FACTORS EFFECTING ADOPTION OF DIGITAL MARKETING BY MICRO ENTREPRENEURS OF RURAL SOUTH ODISHA.
Abstract
Digital Marketing has emerged as one of the greatest tools of marketing in the modern world. Not only it has brought down the marketing expenses through its efficiency but has also helped the entrepreneurs in engaging with the customers more effectively. It also helps in collecting and analysing the data on customers behaviour so that the entrepreneurs can make more efficient strategies for attainment of their business goals. (Sheoliha et al 2023). Various studies have been done on use of Digital marketing by entrepreneurs. However, the utilisation of Digital marketing options by rural micro entrepreneurs of India is still a field to be explored. Purpose of study: Presented study aims at Identifying the factors effecting the adoption of Digital Marketing by micro entrepreneurs of rural South Odisha. Methodology used: The study employes the combination of UTAUT and TOE model. It is done based on the primary data collected from 386 respondents from the region. The data is then subjected to Exploratory factor analysis for factor extraction and regression analysis for hypothesis testing. Outcome: The outcome of the study suggests that the factors like Performance expectancy, Effort expectancy, Technological factors, Organisational factors, and Environmental factors impact the adoption of Digital marketing by micro entrepreneurs of rural South Odisha.
Keyword : Digital marketing, micro entrepreneurs, rural entrepreneurs, rural micro entrepreneurs, rural micro entrepreneurs of India, South Odisha.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
1. Abdallah, N.; Abdallah, O.; Bohra, O. Factors affecting mobile learning acceptance in higher education: An empirical study. Int. J. Adv. Comput. Sci. Appl. 2021, 12, 664–671. [CrossRef] 2. Ahmad, M.O.; Markkula, J.; Oivo, M. Factors affecting e-government adoption in Pakistan: A citizen’s perspective. Transform. Gov. People Process. Policy 2013, 7, 225–239. 3. Ahmad, S. R., Prasad, K. D. V., Bhakuni, S., Hedau, A., Narayan, P. S., & Parameswari, P. (2023). The role and relation of emotional intelligence with work-life balance for working women in job stress. The Scientific Temper, 14(01), 233-237. 4. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [CrossRef] 5. Ajzen, I.; Madden, T.J. Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. J. Exp. Soc. Psychol. 1986, 22, 453–474. [CrossRef] 6. Alatawi, F. M. H., Dwivedi, Y. K., & Williams, M. D. (2013). Developing a conceptual model for investigating adoption of knowledge management system in Saudi Arabian public sector. International Journal of Business Information Systems, 14(2), 135-163. 7. Alraja, M.N.; Hammami, S.; Chikhi, B.; Fekir, S. The influence of effort and performance expectancy on employees to adopt e-government: Evidence from oman. Int. Rev. Manag. Mark. 2016, 6, 930–934. Appl. Geogr. 52, 25–33. 8. Baker, J. (2011) ‘Technology-organization-environment framework’, in Dwivedi, Y.K., Wade, M.R. and Schneberger, S.L. (Eds.): Information Systems Theory: Explaining and Predicting Our Digital Society, Vol. 1, pp.231–245. 9. Bala, M. and Verma, D. (2018). A critical review of digital marketing. International Journal of Management, IT and Engineering, 8(10). ISSN: 2249-0558 Impact Factor: 7.119. 10. Brereton RG. ANOVA tables and statistical significance of models. Journal of Chemometrics. 2019; 33:e3019. https://doi.org/10.1002/cem.3019 11. Chan, A.P.C.; Lam, P.T.I.; Chan, D.W.M.; Cheung, E.; Ke, Y. Critical Success Factors for PPPs in InfrastructureDevelopments: Chinese Perspective. J. Construct. Eng. Manag. 2010, 136, 484–494. [CrossRef] 12. Chao, C.-M. Factors determining the behavioral intention to use mobile learning: An application and extension of the utaut model. Front. Psychol. 2019, 10, 1652. [CrossRef] [PubMed] 13. Chau, P.Y.K and Tam, K.Y. (1997) ‘Factors affecting the adoption of open systems: an exploratory study’, MIS Quarterly, Vol. 21, No. 1, pp.1–24. 