The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Data Privacy: Effects on Customer and Firm Performance
Abstract
Although marketers increasingly rely on customer data, firms have little insight into the ramifications of such data use and do not know how to prevent negative effects. Data management efforts may heighten customers’ vulnerability worries or create real vulnerability. Using a conceptual framework grounded in gossip theory, the authors link customer vulnerability to negative performance effects. Three studies show that transparency and control in firms’ data management practices can suppress the negative effects of customer data vulnerability. Experimental manipulations reveal that mere access to personal data inflates feelings of violation and reduces trust. An event study of data security breaches affecting 414 public companies also confirms negative effects, as well as spillover vulnerabilities from rival firms’ breaches, on firm performance. Severity of the breach hurts the focal firm but helps the rival firm, which provides some insight into mixed findings in prior research. Finally, a field study with actual customers of 15 companies across three industries demonstrates consistent effects across four types of customer data vulnerability and confirms that violation and trust mediate the effects of data vulnerabilities on outcomes.
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“Privacy concerns also play significant role; if emails feel invasive, customer trust can drop and poor data practices can harm brand's reputation, making transparency in data usage essential for long-term success (Acquisti & Gross, 2006;Martin et al., 2017).”
From Feeling Watched: A Phenomenological Exploration of Consumer Discomfort and Data Privacy Concerns in E-Commerce Personalized Email Marketing (2025) · cites this paper as Martin et al., 2017
Citations
Cites
Preacher, K. J., & Hayes, A. F. (2008) · Behavior Research Methods · doi:10.3758/brm.40.3.879 · Cited by 34,117
The need to belong: Desire for interpersonal attachments as a fundamental human motivation.
Baumeister, R. F., & Leary, M. R. (1995) · Psychological Bulletin · doi:10.1037//0033-2909.117.3.497 · Cited by 23,245
CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK*
Sharpe, W. F. (1964) · The Journal of Finance · doi:10.1111/j.1540-6261.1964.tb02865.x · Cited by 19,441
Specification Tests in Econometrics
Hausman, J. A. (1978) · Econometrica · doi:10.2307/1913827 · Cited by 18,820
Williams, K. D. (2007) · Annual Review of Psychology · doi:10.1146/annurev.psych.58.110405.085641 · Cited by 1,828
Solove, D. J. (2006) · University of Pennsylvania Law Review · doi:10.2307/40041279 · Cited by 1,388
Smart Richman, L., & Leary, M. R. (2009) · Psychological Review · doi:10.1037/a0015250 · Cited by 942
The role of data privacy in marketing
Martin, K. D., & Murphy, P. E. (2017) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-016-0495-4 · Cited by 902 · cited 1×
“Nobody can articulate what it means ” (Solove 2006, p. 476; for a comprehensive review of privacy literature in marketing, see also Martin and Murphy [2016]).”
Self-citationBuilding Understanding of the Domain of Consumer Vulnerability
Baker, S. M., Gentry, J. W., & Rittenburg, T. L. (2005) · Journal of Macromarketing · doi:10.1177/0276146705280622 · Cited by 895
Intimate Exchanges: Using Computers to Elicit Self-Disclosure from Consumers
Moon, Y. (2000) · Journal of Consumer Research · doi:10.1086/209566 · Cited by 842
Social Networks, Personalized Advertising, and Privacy Controls
Tucker, C. E. (2014) · Journal of Marketing Research · doi:10.1509/jmr.10.0355 · Cited by 829
Research on Gossip: Taxonomy, Methods, and Future Directions
Foster, E. K. (2004) · Review of General Psychology · doi:10.1037/1089-2680.8.2.78 · Cited by 671 · cited 2×
“Gossip theory describes how people respond to the unsanctioned collection, use, or disclosure of their personal information (Dunbar 2004; Foster 2004), and we consider it germane for understanding how customers respond when fi rms collect and use their personal data.”
Customer Loyalty to Whom? Managing the Benefits and Risks of Salesperson-Owned Loyalty
Palmatier, R. W., Scheer, L. K., & Steenkamp, J.-B. E. M. (2007) · Journal of Marketing Research · doi:10.1509/jmkr.44.2.185 · Cited by 555
Self-citationConsumer online privacy: Legal and ethical issues
Caudill, E. M., & Murphy, P. E. (2000) · Journal of Public Policy & Marketing · doi:10.1509/jppm.19.1.7.16951 · Cited by 382
When Will a Brand Scandal Spill Over, and how Should Competitors Respond?
Roehm, M. L., & Tybout, A. M. (2006) · Journal of Marketing Research · doi:10.1509/jmkr.43.3.366 · Cited by 380 · cited 1×
“Customers often shift from a fi rm experiencing a brand crisis, and the switch ultimately may be permanent (Roehm and Tybout 2006).”
Flagged first, then by citations
Research works printed but not linked: 59
- Acquisti Alessandro, 2006, Proceedings of the 27th International Conference on Information Systems, 94
- 10.1509/jmr.09.0215 · DOI · Paper page
- 10.2307/25148715 · DOI · Paper page
- 10.1509/jmkg.2005.69.4.133 · DOI · Paper page
- 10.1037/0033-2909.117.3.497 · DOI · Paper page
- 10.1037/1089-2680.8.2.111 · DOI · Paper page
- 10.1111/j.1559-1816.2012.00956.x · DOI
- BiesdorfStefan, CourtDavid, and WillmottPaul (2013), “Big Data: What's Your Plan?” McKinsey Quarterly (March), http://www.mckinsey.com/business-functions/business-technology/our-insights/big-data-whats-your-plan.
