Channel preferences and attitudes of domestic buyers in purchase decision processes of high-value electronic devices
Objective: The objective of the article is to examine how respondents’ technological readiness (as an individual factor besides demographic characteristics) influences channel preference (in-store, online big- and small-screen at different stages of the purchasing decision process for high-value electronic devices (products).
Research Design & Methods: The research encompassed data collected by a quantitative online survey of 415 respondents in Hungary. To identify homogenous groups in the sample, we used cluster analysis based on factors we determined among the technology-readiness variables.
Findings: We identified the technological readiness index 2.0 (TRI) segments in our sample and our findings confirmed that the perceived technological readiness has a significant influence on customers’ channel choice.
Implications & Recommendations: Customer experience (CX) is far more than satisfaction with the product; it is influenced by the total purchasing decision process starting at the need recognition and ending at the post-purchasing stage. The difficulties and uncertainties in any stage of the decision-making process result in anxiety and reduce the CX. The uncertainty can arise from factors related to the product, individual, or channel.
Contribution & Value Added: Although the sample is not representative, it provides insight into how Hungarian respondents can be segmented based on technological readiness and how this affects their channel preferences during the customer journey through purchase decisions regarding electronic devices.
technological readiness; omnichannel; customer experience; pattern of channel usage; perceived control over the purchasing process; TRI
Arun, A., Dahlström, P., Hazan, E., Khan, H., & Khanna, R. (2020). Reimagining marketing in the Next Normal | McKinsey. Retrieved from https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/reimagining-marketing-in-the-next-normal on April 1, 2023.
Balakrishnan, A., Sundaresan, S., & Zhang, B. (2014). Browse-and-Switch: Retail-Online Competition under Value Uncertainty. Production and Operations Management, 23(7), 1129-1145. https://doi.org/10.1111/poms.12165
Davis, F.D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: three experiments International Journal of Human-Computer Studies, 45(1), 19-45. https://doi.org/10.1006/ijhc.1996.0040
Flavián, C., Gurrea, R., & Orús, C. (2016). Choice confidence in the webrooming purchase process: the impact of online positive reviews and the motivation to touch. Journal of Consumer Behaviour, 15, 459-476. https://doi.org/10.1002/cb.1585
Frasquet, M., Mollá, A., & Ruiz, E. (2015). Identifying patterns in channel usage across the search, purchase and post-sales stages of shopping. Electronic Commerce Research and Applications, 14, 654-665. https://doi.org/10.1016/j.elerap.2015.10.002
GlobalData. (2021). Retail in 2021 and beyond: Trends and solutions with edge computing. Prepared for Lumen by GlobalData April 05, 2021. Retrieved from https://assets.lumen.com/is/content/Lumen/retail-now-and-beyond-global-data-and-lumen?Creativeid=7565f693-a342-4b14-b8f0-0fa1c40dbd9f on August 5, 2022.
Gensler, S., Scott, A., & Verhoef, P.C. (2017). The Showrooming Phenomenon: It's More than Just About Price. Journal of Interactive Marketing, 38, 29-43. https://doi.org/10.1016/j.intmar.2017.01.003
Gu, J.Z., & Tayi, G.K. (2016). Consumer Pseudo-Showrooming and Omni-Channel Product Placement Strate-gies. Management Information Systems Quarterly, Forthcoming. https://doi.org/10.13140/RG.2.1.3880.8569
Hallikainen, H., Alamaki, A., & Laukkanen, T. (2019). Individual preferences of digital touchpoints: A latent class analysis. Journal of Retailing and Consumer Services, 50, 386-393. https://doi.org/10.1016/j.jretconser.2018.07.014
Hammond, R. (2017). Smart Retail, Winning ideas and strategies from the most successful retailers in the world. Pearson Education Limited (pp. 11-12).
Hansen, J.M., Saridakis, G., & Benson, V. (2018). Risk, trust, and the interaction of perceived ease of use and behavioral control in predicting consumers’ use of social media for transactions. Computers in Human Behavior, 80, 197-206. https://doi.org/10.1016/j.chb.2017.11.010
Heitmann, M., Lehmann, D.R., & Herrmann, A. (2007). Choice goal attainment and decision and consump-tion satisfaction. Journal of Marketing Research, 44(2), 234-250. https://doi.org/10.1509/jmkr.44.2.234
Herhausen, D., Kleinlercher, K., Verhoef, P.C., Emrich, O., & Rudolph, T. (2019). Loyalty Formation for Differ-ent Customer Journey Segments. Journal of Retailing, 95(3), 9-29. https://doi.org/10.1016/j.jretai.2019.05.001
Hyun, H., Thavisay, T., & Lee, S.H. (2022). Enhancing the role of flow experience in social media usage and its impact on shopping. Journal of Retailing and Consumer Services, 65, 102492. https://doi.org/10.1016/j.jretconser.2021.102492
Kannan, P.K., & Kulkarni, G. (2021). The impact of Covid-19 on customer journeys: Implications for interac-tive marketing. Journal of Research in Interactive Marketing, 16(1), 22-36. https://doi.org/10.1108/JRIM-03-2021-0078
Keszey, T., & Zsukk, J. (2017). Az új technológiák fogyasztói elfogadása. A magyar és nemzetközi szakirodalom áttekintése és kritikai értékelése. Vezetéstudomány / Budapest Management Review, 48(10), 38-47. https://doi.org/10.14267/VEZTUD.2017.10.05
Konus, U., Verhoef, P.C., & Neslin, S.A. (2008). Multichannel Shopper Segments and Their Covariates. Journal of Retailing, 84(4), 398-413. https://doi.org/10.1016/j.jretai.2008.09.002
Mehra, A., Kumar, S., &. Raju, J.S. (2013). Competitive Strategies for Brick-and-Mortar Stores to Counter ’Showrooming’ and the Competition between Store and Online Retailers. SSRN Electronic Journal. Re-trieved from https://ur.booksc.eu/book/71896823/da5046 on September 20, 2022.