14. Chong Sandy., & B,Rameseshan. (2005).Factors influencing the adoption of electronic commerce among the small and medium sized enterprises in Australia. Journal of marketing & Communication , Volume 1 (Issue 2). 15. Davis, F.D. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 1989, 319–340. [CrossRef] 16. Davis, F.D.; Bagozzi, R.P.; Warshaw, P.R. User acceptance of computer technology: A comparison of two theoretical models. Manag. Sci. 1989, 35, 982–1003. [CrossRef] 17. Dhanlaxmi Bank. (2010, December 1). In focus. https://www.dhanbank.com/pdf/reports/InFocus-December%201,%202010.pdf 18. Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information systems research, 17(1), 61-80. 19. Eid, R.; El-Gohary, H. The impact of E-marketing use on small business enterprises’ marketing success. Serv. Ind. J. 2013, 33,31–50. [CrossRef] 20. Exploding Topics. (n.d.). Countries with the most internet users in 2023. https://explodingtopics.com/blog/countries-internet-users 21. Eze, S. C., Chinedu-Eze, V. C., Okike, C. K., & Bello, A. O. (2020). Critical factors influencing the adoption of digital marketing devices by service-oriented micro-businesses in Nigeria: A thematic analysis approach. Humanities and Social Sciences Communications, 7(1), 1-14. 22. Fachrurazi, F., Zarkasi, Z., Maulida, S., Hanis, R., & Yusuf, M. (2022). Ingcreasing micro small medium enteprises activity entrepreneurial capacity in the field of digital marketing. Jurnal Ekonomi, 11(03), 1653-1660. 23. Fichman, R. G., & Kemerer, C. F. (1997). Object technology and reuse: Lessons from early adopters. Computer, 30(10), 47-59. 24. Fichman, R. G., & Kemerer, C. F. (1997). The assimilation of software process innovations: An organizational learning perspective. Management science, 43(10), 1345-1363. 25. Field, A. Discovering Statistics Using IBM SPSS Statistics; Sage: Newcastle upon Tyne, UK, 2013 26. Fishbein, M.; Ajzen, I. Misconceptions about the fishbein model: Reflections on a study by songer-nocks. J. Exp. Soc. Psychol. 1976, 12, 579–584. [CrossRef] 27. Ghalandari, K. The effect of performance expectancy, effort expectancy, social influence and facilitating conditions on acceptance of e-banking services in Iran: The moderating role of age and gender. Middle-East J. Sci. Res. 2012, 12, 801–807. 28. Globerman, S. (1975) ‘Technological diffusion in the Canadian tool and die industry’, Review of Economics and Statistics, Vol. 57, No. 4, pp.428–434. 29. Goel, R., Veluri, K. K., & Mishra, S. (2024). Understanding The Use Of Digital Marketing By Rural Micro Entrepreneurs Of India: A Systematic Literature Review. Educational Administration: Theory and Practice, 30(5), 7629-7638. 30. Gouda, S. K., Patro, Y. S. S., & Mishra, S. (2024). A Study of E-recruitment technology adoption in India. Educational Administration: Theory and Practice, 30(5), 11804-11812. 31. Grover, V. (1993) ‘An empirically derived model for the adoption of customer-based interorganizational systems’, Decision Sciences, Vol. 24, No. 3, pp.603–640. 32. Guner, H.; Acarturk, C. The use and acceptance of ict by senior citizens: A comparison of technology acceptance model tam) for elderly and young adults. Univers. Access Inf. Soc. 2020, 19, 311–330. [CrossRef] 33. H.C. Kimaro and J.L. Nhampossa, "Analyzing the Problem of Unsustainable Health Information Systems in Less-Developed Economies: Case Studies From Tanzania and Mozambique", Information Technology for Development, vol. 11, no. 3, pp. 273-298, 2005. 34. Hardill, I.; MacDonald, S. Skilled international migration: The experience of nurses in the uk. Reg. Stud. 2000, 34, 681–692. [CrossRef] 35. He, W.; Wang, F.-K.; Zha, S. Enhancing social media competitiveness of small businesses: Insights from small pizzerias. New Rev.Hypermedia Multimed. 2014, 20, 225–250. [CrossRef] 36. Hedau, A. (2020). Value Investing: Evidence From Listed Construction And Infrastucture Sector Companies In India. Romanian Economic and Business Review, 15(4), 104-114. 37. Hedau, A. (2024). Impact of Macroeconomic Variables on the Performance of the Indian stock market. Journal of Informatics Education and Research, 4(1). 