Skip to main content
SpringerLink
Log in

Adoption of cashless payment systems in the bottom-of-the-pyramid retail supply chains in India: A technology-organization-environment framework perspective

  • Published:
Electronic Commerce Research Aims and scope Submit manuscript

Abstract

We investigate the adoption of cashless payment systems by small retailers and their upstream suppliers (wholesalers, distributors, and manufacturers) serving the bottom-of-the-pyramid customers in India. We use the Technology-Organization-Environment framework to hypothesize how relative advantage, perceived barriers, firm size, firm scope, and competition influence the adoption of cashless payment systems. We collected data from 392 small retailers and 269 upstream suppliers from urban, semi-urban, and rural India. The results indicate that perceived barriers, firm scope, firm size, and competition influence the adoption of cashless payment systems. Upon further investigation, we found that all five factors influence retailers’ adoption of cashless payment systems, but only firm scope and competition are significantly related to adoption for upstream suppliers. These results highlight that the factors influencing the adoption of cashless payment systems may also depend on supply chain position. We discuss the theoretical and practical implications of these results. We also validate the findings from our quantitative analysis by presenting excerpts from interviews with the merchants.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. We use the term merchants to include retailers, wholesalers, distributors, and manufacturers.

  2. Aadhar is a unique identification number similar to the Social Security Number in the US.

  3. Districts in India are equivalent to Counties in the US. They have a governing body that eventually reports to the state government.

  4. Reserve Bank of India (RBI) is equivalent to Federal Reserve and it classifies various districts in India based on MPCE.

  5. Typically, kirana stores stock the following categories of products: Produce (fruits & vegetables); Packaged foods; Drinks & Beverages; Dairy; Non-Food cosmetics; Cooking essentials and Spices.

  6. IMPS is Immediate payment service that facilitates inter-bank electronic funds transfer that can be initiated on a mobile phone.

  7. We thank the reviewer for suggesting we include the alternate specification in the paper. It adds to the insights gained from our original specification.

References

  1. Garcia-Swartz, D. D., Hahn, R. W., & Layne-Farrar, A. (2006). The move toward a cashless society: A closer look at payment instrument economics. Review of Network Economics, 5(2), 199–228.

  2. Capgemini. (2019). World payments report.

  3. Ramya, N., Sivasakthi, D., & Nandhini, M. (2017). Cashless transaction: Modes, advantages and disadvantages. International Journal of Applied Research, 3(1), 122–125.

    Google Scholar 

  4. Sarkar, M. P. (2019). Literature review on adoption of digital payment system. Global Journal of Enterprise Information System, 11(3), 62–67.

    Google Scholar 

  5. Mohapatra, S. (2017). Unified payment interface (UPI): A cashless Indian e-transaction process. International Journal of Applied Science and Engineering, 5(1), 29.

    Article  Google Scholar 

  6. Merritt, C. (2011). Mobile money transfer services: The next phase in the evolution of person-to-person payments. Journal of Payments Strategy & Systems, 5(2), 143–160.

    Google Scholar 

  7. Khare, A., Pandey, S. K., & Bhardwaj, P. (2014). Impact of culture, cosmopolitanism, and price on local store loyalty: An empirical study from India. Journal of International Consumer Marketing, 26(3), 185–200.

    Article  Google Scholar 

  8. Narula, S. A., & Garg, A. (2011). Promotional strategies for the rollout of rural retail store: A case of Triveni Khushali Bazaar. IUP Journal of Agricultural Economics, 8(4), 58.

    Google Scholar 

  9. Roy, K. (2012). The co-existence of kirana stores and supermarkets: A potential possibility? Journal of Marketing & Communication, 7(3), 64–67.

    Google Scholar 

  10. Sarkar, D. N., Kundu, K., & Chaudhuri, H. R. (2016). Constructing a conceptual model of purchase behaviour of village shopkeepers–A study of small rural retailers in Eastern India. Journal of Retailing and Consumer Services, 28, 1–16.

    Article  Google Scholar 

  11. Sharma, H., Lowalekar, V., & Jain, R. (2013). Buyers’ perception of important retail store attributes in Indian traditional grocery setting. International Journal of Marketing & Business Communication, 2(2), 44–52.

    Google Scholar 

  12. Singh, K. (2014). Retail sector in India: Present scenario, emerging opportunities and challenges. Journal of Business and Management, 16(4), 72–81.

