Research on Influencing Factors of AI Chat Robot on Customer Satisfaction of Online Shopping Platform: Take Alibaba as an example

VAKHRUSHVE NATALIA

doi:10.54097/zx7y7622

Authors

VAKHRUSHVE NATALIA

DOI:

https://doi.org/10.54097/zx7y7622

Keywords:

AI chatbot, Customer satisfaction, ALIBABA, SE.

Abstract

Based on the technology acceptance model, this study deeply investigates the factors influencing customer satisfaction of AI Chatbot, and portrays the relationships between different latent variables from both TAM and external factors to reveal the information quality, usability, self-efficacy, perceived enjoyment, subjective norms, perceived ease of use, perceived usefulness and customer satisfaction. A total of 481 valid questionnaires were obtained through online questionnaire distribution and offline interview research, and the samples were analyzed by SPSS software for reliability and heterogeneity, and then the SEM model path analysis was conducted by Amos software to derive the direct or indirect relationships among the variables. Main research conclusions include:(1) information quality, usability, self-efficacy, perceived enjoyment have a direct impact on customers' perceived ease of use (2) subjective norms can positively affect customers' perceived usefulness; (3) perceived ease of use and perceived usefulness have a direct positive impact on customers' satisfaction. Last, this study further discusses the research results, elaborates the theoretical significance and practical significance of this study, and finally puts forward the limitations and looks forward to future studies.

Downloads

Download data is not yet available.

References

Katie C. Gartner Survey Shows 37 Percent of Organizations Have Implemented AI in Some Form (2019-01-21). https://www.gartner.com/en/newsroom/press-releases/2019-01-21-gartner-survey-shows-37-percent-of-organizations-have.

Yuen T H J, Cheung H H. Using clinical history taking chatbot mobile app for clinical bedside teachings–a prospective case control study[J]. Heliyon, 2022, 8(6).

Janssen A, Rodriguez Cardona D, Breitner M H. More than FAQ! Chatbot taxonomy for business-to-business customer services[C]//International Workshop on Chatbot Research and Design. Cham: Springer International Publishing, 2020: 175-189.

Ervin L. Survey: Consumers say No to Chatbot Silos (2018-02-07). https://www.chatbots.org/conversational/agent/chatbots.org_report_consumers_chatbot_usage_uk_us/.

Hubona G S, Kennick E. The influence of external variables on information technology usage behavior[C]//Proceedings of HICSS-29: 29th Hawaii International Conference on System Sciences. IEEE, 1996, 4: 166-175.

Davis F D. Perceived usefulness, perceived ease of use, and user acceptance of information technology[J]. MIS quarterly, 1989: 319-340.

Lin G T R, Sun C C. Factors influencing satisfaction and loyalty in online shopping: an integrated model[J]. Online information review, 2009, 33(3): 458-475.

Szymanski D M, Hise R T. E-satisfaction: an initial examination[J]. Journal of retailing, 2000, 76(3): 309-322.

Bansal H S, McDougall G H G, Dikolli S S, et al. Relating e‐satisfaction to behavioral outcomes: an empirical study[J]. Journal of services marketing, 2004, 18(4): 290-302.

Hubona G S, Geitz S. External variables, beliefs, attitudes and information technology usage behavior[C]//Proceedings of the thirtieth Hawaii international conference on system sciences. IEEE, 1997, 3: 21-28.

Venkatesh V. Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model[J]. Information systems research, 2000, 11(4): 342-365.

Burton-Jones A, Hubona G S. Individual differences and usage behavior: revisiting a technology acceptance model assumption[J]. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 2005, 36(2): 58-77.

Hubona G S, Burton-Jones A. Modeling the user acceptance of e-mail[C]//36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the. IEEE, 2003: 10 pp.

McKinney V, Yoon K, Zahedi F M. The measurement of web-customer satisfaction: An expectation and disconfirmation approach[J]. Information systems research, 2002, 13(3): 296-315.

