Artificial Intelligence (AI) Adoption as Marketing Tools among Micro, Small, and Medium Enterprises (MSMEs) in Indonesia
Abstract
Despite MSMEs' crucial role in Indonesia's economy, their utilization of artificial intelligence (AI) remains restricted. This paper investigates the adoption of artificial intelligence (AI) among micro, small, and medium enterprises (MSMEs) in Indonesia, providing a comprehensive analysis of the difficulties and potential advantages. AI implementation is essential for these businesses because it may significantly enhance economic growth through improved productivity, cost reduction, and increased competitiveness. Furthermore, AI facilitates the decision-making process and fosters data-based innovation. The study investigates the correlation between competitive pressure, top management commitment, staff adaptability, perceived utility, and simplicity of use in the adoption of artificial intelligence (AI) among micro, small, and medium enterprises (MSMEs) in Indonesia. By addressing these gaps, we can enhance our comprehension of how MSMEs can utilize AI adoption as a marketing tool, thereby fostering their growth and success. The results emphasize the significance of top management commitment (TMC), employee adaptability (EA), perceived usefulness (PU), and perceived ease of use (PEOU) in encouraging the adoption of AI among micro, small, and medium enterprises (MSMEs) in Indonesia.
Keywords
Full Text:
PDFReferences
Bettoni, A., Matteri, D., Montini, E., Gladysz, B., & Carpanzano, E. (2021). An AI adoption model for SMEs: A conceptual framework. IFAC-PapersOnLine, 54(1), 702–708. https://doi.org/10.1016/j.ifacol.2021.08.082
Daoud, L., Marei, A., Al-Jabaly, S. M., & Aldaas, A. A. (2021). Moderating the role of top management commitment in usage of computer-assisted auditing techniques. Accounting, 7(2), 457–468. https://doi.org/10.5267/j.ac.2020.11.005
Hair, Joseph. F., & et al., et al. (2010). Multivariate Data Analysis. Pearson Education International.
Haleem, A., Javaid, M., Asim Qadri, M., Pratap Singh, R., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. In International Journal of Intelligent Networks (Vol. 3, pp. 119–132). KeAi Communications Co. https://doi.org/10.1016/j.ijin.2022.08.005
Keegan, B. J., Canhoto, A. I., & Yen, D. A. wan. (2022). Power negotiation on the tango dancefloor: The adoption of AI in B2B marketing. Industrial Marketing Management, 100, 36–48. https://doi.org/10.1016/j.indmarman.2021.11.001
Kumar, A., Mani, V., Jain, V., Gupta, H., & Venkatesh, V. G. (2023). Managing healthcare supply chain through artificial intelligence (AI): A study of critical success factors. Computers and Industrial Engineering, 175. https://doi.org/10.1016/j.cie.2022.108815
Lada, S., Chekima, B., Karim, Mohd. R. A., Fabeil, N. F., Ayub, M. S., Amirul, S. M., Ansar, R., Bouteraa, M., Fook, L. M., & Zaki, H. O. (2023). Determining Factors Related to Artificial Intelligence (AI) Adoption Among Malaysia’s Small and Medium-Sized Businesses. Journal of Open Innovation: Technology, Market, and Complexity, 100144. https://doi.org/10.1016/j.joitmc.2023.100144
Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning. University of Illinois Press.
Rasheed, H. M. W., Chen, Y., Khizar, H. M. U., & Safeer, A. A. (2023). Understanding the factors affecting AI services adoption in hospitality: The role of behavioral reasons and emotional intelligence. Heliyon, 9(6). https://doi.org/10.1016/j.heliyon.2023.e16968
Regona, M., Yigitcanlar, T., Xia, B., & Li, R. Y. M. (2022). Opportunities and Adoption Challenges of AI in the Construction Industry: A PRISMA Review. Journal of Open Innovation: Technology, Market, and Complexity, 8(1). https://doi.org/10.3390/joitmc8010045
Sipola, J., Saunila, M., & Ukko, J. (2023). Adopting artificial intelligence in sustainable business. Journal of Cleaner Production, 426, 139197. https://doi.org/10.1016/j.jclepro.2023.139197
Ulrich, P., & Frank, V. (2021). Relevance and adoption of AI technologies in German SMEs - Results from survey-based research. Procedia Computer Science, 192, 2152–2159. https://doi.org/10.1016/j.procs.2021.08.228
Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1). https://doi.org/10.1016/j.jjimei.2020.100002
DOI: http://dx.doi.org/10.12962/j24433527.v17i1.20520
Refbacks
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 4.0 International License.