Facebook users' motivation for clicking the "Like" button

Main Article Content

Chih-Yu Chin

Hsi-Peng Lu

Chao-Ming Wu

Cite this article:  Chin, C.-Y., Lu, H.-P., & Wu, C.-M. (2015). Facebook users' motivation for clicking the "Like" button. Social Behavior and Personality: An international journal, 43(4), 579-592.


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To explore the motivation and behavior of Facebook users when clicking the “Like” button, we analyzed the behaviors of 743 university student Facebook users using motivational theory and the theory of reasoned action. The main study findings were as follows: (a) hedonic motivation, utilitarian motivation, compliance motivation, conformity motivation, and affiliation motivation all had a positive impact on attitudes toward “Like”-clicking behaviors; (b) subjective norms and attitudes toward “Like”-clicking behaviors all had a positive impact on behavioral intention, and (c) behavioral intention had a positive impact on actual behaviors. These findings provide a valuable basis for constructing an explanatory model for “Like”-clicking behaviors of Facebook community platform users, as well as making significant practical contributions to enhance social and commercial benefits for businesses and individuals.

Facebook, established on February 4, 2004, was the first form of social media to create the mechanism of clicking the “Like” button, which has since become an important social networking activity to maintain interpersonal relationships. Businesses may also be able to understand consumers’ point of view according to the number of “Likes” they receive on specific Facebook posts. This may, in turn, allow them to analyze and understand consumers’ attitudes and evaluations of products and services, their intention to buy these products and services, and their levels of brand acceptance (Poyry, Parvinen, & Malmivaara, 2013). In the past, intelligence concerning such consumer behaviors could only be obtained through sizable monetary and human efforts; however, consumers’ opinion of products can now be clearly understood through social platforms, such as Facebook. Therefore, in this era of social networking, how often users click the “Like” button has become a research area that cannot be overlooked when considering how to maintain consumer relations in business. However, as yet it is not known exactly why Facebook users click the “Like” button. What is their motivation? What factors influence “Like”-clicking behavior? Scholars and businesspeople who study social networking and marketing must pay attention to these factors.

In previous studies of related areas in which websites and blogs were the main focus, the forwarding of messages has mainly been influenced by motivation to share, without which information flow is hindered (Bao & Bouthillier, 2007). The design of an incentive mechanism is also helpful for increasing the motivation to forward messages (Chu, 2007). In addition, individual cognitive and social influences are crucial factors affecting the behavioral intention to forward messages (Kankanhalli, Tan, & Wei, 2005; Koh & Kim, 2004). As social networking platforms have emerged, scholars have begun to conduct relevant research on how to use these (Poyry et al., 2013; Shen, Brdiczka, & Ruan, 2013); however, experimental studies on the motivations and behaviors pertaining to clicking the “Like” button are still relatively rare.

The sharing of self-dynamics and two-way interactions with others via social networking platforms are new trends in social contact, entertainment, information transfer, and facilitating instant interpersonal interactions. However, when text, pictures, links, and other content are shared on social networking platforms, such as Facebook, are new attitudes and behaviors pertaining to clicking the “Like” button induced among those who see this new information? What motives actually bring about these attitudes and behaviors? Do the person posting, the number of “Likes” already received, and the posted content influence the decision to click the “Like” button? Does the “Real-Name Registration” requirement that characterizes Facebook influence users’ behavior due to worry regarding comments from others after they click the “Like” button? In this study, we will further discuss and explore these questions. In order to gain a deeper understanding of why Facebook users click the “Like” button on certain content, we developed research structures and hypotheses based on the motivational theory and the theory of reasoned action (TRA).

Conceptual Framework and Hypotheses Development

Hedonic motivation, which is related to playfulness, entertainment, and enjoyment, is a major human inclination that determines behaviors related to shopping (Sit & Merrilees, 2005). This motivation has also been noted in regard to the Internet in general and social networking websites specifically (Sledgianowski & Kulviwat, 2009). Atkinson and Kydd (1997) found that perceived playfulness has an impact on Internet users’ attitude and behavior, and Szymanski and Hise (2000) proposed the idea of seeking online hedonic value as an important motivator for consumers’ online shopping behavior. Wu, Chen, and Chung (2010) studied entertainment websites and found that user satisfaction, motivation, and behavior regarding these websites are all highly correlated. Therefore, hedonic motivation, such as playfulness and entertainment, can be considered an important factor in how Internet users evaluate websites, how they form attitudes toward these websites, and how they decide to act on these attitudes. In this study, we proposed that Internet users would also evaluate the content of social networking websites, such as Facebook, through hedonic motivation, and that they would subsequently form corresponding attitudes.
Hypothesis 1: Hedonic motivation will be positively related to attitude toward clicking the “Like” button in regard to content posted on Facebook.

