政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/143723

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/143723

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | 全文笔数/总笔数 : 113318/144297 (79%)
造访人次 : 50995387 在线人数 : 766

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

搜寻范围

查询小技巧：

您可在西文检索词汇前后加上"双引号"，以获取较精准的检索结果

若欲以作者姓名搜寻，建议至进阶搜寻限定作者字段，可获得较完整数据

进阶搜寻

主页 ‧ 登入 ‧ 上传 ‧ 说明 ‧ 关于政大典藏 ‧ 管理

到手机版

政大機構典藏 > 傳播學院 > 數位內容碩士學位學程 > 學位論文 > Item 140.119/143723

请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/143723

题名:	性別一致性對聊天機器人滿意度之影響 The Effect of Gender Congruence on Chatbot Satisfaction
作者:	張鈞宏 Chang, Chun-Hung
贡献者:	林芝璇廖峻鋒 Lin, Jhih-Syuan Liao, Chun-Feng 張鈞宏 Chang, Chun-Hung
关键词:	聊天機器人性別刻板印象一致性心理性別社會臨場感 Chatbot Gender Stereotypes Consistency Psychological Gender Social Presence
日期:	2023
上传时间:	2023-03-09 18:13:38 (UTC+8)
摘要:	科技的進步往往會改變人們的互動方式，隨著近年疫情和人工智慧的發展，聊天機器人的應用遍地開花，越來越多的企業將聊天機器人導入服務當中。聊天機器人通常會被賦予擬人化的特徵，性別是其中一個常被討論的變項。雖然過去的研究已對性別和聊天機器人滿意度之間的關係進行探索，但仍不夠全面，故本研究提出一調節中介模型，以聊天機器人的性別和性別刻板印象領域的一致性切入，同時探討使用者的心理性別對滿意度可能產生的調節影響，以及社會臨場感的中介效果。本研究的實驗為2（聊天機器人性別）x 2（性別刻板印象領域）x 2（使用者心理性別）的受測者間設計，透過操弄Line聊天機器人的設計，讓使用者在與聊天機器人實際互動後，回覆研究問卷。本研究以365份樣本進行分析，研究結果發現，聊天機器人的性別和性別刻板印象領域一致與否，並不會對滿意度造成顯著影響，另外，心理性別無法有效調節性別一致性對滿意度或社會臨場感的效果。但研究發現，社會臨場感雖然沒有顯著的中介效果，但卻能顯著地提高使用者滿意度，另外也發現，生理女性的使用者，滿意度顯著高於生理男性的使用者。本研究針對結果的學術與實務性意涵進行討論，並提出研究限制和未來研究可發展之方向。 The advancement of technology often changes the way people interact. As chatbots have become increasingly popular with the development of AI and recent pandemics, more and more companies have integrated chatbots into their services. Chatbots are often designed with human-like characteristics, such as gender, which is a commonly discussed variable in prior research. Although previous studies have explored the relationship between gender and chatbot satisfaction, more research is warranted in this area. Therefore, this study proposes a moderated mediation model that examines how the congruence between chatbot gender and gender stereotype domains may influence chatbot satisfaction, as well as the moderating role of users` psychological gender and the mediating role of social presence in the process. This study employed a 2 (chatbot gender) x 2 (gender stereotype domains) x 2 (user psychological gender) between-subject design. Participants interacted with a Line chatbot and then responded to the study questionnaire. A total of 365 responses were analyzed after data cleaning. The findings show that the congruence between chatbot gender and gender stereotype domains does not have a significant effect on satisfaction. Psychological gender does not moderate the effect of gender congruency on satisfaction and social presence. Although social presence does not have a significant mediating effect between gender congruency and satisfaction, it significantly improves user satisfaction. Additionally, the findings reveal that female users tend to have a higher level of satisfaction than male users. The theoretical and managerial implications of the findings, as well as limitations and directions for future research, are discussed.
參考文獻:	李大有 (2022) 。嘉義地區大學生的性別刻板印象與性別平等意識之關係研究。﹝碩士論文。國立嘉義大學﹞。臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/g3kf99。林慧閔 (2017) 。職業性別刻板印象一致/不一致與正向/負向訊息對知覺職業適合度之影響。﹝碩士論文。國立中山大學﹞。臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/sg5287。施事誠 (2015) 。高職餐飲科學生性別刻板印象、自我概念與成就動機之研究。﹝碩士論文。國立高雄餐旅大學﹞。臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/gr8su9。梁力友 (2020) 。個人性別態度檢測量表之建構效度研究。﹝碩士論文。國立暨南國際大學﹞。臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/c4m56w。蔡宛樺 (2015) 。高雄市國中學生在性別刻板印象與性別平等行為表現之相關研究。﹝碩士論文。國立臺灣師範大學﹞。臺灣博碩士論文知識加值系統。 https://hdl.handle.net/11296/wt75v3。 Abercrombie, G., Curry, A. C., Pandya, M., & Rieser, V. (2021). Alexa, Google, Siri: What are your pronouns? Gender and anthropomorphism in the design and perception of conversational assistants. arXiv preprint arXiv:2106.02578. Adam, M., Wessel, M., & Benlian, A. (2020). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427-445. https://doi.org/10.1007/s12525-020-00414-7 Ahn, J., Kim, J., & Sung, Y. (2022). The effect of gender stereotypes on artificial intelligence recommendations. Journal of Business Research, 141, 50-59. https://doi.org/10.1016/j.jbusres.2021.12.007 An, D., & Kim, S. (2007). Relating Hofstede`s masculinity dimension to gender role portrayals in advertising. International Marketing Review, 24(2), 181-207. https://doi.org/10.1108/02651330710741811 Baxter, D. N., McDonnell, M., & McLoughlin, R. J. (2018). Impact of Chatbot Gender on User’s Stereotypical Perception and Satisfaction Baylor, A. L., & Kim, Y. (2004). Pedagogical Agent Design: The Impact of Agent Realism, Gender, Ethnicity, and Instructional Role. In Intelligent Tutoring Systems (pp. 592-603). https://doi.org/10.1007/978-3-540-30139-4_56 Beldad, A., Hegner, S., & Hoppen, J. (2016). The effect of virtual sales agent (VSA) gender – product gender congruence on product advice credibility, trust in VSA and online vendor, and purchase intention. Computers in Human Behavior, 60, 62-72. https://doi.org/10.1016/j.chb.2016.02.046 Bem, S. L. (1974). The measurement of psychological androgyny. Journal of consulting and clinical psychology, 42(2), 155. Bergen, H. (2016). ‘I’d Blush if I Could’: Digital Assistants, Disembodied Cyborgs and the Problem of Gender. A Journal of Literary Studies and Linguistics. Best, D. L., Williams, J. E., Cloud, J. M., Davis, S. W., Robertson, L. S., Edwards, J. R., Giles, H., & Fowles, J. (1977). Development of Sex-Trait Stereotypes among Young Children in the United States, England, and Ireland. Society for Research in Child Development. Bharti, U., Bajaj, D., Batra, H., Lalit, S., Lalit, S., & Gangwani, A. (2020). Medbot: Conversational artificial intelligence powered chatbot for delivering tele-health after covid-19. 2020 5th international conference on communication and electronics systems (ICCES), Bhatti, A., Akram, H., Basit, H. M., Khan, A. U., Raza, S. M., & Naqvi, M. B. (2020). E-commerce trends during COVID-19 Pandemic. International Journal of Future Generation Communication and Networking, 13(2), 1449-1452. Bickmore, T. W., Puskar, K., Schlenk, E. A., Pfeifer, L. M., & Sereika, S. M. (2010). Maintaining reality: Relational agents for antipsychotic medication adherence. Interacting with Computers, 22(4), 276-288. Biz-Solutions, L. (2021). 2021 LINE CONVERGE行銷年會-TO THE NEXT BIZ (上集). Retrieved 11/18 from https://tw.linebiz.com/news/20211118/ Brahnam, S., & De Angeli, A. (2012). Gender affordances of conversational agents. Interacting with Computers, 24(3), 139-153. https://doi.org/10.1016/j.intcom.2012.05.001 Bresge, A. (2019). Why do popular digital assistants default to female voices? CTVNews. Retrieved 05/02 from https://www.ctvnews.ca/sci-tech/why-do-popular-digital-assistants-default-to-female-voices-1.4349613 Brill, T. M., Munoz, L., & Miller, R. J. (2019). Siri, Alexa, and other digital assistants: a study of customer satisfaction with artificial intelligence applications. Journal of Marketing Management, 35(15-16), 1401-1436. https://doi.org/10.1080/0267257x.2019.1687571 Broverman, I. K., Vogel, S. R., Broverman, D. M., Clarkson, F. E., & Rosenkrantz, P. S. (1972). Sex-Role Stereotypes: A Current Appraisal. Bruwer, B., Emsley, R., Kidd, M., Lochner, C., & Seedat, S. (2008). Psychometric properties of the Multidimensional Scale of Perceived Social Support in youth. Compr Psychiatry, 49(2), 195-201. https://doi.org/10.1016/j.comppsych.2007.09.002 Burgess, D., & Borgida, E. (1999). Who women are, who women should be: Descriptive and prescriptive gender stereotyping in sex discrimination. Psychology, Public Policy, and Law, 5(3), 665-692. https://doi.org/10.1037/1076-8971.5.3.665 Carver, L. F., Vafaei, A., Guerra, R., Freire, A., & Phillips, S. P. (2013). Gender differences: examination of the 12-item bem sex role inventory (BSRI-12) in an older Brazilian population. PLoS One, 8(10), e76356. https://doi.org/10.1371/journal.pone.0076356 Chabris, C. F., & Simons, D. J. (2010). The invisible gorilla: And other ways our intuitions deceive us. Harmony. Chandler, D. (2007). Semiotics: the basics. Routledge. Charlesworth, T. E. S., & Banaji, M. R. (2021). Patterns of Implicit and Explicit Stereotypes III: Long-Term Change in Gender Stereotypes. Social Psychological and Personality Science, 13(1), 14-26. https://doi.org/10.1177/1948550620988425 Cicco, R. D., Costa e Silva, S. C. L. d., & Palumbo, R. (2020). Should a Chatbot Disclose Itself? Implications for an Online Conversational Retailer. International Workshop on Chatbot Research and Design, Croes, E. A., & Antheunis, M. L. (2020). 