Share:


Variety of shopping modes: theoretical framework, pivotal factors, and managerial implications

    Ignacio Redondo Affiliation
    ; Jean-Philippe Charron Affiliation

Abstract

With the development of e-commerce and smartphones, consumers can use a variety of shopping modes (i.e., showrooming, webrooming, and completely offline/online shopping), each of which provides specific advantages in terms of price, assortment, service, etc. Using a great variety of these shopping modes can confer many benefits. However, previous studies have found evidence of sizable segments of consumers who typically avoid using a great variety of shopping modes. To understand the contrast in consumers’ variety of shopping modes, we propose a theoretical framework and measure the effect of the desired variety in the information-seeking and purchase processes. Results – from a representative sample of the Spanish consumers – confirm that the variety of shopping modes pivots on the extent to which e-commerce use, smartphone use, offline and online interactivity, and online device interchangeability differ. Better understanding the variety of shopping modes may help marketers adjust their channel strategies to the actual preferences of different consumer segments and assess the economic viability of an omnichannel approach.

Keyword : shopping behaviour, consumer segmentation, e-commerce, showrooming, webrooming, channel management

How to Cite
Redondo, I., & Charron, J.-P. (2023). Variety of shopping modes: theoretical framework, pivotal factors, and managerial implications. Journal of Business Economics and Management, 24(5), 857–876. https://doi.org/10.3846/jbem.2023.20438
Published in Issue
Dec 22, 2023
Abstract Views
552
PDF Downloads
481
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Adomavicius, G., Bockstedt, J., & Curley, S. P. (2015). Bundling effects on variety seeking for digital information goods. Journal of Management Information Systems, 31(4), 182–212. https://doi.org/10.1080/07421222.2014.1001266

Ailawadi, K. L., & Farris, P. W. (2017). Managing multi- and omni-channel distribution: Metrics and research directions. Journal of Retailing, 93(1), 120–135. https://doi.org/10.1016/j.jretai.2016.12.003

Avornyo, P., Fang, J., Antwi, C. O., Aboagye, M. O., & Boadi, E. A. (2019). Are customers still with us? The influence of optimum stimulation level and IT-specific traits on mobile banking discontinuous usage intentions. Journal of Retailing and Consumer Services, 47, 348–360. https://doi.org/10.1016/j.jretconser.2019.01.001

Bawa, K. (1990). Modeling inertia and variety seeking tendencies in brand choice behavior. Marketing Science, 9(3), 263–278. https://doi.org/10.1287/mksc.9.3.263

Berry, C., Kees, J., & Burton, S. (2022). Drivers of data quality in advertising research: Differences across MTurk and professional panel samples. Journal of Advertising, 51(4), 515–529. https://doi.org/10.1080/00913367.2022.2079026

Blake, B. F., Neuendorf, K. A., & Valdiserri, C. M. (2003). Innovativeness and variety of Internet shopping. Internet Research, 13(3), 156–169. https://doi.org/10.1108/10662240310478187

Burns, D. J. (2006). Consumers’ decision-making style: Relationships with attitude toward consumer free-riding activity. Marketing Management Journal, 16(1), 148–157. http://www.mmaglobal.org/publications/MMJ/MMJ-Issues/2006-Spring/MMJ-2006-Spring-Vol16-Issue1-Burns-pp148-157.pdf

Chiu, H.-C., Hsieh, Y.-C., Roan, J., Tseng, K.-J., & Hsieh, J.-K. (2011). The challenge for multichannel services: Cross-channel free-riding behavior. Electronic Commerce Research and Applications, 10(2), 268–277. https://doi.org/10.1016/j.elerap.2010.07.002

Colla, E., & Lapoule, P. (2012). E‐commerce: Exploring the critical success factors. International Journal of Retail & Distribution Management, 40(11), 842–864. https://doi.org/10.1108/09590551211267601

Cui, T. H., Ghose, A., Halaburda, H., Iyengar, R., Pauwels, K., Sriram, S., Tucker, C., & Venkataraman, S. (2021). Informational challenges in omnichannel marketing: Remedies and future research. Journal of Marketing, 85(1), 103–120. https://doi.org/10.1177/0022242920968810

De Keyser, A., Schepers, J., & Konuş, U. (2015). Multichannel customer segmentation: Does the after-sales channel matter? A replication and extension. International Journal of Research in Marketing, 32(4), 453–456. https://doi.org/10.1016/j.ijresmar.2015.09.005

Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication, 6(1), Article JCMC611. https://doi.org/10.1111/j.1083-6101.2000.tb00110.x

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(5), 459–476. https://doi.org/10.1002/cb.1585

Frasquet, M., Ieva, M., & Ziliani, C. (2021). Online channel adoption in supermarket retailing. Journal of Retailing and Consumer Services, 59, Article 102374. https://doi.org/10.1016/j.jretconser.2020.102374

Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.

