers’ trust in intermediary. 2.5. Satisfaction, trust in intermediary, and continuance use We deploy the constructs such as satisfaction, trust in intermediary, and continuance use to examine consumers’ psychological state, which is formed by post-usage of group-buying offerings and coupled with consumers’ emotion and experience. First, consumer satisfaction has drawn much attention in research (Oliver, 1980, 1997; Bolton and Lemon, 1999; Cronin et al., 2000; Garbarino and Johnson, 1999). The expectation confirmation theory conceptualizes satisfaction as a post-usage judgment on product or service performance related to either expectation prior to purchase or experience after using a product or service over time (Oliver, 1980). The measurement of consumer satisfaction includes cognitive and affective views. The former evaluates consumer satisfaction with the offerings from a supplier and its transaction mechanism in terms of economic performance such as price, cost,

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benefit, and efficiency. The latter is consumers’ assessment of a supplier and its group-buying mechanism in terms of social, emotional, and intangible benefits in the delivering process. As the affective view is widely accepted in explicating the consequence of consumer satisfaction, we use it in this study and define satisfaction as consumers’ emotional and favorable response to an intermediary and its institutional mechanism for fulfillment of its social implications and transactions. In addition, trust in intermediary refers to consumers’ institution-based trust, because it is recognized as an important cornerstone of economic and social exchanges, which involve risk and uncertainty especially in the virtual environment (Gefen, et al., 2003; Pavlou and Gefen, 2004; Kim et al., 2008; Pappas, 2016). Institution-based trust is formed by institutional structure that coordinates social exchanges and economic transactions between consumers and an institution, and convinces consumers to be confident in and depend on the institution. As an extension of the theory to online intermediary, we postulate that intermediary’s institutional mechanism regulates, organizes, and facilitates online group-buying activities between consumers and intermediary. Thus, we define trust in the intermediary as consumers’ confidence in and willingness to be dependent on the online intermediary. Moreover, we employ continuance use of online group-buying as the endogenous construct in our conceptual model. This is because continuance use may serves as a proxy for repurchase behavior (Cronin et al., 2000), which is a post-usage behavior to represent the level of consumer commitment and loyalty. In line with the expectation confirmation theory, satisfaction is a determinant of continuance use and a predictor of loyalty behavior (Bhattacherjee et al., 2008). In the context of business-to-consumer e-commerce, satisfaction is a significant predictor of continuance use (Lee and Kwon, 2011). This reasoning logic can be extended to examine the mediating effect of consumer satisfaction, because it may transform consumer perceptions of effectiveness, structural assurance, and familiarity into continuance use of online group-buying. Therefore, we propose the following hypothesis: H7: Consumer satisfaction positively mediates the effects of perceived effectiveness, perceived structural assurance, and familiarity with intermediary on continuance use of online group-buying.

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Finally, consumers should be willing to dependent on a trustworthy intermediary that has robust mechanism to protect its consumers in online group-buying, because the existing works suggest that if an intermediary has a rigorous mechanism for delivering structural assurance, trust in intermediary may reduce uncertainty in transactions and eliminate opportunistic behavior of suppliers (Kim et al., 2008). With the institutional mechanisms for protecting consumers from fraudulent suppliers, an intermediary can take legal actions against the suppliers on behalf of the consumers (Mudambi and Schuff, 2010). It should also protect the consumers by absorbing transaction risks in group-buying transactions and minimizing suppliers’ opportunistic behavior (Pavlou and Gefen, 2004; Shiau and Luo, 2012). Thus, consumer trust in intermediary may play a mediating role in predicting continuance use of online group-buying. Generalizing from the above observations, we propose the following hypothesis: H8: Consumers’ trust in the intermediary positively mediates the effects of perceived effectiveness, perceived structural assurance, and familiarity with intermediary on continuance use of online group-buying.

3. Research Method 3.1. Study setting As a leading online intermediary offering deal-of-the-day group-buying in forty-six countries, Groupon together with its group-buying mechanisms provides an appropriate context for testing our conceptual model. According to www.groupon.hk, Groupon Hong Kong offers various deals in relation to restaurants, beauty, leisure, sport, and so on. Customer experience can happen when a minimum number of customers would like to purchase a deal. If sufficient people participate in a group-buying transaction, they may enjoy a particular high-end deal for a relatively lower price. The website of Groupon displays rich information, clear procedures, and transaction requirements such as price and number of customers needed to participate in a transaction, which friendly develops consumers’ familiarity with its institutional mechanisms. In particular, it hosts social media enabling consumers to post reviews and share opinions and views with regard to relevant products and services. Its institutional mechanisms provide structural assurance to protect customers’ privacy and transaction 13