Babin, Darden, and Griffin (1994) believe that human behavior can be driven by utilitarian motivation and that the purpose of a behavior is to meet expectations. Every human behavior has its purpose, such that, by undertaking an action, people hope to gain external benefits (e.g., acquiring information and resources) in order to establish their reputation, mutual benefits, and so on (He & Wei, 2009; Hsu & Lin, 2008). Utilitarian motivation results from the conscious pursuit of an intended consequence (Babin et al., 1994). For instance, people can gain extrinsic rewards (e.g., monetary awards, prizes) from participating in competitive events, but they can also gain a more intrinsic, personal, and emotional reward from the competitively derived pleasure of hedonic motivation (Deci, Betley, Kahle, Abrams, & Porac, 1981).

Utilitarian motivation is also an important factor for Internet users in evaluating websites or forming usage attitudes and behaviors. Baty and Lee (1995) suggested that whether or not resources can be obtained is a critical factor that influences Internet usage behavior. Alba et al. (1997) showed that there is a positive correlation between a website’s positive feedback, users’ perceptions of whether or not they obtained rich resources from the website, and the belief that they should continue using the website. Hummel and Lechner (2002) proposed that one of the reasons social networks exist is that they provide mutual benefits, such as information exchange and knowledge sharing, providing the user with the ability to obtain benefits, and that this is one of the factors that underpins the maintenance of such social networks. The content of the Facebook network can also be evaluated from the perspective of benefits, that, in turn, affect people’s “Like”-clicking attitudes and behaviors. Therefore, we formed the following hypothesis:
Hypothesis 2: Utilitarian motivation will be positively related to attitude toward clicking the “Like” button in regard to content posted on Facebook.

Compliance refers to the phenomenon whereby an individual changes his/her own behavior in order to take into consideration external expectations, namely, the expectations of others (Etzioni, 1975). In such a situation, people with high levels of authority can influence people with lower levels of authority (Tan & Yates, 2007). In a virtual community, the influence of the person making the social media post can result in the adoption of an obedient mindset (Kelman, 1961). Bagozzi and Dholakia (2002) conducted an empirical study on virtual communities and found that compliance is a key influencing social factor, in which the attitudes and behavior of the community members are easily influenced by specific reference groups within the community. In the Facebook community, most members can easily find out each other’s real identity, so according to compliance motivation, members who share a specific relationship with the person posting will click the “Like” button to express their acceptance of that particular individual. Therefore, we formed the following hypothesis:
Hypothesis 3: Compliance motivation will be positively related to attitude toward clicking the “Like” button in regard to content posted on Facebook.

Conformity refers to the phenomenon by which an individual who is under the influence of a group changes his/her behavior or mind about something in order to follow the most popular opinion, even though that opinion may be wrong (Lascu, Bearden, & Rose, 1995; Mowen & Minor, 1998). Conformity behavior has been proven to exist in the context of the Internet. Hanson and Putler (1996) conducted an experiment on two files that shared similar characteristics and were available on a free download website. The results showed that users made use of the number of downloads as a reference point for making their own decision about which one of the files to download. The file with the higher number of downloads attracted more new downloads, a result that supported the view that the big always get bigger. Dholakia and Soltysinski (2001) also found that users of a digital auction site were more inclined to bid for popular products with a higher number of bids and ignore similar products with very few bids. In this study, we proposed that conformity motivation would also exist in relation to how Facebook users browse articles or images and determine the quality of posts based on the number of “Likes” they attain. Therefore, we proposed the following hypothesis:
Hypothesis 4: Conformity motivation will be positively related to attitude toward clicking the “Like” button in regard to content posted on Facebook.