36 Questions to Loving a Chatbot: Are People Willing to Self-disclose to a Chatbot? International Workshop on Chatbot Research and Design, Crosby, L. A., Evans, K. R., & Cowles, D. (1990). Relationship quality in services selling: an interpersonal influence perspective. Journal of marketing, 54(3), 68-81. Cui, L., Huang, S., Wei, F., Tan, C., Duan, C., & Zhou, M. (2017). SuperAgent: A Customer Service Chatbot for E-commerce Websites Proceedings of ACL 2017, System Demonstrations, De Meulenaer, S., Dens, N., De Pelsmacker, P., & Eisend, M. (2017). How consumers` values influence responses to male and female gender role stereotyping in advertising. International Journal of Advertising, 37(6), 893-913. https://doi.org/10.1080/02650487.2017.1354657 Deng, L., Turner, D. E., Gehling, R., & Prince, B. (2017). User experience, satisfaction, and continual usage intention of IT. European Journal of Information Systems, 19(1), 60-75. https://doi.org/10.1057/ejis.2009.50 DeVellis, R. F., & Thorpe, C. T. (2021). Scale development: Theory and applications. Sage publications. DiDonato, L., & Strough, J. (2013). Do College Students’ Gender-typed Attitudes About Occupations Predict Their Real-World Decisions? Sex Roles, 68(9-10), 536-549. https://doi.org/10.1007/s11199-013-0275-2 Diekman, A. B., & Goodfriend, W. (2006). Rolling with the changes: A role congruity perspective on gender norms. Psychology of Women Quarterly, 30(4), 369-383. Eagly, A. H., & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological Review, 109(3), 573-598. https://doi.org/10.1037/0033-295x.109.3.573 Eagly, A. H., Nater, C., Miller, D. I., Kaufmann, M., & Sczesny, S. (2020). Gender stereotypes have changed: A cross-temporal meta-analysis of U.S. public opinion polls from 1946 to 2018. Am Psychol, 75(3), 301-315. https://doi.org/10.1037/amp0000494 Eagly, A. H., & Wood, W. (2012). Social Role Theory. In Handbook of Theories of Social Psychology (pp. 458-476). https://doi.org/10.4135/9781446249222.n49 Elias, J. (2023, February 1). Google is asking employees to test potential ChatGPT competitors, including a chatbot called `Apprentice Bard`. Retrieved February 12 from https://www.cnbc.com/2023/01/31/google-testing-chatgpt-like-chatbot-apprentice-bard-with-employees.html Ellemers, N. (2018). Gender stereotypes. Annual review of psychology, 69, 275-298. Esposito, A., Esposito, A. M., & Vogel, C. (2015). Needs and challenges in human computer interaction for processing social emotional information. Pattern Recognition Letters, 66, 41-51. https://doi.org/10.1016/j.patrec.2015.02.013 Fajen, B. R. (2007). Affordance-Based Control of Visually Guided Action. Ecological Psychology, 19(4), 383-410. https://doi.org/10.1080/10407410701557877 Feine, J., Gnewuch, U., Morana, S., & Maedche, A. (2020). Gender Bias in Chatbot Design. In Chatbot Research and Design (pp. 79-93). https://doi.org/10.1007/978-3-030-39540-7_6 Felnhofer, A., Kothgassner, O. D., Hauk, N., Beutl, L., Hlavacs, H., & Kryspin-Exner, I. (2014). Physical and social presence in collaborative virtual environments: Exploring age and gender differences with respect to empathy. Computers in Human Behavior, 31, 272-279. https://doi.org/10.1016/j.chb.2013.10.045 Fiske, S. T. (1998). Stereotyping, prejudice, and discrimination. Fiske, S. T., & Linville, P. W. (1980). What does the schema concept buy us? Personality and social psychology bulletin, 6(4), 543-557. Fogg, B. J. (2002). Persuasive technology: using computers to change what we think and do. Ubiquity, 2002(December), 2. Foster, C. (2004). Gendered retailing: a study of customer perceptions of front‐line staff in the DIY sector. International Journal of Retail & Distribution Management, 32(9), 442-447. https://doi.org/10.1108/09590550410549329 Foster, C., & Resnick, S. (2013). Service worker appearance and the retail service encounter: the influence of gender and age. The Service Industries Journal, 33(2), 236-247. https://doi.org/10.1080/02642069.2011.614341 Gao, X., De Hooge, I. E., & Fischer, A. R. H. (2022). Something underneath? Using a within-subjects design to examine schema congruity theory at an individual level. Journal of Retailing and Consumer Services, 68. https://doi.org/10.1016/j.jretconser.2022.102994 Gasch Gallen, A., Tomas Aznar, C., & Rubio Aranda, E. (2018). Assessing gender stereotypes and sexual risk practices in men who have sex with men. Gac Sanit, 32(6), 519-525. https://doi.org/10.1016/j.gaceta.2017.05.001 Gefen, D., & Straub, D. W. (2004). Consumer trust in B2C e-Commerce and the importance of social presence: experiments in e-Products and e-Services. Omega, 32(6), 407-424. https://doi.org/10.1016/j.omega.2004.01.006 Gibson, J. J. (1977). The theory of affordances. Hilldale, USA, 1(2), 67-82. Gilligan, C. (1982). In a different voice: Psychological theory and women`s development. Harvard University Press. Grönroos, C. (1984). A service quality model and its marketing implications. European Journal of marketing. Guadagno, R. E., Muscanell, N. L., Okdie, B. M., Burk, N. M., & Ward, T. B. (2011). Even in virtual environments women shop and men build: A social role perspective on Second Life. Computers in Human Behavior, 27(1), 304-308. https://doi.org/10.1016/j.chb.2010.08.008 Gunawardena, C. N., & Zittle, F. J. (1997). Social presence as a predictor of satisfaction within a computer‐mediated conferencing environment. American Journal of Distance Education, 11(3), 8-26. https://doi.org/10.1080/08923649709526970 Gustavsson, E. (2005). Virtual servants: stereotyping female front‐office employees on the internet. Gender, Work & Organization, 12(5), 400-419. Haines, E. L., Deaux, K., & Lofaro, N. (2016). The Times They Are a-Changing … or Are They Not? A Comparison of Gender Stereotypes, 1983–2014. Psychology of Women Quarterly, 40(3), 353-363. https://doi.org/10.1177/0361684316634081 Handoyo, E., Arfan, M., Soetrisno, Y. A. A., Somantri, M., Sofwan, A., & Sinuraya, E. W. (2018). Ticketing chatbot service using serverless NLP technology. 2018 5th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), Hau-siu Chow, I., Lau, V. P., Wing-chun Lo, T., Sha, Z., & Yun, H. (2007). Service quality in restaurant operations in China: Decision- and experiential-oriented perspectives. International Journal of Hospitality Management, 26(3), 698-710. https://doi.org/10.1016/j.ijhm.2006.07.001 Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press. Heller, B., Proctor, M., Mah, D., Jewell, L., & Cheung, B. (2005). Freudbot: An investigation of chatbot technology in distance education. EdMedia+ innovate learning, Helwick, T. (2019). Messenger at F8 2019: Over 20B messages exchanged between People and Businesses every month. Messenger Business. Retrieved May 30 from https://messengernews.fb.com/2019/04/30/messenger-at-f8-2019-over-20b-messages-exchanged-between-people-and-businesses-every-month/ Hendriks, F., Ou, C. X. J., Khodabandeh Amiri, A., & Bockting, S. (2020). The Power of Computer-Mediated Communication Theories in Explaining the Effect of Chatbot Introduction on User Experience Proceedings of the 53rd Hawaii International Conference on System Sciences, Hien, H. T., Cuong, P.-N., Nam, L. N. H., Nhung, H. L. T. K., & Thang, L. D. (2018). Intelligent Assistants in Higher-Education Environments Proceedings of the Ninth International Symposium on Information and Communication Technology - SoICT 2018, Hofstede Insights. (2023, January 27). Retrieved February 12 from https://www.hofstede-insights.com/country-comparison/taiwan/ Hoy, M. B. (2018). Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants. Med Ref Serv Q, 37(1), 81-88. https://doi.org/10.1080/02763869.2018.1404391 Huang, J., Zhou, M., & Yang, D. (2007). Extracting Chatbot Knowledge from Online Discussion Forums. IJCAI, Hyde, J. S., Bigler, R. S., Joel, D., Tate, C. C., & van Anders, S. M. (2019). The future of sex and gender in psychology: Five challenges to the gender binary. Am Psychol, 74(2), 171-193. https://doi.org/10.1037/amp0000307 Jin, S.