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International Journal of Marketing & Financial Management

FACTORS AFFECTING BEHAVIOUR INTENTION TO ADOPT BLOCKCHAIN TECHNOLOGY BASED LOYALTY PROGRAM

Mr. Rakesh Kumar, Dr. Harpreet Kaur

*Mr. Rakesh Kumar, **Dr. Harpreet Kaur

*PhD scholar, Maharaja Agrasen School of Management, Maharaja Agrasen University, Baddi, Himachal Pradesh.174103,

**Asst Professor, Maharaja Agrasen School of Management, Maharaja Agrasen University, Baddi, (HP). 174103,

DOI : https://doi.org/10.5281/zenodo.15393708 Page No : 72-88

Published Online : 2025-05-13

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Blockchain is an innovative technology that can completely change how customer loyalty programs are offered by ensuring efficiency, security, and transparency. However, behavioural intentions, which are influenced by a number of factors, determine whether it is implemented successfully. This study tests the Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine the factors that influence consumer behavioural intentions (BI) to adopt blockchain technology in the context of loyalty programs. Research on the adoption of blockchain-based loyalty programs tests four factors: performance expectancy, effort expectancy, social influence, and enabling conditions. Additionally, the effects of moderators like gender, age, experience, position, and voluntariness of use on user attitudes towards implementing a blockchain-based loyalty program are investigated. Regarding the perceived security, transparency, and dependability of blockchain technology, the determinant of trust is emphasised. Structured questionnaires were used to collect consumer data as part of a quantitative research design. Descriptive statistics and structural equation modelling were used to analyse the collected data and look for connections between the block chain adoptions and the UTAUT constructs.

According to the study's findings, people are more likely to trust technology when it helps them personally. It also demonstrates that consumers' behavioural attitudes towards new technology are influenced by their own acceptance of it, which in turn affects their intention to adopt it. The study also demonstrates that widespread adoption in loyalty programs depends on building trust through transparent and safe blockchain applications. Both scholarly research and practical applications are supported by these findings, which help companies develop more effective blockchain-based loyalty programs that encourage consumer interaction and long-lasting brand loyalty.

Keywords: Blockchain technology, Loyalty Programs, Trust, UTAUT Model, Technology Acceptance, Consumer Behaviour

Type of paper: Research Paper

References:

Casey, M. J. (2015). How bitcoin technology could shake up the loyalty-points business. The Wall Street Journal.
Chang, M., Walimuni, A. C., Kim, M., & Lim, H. (2022). Acceptance of tourism blockchain based on UTAUT and connectivism theory. Technology in Society, 71, 102027. https://doi.org/10.1016/j.techsoc.2022.102027
Clark, P. (2010). The 15 business benefits of a loyalty initiative. The Wise Marketer.
Cronbach, L. T. (1947). Test reliability: Its meanings and determination. Psychometrika, 12(1), 1–16. https://doi.org/10.1007/BF02289289
De Covny, S. (2015). Chips of the old blockchain. CFA Institute Magazine, 26(6).
Dennis, S. (2016). How to become a rewards application operator. Medium. https://medium.com
Dowling, G. R., & Uncles, M. (1997). Do customer loyalty programs really work? Sloan Management Review. http://sloan.mit.edu/?content_type=research=feature
Ghavami, A., & Olyaei, A. (2006). The impact of CRM on customer retention (Master’s thesis, Luleå University of Technology).
Hair Jr., J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson.
Hamidi, H., & Chavoshi, A. (2018). Analysis of the essential factors for the adoption of mobile learning in higher education: A case study of students of the University of Technology. Telematics and Informatics, 35, 1053–1070. https://doi.org/10.1016/j.tele.2018.03.002
Hamidi, H., & Jahan Shaheefard, M. (2019). Essential factors for the application of education information systems using mobile learning. Telematics and Informatics, 38, 207–224. https://doi.org/10.1016/j.tele.2018.10.002
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
Hoque, R., & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International Journal of Medical Informatics, 101, 75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002
Iansiti, M., & Lakhani, K. R. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118–127.
Jenn, S. (2015). How bitcoin technology is changing the loyalty rewards industry. NewsBTC. https://www.newsbtc.com
Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioral intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34, 1250–1261.
Kahilzadeh, J., Ozturk, A. B., & Bilgihan, A. (2017). Security-related factors in the extended UTAUT model for NFC-based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460–474.
Kannan, P. K., & Bramlett, M. D. (2000). Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science, 28(1), 95–108.
Kayode, D. J., Alabi, A. T., Sofoluwe, A. O., & Oduwaiye, R. O. (2019). Problems and challenges of mobile learning in Nigerian university system. In Y. Zhang & D. Cristol (Eds.), Handbook of Mobile Teaching and Learning (pp. 1–15). Springer.
Khan. (2012). Blockchain technology is still in its nascent stage; it holds significant potential for loyalty rewards programs.
Kim, H. J., Lee, J. M., & Rha, J. Y. (2017). Understanding the role of user resistance on mobile learning usage among university students. Computers & Education, 113, 108–118.
Kolowich, L. (2015). 7 customer loyalty programs that actually add value. HubSpot. https://blog.hubspot.com
Koufaris, M., & Hampton-Sosa, W. (2004). The development of initial trust in an online company by new customers. Information & Management, 41, 377–397.
Kumar, J. A., & Bervell, B. (2019). Google Classroom for mobile learning in higher education: Modelling the initial perceptions of students. Education and Information Technologies, 24, 1793–1817.
Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89.
Lewis, M. (2004). The influence of loyalty programs and short-term promotions on customer retention. Journal of Marketing Research, 41(3), 281–292.
Lowenstein, M. W. (2002). Customer win back: How to recapture lost customers and keep them loyal. John Wiley & Sons.
Mou, J., Shin, D. H., & Cohen, J. (2016). Understanding trust and perceived usefulness in the consumer acceptance of an e-service: A longitudinal investigation. Behaviour & Information Technology, 36, 125–139.
O'Brien, J., & Montali, D. (2016). Loyalty programs see opportunities in blockchain technology.
Peiguss, K. (2012). 7 customer loyalty programs that actually add value. HubSpot. http://blog.hubspot.com/blog/tabid/6307/bid/31990/7-Customer-Loyalty
Ream, J., Chu, Y., & Schatsky, D. (2016). Upgrading blockchains: Smart contract use cases in industry. Deloitte University Press.
Reinartz, W., Krafft, M., & Hoyer, W. D. (2004). The customer relationship management process: Its measurement and impact on performance. Journal of Marketing Research, 41(3), 293–305.
Schatsky, D., & Muraskin, C. (2015). Beyond bitcoin: Blockchain is coming to disrupt your industry. Deloitte University Press.
Sharp, B., & Sharp, A. (1997). Loyalty programs and their impact on repeat-purchase loyalty patterns. International Journal of Research in Marketing, 14(5), 473–486.
Singh, R., & Khan, I. (2012). An approach to increase customer retention and loyalty in B2C world. International Journal of Scientific and Research Publications, 2(6).
Thatcher, J. B., McKnight, D. H., Baker, E. A., Arsal, R. E., & Roberts, N. W. (2011). The role of trust in post-adoption IT exploration: An empirical examination of knowledge management systems. IEEE Transactions on Engineering Management, 58(1), 56–70.
Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483–502.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
Wong, L. M., Tan, G. W. H., Lee, V. H., Ooi, K. B., & Sohal, A. S. (2020). Unearthing the determinants of blockchain adoption in supply chain management. International Journal of Production Research, 58(7), 2100–2123.
Zikmund, W. G., McLeod, R., Jr., & Gilbert, F. W. (2002). Customer relationship management: Integrating marketing strategy and information technology. Wiley.

Cite this Article as: Rakesh K & Harpreet K (2025), “Factors Affecting Behaviour Intention To Adopt Blockchain Technology Based Loyalty Program”, International Journal of Marketing & Financial Management, Volume 13, Issue 1, 2025, pp 72-88, DOI : https://doi.org/10.5281/zenodo.15393708

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References:

Casey, M. J. (2015). How bitcoin technology could shake up the loyalty-points business. The Wall Street Journal.
Chang, M., Walimuni, A. C., Kim, M., & Lim, H. (2022). Acceptance of tourism blockchain based on UTAUT and connectivism theory. Technology in Society, 71, 102027. https://doi.org/10.1016/j.techsoc.2022.102027
Clark, P. (2010). The 15 business benefits of a loyalty initiative. The Wise Marketer.
Cronbach, L. T. (1947). Test reliability: Its meanings and determination. Psychometrika, 12(1), 1–16. https://doi.org/10.1007/BF02289289
De Covny, S. (2015). Chips of the old blockchain. CFA Institute Magazine, 26(6).
Dennis, S. (2016). How to become a rewards application operator. Medium. https://medium.com
Dowling, G. R., & Uncles, M. (1997). Do customer loyalty programs really work? Sloan Management Review. http://sloan.mit.edu/?content_type=research=feature
Ghavami, A., & Olyaei, A. (2006). The impact of CRM on customer retention (Master’s thesis, Luleå University of Technology).
Hair Jr., J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson.
Hamidi, H., & Chavoshi, A. (2018). Analysis of the essential factors for the adoption of mobile learning in higher education: A case study of students of the University of Technology. Telematics and Informatics, 35, 1053–1070. https://doi.org/10.1016/j.tele.2018.03.002
Hamidi, H., & Jahan Shaheefard, M. (2019). Essential factors for the application of education information systems using mobile learning. Telematics and Informatics, 38, 207–224. https://doi.org/10.1016/j.tele.2018.10.002
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
Hoque, R., & Sorwar, G. (2017). Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model. International Journal of Medical Informatics, 101, 75–84. https://doi.org/10.1016/j.ijmedinf.2017.02.002
Iansiti, M., & Lakhani, K. R. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118–127.
Jenn, S. (2015). How bitcoin technology is changing the loyalty rewards industry. NewsBTC. https://www.newsbtc.com
Kabra, G., Ramesh, A., Akhtar, P., & Dash, M. K. (2017). Understanding behavioral intention to use information technology: Insights from humanitarian practitioners. Telematics and Informatics, 34, 1250–1261.
Kahilzadeh, J., Ozturk, A. B., & Bilgihan, A. (2017). Security-related factors in the extended UTAUT model for NFC-based mobile payment in the restaurant industry. Computers in Human Behavior, 70, 460–474.
Kannan, P. K., & Bramlett, M. D. (2000). Implications of loyalty program membership and service experiences for customer retention and value. Journal of the Academy of Marketing Science, 28(1), 95–108.
Kayode, D. J., Alabi, A. T., Sofoluwe, A. O., & Oduwaiye, R. O. (2019). Problems and challenges of mobile learning in Nigerian university system. In Y. Zhang & D. Cristol (Eds.), Handbook of Mobile Teaching and Learning (pp. 1–15). Springer.
Khan. (2012). Blockchain technology is still in its nascent stage; it holds significant potential for loyalty rewards programs.
Kim, H. J., Lee, J. M., & Rha, J. Y. (2017). Understanding the role of user resistance on mobile learning usage among university students. Computers & Education, 113, 108–118.
Kolowich, L. (2015). 7 customer loyalty programs that actually add value. HubSpot. https://blog.hubspot.com
Koufaris, M., & Hampton-Sosa, W. (2004). The development of initial trust in an online company by new customers. Information & Management, 41, 377–397.
Kumar, J. A., & Bervell, B. (2019). Google Classroom for mobile learning in higher education: Modelling the initial perceptions of students. Education and Information Technologies, 24, 1793–1817.
Kshetri, N. (2018). Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89.
Lewis, M. (2004). The influence of loyalty programs and short-term promotions on customer retention. Journal of Marketing Research, 41(3), 281–292.
Lowenstein, M. W. (2002). Customer win back: How to recapture lost customers and keep them loyal. John Wiley & Sons.
Mou, J., Shin, D. H., & Cohen, J. (2016). Understanding trust and perceived usefulness in the consumer acceptance of an e-service: A longitudinal investigation. Behaviour & Information Technology, 36, 125–139.
O'Brien, J., & Montali, D. (2016). Loyalty programs see opportunities in blockchain technology.
Peiguss, K. (2012). 7 customer loyalty programs that actually add value. HubSpot. http://blog.hubspot.com/blog/tabid/6307/bid/31990/7-Customer-Loyalty
Ream, J., Chu, Y., & Schatsky, D. (2016). Upgrading blockchains: Smart contract use cases in industry. Deloitte University Press.
Reinartz, W., Krafft, M., & Hoyer, W. D. (2004). The customer relationship management process: Its measurement and impact on performance. Journal of Marketing Research, 41(3), 293–305.
Schatsky, D., & Muraskin, C. (2015). Beyond bitcoin: Blockchain is coming to disrupt your industry. Deloitte University Press.
Sharp, B., & Sharp, A. (1997). Loyalty programs and their impact on repeat-purchase loyalty patterns. International Journal of Research in Marketing, 14(5), 473–486.
Singh, R., & Khan, I. (2012). An approach to increase customer retention and loyalty in B2C world. International Journal of Scientific and Research Publications, 2(6).
Thatcher, J. B., McKnight, D. H., Baker, E. A., Arsal, R. E., & Roberts, N. W. (2011). The role of trust in post-adoption IT exploration: An empirical examination of knowledge management systems. IEEE Transactions on Engineering Management, 58(1), 56–70.
Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: The competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483–502.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.
Wong, L. M., Tan, G. W. H., Lee, V. H., Ooi, K. B., & Sohal, A. S. (2020). Unearthing the determinants of blockchain adoption in supply chain management. International Journal of Production Research, 58(7), 2100–2123.
Zikmund, W. G., McLeod, R., Jr., & Gilbert, F. W. (2002). Customer relationship management: Integrating marketing strategy and information technology. Wiley.

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