Pudjihardjo M C, Wijaya H, Remiasa M. Analisa Pengaruh Kepercayaan, Kemudahan, Kualitas Informasi, Dan Tampilan Produk Terhadap Keputusan Pembelian Melalui Pemasaran Di Media Sosial (Studi Pada Pengguna Media Sosial Di Shapeharve)[J]. Jurnal Hospitality dan Manajemen Jasa, 2015, 3(2): 364-379.

Kim M J, Chung N, Lee C K, et al. Dual-route of persuasive communications in mobile tourism shopping[J]. Telematics and Informatics, 2016, 33(2): 293-308.

Chen C W, Chen W C, Chen W K. Understanding the effects of eWOM on cosmetic consumer behavioral intention[J]. International Journal of Electronic Commerce Studies, 2014, 5(1): 97-102.

McKinney V, Yoon K, Zahedi F M. The measurement of web-customer satisfaction: An expectation and disconfirmation approach[J]. Information systems research, 2002, 13(3): 296-315.

Dillon A. User acceptance of information technology[M]. London: Taylor and Francis, 2001.

Bandura A. Social foundations of thought and action[J]. Englewood Cliffs, NJ, 1986, 1986(23-28): 2.

Compeau D R, Higgins C A. Application of social cognitive theory to training for computer skills[J]. Information systems research, 1995, 6(2): 118-143.

Lai M L. Technology readiness, internet self‐efficacy and computing experience of professional accounting students[J]. Campus-Wide Information Systems, 2008, 25(1): 18-29.

Venkatesh V, Davis F D. A model of the antecedents of perceived ease of use: Development and test[J]. Decision sciences, 1996, 27(3): 451-481.

Chen N S, Huang H Y, Shih Y C. Factors affecting usage of web-based teachers' training in elementary and high school[C]//International Conference on Computers in Education, 2002. Proceedings. IEEE, 2002: 589-592.

Venkatesh V, Davis F D. A theoretical extension of the technology acceptance model: Four longitudinal field studies[J]. Management science, 2000, 46(2): 186-204.

Muslimah D A, Aisyah M N. Pengaruh computer self-efficacy, subjective norm, dan system quality terhadap penerimaan womunity oleh nasabah WOM finance[J]. Jurnal Profita: Kajian Ilmu Akuntansi, 2016, 4(8).

Venkatesh V, Bala H. Technology acceptance model 3 and a research agenda on interventions[J]. Decision sciences, 2008, 39(2): 273-315

Amelia E. Analisis perilaku minat menggunakan mobile payment dengan pendekatan technology acceptance model 3: Studi pada pengguna aplikasi pembayaran OVO[D]. Universitas Pendidikan Indonesia, 2019.

Ajzen I. The theory of planned behavior[J]. Organizational behavior and human decision processes, 1991, 50(2): 179-211.

Venkatesh V, Davis F D. A theoretical extension of the technology acceptance model: Four longitudinal field studies[J]. Management science, 2000, 46(2): 186-204.

Muslimah D A, Aisyah M N. Pengaruh computer self-efficacy, subjective norm, dan system quality terhadap penerimaan womunity oleh nasabah WOM finance[J]. Jurnal Profita: Kajian Ilmu Akuntansi, 2016, 4(8).

Bogea F, Brito E P Z. Determinants of social media adoption by large companies[J]. Journal of technology management & innovation, 2018, 13(1): 11-18.

Hasan B. Examining the effects of computer self-efficacy and system complexity on technology acceptance[J]. Information Resources Management Journal (IRMJ), 2007, 20(3): 76-88

Kang Y, Lee M, Lee S. Service-oriented factors affecting the adoption of smartphones[J]. Journal of technology management & innovation, 2014, 9(2): 98-117.

Padilla-Melendez A, del Aguila-Obra A R, Garrido-Moreno A. Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario[J]. Computers & Education, 2013, 63: 306-317.

Winarno W A, Putra H S. Technology acceptance model of the Indonesian government financial reporting information systems[J]. International Journal of Public Sector Performance Management, 2020, 6(1): 68-84.

