The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Multichannel Shopping: Causes and Consequences
Abstract
The authors explore the drivers of multichannel shopping and the impact of multichannel shopping on customer profitability. Through a longitudinal analysis, the authors provide evidence that multichannel shopping is associated with higher customer profitability. Using the social exchange theory, they develop hypotheses regarding the impact of several customer–firm interaction characteristics on customer channel adoption duration. They propose a shared-frailty hazard model for testing the proposed hypotheses. They use the customer database of an apparel manufacturer that sells through three distinct channels for the empirical analysis and find that frequency-related interaction characteristics have the greatest influence on second-channel adoption duration. In contrast, proportion of returns, a purchase-related interaction characteristic, has the greatest influence on third-channel adoption duration. Variation across customers in purchase-related attributes has a greater impact on the duration to adopt the second channel than the duration to adopt the third channel. In contrast, variation across customers in the channel-related attributes has a greater impact on the third-channel adoption duration than on the second-channel adoption duration. The customer–firm interaction characteristics identified in this study and the proposed model framework allow for forward-looking allocation of multichannel marketing resources.
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Cites
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A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy
Venkatesan, R., & Kumar, V. (2004) · Journal of Marketing · doi:10.1509/jmkg.68.4.106.42728 · Cited by 948
Self-citationCausality: Some Statistical Aspects
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Cited by
Understanding customer experience throughout the customer journey
Lemon, K. N., & Verhoef, P. C. (2016) · Journal of Marketing · doi:10.1509/jm.15.0420 · Cited by 5,765
Multichannel customer management: Understanding the research-shopper phenomenon.
Verhoef, P. C., Neslin, S. A., & Vroomen, B. (2007) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2006.11.002 · Cited by 999
Multichannel Shopper Segments and Their Covariates☆
KONUS, U., VERHOEF, P., & NESLIN, S. (2008) · Journal of Retailing · doi:10.1016/j.jretai.2008.09.002 · Cited by 577
On the Go: how mobile shopping affects customer purchase behavior.
Wang, R. J.-H., Malthouse, E. C., & Krishnamurthi, L. (2015) · Journal of Retailing · doi:10.1016/j.jretai.2015.01.002 · Cited by 559
Adding Bricks to Clicks: Predicting the Patterns of Cross-Channel Elasticities over Time
Avery, J., Steenburgh, T. J., Deighton, J., & Caravella, M. (2012) · Journal of Marketing · doi:10.1509/jm.09.0081 · Cited by 533
Metadata
- Authors
- Venkatesan, R., Kumar, V., & Ravishanker, N.
- Venue
- Journal of Marketing
- Publisher
- SAGE Publications
- Published
- 2007-04
- Volume
- 71
- Issue
- 2
- Pages
- 114-132
- ISSN
- 0022-2429 (ISSN-L)
- 1547-7185
- OpenAlex
- W2026181095
- Cited by
- 393
- References
- 9
- FWCI
- 60.26
- Type
- journal article
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.