DIGITAL MARKETING ADOPTION AMONG STARTUPS IN INDIA: AN EXPLORATORY STUDY USING S-O-R FRAMEWORK
DOI:
https://doi.org/10.46793/GlasnikDN18.1.031MKeywords:
startups, digital marketing, entrepreneurship, stimuli, facilitator, inhibitor, adoption intentionAbstract
India is right now going through an exciting phase of the entrepreneurial drive where first-generation entrepreneurs are creating startups that are solving issues and challenges faced by customers and creating wealth for themselves. India right now has the third largest number of startups in the World right after USA and China. In a parallel development, we have also seen the meteoric rise of digital marketing which offers to run targeted marketing campaigns that deliver outcomes at optimum costs. Many startups are using digital marketing tools and technologies for business promotions, while many others are refraining from using digital marketing.
This research paper explores digital marketing adoption by startups using the SOR theory. We have used constructs like hedonic values, utilitarian values and environmental stimuli that act either as facilitators or inhibitors to encourage or discourage digital marketing adoption by startups. Our major findings are that environmental stimuli act as a strong facilitator in encouraging the adoption of digital marketing by startups while utilitarian values act as a strong inhibitor in dissuading the adoption of digital marketing. The findings are significant as they will help the policymakers, regulators, incubators, accelerators, venture capitalists and startup promotion councils to understand how startup companies...
References
Andonov, A. D. (2020, September). The Application of Search Engine Optimization in Internet Marketing. In 2020 55th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST) (pp. 37-41). IEEE.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.
Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. Journal of consumer research, 20(4), 644-656.
Bala, M., & Verma, D. (2018). A Critical Review of Digital Marketing. International Journal of Management, IT & Engineering, 8(10), 321-339.
Blakeman, R. (2018). Integrated marketing communication: creative strategy from idea to implementation. Rowman & Littlefield.
Chahal, R., & Chakraborti, J. (2018). Digital Marketing 2.0. Himalaya Publishing House.
Chakraborti, J., Dutta, A., & Jana, B. (2022a). An empirical investigation into why startups resist use of digital marketing. Journal of Content, Community & Communication, 15(8), 69-83.
Chakraborti, J., Dutta, A., & Jana, B. (2022b). Digital marketing adoption among startups in India: A systematic review and bibliometric analysis. Journal of Information and Optimization Sciences, 43(6), 1301-1309.
Chopdar, P. K., & Balakrishnan, J. (2020). Consumers response towards mobile commerce applications: SOR approach. International Journal of Information Management, 53, 102106.
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd Edition). Hillsdale, NJ: Lawrence Earlbaum Associates.
Cutroni, J. (2010). Google Analytics: understanding visitor behavior. “O’Reilly Media, Inc.".
Dastane, D. O. (2020). Impact of digital marketing on online purchase intention: Mediation effect of customer relationship management. Journal of Asian Business Strategy, DOI, 10, 142-158.
Davis, FD (1989). Perceived Usefulness, Perceived Ease of Use, And User Acceptance of Information Technology, MIS Quart, 13(3): 319-340
Fornell, C.G. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.
Fortune India. (2022, February 1). Budget 2022: Eco Survey says India has 83 unicorns worth $278 billion. Fortune India. https://www.fortuneindia.com/budget-2022/budget-2022-eco-survey-says-india-has-83-unicorns-worth-278-billion/106940
Gupta, S. (2020). Digital marketing. McGraw-Hill Education.
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.). Thousand Oaks: Sage.
Khare, A. Influence of hedonic and utilitarian values in determining attitude towards malls: A case of Indian small city consumers. J Retail Leisure Property 9, 429–442 (2011). https://doi.org/10.1057/rlp.2011.6
Kock, N. (2015), “Common method bias in PLS-SEM: a full collinearity assessment approach”,International Journal of E-Collaboration, Vol. 11, pp. 1-10.