Muslimah D A, Aisyah M N. Pengaruh computer self-efficacy, subjective norm, dan system quality terhadap penerimaan womunity oleh nasabah WOM finance[J]. Jurnal Profita: Kajian Ilmu Akuntansi, 2016, 4(8).

Doll, W.J. and Torkzadeh, G. (1988); *The measurement of end-user computingsatisfaction" MIS Quarterly Vol. 12 Issue 2

O. Pappas I, G. Pateli A, N. Giannakos M, et al. Moderating effects of online shopping experience on customer satisfaction and repurchase intentions[J]. International Journal of Retail & Distribution Management, 2014, 42(3): 187-204.

Little T D. Mean and covariance structures (MACS) analyses of cross-cultural data: Practical and theoretical issues[J]. Multivariate behavioral research, 1997, 32(1): 53-76.

Wang Qing. Study on Electric Vehicle Purchase Intention based on TAM and PMT integrated model [D]. Beijing Institute of Technology, 2015.

Ali B M, Younes B. The impact of information systems on user performance: an exploratory study[J]. Journal of Knowledge Management, Economics and Information Technology, 2013, 3(2): 128-154.

International Standards Organisation. Ergonomics of Human-System Interaction—Part 11: Usability: Definitions and Concepts (ISO 9241-11: 2018); International Organization for Standardization: Geneva, Switzerland, 2008.

Kurniawati H A, Arif A, Winarno W A. Analisis minat penggunaan mobile banking dengan pendekatan Technology Acceptance Model (TAM) yang telah dimodifikasi[J]. E-Journal Ekonomi Bisnis Dan Akuntansi, 2017, 4(1): 24-29.

Amelia E. Analisis perilaku minat menggunakan mobile payment dengan pendekatan technology acceptance model 3: Studi pada pengguna aplikasi pembayaran OVO[D]. Universitas Pendidikan Indonesia, 2019.

Maranguni, Grani A. Technology acceptance model: a literature review from 1986 to 2013[J]. Universal access in the information society, 2015, 14: 81-95.

Venkatesh V, Bala H. Technology acceptance model 3 and a research agenda on interventions[J]. Decision sciences, 2008, 39(2): 273-315.

Muslimah D A, Aisyah M N. Pengaruh computer self-efficacy, subjective norm, dan system quality terhadap penerimaan womunity oleh nasabah WOM finance[J]. Jurnal Profita: Kajian Ilmu Akuntansi, 2016, 4(8).

Davis F D. Perceived usefulness, perceived ease of use, and user acceptance of information technology[J]. MIS quarterly, 1989: 319-340.

Davis F D, Bagozzi R P, Warshaw P R. User acceptance of computer technology: A comparison of two theoretical models[J]. Management science, 1989, 35(8): 982-1003.

Padilla-Melendez A, del Aguila-Obra A R, Garrido-Moreno A. Perceived playfulness, gender differences and technology acceptance model in a blended learning scenario[J]. Computers & Education, 2013, 63: 306-317.

Winarno W A, Putra H S. Technology acceptance model of the Indonesian government financial reporting information systems[J]. International Journal of Public Sector Performance Management, 2020, 6(1): 68-84.

Kurniawati H A, Arif A, Winarno W A. Analisis minat penggunaan mobile banking dengan pendekatan Technology Acceptance Model (TAM) yang telah dimodifikasi[J]. E-Journal Ekonomi Bisnis Dan Akuntansi, 2017, 4(1): 24-29.

Muslimah D A, Aisyah M N. Pengaruh computer self-efficacy, subjective norm, dan system quality terhadap penerimaan womunity oleh nasabah WOM finance[J]. Jurnal Profita: Kajian Ilmu Akuntansi, 2016, 4(8).

Venkatesh V, Davis F D. A theoretical extension of the technology acceptance model: Four longitudinal field studies[J]. Management science, 2000, 46(2): 186-204.

Daud A, Farida N, Andriansah A, et al. Impact of customer trust toward loyalty: The mediating role of perceived usefulness and satisfaction[J]. Journal od Business and Retail Management Research (JBRMR), 2018, 13(2): 235-242.