security, which helps consumers appreciate Groupon as a trustworthy intermediary in offering online group-buying services. Groupon.com can serve as a representative group-buying platform, because it provides transactions features that are consistent with other online group-buying platforms. The present study was carried out in Hong Kong, because e-commerce has been penetrating in daily lives and many individuals are experienced consumers and informants who have participated in various online shopping activities. 3.2. Measurement In this study, we formulate measurement items or observable variables in relation to the constructs in the conceptual model. All constructs are reflective latent variables with multiple indicators (Hair et al., 2010). Actually, we adapt survey question items that were conceptualized and established in extant literature, though it is necessary to make wording adjustments to cope with the context of online group-buying. First, we develop four items to measure the construct of OCR with reference to Park et al. (2007), Chen and Xie (2008), Mudambi and Schuff (2010), and Jing and Xie (2011). Second, we employ eight items to manifest perceived effectiveness from Cronin et al. (2000) and Sweeney and Soutar (2001). Third, we identify five items to measure the construct of structural assurance from existing studies (McKnight et al., 2002; Pavlou and Dimoka, 2006; Sha, 2008). Fourth, we modify five items to measure the construct of familiarity with reference to Genfen et al. (2003) and Lee and Kwon (2011). Moreover, the construct of satisfaction is manifested by four items based on the studies by Bolton and Lemon (1999); Cronin et al. (2000); Garbarino and Johnson (1999), and Oliver (1997), while the construct of trust in intermediary is manifested by five items adapted from the works of Mayer et al. (1995), Gefen et al. (2003), Pavlou and Gefen (2004), and Kim et al. (2008). Lastly, we adapt five items to measure the construct of continuance use in line with such literature as Bhattacherjee et al. (2008) and Lee and Kwon (2011). Table 1 presents the constructs and items retained with exploratory factor analysis including factor loadings, eigenvalues, and the percentage of variance extracted. ~ Insert Table 1 ~

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3.3. Survey instrument and data collection We develop a preliminary questionnaire that includes the above-mentioned measurement items, and conducted a pilot study to examine the relevant question items. In the pilot study, we ask fifteen consumers with experience in group-buying to form a panel. The panel members scrutinize question items and provide suggestions for revising the questionnaire. We also invite thirty individual consumers to offer comments and suggestions, and refine the questionnaire for survey in light of the comments from the pilot study. Thereafter, we carry out a survey to collect data from individual consumers of Groupon in Hong Kong. Because our study aims at examining consumer perceptions, beliefs, and continuance use of online group-buying at the post-usage stage, it is useful to gather data from the consumers who have participated in the deal-of-the-day transactions with Groupon. Thus, we randomly select graduates from the university alumni associations, and ask whether they have experience in online group-buying with Groupon. If one is not a Groupon consumer, he or she does not need to complete our questionnaire. The questionnaire together with a brief explanatory note for answering the question items has been distributed to respondents. The respondents are requested to answer the question items, based on a Likert-scale of 1-7 ranging from ‘strongly disagree’ to ‘strongly agree’. As a result, we collect 339 completed questionnaires. 34 of them are discarded because the respondents do not complete all questions. Thus, the sample size for data analysis is 305. The control variables in relation to respondent demographic data include gender (55% male and 45% female), age (6% below 25; 87% within 25-28; 7% over 28), education (92% Bachelor; 8% Master or above), online shopping experience (less than 6 months 8%; 7 to 12 months 53%; less than 2 years 32%; others 7%), frequency of visiting Groupon website per week (mean = 2.13 and SD = 0.52), and frequency of group-buying via Groupon website per month (mean = 1.65, and SD = 0.47). 3.4. Reliability, common method variance, and construct validity We conduct exploratory factor analysis to ensure the factor structure as well as principal component analysis and varimax rotation to purify the observable variables for all constructs. No variable in a construct is dropped if the loading is smaller than 0.50, and cross loading is greater than 0.40. A factor is retained as a construct if its eigenvalue is greater than 1.0 (Churchill, 1979; Hair et al., 2010). Table 15

2 displays the descriptive statistics of the constructs. The Cronbach’s alpha (α) value of a construct is used to assess construct reliability with the respective observable variables. As shown in Table 3, the alpha values are greater than 0.70. Thus, the reliability of each construct is established. In addition, we use structural equation modeling with AMOS to analyze common variance bias, according to the recommendation of Podsakoff et al. (2003). We add a construct in the structure model and connect it to all observable variables. The construct serves as the common method factor to control the common variance among all endogenous and exogenous constructs. The analytical results of ‘with’ and ‘without’ the common method factor models indicate that there are no significant differences between the estimated parameters and fit indices between the models, which indicates that common method bias is unlikely to affect hypothesis testing. In addition, we justify the construct validity by examining the extent to which the observable variables can measure the theoretical constructs (Bagozzi et al., 1991; Gerbing and Anderson, 1988). The validity indicates the measurement accuracy and suggests that the sample data represent the ‘true view’ of population. In this study, we use confirmatory factor analysis (CFA) to evaluate construct validity in terms of convergent validity and discriminant validity. First, convergent validity is the extent to which observable variables converge to a manifested construct with high loading coefficients. It examines whether the loading coefficient of an observable variable is significantly greater than 0.50 and whether the corresponding t-value is greater than 2.0 (Anderson and Gerbing, 1988; Bagozzi et al., 1991). As shown in Table 3, all observable variables are significantly loaded onto their respective constructs with high coefficient values, which justify the convergent validity of seven constructs in the conceptual model. Second, discriminant validity is the extent to which a construct is truly distinct from other constructs. A high degree of the validity indicates that a construct is unique and captures the propensity of the represented concept that other constructs do not. The validity is analyzed by compelling CFA models for chi-square differences (∆χ2) and statistical significance at p < 0.01 for the pairs of constructs, which allows the correlation between two constructs and fixes the correlation at unity (1.0). A significant ∆χ2 for the free and fixed pairs of constructs indicates the discriminant validity of two constructs (Anderson and Gerbing, 1988; Bagozzi et al., 1991). Another assessment is