Affiliation motivation refers to the tendency for an individual in a group-based society to take friendly measures to obtain the approval of others, because of the inherent necessity to maintain harmonious interpersonal relationships with others (McClelland, 1987). Many researchers have suggested that maintaining existing interpersonal relationships is the primary motive for using Facebook (Ellison, Steinfield, & Lampe, 2007; Hoadley, Xu, Lee, & Rosson, 2010; Joinson, 2008; Lewis & West, 2009; Pempek, Yermolayeva, & Calvert, 2009; Sheldon, 2008). Facebook users will communicate and interact with their friends through various means on this social network and gain knowledge of their friends’ recent status through activity alerts, thereby allowing them to maintain close relationships (Lewis & West, 2009). Therefore, we proposed that Facebook users would show interest in their friends’ status and moods by clicking the “Like” button, thereby maintaining relationships with their friends and satisfying their affiliation motivation.
Hypothesis 5: Affiliation motivation will be positively related to attitude toward clicking the “Like” button in regard to content posted on Facebook.

Ajzen and Fishbein (1975) proposed the TRA, in which it is suggested that behavioral intention will be subject to the mutual influence of behavioral attitudes and subjective norms, whereas a person’s actual behavior will be influenced by his/her behavioral intention. In social media, many people are not very focused and browse the posts very quickly. Thus, in this study our aim was to test whether or not the relationship between attitudes, social norms, behavioral intent, and behavior would change. Therefore, the following hypotheses were proposed:
Hypothesis 6: Attitudes toward clicking the “Like” button will be positively related to behavioral intention to click in regard to content posted on Facebook.
Hypothesis 7: Subjective norm will be positively related to behavioral intention to click the “Like” button in regard to content posted on Facebook.
Hypothesis 8: Behavioral intention to click the “Like” button will be positively related to actual behavior to click in regard to content posted on Facebook.

Method

Participants

We recruited participants for this study from a pool of Taiwanese undergraduate students via the bulletin board system of a university from May to June 2014. We received 743 survey forms and after incomplete forms were excluded, 613 were confirmed to be valid. The sample comprised 53% men and 47% women, with most aged between 18 and 22 years, M = 19.75 years, SD = 0.96.

Table 1. Variable Definitions and Items Used in this Study

Table/Figure

Procedure

To reflect a true picture of user behavior in regard to clicking the “Like” button on Facebook, we adopted the field experiment method to control the study variables.

From the five control variables, which were hedonic, utilitarian, affiliation, compliance, and conformity motivations, we developed 32 different combinations of content posted on Facebook. Four positive and negative narratives were designated as hedonic and utilitarian. Two types of content were included for compliance, based on whether or not the people making the Facebook posts knew the participants. Conformity content was divided into two types based on the number of “Like” clicks received. The affiliation content was designated according to whether or not the posted content was related to the originators’ daily lives or mood changes, which we determined by sharing some celebrities’ posts about living status, mood, and so forth. The corresponding operationalization of these control variables is shown in Table 1.

We conducted a field experiment from May 27, 2014, to June 12, 2014 using the following process: The participant accessed a webpage containing the experimental procedure. The posted content on Facebook was displayed once the participant accessed the experiment webpage, and the system randomly displayed predetermined content. Next, the participants read and filled in the survey forms. The system then selected five posts in a random order and invited the participants to read them within the Facebook environment. The participants then answered questions based on what they had read in the posts. The experiment ended when the participants had completed the tasks, and the system displayed “End of experiment” on the webpage.

Measures

The research constructs and corresponding measurement items are shown in Table 1. We designed a survey containing three items to assess each construct, with the exception of actual behavior (one item). Participants rated their responses to the items on a 5-point Likert scale, where 1 indicated strongly disagree and 5 indicated strongly agree.

Data Analysis

Structural equation modeling was used to examine the relationships among the research constructs.

Results

Reliability and Validity Assessment

In terms of validity and reliability the Cronbach’s alpha values were between .86 and .96, the composite reliability values were above .70, and the average variation extracted values were all above .50 for all constructs. According to the above three indices, the constructs in this study exhibited good reliability (Fornell & Larcker, 1981). More detailed results are shown in Table 2.

Table 2. Factor Loading, Alpha, Composite Reliability, and Average Variance Extracted Values

Table/Figure

Note. CR = composite reliability, AVE = average variance extracted.