    Google Scholar 

  13. Adjei, M. T., Griffith, D. A., & Noble, S. M. (2009). When do relationships pay off for small retailers? Exploring targets and contexts to understand the value of relationship marketing. Journal of Retailing, 85(4), 493–501.

    Article  Google Scholar 

  14. Viswanathan, M., Rosa, J. A., & Ruth, J. A. (2010). Exchanges in marketing systems: The case of subsistence consumer–merchants in Chennai. India. Journal of Marketing, 74(3), 1–17.

    Article  Google Scholar 

  15. Pandey, S., Khare, A., & Bhardwaj, P. (2015). Antecedents to local store loyalty: Influence of culture, cosmopolitanism and price. International Journal of Retail & Distribution Management, 43(1), 5–25.

  16. Prahalad, C. K. (2012). Bottom of the pyramid as a source of breakthrough innovations. Journal of Product Innovation Management, 29(1), 6–12.

    Article  Google Scholar 

  17. Kemp, R. (2013). Mobile payments: Current and emerging regulatory and contracting issues. Computer Law & Security Review, 29(2), 175–179.

    Article  Google Scholar 

  18. Deutsche Bundesbank. (2017). Payment behaviour in Germany in 2017.

  19. Valletti, T., & Wu, J. (2020). Consumer profiling with data requirements: Structure and policy implications. Production and Operations Management, 29(2), 309–329.

    Article  Google Scholar 

  20. Cardinali, M. G., & Bellini, S. (2014). Interformat competition in the grocery retailing. Journal of Retailing and Consumer Services, 21(4), 438–448.

    Article  Google Scholar 

  21. Kumar, S., Lim, W. M., Pandey, N., & Christopher Westland, J. (2021). 20 years of electronic commerce research. Electronic Commerce Research, 21, 1–40.

    Article  Google Scholar 

  22. Kumar, S., Xiao, J. J., Pattnaik, D., Lim, W. M., & Rasul, T. (2022). Past, present and future of bank marketing: A bibliometric analysis of International Journal of Bank Marketing (1983–2020). International Journal of Bank Marketing, 40(2), 341–383.

    Article  Google Scholar 

  23. Khan, A. N., & Ali, A. (2018). Factors affecting retailer’s adoption of mobile payment systems: A SEM-neural network modeling approach. Wireless Personal Communications, 103(3), 2529–2551. https://doi.org/10.1007/s11277-018-5945-5

    Article  Google Scholar 

  24. Azmat, F., Lim, W. M., Moyeen, A., Voola, R., & Gupta, G. (2023). Convergence of business, innovation, and sustainability at the tipping point of the sustainable development goals. Journal of Business Research, 167, 114170.

    Article  Google Scholar 

  25. Lim, W. M. (2022). The sustainability pyramid: A hierarchical approach to greater sustainability and the United Nations Sustainable Development Goals with implications for marketing theory, practice, and public policy. Australasian Marketing Journal, 30(2), 142–150.

    Article  Google Scholar 

  26. Tushman, M. L., & Anderson, P. (1986). Technological discontinuities and organizational environments. Administrative Science Quarterly, 31(3), 439–465.

    Article  Google Scholar 

  27. Baker, J. (2012). The technology-organization-environment framework. In Y. K. Dwivedi, M. R. Wade, & S. L. Schneberger (Eds.), Information systems theory: Explaining and predicting our digital society (Vol. 1, p. 461). Springer Science & Business Media LLC.

  28. Goswami, P., & Mishra, M. S. (2009). Would Indian consumers move from kirana stores to organized retailers when shopping for groceries? Asia Pacific Journal of Marketing and Logistics, 21(1), 127–143.

    Article  Google Scholar 

  29. Ramakrishnan, K. (2010). The competitive response of small, independent retailers to organized retail: Study in an emerging economy. Journal of Retailing and Consumer Services, 17(4), 251–258.

    Article  Google Scholar 

  30. Zameer, A., & Mukherjee, D. (2011). Food and grocery retail: Patronage behavior of Indian urban consumers. South Asian Journal of Management, 18(1), 119–148.

    Google Scholar 

  31. Maruyama, M., & Trung, L. V. (2007). Traditional bazaar or supermarkets: A probit analysis of affluent consumer perceptions in Hanoi. International Review of Retail, Distribution and Consumer Research, 17(3), 233–252.

