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‘Online Omnivores’ or ‘Willing but struggling’? Identifying online grocery shopping behavior segments using attitude theory

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  • Brand, Christian
  • Schwanen, Tim
  • Anable, Jillian

Abstract

The landscape of grocery shopping is changing fast. Online retailing via home delivery or ‘click and collect’, convenience stores and various hybrid shopping channels are gaining popularity with some consumers, but not with others. The central premise of this paper is that focusing on the ‘average grocery shopper’ is not very helpful if the objective is to understand recent and future changes in grocery shopping. There are few recent studies that have identified groups of individuals using online and multi-channel shopping by considering both observable behavior and associated attitudes – feelings, beliefs, opinions and behavioral dispositions – and by drawing explicitly on attitude theories from social psychology. The current paper thus aims to identify and describe groups of grocery shoppers using a psychographic segmentation approach that is explicitly grounded in the Theory of Planned Behavior (TPB) (Ajzen, 1991) and its close cousin, the Technology Acceptance Model (TAM) (Davis et al., 1989). Primary data were collected through a self-completion questionnaire that produced a largely representative study sample of 2032 grocery shoppers across the United Kingdom, Europe's largest market for online grocery shopping. A principal component and two stage cluster analysis methodology was implemented to identify five well-defined and highly interpretable segments according to their attitudes, norms, perceptions and beliefs, then profiled by their socio-economic and grocery shopping characteristics. The segments reveal a range of different grocery shopping preference levels, from those ‘super-shoppers’ (Flynn and Goldsmith, 2016) who are clearly attracted to the online experience and want more (‘Intensive Urbanites’, ‘Online Omnivores’) to those who appear resistant and socially responsible towards the adoption of online shopping services (‘Resisting and Responsible’). The key distinguishing features of these segments suggest that shoppers might be attracted to or repelled from online shopping for reasons of convenience, perceived benefits, costs and risks, technology affect, time pressures and fit into daily schedules (perceived behavioral control), as well as social and environmental dimensions of personal norms and beliefs.

