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Electronic Commerce Research
Erschienen in: Electronic Commerce Research 4/2018

09.11.2017

Influence of individual characteristics on whether and how much consumers engage in showrooming behavior

verfasst von: Wirawan Dony Dahana, HeeJae Shin, Sotaro Katsumata

Erschienen in: Electronic Commerce Research | Ausgabe 4/2018

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Abstract

This article investigates a set of individual characteristics that can explain whether and how much a consumer engages in showrooming behavior. The authors conceptualized and empirically examined certain variables’ impact on both showrooming probability as well as the extent of behavior. The variables under consideration include consumers’ involvement, prior knowledge, perceived risk, price consciousness, Internet usage, access device usage, and certain demographic variables. The results reveal that involvement and price consciousness significantly explain whether a consumer is a potential showroomer. Further, showrooming frequency is found to be affected by prior knowledge, perceived risk, price consciousness, Internet usage, access devise usage, and age. Some implications are discussed regarding how retailers can handle showrooming.
Nächster Artikel Does friendship quality matter in social commerce? An experimental study of its effect on purchase intention

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Fußnoten
1
Note that our hypotheses imply that each \(\beta_{j}\) has the opposite sign with the respective \(\gamma_{j}\) for \(j \ge 1\).
 
2
We find that the result is considerably sensitive to the exclusion of the outliers. The results of a likelihood ratio test revealed that the model’s accuracy significantly increased after we omitted the outliers from the analysis.
 
3
This can be calculated using Eq. (5).
 
4
We thank an anonymous reviewer for pointing out this policy.
 
5
This can be accomplished by using the expected showrooming frequency conditional on customer characteristics, or \(E(y_{i} ) = (1 - p_{i} )\lambda_{i}\). The small and large values of \(E(y_{i} )\) correspond to occasional and frequent showroomers, respectively.
 