    Google Scholar 

  32. D’Andrea, G., Lopez-Aleman, B., & Stengel, A. (2006). Why small retailers endure in Latin America. International Journal of Retail & Distribution Management, 34(3), 661–673.

    Article  Google Scholar 

  33. Coca-Stefaniak, J. A., Parker, C., & Rees, P. (2010). Localisation as a marketing strategy for small retailers. International Journal of Retail & Distribution Management, 38, 677.

    Article  Google Scholar 

  34. Chung, J. (2014). Does small retailer market orientation matter for long-term oriented relationships with suppliers? Journal of Small Business Management, 52(4), 790–807.

    Article  Google Scholar 

  35. Saini, G. K., & Sahay, A. (2014). Comparing retail formats in an emerging market. Journal of Indian Business Research, 6, 48.

    Article  Google Scholar 

  36. Prasad, C. J., & Aryasri, A. R. (2011). Effect of shopper attributes on retail format choice behaviour for food and grocery retailing in India. International Journal of Retail & Distribution Management, 39, 68.

    Article  Google Scholar 

  37. Alshamaila, Y., Papagiannidis, S., & Li, F. (2013). Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework. Journal of Enterprise Information Management, 26(3), 250–275. https://doi.org/10.1108/17410391311325225

    Article  Google Scholar 

  38. Oliveira, T., & Fraga Martins, M. (2011). Literature review of information technology adoption models at firm level. The Electronic Journal Information Systems Evaluation, 14, 110.

    Google Scholar 

  39. Mkansi, M. (2022). E-business adoption costs and strategies for retail micro businesses. Electronic Commerce Research (Vol. 22). Springer US. https://doi.org/10.1007/s10660-020-09448-7

  40. Tornatzky, L. G., & Fleischer, M. (1990). The process of technology innovation. Lexington Books.

    Google Scholar 

  41. Rogers, E. M., Singhal, A., & Quinlan, M. M. (1995). Diffusion of innovations. An Integrated Approach to Communication Theory and Research (3rd ed.). https://doi.org/10.4324/9780203710753-35

  42. Lim, W. M. (2018). Dialectic antidotes to critics of the technology acceptance model: Conceptual, methodological, and replication treatments for behavioural modelling in technology-mediated environments. Australasian Journal of Information Systems, 22, 1–11. https://doi.org/10.3127/ajis.v22i0.1651

    Article  Google Scholar 

  43. Wen, K. W., & Chen, Y. (2010). E-business value creation in Small and Medium Enterprises: A US study using the TOE framework. International Journal of Electronic Business, 8(1), 80.

    Article  Google Scholar 

  44. Sila, I. (2013). Factors affecting the adoption of B2B e-commerce technologies. Electronic Commerce Research, 13(2), 199–236. https://doi.org/10.1007/S10660-013-9110-7/TABLES/9

    Article  Google Scholar 

  45. Mkansi, M., & Nsakanda, A. L. (2023). Mobile application e-grocery retail adoption challenges and coping strategies: A South African small and medium enterprises’ perspective. Electronic Commerce Research, 1–46. https://doi.org/10.1007/S10660-023-09698-1/FIGURES/4

  46. Lola, I., & Bakeev, M. (2021). What determines the differentiation in the e-commerce adoption by consumers: Evidence from Russia. Electronic Commerce Research, 23(2), 1143–1159. https://doi.org/10.1007/s10660-021-09507-7

    Article  Google Scholar 

  47. Gangwar, H., Date, H., & Raoot, A. D. (2014). Review on IT adoption: Insights from recent technologies. Journal of Enterprise Information Management, 27(4), 488–502.

    Article  Google Scholar 

  48. Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14(5), 265–284. https://doi.org/10.1016/j.elerap.2015.07.006

    Article  Google Scholar 

  49. Grandon, E. E., & Pearson, J. M. (2004). Electronic commerce adoption: An empirical study of small and medium US businesses. Information and Management, 42(1), 197–216. https://doi.org/10.1016/j.im.2003.12.010

    Article  Google Scholar 

  50. Chau, P. Y. K., & Tam, K. Y. (1997). Factors affecting the adoption of open systems: An exploratory study. MIS Quarterly: Management Information Systems, 21(1), 1–20.

