博碩士論文 102421035 詳細資訊




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姓名 王若瑜(Jo-yu Wang)  查詢紙本館藏   畢業系所 企業管理學系
論文名稱 探討影響網路團購消費者願意等待成團的因素
(Exploring the Factors of Influence Group-buying Consumers Waiting for the Tour.)
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摘要(中) 根據過去學者對於網路團購的投入,主要是探討消費者對於網路團購的購買意圖與購買行為;或是探討滿意度及再購意圖;亦有聚焦於價格機制與需求,鮮少有文獻是針對網路團購消費者願意等待成團的因素進行探討。由於需要湊滿一定的數量才能夠達到成團,因此必須耗費一段時間等待其他人跟團參與,故探討影響等待成團的因素只考慮個人面因素是不夠的,還需要加入群體因素共同探討。本研究將願意等待成團的因素分為個人面及群體面,建構容易了解網路團購消費者願意等待成團的因素之研究架構,以彌補過去研究之不足。
本研究採用網路問卷的方式進行調查,共回收559份問卷,有效問卷520份,並依據消費者跟團參與的主購所開團之同一團購商品,將樣本分成33團。本研究以階層線性模型 (HLM)進行本研究假設之驗證分析,研究結果如下:
1. 專注沉浸、關鍵多數及同步價值對於知覺等待時間具有反向顯著影響,其中以同步價值的影響程度最大,其次為關鍵多數,表示探討網路團購消費者願意等待成團時,考量群體面因素是相當重要的。
2. 關鍵多數及同步價值對於再次購買行為不具有顯著影響,表示愈多人跟團愈能提高與網路商家的議價能力,並無法表示關鍵多數愈多,促使個人的再次購買行為愈高。另外,網路團購為消費者購物的管道之一,因此對於可以與其他跟團者互動是使用網路團購的附加價值,並不會真正影響其再次購買行為。
3.關鍵多數及同步價值並不會對於個別消費者的再次購買行為產生顯著的直接影響,但是可以透過知覺等待時間的間接效果,而對於再次使用網路團購的購買行為產生顯著的影響。
摘要(英) In the past, most study of online group-buying focus on purchase intention and behavior to online group-buying; the others focus on satisfication and repurchase intention. Also, some studies focus on the price mechanism and demand. Few study aims to argue that what factors influence on waitng for the tour to be confirmed for online group-buying consumers. Consumers must wait for others joining the tour to achieve specific quantities for product. Therefore, only considering the personal factors is not enough, the group factor should be jointly added to. This study divides the factors into personal and group to supplement the lack of past study. The study uses online questionnaire and surveys 559 consumers of online group-buying, in which 520 are valid. According to buying the same products which is appeal by the same initiators, the samples are separated into 33 groups. Hierarchical Linear Modeling (HLM) is applied to test the hypotheses. The findings of this study are as follows.
1. Focused immersion, critical mass and synchronization value have negative effect on perceived waiting time. Among of them, synchronization value has the greatest influence and critical mass secondly. This shows the importance of groups.
2. Critical mass and synchronization value have no effect on repurchase behavior. This shows that the more people join the tour and the more capability to bargain. No evidence demonstrates that critical mass has no effect on repurchase behavior. Besides, providing a platform to interact with others is an additional features or value for who use the online group-buying for shopping.
3. Critical mass and synchronization value have no direct effect on purchase intention, but there is an indirect effect through perceived waiting time on repurchase behavior.
