Abstract
Subscription platforms based on artificial intelligence (AI) that offer the delivery of physical goods represent a new frontier in retailing. Therefore, empirical investigation into consumers’ views on the factors driving their motivation to use such platforms is necessary. Considering the lack of research on this front, this study aims to examine consumers’ insights into the enabling and constraining technological affordances of platforms that inhibit or facilitate subscription motivation. Drawing on Regulatory Focus Theory, this study tests the effects of situational prevention-focused and promotion-focused factors on subscription intention. Based on data from 290 respondents, we found that intention is positively influenced by perceived functional congruity, which is determined by perceived service personalization and ease of use. In contrast, the effect of psychological reactance associated with perceived lack of control over service delivery is negative. These findings advance our understanding of the features of platforms offering physical goods subscription services that drive the predisposition to use such platforms, thus informing retailers on how AI can support platform expansion.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Pasirayi, S., Fennell, P.B.: The effect of subscription-based direct-to-consumer channel additions on firm value. J. Bus. Res. 123, 355–366 (2021)
Kerschbaumer, R.H., et al.: Subscription commerce: an attachment theory perspective. Int. Rev. Retail, Distrib. Consum. Res. 33(1), 92–115 (2023)
Roy, A., Ortiz, M.: Is it risky to subscribe? Perceived control and subscription choice. Psychol. Market. 40(2), 365–372 (2023)
Wagner, L., Pinto, C., Amorim, P.: On the value of subscription models for online grocery retail. Eur. J. Oper. Res. 294(3), 874–894 (2021)
Pantano, E., Stylos, N.: The Cinderella moment: exploring consumers’ motivations to engage with renting as collaborative luxury consumption mode. Psychol. Market. 37(5), 740–753 (2020)
Bhatt, D., Kim, H.-S., Bhatt, S.: Shopping motivations of fashion subscription service consumers. Int. Rev. Retail, Distrib. Consum. Res. 31(5), 549–565 (2021)
Tao, Q., Xu, Y.: Fashion subscription retailing: an exploratory study of consumer perceptions. J. Fashion Market. Manag.: An Int. J. 22(4) (2018)
Bray, J., et al.: Thinking inside the box: an empirical exploration of subscription retailing. J. Retailing Consum. Serv. 58, 102333 (2021)
Bischof, S.F., Boettger, T.M., Rudolph, T.: Curated subscription commerce: a theoretical conceptualization. J. Retail. Consum. Serv. 54, 101822 (2020)
Niculescu, M.F., Shin, H., Whang, S.: Underlying consumer heterogeneity in markets for subscription-based IT services with network effects. Inform. Syst. Res. 23(4), 1322–1341 (2012)
Feng, N., et al.: Designing subscription menu for software products: whether to release a long-length option. Inform. Manag. 59(6), 103665 (2022)
Pantano, E., Scarpi, D.: I, robot, you, consumer: measuring artificial intelligence types and their effect on consumers emotions in service. J. Serv. Res. 25(4), 583–600 (2022)
Wirtz, J., et al.: Corporate digital responsibility in service firms and their ecosystems. J. Serv. Res. 26(2), 173–190 (2023)
Kopalle, P.K., et al.: Examining artificial intelligence (AI) technologies in marketing via a global lens: current trends and future research opportunities. Int. J. Res. Market. 39(2), 522–540 (2022)
Higgins, E.T.: Regulatory focus theory. In: Van Lange, P., Kruglanski, A., Higgins, E. (eds.) Handbook of Theories of Social Psychology: Vol. 1, pp. 483–504. SAGE Publications Ltd, 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom (2012). https://doi.org/10.4135/9781446249215.n24
Kronemann, B., et al.: How AI encourages consumers to share their secrets? The role of anthropomorphism, personalisation, and privacy concerns and avenues for future research. Spanish J. Market.-ESIC 27(1), 2–19 (2023)
Nawaz, I.Y.: Characteristics of millennials and technology adoption in the digital age. In: Dadwal, S.S. (ed.) Handbook of Research on Innovations in Technology and Marketing for the Connected Consumer, pp. 241–262. IGI Global (2020). https://doi.org/10.4018/978-1-7998-0131-3.ch012
Zhang, B., Sundar, S.S.: Proactive vs. reactive personalization: can customization of privacy enhance user experience? Int. J. Human-Comput. Stud. 128, 86–99 (2019)
Childers, T.L., et al.: Hedonic and utilitarian motivations for online retail shopping behavior. J. Retail. 77(4), 511–535 (2001)
Marikyan, D., et al.: Working in a smart home environment: examining the impact on productivity, well-being and future use intention. Internet Res. (2023)
Marikyan, D., Papagiannidis, S., Alamanos, E.: A systematic review of the smart home literature: a user perspective. Technol. Forecast. Soc. Change 138, 139–154 (2019)
Li, L., Ota, K., Dong, M.: Humanlike driving: empirical decision-making system for autonomous vehicles. IEEE Trans. Veh. Technol. 67(8), 6814–6823 (2018)
Endsley, M.R.: From here to autonomy: lessons learned from human–automation research. Hum. Factors 59(1), 5–27 (2017)
Higgins, E.T.: Beyond pleasure and pain. Am. Psychol. 52(12), 1280 (1997)
Brockner, J., Higgins, E.T.: Regulatory focus theory: implications for the study of emotions at work. Organ. Behav. Hum. Decis. Processes 86(1), 35–66 (2001)
Zimmermann, R., et al.: Enhancing brick-and-mortar store shopping experience with an augmented reality shopping assistant application using personalized recommendations and explainable artificial intelligence. J. Res. Interact. Mark. 17(2), 273–298 (2023)
Sirgy, M.J., Johar, J.: Toward an integrated model of self-congruity and functional congruity. ACR Eur. Adv. 4, 252–256 (1999)
Brehm, S.S., Brehm, J.W.: Psychological Reactance: A Theory of Freedom and Control. Academic Press (2013)
Sirgy, M.J., et al.: Self-congruity versus functional congruity: predictors of consumer behavior. J. Acad. Market. Sci. 19, 363–375 (1991)
Marikyan, D., et al.: “Alexa, let’s talk about my productivity”: the impact of digital assistants on work productivity. J. Bus. Res. 142, 572–584 (2022)
Balakrishnan, J., Dwivedi, Y.K.: Conversational commerce: entering the next stage of AI-powered digital assistants. Ann. Operat. Res. 1–35 (2021). https://doi.org/10.1007/s10479-021-04049-5
Pansari, A., Kumar, V.: Customer engagement: the construct, antecedents, and consequences. J. Acad. Market. Sci. 45, 294–311 (2017)
Barth, S., De Jong, M.D.: The privacy paradox–Investigating discrepancies between expressed privacy concerns and actual online behavior–A systematic literature review. Telematics Inform. 34(7), 1038–1058 (2017)
Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13(3), 319–340 (1989). https://doi.org/10.2307/249008
King, W.R., He, J.: A meta-analysis of the technology acceptance model. Inform. Manag. 43(6), 740–755 (2006)
Davis, F.D.: User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. Int. J. Man-Mach. Stud. 38(3), 475–487 (1993)
Papagiannidis, S., Davlembayeva, D.: Bringing smart home technology to peer-to-peer accommodation: exploring the drivers of intention to stay in smart accommodation. Inform. Syst. Front. 24(4), 1189–1208 (2022)
Kim, H., So, K.K.F., Wirtz, J.: Service robots: Applying social exchange theory to better understand human–robot interactions. Tourism Manag. 92, 104537 (2022)
Papagiannidis, S., Marikyan, D.: Smart offices: a productivity and well-being perspective. Int. J. Inform. Manag. 51, 102027 (2020)
Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Dec. Proc. 50(2), 179–211 (1991)
Taylor, S., Todd, P.A.: Understanding information technology usage: a test of competing models. Inform. Syst. Res. 6(2), 144–176 (1995)
Wnuk, A., Oleksy, T., Maison, D.: The acceptance of Covid-19 tracking technologies: the role of perceived threat, lack of control, and ideological beliefs. PloS one 15(9), e0238973 (2020)
Straub, D.W., Welke, R.J.: Coping with systems risk: Security planning models for management decision making. MIS Q. 22(4), 441 (1998). https://doi.org/10.2307/249551
Clee, M.A., Wicklund, R.A.: Consumer behavior and psychological reactance. J. Consum. Res. 6(4), 389–405 (1980)
Sirgy, M.J., Samli, A.C.: A path analytic model of store loyalty involving self-concept, store image, geographic loyalty, and socioeconomic status. J. Acad. Market. Sci. 13, 265–291 (1985)
Suh, K.-S., Kim, H., Suh, E.K.: What if your avatar looks like you? Dual-congruity perspectives for avatar use. MIS Q. 35, 711–729 (2011)
Wu, S., et al.: Self-image congruence, functional congruence, and mobile app intention to use. Mobile Inform. Syst. 2020, 1–17 (2020)
Su, N., Reynolds, D.: Effects of brand personality dimensions on consumers’ perceived self-image congruity and functional congruity with hotel brands. Int. J. Hospitality Manag. 66, 1–12 (2017)
Jing, R.: A brief analysis of the influencing mechanism of Internet financial behavior: based on congruity perspective. In: 2018 International Conference on Economics, Business, Management and Corporate Social Responsibility (EBMCSR 2018). Atlantis Press (2018)
Kumar, V., Nayak, J.K.: The role of self-congruity and functional congruity in influencing tourists’ post visit behaviour. Adv. Hospitality Tourism Res. (AHTR) 2(2), 24–44 (2014)
Gupta, A.S., Mukherjee, J.: Decoding revenge buying in retail: role of psychological reactance and perceived stress. Int. J. Retail Distrib. Manag. 50(11), 1378–1394 (2022). https://doi.org/10.1108/IJRDM-01-2022-0022
Brehm, J.W.: A Theory of Psychological Reactance. Academic Press (1966)
Rosenberg, B.D., Siegel, J.T.: A 50-year review of psychological reactance theory: do not read this article. Motiv. Sci. 4(4), 281 (2018)
Veloutsou, C., McAlonan, A.: Loyalty and or disloyalty to a search engine: the case of young Millennials. J. Consum. Market. 29(2), 125–135 (2012)
Venkatesh, V., Bala, H.: Technology acceptance model 3 and a research agenda on interventions. Dec. Sci. 39(2), 273–315 (2008)
Sop, S.A., Kozak, N.: Effects of brand personality, self-congruity and functional congruity on hotel brand loyalty. J. Hospitality Market. Manag. 28(8), 926–956 (2019)
Zhang, P., Meng, F., So, K.K.F.: Cocreation experience in peer-to-peer accommodations: conceptualization and scale development. J. Travel Res. 60(6), 1333–1351 (2021)
Lee, G., Lee, J., Sanford, C.: The roles of self-concept clarity and psychological reactance in compliance with product and service recommendations. Comput. Hum. Behav. 26(6), 1481–1487 (2010)
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. 36, 157–178 (2012)
Hair, J.F., et al.: Multivariate Data Analysis: Pearson New, International Pearson Education Limited, Essex (2014)
Podsakoff, P.M., et al.: Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol. 88(5), 879 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 IFIP International Federation for Information Processing
About this paper
Cite this paper
Davlembayeva, D., Marikyan, D., Pantano, E., Serravalle, F., Babayan, D. (2023). Creating Demand for AI-Based Subscription of Physical Goods: A Consumer Perspective in the Food Industry. In: Janssen, M., et al. New Sustainable Horizons in Artificial Intelligence and Digital Solutions. I3E 2023. Lecture Notes in Computer Science, vol 14316. Springer, Cham. https://doi.org/10.1007/978-3-031-50040-4_5
Download citation
DOI: https://doi.org/10.1007/978-3-031-50040-4_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-50039-8
Online ISBN: 978-3-031-50040-4
eBook Packages: Computer ScienceComputer Science (R0)