Gensler, S., Neslin, S. 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

Gullo, K., Berger, J., Etkin, J., & Bollinger, B. (2019). Does time of day affect variety-seeking? Journal of Consumer Research, 46(1), 20–35. https://doi.org/10.1093/jcr/ucy061

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (7th ed.). Pearson Education.

Hajdas, M., Radomska, J., & Silva, S. C. (2022). The omni-channel approach: A utopia for companies? Journal of Retailing and Consumer Services, 65, Article 102131. https://doi.org/10.1016/j.jretconser.2020.102131

Hansberger, J. T., Schunn, C. D., & Holt, R. W. (2006). Strategy variability: How too much of a good thing can hurt performance. Memory & Cognition, 34(8), 1652–1666. https://doi.org/10.3758/BF03195928

Hansson, L., Holmberg, U., & Post, A. (2022). Reorganising grocery shopping practices – the case of elderly consumers. International Review of Retail, Distribution and Consumer Research, 32(4), 351–369. https://doi.org/10.1080/09593969.2022.2085137

Herhausen, D., Kleinlercher, K., Verhoef, P. C., Emrich, O., & Rudolph, T. (2019). Loyalty Formation for Different Customer Journey Segments. Journal of Retailing, 95(3), 9–29. https://doi.org/10.1016/j.jretai.2019.05.001

Hernando-Cuñado, J., Colvin-Díez, J., & Enríquez-Román, J. (2019). Mercadona – A successful business case. Academicus International Scientific Journal, 20, 128–141. https://doi.org/10.7336/academicus.2019.20.10

Holyoak, K. J. (1991). Symbolic connectionism: Toward third-generation theories of expertise. In K. A. Ericsson & J. Smith (Eds.), Toward a general theory of expertise: Prospects and limits (pp. 301–335). Cambridge University Press.

Jiao, C., & Hu, B. (2022). Showrooming, webrooming, and operational strategies for competitiveness. Production and Operations Management, 31(8), 3217–3232. https://doi.org/10.1111/poms.13747

Kamboj, S., & Gupta, S. (2020). Use of smart phone apps in co-creative hotel service innovation: An evidence from India. Current Issues in Tourism, 23(3), 323–344. https://doi.org/10.1080/13683500.2018.1513459

Kondo, F. N., & Okubo, T. (2022). Understanding multi-channel consumer behavior: A comparison between segmentations of multi-channel purchases by product category and overall products. Journal of Retailing and Consumer Services, 64, Article 102792. https://doi.org/10.1016/j.jretconser.2021.102792

Konuş, 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

Kumar, V., & Venkatesan, R. (2005). Who are the multichannel shoppers and how do they perform? Correlates of multichannel shopping behavior. Journal of Interactive Marketing, 19(2), 44–62. https://doi.org/10.1002/dir.20034

Kwon, O., Singh, T., & Kim, S. (2023). The competing roles of variety seeking in new brand adoption. Journal of Retailing and Consumer Services, 72, Article 103283. https://doi.org/10.1016/j.jretconser.2023.103283

Lindquist, J. D., & Kaufman-Scarborough, C. J. (2007). The polychronic-monochronic tendency model: PMTS scale development and validation. Time & Society, 16(2–3), 253–285. https://doi.org/10.1177/0961463X07080270

Lovett, M. C., & Schunn, C. D. (1999). Task representations, strategy variability, and base-rate neglect. Journal of Experimental Psychology: General, 128(2), 107–130. https://doi.org/10.1037/0096-3445.128.2.107

Mahatanankoon, P. (2007). The effects of personality traits and optimum stimulation level on text-messaging activities and m-commerce intention. International Journal of Electronic Commerce, 12(1), 7–30. https://doi.org/10.2753/JEC1086-4415120101

Martenson, R. (2018). Curiosity motivated vacation destination choice in a reward and variety-seeking perspective. Journal of Retailing and Consumer Services, 41, 70–78. https://doi.org/10.1016/j.jretconser.2017.11.009

Menon, S., & Kahn, B. E. (1995). The impact of context on variety seeking in product choices. Journal of Consumer Research, 22(3), 285–295. https://doi.org/10.1086/209450

Mishra, R., Singh, R. K., & Koles, B. (2021). Consumer decision-making in omnichannel retailing: Literature review and future research agenda. International Journal of Consumer Studies, 45(2), 147–174. https://doi.org/10.1111/ijcs.12617

Mittelstaedt, R. A., Grossbart, S. L., Curtis, W. W., & DeVere, S. P. (1976). Optimal stimulation level and the adoption decision process. Journal of Consumer Research, 3(2), 84–94. https://doi.org/10.1086/208655