In terms of validity, the model parameters were estimated using the maximum likelihood method. The matching indices of parameter estimation results were as follows: normal theory weighted least-squares chi square (WLS χ2) = 767.29 (n = 613), degrees of freedom (df) = 251, WLS χ2/df = 3.06, and root mean square error of approximation (RMSEA) = .058. According to Steiger (1989) and Browne and Mels (1990), an RMSEA value of .05 or below indicates a good fit, between .05 and .08 indicates a relatively good fit, between .08 and .10 indicates an ordinary fit, and above .10 indicates a poor fit. In terms of the validity testing of the individual constructs, the standardized factor loadings (λ) for all constructs in this study were higher than .70, suggesting concurrent validity between all constructs and their corresponding measurement items (Nunnally, 1978). The detailed data are shown in Table 2.

Path Analysis

Path analyses were performed to validate the hypotheses, and the results of each path analysis reached significance (see Figure 1). All hypotheses were supported.

Table/Figure

Figure 1. Model diagram and corresponding path coefficients.
Note. * p < 0.1, ** p < .05, *** p < .01

Discussion

Implications

Based on the above research findings, we generated the following conclusions and recommendations:

Hedonic, utilitarian, and affiliation motivations. Because of hedonic, utilitarian, and affiliation motivations, content posted on Facebook positively affects readers’ attitudes toward the behavior of clicking the “Like” button, thereby affecting their behavioral intention and actual behavior. When content posted on Facebook triggered readers’ hedonic, utilitarian, and affiliation types of motivation, it increased the likelihood that they would click the “Like” button. In other words, if the poster hopes to have more readers click the “Like” button on Facebook, the posted content should be as amusing, entertaining, and interesting as possible in order to stimulate readers’ hedonic motivation. In addition, posted content that readers feel is useful, helpful, and informative more readily stimulates their utilitarian motivation. One can trigger readers’ affiliation motivation by posting content that helps readers and readers’ friends understand daily life and mood changes, thus improving the number of “Likes” generated. However, among the motivations that we examined in this study, hedonic and utilitarian types had a stronger impact on readers’ attitudes and their behaviors than did affiliation type.

Compliance motivation. As a result of compliance motivation, the identity of the person posting on Facebook positively affects readers’ willingness to click the “Like” button, thus affecting their behavioral intention and actual behavior. We discovered that posters on Facebook who were able to trigger readers’ compliance motivation could affect readers’ willingness to click the “Like” button. In other words, readers’ attitudes and intention toward clicking the “Like” button, as well as their actual behavior, can be influenced by whether or not they share the Facebook poster’s opinions or whether or not they support their right to have differing opinions. Therefore, it is important for a poster to build his/ her popularity, credibility, and interpersonal relationships in both the physical and networked worlds in order to increase the number of “Likes” his/her posts generate on Facebook.

Conformity motivation. Because of conformity motivation, the number of “Likes” already obtained on Facebook posts can positively affect readers’ attitudes toward taking the action of clicking the “Like” button, thereby affecting their behavioral intention and actual behavior. In this study, we observed that, when the number of “Likes” on Facebook content triggered readers’ conformity motivation, it increased their willingness to click the “Like” button. In other words, when a large number of readers have previously “Liked” posted content, this can affect new readers’ attitudes, intention, and actual behavior. Therefore, attracting more people to click the “Like” button by means of advertising through media or sharing with friends to generate a conformity effect can increase the number of “Likes” received on a Facebook post.

Subjective norms. The subjective norms of readers can positively influence readers’ behavioral intention to click the “Like” button. We found that negative and positive comments from others regarding Facebook readers’ “Like”-clicking behavior might affect their intention and actual “Liking” behavior in the future. In other words, a reader on Facebook might worry that his/her clicking might trigger negative comments from others, thus affecting his/her clicking intention. Therefore, despite the fact that the posted content, the person posting, and the number of “Like” clicks can all trigger readers’ motivations toward clicking the “Like” button, readers may still be influenced by subjective norms and may change their behavioral intention accordingly.