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performed by comparing the average variance extracted (AVE) values of two constructs (e.g., for constructs of A and B, we get AVEA and AVEB) with the square of the correlation coefficient between the two constructs (C2AB). AVE values that are greater than the squared correlation coefficient (AVEA and AVEB > C2AB) indicate discriminant validity (Anderson and Gerbing, 1988; Fornell and Larcker, 1981). We analyze 21 pairs of the constructs in the structural model and find that all of the χ2 differences are significant. Table 3 shows that all AVE values are greater than the squared correlation coefficients of corresponding pairs, which justify the discriminant validity of the constructs. ~ Insert Table 2 and Table 3 ~

4. Analysis and Results 4.1. Measurement model We employ the two-step procedure suggested by Anderson and Gerbing (1988) to test the conceptual model. First, CFA is conducted to examine the measurement model and unidimensionality of constructs (Bagozzi et al., 1991; Gerbing and Anderson, 1988). The criteria used to assess the model fitness include the normed fit index (NFI), incremental fit index (IFI), Tucker-Lewis index (TLI), and comparative fit index (CFI). A value of 0.90 or higher in these indices suggests a sufficient fit (Anderson and Gerbing, 1988; Byrne, 2010; Hair et al., 2010). Chi-square (χ2) test is also conducted to evaluate the goodness of fit between the reproduced and observed covariance matrices. The root mean squared error of approximation (RMSEA) is used to estimate the discrepancy between the original and reproduced covariance matrices in the population. A RMSEA value of below 0.08 represents a reasonable fit. The results indicate that the measurement model fit indices include χ2 = 1034.08, p < 0.01, df = 563, χ2/df = 1.84, TLI = 0.936, NFI = 0.909, IFI = 0.940, CFI = 0.940, and RMSEA = 0.005, which indicate that the measurement model fits significantly well. The observable variables are sufficiently loaded to their underlying constructs as the loadings are greater than 0.50. The measurement model confirms the unidimensionality of the constructs. Table 3 displays the measurement statistics for the measurement model and constructs including item loadings, t-statistics of loadings, and composite reliability.

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4.2. Hypothesis Testing We use SEM and the maximum likelihood procedure of AMOS to estimate the fit indices of the structure model and path coefficients (Anderson and Gerbing, 1988; Byrne, 2010). The same criteria used to test the measurement model are applied to examine the structural model. As shown in Fig. 2, the analysis of M1 results in the goodness of fit indices (χ2 = 1502.22, df = 794, χ2/df = 1.89, p < 0.001, CFI = 0.926, TLI = 0.919, IFI = 0.926, NFI = 0.893, RMSEA = 0.05). In addition, we suggest seven compelling models and respectively conduct structural equation modeling analysis to test these alternative models (Baron and Kenny, 1986). Table 4 displays the analytical results that include fit indices, coefficients of structure paths, and added path estimations. For instance, an alternative model M2, which omits the construct of OCR, is suggested to compare with M1. The comparisons of the parameters between M1 and M2 show that (a) The path coefficient from perceived effectiveness to satisfaction decreases from 0.81 to 0.78; (b) The path coefficient from perceived effectiveness to trust in intermediary changes from 0.59 to 0.51; (c) The path coefficient from structural assurance to trust in intermediary alters from 0.27 to 0.26; and (d) The path coefficient from familiarity to trust in intermediary reduces from 0.17 to 0.15, while other two insignificant paths remain insignificant. We also suggest three mediating models M3, M4, and M5 to respectively test whether OCR directly affects consumer satisfaction, trust in intermediary, and continuance use. The relevant fit indices and path coefficients are shown in Table 4. The outcomes of these models indicate that perceived effectiveness, perceived structural assurance, and familiarity mediate the relationships between OCR and consumer beliefs. Moreover, we examine whether consumer perceptions directly affect continuance use and the extent to which satisfaction and trust in intermediary mediate the effects of consumer perceptions. Thus, we suggest three alternative models (M6, M7, and M8) by adding a path from perceived effectiveness, or perceived structural assurance, or familiarity to continuance use, respectively. As shown in Table 4, the analytical results of M6 suggest that satisfaction has a partial mediating effect on the relationships between consumer perceptions and continuance use, as the path from perceived effectiveness to continuance use is significant, while the analytical results of M7 and M8 show that trust in intermediary fully mediates the relevant effects of consumer perceptions on continuance use.