Suggested Citation

  • Brand, Christian & Schwanen, Tim & Anable, Jillian, 2020. "‘Online Omnivores’ or ‘Willing but struggling’? Identifying online grocery shopping behavior segments using attitude theory," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
  • Handle: RePEc:eee:joreco:v:57:y:2020:i:c:s0969698918306313
    DOI: 10.1016/j.jretconser.2020.102195
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    as
    1. Farag, Sendy & Schwanen, Tim & Dijst, Martin & Faber, Jan, 2007. "Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(2), pages 125-141, February.
    2. Babin, Barry J & Darden, William R & Griffin, Mitch, 1994. "Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(4), pages 644-656, March.
    3. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    4. van Wee, Bert & De Vos, Jonas & Maat, Kees, 2019. "Impacts of the built environment and travel behaviour on attitudes: Theories underpinning the reverse causality hypothesis," Journal of Transport Geography, Elsevier, vol. 80(C).
    5. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    6. Nakano, Satoshi & Kondo, Fumiyo N., 2018. "Customer segmentation with purchase channels and media touchpoints using single source panel data," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 142-152.
    7. Rohm, Andrew J. & Swaminathan, Vanitha, 2004. "A typology of online shoppers based on shopping motivations," Journal of Business Research, Elsevier, vol. 57(7), pages 748-757, July.
    8. Oecd, 1999. "Economic and Social Impact of E-commerce: Preliminary Findings and Research Agenda," OECD Digital Economy Papers 40, OECD Publishing.
    9. Midgley, David F & Dowling, Grahame R, 1978. "Innovativeness: The Concept and Its Measurement," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 4(4), pages 229-242, March.
    10. Mortimer, Gary & Weeks, Clinton S., 2019. "How unit price awareness and usage encourages grocery brand switching and expenditure," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 346-356.
    11. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    12. Golob, Thomas F., 2001. "Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(6), pages 495-514, July.
    13. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
    14. Bruno Durand & Jesus Gonzalez-Feliu, 2012. "Urban Logistics and E-Grocery: Have Proximity Delivery Services a Positive Impact on Shopping Trips? [Logistique urbaine et épicerie en ligne : les services de livraison de proximité ont-ils un imp," Post-Print hal-01770406, HAL.
    15. Patricia L Mokhtarian & David T Ory & Xinyu Cao, 2009. "Shopping-Related Attitudes: A Factor and Cluster Analysis of Northern California Shoppers," Environment and Planning B, , vol. 36(2), pages 204-228, April.
    16. Suel, Esra & Polak, John W., 2017. "Development of joint models for channel, store, and travel mode choice: Grocery shopping in London," Transportation Research Part A: Policy and Practice, Elsevier, vol. 99(C), pages 147-162.
    17. Lee, Richard J. & Sener, Ipek N. & Mokhtarian, Patricia L. & Handy, Susan L., 2017. "Relationships between the online and in-store shopping frequency of Davis, California residents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 40-52.
    18. Chi, Ting, 2018. "Understanding Chinese consumer adoption of apparel mobile commerce: An extended TAM approach," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 274-284.
    19. Sands, Sean & Ferraro, Carla & Campbell, Colin & Pallant, Jason, 2016. "Segmenting multichannel consumers across search, purchase and after-sales," Journal of Retailing and Consumer Services, Elsevier, vol. 33(C), pages 62-71.
    20. Elms, Jonathan & de Kervenoael, Ronan & Hallsworth, Alan, 2016. "Internet or store? An ethnographic study of consumers' internet and store-based grocery shopping practices," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 234-243.
    21. Kroesen, Maarten & Handy, Susan & Chorus, Caspar, 2017. "Do attitudes cause behavior or vice versa? An alternative conceptualization of the attitude-behavior relationship in travel behavior modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 190-202.
    22. Konuş, Umut & Verhoef, Peter C. & Neslin, Scott A., 2008. "Multichannel Shopper Segments and Their Covariates," Journal of Retailing, Elsevier, vol. 84(4), pages 398-413.
    23. Tang, Wei & Mokhtarian, Patricia L, 2009. "Accounting for Taste Heterogeneity in Purchase Channel Intention Modeling: An Example from Northern California for Book Purchases," Institute of Transportation Studies, Working Paper Series qt9mg5s5g8, Institute of Transportation Studies, UC Davis.
    24. Suri, Rajneesh & Monroe, Kent B, 2003. "The Effects of Time Constraints on Consumers' Judgments of Prices and Products," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(1), pages 92-104, June.
    25. Doti, James L & Sharir, Shumel, 1981. "Households' Grocery Shopping Behavior in the Short-Run: Theory and Evidence," Economic Inquiry, Western Economic Association International, vol. 19(2), pages 196-208, April.
    26. Chu, Junhong & Arce-Urriza, Marta & Cebollada-Calvo, José-Javier & Chintagunta, Pradeep K., 2010. "An Empirical Analysis of Shopping Behavior Across Online and Offline Channels for Grocery Products: The Moderating Effects of Household and Product Characteristics," Journal of Interactive Marketing, Elsevier, vol. 24(4), pages 251-268.
    27. Xinyu Cao & Zhiyi Xu & Frank Douma, 2012. "The interactions between e-shopping and traditional in-store shopping: an application of structural equations model," Transportation, Springer, vol. 39(5), pages 957-974, September.
    28. Marko Sarstedt & Erik Mooi, 2014. "A Concise Guide to Market Research," Springer Texts in Business and Economics, Springer, edition 2, number 978-3-642-53965-7, June.
    29. Anable, Jillian, 2005. "'Complacent Car Addicts' or 'Aspiring Environmentalists'? Identifying travel behaviour segments using attitude theory," Transport Policy, Elsevier, vol. 12(1), pages 65-78, January.
    30. Ganesh, Jaishankar & Reynolds, Kristy E. & Luckett, Michael & Pomirleanu, Nadia, 2010. "Online Shopper Motivations, and e-Store Attributes: An Examination of Online Patronage Behavior and Shopper Typologies," Journal of Retailing, Elsevier, vol. 86(1), pages 106-115.
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    2. Yusuf Arslan & Aykut Hamit Turan, 2022. "Consumers' Acceptance of Online Grocery Shopping in a Pandemic Situation: An Extended Technology Acceptance Model Perspective," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 8(2), pages 143-158.
    3. Vakulenko, Yulia & Arsenovic, Jasenko & Hellström, Daniel & Shams, Poja, 2022. "Does delivery service differentiation matter? Comparing rural to urban e-consumer satisfaction and retention," Journal of Business Research, Elsevier, vol. 142(C), pages 476-484.
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