-A. A. (2010). Parasocial interaction with an avatar in second life: A typology of the self and an empirical test of the mediating role of social presence. Presence, 19(4), 331-340. Jones, K. S. (2003). What Is an Affordance? Ecological Psychology, 15(2), 107-114. https://doi.org/10.1207/s15326969eco1502_1 Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux. Kanahara, S. (2006). A Review of the Definitions of Stereotype and a Proposal for a Progressional Model. Individual Differences Research, 4(5). Kemp, S. (2022). Digital 2022: Taiwan - datareportal – global digital insights. DataReportal – Global Digital Insights. Retrieved October 19 from https://datareportal.com/reports/digital-2022-taiwan Khan, A., Ranka, S., Khakare, C., & Karve, S. (2019). NEEV: An Education Informational Chatbot. International Research Journal of Engineering and Technology (IRJET), 6(4), 492-495. Khan, M. M. (2020). Development of An e-commerce Sales Chatbot 2020 IEEE 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET), Kim, J. (2011). Developing an instrument to measure social presence in distance higher education. British Journal of Educational Technology, 42(5), 763-777. https://doi.org/10.1111/j.1467-8535.2010.01107.x Kim, M.-K., Park, M.-C., & Jeong, D.-H. (2004). The effects of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services. Telecommunications Policy, 28(2), 145-159. https://doi.org/10.1016/j.telpol.2003.12.003 King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740-755. https://doi.org/10.1016/j.im.2006.05.003 Koch, A. J., D`Mello, S. D., & Sackett, P. R. (2015). A meta-analysis of gender stereotypes and bias in experimental simulations of employment decision making. J Appl Psychol, 100(1), 128-161. https://doi.org/10.1037/a0036734 Koenig, A. M. (2018). Comparing Prescriptive and Descriptive Gender Stereotypes About Children, Adults, and the Elderly. Front Psychol, 9, 1086. https://doi.org/10.3389/fpsyg.2018.01086 Koestner, R., & Aube, J. (1995). A multifactorial approach to the study of gender characteristics. Journal of personality, 63(3), 681-710. Konrad, A. M., Ritchie, J. E., Jr., Lieb, P., & Corrigall, E. (2000). Sex differences and similarities in job attribute preferences: A meta-analysis. Psychological Bulletin, 126(4), 593-641. https://doi.org/10.1037//0033-2909.126.4.593 Kotler, P. (2000). Marketing management: The millennium edition (Vol. 10). Kuchenbrandt, D., Eyssel, F., Bobinger, S., & Neufeld, M. (2013). When a Robot’s Group Membership Matters. International Journal of Social Robotics, 5(3), 409-417. https://doi.org/10.1007/s12369-013-0197-8 Lee, E.-J. (2003). Effects of “gender” of the computer on informational social influence: the moderating role of task type. International Journal of Human-Computer Studies, 58(4), 347-362. https://doi.org/10.1016/s1071-5819(03)00009-0 Lee, K. M. (2004). Presence, explicated. Communication theory, 14(1), 27-50. Lee, K. M., Peng, W., Jin, S.-A., & Yan, C. (2006). Can Robots Manifest Personality?: An Empirical Test of Personality Recognition, Social Responses, and Social Presence in Human–Robot Interaction. Journal of Communication, 56(4), 754-772. https://doi.org/10.1111/j.1460-2466.2006.00318.x Leon, S. P., Abengozar Sanchez, C., Augusto-Landa, J. M., & Garcia-Martinez, I. (2021). Analysis of Sexual Inhibition and Satisfaction from a Gender Perspective among University Students. Int J Environ Res Public Health, 18(15). https://doi.org/10.3390/ijerph18157994 Lester, J. C., Voerman, J. L., Towns, S. G., & Callaway, C. B. (1997). Cosmo: A life-like animated pedagogical agent with deictic believability. Liu, C., Jiang, J., Xiong, C., Yang, Y., & Ye, J. (2020). Towards Building an Intelligent Chatbot for Customer Service Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Ma, E., Qu, H., & Njite, D. (2011). U.S. Customer Perceptions Toward Chinese Restaurant Service Quality: An Importance and Performance Approach. Journal of Foodservice Business Research, 14(3), 290-308. https://doi.org/10.1080/15378020.2011.594390 Macrae, C. N., & Bodenhausen, G. V. (2000). Social cognition: Thinking categorically about others. Annual review of psychology, 51(1), 93-120. Martin, C. L., & Ruble, D. (2004). Children`s Search for Gender Cues: Cognitive Perspectives on Gender Development. American Psychological Society. McGeown, S., Goodwin, H., Henderson, N., & Wright, P. (2012). Gender differences in reading motivation: Does sex or gender identity provide a better account? Journal of Research in Reading, 35(3), 328-336. Meuter, M. L., Bitner, M. J., Ostrom, A. L., & Brown, S. W. (2005). Choosing among alternative service delivery modes: An investigation of customer trial of self-service technologies. Journal of marketing, 69(2), 61-83. Meyer Von Wolff, R., Hobert, S., & Schumann, M. (2022). Chatbot Introduction and Operation in Enterprises–A Design Science Research-based Structured Procedure Model for Chatbot Projects. Proceedings of the 55th Hawaii International Conference on System Sciences, Meyers-Levy, J., & Tybout, A. M. (1989). Schema congruity as a basis for product evaluation. Journal of consumer research, 16(1), 39-54. Milkman, K. L., Chugh, D., & Bazerman, M. H. (2009). How can decision making be improved? Perspectives on psychological science, 4(4), 379-383. Moallem, M. (2015). The impact of synchronous and asynchronous communication tools on learner self-regulation, social presence, immediacy, intimacy and satisfaction in collaborative online learning. The Online Journal of Distance Education and e-Learning, 3(3), 55-77. Moreno, K. N., Person, N. K., Adcock, A. B., Eck, R. N. V., Jackson, G. T., & Marineau, J. C. (2002). Etiquette and Efficacy in Animated Pedagogical Agents: The Role of Stereotypes. Nag, P., & Yalçın, Ö. N. (2020). Gender Stereotypes in Virtual Agents Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents, Nass, C., Moon, Y., Fogg, B. J., Reeves, B., & Dryer, D. C. (1995). Can computer personalities be human personalities? International Journal of Human-Computer Studies, 43(2), 223-239. Nass, C., Moon, Y., & Green, N. (1997). Are Machines Gender Neutral? Gender-Stereotypic Responses to Computers With Voices. Neiss, M. B., Leigland, L. A., Carlson, N. E., & Janowsky, J. S. (2009). Age differences in perception and awareness of emotion. Neurobiol Aging, 30(8), 1305-1313. https://doi.org/10.1016/j.neurobiolaging.2007.11.007 Neto, A. J. M., & Fernandes, M. A. (2019). Chatbot and conversational analysis to promote collaborative learning in distance education. 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), Ng, M., Coopamootoo, K. P. L., Toreini, E., Aitken, M., Elliot, K., & van Moorsel, A. (2020). Simulating the Effects of Social Presence on Trust, Privacy Concerns & Usage Intentions in Automated Bots for Finance 2020 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), Ngai, E. W. T., & Gunasekaran, A. (2007). A review for mobile commerce research and applications. Decision Support Systems, 43(1), 3-15. https://doi.org/10.1016/j.dss.2005.05.003 Oghuma, A. P., Libaque-Saenz, C. F., Wong, S. F., & Chang, Y. (2016). An expectation-confirmation model of continuance intention to use mobile instant messaging. Telematics and Informatics, 33(1), 34-47. https://doi.org/10.1016/j.tele.2015.05.006 Oh, C. S., Bailenson, J. N., & Welch, G. F. (2018). A Systematic Review of Social Presence: Definition, Antecedents, and Implications. Front Robot AI, 5, 114. https://doi.org/10.3389/frobt.2018.00114 Oh, K.-J., Lee, D., Ko, B., & Choi, H.-J. (2017). A Chatbot for Psychiatric Counseling in Mental Healthcare Service Based on Emotional Dialogue Analysis and Sentence Generation 2017 18th IEEE International Conference on Mobile Data Management (MDM), Okuda, T., & Shoda, S. (2018). AI-based chatbot service for financial industry. Fujitsu Scientific and Technical Journal, 54(2), 4-8. Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of marketing research, 17(4), 460-469. Oliver, R. L., Rust, R. T., & Varki, S. (1997). Customer delight: foundations, findings, and managerial insight. Journal of retailing, 73(3), 311-336. Omar, M. S., Ariffin, H. F., & Ahmad, R. (2016). Service Quality, Customers’ Satisfaction and the Moderating Effects of Gender: A Study of Arabic Restaurants. Procedia - Social and Behavioral Sciences, 224, 384-392. https://doi.org/10.1016/j.sbspro.2016.05.393 Oulasvirta, A., Dayama, N. R., Shiripour, M., John, M., & Karrenbauer, A. (2020). Combinatorial Optimization of Graphical User Interface Designs. Proceedings of the IEEE, 108(3), 434-464. https://doi.org/10.1109/jproc.2020.2969687 Pham, X. L., Pham, T., Nguyen, Q. M., Nguyen, T. H., & Cao, T. T. H. (2018). Chatbot as an Intelligent Personal Assistant for Mobile Language Learning Proceedings of the 2018 2nd International Conference on Education and E-Learning, Raj, M., Sundararajan, A., & You, C. (2020). COVID-19 and digital resilience: Evidence from Uber Eats. arXiv preprint arXiv:2006.07204. Ranoliya, B. R., Raghuwanshi, N., & Singh, S. (2017). Chatbot for university related FAQs 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Reeves, B., & Nass, C. (1996). The media equation: How people treat computers, television, and new media like real people. Cambridge university press Cambridge, United Kingdom. Reshmi, S., & Balakrishnan, K. (2016). Implementation of an inquisitive chatbot for database supported knowledge bases. Sādhanā, 41(10), 1173-1178. https://doi.org/10.1007/s12046-016-0544-1 Reskin, B. F., & Bielby, D. D. (2005). A sociological perspective on gender and career outcomes. Journal of Economic Perspectives, 19(1), 71-86. Rodriguez-Roca, B., Subiron-Valera, A. B., Gasch-Gallen, A., Calatayud, E., Gomez-Soria, I., & Marcen-Roman, Y. (2021). Gender Self-Perception and Psychological Distress in Healthcare Students during the COVID-19 Pandemic. Int J Environ Res Public Health, 18(20). https://doi.org/10.3390/ijerph182010918 Ruane, E., Farrell, S., & Ventresque, A. (2020). User perception of text-based chatbot personality. International Workshop on Chatbot Research and Design, Schramm, W. (1954). How communication works. 1954, 3-26. Schuetzler, R. M., Grimes, G. M., & Scott Giboney, J. (2020). The impact of chatbot conversational skill on engagement and perceived humanness. Journal of Management Information Systems, 37(3), 875-900. https://doi.org/10.1080/07421222.2020.1790204 Sharma, P., Chen, I. S., & Luk, S. T. (2012). Gender and age as moderators in the service evaluation process. Journal of Services Marketing. Short, J. W. E. C. B. (1976). The social psychology of telecommunications. Wiley. Shumanov, M., & Johnson, L. (2021). Making conversations with chatbots more personalized. Computers in Human Behavior, 117. https://doi.org/10.1016/j.chb.2020.106627 Sinha, G., Shahi, R., & Shankar, M. (2010). Human Computer Interaction 2010 3rd International Conference on Emerging Trends in Engineering and Technology, Siriaraya, P., & Siang Ang, C. (2012). Age differences in the perception of social presence in the use of 3D virtual world for social interaction. Interacting with Computers, 24(4), 280-291. https://doi.org/10.1016/j.intcom.2012.03.003 Soboczenski, F., Cairns, P., & Cox, A. L. (2013). Increasing accuracy by decreasing presentation quality in transcription tasks. IFIP Conference on Human-Computer Interaction, Stalmachova, K., Chinoracky, R., & Strenitzerova, M. (2021). Changes in Business Models Caused by Digital Transformation and the COVID-19 Pandemic and Possibilities of Their Measurement—Case Study. Sustainability, 14(1). https://doi.org/10.3390/su14010127 Stout, J. G., Grunberg, V. A., & Ito, T. A. (2016). Gender Roles and Stereotypes about Science Careers Help Explain Women and Men’s Science Pursuits. Sex Roles, 75(9-10), 490-499. https://doi.org/10.1007/s11199-016-0647-5 Tamayo, P. A., Herrero, A., Martín, J., Navarro, C., & Tránchez, J. M. (2019). Design of a chatbot as a distance learning assistant. Open Praxis, 12(1). https://doi.org/10.5944/openpraxis.12.1.1063 Tatai, G., Csordás, A., Kiss, Á., Szaló, A., & Laufer, L. (2003). Happy Chatbot, Happy User. Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach`s alpha. Int J Med Educ, 2, 53-55. https://doi.org/10.5116/ijme.4dfb.8dfd Thomas, N. (2016). An e-business chatbot using AIML and LSA. 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Thorat, S. A., & Jadhav, V. (2020). A review on implementation issues of rule-based chatbot systems. Proceedings of the International Conference on Innovative Computing & Communications (ICICC), Toader, D.-C., Boca, G., Toader, R., Măcelaru, M., Toader, C., Ighian, D., & Rădulescu, A. T. (2019). The Effect of Social Presence and Chatbot Errors on Trust. Sustainability, 12(1). https://doi.org/10.3390/su12010256 Tsai, W.-H. S., Liu, Y., & Chuan, C.-H. (2021). How chatbots` social presence communication enhances consumer engagement: the mediating role of parasocial interaction and dialogue. Journal of Research in Interactive Marketing, 15(3), 460-482. https://doi.org/10.1108/jrim-12-2019-0200 Tu, C.-H. (2000). On-line learning migration: from social learning theory to social presence theory in a CMC environment. Journal of Network and Computer Applications, 23(1), 27-37. https://doi.org/10.1006/jnca.1999.0099 Tu, C.-H., & McIsaac, M. (2002). The Relationship of Social Presence and Interaction in Online Classes. American Journal of Distance Education, 16(3), 131-150. https://doi.org/10.1207/s15389286ajde1603_2 Turing, A. (1950). Computing Machinery and Intelligence. Mind. Vafaei, A., Alvarado, B., Tomas, C., Muro, C., Martinez, B., & Zunzunegui, M. V. (2014). The validity of the 12-item Bem Sex Role Inventory in older Spanish population: an examination of the androgyny model. Arch Gerontol Geriatr, 59(2), 257-263. https://doi.org/10.1016/j.archger.2014.05.012 Vaira, L., Bochicchio, M. A., Conte, M., Casaluci, F. M., & Melpignano, A. (2018). MamaBot Proceedings of the 22nd International Database Engineering & Applications Symposium on - IDEAS 2018, Verhagen, T., van Nes, J., Feldberg, F., & van Dolen, W. (2014). Virtual Customer Service Agents: Using Social Presence and Personalization to Shape Online Service Encounters. Journal of computer-mediated communication, 19(3), 529-545. https://doi.org/10.1111/jcc4.12066 Walther, J. B. (1992). Interpersonal effects in computer-mediated interaction: A relational perspective. Communication research, 19(1), 52-90. Wang, D., & Fang, H. (2020). Length Adaptive Regularization for Retrieval-based Chatbot Models Proceedings of the 2020 ACM SIGIR on International Conference on Theory of Information Retrieval, Wang, L. C., Baker, J., Wagner, J. A., & Wakefield, K. (2007). Can A Retail Web Site be Social? Journal of marketing, 71(3), 143-157. https://doi.org/10.1509/jmkg.71.3.143 Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45. https://doi.org/10.1145/365153.365168 Xu, A., Liu, Z., Guo, Y., Sinha, V., & Akkiraju, R. (2017). A New Chatbot for Customer Service on Social Media Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Xu, K., & Lombard, M. (2017). Persuasive computing: Feeling peer pressure from multiple computer agents. Computers in Human Behavior, 74, 152-162. https://doi.org/10.1016/j.chb.2017.04.043 Yen, C.-J., & Tu, C.-H. (2008). Online social presence: A study of score validity of the computer-mediated communication questionnaire. Quarterly Review of Distance Education, 9(3). Zarouali, B., Van den Broeck, E., Walrave, M., & Poels, K. (2018). Predicting consumer responses to a chatbot on Facebook. Cyberpsychology, Behavior, and Social Networking, 21(8), 491-497. Zumstein, D., & Hundertmark, S. (2017). CHATBOTS--AN INTERACTIVE TECHNOLOGY FOR PERSONALIZED COMMUNICATION, TRANSACTIONS AND SERVICES. IADIS International Journal on WWW/Internet, 15(1).
描述:	碩士國立政治大學數位內容碩士學位學程 109462015
資料來源:	http://thesis.lib.nccu.edu.tw/record/#G0109462015
数据类型:	thesis
显示于类别:	[數位內容碩士學位學程] 學位論文

文件中的档案:

档案	描述	大小	格式	浏览次数
201501.pdf		3102Kb	Adobe PDF2	175	检视/开启

在政大典藏中所有的数据项都受到原著作权保护.

社群 sharing

著作權政策宣告 Copyright Announcement

1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.

DSpace Software Copyright © 2002-2004 MIT & Hewlett-Packard / Enhanced by NTU Library IR team Copyright © - 回馈