Abstract
This paper aims to expand the knowledge of how mobile apps can be used to establish a smart grocery retail setting. By offering real-time, personalized digital information, mobile apps enable bidirectional interaction with customers in the grocery shopping situation. A conjoint experiment (n = 90) was used to examine the use of mobile apps in a consumer choice situation where participants were choosing fresh salmon in a grocery store. Findings show that, relative to static information given by the mobile app about expiry date, price, offers, and quality indicator, digital information was the most prominent attribute. Among digital information given by the mobile app, quality indicators by other customers were the most prominent, followed by an offer based on a product in the shopping basket, updated expiry date, and real-time price. The results expand our understanding of how mobile apps can be used to design a setting in the grocery store that creates value for customers. Based on this result, we recommend that managers that plan to invest in mobile app technology to improve the electronic commerce ecosystem should include digital information.
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References
Ellickson, P.B.: The evolution of the supermarket industry: From A&P to Wal-Mart. Simon School Working Paper Series No. FR 11–17 (2011)
Desai, P., Potia, A., Salsberg, B.: Retail 4.0: The Future of Retail Grocery in a Digital World. McKinsey & Company. http://www.mckinseyonmarketingandsales.com/retail-4-0-the-future-of-retail-grocery-in-a-digital-world
Accenture: Customers are shouting, are apparel retailers listening? Accenture Global Research (2016). https://www.accenture.com/t20160526T041237__w__/us-en/_acnmedia/Accenture/Conversion-Assets/NonSecureClients/Documents/PDF/1/Accenture-Retail-Adaptive-Research-Results-Global-Generational-Data-2016-SCROLL.pdf
Barile, S., Polese, F.: Grocery retailing in the I4.0 era. SYMPHONYA Emerg. Issues Manage. 2018(2), 38–51 (2018)
Kallweit, K., Spreer, P., Toporowski, W.: Why do customers use self-service information technologies in retail? The mediating effect of perceived service quality. J. Retail. Consum. Serv. 21(3), 268–276 (2014)
Piotrowicz, W., Cuthbertson, R.: Introduction to the special issue information technology in retail: toward Omnichannel retailing. Int. J. Electron. Commerce, 18(4), 5–16 (2014)
Mehta, R.: How will the Internet of Things impact mobile application development (2017). Cited 21 April 2018. Available from: https://www.itproportal.com/features/how-will-the-internet-of-things-impact-mobile-application-development/
Hyun-Joo, L.: Consumer-to-store employee and consumer-to-self-service technology (SST) interactions in a retail setting. Int. J. Retail Distribut. Manage. 43(8), 676–692 (2015)
Dacko, S.G.: Enabling smart retail settings via mobile augmented reality shopping apps. Technol. Forecast. Soc. Chang. 124, 243–256 (2017)
Inman, J.J., Nikolova, H.: Shopper-facing retail technology: a retailer adoption decision framework incorporating shopper attitudes and privacy concerns. J. Retail. 93(1), 7–28 (2017)
Lee, H.-J., Lyu, J.: Personal values as determinants of intentions to use self-service technology in retailing. Comput. Hum. Behav. 60, 322–332 (2016)
Green, P.E., Srinivasan, V.: Conjoint analysis in consumer research: issues and outlook. J. Consum. Res. 5(2), 103–123 (1978)
Green, P.E., Wind, Y.: New way to measure consumer´s judgments. Harvard Bus. Rev. 53, 107–117 (1975)
Green, P.E., Srinivasan, V.: Conjoint analysis in marketing: new developments with implication with implications for research and practice. J. Market. 54, 3–19 (1990)
Vriens, M.: Solving marketing problems with conjoint analysis. J. Market. Manage. 10, 37–55 (1994)
Wittink, D.R., Vriens, M., Burhenne, W.: Commercial use of conjoint analysis in Europe: results and critical reflections. Int. J. Res. Mark. 11, 41–52 (1994)
Holbrook, M.B., Moore, W.L.: Feature interactions in consumer judgments of verbal versus pictorial presentations. J. Consum. Res. 8(1), 103–113 (1981)
Hair, J.F., et al.: Multivariate data analysis, 7th edn. Pearson Prentice Hall, Upper Saddle River (2014)
Zeithaml, V.A.: Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. J. Market. 52(3), 2–22 (1988)
Grewal, D., et al.: Innovations in retail pricing and promotions. J. Retail. 87(Supplement 1), S43–S52 (2011)
Dellarocas, C.: The digitization of word of mouth: promise and challenges of online feedback mechanisms. Manage. Sci. 49(10), 1407–1424 (2003)
Chrzan, K.: Three kinds of order effects in choice-based conjoint analysis. Market. Lett. 5(2), 165–172 (1994)
Fagerstrøm, A., Sigurdsson, V.: The experimental analysis of consumer choice. In: Foxall, G.R. (Ed.) The Routledge Companion to Consumer Behavior Analysis. Routledge: London (2016)
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Fagerstrøm, A., Eriksson, N., Sigurdsson, V. (2021). The Use of Mobile Apps to Facilitate Customers’ Choice-Making When Grocery Shopping. In: Zhang, YD., Senjyu, T., SO–IN, C., Joshi, A. (eds) Smart Trends in Computing and Communications: Proceedings of SmartCom 2020. Smart Innovation, Systems and Technologies, vol 182. Springer, Singapore. https://doi.org/10.1007/978-981-15-5224-3_4
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