在網路普及化，逐漸融入群眾生活之後，各種新興的消費方式因應而生，透過虛擬通路所進行的交易，較傳統消費方式來的方便，也免除了許多成本，因此能夠取得相對的低價，受到消費者喜愛。「線上合購」亦為一種受到消費者歡迎的消費模式，本研究從消費者方面著手，探討線上合購行為，過去研究認為使用人格特質進行研究，最能聚焦於影響消費者之因素，因此本研究使用問卷調查法，透過五大人格特質模型，進一步分析消費者不同的人格特質，是否在線上合購過程中，對其所感知到的互惠、名聲及信任之三項社會交換因子造成影響，也探討社會交換因子對於合購滿意度，以及合購滿意度對再參與意願的影響。
本研究資料蒐集以參與過「PTT合購板」或「愛合購」網站之線上合購的消費者為研究主體，發放線上問卷於PTT合購板、愛合購網站，問卷共回收471份，而經過整理後有效問卷為395份。在資料分析方面使用IBM SPSS Statistics 20統計軟體來分析有效樣本之人口統計變項分佈等敘述性統計以及T檢定，並使用SPSS Macro分析中介效果，再加上SmartPLS 2.0來驗證假說及研究架構。分析結果發現，(1)不同的人格特質確實對於消費者所感知到的互惠、名聲及信任造成不同影響；(2)消費者感知到的「互惠」及「信任」對於合購滿意度有正向顯著影響；(3)消費者感知到的「名聲」對於合購滿意度無正向顯著影響；(4)消費者感知到的合購滿意度對再參與意願有正向顯著影響；(5)人格特質會透過SET構面的中介效果影響到合購滿意度。
研究結果顯示，以社會交換觀點來看，不同人格特質的消費者在線上合購的交換關係中，需求也不盡相同，對活動、資訊或是人際關係的需求都必須要重視，建議如PTT合購板及愛合購網站等，由消費者發起合購的平台，應強化互惠、評價機制，鼓勵成員資訊分享，刺激社會交換關係，以吸引消費者持續參與線上合購，透過社會交換因子的中介效果及成功的合購經驗，影響合購滿意度，進一步提高再參與意願。

SUMMARY
As the Internet promptly develops, online group-buying (OGB) is growing rapidly in Taiwan. The purpose of this research is to examine the relationship among the “Big Five” personality traits, social exchange theory (SET) beliefs (reciprocity, reputation, and trust), satisfaction, and re-participation intention of consumers in OGB. Data from 395 valid samples is obtained via an online survey. The research model is assessed with partial least squares (PLS) analysis. SPSS macros for estimating indirect effects are used to test the mediation effects of SET beliefs. It is proved that for OGB consumers, personality traits do influence reciprocity, reputation, and trust; OGB satisfaction is determined by reciprocity and trust; OGB satisfaction positively affects re-participation intention, and the indirect effect of SET beliefs on personality traits through OGB satisfaction is significant. The results also suggest that OGB platforms should strengthen their reciprocity and evaluation mechanism, encourage information sharing, and activate exchange relationships, to attract consumers to join OGB and keep them participating in OGB.

INTRODUCTION
The recent rapid growth of the Internet, and the e-commerce boom have changed consumer behaviors. According to Taiwan Network Information Center (TWNIC), the total estimated population of Internet users in Taiwan is 17.53 million. Among the interviewees who have Internet experience, 59.62% have online shopping experience (TWNIC, 2012). The Internet has significantly influenced lots aspects in the daily life. More and more businesses have shifted form physical stores to the virtual market. Group-buying represents one of the major factors.
Online group-buying (OGB) has become popular because merchandise can be purchased at significantly lower prices when enough buyers participate. Also, it is comparatively easy to participate in an OGB at home through the Internet. There are mainly three types of group-buying transactions: (1) Customer-Initiated Transaction; (2) Merchants-Initiated Transaction; and (3)Independent Third-Party-Initiated Transaction. This study focuses on the customer-initiated transaction on PTT (Telnet://ptt.cc) and ihergo (Http://www.ihergo.com/), two of the most popular customer-initiated transaction OGB websites in Taiwan.
Despite various studies about group-buying, the emphasis is often on sellers or firms. For example, scholars develop analytical models of web-based group-buying mechanisms under different kinds of demand uncertainty (Anand & Aron, 2003), or try to provide new negotiation mechanisms to achieve the best price for both sellers and buyers (Yuan & Lin, 2004). Even in the studies targeting to focus on consumers, they are still considered a group or a community (Cheng et al., 2012; Wang et al., 2013). To focus on the participants in OGB, this study investigates OGB behavior from individual’s perspective.
Past studies indicate that personality is useful for predicting consumer intentions to purchase products and services online. Many researches have adopted personality traits in their research model, for example, Pentina et al. (2013) use the Big-Five Factor Model to investigate the influence on trust, and Chang et al. (2013) adopt personality traits to study members’ participation phenomenon in online brand communities. In order to know more about consumers’ OGB behavior, this research applies the Big-Five Factor model developed by Costa and McCrae (1992) to investigate the impact caused by personality traits.
Originating in the 1950s and based on psychology, SET embraces the fundamental concept of modern economics as a foundation for analyzing human behavior and relationships to determine social structure complexity. Considering OGB characteristics of customer-initiated transactions, social exchange behaviors occur within every transaction. Per Shiau and Luo (2012), SET beliefs contain three constructs, reciprocity, reputation, and trust. Based on SET, this study proposes that beliefs influence consumer satisfaction; and consumer satisfaction influences repurchase intention.
To sum up, this research addresses the questions of (1) whether personality traits influence SET beliefs; (2) whether SET beliefs are antecedents of OGB satisfaction; (3) whether OGB satisfaction is a significant factor affecting re-participation intention, and (4) whether SET beliefs have indirect effects on personality traits through OGB satisfaction.
The results demonstrate that for OGB consumers, personality traits do influence reciprocity, reputation, and trust; OGB satisfaction is determined by reciprocity and trust; OGB satisfaction positively affects re-participation intention, and the indirect effect of SET beliefs on personality traits through OGB satisfaction is significant.

MATERIALS AND METHODS
Questionnaire is the methodology in this study. The designed questionnaire combines and modifies former related researches. All items use a five-point likert type scale. Data is obtained through an online survey. A hyperlink to the survey is posted on PTT and ihergo to reach to a larger number of consumers. The result contains a total of 395 valid responses. In the analysis stage, IBM SPSS Statistics 20 and SmartPLS 2.0 (Ringle et al., 2005) are the main tools. Descriptive statistics, t-test, ANOVA, and mediation effects are analyzed by SPSS. SmartPLS is adopted for structural equation model analysis. In addition, the bootstrap resampling method (5000 resamples) is applied when necessary.

RESULTS AND DISCUSSION
A total of 395 respondents are surveyed online, among whom, 34 are men (8.6%) and the other 361 are women (91.4%).. 42.3% of the respondents are students; 62.3% are aged below twenty-five, and 97.0% have post-secondary education.
All of the item results exceed the minimum threshold of reliability and validity, indicating that this study achieves good level of reliability and validity. It also demonstrates that for OGB consumers, personality traits truly influence reciprocity, reputation, and trust; OGB satisfaction is determined by reciprocity and trust; OGB satisfaction positively affects re-participation intention, and the indirect effect of SET beliefs on personality traits through OGB satisfaction is significant.

CONCLUSION
This study investigates factors, including Big Five personality traits and SET beliefs, which affect consumers’ online group-buying behavior and their future intention to engage in OGB. The results prove that personality traits truly influence their perception and behavior. Only Neuroticism shows no significant positive effects. This may be because Neuroticism people tend to be suspicious, so they can hardly trust others (Alsajjan, 2010). In SET beliefs, perceived reciprocity and trust positively affect OGB satisfaction. The only exception is reputation. This is probably because the survey platform, PTT, lacks evaluation mechanism and makes reputation no influences (Shiau & Luo, 2012). Consequently, OGB satisfaction will positively affects re-participation intention (Chang et al., 2014). Besides, the indirect effect of SET beliefs on personality traits through OGB satisfaction is significant.
The results suggest that OGB platforms should strengthen their reciprocity and evaluation mechanism, encourage information sharing, and activate exchange relationships, so as to attract consumers join OGB and keep them participating in OGB in the future.

中文文獻
邱皓政. (2010)。量化研究與統計分析(五版)。台北：五南圖書出版股份有限公司。

財團法人台灣網路資訊中心. (2012), from http://www.twnic.net.tw/

蕭文龍. (2013)。統計分析入門與應用：SPSS中文版+PLS-SEM(SmartPLS)。台北：碁峰資訊股份有限公司。

英文文獻
Allport, G. W. (1937). Personality: a psychological interpretation. Oxford, England: Holt.

Allport, G. W., & Odbert, H. S. (1936). Trait-Names A Psycho-lexical Study. Psychological Monographs, 47(1), 1-171.

Alsajjan, B. A. (2010). How The Big Five Personality Dimensions Influence Customers Trust In UK Cellular
Providers? International Journal of Global Business, 3(1), 15.

Anand, K. S., & Aron, R. (2003). Group buying on the web: A comparison of price-discovery mechanisms. Management Science, 49(11), 1546-1562.

Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer Satisfaction, Market Share, and Profitability - Findings From Sweden. Journal of Marketing, 58(3), 53-66.

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(6), 1173.

Blau, P. M. (1964). Exchange and power in sociallife. N.Y.: Wiley.

Bontis, N., Booker, L. D., & Serenko, A. (2007). The mediating effect of organizational reputation on customer loyalty and service recommendation in the banking industry. Management Decision, 45(9), 1426-1445.

Borgatta, E. F. (1964). The structure of personality characteristics. Behavioral Science, 9(1), 8-17.

Bosnjak, M., Galesic, M., & Tuten, T. (2007). Personality determinants of online shopping: Explaining online purchase intentions using a hierarchical approach. Journal of Business Research, 60(6), 597-605.

Cardozo, R. N. (1965). An Experimental Study of Customer Effort, Expectation, and Satisfaction. Journal of Marketing Research, 2(3), 244-249.

Cattell, R. B. (1943). The description of personality: basic traits resolved into clusters. The Journal of Abnormal and Social Psychology, 38(4), 476-506.

Chang, A., Hsieh, S. H., & Lin, F. (2013). Personality Traits That Lead Members of Online Brand Communities to Participate in Information Sending and Receiving. International Journal of Electronic Commerce, 17(3), 37-62.

Chang, S.-C., Chou, P.-Y., & Lo, W.-C. (2014). Evaluation of satisfaction and repurchase intention in online food group-buying, using Taiwan as an example. British Food Journal, 116(1), 44-61.

Chen, C.-J., & Hung, S.-W. (2010). To give or to receive? Factors influencing members’ knowledge sharing and community promotion in professional virtual communities. Information & Management, 47(4), 226-236.

Cheng, H.-H., & Huang, S.-W. (2013). Exploring antecedents and consequence of online group-buying intention: An extended perspective on theory of planned behavior. International Journal of Information Management, 33(1), 185-198.

Cheng, S.-Y., Tsai, M.-T., Cheng, N.-C., & Chen, K.-S. (2012). Predicting intention to purchase on group buying website in Taiwan: Virtual community, critical mass and risk. Online Information Review, 36(5), 698-712.

Chin, W. W. (1998). Commentary: Issues and opinion on structural equation modeling. MIS quarterly, vii-xvi.

Churchill Jr, G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of Marketing research, 491-504.

Costa, P. T., & McCrae, R. R. (1985). The NEO personality inventory. Odessa (Fla.): PAR Psychological Assessment Resources.

Costa, P. T., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO PI-R) and NEO Five-Factor Inventory (NEO FFI): Professional Manual. Odessa, FL: Psychological Assessment Resources.

Cyr, D., Head, M., & Ivanov, A. (2009). Perceived interactivity leading to e-loyalty: Development of a model for cognitive–affective user responses. International Journal of Human-Computer Studies, 67(10), 850-869.

Day, D. V., & Silverman, S. B. (1989). Personality and job performance: Evidence of incremental validity. Personnel Psychology, 42(1), 25-36.

Digman, J. M. (1990). Personality Structure: Emergence of the Five-Factor Model. Annual Review of Psychology, 41, 417-440.

Dwyer, C., Hiltz, S. R., & Passerini, K. (2007). Trust and Privacy Concern Within Social Networking Sites: A Comparison of Facebook and MySpace. Paper presented at the AMCIS.

Fang, Y.-H., Chiu, C.-M., & Wang, E. T. G. (2011). Understanding customers' satisfaction and repurchase intentions: An integration of IS success model, trust, and justice. Internet Research, 21(4), 479-503.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior : an introduction to theory and research. Reading, Mass.: Addison-Wesley Pub. Co.

Gupta, S., & Kim, H.-W. (2010). Value-driven Internet shopping: The mental accounting theory perspective. Psychology and Marketing, 27(1), 13-35.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (Vol. 7): Upper Saddle River, NJ: Prentice Hall.

Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152.

Harman, H. H. (1976). Modern factor analysis. Chicago: University of Chicago Press.

Hayes, A. F. (2008). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach.

Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust online. Communications of the ACM, 42(4), 80-85.

Homans, G. C. (1958). Social behavior as exchange. American Journal of Sociology, 63(6), 597-606.

Hong, S. J., Thong, J. Y. L., & Tam, K. Y. (2006). Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decision Support Systems, 42(3), 1819-1834.

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(1), 65-74.

Hung, S.-W., Cheng, M.-J., & Chen, P.-C. (2012). Reexamining the Factors for Trust in Cultivating Online Customer Repurchase Intentions: The Moderating Effect of Perceived Waiting. International Journal of Human-Computer Interaction, 28(10), 666-677.

John, O., & Srivastava, S. (1999). The Big Five trait taxonomy: History, measurement, and theoretical perspectives. In L. Pervin & O. John (Eds.), Handbook of Personality: Theory and Research (pp. 102-138): Guilford Press.

Kankanhalli, A., Tan, B. C. Y., & Wei, K.-K. (2005). Contributing Knowledge to Electronic Knowledge Repositories: An Empirical Investigation. MIS Quarterly, 29(1), 113-143.

Kauffman, R. J., Lai, H., & Ho, C.-T. (2010). Incentive mechanisms, fairness and participation in online group-buying auctions. Electronic Commerce Research and Applications, 9(3), 249-262.

Kauffman, R. J., Lai, H., & Lin, H.-C. (2010). Consumer adoption of group-buying auctions: an experimental study. Information Technology and Management, 11(4), 191-211.

Kauffman, R. J., & Wang, B. (2001). New buyers' arrival under dynamic pricing market microstructure: The case of group-buying discounts on the Internet. Journal of Management Information Systems, 18(2), 157-188.

Kermani, Z. Z. (2011). The relationship between the ``Big Five`` personality traits
and customer satisfaction: A case study of Melli Bank. Journal of Business and Retail Management Research, 6(1), 82-89.

Kim, C., Galliers, R. D., Shin, N., Ryoo, J.-H., & Kim, J. (2012). Factors influencing Internet shopping value and customer repurchase intention. Electronic Commerce Research and Applications, 11(4), 374-387.

Klages, L. J. W. H. (1929). The science of character. London: G. Allen & Unwin.

Ku, E. C. (2012). Beyond price: how does trust encourage online group's buying intention? Internet Research, 22(5), 569-590.

LaTour, S. A., & Peat, N. C. (1979). Conceptual and methodological issues in consumer satisfaction research. Advances in consumer research, 6(1), 431-437.

Lee, H. S. (2010). Factors influencing customer loyalty of mobile phone service: empirical evidence from Koreans. Journal of Internet Banking and Commerce, 15(2), 1-14.

McCrae, R. R. (1990). Traits and trait names - How well is openness represented in natural languages. European Journal of Personality, 4(2), 119-129.

Moberg, P. J. (2001). Linking conflict strategy to the five-factor model: Theoretical and empirical foundations. International Journal of Conflict Management, 12(1), 47-68.

Mooradian, T. A. (1996). The five factor model and market mavenism. Advances in consumer research, 23, 260-263.

Mooradian, T. A., & Olver, J. M. (1997). “I can't get no satisfaction:” The impact of personality and emotion on postpurchase processes. Psychology and Marketing, 14(4), 379-393.