Literatur
1.
Blattberg, R. C., Kim, B., & Neslin, S. A. (2008). Database marketing: analyzing and managing customers, international series in quantitative marketing. New York, NY: Springer.CrossRef
2.
Verhoef, P. C., Neslin, S. A., & Vroomen, B. (2007). Multichannel customer management: Understanding the research-shopper phenomenon. International Journal of Research in Marketing, 24(2), 129–148.CrossRef
3.
Quint, M., Rogers, D., & Ferguson, R. (2013). Showrooming and the rise of the mobile-assisted shopper. New York, NY: Columbia Business School Center on Global Brand Leadership.
4.
5.
Rapp, A., Baker, T. L., Bachrach, D. G., Ogilvie, J., & Beitelspacher, L. S. (2015). Perceived customer showrooming behavior and the effect on retail salesperson self-efficacy and performance. Journal of Retailing, 91(2), 358–369.CrossRef
6.
Brown, T. A., Friedman, D. C., & Taran, Z. (2013). Showrooming and the small retailer. Proceedings of marketing and management association, pp. 46–48.
7.
8.
Zimmerman, A., & Mattioli, D. (2012). Retailers’ new odd couple. Wall Street Journal, July 11, B1.
9.
Bandura, A. (1991). Social cognitive theory of self-regulation. Organizational Behavior and Human Decision Processes, 50(2), 248–287.CrossRef
10.
Herhausen, D., Binder, J., Schoegel, M., & Herrmann, A. (2015). Integrating bricks with clicks: Retailer-level and channel-level outcomes of online-offline channel integration. Journal of Retailing, 91(2), 309–325.CrossRef
11.
Neslin, S. A., Grewal, D., Leghorn, R., Shankar, V., Teerling, M. L., Thomas, J. S., et al. (2006). Challenges and opportunities in multichannel customer management. Journal of Service Research, 9(2), 95–112.CrossRef
12.
Ansari, A., Mela, C. F., & Neslin, S. A. (2008). Customer channel migration. Journal of Marketing Research, 45(1), 60–76.CrossRef
13.
Thomas, J. S., & Sullivan, U. Y. (2005). Managing marketing communications with multichannel customers. Journal of Marketing, 69(4), 239–251.CrossRef
14.
Montoya-Weiss, M. M., Voss, G. B., & Grewal, D. (2003). Determinants of online channel use and overall satisfaction with a relational, multichannel service provider. Journal of the Academy of Marketing Science, 31(4), 448–458.CrossRef
15.
Zhou, L., Dai, L., & Zhang, D. (2007). Online shopping acceptance model—A critical survey of consumer factors in online shopping. Journal of Electronic Commerce Research, 8(1), 41–62.
16.
Higgins, E. T. (2000). Making a good decision: Value from fit. American Psychologist, 55(11), 12–17.CrossRef
17.
Higgins, E. T. (2005). Value from regulatory fit. Current Directions in Psychological Science, 14(4), 209–213.CrossRef
18.
Clarke, K., & Belk, R. W. (1978). Product involvement and task definition on anticipated consumer effort. Advances of Consumer Research, 5, 313–318.
19.
Bloch, P. H., & Richins, M. L. (1983). A theoretical model for the study of product importance perceptions. Journal of Marketing, 47, 69–81.CrossRef
20.
Bloch, P. H., Sherrell, D. L., & Ridgway, N. M. (1986). Consumer search: An extended framework. Journal of Consumer Research, 13(1), 119–126.CrossRef
21.
Moore, W. L., & Lehmann, D. R. (1980). Individual differences in search behavior for a nondurable. Journal of Consumer Research, 7(3), 296–307.CrossRef
22.
Srinivasan, N., & Ratchford, B. T. (1991). An empirical test of a model of external search for automobiles. Journal of Consumer Research, 18(2), 233–242.CrossRef
23.
Beatty, S. E., & Smith, S. M. (1987). External search effort: An investigation across several product categories. Journal of Consumer Research, 14(1), 83–95.CrossRef
24.
Moorthy, S., Ratchford, B. T., & Talukdar, D. (1997). Consumer information search revisited: Theory and empirical analysis. Journal of Consumer Research, 23(4), 263–277.CrossRef
25.
Alba, W., & Hutchinson, J. W. (1987). Dimensions of consumer expertise. Journal of Consumer Research, 13(4), 411–454.CrossRef
26.
Rao, A. R., & Monroe, K. B. (1988). The moderating effect of prior knowledge on cue utilization in product evaluations. Journal of Consumer Research, 15(2), 253–264.CrossRef
27.
Brucks, M. (1985). The effects of product class knowledge on information search behavior. Journal of Consumer Research, 12(1), 1–16.CrossRef
28.
Johnson, E. J., & Russo, J. E. (1984). Product familiarity and learning new information. Journal of Consumer Research, 11(1), 542–550.CrossRef
29.
Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 14(3), 350–362.CrossRef
30.
Punj, G., & Staelin, R. (1983). A model of consumer information search behavior for new automobiles. Journal of Consumer Research, 9(4), 366–380.CrossRef
31.
Urbany, J., Dickson, P., & Wilkie, W. (1989). Buyer uncertainty and information search. Journal of Consumer Research, 16(2), 208–215.CrossRef
32.
Mitchell, A. A., & Dacin, P. A. (1996). The assessment of alternative measures of consumer expertise. Journal of Consumer Research, 23(3), 219–239.CrossRef
33.
Forsythe, S. M., Kim, J. O., & Petee, T. (2002). Modeling consumer behavior in on-line environments. National Textile Center Annual Report, pp. 1–10.
34.
Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business Research, 56(11), 867–875.CrossRef
35.
Lee, K. S., & Tan, S. J. (2003). E-retailing versus physical retailing: A theoretical model and empirical test of consumer choice. Journal of Business Research, 56(11), 877–885.CrossRef