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The outcomes of compelling model analysis offer a holistic view of hypothesis testing and rigorously validate the causal structure of the conceptual model. The empirical findings in relation to the hypotheses are summarized as follows. First, the empirical results support H1, H2 and H3, because of the relevant path coefficients β1 = 0.49 (t = 6.63, p < 0.01), β2 = 0.33 (t = 4.63, p < 0.01), and β3 = 0.25 (t = 3.78, p < 0.05), respectively, which suggest that OCR significantly affects consumer perceptions in terms of perceived effectiveness, perceived structural assurance, and familiarity with intermediary. Second, the analytical results support H4a and H4b, because of β4a = 0.81, t = 8.40, p < 0.01 and β4b = 0.59, t = 10.16, p < 0.01. The significant results indicate that perceived effectiveness is an important predictor of consumers’ briefs, because it positively and significantly influences consumer satisfaction and trust in intermediary. Third, H5a receives little support (β5a = -0.09, t = -0.20, p < 0.2), which suggests that consumers may not be affectively satisfactory with the cost brought out by perceived structural assurance, as they know that protective assurance requires them to pay for it. However, H5b is supported (β5a = 0.27, t = 5.07, p < 0.01), which indicates that perceived structural assurance enhances trust in intermediary. Since consumers appreciate that transactions with intermediary can be protected, they cognitively accept the necessity of structural assurance and consider it as intermediary’s integrity and benevolent action. Moreover, H6a receives limited support (β6a = -0.11, t = -1.94, p = 0.23 > 0.05), which suggests that consumers’ familiarity with intermediary may not lead to satisfaction with online group-buying. However, H6b receives a strong support (β 6b = 0.17, t = 4.01, p < 0.01), indicating that consumers’ familiarity with intermediary may reinforce their trust in intermediary. Lastly, H7 is partially supported, though the path efficiency is significant (β7 = 0.14, t = 2.60, p < 0.05). This is because satisfaction significantly mediates the relationship between perceived effectiveness and continuance use, while perceived structural assurance and familiarity have limited effects on satisfaction. It has also been identified that perceived effectiveness has a direct effect on continuance use. On the other hand, H8 is strongly supported (β8 = 0.13, t = 2.46, p < 0.05). In line with the analytical results in relation to H4b, H5b, and H6b, consumers’ trust in intermediary fully mediates the effects of

19

perceived effectiveness, perceived structural assurance, and familiarity with intermediary on continuous participation in online group-buying. ~ Insert Table 4 and Fig. 2 ~

5 . Discussion This study empirically tests the conceptual model together with the hypotheses using the survey data with regard to a popular online group-buying intermediary, which results in an appropriate causal structure and meaningful findings with theoretical significance. It has been validated that OCR has a positive and significant effect on consumer perceptions in terms of perceived effectiveness, perceived structural assurance, and familiarity with online intermediary, while consumer perceptions reinforce consumer satisfaction and trust in intermediary, which eventually lead to continuance use of online group-buying. Particularly, perceived effectiveness positively affects consumer satisfaction, as consumers may have utilitarian orientation in online group-buying, while consumer satisfaction may be a sentimental response, because it is value-oriented and transaction scenario-sensitive attribute. More importantly, perceived effectiveness, structural assurance, and familiarity have significant impacts on consumers’ trust in intermediary, which may serve as key cornerstones to the sustainability of online group-buying operations. The present work makes contributions to research by advancing the theoretical understanding of the relationships between OCR and online group-buying participation. The empirical findings suggest that the theoretical underpinnings of social exchange and institution-based trust can be blended to theorize a conceptual model for articulating consumer review and continuance use of online exchanges. The present work moves forward the research in relation to online review from the previous works such as Chen and Xie (2008), Jing and Xie (2011), Mudambi and Schuff (2010), and Park et al. (2007). In particular, our conceptual model provides a causal framework that reflects consumers’ complex decision-making process with regard to impact of consumer review in the virtual environment. Our empirical analysis validates the structural relationships of the relevant constructs in the conceptual model and reveals that OCR significantly affects perceived effectiveness, perceived

20

structural assurance, and consumers’ familiarity with online intermediary, which further influences consumer beliefs in terms of consumers’ satisfaction and trust in intermediary. At the same time, consumer satisfaction and trust in intermediary mediate the effects of the antecedents on consumers’ continuance use, which is consistent with the previous works that were conducted in different contexts (e.g., Pavlou and Gefen, 2004; Kim et al., 2008; Bhattacherjee and Lin, 2015; Chang et al., 2015). The present empirical findings indicate that the theory of social exchange and the theory of institution-based trust not only underpin our conceptual model, but also provide guidance and rationale for studying OCR or other forms of social media in association with various online shopping websites. It has been conceptualized that OCR may strength perceived effectiveness, structural assurance, and familiarity with intermediary’s institutional mechanism, while enhanced perceptions have considerable impacts on consumer satisfaction and trust in intermediary. The confirmed causal model structure shows that the consequential impact of OCR on continuance use of online groupbuying is mediated by consumer perceptions and psychological beliefs. Such a causal structure may reflect the decision-making process of consumers, through which individuals may overcome the barrier of information asymmetry through acquiring feedbacks from other consumers to reinforce cognitive judgments and purchase decisions. Therefore, the present work paves an avenue for exploring the effects of other forms of social media or social commerce on consumer behavior in association with online shopping and online exchanges. In addition, the present study makes contributions to practice, because the present findings possess managerial implications for online service operations. As a social media hosted by online intermediary, OCR can serve as an efficient communication channel for many different consumers. Our analytical results suggest that OCR positively and significantly affects consumer perceptions and therefore enhances customer satisfaction and institution-based trust. The online intermediary should effectively utilize such a platform to generate desirable effects on consumer perceptions and improve customer relationships. In particular, the institutional mechanism of the online group-buying service provider should be well established and thoroughly perceived by the consumers, because perceived structure assurance considerably influences on institution-based trust. The online intermediary must

21

govern the online service operations through implementing appropriate institutional mechanisms and effectively promote its institutional mechanisms to consumers. In general, a reputable online intermediary has advantages, since its institutional mechanisms can lessen consumers’ concerns about the risks of getting substandard products or services. Therefore, the online group-buying intermediary must consistently improve its institutional mechanisms and implement a series of measures and policies to ensure the rigorousness of online service operations and protect the transactions data and legal rights of customers. Furthermore, the present empirical findings suggest that OCR plays an important role in decreasing information and knowledge asymmetry as it may serve as a platform that enables individuals to share opinions and views with regard to different products and services, which may facilitate the cognitive judgment and decision-making of other consumers in their shopping processes. At the same time, OCR may also serve as a useful communication channel for the online intermediary to gather feedback and understand the needs of consumers. Thus, the online intermediary should make use of social media to facilitate consumer interactions and let consumers appreciate the economic and social benefits of online group-buying services by developing consumers’ awareness, spreading goodwill to consumers, and improving online group-buying service operations, which may help the online intermediary retain customers, penetrate new markets, and increase market share. Finally, the present work provides practically useful insights for managing online groupbuying services. As a collective shopping activity over the Internet, online group-buying is an exchange process that concurrently involves a number of consumers who may have different expectations. Therefore, the online intermediary should devote itself to meet consumers’ expectations in terms of price, convenience, and transactions security. In addition to the provision of OCR, the online group-buying platform should effectively enable multiple consumers to participate in a particular group-buying process, as online group-buying is different from individual online shopping from a supplier. Actually, it is not uncommon that the consumers participating in group-buying may look for more competitive price. Therefore, the products and services promoted through online groupbuying should possess economic value to satisfy the needs of consumers. In comparison with offline

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group-buying, the online group-buying platform may offer timely steep discount, which may help gather consumers faster in a particular group-buying activity. The online group-buying platform may also constantly offer a variety of competitive goods and value-added services to encourage more consumers to continuously participate in online group-buying transactions.

6. Conclusion This study systematically validates our conceptual model in line with the social exchange theory and the theory of institution-based trust. The present findings make contributions to research and practice. In summary, the empirical results not only reveal that OCR in association with online group-buying is an important precursor for enhancing consumer perceptions in terms of perceived effectiveness, perceived structure assurance, and familiarity with intermediary, but also advance the theoretical understanding of the mediating effects of consumer satisfaction and trust in intermediary on the relationships between consumer perceptions and continuance use of online group-buying. Particularly, it has been justified that consumer satisfaction and trust in intermediary have significant impacts on continuous participation in online group-buying activities, which is of importance to the sustainable development of online group-buying services. In addition, the present work provides useful insights for the implementation and application of social media in electronic commerce service operations. It is suggested that online intermediaries should undertake service operations in line with market mechanisms, trustfully meet the needs of consumers, and consistently enhance institution-based trust to strengthen consumers’ confidence in online services. Future research can be carried out to gather longitudinal data to articulate the impact of social media on consumer satisfaction and trust at the aftermath of consumption of goods from participating in online exchanges. It is meaningful examine causal structure and relationship dynamics with regard to the stability and variability of consumer satisfaction and institution-based trust. It is also meaningful to articulate the effects of social and economic attributes on consumer behavior in association with electronic commerce or mobile commerce in different contexts.

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References Anderson, J.C., Gerbing, D.W. 1988. Structural equation modeling in practice: review and recommended two-step approach. Psychological Bulletin 103 (3), 411-423. Baber, A., Thurasamy, R., Malik, M.I., Sadiq, B., Islam, S., Sajjad, M. 2016. Online word-of-mouth antecedents, attitude and intention-to-purchase electronic products in Pakistan. Telematics and Informatics 33 (2), 388-400. Bagozzi, R.P., Yi, Y., Phillips, L.W. 1991. Assessing construct validity in organizational research. Administrative Science Quarterly 36 (1), 421-458. Bakos, Y. 1998. The emerging role of electronic marketplaces on the Internet. Communications of the ACM 41 (8), 35-42. Baron, R.M., Kenny, D.A. 1986. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51, 1173-1182. Bhattacherjee A., Lin C. P. 2015. A unified model of IT continuance: Three complementary perspectives and crossover effects,” European Journal of Information Systems, 24, 364-373.2 Bolton, R.N., Drew, L.L. 1991. A multistage model of customer’s assessment of service quality and value. Journal of Consumer Research 17, 375-384. Bolton, R.N., Lemon, K.N. 1999. A dynamic model of customers’ usage of services: usage as an antecedent and consequence of satisfaction. Journal of Marketing Research 36, 171-186. Byrne, B.M. 2010. Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming. Routledge, Taylor & Francis Group: New York. Chang, C.C., 2013. Examining users’ intention to continue using social network games: a flow experience perspective. Telematics and Informatics 30 (4), 311-321. Chang, I.C., Chang, C.H., Wu, J.W., Huang, T.C.K. 2015. Assessing the performance of long-term care information systems and the continued use intention of users. Telematics and Informatics 32 (2), 273-281. Chen, Y., Xie, J. 2008. Online consumer review: word-of-mouth as a new element of marketing communication mix. Management Science 54 (3), 477-491. Churchill, G.A. 1979. A paradigm for developing better measures of marketing constructs. Journal of Marketing Research 16 (2), 64-73. Collquitt, J.A., Rodell, J.B. 2011. Justice, trust, and trustworthiness: a longitudinal analysis integrating three theoretical perspectives. Academy of Management Journal 54 (6), 1183-1206. 24