Kotane, I., Znotina, D., & Hushko, S. (2019). Assessment of trends in the application of digital marketing. Scientific Journal of Polonia University, 33(2), 28-35.
Kotler, P., & Armstrong, G. (2013). Principles of Marketing. Pearson. (16th Global Edition).
Kotler, P., Kartajaya, H., Setiawan, I. (2017). Marketing 4.0 – Moving from traditional to digital. John Wiley and Sons.
Lawrence, M V. (2022). The Case Study Analysis of Indian Unicorn Start-up Companies. International Journal of Research Publication and Reviews, Vol 3, no 11, pp 1583.
Mehrabian, A., Russell, J.A. (1974). An Approach to Environmental Psychology. MIT Press, Cambridge, MA.
Menon, R., & James, L. (2022). Understanding Startup Valuation and its Impact on Startup Ecosystem. Journal of Business Valuation and Economic Loss Analysis, 17(1), 101-114.
Morgan Stanley. (2022, June 14). Stronger for Longer in Global E-Commerce. https://www.morganstanley.com/ideas/global-ecommerce-growth-forecast-2022
Muthukumaran, A., & Vani, H. (2020). Optimizing the usage of voice assistants for shopping. Indian Journal of Science & Technology, 1343, 4407-4416.
Pal, D., Arpnikanondt, C., Funilkul, S., & Varadarajan, V. (2019, July). User experience with smart voice assistants: the accent perspective. In 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE.
Peng, C & Kim, Y.G. (2014). Application of the Stimuli-Organism-Response (S-O-R) Framework to Online Shopping Behavior, Journal of Internet Commerce, 13:3-4, 159-176, DOI: 10.1080/15332861.2014.944437
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879
Ram, S. and Sheth, J.N. (1989), “Consumer resistance to innovations: the marketing problem and its solutions”, Journal of Consumer Marketing, Vol. 6 No. 2, pp. 5-14.
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2014). Diffusion of innovations (pp. 432-448). Routledge.
Ritz, W, Wolf, M & McQuitty, S. (2019). "Digital marketing adoption and success for small businesses: The application of the do-it-yourself and technology acceptance models", Journal of Research in Interactive Marketing, https://doi.org/10.1108/JRIM-04-2018-0062
Ryan, D., & Jones, C. (2009). Digital marketing: Marketing strategies for engaging the digital generation. London and Philedelphia: Kogan page Ltd.
Sharma, A., Dwivedi, Y., Arya, V., Siddiqui, M. (2021). Does SMS advertising still have relevance to increase consumer purchase intention? A hybrid PLS-SEM-neural network modelling approach. Computers in Human Behavior, Volume 124, 106919, ISSN 0747-5632, https://doi.org/10.1016/j.chb.2021.106919
Soper, D.S. (2022). A-priori Sample Size Calculator for Structural Equation Models [Software]. Available from https://www.danielsoper.com/statcalc
Sriram. (2021, December 31). Your guide to India’s startup unicorns of 2021. Moneycontrol.com. https://www.moneycontrol.com/news/business/startup/your-guide-to-indias-startup-unicorns-of-2021-7876201.html
Talwar, S., Kaur, P., Yadav, R., Bilgihan, A., Dhir, A. (2021). What drives diners' eco-friendly behaviour? The moderating role of planning routine, Journal of Retailing and Consumer Services, Volume 63, 102678, ISSN 0969-6989, https:// doi.org /10.1016 / j.jretconser.2021.102678
Tornatzky, L. and Fleischer, M. (1990). The process of technology innovation, Lexington, MA, Lexington Books.
Vassileva, B. (2017). Marketing 4.0: How technologies transform marketing organization. Óbuda university e-Bulletin, 7(1), 47.
Yang, Y., Pan, B., & Song, H. (2014). Predicting hotel demand using destination marketing organization’s web traffic data. Journal of Travel Research, 53(4), 433-447.
Zimmerman, J. (2012). Using the SOR model to understand the impact of website attributes on the online shopping experience. University of North Texas.
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