    Article  Google Scholar 

  51. Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega, 27(4), 467–484. https://doi.org/10.1016/S0305-0483(98)00071-1

    Article  Google Scholar 

  52. Mallat, N., & Tuunainen, V. K. (2008). Exploring merchant adoption of mobile payment systems: An empirical study. e-Service Journal, 6(2), 24. https://doi.org/10.2979/esj.2008.6.2.24

  53. Gurbaxani, V., & Whang, S. (1991). The impact of information systems on organisations and markets. Communications of the ACM, 34(1), 59–73.

    Article  Google Scholar 

  54. Brynjolfsson, E., Malone, T. W., Gurbaxani, V., & Kambil, A. (1994). Does information technology lead to smaller firms? Management science, 40(12), 1628–1644.

    Article  Google Scholar 

  55. Pan, M.-J., & Jang, W.-Y. (2008). Taiwan’s Communications Industry. Journal of Computer Information Systems, 48(3), 94–102. https://doi.org/10.1080/08874417.2008.11646025

    Article  Google Scholar 

  56. Ramdani, B., Kawalek, P., & Lorenzo, O. (2009). Predicting SMEs’ adoption of enterprise systems. Journal of Enterprise Information Management, 22, 10–24. https://doi.org/10.1108/17410390910922796

    Article  Google Scholar 

  57. Senyo, P. K., Effah, J., & Addae, E. (2016). Preliminary insight into cloud computing adoption in a developing country. Journal of Enterprise Information Management, 29(4), 505–524. https://doi.org/10.1108/JEIM-09-2014-0094

    Article  Google Scholar 

  58. Zhu, K., Kraemer, K., Xu, S., & Zhu, K. (2003). Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors. European Journal of Information Systems, 12, 251–268. https://doi.org/10.1057/palgrave.ejis.3000475

    Article  Google Scholar 

  59. Xia, Y., & Zhang, G. P. (2010). The impact of the online channel on retailers’ performances: An empirical evaluation. Decision Sciences, 41(3), 517–546. https://doi.org/10.1111/j.1540-5915.2010.00279.x

    Article  Google Scholar 

  60. Bollweg, L., Siepermann, M., Lackes, R., & Weber, P. (2016). Digitalization of local Owner Operated Retail Outlets: The role of the perception of competition and customer expectations. aisel.aisnet.org.

  61. Zhu, K., Kraemer, K. L., & Xu, S. (2006). The process of innovation assimilation by firms in different countries: A technology diffusion perspective on e-business. Management Science, 52(10), 1557–1576. https://doi.org/10.1287/mnsc.1050.0487

    Article  Google Scholar 

  62. Hsu, P. F., Ray, S., & Li-Hsieh, Y. Y. (2014). Examining cloud computing adoption intention, pricing mechanism, and deployment model. International Journal of Information Management, 34(4), 474–488. https://doi.org/10.1016/j.ijinfomgt.2014.04.006

    Article  Google Scholar 

  63. McFadyen, E. (1987). Retailers’ attitudes to EFTPoS. Retail and Distribution Management, 15(4), 19–20.

    Article  Google Scholar 

  64. Weber, M. M., & Kantamneni, S. P. (2002). POS and EDI in retailing: An examination of underlying benefits and barriers. Supply Chain Management, 7(5), 311–317.

    Article  Google Scholar 

  65. Grover, V. (1993). An empirically derived model for the adoption of customer-based interorganizational systems. Decision Sciences, 24(3), 603–640.

    Article  Google Scholar 

  66. BCG. (2020). Digital payments 2020: The making of a $500 billion ecosystem in India.

  67. Franciska, M. A., & Sahayaselvi, S. (2017). An overview on digital library. International journal of research, 4(13), 2101–2111.

    Google Scholar 

  68. Awa, H. O., & Ojiabo, O. U. (2016). A model of adoption determinants of ERP within T-O-E framework. Information Technology and People, 29(4), 901–930. https://doi.org/10.1108/ITP-03-2015-0068

    Article  Google Scholar 

  69. Dewan, S., Michael, S. C., & Min, C.-K. (1998). Information systems research firm characteristics and investments in information technology: Scale and scope effects firm characteristics and investments in information technology: Scale and scope effects. Information Systems Research, 9(3), 219. https://doi.org/10.1287/isre.9.3.219

    Article  Google Scholar 

  70. Zhu, K., & Kraemer, K. L. (2002). e-Commerce metrics for net-enhanced organizations: Assessing the value of e-commerce to firm performance in the manufacturing sector. Information Systems Research, 13(3), 275–295. https://doi.org/10.1287/isre.13.3.275.82

    Article  Google Scholar 

  71. Zhu, K., Kraemer, K. L., & Dedrick, J. (2004). Information technology payoff in e-business environments: An international perspective on value creation of e-business in the financial services industry. Journal of Management Information Systems, 21(1), 17–54. https://doi.org/10.1080/07421222.2004.11045797

    Article  Google Scholar 

  72. Gerrit, H., & Christoph, S. (2010). New online retailing.

  73. Jacobs, B. W., Swink, M., & Linderman, K. (2015). Performance effects of early and late Six Sigma adoptions. Journal of Operations Management, 36, 244–257.

    Article  Google Scholar 

  74. Srinivasan, R., Lilien, G. L., & Sridhar, S. (2011). Should firms spend more on research and development and advertising during recessions? Journal of Marketing, 75(3), 49–65.

    Article  Google Scholar 

  75. Homburg, C., & Fürst, A. (2005). How organizational complaint handling drives customer loyalty: An analysis of the mechanistic and the organic approach. Journal of Marketing, 69(3), 95–114.

    Article  Google Scholar 

  76. Dant, R. P., & Brown, J. R. (2008). Bridging the B2C and B2B research divide: The domain of retailing literature. Journal of Retailing, 84(4), 371–397.

    Article  Google Scholar 

  77. Granados, N., Gupta, A., & Kauffman, R. J. (2010). Research commentary—Information transparency in business-to-consumer markets: Concepts, framework, and research agenda. Information Systems Research, 21(2), 207–226.

    Article  Google Scholar 

  78. Dewan, S., & Ren, F. (2007). Risk and return of information technology initiatives: Evidence from electronic commerce announcements. Information Systems Research, 18(4), 370–394.

    Article  Google Scholar 

  79. Krishnaswamy, R. (2012). Pattern of consumer expenditure in india: Some revelations. Economic and Political Weekly, 47, 80–83.

    Google Scholar 

  80. Rogers, E. M. (1995). Diffusion of innovations. Free Press.

    Google Scholar 

  81. Zhu, K., Kraemer, K., & Xu, S. (2003). Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors. European journal of information systems, 12(4), 251–268.

    Article  Google Scholar 

  82. Low, C., Chen, Y., & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management and Data Systems, 111(7), 1006–1023. https://doi.org/10.1108/02635571111161262

    Article  Google Scholar 

  83. Cruz-Jesus, F., Pinheiro, A., & Oliveira, T. (2019). Understanding CRM adoption stages: Empirical analysis building on the TOE framework. Computers in Industry, 109, 1–13. https://doi.org/10.1016/j.compind.2019.03.007

    Article  Google Scholar 

  84. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55.

    Article  Google Scholar 

  85. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  86. Dillman, D. A., Smyth, J. D., & Christian, L. M. (2008). Internet, mail, and mixed-mode surveys: The tailored design method. Wiley & Sons.

    Google Scholar 

  87. Malhotra, N. K., Kim, S. S., & Patil, A. (2006). Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management Science, 52(12), 1865–1883.

    Article  Google Scholar 

  88. Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544.

    Article  Google Scholar 

  89. Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology, 86(1), 114–121.

    Article  Google Scholar 

  90. Liu, G. (Jason), Shah, R., & Babakus, E. (2012). When to mass customize: The impact of environmental uncertainty*. Decision Sciences, 43(5), 851–887.

  91. Harrell Frank E, J., & Harrell, F. E. (2015). Ordinal logistic regression. In Regression modeling strategies: With applications to linear models, logistic and ordinal regression, and survival analysis (pp. 311–325). Springer.

  92. Wang, Y. S., Li, H. T., Li, C. R., & Zhang, D. Z. (2016). Factors affecting hotels’ adoption of mobile reservation systems: A technology-organization-environment framework. Tourism Management, 53, 163–172. https://doi.org/10.1016/j.tourman.2015.09.021

    Article  Google Scholar 

  93. Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information and Management, 51(5), 497–510.

    Article  Google Scholar 

  94. Manikandan, A. (2020). Reserve Bank sets up a Rs.500 crore digital payments infra fund. Economic Times.

  95. Lim, W. M. (2022). Ushering a new era of Global Business and Organizational Excellence: Taking a leaf out of recent trends in the new normal. Global Business and Organizational Excellence. Wiley Online Library.

