AI-Plugged, Digitally-Driven Progress: Exploring AI Adoption in Digital Marketing SMEs via the TOE Framework
Keywords:
Technology–Organization–Environment, framework, Artificial Intelligence, SMEs, Digital MarketingAbstract
Artificial Intelligence (AI) is reshaping digital marketing through hyper-personalized customer engagement, optimized workflows, and sustainable growth. This empirical study identifies determinants of AI adoption in Delhi NCR's digital marketing SMEs—a critical innovation hub in India—using the (TOE) Technology–Organization–Environment framework model. We assess how technological factors (perceived advantages, cost, complexity, compatibility), organizational elements (workforce expertise, leadership support), and environmental forces (client expectations, policy incentives) drive adoption. Business outcomes (operational efficiency, financial growth) were evaluated using Structural Equation Modeling (Smart PLS 4) with data from 250 SMEs (June–August 2024). Results show perceived advantages, compatibility, skilled workforce, client demand, and policy incentives significantly explain 61% of adoption variance (R² = 0.61) and enhance performance. Medium-sized SMEs exhibit stronger advantages-to-adoption linkages than smaller firms.
Downloads
References
1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
2. Alkdour, T., Alkdour, T., Shishakly, R., & Alrawad, M. (2023). Exploring the success factors of smart city adoption via structural equation modeling. Sustainability, 15(22), 15915.
3. Alsheibani, S. A., Messom, C., & Cheung, Y. (2020). Artificial intelligence adoption in Saudi Arabian SMEs: A TOE framework perspective. Journal of Enterprise Information Management, 33(6), 1591–1612.
4. Andries, P., & Stephan, U. (2019). Environmental and organizational factors influencing technology adoption in SMEs. Journal of Small Business Management, 57(4), 1493–1514.
5. Aslam, S., & Jawaid, S. T. (2023). Green banking practices and their impact on financial performance: A study of commercial banks in Pakistan. Environmental Science and Pollution Research, 30(10), 27803–27815.
6. Awa, H. O., & Ojiabo, O. U. (2016). The moderating role of firm size in the relationship between TOE framework and e-commerce adoption. Journal of Enterprise Information Management, 29(5), 705–724.
7. Baabdullah, A. M., Al-Balushi, S. M., & Al-Badi, A. H. (2021). Artificial intelligence adoption in B2B SMEs in Saudi Arabia: An empirical study. Journal of Business & Industrial Marketing, 36(13), 2415–2429.
8. Badghish, S., & Soomro, M. A. (2024). Drivers of AI adoption in Saudi Arabian SMEs: An empirical study. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100160.
9. Chatterjee, S., Kumar, A., Kar, A. K., & Sharma, S. (2021a). The role of artificial intelligence in digital marketing: A systematic literature review. Journal of Business Research, 130, 13–25.
10. Chatterjee, S., Kumar, A., Kar, A. K., & Sharma, S. (2021b). AI adoption in Indian SMEs: An integrated TAM-TOE perspective. Journal of Global Information Management, 29(4), 1–20.
11. Chen, S. C., Chen, P. C., & Chen, Y. C. (2023). Artificial intelligence in hospitality during COVID-19: A TOE framework perspective. International Journal of Hospitality Management, 108, 103380.
12. Das, S., & Kundu, A. (2023). AI readiness in Delhi NCR SMEs: An empirical study using TOE framework. Journal of Small Business and Enterprise Development, 30(5), 897–915.
13. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
14. Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data: A review and future directions. International Journal of Information Management, 48, 107–114.
15. Dutt, A., & Srite, M. (2005). A cultural perspective on technology acceptance. https://core.ac.uk/download/301348254.pdf
16. El-Kassar, A. N., & Li, B. (2019). The impact of leadership on technology adoption in SMEs. Journal of Business Research, 99, 21–30.
17. Ganguly, S. (2023). Blockchain adoption in Indian SMEs: A TOE framework perspective. Journal of Global Information Management, 31(1), 1–20.