Morgan, R. M., & Hunt, S. D. (1994). The Commitment-Trust Theory of Relationship Marketing. Journal of Marketing, 58(3), 20-38.

Neuman, W. L. (2006). Social research methods : qualitative and quantitative approaches. Boston, Mass.: Pearson.

Ngo, H.-y., Loi, R., Foley, S., Zheng, X., & Zhang, L. (2013). Perceptions of organizational context and job attitudes: The mediating effect of organizational identification. Asia pacific journal of management, 30(1), 149-168.

Norman, W. T. (1963). Toward an adequate taxonomy of personality attributes: Replicated factor structure in peer nomination personality ratings. The Journal of Abnormal and Social Psychology, 66(6), 574-583.

Oliver, R. L. (1980). A Cognitive Model of The Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4), 460-469.

Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: an extension of the theory of planned behavior. MIS quarterly, 115-143.

Pentina, I., Zhang, L., & Basmanova, O. (2013). Antecedents and consequences of trust in a social media brand: A cross-cultural study of Twitter. Computers in Human Behavior, 29(4), 1546-1555.

Pervan, S. J., Bove, L. L., & Johnson, L. W. (2009). Reciprocity as a key stabilizing norm of interpersonal marketing relationships: Scale development and validation. Industrial Marketing Management, 38(1), 60-70.

Ringle, C. M., Wende, S., & Will, A. (2005). SmartPLS 2.0 (beta). Hamburg, Germany: University of Hamburg.

Rosipal, R., & Krämer, N. (2006). Overview and recent advances in partial least squares Subspace, Latent Structure and Feature Selection (pp. 34-51): Springer.

Scott, W. G. (1972). Organization theory; a structural and behavioral analysis. Homewood, Ill: R. D. Irwin.

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.

Shin, J. I., Chung, K. H., Oh, J. S., & Lee, C. W. (2013). The effect of site quality on repurchase intention in Internet shopping through mediating variables: The case of university students in South Korea. International Journal of Information Management, 33(3), 453-463.

Standifird, S. S. (2001). Reputation and e-commerce: eBay auctions and the asymmetrical impact of positive and negative ratings. Journal of Management, 27(3), 279-295.

Sun, P.-C., Liu, Y.-L., & Luo, J.-J. (2010). Perceived Risk and Trust in Online Group Buying Context. 660-663.

Tanaka, J. S. (1987). "How Big Is Big Enough?": Sample Size and Goodness of Fit in Structural Equation Models with Latent Variables. Child Development, 58(1), 134-146.

Tayie, S. (2005). Research methods and writing research proposals: Pathways to Higher Education.

Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational statistics & data analysis, 48(1), 159-205.

Tsai, M.-T., Cheng, N.-C., & Chen, K.-S. (2011). Understanding online group buying intention: the roles of sense of virtual community and technology acceptance factors. Total Quality Management & Business Excellence, 22(10), 1091-1104.

Wang, H., Meng, Y., & Wang, W. (2013). The role of perceived interactivity in virtual communities: building trust and increasing stickiness. Connection Science, 25(1), 55-73.

Wang, J. J., Zhao, X., & Li, J. J. (2013). Group Buying: A Strategic Form of Consumer Collective. Journal of Retailing, 89(3), 338-351.

Wang, W., Ngai, E. W. T., & Wei, H. (2012). Explaining Instant Messaging Continuance Intention: The Role of Personality. International Journal of Human-Computer Interaction, 28(8), 500-510.

Webber, S. S., Payne, S. C., & Taylor, A. B. (2011). Personality and Trust Fosters Service Quality. Journal of Business and Psychology, 27(2), 193-203.

Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. Mis Quarterly, 33(1).

Yeh, Y. S., & Li, Y.-M. (2009). Building trust in m-commerce: contributions from quality and satisfaction. Online Information Review, 33(6), 1066-1086.

Yuan, S.-T., & Lin, Y.-H. (2004). Credit based group negotiation for aggregate sell/buy in e-markets. Electronic Commerce Research and Applications, 3(1), 74-94.

Zhang, Y., Fang, Y., Wei, K.-K., Ramsey, E., McCole, P., & Chen, H. (2011). Repurchase intention in B2C e-commerce—A relationship quality perspective. Information & Management, 48(6), 192-200.