  96. Lim, W. M., Kumar, S., Pandey, N., Verma, D., & Kumar, D. (2023). Evolution and trends in consumer behaviour: Insights from Journal of Consumer Behaviour. Journal of Consumer Behaviour, 22(1), 217–232.

    Article  Google Scholar 

  97. Dedrick, J., & West, J. (2003, April). Why firms adopt open source platforms: A grounded theory of innovation and standards adoption. MISQ Special Issue Workshop: Standard Making: A Critical Research Frontier for Information Systems, 236–257.

  98. Kuan, K. K. Y., & Chau, P. Y. K. (2001). A perception-based model for EDI adoption in small businesses using a technology-organization-environment framework. Information and Management, 38(8), 507–521. https://doi.org/10.1016/S0378-7206(01)00073-8

    Article  Google Scholar 

  99. Teo, T. S. H., Ranganathan, C., & Dhaliwal, J. (2006). Key dimensions of inhibitors for the deployment of web-based business-to-business electronic commerce. IEEE Transactions on Engineering Management, 53(3), 395–411.

    Article  Google Scholar 

  100. Borgman, H. P., Bahli, B., Heier, H., & Schewski, F. (2013). Cloudrise: Exploring cloud computing adoption and governance with the TOE framework. In Proceedings of the annual Hawaii international conference on system sciences (pp. 4425–4435).

  101. Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management, 28(6), 788–807.

    Article  Google Scholar 

  102. Hassan, H., Nasir, M. H. M., Khairudin, N., & Adon, I. (2017). Factors influencing cloud computing adoption in small and medium enterprises. Journal of ICT, 1(1), 21–41.

    Google Scholar 

  103. Sandu, R., & Gide, E. (2018, July). Technological, Organisational and Environmental (TOE) factors that influence the adoption of cloud based service SMEs in India. In IEEE International Conference on Cloud Computing, CLOUD (Vol. 2018, pp. 866–870).

  104. Al-Hujran, O., Al-Lozi, E. M., Al-Debei, M. M., & Maqableh, M. (2018). Challenges of cloud computing adoption from the TOE framework perspective. International Journal of e-Business Research, 14(3), 77–94.

    Article  Google Scholar 

  105. Seethamraju, R. (2015). Adoption of Software as a Service (SaaS) Enterprise resource planning (ERP) systems in small and medium sized enterprises (SMEs). Information Systems Frontiers, 17(3), 475–492.

    Article  Google Scholar 

  106. Oliveira, T., Martins, R., Sarker, S., Thomas, M., & Popovič, A. (2019). Understanding SaaS adoption: The moderating impact of the environment context. International Journal of Information Management, 49, 1–12.

    Article  Google Scholar 

  107. Wang, Y. M., Wang, Y. S., & Yang, Y. F. (2010). Understanding the determinants of RFID adoption in the manufacturing industry. Technological Forecasting and Social Change, 77(5), 803–815.

    Article  Google Scholar 

  108. Wu, X., & Subramaniam, C. (2011). Understanding and predicting radio frequency identification (RFID) adoption in supply Chains. Journal of Organizational Computing and Electronic Commerce, 21(4), 348–367.

    Article  Google Scholar 

  109. Lai, H. M., Lin, I. C., & Tseng, L. T. (2014). High-level managers’ considerations for RFID adoption in hospitals: An empirical study in Taiwan. Journal of Medical Systems, 38(2), 1–17.

    Article  Google Scholar 

  110. Bhattacharya, M., & Wamba, S. F. (2015). A conceptual framework of RFID adoption in retail using TOE framework. International Journal of Technology Diffusion, 6(1), 1–32.

    Article  Google Scholar 

  111. Shi, P., & Yan, B. (2016). Factors affecting RFID adoption in the agricultural product distribution industry: Empirical evidence from China. Springerplus, 5(1), 1–11.

    Article  Google Scholar 

  112. Lin, H. F. (2014). Understanding the determinants of electronic supply chain management system adoption: Using the technology-organization-environment framework. Technological Forecasting and Social Change, 86, 80–92. https://doi.org/10.1016/j.techfore.2013.09.001

    Article  Google Scholar 

  113. Hwang, B. N., Huang, C. Y., & Wu, C. H. (2016). A TOE approach to establish a green supply chain adoption decision model in the semiconductor industry. Sustainability (Switzerland), 8(2), 168.

    Article  Google Scholar 

  114. Yeh, C. C., & Chen, Y. F. (2018). Critical success factors for adoption of 3D printing. Technological Forecasting and Social Change, 132, 209–216.

