The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Who are the multichannel shoppers and how do they perform?: Correlates of multichannel shopping behavior
Abstract
We develop a conceptual framework, which identifies the customer-level characteristics and supplier factors that are associated with purchase behavior across multiple channels. We also propose that multichannel shoppers provide benefits as measured by several customer-based metrics. We conduct an empirical analysis of our propositions using the customer database of a high technology hardware and software manufacturer. We find that customers who buy across multiple product categories, initiate more contacts with the firm, have past experience with the supplier through the online channel, have longer tenure, purchase more frequently, are larger and receive communication from the supplier through multiple communication channels, especially through highly interpersonal channels. We also find evidence for a nonlinear relationship between returns and multichannel shopping, and that there is a positive synergy towards multichannel shopping when customers are contacted through various communication channels. Customers who shop across multiple transaction channels provide higher revenues, higher share of wallet, have higher past customer value, and have a higher likelihood of being active than other customers.We derive several implications for managers who wish to target customers for a multichannel strategy.
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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
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Cited by
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
Managing Marketing Communications with Multichannel Customers
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Cross-buying in retailing: Drivers and consequences
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Self-citationYang, S., Lu, Y., & Chau, P. Y. K. (2013) · Decision Support Systems · doi:10.1016/j.dss.2012.09.011 · Cited by 112
A Review of Consumer-Facing Digital Technologies Across Different Types of Fashion Store Formats
Bonetti, F., & Perry, P. (2017) · Advances in Business Information Systems and Analytics · doi:10.4018/978-1-5225-1865-5.ch006 · Cited by 41
Reimer, K., & Becker, J. U. (2015) · Management Review Quarterly · doi:10.1007/s11301-014-0110-z · Cited by 11
Developing an Instrument to Measure Consumers' Multimedia Usage in the Purchase Process
Voorveld, H. A. M., Bronner, F. E., Neijens, P. C., & Smit, E. G. (2013) · International Journal on Media Management · doi:10.1080/14241277.2012.756815 · Cited by 10
(2014) · Electronic Journal of e-Government · Cited by 9
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Metadata
- Authors
- Kumar, V., & Venkatesan, R.
- Venue
- Journal of Interactive Marketing
- Publisher
- SAGE Publications
- Published
- 2005-05
- Volume
- 19
- Issue
- 2
- Pages
- 44-62
- ISSN
- 1094-9968 (ISSN-L)
- 1520-6653
- OpenAlex
- W2113879048
- Cited by
- 513
- References
- 4
- FWCI
- 57.22
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