Neslin, S.A. (2022). The omnichannel continuum: Integrating online and offline channels along the customer journey. Journal of Retailing, 98(1), 111-132. https://doi.org/10.1016/j.jretai.2022.02.003
Oyman, M., Bal, D., & Ozer, S. (2022). Extending the technology acceptance model to explain how perceived augmented reality affects consumers’ perceptions. Computers in Human Behavior, 128, 107127. https://doi.org/10.1016/j.chb.2021.107127
Parasuraman, A., & Colby, C.L. (2015). An updated and streamlined technology readiness index: TRI 2.0 Jour-nal of Service Research, 18(1), 59-74. https://doi.org/10.1177/1094670514539730
Parasuraman, A., & Colby, C.L. (2001). Techno-ready Marketing: How and Why Your Customers Adopt Tech-nology, 224. New York: Free Press.
Park, S., & Lee, D. (2017). An empirical study on consumer online shopping channel choice behavior in omni-channel environment. Telematics and Informatics, 34(8), 1398-1407. https://doi.org/10.1016/j.tele.2017.06.003
Peck, J., & Childers, T.L. (2003). Individual Differences in Haptic Information Processing: The “Need for Touch” Scale. Journal of Consumer Research, 30(3), 430-442. https://doi.org/10.1086/378619
Puccinelli, N.M., Goodstein, R., Grewal, D., Price, R., Raghubir, P., & Stewart, D. (2009). Customer Experience Management in Retailing: Understanding the Buying Process. Journal of Retailing, 85(1), 15-30. https://doi.org/10.1016/j.jretai.2008.11.003
Rodrígez-Torrico, P., San José Cabezudo, R., & San-Martin, S. (2014). Tell me what they are like and I will tell you where they buy. An analysis of omnichannel consumer behavior. Computers in Human Behavior, 68, 465-471. https://doi.org/10.1016/j.chb.2016.11.064
Santos, S., & Martins Gonçalves, H. (2019). Multichannel consumer behaviors in the mobile environment: Using fsQCA and discriminant analysis to understand webrooming motivations. Journal of Business Re-search, 101(1), 757-766. https://doi.org/10.1016/j.jbusres.2018.12.069
Schul, Y., & Mayo, R. (2003). Searching for certainty in an uncertain world: the difficulty of giving up the experiential for the rational mode of thinking. Journal of Behavioral Decision Making, 16(2), 93-106. https://doi.org/10.1002/bdm.434
Valentini, S., Neslin, S.A., & Montaguti, E. (2020). Identifying omnichannel deal prone segments, their ante-cedents, and their consequences. Journal of Retailing, 96(3), 310-327. https://doi.org/10.1016/j.jretai.2020.01.003
Walsh, G., & Mitchell, V.-W. (2010). The effect of consumer confusion proneness on word of mouth, trust, and customer satisfaction. European Journal of Marketing, 44, 838-859. https://doi.org/10.1108/03090561011032739
Verhoef, P.C., Kannan, P.K., & Inman, J.J. (2015). From multi-channel retailing to omni-channel retailing: introduction to the special issue on multi-channel retailing. Journal of Retailing, 91, 174-181. https://doi.org/10.1016/j.jretai.2015.02.005
Walsh, G., & Mitchell, V.W. (2010). The effect of consumer confusion proneness on word of mouth, trust, and customer satisfaction. European Journal of Marketing, 44(6), 838-859. https://doi.org/10.1108/03090561011032739
Zielke, S., Komor, M., & Schlößer, A. (2023). Coping strategies and intended change of shopping habits after the Corona pandemic – Insights from two countries in Western and Eastern Europe. Journal of Retailing and Consumer Services, 72, 103255. https://doi.org/10.1016/j.jretconser.2023.103255
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a CC BY-4.0 licence that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are asked to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) only the final version of the article, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access). We advise using any of the following research society portals: