本研究以科技接受模式為核心架構，納入系統彈性與資訊完整性作為外部因素，藉以探討影響消費者使用生成式人工智慧如ChatGPT輔助搜尋商品資訊接受程度的因素，以及對後續Webrooming行為意圖的影響。研究方法部分，針對年齡介於18至42歲的族群進行便利抽樣的問卷調查，受測者須在觀看ChatGPT簡介與演示影片後進行問卷填答。正式的問卷調查共計回收480份有效樣本，並使用偏最小平方法的結構方程模型（PLS-SEM）對蒐集到的數據結果進行分析。分析結果指出，當消費者使用ChatGPT輔助搜尋商品資訊時，ChatGPT的系統彈性與資訊完整性，會對其接受程度造成影響，進而影響ChatGPT的使用意圖。同時，這樣的使用意圖，以及對ChatGPT的知覺易用性、知覺有用性，也進一步影響消費者發生Webrooming行為的可能。

This study adopts the technology acceptance model (TAM) as the core framework and incorporates system flexibility and information completeness as external variables. The objective is to explore the factors influencing consumers' acceptance when using generative artificial intelligence, such as ChatGPT, to assist in product information searching and the subsequent impact on their intention to engage in webrooming behavior. In terms of research methodology, a questionnaire survey using convenience sampling was conducted targeting individuals aged between 18 and 42 years old. The participants were required to complete the questionnaire after watching an introduction and demonstration video of ChatGPT. A total of 480 valid samples were collected from the formal survey. The collected data were analyzed by the PLS-SEM method. The analysis results indicate that when consumers use ChatGPT to assist in product information searching, both system flexibility and information completeness have an impact on their acceptance, subsequently influencing their intention to use ChatGPT. Moreover, the intention to use, perceived ease of use, and perceived usefulness of ChatGPT, further impact the likelihood of consumers engaging in webrooming behavior.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
Arora, S., & Sahney, S. (2018). Consumer’s webrooming conduct: an explanation using the theory of planned behavior. Asia Pacific Journal of Marketing and Logistics, 30(4), 1040-1063. https://doi.org/https://doi.org/10.1108/APJML-08-2017-0185
Arora, S., & Sahney, S. (2019). Examining consumers’ webrooming behavior: an integrated approach. Marketing Intelligence & Planning, 37(3), 339-354. https://doi.org/https://doi.org/10.1108/MIP-05-2018-0152
Aw, E. C.-X., Basha, N. K., Ng, S. I., & Ho, J. A. (2021). Searching online and buying offline: Understanding the role of channel-, consumer-, and product-related factors in determining webrooming intention. Journal of Retailing and Consumer Services, 58, 102328. https://doi.org/https://doi.org/10.1016/j.jretconser.2020.102328
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16, 74-94.
Bansal, H. S., & Voyer, P. A. (2000). Word-of-Mouth Processes within a Services Purchase Decision Context. Journal of service research, 3(2), 166-177. https://doi.org/https://doi.org/10.1177/109467050032005
Change, S., Witteloostuijn, A., & Eden, L. (2010). From the editors: Common method variance in international research. Journal of International Business Studies, 41(2), 178-184.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences. Academic press.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16, 297-334. https://doi.org/https://doi.org/10.1007/BF02310555
Dale, R. (2016). The return of the chatbots. Natural Language Engineering, 22(5), 811-817. https://doi.org/https://doi.org/10.1017/S1351324916000243
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results Massachusetts Institute of Technology].
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Management science, 35(8), 982-1003. https://doi.org/https://doi.org/10.1287/mnsc.35.8.982
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of applied social psychology, 22(14), 1111-1132. https://doi.org/https://doi.org/10.1111/j.1559-1816.1992.tb00945.x
Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: three experiments. International journal of human-computer studies, 45(1), 19-45. https://doi.org/https://doi.org/10.1006/ijhc.1996.0040
Fernández, N. V., Pérez, M. J. S., & Vázquez-Casielles, R. (2018). Webroomers versus showroomers: are they the same? Journal of Business Research, 92, 300-320. https://doi.org/https://doi.org/10.1016/j.jbusres.2018.08.004
Flavián, C., Gurrea, R., & Orús, C. (2016). Choice confidence in the webrooming purchase process: The impact of online positive reviews and the motivation to touch. Journal of Consumer Behaviour, 15(5), 459-476. https://doi.org/https://doi.org/10.1002/cb.1585
Flavián, C., Gurrea, R., & Orús, C. (2019). Feeling Confident and Smart with Webrooming: Understanding the Consumer's Path to Satisfaction. Journal of Interactive Marketing, 47(1), 1-15. https://doi.org/https://doi.org/10.1016/j.intmar.2019.02.002
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the association for information systems, 4(1), 7.
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of management information systems, 18(1), 185-214.
Guo, Y., Zhang, M., & Lynette Wang, V. (2022). Webrooming or showrooming? The moderating effect of product attributes. Journal of Research in Interactive Marketing, 16(4), 534-550. https://doi.org/https://doi.org/10.1108/JRIM-08-2020-0161
Gurău, C. (2012). A life‐stage analysis of consumer loyalty profile: comparing Generation X and Millennial consumers. Journal of consumer Marketing, 29(2), 103-113. https://doi.org/https://doi.org/10.1108/07363761211206357
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. Journal of Marketing theory and Practice, 19(2), 139-152. https://doi.org/http://dx.doi.org/10.2753/MTP1069-6679190202
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). European business review, 26(2), 106-121. https://doi.org/https://doi.org/10.1108/EBR-10-2013-0128
Hall, A., Towers, N., & Shaw, D. R. (2017). Understanding how Millennial shoppers decide what to buy: Digitally connected unseen journeys. International Journal of Retail & Distribution Management, 45(5), 498-517. https://doi.org/https://doi.org/10.1108/IJRDM-11-2016-0206
Haridasan, A. C., Fernando, A. G., & Balakrishnan, S. (2021). Investigation of consumers' cross‐channel switching intentions: A push‐pull‐mooring approach. Journal of Consumer Behaviour, 20(5), 1092-1112. https://doi.org/https://doi.org/10.1002/cb.1918
Harman, H. H. (1976). Modern factor analysis. University of Chicago Press.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43, 115-135.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), New Challenges to International Marketing (Vol. 20, pp. 277-319). Emerald Group Publishing Limited. https://doi.org/https://doi.org/10.1108/S1474-7979(2009)0000020014
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic management journal, 20(2), 195-204. https://doi.org/https://doi.org/10.1002/(SICI)1097-0266(199902)20:2%3C195::AID-SMJ13%3E3.0.CO;2-7
Lemon, K. N., & Verhoef, P. C. (2016). Understanding Customer Experience Throughout the Customer Journey. Journal of marketing, 80(6), 69-96. https://doi.org/https://doi.org/10.1509/jm.15.0420
Lester, J., Branting, K., & Mott, B. (2004). Conversational agents. The practical handbook of internet computing, 220-240.
Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230. https://doi.org/https://doi.org/10.1016/S0378-7206(00)00061-6
Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of Information and System Quality: An Empirical Examination Within the Context of Data Warehousing. Journal of management information systems, 21(4), 199-235. https://doi.org/https://doi.org/10.1080/07421222.2005.11045823
Neslin, S. A. (2022). The omnichannel continuum: Integrating online and offline channels along the customer journey. Journal of Retailing, 98(1), 111-132. https://doi.org/https://doi.org/10.1016/j.jretai.2022.02.003
Nunally, J., & Bernstein, I. (1994). Psychology theory. New York: McGrew-Hill.
Rauschnabel, P. A., Rossmann, A., & tom Dieck, M. C. (2017). An adoption framework for mobile augmented reality games: The case of Pokémon Go. Computers in Human Behavior, 76, 276-286. https://doi.org/https://doi.org/10.1016/j.chb.2017.07.030
Rese, A., Ganster, L., & Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance? Journal of Retailing and Consumer Services, 56, 102176. https://doi.org/https://doi.org/10.1016/j.jretconser.2020.102176
Rietz, T., Benke, I., & Maedche, A. (2019). The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance Karlsruhe Institute of Technology, Institute of Information Systems and Marketing,
Karlsruhe, Germany.
Shawar, B. A., & Atwell, E. (2007). Chatbots: Are they Really Useful? Journal for Language Technology and Computational Linguistics, 22(1), 29-49.
Smith, K. T. (2011). Digital marketing strategies that Millennials find appealing, motivating, or just annoying. Journal of Strategic marketing, 19(6), 489-499. https://doi.org/https://doi.org/10.1080/0965254X.2011.581383
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International journal of medical education, 2, 53-55. https://doi.org/https://doi.org/10.5116/ijme.4dfb.8dfd
Teo, T. S., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of management information systems, 25(3), 99-132.
Van der Heijden, H. (2004). User Acceptance of Hedonic Information Systems. MIS quarterly, 28(4), 695-704. https://doi.org/https://doi.org/10.2307/25148660
Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information systems research, 11(4), 342-365. https://doi.org/http://dx.doi.org/10.1287/isre.11.4.342.11872
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management science, 46(2), 186-204. https://doi.org/https://doi.org/10.1287/mnsc.46.2.186.11926
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS quarterly, 36(1), 157-178. https://doi.org/https://www.jstor.org/stable/41410412
Verhoef, P. C., Kannan, P. K., & Inman, J. J. (2015). From Multi-Channel Retailing to Omni-Channel Retailing: Introduction to the Special Issue on Multi-Channel Retailing. Journal of Retailing, 91(2), 174-181. https://doi.org/https://doi.org/10.1016/j.jretai.2015.02.005
Verhoef, P. C., Neslin, S. A., & Vroomen, B. (2007). Multichannel customer management: Understanding the research-shopper phenomenon. International journal of research in marketing, 24(2), 129-148. https://doi.org/https://doi.org/10.1016/j.ijresmar.2006.11.002
Vinzi, V. E., Trinchera, L., & Amato, S. (2010). PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement. Handbook of partial least squares: Concepts, methods and applications, 47-82.
Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the Hedonic and Utilitarian Dimensions of Consumer Attitude. Journal of marketing research, 40(3), 310-320. https://doi.org/https://doi.org/10.1509/jmkr.40.3.310.19238
Williams, L. J., & Hazer, J. T. (1986). Antecedents and consequences of satisfaction and commitment in turnover models: A reanalysis using latent variable structural equation methods. Journal of applied psychology, 71(2), 219-231. https://doi.org/https://psycnet.apa.org/doi/10.1037/0021-9010.71.2.219
Wixom, B. H., & Todd, P. A. (2005). A Theoretical Integration of User Satisfaction and Technology Acceptance. Information systems research, 16(1), 85-102. https://doi.org/https://doi.org/10.1287/isre.1050.0042
賴宜弘, 黃芬芬, & 楊雪華. (2015). 科技接受模式中文版量表之編製與相關研究. 亞東學報(35), 201-221.