- 10.1287/mksc.2013.0818 · DOI
- 10.1509/jmr.13.0009 · DOI
- 10.1016/j.jbankfin.2010.07.016 · DOI
- 10.1007/s10799-005-5879-y · DOI
- 10.1509/jm.10.0414 · DOI
- 10.1177/1096348004265027 · DOI
- 10.1016/j.clsr.2013.07.007 · DOI
- 10.1509/jmr.11.0136 · DOI
- 10.1037/1089-2680.8.2.100 · DOI
- 10.2307/2096270 · DOI
- Emler Nicholas, 1994, Good Gossip, 119
- 10.1016/S0304-405X(98)00026-9 · DOI
- 10.1037/a0026650 · DOI
- Fisher John A., 2013, William & Mary Business Law Review, 215, 217
- 10.1007/s11002-006-3796-4 · DOI
- 10.1007/s11747-007-0054-0 · DOI
- 10.1509/jm.12.0179 · DOI
- 10.1109/THS.2015.7225301 · DOI
- 10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7 · DOI · Paper page
- Iyengar Sheena, 2010, The Art of Choosing
- 10.1086/656423 · DOI · Paper page
- Ko Myung, 2006, Journal of Information Technology Management, 17, 13
- 10.1509/jmr.13.0169 · DOI
- 10.1017/CBO9780511770548.003 · DOI
- 10.1007/s11747-006-0003-3 · DOI
- 10.1177/1094670510383409 · DOI
- 10.1287/isre.1040.0032 · DOI · Paper page
- McAfee Andrew, 2012, Harvard Business Review, 3
- 10.2307/257056 · DOI
- Mills Colleen, 2010, Group & Organization Management, 35, 371, 10.1177/1059601109360389 · DOI
- 10.1111/j.1745-6606.2004.tb00865.x · DOI
- 10.1016/j.jom.2011.01.002 · DOI
- 10.1177/1094670511424924 · DOI · Paper page
- 10.1509/jmkg.72.4.076 · DOI
- 10.1509/jmkg.70.4.136 · DOI · Paper page
- Ponemon Institute, 2015, 2015 Cost of Data Breach Study: Global Analysis
- 10.1509/jmr.09.0317 · DOI
- 10.1002/pam.20567 · DOI
- Scharf S., 2007, Internal Auditor, 64, 23
- 10.1108/ICS-03-2014-0020 · DOI
- 10.1509/jmkg.70.2.133 · DOI · Paper page
- 10.1509/jm.11.0316 · DOI · Paper page
- 10.1080/07421222.2015.1063315 · DOI
- Sharpe William F., 1964, Journal of Finance, 19, 425
- 10.1177/1088868314530515 · DOI
- 10.1177/002224299706100301 · DOI
- Solove Daniel J., 2003, Hastings Law Journal, 54, 1
- 10.1509/jmkg.75.3.49 · DOI
- 10.1509/jmkr.46.3.293 · DOI
- 10.1080/0363775032000133782 · DOI
- 10.1207/s15327663jcp1401&2_6 · DOI · Paper page
Cited by
Sorted by citations
How artificial intelligence will change the future of marketing
Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00696-0 · Cited by 2,875
The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes
Nambisan, S., Wright, M., & Feldman, M. (2019) · Research Policy · doi:10.1016/j.respol.2019.03.018 · Cited by 3,089
“, social media as a surveillance tool, lack of trust in media and democratic institutions) (e.g., Allcott and Gentzkow, 2017; Grinberg et al., 2019; Martin, 2018; Martin et al., 2017; Trottier, 2016).”
BackgroundThe future of social media in marketing
Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00695-1 · Cited by 1,893
“…privacy (e.g., Aguirre et al. 2015; White et al. 2008), the relationship of privacy as it relates to consumer trust and firm performance (e.g., Martin 2018; Martin et al. 2017), and the legal and ethical aspects of data and digital privacy (e.g., Culnan and Williams 2009; Nill and Aalberts 2014).”
BackgroundThe role of data privacy in marketing
Martin, K. D., & Murphy, P. E. (2017) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-016-0495-4 · Cited by 902
“In a third example, Martin et al. (2016) pair two consumer-focused investigations of company data management perceptions with a third, parallel study of firms ’ actual data management following a security breach.”
BackgroundInfluentialSelf-citationCustomer experience challenges: Bringing together digital, physical and social realms
Bolton, R. N., McColl-Kennedy, J. R., Cheung, L., Gallan, A., Orsingher, C., Witell, L., & Zaki, M. (2018) · Journal of Service Management · doi:10.1108/josm-04-2018-0113 · Cited by 849
“B ol to n A t 0 8: 23 2 0 Se pt em be r 20 18 ( PT ) offset their perceptions of vulnerability (Martin et al., 2017, p. 36).”
Background
Metadata
- Authors
- Martin, K. D., Borah, A., & Palmatier, R. W.
- Affiliations
- Colorado State University (US)
- University of Washington (US)
- Venue
- Journal of Marketing
- Publisher
- SAGE Publications
- Published
- 2017-01
- Volume
- 81
- Issue
- 1
- Pages
- 36-58
- ISSN
- 0022-2429 (ISSN-L)
- 1547-7185
- OpenAlex
- W2495772237
- Cited by
- 786
- References
- 0
- Citations by year
- 2026: 123 · 2025: 132 · 2024: 92 · 2023: 99 · 2022: 97 · 2021: 67 · 2020: 82 · 2019: 54 · 2018: 26 · 2017: 13
- FWCI
- 89.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Marketing (publishedVersion)
- Griffith Research Online (submittedVersion)
- Funders
- Colorado State University
- Marketing Science Institute
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Social Sciences › Business, Management and Accounting › Marketing › Customer Service Quality and Loyalty
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Keywords
- data privacy, data management practices, consumer trust, data breaches, firm performance, customer performance, transparency, data control, spillover effects, rival firms
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