Customer adoption of Chat GPT for web development and programming assistance in the Zimbabwe tech industry
Abstract
ChatGPT, an advanced conversational AI model by OpenAI, signifies a significant leap in human-computer interaction. Optimized for dialogue, ChatGPT has the potential to transform web development and programming support. In Zimbabwe, 60% of IT programmers express concerns about UI/UX design, while 70% face challenges in service quality due to software flaws and inadequate testing. This study investigates ChatGPT's application in Zimbabwe's tech industry for web development and programming support, and its impact on organizational performance. Employing an integrated Delone and McLean IS Success Model, the research examines adoption trends, barriers, and benefits of integrating ChatGPT into development workflows.A quantitative approach was utilized, employing survey data and statistical methods. A 5-point Likert Scale survey was distributed to 30 Zimbabwean ICT workers. Data analysis with SmartPLS 3.0 included descriptive and confirmatory factor analyses to assess reliability (Cronbach's alpha, composite reliability) and validity (factor loadings, AVE, HTMT ratio). Results indicate that ChatGPT significantly influences system, information, and service quality, enhancing user satisfaction and organizational benefits, with system quality exerting the strongest impact. Moreover, system quality positively affects organizational performance, though the moderating role of flexible organizational culture was insignificant. Recommendations include enhancing training data tailored to local technological needs, integrating real-time data sources, offering a paid version for updated data, ensuring robust error handling for service quality, providing educational resources, implementing feedback mechanisms, conducting developer training programs, and promoting cross-functional collaboration.
References
AI, C. O. (2023). Chatgpt by Open AI. Retrieved from Chatgpt by Open AI: https://openai.com/blog/chatgpt#:~:text=Authors&text=ChatGPT%20is%20a%20sibling%20model,at%20chat.openai.com.
AI, C. G. (2023). Chat Gpt Help . Retrieved from Chat GPT by Open AI : https://help.openai.com/en/articles/6783457-what-is-chatgpt#:~:text=How%20does%20ChatGPT%20work%3F,the%20model%20toward%20desired%20behavior.
Statista. (2023). Retrieved from Statista: https://www.statista.com/chart/29174/time-to-one-million-users/
IOT Anayltics . (2023). Retrieved from IOT Anayltics : https://iot-analytics.com/industry-4-0-in-5-stats/
dataxan. (2022). Retrieved from dataxan: https://dataxan.com/chatgpt-and-its-use-cases
The exchange Africa. (2023). Retrieved from The exchange Africa: https://theexchange.africa/tech-business/zimbabwe-ecocash-introduces-ai-powered-bot-to-improve-customer-experience
Arthur, F. (2023). Making the Marketing Concept Work. Harvard Business Review, 55-65.
Oke, A. O. (2015). Consumer Behavior towards Decision Making and Loyalty to Particular Brands.
Delone, W. H. (2003). The DeLone and McLean model of information systems success: A ten-year update".
L. Gao, K. A. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study—A case of China. Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study—A case of China, 249-262.
Palmer, J. W. (2002). Web site usability design and performance metrics. Inf. Syst. Res.
Lin, H.-F. (2007). The impact of website quality dimensions on customer satisfaction in the B2C e-commerce context". Total Quality Manage. Bus. Excellence, 363-378.
Donna, L. (1997). A new marketing paradigm for electronic commerce. Inf. Soc.
J. V. Chen, D. C. (2015). E-commerce web site loyalty: A cross cultural comparison.
T. S. H. Teo, S. C. (2008). Trust and electronic government success: An empirical study.
R. Filieri, S. A. (2015). Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-generated media and its influence on recommendation adoption and word of mouth. Tourism Manage.
L.Gao. (2017). Examining the role of initial trust in user adoption of mobile payment services: An empirical investigation. 525-548.
Bell, H. (1998). The effectiveness of commercial internet web sites: A user’s perspective. 219-228.
Szymanski, D. M. (2000). E-satisfaction: An initial examination. J. Retailing, 309-322.
Kim, S. (2004). Apparel retailers: Website quality dimensions and satisfaction". J. Retailing Consum. Services, 109-177.
L. Ciechanowski, A. P. (2019). In the shades of the uncanny valley: An experimental study of human–chatbot interaction. Future Gener. Comput. Syst., vol. 92, 539-548.
G.Mclean. (2016). Evolving the online customer experience ⋅⋅⋅ is there a role for online customer support? Comput. Hum. Behav., vol. 60, 602-610.
Mills, A. M. (2011). Knowledge management and organizational performance: A decomposed view. J. Knowl. Manage., vol. 15, 156-171.
G.N.Stock. (2007). Organizational culture critical success factors and the reduction of hospital errors. nt. J. Prod. Econ., vol. 106, 368-392.
Z.Shao. (2016). Impact of chief information officer’s strategic knowledge and structural power on enterprise systems success. Impact of chief information officer’s strategic knowledge and structural power on enterprise systems success, 43-64.
Park, Y. S. (2020 ). Himmelfarb Health Sciences Library, The George Washington UniversityHimmelfarb Health Sciences Library, The George Washington University Health Sciences Research CommonsHealth Sciences R. The Positivism Paradigm of Research. .
Research guides . (2023). Retrieved from USC Libraries : https://libguides.usc.edu/writingguide/quantitative
Chu, M.-N. (2022). Assessing the Benefits of ChatGPT for Business: An Empirical Study on Organizational Performance.
Statista. (2022). Retrieved from Statista: https://www.statista.com/statistics/1384324/chat-gpt-demographic-usage/
Anderson, T., Varnhagen, S., & Campbell, K. (1998). Faculty adoption of teaching and learning technologies: Contrasting earlier adopters and mainstream faculty. The Canadian Journal of Higher Education, 28(23),71-78.
Bennett, J., & Bennett, L. (2003). A review of factors that influence the diffusion of innovation when structuring faculty training programs. Internet and Higher Education,6, 53-63.Blankenship, S.E. (1998). Factors related to computer use by teachers in classroom instruction (Doctoral
Dissertation, Virginia Polytechnic Institute and State University, 1998). ProQuest Digital Dissertations.(UMI No. AAT 9831651).Break, J.V. (2001). Individual characteristics influencing teachers’ class use of computers. Journal of Educational Computing Research, 25(2), 141-157.
Carter, C.W. (1998). An assessment of the status of the diffusion and adoption of computer-based technology in Appalachian College Association colleges and universities (Doctoral Dissertation, Virginia Polytechnic Institute and State University, 1998). ProQuest Digital Dissertations. (UMI No. AAT 9905169).
Casmar S.P. (2001). The adoption of computer technology by faculty in a college of education: an analysis of administrative planning issues (Doctoral dissertation, Washington State University, 2001). ProQuestDigitalDissertations. (UMI No. AAT 3025011).
Dooley, K.E. (1999). Towards a holistic model for the diffusion of educational technologies: An integrative review of educational innovation studies. Educational Technology & Society 2(4), 35-45.Finley, T.R. (2003). A descriptive study of the utilization of technology from the perspective of full-time faculty in
Virginia’s higher education teacher-education programs (Doctoral dissertation, The George Washington University, 2003). ProQuest Digital Dissertations. (UMI No. AAT 3083800).
Hoerup, S.L. (2001). Diffusion of innovation: computer technology integration and the role of collaboration(Doctoral dissertation, Virginia Polytechnic Institute and State University, 2001). ProQuest
Digital Dissertations. (UMI No. AAT 3031436).Isleem, M I. (2003). Relationships of selected factors and the level of computer use for instructional purposes by technology education teachers in Ohio public schools: a state-wide survey (Doctoral dissertation, The Ohio State University, 2003). ProQuest DigitalDissertations. (UMI No. AAT 3124087).
Jacobsen, M. (1998). Adoption patterns and characteristics of faculty who integrate computer technology for teaching and learning in higher education. (Doctoral dissertation, The University of Calgary, 1998).ProQuest DigitalDissertations. (UMI No. AAT NQ34679).
Less, K.H. (2003). Faculty adoption of computer technology for instruction in the North Carolina Community College System (Doctoral dissertation, East Tennessee State University, 2003). ProQuestDigitalDissertations. (UMI No. AAT 3097072).
Light, P.C. (1998). Sustaining innovation. San Francisco: Jossey-Bass.
Martin, M.H. (2003). Factors influencing faculty adoption of Web-based courses in teacher education programs within the State University of New York (Doctoral dissertation, Virginia Polytechnic Institute and State University, 2001). ProQuest DigitalDissertations. (UMI No. AAT 3089087).
McKenzie, J. (2001). How teachers learn technology best. From Now On: The Educational Technology Journal,10(6). Retrieved March 01, 2005, from http://www.fno.org/mar01/howlearn.html
Medlin, B.D. (2001). The factors that may influence a faculty member's decision to adopt electronic technologies in instruction (Doctoral dissertation, Virginia Polytechnic Institute and State University, 2001). ProQuestDigitalDissertations. (UMI No. AAT 3095210).
Parisot, A.H. (1995). Technology and teaching: The adoption and diffusion of technological innovations by a community college faculty (Doctoral dissertation, Montana State University, 1995). ProQuestDigitalDissertations. (UMI No. AAT 9542260).
Parisot, A.H. (1997). Distance education as a catalyst for changing teaching in the community college: Implications for institutional policy. New Directions for Community Colleges, 99, 5-13.
Rogers, E.M. (2003). Diffusion of innovations (5th ed.). New York: Free Press. Schmidt, D. (1995). Use and integration of computer-related technology in teaching by preservice teacher
education faculty (Doctoral dissertation, Iowa State University, 1995). ProQuest DigitalDissertations.(UMI No. AAT 9610982).
Seemann, K. (2003). Basic principles in holistic technology education. Journal of Technology Education, 14(2),28-39.
Sherry, L. (1997). The Boulder Valley Internet project: Lessons learned. THE (Technological Horizons in Education) Journal, 25(2), 68-73.
The Turkish Online Journal of Educational Technology – TOJET April 2006 ISSN: 1303-6521 volume 5 Issue 2 Article 3Slyke, C.V. (1998). Technology cluster innovations: impacts of adding a technology to an existing cluster
(Doctoral dissertation, University of South Florida, 1998). ProQuest DigitalDissertations. (UMI No. AAT9911522).
Spots, T.H. (1999). Discriminating factors in faculty use of instructional technology in higher education. Educational Technology & Society, 2(4), 92-99.Sprague, D., Kopfman, K., & Dorsey, S. (1999). Faculty development in the integration of technology in teacher education courses. Journal of Computing in Teacher Education, 14(2), 24-28.
Stuart, W.D. (2000). Influence of sources of communication, user characteristics, and innovation characteristics on adoption of a communication technology (Doctoral dissertation, The University of Kansas, 2000).ProQuest DigitalDissertations. (UMI No. AAT 9998115).
