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Shopping-Related Attitudes: A Factor and Cluster Analysis of Northern California Shoppers

Author

Listed:
  • Patricia L Mokhtarian

    (Department of Civil and Environmental Engineering, and Institute of Transportation Studies, University of California, Davis, CA 95616, USA)

  • David T Ory

    (Parsons Brinckerhoff, 1401 K Street, NW, Suite 701, Washington, DC 20005, USA)

  • Xinyu Cao

    (Humphrey Institute of Public Affairs, University of Minnesota, 301 19th Avenue South, Minneapolis, MN 55455, USA)

Abstract

This paper presents an analysis of general shopping and travel-related attitudes collected from a custom-designed Internet-based survey conducted in the spring of 2006, of randomly selected residents of two communities in Northern California. These and other data collected in the survey will eventually lead to models of shopping mode (channel) choice, intention, and frequency among other analyses. In this early examination of the data ( N = 966), exploratory factor analysis is performed to identify the conceptual constructs underlying a group of forty-two general shopping-related attitudinal statements, with which respondents agreed or disagreed on a five-point Likert-type scale. From the nineteen potential constructs identified in the design stage, thirteen dimensions emerged empirically: shopping and store enjoyment, price and time consciousness, impulse buying, materialism, trust, caution, trendsetting, and opinions with respect to credit card usage, technology, exercise, and the environment. Cluster analysis is then conducted to identify seven market segments having different attitudinal profiles: store shopaholics (15%), bichannel shopaholics (14%), time-starved worriers (16%), nonmaterialistic greens (16%), unwired antishoppers (14%), practical and leisure-oriented (13%), and technoconservatives (11%). These segments differ significantly, in logical ways, on a number of sociodemographic and other characteristics, including shopping channel choices. Thus, more detailed investigations of choice behavior using these market segments should prove fruitful.

Suggested Citation

  • 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.
  • Handle: RePEc:sae:envirb:v:36:y:2009:i:2:p:204-228
    DOI: 10.1068/b34015t
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    References listed on IDEAS

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    1. Cao, Xinyu & Mokhtarian, Patricia L., 2005. "The Intended and Actual Adoption of Online Purchasing: A Brief Review of Recent Literature," University of California Transportation Center, Working Papers qt5z75n416, University of California Transportation Center.
    2. Marios Koufaris, 2002. "Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior," Information Systems Research, INFORMS, vol. 13(2), pages 205-223, June.
    3. Ory, David T & Mokhtarian, Patricia L, 2007. "Description of a Northern California Shopping Survey Data Collection Effort," Institute of Transportation Studies, Working Paper Series qt39w9w743, Institute of Transportation Studies, UC Davis.
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    Cited by:

    1. Xi, Guangliang & Cao, Xinyu & Zhen, Feng, 2020. "The impacts of same day delivery online shopping on local store shopping in Nanjing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 35-47.
    2. Becky P. Y. Loo & Bo Wang, 2018. "Factors associated with home-based e-working and e-shopping in Nanjing, China," Transportation, Springer, vol. 45(2), pages 365-384, March.
    3. 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).
    4. Colaço, Rui & de Abreu e Silva, João, 2022. "Exploring the e-shopping geography of Lisbon: Assessing online shopping adoption for retail purchases and food deliveries using a 7-day shopping survey," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    5. Qing Zhai & Xinyu Cao & Patricia L. Mokhtarian & Feng Zhen, 2017. "The interactions between e-shopping and store shopping in the shopping process for search goods and experience goods," Transportation, Springer, vol. 44(5), pages 885-904, September.
    6. Minh Hieu Nguyen & Jimmy Armoogum & Binh Nguyen Thi, 2021. "Factors Affecting the Growth of E-Shopping over the COVID-19 Era in Hanoi, Vietnam," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
    7. Al Haddad, Christelle & Chaniotakis, Emmanouil & Straubinger, Anna & Plötner, Kay & Antoniou, Constantinos, 2020. "Factors affecting the adoption and use of urban air mobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 696-712.
    8. Patricia L. Mokhtarian & Wei (Laura) Tang, 2013. "Trivariate probit models of pre-purchase/purchase shopping channel choice: clothing purchases in Northern California," Chapters, in: Stephane Hess & Andrew Daly (ed.), Choice Modelling, chapter 12, pages 243-273, Edward Elgar Publishing.
    9. Schmid, Basil & Axhausen, Kay W., 2019. "In-store or online shopping of search and experience goods: A hybrid choice approach," Journal of choice modelling, Elsevier, vol. 31(C), pages 156-180.
    10. 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 qt3v25m8dc, Institute of Transportation Studies, UC Davis.
    11. Oleksandr Rossolov & Yusak O. Susilo, 2023. "Are consumers ready to pay extra for crowd-shipping e-groceries and why? A hybrid choice analysis for developing economies," Papers 2303.07044, arXiv.org.
    12. Basil Schmid & Milos Balac & Kay W. Axhausen, 2019. "Post-Car World: data collection methods and response behavior in a multi-stage travel survey," Transportation, Springer, vol. 46(2), pages 425-492, April.
    13. Shah, Harsh & Carrel, Andre L. & Le, Huyen T.K., 2021. "What is your shopping travel style? Heterogeneity in US households’ online shopping and travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 83-98.
    14. Jonas De Vos & Patricia L. Mokhtarian & Tim Schwanen & Veronique Van Acker & Frank Witlox, 2016. "Travel mode choice and travel satisfaction: bridging the gap between decision utility and experienced utility," Transportation, Springer, vol. 43(5), pages 771-796, September.
    15. Kim, Sung Hoo & Circella, Giovanni & Mokhtarian, Patricia L., 2019. "Identifying latent mode-use propensity segments in an all-AV era," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 192-207.
    16. 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.

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