Collquitt, J.A., Scott, B.A., LePine, J.A. 2007. Trust, trustworthiness, and trust propensity: a metaanalytic test of their unique relationships with risk taking and job performance. Journal of Applied Psychology 92 (4), 909-927. Cronin, J.J., Brady, M.K., Hult, T.M. 2000. Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intention in service environments. Journal of Retailing 76 (2), 193-218. Emerson, R.M. 1976. Social exchange theory. American Review of Sociology 2, 335-362. Engler, T.H., Winter, P., Schulz, M. 2015. Understanding online product ratings: a customer satisfaction model. Journal of Retailing and Consumer Services 27, 113-120. Fornell, C., Larcker, D.F. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18 (1), 39-50. Garbarino, E., Johnson, M.S. 1999. The different roles of satisfaction, trust, and commitment in customer relationships. Journal of Marketing 63 (2), 70-87. Gefen, D., Karahanna, E., Straub, D.W. 2003. Inexperience and experience with online stores: the importance of ATM and trust. IEEE Transactions on Engineering Management 50 (3), 307-321. Gerbing, D.W., Anderson, J.C. 1988. An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research 25 (2), 186-192. Groupon Hong Kong. About Groupon Hong Kong. https://www.groupon.hk Gulati, R. 1995. Does familiarity breed trust? the implications of repeated ties of contractual choices in alliances. Academy of Management Journal 38, 85-112. Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. 2010. Multivariate Data Analysis: A Global Perspective. Pearson Prentice Hall: New Jersey. Homans, G.C. 1958. Social behavior as exchange. American Journal of Sociology 63, 597-606. Jing, X., Xie, J. 2011. Group buying: a new mechanism for selling through social interactions. Management Science 57 (8), 1354-1372. Kim, D.J., Ferrin, D.L., Rao, H.R. 2008. Trust and satisfaction, two stepping stones for successful ecommerce relationships: a longitudinal exploration. Information Systems Research 20 (2), 237257. Komiak, S.Y.X., Benbasat, I. 2006. The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly 30 (4), 941-960.

25

Lee, Y., Kwon, O. 2011. Intimacy, familiarity and continuance intention: an extended expectation– confirmation model in web-based services. Electronic Commerce Research and Applications 10 (3), 342-357. Liao, Z., Cheung, M.T. 2001. Internet-based e-shopping and consumer attitudes: an empirical study. Information & Management 38 (5), 299-306. Liao, Z., Shi, X. 2009. Consumer perceptions of Internet-based e-retailing: an empirical research in Hong Kong. Journal of Services Marketing 23 (1), 24-30. Liu, Y., Sutanto, J. 2012. Buyers’ purchasing time and herd behavior on deal-of-the-day group buying websites. Electron Markets 22, 83-93. Luhmann, N. 2000. Familiarity, confidence, trust: problems and alternatives. In: Gambetta, D. (Ed.), Trust: Making and Breaking Cooperative Relations, Department of Sociology, University of Oxford, 94-107. McKnight, D.H., Choudhury, V., Kacmar, C. 2002. Developing and validating trust measures for ecommerce: an integrative typology. Information Systems Research 13 (3), 334-359. Mudambi, S.M., Schuff, D. 2010. What makes a helpful online review? a study of customer reviews on amazon.com. MIS Quarterly 34 (1), 185-200. Oliver, R.L. 1980. A cognitive model of the antecedents and consequences of satisfaction decisions. Journal Marketing Research 17, 460-469. Oliver, R.L. 1997. Satisfaction: A Behavioral Perspective on the Consumer. McGraw-Hill: New York. Pappas, N. 2016. Marketing strategies, perceived risks, and consumer trust in online buying behavior. Journal of Retailing and Consumer Services, 29, 92-103. Park, D.H., Kim, S. 2008. The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic Commerce Research and Applications 7 (4), 399-410. Park, D.H., Lee, J., Han, I. 2007. The effect of online consumer review on consumer purchasing intention: the moderating role of involvement. International Journal of Electronic Commerce 11 (4), 125-148. Pavlou, P.A., Dimoka, A. 2006. The nature and role of feedback text comments in online marketplaces: implications for trust building, price premiums, and seller differentiation. Information Systems Research 17 (4), 392-414. Pavlou, P.A., Gefen, D. 2004. Building effective online marketplaces with institution-based trust. Information Systems Research 15 (1), 37-59.