Study Limitations and Directions for Future Research

In this study, we recruited only university students as study participants; thus, the sample did not cover all the diverse groups of Facebook users. Therefore, the conclusions we have drawn in this study might not be adequate to explain all users’ motivations for clicking the “Like” button. Future researchers may focus on groups other than university students (such as workplace groups) or on different age groups, so as to understand whether or not groups with different backgrounds and characteristics are influenced by different motivational factors. Although all of the study constructs were obtained following a literature review and expert discussions, the posted content, the posters, and the number of “Like” clicks generated in this experiment may still have resulted in an experimental bias that might have affected the results regarding the actual performance of the participants in clicking the “Like” button. In related future studies, researchers should utilize different design methods to assess the posted content, the posters, and the generated number of “Like”s to see whether or not different methods result in different influencing effects.

Conclusion and Contributions

A social platform is an important contemporary channel for interpersonal interactions and commercial sales. In this study, we found that if, concerning content posted on Facebook, the identity of the posters and the number of “Likes” triggered hedonic, utilitarian, compliance, conformity, and affiliation motivations in the users, there is a chance that motivation can be used to influence users’ attitudes in favor of clicking the “Like” button. In turn, motivation should be able to be used to influence the users’ intentions and increase the likelihood that they will click the “Like” button. In addition, potential positive and negative evaluations (i.e., subjective norms) from the reference groups in response to a user’s “Like” clicks may also influence the user’s intention to click the “Like” button. These findings provide a valuable basis for constructing an explanatory model for the “Like”-clicking behaviors of Facebook community platform users, as well as making significant practical contributions to enhance the social and commercial benefits for businesses and individuals by increasing the number of “Likes” they receive for the content they post.

Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological Bulletin, 82, 261-277. http://doi.org/b7r3qh

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall.

Alba, J., Lynch, J., Weitz, B., Janiszewski, C., Lutz, R., Sawyer, A., & Wood, S. (1997). Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. Journal of Marketing, 61, 38-53. http://doi.org/bft2ws

Atkinson, M., & Kydd, C. (1997). Individual characteristics associated with world wide web use: An empirical study of playfulness and motivation. ACM SIGMIS Database, 28, 53-62. http://doi.org/brtjt7

Babin, B. J., Darden, W., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 20, 644-656. http://doi.org/cjt

Bagozzi, R. P., & Dholakia, U. M. (2002). Intentional social action in virtual communities. Journal of Interactive Marketing, 16, 2-21. http://doi.org/d2sdtt

Bao, X., & Bouthillier, F. (2007). Information sharing: As a type of information behavior. Paper presented at the 35th Annual Conference of the Canadian Association for Information Science, Information Sharing in a Fragmented World, Crossing Boundaries, Montreal, Canada, May 10-12.

Baty, J. B., II, & Lee, R. M. (1995). InterShop: Enhancing the vendor/customer dialectic in electronic shopping. Journal of Management Information Systems, 11, 9-31.

Browne, M. W., & Mels, G. (1990). RAMONA PC user’s guide. Pretoria, South Africa: Human Sciences Research Council.

Chu, K. M. (2007). A study of members’ helping behaviors in online communities from a consumer decision-making process perspective [In Chinese]. Electronic Commerce Studies, 5, 197-226.

Deci, E. L., Betley, G., Kahle, J., Abrams, L., & Porac, J. (1981). When trying to win: Competition and intrinsic motivation. Personality and Social Psychology Bulletin, 7, 79-83. http://doi.org/c48shp

Dholakia, U. M., & Soltysinski, K. (2001). Coveted or overlooked? The psychology of bidding for comparable listings in digital auctions. Marketing Letters, 12, 223-237. http://doi.org/ft53k5

Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: Social capital and college students’ use of online social network sites. Journal of Computer-Mediated Communication, 12, 1143-1168. http://doi.org/cqv79r

Etzioni, A. (1975). A comparative analysis of complex organization (rev. ed.). New York: Macmillan.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-51. http://doi.org/cwp

Hanson, W. A., & Putler, D. S. (1996). Hits and misses: Herd behavior and online product popularity. Marketing Letters, 7, 297-305. http://doi.org/dx2ms4

He, W., & Wei, K.-K. (2009). What drives continued knowledge sharing? An investigation of knowledge-contribution and -seeking beliefs. Decision Support Systems, 46, 826-838. http://doi.org/d86k7v

Hill, C. A. (1987). Affiliation motivation: People who need people...but in different ways. Journal of Personality and Social Psychology, 52, 1008-1018. http://doi.org/dsszbh

Hoadley, C. M., Xu, H., Lee, J. J., & Rosson, M. B. (2010). Privacy as information access and illusory control: The case of the Facebook news feed privacy outcry. Electronic Commerce Research and Applications, 9, 50-60. http://doi.org/fpsgpm

Hsu, C.-L., & Lin, J. C.-C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45, 65-74. http://doi.org/csjbm3

Hummel, J., & Lechner, U. (2002). Social profiles of virtual communities. Paper presented at the 35th Hawaii International Conference on Systems Sciences, Hawaii, USA, January 7-10.

