Exploring Growth Strategies of European Small and Medium-sized Enterprises in the Service Sector using ChatGPT

Authors

  • Linmu Cui Turiba University

DOI:

https://doi.org/10.5755/j01.eis.1.17.33726

Keywords:

artificial intelligence, ChatGPT, small and medium-sized enterprises (SMEs), service sector, efficiency improvement, growth strategy

Abstract

In recent years, the development of the artificial intelligence is changing with each passing day. Artificial intelligence has more and more application scenarios in modern production and life, generating more value and sparking numerous discussions. The epoch-making significance of the launch of ChatGPT (and its successive version GPT4) in late 2022 cannot be overstated. In just two months, it became the fastest application in human history to exceed 100 million registered users worldwide and is considered the core digital product of the next-generation technological revolution, with great potential for development. ChatGPT's high intelligence can efficiently solve many problems faced by the European small and medium-sized enterprises in the service sector, providing more possible approaches for their growth. To explore growth strategies for small and medium-sized enterprises in the service sector, semi-structured interviews have been conducted (n=24) and a qualitative methodology is used to analyze the role that ChatGPT can play. The optimization and assistance that ChatGPT can bring to the development of small and medium-sized enterprises in the service sector is analyzed in a structured way from the aspects of human resource management, strategy decision making, fund raising, service research and development, finance, marketing, sales, administration and operation. Based on findings and existing research on the role of artificial intelligence in SMEs’ development, the authors propose development paths and implementation strategies for ChatGPT technology to assist small and medium-sized enterprises in optimization and growing.

References

Agrawal, A., Gans, J., & Goldfarb, A. (2022). ChatGPT and How AI Disrupts Industries. Harvard Business Review. Retrieved December 12, 2022, from https://hbr.org/2022/12/chatgpt-and-how-ai-disrupts-industries

Alshater, M. (2022). Exploring the role of artificial intelligence in enhancing academic performance: A case study of ChatGPT. Available at SSRN: https://ssrn.com/abstract=4312358 or https://doi.org/10.2139/ssrn.4312358

Araujo, T. (2018). Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers in Human Behavior, 85, 183–189.

Azaria, A. (2022). ChatGPT usage and limitations. HAL Open Science hal-03913837.

Balakrishnan, J., Nwoba, A., & Nguyen, N. (2021). Emerging-market consumers’ interactions with banking chatbots. Telematics and Informatics, 65, Article 101711.

Bates, M. (2019). Health care chatbots are here to help. IEEE Pulse (Volume: 10) (Issue: 3). May-June Page(s): 12 - 14.

Belk, R. (2021). Ethical issues in service robotics and artificial intelligence. The Service Industries Journal, 41(13–14), 860–876.

Bock, D. E., Wolter, J. S., & Ferrell, O. C. (2020). Artificial intelligence: disrupting what we know about services. Journal of Services Marketing, 34(3), 317–334.

Brachten, F., Kissmer, T., & Stieglitz, S. (2021). The acceptance of chatbots in an enterprise context – A survey study. International Journal of Information Management, 60, Article 102375.

Buhalis, D., & Moldavska, I. (2022). Voice assistants in hospitality: using artificial intelligence for customer service. Journal of Hospitality and Tourism Technology, 13 (3), 386–403.

Castelvecchi, D. (2022). Are ChatGPT and AlphaCode going to replace programmers? Nature. https://doi.org/10.1038/d41586-022-04383-z

Cocco, L., Mannaro, K., Tonelli, R., Mariani, L., Lodi, M. B., Melis, A., Simone, M., & Fanti, A. (2021). A blockchain-based traceability system in agri-food SME: Case study of a traditional bakery. IEEE Access, 9, 62899–62915. https://doi.org/10.1109/ACCESS.2021.3074874

Coombs, C., Stacey, P., Kawalek, P., Simeonova, B., Becker, J., Bergener, K., & Trautmann, H. (2021). What is it about humanity that we can’t give away to intelligent machines? A European perspective. International Journal of Information Management, 58, Article 102311.

Cranefield, J., Winikoff, M., Chiu, Y. T., Li, Y., Doyle, C., & Richter, A. (2022). Partnering with AI: The case of digital productivity assistants. Journal of the Royal Society of New Zealand. https://doi.org/10.1080/03036758.2022.2114507

Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.

Deng, J., & Lin, Y. (2022). The benefits and challenges of ChatGPT: An overview. Frontiers in Computing and Intelligent Systems, 2(2), 81–83.

Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71.

Firat, M. (2023). How ChatGPT Can Transform Autodidactic Experiences and Open Education? https://doi.org/10.31219/osf.io/9ge8m

Floridi, L. (2019). Establishing the rules for building trustworthy AI. Nature Machine Intelligence, 1(6), 261–262.

Floridi, L., & Chiratti, M. (2020). GPT-3: Its nature, scope, limits, and consequences. Minds and Machines, 30, 681–694.

Getahun, H. (2023). ChatGPT could be used for good, but like many other AI models, it’s rife with racist and discriminatory bias. From https://www.insider.com/chatgpt-is-like-many-other-ai-models-rife-with-bias-2023-1

Gherghina Ș.C., Botezatu M.A., Hosszu A., & Simionescu L.N. (2020) Small and Medium-Sized Enterprises (SMEs): The Engine of Economic Growth through Investments and Innovation. Sustainability. 2020; 12(1):347. https://doi.org/10.3390/su12010347

Gupta, S., & Chen, Y. (2022). Supporting Inclusive Learning Using Chatbots? A Chatbot Led Interview Study. Journal of Information Systems Education, 33(1), 98–108.

Kietzmann, J., Paschen, J., & Treen, E. R. (2018). “Artificial Intelligence in Advertising: How Marketers Can Leverage Artificial Intelligence Along the Consumer Journey. Journal of Advertising Research, 58(3), 263–267.

Kim, H., Shin, D. K., Yang, H., & Lee, J. H. (2019). A study of AI chatbot as an assistant tool for school English curriculum. Korean Association for Learner-Centered Curriculum and Instruction, 19(1), 89–110. https://doi.org/10.22251/jlcci.2019.19.1.89

Krügel, S., Ostermaier, A., & Uhl, M. (2023). The moral authority of ChatGPT. arXiv preprint arXiv:2301.07098.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., ... Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, Volume 71,102642, ISSN 0268-4012, https://doi.org/10.1016/j.ijinfomgt.2023.102642

Kushwaha, A. K., & Kar, A. K. (2021). MarkBot – A Language Model-Driven Chatbot for Interactive Marketing in Post-Modern World. Retrieved January 31, 2023, from Information Systems Frontiers. https://doi.org/10.1007/s10796-021-10184-y

Ma, L., & Sun, B. (2020). Machine learning and AI in marketing–Connecting computing power to human insights. International Journal of Research in Marketing, 37(3), 481–504.

Mariani, M. M., Machado, I., & Nambisan, S. (2023). Types of innovation and artificial intelligence: A systematic quantitative literature review and research agenda. Journal of Business Research, 155, Article 113364. https://doi.org/10.1016/j.jbusres.2022.113364

Merhi, M. I. (2022). An Evaluation of the Critical Success Factors Impacting Artificial Intelligence Implementation. International Journal of Information Management., Article 102545. https://doi.org/10.1016/j.ijinfomgt.2022.102545

Mithas, S., Chen, Z.-L., Saldanha, T., & Silveira, A. D. O. (2022). How Will Artificial Intelligence and Industry 4.0 Emerging Technologies Transform Operations Management? Production and Operations Management, 31(12), 4475–4487. https://doi.org/10.1111/poms.13864

Mogaji, E., Farquhar, J. D., Van Esch, P., Durodi ́e, C., & Perez-Vega, R. (2022). Guest editorial: Artificial intelligence in financial services marketing. International Journal of Bank Marketing, 40(6), 1097–1101.

Mogaji, E., Olaleye, S., & Ukpabi, D. (2020). Using AI to personalize emotionally appealing advertisement. Digital and Social Media Marketing: Emerging Applications and Theoretical Development (pp. 137–150). Cham: Springers.

Northey, G., Hunter, V., Mulcahy, R., & Choong, K. (2022). Man vs machine: how artificial intelligence in banking influences consumer belief in financial advice. International Journal of Bank Marketing, 40(6), 1182–1199.

Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education Artificial Intelligence, 2, Article 100033. https://doi.org/10.1016/j.caeai.2021.100033

Pizzi, G., Scarpi, D., & Pantano, E. (2021). Artificial intelligence and the new forms of interaction: Who has the control when interacting with a chatbot? Journal of Business Research, 129, 878–890.

Qadir, J. (2022). Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education. TechRxiv. https://doi.org/10.36227/techrxiv.21789434.v1

Prasanna, R., Jayasundara, J., Naradda Gamage, S. K., Ekanayake, E., Rajapakshe, P., & Abeyrathne, G. (2019). Sustainability of SMEs in the competition: A systemic review on technological challenges and SME performance. Journal of Open Innovation, 5(4), 100. https://doi.org/10.3390/joitmc5040100

Sheth, J. N., Jain, V., Roy, G., & Chakraborty, A. (2022). AI-driven banking services: the next frontier for a personalised experience in the emerging market. International Journal of Bank Marketing, 40(6), 1248–1271.

Singh, V., Chen, S. S., Singhania, M., Nanavati, B., & Gupta, A. (2022). How are reinforcement learning and deep learning algorithms used for big data-based decision making in financial industries–A review and research agenda. International Journal of Information Management Data Insights, 2(2), Article 100094.

Singh, V., Nanavati, B., Kar, A. K., & Gupta, A. (2022). How to maximize clicks for display advertisement in digital marketing? A reinforcement learning approach. Information Systems Frontiers, 1–18. https://doi.org/10.1007/s10796-022-10314-0

Stahl, B. C. (2021). Artificial Intelligence for a Better Future: An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies, SpringerBriefs in Research and Innovation Governance. Springer International Publishing. https://doi.org/10.1007/978-3-030-69978-9

Stokel-Walker, C. J. N. (2023). ChatGPT listed as author on research papers: many scientists disapprove. Nature, 613, 620–621. https://doi.org/10.1038/d41586-023-00107-z

Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36 (2), 368–383.

Tércio Pereira, P., Limberger, F., Minasi, S. M., & Buhalis, D. (2022). New Insights into Consumers’ Intention to Continue Using Chatbots in the Tourism Context. Journal of Quality Assurance in Hospitality & Tourism. https://doi.org/10.1080/1528008X.2022.2136817

UK Government. (2021). National AI Strategy. Available at https://www.gov.uk/government/publications/national-ai-strategy

Van Dis, E. A. M., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. (2023). ChatGPT: five priorities for research. Nature, 614, 224–226. https://doi.org/10.1038/d41586-023-00288-7

Van Noorden, R. (2022). How language-generation AIs could transform science, 21–21 Nature, 605. https://doi.org/10.1038/d41586-022-01191-3

Vassilakopoulou, P., Haug, A., Salvesen, L. M., & Pappas, I. O. (2023). Developing Human/AI interactions for chat-based-customer-services: lessons learned from the Norwegian Government. European Journal of Information Systems, 32(1), 10–22.

Winikoff, M., Cranefield, J., Li, J., Doyle, C., & Richter, A. (2021). The Advent of Digital Productivity Assistants: The Case of Microsoft MyAnalytics. In IEEE Annual Hawaii International Conference on System Sciences (HICSS) 2021.

Wirtz, J., & Zeithaml, V. (2018). Cost-effective service excellence. Journal of the Academy of Marketing Science, 46(1), 59–80.

Wirtz, J., Kunz, W. H., Hartley, N., & Tarbit, J. (2023). Corporate digital responsibility in service firms and their ecosystems. Journal of Service Research, published Online first. https://doi.org/10.1177/10946705221130467

Zhang, L., Pentina, I., & Fan, Y. (2021). Who do you choose? Comparing perceptions of human vs robo-advisor in the context of financial services. Journal of Services Marketing, 35(5), 634–646.

Zhang, Z., Hummel, J. T., Nandhakumar, J., & Waardenburg, L. (2020). Addressing the key challenges of developing machine learning AI systems for knowledge-intensive work. MIS Quarterly Executive, 19(4), 221–238.

Downloads

Published

2023-09-15

Issue

Section

Managerial Aspects of European Integration