38. Hedau, A., & Joshi, V. K. (2015). Under Pricing Anomaly –Empirical Evidence from Indian Capital Market. International Journal of Innovative Research and Development. 39. Hedau, A., & Mishra, S. (2023). EQUITY PRICE DETERMINANTS OF INDIA'S NIFTY NEXT 50 INDEX FIRMS'. Indian Journal of Finance and Banking, 13(2), 14-22. 40. Hogeboom, D.L.; McDermott, R.J.; Perrin, K.; Osman, H.; Bell-Ellison, B.A. Internet use and social networking among middle aged and older adults. Educ. Gerontol. 2010, 36, 93–111. [CrossRef] 41. Iacovou, C., Benbasat, I. and Dexter, A. (1995) ‘Electronic data interchange and small organisations: adoption and impact of technology’, MIS Quarterly, Vol. 19, No. 4, pp.465–485 42. Jongebloed, H., Anderson, K., Winter, N. et al. The digital divide in rural and regional communities: a survey on the use of digital health technology and implications for supporting technology use. BMC Res Notes 17, 90 (2024). https://doi.org/10.1186/s13104-024-06687-x 43. Kamath, R. and Liker, J. (1994) ‘A second look at supplier development’, Harvard Business Review, November–December, pp.154–168. 44. Kano, K., Choi, L. K., subhan Riza, B., & Octavyra, R. D. (2022). Implications of digital marketing strategy the competitive advantages of small businesses in indonesia. Startupreneur Business Digital (SABDA Journal), 1(1), 44-62. 45. Levin, S.G., Levin, S.L. and Meisel, J.B. (1987) ‘A dynamic analysis of the adoption of a new technology: the case of optical scanners’, The Review of Economics and Statistics, Vol. 69, No. 1, pp.12–17 46. Li, Y.Y.; Chen, P.-H.; Chew, D.A.S.; Teo, C.C.; Ding, R.G. Critical Project Management Factors of AEC Firms forDelivering Green Building Projects in Singapore. J. Construct.Eng. Manag. 2011, 137, 1153–1163. [CrossRef] 47. Maiga, G.; Namagembe, F. Predicting adoption of mhealth technology in resource constrained environments. In Proceedings of the 2014 IST-Africa Conference Proceedings, Pointe aux Piments, Mauritius, 7–9 May 2014; pp. 1–12. 48. Mansfield, E. (1968) Industrial Research and Technological Innovation: An Economic Analysis, Norton, New York. 49. Mansfield, E., Rapoport, J., Romeo, A., Villani, E., Wagner, S. and Husic, F. (1977) The Production and Application of New Industrial Technology, Norton, New York. 50. Maranguni´c, N.; Grani´c, A. Technology acceptance model: A literature review from 1986 to 2013. Univers. Access Inf. Soc. 2015, 14, 81–95. [CrossRef] 51. Mcmanus, P.; Standing, C.; Zanoli, R. A preliminary Laddering Analysis on Mobile Services Usage; McGraw Hill: New York, NY,USA, 2009. 52. Miloševi´c, I.; Živkovi´c, D.; Manasijevi´c, D.; Nikoli´c, D. The effects of the intended behavior of students in the use of m-learning. Comput. Hum. Behav. 2015, 51, 207–215. [CrossRef] 53. Milosevic, D.; Andrei, S.; Vishny, R.W. A survey of corporate governance. J. Financ. 2015, 52, 737–783. 54. Ministry of Micro, Small & Medium Enterprises. (n.d.). Know about MSME. https://msme.gov.in/know-about-msme 55. Mishra, S., & Mohanty, M. (2009). Financing and Risk Management Techniques in Green Field Projects Under Public, Private Partnership (PPP) Model: A Case Study Of Rajiv Gandhi International Airport (RGIA) Ltd, Hyderabad. Interscience Management Review, 22-31. 56. Nhuvira, C.E.; Dorasamy, N. Adapt Or Die: The Adoption of Digital Marketing by Fashion SMMES in South Africa. J. Manag. Inf.Decis. Sci. 2021, 24, 1–16. 57. Nikolopoulou, K.; Gialamas, V.; Lavidas, K. Habit, hedonic motivation, performance expectancy and technological pedagogical knowledge affect teachers’ intention to use mobile internet. Comput. Educ. Open 2021, 2, 100041. [CrossRef] 58. Norusis, M. SPSS 16.0 Advanced Statistical Procedures Companion; Prentice Hall Press: Upper Saddle River, NJ,USA, 2008. 59. Nuseira, M.T.; Aljumahb, A. Digital marketing adoption influenced by relative advantage and competitive industry: A UAE tourism case study. Marketing 2020, 11, 23–37. 