Joinson, A. N. (2008). Looking at, looking up, or keeping up with people? Motives and uses of Facebook. Paper presented at the CHI Conference on Human Factors in Computing Systems, Florence, Italy, April 5-10.

Kankanhalli, A., Tan, B., & Wei, K.-K. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. MIS Quarterly, 29, 113-143.

Kelman, H. C. (1961). Processes of opinion change. Public Opinion Quarterly, 25, 57-78. http://doi.org/fj7mgz

Koh, J., & Kim, Y.-G. (2004). Knowledge sharing in virtual communities: An e-business perspective. Expert Systems with Applications, 26, 155-166. http://doi.org/fvxffs

Lascu, D.-N., Bearden, W. O., & Rose, R. L. (1995). Norm extremity and interpersonal influences on consumer conformity. Journal of Business Research, 32, 201-212. http://doi.org/cwkr3n

Lewis, J., & West, A. (2009). “Friending”: London-based undergraduates’ experience of Facebook. New Media & Society, 11, 1209-1229. http://doi.org/fr2tjv

McClelland, D. C. (1987). Human motivation. New York: Cambridge University Press.

Mowen, J. C., & Minor, M. (1998). Consumer behavior (5th ed.). New Jersey, NY: Prentice-Hall.

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.

Pempek, T. A., Yermolayeva, Y. A., & Calvert, S. L. (2009). College students’ social networking experiences on Facebook. Journal of Applied Developmental Psychology, 30, 227-238. http://doi.org/ftrz56

Poyry, E., Parvinen, P., & Malmivaara, T. (2013). The power of ‘like’-interpreting usage behaviors in company-hosted Facebook pages. Paper presented at the 46th Hawaii International Conference on System Science, Hawaii, USA, January 7-10.

Sheldon, P. (2008). The relationship between unwillingness-to-communicate and students’ Facebook use. Journal of Media Psychology: Theories, Methods, and Applications, 20, 67-75. http://doi.org/b9926k

Shen, J., Brdiczka, O., & Ruan, Y. (2013). A comparison study of user behavior on Facebook and Gmail. Computers in Human Behavior, 29, 2650-2655. http://doi.org/zmg

Sit, J., & Merrilees, B. (2005). Understanding satisfaction formation of shopping mall entertainment seekers: A conceptual model. Paper presented at the Australian and New Zealand Marketing Academy Conference: Broadening the Boundaries, Fremantle, Australia, December 5-7.

Sledgianowski, D., & Kulviwat, S. (2009). Using social network sites: The effects of playfulness, critical mass and trust in a hedonic context. Journal of Computer Information Systems, 49, 74-83.

Steiger, J. H. (1989). EzPATH: A supplementary module for SYSTAT and SYGRAPH. Evanston, IL: SYSTAT.

Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: An initial examination. Journal of Retailing, 76, 309-322. http://doi.org/b7fgnr

Tan, J., & Yates, S. M. (2007). A Rasch analysis of the Academic Self-Concept Questionnaire. International Education Journal, 8, 470-484.

Wu, J.-J., Chen, Y.-H., & Chung, Y.-S. (2010). Trust factors influencing virtual community members: A study of transaction communities. Journal of Business Research, 63, 1025-1032. http://doi.org/ftph6v

Table 1. Variable Definitions and Items Used in this Study

Table/Figure

Table 2. Factor Loading, Alpha, Composite Reliability, and Average Variance Extracted Values

Table/Figure

Note. CR = composite reliability, AVE = average variance extracted.


Table/Figure

Figure 1. Model diagram and corresponding path coefficients.
Note. * p < 0.1, ** p < .05, *** p < .01


Chih-Yu Chin, Graduate Institute of Management, No. 556, Sec. 2, Zhongshan E. Road, Zhongli City, Taoyuan 32082, Taiwan, ROC. Email: [email protected]

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