    Article  Google Scholar 

  115. Chang, T. M., Liao, L. L., & Hsiao, W. F. (2005). An empirical study on the e-CRM performance influence model for service sectors in Taiwan. In Proceedings—2005 IEEE international conference on e-technology, e-commerce and e-service, EEE-05 (pp. 240–245).

  116. Racherla, P., & Hu, C. (2008). eCRM system adoption by hospitality organizations: A technology-organization-environment (toe) framework. Journal of Hospitality and Leisure Marketing, 17(1–2), 30–58.

    Article  Google Scholar 

  117. Clohessy, T., & Acton, T. (2019). Investigating the influence of organizational factors on blockchain adoption: An innovation theory perspective. Industrial Management and Data Systems, 119(7), 1457–1491.

    Article  Google Scholar 

  118. Barnes III, B. W., Xiao, B., & Iii, B. (2019). Association for information systems organizational adoption of blockchain technology: An ecosystem organizational adoption of blockchain technology: An ecosystem perspective perspective recommended citation recommended citation.

  119. Wong, L. W., Leong, L. Y., Hew, J. J., Tan, G. W. H., & Ooi, K. B. (2020). Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs. International Journal of Information Management, 52, 101997.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Systems, Law and Operations, Sellinger School of Business and Management, Loyola University Maryland, Baltimore, MD, USA

    Ravi Srinivasan

  2. Production and Operations Management, Indian Institute of Management Bangalore, Bengaluru, India

    Krishna Sundar Diatha & Shubham Singh

Authors
  1. Ravi Srinivasan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Krishna Sundar Diatha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shubham Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ravi Srinivasan.

Ethics declarations

Conflict of interest

The authors do not have a conflict of interest in this submission. Specifically, the authors do not have any conflicts of interest with the suggested reviewers because they are not close associates of the authors, frequent collaborators, former advisees, or former advisors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix A: Measures used in this study

Appendix A: Measures used in this study

  1. 1.

    What is the frequency of usage of the following payment mechanisms by your customer to pay you (Likert Scale; 1. Very Low, 2. Low, 3. Below Average, 4. Average, 5. Above Average, 6. High, 7. Very High)

 

Frequency of usage

 

Very low

   

Very high

Credit cards

1

2

3

4

5

6

7

Debit Cards

1

2

3

4

5

6

7

Online Account Transfers

1

2

3

4

5

6

7

Mobile wallet (E.g., PayTM etc.)

1

2

3

4

5

6

7

IMPS

1

2

3

4

5

6

7

  1. 2.

    Please answer the following based on your experience using cashless payment systems. Using the cashless system…

 

Strongly disagree

 

Strongly agree

 

Enables me to accomplish tasks more quickly

1

2

3

4

5

6

7

Improves the quality of the work I do

1

2

3

4

5

6

7

Makes it easier to do my business

1

2

3

4

5

6

7

Enhances my effectiveness in the business

1

2

3

4

5

6

7

Increases my productivity

1

2

3

4

5

6

7

  1. 3.

    Please answer the following based on your experience using cash. Using cash would…

 

Strongly disagree

 

Strongly agree

would be more convenient for me

1

2

3

4

5

6

7

would increase my efficiency

1

2

3

4

5

6

7

would help me pay more quickly

1

2

3

4

5

6

7

is very secure

1

2

3

4

5

6

7

  1. 4.

    What are your future plans for your store?

 

Strongly disagree

  

Strongly agree

 

Expanding the store

1

2

3

4

5

6

7

Opening a new store

1

2

3

4

5

6

7

Computerisation

1

2

3

4

5

6

7

Taking orders through the internet

1

2

3

4

5

6

7

  1. 5.

    Based on your current and past business experience, please answer the following:

 

Very low

Very high

Competition from other Kirana stores

1

2

3

4

5

6

7

Competition from super markets

1

2

3

4

5

6

7

Competition from online grocery stores

1

2

3

4

5

6

7

  1. a—This question was changed for upstream partners based on the sampling frame

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Srinivasan, R., Diatha, K.S. & Singh, S. Adoption of cashless payment systems in the bottom-of-the-pyramid retail supply chains in India: A technology-organization-environment framework perspective. Electron Commer Res (2024). https://doi.org/10.1007/s10660-023-09803-4

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10660-023-09803-4

Keywords

Search

Navigation