26

Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y., Podsakoff, N.P. 2003. Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology 88, 879-903. Ramayah, T., Ling, N.S., Taghizadeh, S. K., Rahman, S.A. 2016. Factors influencing SMEs website continuance intention in Malaysia. Telematics and Informatics 33 (1), 150-164. Rese, A., Schreiber, S., Baier, D. 2014. Technology acceptance modeling of augmented reality at the point of sale: Can surveys be replaced by an analysis of online reviews? Journal of Retailing and Consumer Services, 21 (5), 869-876. Rishika, R., Kumar, A., Janakiraman, R., Bezawada, R. 2013. The effect of customers’ social media participation on customer visit frequency and profitability: an empirical investigation. Information Systems Research 24 (1), 108-127. Schindler, R.M., Bickart, B. 2012. Perceived helpfulness of online consumer reviews: the role of message content and style. Journal of Consumer Behaviour 11 (3), 234-243. Sha, W. 2008. Types of structural assurance and their relationships with trusting intentions in business-to-consumer e-commerce. Electronic Markets 19 (1), 43-54. Shi, X., Liao, Z. 2013. Managing supply chain relationships in the hospitality services: an empirical study of hotels and restaurants. International Journal of Hospitality Management 35, 112-121. Shiau, W.L., Luo, M.M. 2012. Factors affecting online group buying intention and satisfaction: a social exchange theory perspective. Computers in Human Behavior 28 (6), 2431-2444. Sweeney, J.C., Soutar, G. 2001. Consumer perceived value: the development of multiple item scale. Journal of Retailing 77 (2), 203-220. Tan, W.K., Lee, P.W., Hsu, C.W., 2015. Investigation of temporal dissociation and focused immersion as moderators of satisfaction–continuance intention relationship: smartphone as an example. Telematics and Informatics 32 (4), 745-754.

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Table 1. Constructs and items Construct

Item

Description

Online consumer review (OCR) (EV = 2.71, VE = 67.73%)

OCR1 OCR2

The information on OCR from other consumers is inspiring. The online group-buying experience by other consumers is interesting.

0.78 0.76

OCR3

The consumer’s comments on online group-buying are informative.

0.70

OCR4

The consumers’ opinions on online group-buying are helpful.

0.66

PE1

Using online group-buying is convenient.

PE2

Using online group-buying saves money.

0.64 0.69

PE3

Using group-buying saves time.

0.67

PE4

Online group-buying is a beneficial way of shopping.

0.68

PE5

I enjoy information exchange with other consumers.

0.76

PE6

I would share my experience and information with other consumers.

0.74

PE7

I have a sense of online group-buying community.

0.73

PE8

I appreciate the social value of online group-buying.

0.63

PSA1

Groupon has clear and rigorous privacy and security policy in force.

PSA2

Groupon has implemented privacy and security measures.

0.72 0.76

PSA3

I perceive that Groupon can lawfully protect customer rights.

0.70

PSA4

I feel that online group-buying from Groupon has low risk.

0.66

PSA5

I feel that transactions with Groupon are free of security problem.

0.65

FAM1

I can easily complete the group-buying process with Groupon.

FAM2

I am good at searching for valuable goods and services with Groupon.

0.74 0.81

FAM3

I am familiar with the group-buying mechanisms with Groupon.

0.81

FAM4

I am skillful in purchasing quality goods and services with Groupon.

0.86

FAM5

I know how to get the best discount from group-buying with Groupon.

0.72

TI1

I would like to depend on Groupon to complete my group-buying.

0.63

TI2

I am confident in Groupon mechanism of online group-buying.

0.81

TI3

Groupon is reliable in providing goods and services.

0.82

TI4

Groupon behaves consistently in accomplishing transactions.

0.76

TI5

Groupon keeps its promises in performing transactions.

0.75

SAT1

I make effective decisions of group-buying.

SAT2

I am satisfied with online group-buying services.

0.81 0.72

SAT3

My expectation is met from online group-buying.

0.61

SAT4

I am happy with the online group-buying process.

0.81

CU1

I would continue to use online group-buying.

CU2

I would repeatedly use online group-buying services.

0.79 0.71

CU3

I would introduce online group-buying to other consumers.

0.69

CU4

I pay attention to goods and services from online group-buying.

0.78

CU5

I would recommend my friends to participate in online group-buying.

0.76

Perceived effectiveness (PE) (EV = 2.73, VE = 64.18%)

Perceived structural assurance(PSA) (EV = 3.48, VE = 69.55%)

Familiarity (FAM) (EV = 3.93, VE = 78.64%)

Trust in intermediary (TI) (EV = 3.77, VE = 75.43%)

Satisfaction (SAT) (EV = 2.85, VE = 71.21%)

Continuance use (CU) (EV = 3.12, VE = 62.47%)

Loading

Notes: EV = Eigenvalue; VE = Variance explained

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Table 2. Descriptive statistics Construct

Mean

SD

C1

C2

C1 Online consumer review

4.74

1.17

0.82

C2 Perceived effectiveness

4.97

0.85

0.42**

0.83

C3 Structural assurance

4.45

0.99

0.27**

0.56**

**

**

0.52**

0.91

C4

C5

C6

4.32

1.27

0.23

C5 Satisfaction

4.95

0.98

0.35**

0.71**

0.32**

0.25**

0.95

0.35

**

0.78

**

0.68

**

**

0.50**

0.17

**

0.46

**

0.22

**

*

**

C7 Continuance use

4.76 4.90

0.84

C7

0.83

C4 Familiarity

C6 Trust in intermediary

0.47

C3

0.60

0.14

0.80

0.43

0.97 0.36**

0.94

Notes: The diagonal value of each construct is the square root of average variance extracted (AVE). * p < 0.05; ** p < 0.01

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Table 3. Measurements and reliability estimates Construct

Online consumer review (OCR)

Perceived effectiveness (PE)

Perceived structural assurance (PSA)

Familiarity (FAM)

Satisfaction (SAT)

Trust in intermediary (TI)

Continuance use (CU)

Item

Loading

t-value

Cronbach’s Alpha (α)

Composite Reliability (CR)