36.
Tan, S. J. (1999). Strategies for reducing consumers’ risk aversion in Internet shopping. The Journal of Consumer Marketing, 16(2), 163–178.CrossRef
37.
Bhatnagar, A., Misra, S., & Rao, H. R. (2000). On risk, convenience, and Internet shopping behavior. Communications of the ACM, 43(11), 98–105.CrossRef
38.
Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.CrossRef
39.
Donthu, N., & Garcia, A. (1999). The Internet shopper. Journal of Advertising Research, 39(3), 52–58.
40.
Lichtenstein, D. R., Bloch, P. H., & Black, W. C. (1988). Correlates of price acceptability. Journal of Consumer Research, 15(2), 243–252.CrossRef
41.
Lichtenstein, D. R., Ridgway, N. M., & Netemeyer, R. G. (1993). Price perceptions and consumer shopping behavior: A field study. Journal of Marketing Research, 30(May), 234–245.CrossRef
42.
Kukar-Kinney, M. (2006). The role of price-matching characteristics in influencing store loyalty. Journal of Business Research, 59(4), 475–482.CrossRef
43.
Citrin, A. V., Sprott, D. E., Silverman, S. N., & Stem, D. E., Jr. (2000). Adoption of Internet shopping: The role of consumer innovativeness. Industrial Management & Data Systems, 100(7), 294–300.CrossRef
44.
Liao, Z., & Cheung, M. T. (2001). Internet-based e-shopping and consumer attitudes: An empirical study. Information & Management, 38(5), 299–306.CrossRef
45.
Häubl, G., & Trifts, V. (2000). Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing Science, 19(1), 4–21.CrossRef
46.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: Conceptual foundations. Journal of Marketing, 60(July), 50–68.CrossRef
47.
Huang, M. (2003). Modeling virtual exploratory and shopping dynamics: An environmental psychology approach. Information & Management, 41(1), 39–47.CrossRef
48.
Lynch, P. D., Kent, R. J., & Srinivasan, S. S. (2001). The global Internet shopper: Evidence from shopping tasks in twelve countries. Journal of Advertising Research, 41(3), 15–24.CrossRef
49.
50.
Garbarino, E., & Strahilevitz, M. (2004). Gender differences in the perceived risk of buying online and the effects of receiving a site recommendation. Journal of Business Research, 57(7), 768–775.CrossRef
51.
Sheehan, K. B. (1999). An investigation of gender differences in on-line privacy concerns and resultant behaviors. Journal of Interactive Marketing, 13(4), 24–38.CrossRef
52.
Liebermann, Y., & Stashevsky, S. (2002). Perceived risks as barriers to Internet and e-commerce usage. Qualitative Market Research: An International Journal, 5(4), 291–300.CrossRef
53.
Andreasen, A. R. (1984). Life status changes and changes in consumer preferences and satisfaction. Journal of Consumer Research, 11(3), 784–794.CrossRef
54.
Shim, S., & Drake, M. F. (1990). Consumer intention to utilize electronic shopping: The Fishbein behavioral intention model. Journal of Direct Marketing, 4(3), 22–33.CrossRef
55.
Cole, C. A., & Balasubramanian, S. K. (1993). Age differences in consumers’ search for information: Public policy implications. Journal of Consumer Research, 20(1), 157–169.CrossRef
56.
Forsythe, S. M., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of Interactive Marketing, 20(2), 55–75.CrossRef
57.
Lee, M. K. O., & Turban, E. (2001). A trust model for consumer Internet shopping. International Journal of Electronic Commerce, 6(1), 75–91.CrossRef
58.
Wang, R. J., Malthouse, E. C., & Krishnamurthi, L. (2015). On the go: How mobile shopping affects customer purchase behavior. Journal of Retailing, 91(2), 217–234.CrossRef
59.
Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14.CrossRef
60.
Lastovicka, J. L., & Gradner, D. M. (1979). Components of involvement. In J. C. Maloney & B. Silverman (Eds.), Attitude research plays for high stakes (pp. 53–73). Chicago, IL: American Marketing Association.
61.
Laurent, G., & Kapferer, J. (1985). Measuring consumer involvement profiles. Journal of Marketing Research, 22, 41–53.CrossRef
62.
Jain, K., & Srinivasan, N. (1990). An empirical assessment of multiple operationalizations of involvement. In M. Goldberg, G. Gorn, & R. Pollay (Eds.), Advances in consumer research (Vol. 17, pp. 594–602). Provo, UT: Association for Consumer Research.
63.
Flynn, L. R., & Goldsmith, R. E. (1999). A short, reliable measure of subjective knowledge. Journal of Business Research, 46(1), 57–66.CrossRef
64.
Vuong, Q. H. (1989). Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica: Journal of the Econometric Society, 57(2), 307–333.CrossRef
65.
Kline, P. (2000). The handbook of psychological testing (2nd ed.). London: Routledge.
66.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis with readings. Upper Saddle River, NJ: Prentice-Hall.
67.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.CrossRef
68.
Smith, K. T. (2011). Digital marketing strategies that millennials find appealing, motivating, or just annoying. Journal of Strategic Marketing, 19(6), 489–499.CrossRef
Metadaten
Titel
Influence of individual characteristics on whether and how much consumers engage in showrooming behavior
verfasst von
Wirawan Dony Dahana
HeeJae Shin
Sotaro Katsumata
Publikationsdatum
09.11.2017
Verlag
Springer US
Erschienen in
Electronic Commerce Research / Ausgabe 4/2018
Print ISSN: 1389-5753
Elektronische ISSN: 1572-9362
DOI
https://doi.org/10.1007/s10660-017-9277-4

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