18. Gupta, S., & Varma, S. (2024). AI adoption in digital marketing SMEs in Delhi NCR: Challenges and opportunities. Journal of Marketing Analytics, 12(1), 45–60.
19. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.
20. Hao, S., Li, Y., & Zhang, Y. (2020). Factors influencing blockchain adoption in supply chain finance: An empirical study in China. Journal of Enterprise Information Management, 33(5), 1199–1218.
21. Keegan, B. J., Rowley, J., & Kitchen, P. J. (2022). Digital marketing in the age of AI: A systematic literature review. Journal of Business Research, 144, 1–15.
22. Kauffman, R. J., & Walden, E. A. (2001). Economics and electronic commerce: A 10-year survey of scholarly research. Journal of Organizational Computing and Electronic Commerce, 11(2), 109–122.
23. Li, Y., Xu, X., & Zhang, J. (2020). Factors influencing AI adoption in SMEs: A systematic review. Journal of Cleaner Production, 277, 123402.
24. Low, C., Chen, Y., & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management & Data Systems, 111(7), 1006–1023.
25. Malik, A., Sharma, S., & Singh, R. (2021). Digital transformation in Indian SMEs: Challenges and opportunities. Journal of Small Business and Enterprise Development, 28(4), 543–560.
26. Mariani, M., & Kumar, V. (2023). Artificial intelligence in marketing: A systematic review and future research agenda. Journal of Business Research, 158, 113622.
27. Mehta, C., Raman, U., & Arora, P. (2023). Digitalisation and transformations of women’s labour in sanitation work. https://core.ac.uk/download/578921369.pdf
28. Mikalef, P., & Gupta, M. (2021). Artificial intelligence capabilities and firm performance: A TOE framework perspective. Information & Management, 58(8), 103502.
29. Mohamed Jalaldeen, M. R., Abdul Karim, N. S., & Mohamed, N. (2009). Organizational readiness and its contributing factors to adopt KM processes: A conceptual model. https://core.ac.uk/download/300358973.pdf
30. Nawaz, M., Farag, E., & Foster, S. (2025). Public sector transformation in emerging economies: Factors affecting change adoption in Pakistan. Administrative Sciences, 15(4), 126.
31. Nasiri, M., Saunila, M., & Ukko, J. (2021). The impact of digital transformation on firm performance: A systematic review. Journal of Business Research, 132, 1–12.
32. Neumann, O., Schuppan, T., & Krcmar, H. (2023). Artificial intelligence in public organizations: A comparative case study using the TOE framework. Government Information Quarterly, 40(1), 101750.
33. Oliveira, T., Thomas, M., & Ramaprasad, A. (2014). Cloud computing adoption: A TOE framework. Journal of Enterprise Information Management, 27(5), 589–603.
34. Racherla, P., & Hu, C. (2008). A TOE framework for eCRM adoption in hospitality. International Journal of Hospitality Management, 27(3), 377–388.
35. Rana, N. P., Luthra, S., & Dwivedi, Y. K. (2021). Artificial intelligence in marketing: A systematic literature review and future research agenda. Journal of Business Research, 124, 1–15.
36. Rawashdeh, A., Al-Hawari, M. A., & Al-Zyoud, M. (2023). AI-driven accounting automation in SMEs: A TOE framework perspective. Journal of Accounting & Organizational Change, 19(2), 261–278.
37. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
38. Satar, M., & Alarifi, G. (2022). E-business adoption in Saudi Arabian SMEs: A TOE framework perspective. Journal of Enterprise Information Management, 35(6), 1541–1560.
39. Scupola, A. (2009). Internet commerce adoption in SMEs: A TOE framework. Journal of Global Information Management, 17(3), 1–21.
40. Sharma, S., Singh, R., & Malik, A. (2022). Workforce readiness for AI adoption in Indian SMEs. Journal of Organizational Change Management, 35(3), 567–584.
41. Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.
42. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: A unified theory of acceptance and use of technology. MIS Quarterly, 27(3), 425–478.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Dr. Anju
This work is licensed under a Creative Commons Attribution 4.0 International License.