Mladenow, A., Mollova, A., & Strauss, C. (2018). Mobile technology contributing to omni-channel retail. In Proceedings of the 16th International Conference on Advances in Mobile Computing and Multimedia (pp. 92–101). https://doi.org/10.1145/3282353.3282371

Mohan, G., Sivakumaran, B., & Sharma, P. (2012). Store environment’s impact on variety seeking behavior. Journal of Retailing and Consumer Services, 19(4), 419–428. https://doi.org/10.1016/j.jretconser.2012.04.003

Montaguti, E., Neslin, S. A., & Valentini, S. (2015). Can marketing campaigns induce multichannel buying and more profitable customers? A field experiment. Marketing Science, 35(2), 201–217. https://doi.org/10.1287/mksc.2015.0923

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

Papagiannidis, S., Alamanos, E., Bourlakis, M., & Dennis, C. (2023). The pandemic consumer response: A stockpiling perspective and shopping channel preferences. British Journal of Management, 34(2), 664–691. https://doi.org/10.1111/1467-8551.12616

Papatla, P., & Bhatnagar, A. (2002). Shopping style segmentation of consumers. Marketing Letters, 13(2), 91–106. https://doi.org/10.1023/A:1016089718390

Polites, G. L., & Karahanna, E. (2012). Shackled to the status quo: The inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly, 36(1), 21–42. https://doi.org/10.2307/41410404

Porter, C. O. L. H., Outlaw, R., Gale, J. P., & Cho, T. S. (2019). The use of online panel data in management research: A review and recommendations. Journal of Management, 45(1), 319–344. https://doi.org/10.1177/0149206318811569

Quach, S., Barari, M., Moudrý, D. V., & Quach, K. (2022). Service integration in omnichannel retailing and its impact on customer experience. Journal of Retailing and Consumer Services, 65, Article 102267. https://doi.org/10.1016/j.jretconser.2020.102267

Raju, P. S. (1980). Optimum stimulation level: Its relationship to personality, demographics, and exploratory behavior. Journal of Consumer Research, 7(3), 272–282. https://doi.org/10.1086/208815

Rohm, A. J., & Swaminathan, V. (2004). A typology of online shoppers based on shopping motivations. Journal of Business Research, 57(7), 748–757. https://doi.org/10.1016/S0148-2963(02)00351-X

Saha, K., & Bhattacharya, S. (2020). Look before you leap: Economics of being an omnichannel retailer. Operations and Supply Chain Management, 13(3), 256–268. https://doi.org/10.31387/oscm0420267

Segovia, M., Grashuis, J., & Skevas, T. (2021). Consumer preferences for grocery purchasing during the COVID-19 pandemic: A quantile regression approach. British Food Journal, 124(11), 3595–3623. https://doi.org/10.1108/BFJ-05-2021-0474

Sipior, J. C., Ward, B. T., & Volonino, L. (2014). Privacy concerns associated with smartphone use. Journal of Internet Commerce, 13(3–4), 177–193. https://doi.org/10.1080/15332861.2014.947902

Srivastava, J., Nakazawa, M., & Chen, Y.-W. (2016). Online, mixed, and offline media multitasking: Role of cultural, socio-demographic, and media factors. Computers in Human Behavior, 62, 720–729. https://doi.org/10.1016/j.chb.2016.04.040

Stafford, T. F., Stafford, M. R., & Schkade, L. L. (2004). Determining uses and gratifications for the Internet. Decision Sciences, 35(2), 259–288. https://doi.org/10.1111/j.00117315.2004.02524.x

Steenkamp, J.-B. E. M., & Baumgartner, H. (1992). The role of optimum stimulation level in exploratory consumer behavior. Journal of Consumer Research, 19(3), 434–448. https://doi.org/10.1086/209313

Trivedi, M. (1999). Using variety-seeking-based segmentation to study promotional response. Journal of the Academy of Marketing Science, 27(1), 37–49. https://doi.org/10.1177/0092070399271003

Truong, D., & Truong, M. D. (2022). How do customers change their purchasing behaviours during the COVID-19 pandemic? Journal of Retailing and Consumer Services, 67, Article 102963. https://doi.org/10.1016/j.jretconser.2022.102963

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(2), 174–181. https://doi.org/10.1016/j.jretai.2015.02.005

Wang, Q., Yang, X., Song, P., & Sia, C. L. (2014). Consumer segmentation analysis of multichannel and multistage consumption: A latent class MNL approach. Journal of Electronic Commerce Research, 15(4), 339–358. https://web.csulb.edu/journals/jecr/issues/20144/Paper5.pdf

Yurova, Y., Rippé, C. B., Weisfeld-Spolter, S., Sussan, F., & Arndt, A. (2017). Not all adaptive selling to omni-consumers is influential: The moderating effect of product type. Journal of Retailing and Consumer Services, 34, 271–277. https://doi.org/10.1016/j.jretconser.2016.01.009