關鍵字(中) ★ 網路團購
★ 知覺等待時間
★ 認知專注
★ 網路外部性
關鍵字(英) ★ Online Group-Buying
★ Perceived Waiting Time
★ Cognitive Absorption Theory
★ Network Externalities
論文目次 中文摘要 i
英文摘要 ii
誌謝 iii
表目錄 v
圖目錄 vi
第一章 緒論 1
1-1 研究背景 1
1-2 研究動機 3
1-3 研究目的 5
1-4 研究流程 6
第二章 文獻探討 7
2-1 網路團購 7
2-2 知覺等待時間 14
2-3 認知專注理論 17
2-4 網路外部性 21
第三章 研究方法 25
3-1 研究架構 25
3-2 研究假設 26
3-3 研究變數之操作型定義與問卷設計 32
3-4 資料來源 37
3-5 資料分析方法與工具 38
第四章 資料分析與研究驗證 40
4-1 敘述性統計 40
4-2 信度分析 45
4-3 效度分析 49
4-4 階層線性模型 51
4-5 研究假說結果彙總 59
第五章 結論與建議 60
5-1 研究討論 60
5-2 管理意涵 66
5-3 研究限制與後續發展 68
參考文獻 69
附錄、問卷 80

參考文獻 中文部分:
[1] Inside,美國團購網站Groupon併購台灣地圖日記,http://www.inside.com.tw/2010/12/01/groupon-has-acquired-atlaspost,2010年
[2] 中華民國電子商務年鑑:2013年我國電子商務發展現況,http://ecommercetaiwan.blogspot.tw/2013/12/2013_4026.html,2013年
[3] 何金銘,「層級線性模型:巢套資料的有效分析方法」,國立中山大學人力資源管理研究所,2008年
[4] 李金泉,易學易用SPSS PASW統計分析實務,二版,全華圖書,2011年
[5] 邱皓政 & 溫福星,「脈絡效果的階層線性模型分析:以學校組織創新氣氛與教師創意表現為例」,國立政治大學 [教育與心理研究],30(1), 1-35,2007年
[6] 陳順宇,多變量分析,四版,華泰書局,2005年
[7] David Court, Dave Elzinga, Susan Mulder and Ole Jrgen Vetvik,「消費者的決策歷程」,麥肯錫季刊,2009年
[8] 溫福星,階層線性模式:原理、方法與應用,台北,雙葉書廊,2006
[9] 資策會MIC,團購將成為網友未來的主要互動模式,http://mic.iii.org.tw/aisp/pressroom/press01_pop.asp?sno=225&type1=2,2010年
[10] 農訊雜誌,第299期,不團,就落伍了,https://www.thekono.com/titles/training_and_development/magazines/54b4a7ff8b297/articles/89a6d84c-0b10-41cf-ac93-1017ef88fc73,2015年1月
[11] 數位觀察,團購給您帶來怎樣的客戶?您該怎麼看團購?,http://www.teamswork.tv,2010年

英文部分:
[1] Agarwal, R., & Karahanna, E. (2000). Time flies when you′re having fun: Cognitive absorption and beliefs about information technology usage. MIS quarterly, Vol. 24, No. 4, pp. 665-694.
[2] Agarwal, R., Sambamurthy, V., & Stair, R. M. (1997, August). COGNITIVE ABSORPTION AND THE ADOPTION OF NEW INFORMATION TECHNOLOGIES. In Academy of Management Proceedings (Vol. 1997, No. 1, pp. 293-297). Academy of Management.
[3] Ajzen, I., & Fishbein, M. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Organizational Behavior and Human Decision Processes, Vol. 50, No. 2, pp. 179-211.
[4] Anand, K. S., & Aron, R. (2003). Group buying on the web: A comparison of price-discovery mechanisms. Management Science, 49(11), 1546-1562.
[5] Anić, I. D., Radas, S., & Miller, J. C. (2011). Antecedents of consumers′ time perceptions in a hypermarket retailer. The Service Industries Journal, 31(5), 809-828.
[6] Baker, J., & Cameron, M. (1996). The effects of the service environment on affect and consumer perception of waiting time: an integrative review and research propositions. Journal of the Academy of Marketing Science, 24(4), 338-349.
[7] Bandura, A. (2000). Exercise of human agency through collective efficacy.Current directions in psychological science, 9(3), 75-78.
[8] Berlyne, D. (1950). Novelty and curiosity as determinants of exploratory behaviour1. British Journal of Psychology. General Section, 41(1‐2), 68-80.
[9] Bhatnagar, A., Misra, S., & Rao, H. R. (2000). On risk, convenience, and Internet shopping behavior. Communications of the ACM, 43(11), 98-105.
[10] Bielen, F., & Demoulin, N. (2007). Waiting time influence on the satisfaction-loyalty relationship in services. Managing Service Quality: An International Journal, 17(2), 174-193.
[11] Block, R. A. 1990. “Models of Psychological Time,” in Cognitive Models of Psychological Time, R. A. Block (ed.), Hillsdale, NJ: Erlbaum, pp. 1-35.
[12] Celik, V., Yesilyurt, E., Korkmaz, O., & Usta, E. (2014). From the Perspective of Loneliness and Cognitive Absorption Internet Addiction as Predictor and Predicted. Eurasia Journal of Mathematics, Science & Technology Education,10(6), 581-594.
[13] Chan, K. W., & Li, S. Y. (2010). Understanding consumer-to-consumer interactions in virtual communities: The salience of reciprocity. Journal of Business Research, 63(9), 1033-1040.
[14] Chandra, S., Srivastava, S. C., & Theng, Y. L. (2012). Cognitive absorption and trust for workplace collaboration in virtual worlds: An information processing decision making perspective. Journal of the assocation for information systems, Vol. 13, Special Issue, pp. 797-835,
[15] Charoensukmongkol, P. (2014). Effects of support and job demands on social media use and work outcomes. Computers in Human Behavior, 36, 340-349.
[16] Chen, J., Chen, X., Kauffman, R. J., & Song, X. (2009). Should we collude? Analyzing the benefits of bidder cooperation in online group-buying auctions. Electronic Commerce Research and Applications, 8(4), 191-202.
[17] Chen, Z., Liang, X., Xie, L., & Yan, H. (2015). On Price Elasticities in the Presence of Network Effects. Available at SSRN 2571872.
[18] Chen, Y. F., & Lu, H. F. (2015). We‐commerce: Exploring factors influencing online group‐buying intention in Taiwan from a conformity perspective. Asian Journal of Social Psychology, 18(1), 62-75.
[19] 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.
[20] 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.
[21] Chien, S. Y., & Lin, Y. T. (2015). The effects of the service environment on perceived waiting time and emotions. Human Factors and Ergonomics in Manufacturing & Service Industries, 25(3), 319-328.
[22] Chinchanachokchai, S., Duff, B. R., & Sar, S. (2015). The effect of multitasking on time perception, enjoyment, and ad evaluation. Computers in Human Behavior, 45, 185-191.
[23] Choi, J. E., Vaswani, P. A., & Shadmehr, R. (2014). Vigor of movements and the cost of time in decision making. The Journal of Neuroscience, 34(4), 1212-1223.
[24] Chou, C. H., Wang, Y. Y., Wang, Y. S., & Tang, T. I. (2014). Exploring the Determinants of Repurchase Behavior in C2B e-Commerce. International Journal of e-Education, e-Business, e-Management and e-Learning, 4(4), 271-282.
[25] Chou, T. J., & Ting, C. C. (2003). The role of flow experience in cyber-game addiction. CyberPsychology & Behavior, 6(6), 663-675.
[26] Cigler, L., Dvořák, W., Henzinger, M., & Starnberger, M. (2014). Limiting Price Discrimination when Selling Products with Positive Network Externalities. InWeb and Internet Economics (pp. 44-57). Springer International Publishing.
[27] Csikszentmihalyi, M. (1990). Flow, the Psychology of Optimal Experience, New York: Harper Collins.
[28] Csikszentmihalyi, M. (2014). Flow (pp. 227-238). Springer Netherlands.
[29] Curtis, T., Abratt, R., Rhoades, D., & Dion, P. (2011). Customer loyalty, repurchase and satisfaction: a meta-analytical review. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 24, 1-26.
[30] Dabholkar, P. A., & Sheng, X. (2008). Perceived download waiting in using web sites: a conceptual framework with mediating and moderating effects. Journal of marketing Theory and Practice, 16(3), 259-270.
[31] Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace1. Journal of applied social psychology, 22(14), 1111-1132.
[32] Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Springer Science & Business Media.
[33] Dennis, A. R., & Taylor, N. J. (2006). Information foraging on the web: The effects of “acceptable” Internet delays on multi-page information search behavior. Decision Support Systems, 42(2), 810-824.
[34] Frels, J. K., Shervani, T., & Srivastava, R. K. (2003). The integrated networks model: Explaining resource allocations in network markets. Journal of Marketing, 67(1), 29-45.
[35] Galletta, D. F., Henry, R., McCoy, S., & Polak, P. (2004). Web site delays: How tolerant are users?. Journal of the Association for Information Systems,5(1), 1.
[36] Gauzente, C., & Roy, Y. (2012). Message content in keyword campaigns, click behavior, and price-consciousness: A study of millennial consumers. Journal of Retailing and Consumer Services, 19(1), 78-87.
[37] Ghani, A.J. and Deshande, P.S. (1994), ‘Task characteristics and the experience of optimal flow in human-computer interaction’, The Journal of Psychology, Vol. 128, No. 4, pp. 381-391.
[38] Ghani, J. A., Supnick, R., & Rooney, P. (1991, January). The Experience of Flow In Computer-Mediated And In Face-To-Face Groups. In ICIS (Vol. 91, pp. 229-237).
[39] Goel, L., Johnson, N. A., Junglas, I., & Ives, B. (2011). From space to place: predicting users′ intentions to return to virtual worlds. MIs Quarterly, 35(3), 749-772.
[40] Goel, L., Johnson, N. A., Junglas, I., & Ives, B. (2013). How cues of what can be done in a virtual world influence learning: an affordance perspective. Information & Management, 50(5), 197-206.
[41] Goel, L., Prokopec, S., & Junglas, I. (2013). Coram Populo—In the presence of people: The effect of others in virtual worlds. Journal of Computer‐Mediated Communication, 18(3), 265-282.
[42] Goldfarb, L. K., & Stevenson, D. (1999). Aggregation: An anti-aggravation pill for new-millennium consumers. The Electricity Journal, 12(6), 78-86.
[43] Gottlieb, B. (2000). Does group-shopping work? The economics of Mercata and Mobshop. Retrieved July 26, 2000, from http://www.slate.com/id/86925
[44] Gupta, A., & Zhdanov, D. (2012). Growth and sustainability of managed security services networks: an economic perspective. Mis Quarterly, 36(4), 1109-1130.
[45] Harris, L. C., & Goode, M. M. (2010). Online services capes, trust, and purchase intentions. Journal of Services Marketing, 24(3), 230-243.
[46] Hoffman, D. L. & Novak, T. P. (1996), "Marketing in Hypermedia Commputer-Mediated Environment: Conceptual Foundations," Journal of Marketing, 60(3), 50-68.
[47] Hoffman, D. L., & Novak, T. P. (2009). Flow online: lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23-34.
[48] Hornik, J. (1984). Subjective vs. objective time measures: A note on the perception of time in consumer behavior. Journal of Consumer Research, 615-618.
[49] Hsiao, C. H., & Yang, C. (2010). Predicting the travel intention to take High Speed Rail among college students. Transportation research part F: traffic psychology and behaviour, 13(4), 277-287.
[50] Hsu, Chin-Lung & Lu, His-Peng. (2004), "Why do people play online games? An extended TAM with social influences & flow experience," Information & Management, 41(7), 853-868.
[51] Hsu, M. H., Chang, C. M., & Chuang, L. W. (2015). Understanding the determinants of online repeat purchase intention and moderating role of habit: The case of online group-buying in Taiwan. International Journal of Information Management, 35(1), 45-56.
[52] Hsu, M. H., Chang, C. M., Chu, K. K., & Lee, Y. J. (2014). Determinants of repurchase intention in online group-buying: The perspectives of DeLone & McLean IS success model and trust. Computers in Human Behavior, 36, 234-245.
[53] Hsu, M. H., Chuang, L. W., & Hsu, C. S. (2014). Understanding online shopping intention: the roles of four types of trust and their antecedents. Internet Research, 24(3), 332-352.
[54] Hu, M., Shi, M., & Wu, J. (2013). Simultaneous vs. sequential group-buying mechanisms. Management Science, 59(12), 2805-2822.
[55] Hu, Z. H., Wei, C., Li, Q., & Xiao, F. (2014). Competition with online and offline demands considering logistics costs based on the Hotelling model. Mathematical Problems in Engineering, 2014.
[56] Hui, M. K., & Tse, D. K. (1996). What to tell consumers in waits of different lengths: An integrative model of service evaluation. The Journal of Marketing, 60(2), 81-90.
[57] Hui, M. K., Alan, C. T., & Zhou, L. (2006). Interaction between two types of information on reactions to delays. Marketing Letters, 17(2), 151-162.
[58] Ilsever, J., Cyr, D., & Parent, M. (2007). Extending models of flow and e-loyalty. Journal of Information Science and Technology, 4(2), 3-22.
[59] Kashdan, T. B., & Steger, M. F. (2007). Curiosity and pathways to well-being and meaning in life: Traits, states, and everyday behaviors. Motivation and Emotion, 31(3), 159-173.
[60] Katz, K. L., Larson, B. M., & Larson, R. C. (1991). Prescription for the waiting in line blues: Entertain, enlighten and engage. Sloan Management Review, 32(2), 44-53.
[61] Katz, M. L., & Shapiro, C. (1985). Network externalities, competition, and compatibility. The American economic review, 75(3), 424-440.
[62] Katz, M. L., & Shapiro, C. (1986). Technology adoption in the presence of network externalities. The journal of political economy, 94(4), 822-841.
[63] 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.
[64] 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.
[65] 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.
[66] Kellaris, J. J., and Mantel, S. P. 1994. “The Influence of Mood and Gender on Customers’ Time Perceptions,” in Advances in Customer Research, Volume 21, C. T. Allen and D. Roedder John (eds.), Provo, UT : Association for Customer Research, pp. 514-518.
[67] Kim, G. S., Park, S. B., & Oh, J. (2008). An examination of factors influencing consumer adoption of short message service (SMS). Psychology & Marketing, 25(8), 769-786.
[68] Kim, H., Suh, K. S., & Lee, U. K. (2013). Effects of collaborative online shopping on shopping experience through social and relational perspectives. Information & Management, 50(4), 169-180.
[69] Kim, J. B. (2015). A Fixed Pricing Group Buying Decision Model: Insights from the Social Perspective. International Journal of E-Business Research (IJEBR),11(2), 40-59.
[70] Ku, E. C. (2012). Beyond price: how does trust encourage online group′s buying intention? Internet Research, 22(5), 569-590.
[71] Kuan, K. K., Zhong, Y., & Chau, P. Y. (2014). Informational and normative social influence in group-buying: Evidence from self-reported and EEG data.Journal of Management Information Systems, 30(4), 151-178.
[72] Kügler, M., Dittes, S., Smolnik, S., & Richter, A. (2015). Connect Me! Antecedents and Impact of Social Connectedness in Enterprise Social Software. Business & Information Systems Engineering, 57(3), 181-196.
[73] Lai, H., & Zhuang, L. T. (2002). Collective bargaining models on e-marketplace. In SSGRR 2002S, International Conference on Advances in Infrastructure for e-Business, e-Education, e-Science, e-Medicine on the Internet, L′Aquila, Italy.
[74] Lallmahomed, M. Z., Rahim, N. Z. A., Ibrahim, R., & Rahman, A. A. (2013). Predicting different conceptualizations of system use: Acceptance in hedonic volitional context (Facebook). Computers in Human Behavior, 29(6), 2776-2787.
[75] Lapointe, L., & Rivard, S. (2007). A triple take on information system implementation. Organization Science, 18(1), 89-107.
[76] Leclerc, F., Schmitt, B. H., & Dube, L. (1995). Waiting time and decision making: Is time like money? Journal of Consumer Research, 22(1), 110-119.
[77] Lee, S. M., & Chen, L. (2010). The impact of flow on online consumer behavior. Journal of Computer Information Systems, 50(4), 1-10.
[78] Lee, Y., Chen, A. N., & Ilie, V. (2012). Can Online Wait Be Managed? The Effect of Filler Interfaces and Presentation Modes on Perceived Waiting Time Online. MIS Quarterly, 36(2), 365-394.
[79] Lengths: An Integrative Model of Service Evaluation,” Journal of Marketing, 60(2), 81-90.
[80] Li, Y. M., Jhang-Li, J. H., Hwang, T. K., & Chen, P. W. (2012). Analysis of pricing strategies for community-based group buying: The impact of competition and waiting cost. Information Systems Frontiers, 14(3), 633-645.
[81] Liang, X., Ma, L., Xie, L., & Yan, H. (2014). The informational aspect of the group-buying mechanism. European Journal of Operational Research, 234(1), 331-340.
[82] Liebowitz, S. J., & Margolis, S. E. (1996). Should technology choice be a concern of antitrust policy. Harv. JL & Tech., 9(2), 283-374.
[83] Lim, N. (2003). Consumers’ perceived risk: sources versus consequences. Electronic Commerce Research and Applications, 2(3), 216-228.
[84] Lin, C. P., Tsai, Y. H., Wang, Y. J., & Chiu, C. K. (2011). Modeling IT relationship quality and its determinants: A potential perspective of network externalities in e-service. Technological Forecasting and Social Change, 78(1), 171-184.
[85] Lin, H. F. (2008). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications,6(4), 433-442.
[86] Lin, K. Y., & Lu, H. P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory.Computers in Human Behavior, 27(3), 1152-1161.
[87] Lin, Y. T., Xia, K. N., & Bei, L. T. (2015). Customer′s perceived value of waiting time for service events. Journal of Consumer Behaviour, 14(1), 28-40.
[88] Lou, H., Luo, W., & Strong, D. (2000). Perceived critical mass effect on groupware acceptance. European Journal of Information Systems, 9(2), 91-103.
[89] M. Csikszentmihalyi (1990). Flow: the Psychology of Optimal Experience. Harper and Row, New York.
[90] Mahnke, R. (2014, January). Designing Flow Experience on the Web: A Grounded Theory of Online Shopping Flow. In System Sciences (HICSS), 2014 47th Hawaii International Conference on (pp. 3015-3024). IEEE.
[91] Maister, D. H. (1984). The psychology of waiting lines. Harvard Business School.
[92] Metcalfe, B. (1995). Metcalfe’s law: A network becomes more valuable as it reaches more users. Infoworld, 17(40), 53-54.
[93] Mishalani, R. G., McCord, M. M., & Wirtz, J. (2006). Passenger wait time perceptions at bus stops: Empirical results and impact on evaluating real-time bus arrival information. Journal of Public Transportation, 9(2), 89.
[94] Mohd Suki, N., Ramayah, T., & Mohd Suki, N. (2008). Internet shopping acceptance: Examining the influence of intrinsic versus extrinsic motivations.Direct Marketing: An International Journal, 2(2), 97-110.
[95] Osuna, E. E. (1985), “The Psychological Cost of Waiting,” Journal of Mathematical Psychology, 29(1), 82-105.
[96] Park, S., Hong, J., Ohk, K., & Yoon, T. (2015). The Moderating Effect of Reference Group on Online Game Loyalty: Focused on Hedonic Information System. International Journal of Multimedia and Ubiquitous Engineering, 10(1), 59-70.
[97] Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS quarterly, 30(1), 115-143.
[98] Pavlou, P. A., Liang, H., & Xue, Y. (2007). Understanding and Mitigating Uncertainty in Online Exchange Relationships: a Principal-Agent Perspective. MIS Quarterly, 31(1), 105-136.
[99] Pelaez, A. (2015). IT-enabled coordination in electronic markets: An experimental investigation of the effects of social communication on group buyers (Doctoral dissertation, CITY UNIVERSITY OF NEW YORK).
[100] Potosky, D. (2002). A field study of computer efficacy beliefs as an outcome of training: the role of computer playfulness, computer knowledge, and performance during training. Computers in Human behavior, 18(3), 241-255.
[101] Prahalad, C. K., & Ramaswamy, V. (2000). Co-opting customer competence. Harvard business review, 78(1), 79-90.
[102] Rajala, A. K., & Hantula, D. A. (2000). Towards a behavioral ecology of consumption: delay‐reduction effects on foraging in a simulated Internet mall. Managerial and Decision Economics, 21(3‐4), 145-158.
[103] Ruebeck, C., Stafford, S., Tynan, N., Alpert, W., Ball, G., & Butkevich, B. (2003). Network externalities and standardization: A classroom demonstration. Southern Economic Journal, 69(4), 1000-1008.
[104] Reychav, I., & Wu, D. (2015). Are your users actively involved? A cognitive absorption perspective in mobile training. Computers in Human Behavior, 44, 335-346.
[105] Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning continuance intention: An extension of the Technology Acceptance Model. International Journal of human-computer studies, 64(8), 683-696.
[106] Rohlfs, J. (1974). A theory of interdependent demand for a communications service. The Bell Journal of Economics and Management Science, 5(1)16-37.
[107] Rose, G. M., Meuter, M. L., & Curran, J. M. (2005). On‐line waiting: The role of download time and other important predictors on attitude toward e‐retailers. Psychology & Marketing, 22(2), 127-151.
[108] Sahay, A. (2012). How to reap higher profits with dynamic pricing. Image.
[109] Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their relationship with burnout and engagement: A multi‐sample study. Journal of organizational Behavior, 25(3), 293-315.
[110] Schmenner, R. W. 1995. Service operations management. Englewood Cliffss, New Jessy: Prentice-Hall.
[111] Scott, J. E., & Walczak, S. (2009). Cognitive engagement with a multimedia ERP training tool: Assessing computer self-efficacy and technology acceptance. Information & Management, 46(4), 221-232.
[112] Seawright, K. K., & Sampson, E. S. (2007). A video method for empirically studying wait-perception bias. Journal of Operations Management, 25(5), 1055-1066.
[113] Shang, R. A., Chen, Y. C., & Shen, L. (2005). Extrinsic versus intrinsic motivations for consumers to shop on-line. Information & Management, 42(3), 401-413.
[114] 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.
[115] Sonntag, A. (2015). Search costs and adaptive consumers: Short time delays do not affect choice quality. Journal of Economic Behavior & Organization, 113, 64-79.
[116] Stavins, R. N. (1999). The costs of carbon sequestration: a revealed-preference approach. American Economic Review, 89(4) 994-1009.
[117] Taylor, S. (1994). Waiting for service: the relationship between delays and evaluations of service. The Journal of Marketing, 58(2) 56-69.
[118] Tellegen, A. 1982. Brief Manual for the Differential Personality Questionnaire, unpublished manuscript, University of Minnesota.
[119] Teo, T. S., & Yu, Y. (2005). Online buying behavior: A transaction cost economics perspective. Omega, 33(5), 451-465.
[120] Trevino, L. K., & Webster, J. (1992). Flow in computer-mediated communication electronic mail and voice mail evaluation and impacts.Communication research, 19(5), 539-573.
[121] Tseng, F. C., & Teng, C. I. (2015). Online Gamers′ Preferences for Online Game Charging Mechanisms: The Effect of Exploration Motivation.International Journal of E-Business Research (IJEBR), 11(1), 23-34.
[122] Tsvetovat, M., Sycara, K., Chen, Y., & Ying, J. (2001). Customer coalitions in electronic markets. In Agent-Mediated Electronic Commerce III (pp. 121-138). Springer Berlin Heidelberg.
[123] Vallerand, R. J. (1997). Toward a hierarchical model of intrinsic and extrinsic motivation.
[124] Vaghefi, M. S., Vaghefi, M. S., & Beheshti, N. (2014). A pricing model for group-buying auction based on customers′ waiting-time. Marketing Letters, 25(4), 425-434.
[125] Van Slyke, C., Ilie, V., Lou, H., & Stafford, T. (2007). Perceived critical mass and the adoption of a communication technology. European Journal of Information Systems, 16(3), 270-283.
[126] Voorhees, C. M., Baker, J., Bourdeau, B. L., Brocato, E. D., & Cronin, J. J. (2009). It Depends Moderating the Relationships Among Perceived Waiting Time, Anger, and Regret. Journal of Service Research, 12(2), 138-155.
[127] Wang, C. C., Hsu, Y., & Fang, W. (2005). Acceptance of technology with network externalities: An empirical study of Internet instant messaging services. Journal of Information Technology Theory and Application (JITTA), 6(4), 4.
[128] Wattal, S., Racherla, P., & Mandviwalla, M. (2010). Network externalities and technology use: a quantitative analysis of intraorganizational blogs. Journal of Management Information Systems, 27(1), 145-174.
[129] Webster, J., & Hackley, P. (1997). Teaching effectiveness in technology-mediated distance learning. Academy of management journal, 40(6), 1282-1309.
[130] Webster, J., & Ho, H. (1997). Audience engagement in multimedia presentations. ACM SIGMIS Database, 28(2), 63-77.
[131] Webster, J., Trevino, L. K., & Ryan, L. (1994). The dimensionality and correlates of flow in human-computer interactions. Computers in human behavior, 9(4), 411-426.
[132] Whiting, A., & Donthu, N. (2009). Closing the gap between perceived and actual waiting times in a call center: results from a field study. Journal of Services Marketing, 23(5), 279-288.
[133] Wu, X., Levinson, D. M., & Liu, H. X. (2009). Perception of waiting time at signalized intersections. Transportation Research Record, 2135, 52-59.
[134] Yamamoto, J., & Sycara, K. (2001, May). A stable and efficient buyer coalition formation scheme for e-marketplaces. In Proceedings of the fifth international conference on Autonomous agents (pp. 576-583). ACM.
[135] Yang, J., & Mai, E. S. (2010). Experiential goods with network externalities effects: An empirical study of online rating system. Journal of Business Research, 63(9), 1050-1057.
[136] Yang, S., Lu, Y., Wang, B., & Zhao, L. (2014). The benefits and dangers of flow experience in high school students’ internet usage: The role of parental support. Computers in Human Behavior, 41, 504-513.
[137] Yen, C., & Chang, C. M. (2015). UNITY IS STRENGTH: UNDERSTANDING USERS’GROUP BUYING BEHAVIOR IN TAIWAN FROM A COLLECTIVISM PERSPECTIVE. Journal of Electronic Commerce Research, 16(2).
[138] 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.
[139] Zakay, D. 1989. “Subjective Time and Attentional Resource Allocation: An Inte grated Model of Time Estimation,” in Time and Human Cognition: A Life Span Perspective, I. Levin and D. Zakay (eds.), Amsterdam: Elsevier Science, pp. 365-397.
[140] Zakay, D., Tsal, Y., Moses, M., & Shahar, I. (1994). The role of segmentation in prospective and retrospective time estimation processes. Memory & Cognition, 22(3), 344-351.
[141] Zhao, L., & Lu, Y. (2012). Enhancing perceived interactivity through network externalities: An empirical study on micro-blogging service satisfaction and continuance intention. Decision Support Systems, 53(4), 825-834.
[142] Zhou, R., & Soman, D. (2003). Looking back: Exploring the psychology of queuing and the effect of the number of people behind. Journal of Consumer Research, 29(4), 517-530.
[143] Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of network externalities and flow experience. Computers in Human Behavior, 27(2), 883-889.
[144] Zhou, Y., & Xie, J. (2014). Potentially self-defeating: Group buying in a two-tier supply chain. Omega, 49, 42-52.
指導教授 洪秀婉、陳春希(Shiu-wan Hung Chun-shi Chen) 審核日期 2015-6-30
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