60. Nyembezi, N.; Bayaga, A. Performance expectancy and usage of information systems and technology: Cloud computing (PEUISTCC). Int. J. Educ. Sci. 2014, 7, 579–586. 61. Ofcom, 2016. Connected Nations Report 2016. Available at: https://www.ofcom.org.uk/ 62. Olaposi, T O. (2021, January 7). Towards the Development of the Informal Economy: The Case of Street Trading in Ile-Ife, Nigeria. https://scite.ai/reports/10.5772/intechopen.93871 63. Onaolapo, S.; Oyewole, O. Performance expectancy, effort expectancy, and facilitating conditions as factors influencing smart phones use for mobile learning by postgraduate students of the University of Ibadan, Nigeria. Interdiscip. J. e-Ski. Lifelong Learn. 2018, 14, 95–115. [CrossRef] [PubMed] 64. Pandey, N.; Nayal, P.; Rathore, A.S. Digital marketing for B2B organizations: Structured literature review and future research directions. J. Bus. Ind. Mark. 2020, 35, 1191–1204. [CrossRef] 65. Petrovˇciˇc, A.; Petriˇc, G.; Manfreda, K.L. The effect of email invitation elements on response rate in a web survey within an online community. Comput. Hum. Behav. 2016, 56, 320–329. [CrossRef] 66. Philip, L., Cottrill, C., Farrington, J., 2015. Two-Speed Scotland: patterns and implications of the digital divide in contemporary Scotland. Scot. Geogr. J. 131 (3–4), 148–170 67. Philip, L., Cottrill, C., Farrington, J., Williams, F., Ashmore, F., 2017. The digital divide: patterns, policy and options for connecting the final few in rural communities across Great Britain. J. Rural Stud. https://doi.org.10.1016/j.jrurstud.2016.12.002. research-and-data/infrastructure-research/connected-nations-2016. 68. Rees, J., Macaulay, S., & Moffitt, M. (1984). The economic impact of technology services. Cambridge University Press. 69. Riddlesden, D., Singleton, A.D., 2014. Broadband speed equity: a new digital divide 70. Ritz, W.; Wolf, M.; McQuitty, S. Digital marketing adoption and success for small businesses: The application of the do-it-yourself and technology acceptance models. J. Res. Interact. Mark. 2019, 13, 179–203. [CrossRef] 71. Rogers, Everett.M. (1983).Diffusion of Innovations. The free press, Newyork. 72. Sharma, U. and Thakur, K.S. (2020). A Study on digital marketing and its impact on consumers purchase. International Journal of Advanced Science and Technology, 29(3):13096-13110. 73. Sheoliha, N., Hajira, B., Singh, A., Rawat, P., Rawal, P., & Sharma, A. (2023). The Impact of Digital Marketing and Digital Transformation on E-Commerce, Positioning and Brand Promotion. Journal of Informatics Education and Research, 3(2). 74. Smith, A.N.; Fischer, E.; Yongjian, C. How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? J. Interact. Mark. 2012, 26, 102–113. [CrossRef] 75. Solakis, K.; Katsoni, V.; Mahmoud, A.B.; Grigoriou, N. Factors affecting value co-creation through artificial intelligence in tourism: A general literature review. J. Tour. Futures 2022. [CrossRef] 76. Thong, J.Y.L. (1999) ‘An integrated model of information systems adoption in small businesses’, Journal of Management Information Systems, Vol. 15, No. 4, pp.187–214. 77. Tornatzky, L.G. and Fleischer, M. (1990) The Processes of Technological Innovation, Lexington Books, Lexington, Massachusetts. 78. Venkatesh, V.; Morris, M.G.; Davis, G.B.; Davis, F.D. User acceptance of information technology: Toward a unified view. MIS Q. 2003, 27, 425–478. [CrossRef] 79. Venkatesh, V.; Thong, J.Y.; Chan, F.K.; Hu, P.J. Managing citizens’ uncertainty in e-government services: The mediating and moderating roles of transparency and trust. Inf. Syst. Res. 2016, 27, 87–111. [CrossRef] 80. Venkatesh, V.; Thong, J.Y.; Xu, X. Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Q. 2012, 36, 157–178. [CrossRef] 81. Xu, X., Zhang W., and Barkhi, R., 2010. IT infrastructure capabilities and IT project success: a de velopment team perspective. Information Technology and Management, 11(3), pp. 123-142. 82. Yamini, G. and Chand, N. (2020). Online marketing influence on startups and small businesses. International Journal of Scientific Research and Engineering Development, 3(6).