Average Variance Extracted (AVE)

OCR1 OCR2 OCR3 OCR4 PE1 PE2 PE3 PE4 PE5 PE6 PE7 PE8 PSA1 PSA2 PSA3 PSA4 PSA5 FAM1 FAM2 FAM3 FAM4 FAM5 SAT1 SAT2 SAT3 SAT4 TI1 TI2 TI3 TI4 TI5 CU1 CU2 CU3 CU4 CU5

0.87 0.86 0.82 0.74 0.74 0.77 0.75 0.75 0.81 0.80 0.80 0.73 0.85 0.87 0.84 0.81 0.80 0.88 0.91 0.91 0.92 0.80 0.87 0.84 0.74 0.87 0.79 0.90 0.90 0.87 0.86 0.76 0.78 0.75 0.82 0.83

12.89 12.72 12.78 9.57 12.56 12.72 12.48 13.46 13.28 13.67 12.90 12.87 12.65 12.89 13.63 13.15 14.70 23.68 23.72 23.48 19.83 19.72 16.35 12.37 16.58 20.97 20.89 21.30 20.10 19.24 15.65 10.38 10.48 11.93 12.04 10.59

0.839

0.893

0.676

0.901

0.920

0.692

0.890

0.919

0.696

0.927

0.948

0.820

0.856

0.897

0.639

0.918

0.939

0.755

0.849

0.924

0.892

Notes: Model fit indices: χ2 /df = 1034/563 = 1.84 (p < .001), TFI = 0.94, NFI = 0.91, CFI = 0.94, IFI = 0.94, RMSEA = 0.005

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Table 4. Structural model estimation and fit Indices

Control variables Gender Age Education Online shopping experience (year) Visit frequency (week) Group-buying via Groupon (month) Structure model path OCR ⇒ PE OCR ⇒ PSA OCR ⇒ FAM PE ⇒ SAT PE ⇒ TI PSA ⇒ SAT PSA ⇒ TI FAM ⇒ SAT FAM ⇒ TI SAT ⇒ CU Trust ⇒ CU OCR ⇒ CU OCR ⇒ SAT OCR ⇒ TI PE ⇒ CU PSA ⇒ CU Familiarity ⇒ CU Structure model fit indices χ2 df χ2/df P-value CFI TLI IFI NFI RMSEA

M1

M2

M3

M4

M5

M6

M7

M8

-0.07 -0.15 -0.05 0.03 0.02 -0.04

-0.07 -0.16 -0.04 0.05 -0.01 -0.03

-0.07 -0.16 -0.05 0.03 0.02 -0.04

-0.07 -0.16 -0.05 0.03 0.02 -0.04

-0.07 -0.15 -0.05 0.03 0.02 -0.04

-0.06 -0.13 -0.05 0.03 0.02 -0.04

-0.07 -0.16 -0.05 0.03 0.02 -0.04

-0.07 -0.15 -0.04 0.05 -0.01 -0.03

0.49** 0.33** 0.25** 0.81** 0.59** -0.08 0.27** -0.11 0.17* 0.32** 0.24** -0.03

0.49** 0.33** 0.25** 0.81** 0.59** -0.09 0.27** -0.11 0.17* 0.32** 0.24**

0.49** 0.33** 0.25** 0.81** 0.59** -0.08 0.27** -0.11 0.17* 0.32** 0.24**

0.49** 0.33** 0.25** 0.81** 0.59** -0.09 0.27** -0.11 0.17* 0.14* 0.13*

0.49** 0.33** 0.25** 0.81** 0.59** -0.08 0.27** -0.11 0.17* 0.32** 0.29**

0.49** 0.33** 0.25** 0.81* 0.59** -0.08 0.27** -0.11 0.17* 0.30** 0.36**

0.49** 0.33** 0.25** 0.81** 0.59** -0.08 0.27** -0.11 0.17* 0.32** 0.24**

0.78** 0.51** -0.08 0.26** -0.11 0.16* 0.33** 0.24**

0.05 -0.03 0.54** 0.02 -0.02 1502.22 794 1.89. <.000 0.93 0.92 0.926 0.89 0.05

1308.51 643 2.04 <.000 0.92 0.91 0.92 0.84 0.06

1502.09. 793 1.89 <.000 0.93 0.92 0.93 0.86 0.06

1501.29 793 1.89 <.000 0.93 0.92 0.93 0.86 0.05

1501.87 793 1.89 <.000 0.93 0.92 0.93 0.86 0.05

1493.41 793 1.88 <.000 0.93 0.92 0.93 0.87 0.05

1502.18 793 1.89 <.000 0.93 0.92 0.93 0.86 0.06

1498.60 793 1.89 <.000 0.93 0.92 0.93 0.87 0.06

Notes: * p < 0.05; ** p < 0.01

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_________________________________________________________________________ Fig. 1. Conceptual model

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_________________________________________________________________________ Fig. 2. Results of structural equation modeling Notes: ** p < 0.01, * p < 0.05; ns - denotes non-significance

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Online consumer review and group-buying participation: The mediating effects of consumer beliefs

Highlights • Examine online consumer review and consumer participation in online group-buying • Articulate the relationships between consumers’ beliefs and group-buying participation • Unveil the mediating effects of consumer beliefs on online group-buying continuance • Provide managerial insights for the application of social media in electronic commerce

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