Thinking beyond Privacy Calculus: Investigating Reactions to Customer Surveillance

Plangger, Kirk; Montecchi, Matteo

doi:10.1016/j.intmar.2019.10.004

Cited by 66 publications

(75 citation statements)

References 63 publications

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“…Specifically, if consumers perceive the intent as manipulative, concerns about the invasion of one's privacy outweigh the possible benefits in terms of relevance, resulting in greater level of OBA avoidance (Ham, 2017). This is consistent with the privacy Data-driven digital advertising calculus described as a rational analysis of the balance between benefits and costs of disclosing personal data to a firm (Culnan and Armstrong, 1999;Plangger and Montecchi, 2020). Therefore, we posit the following hypothesis: H4.…”

Section: Privacy Concernsavoidancesupporting

confidence: 64%

“…According to ethical problems in marketing studied by the acquisition-transaction theory (Baek and Morimoto, 2012), the likelihood of a consumer purchasing a product or service depends on the comparison between perceived benefits and perceived risks and costs (Baek and Morimoto, 2012;Plangger and Montecchi, 2020). This process refers to the so-called privacy calculus described as a rational analysis of the balance between benefits and costs of disclosing personal data to a firm (Culnan and Armstrong, 1999;Plangger and Montecchi, 2020). Similarly, the social exchange theory (Emerson, 1976) suggests that people evaluate social exchanges in terms of costs and rewards.…”

Section: Introductionmentioning

confidence: 99%

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Data-driven digital advertising: benefits and risks of online behavioral advertising

Aiolfi

Bellini

Pellegrini

2021

IJRDM

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PurposeThe research aims to investigate how individuals can be persuaded to make purchases through repeated and personalized messages. Specifically, the study proposes a framework of the potential benefits and risks of the online behavioral and data-driven digital advertising (OBA), which can help researchers and practitioners to better understand shopping behavior in the online retailing setting. In addition, the research focuses on the role of privacy concerns in affecting avoidance or adoption of OBA.Design/methodology/approachThe authors apply a structural equation modeling (SEM) approach with partial least square (PLS) regression method to test the research hypotheses through data coming from a structured questionnaire.FindingsOBA is a controversial type of advertising that activates opposing reactions on consumers' perspective. Specifically, acceptance of the OBA is positively related to relevance, usefulness and credibility of the personalized advertisements, while the intention to avoid personalized ads is strictly related to the privacy concerns. Consequently, OBA acceptance and avoidance affected the click intention on the ad and the behavioral intention that are decisive for the success of data-driven digital advertising.Originality/valuePrior research came up with complex theoretical frameworks that explain antecedents of OBA focusing only on ethical issues in marketing, on the effectiveness of a single OBA campaign or on how to create a successful advertising campaign. However, no study focuses on the intended or actual behavior of shoppers. Specifically, filling the gap in the existing literature, our research applies an SEM approach to identify both benefits and risks and the antecedents of the actual behavior of individuals in terms of actual purchases promoted by OBA.

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Section: Privacy Concernsavoidancesupporting

confidence: 64%

Section: Introductionmentioning

confidence: 99%

Data-driven digital advertising: benefits and risks of online behavioral advertising

Aiolfi

Bellini

Pellegrini

2021

IJRDM

View full text Add to dashboard Cite

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“…Reputation is “ the overall assessment of an organization's product and service expertise, social characters, customer experience, and credible communications about the organization's abilities to serve customers ” (Li, 2014, p. 347). One of the important cues of favorable reputation is the way an organization handles its customers' affairs, for example, personal information (Kim et al, 2008; Li, 2014; Plangger & Montecchi, 2020). The literature suggests that reputation of an e‐commerce platform reduces customers' privacy concerns (Dai et al, 2012; Eastlick et al, 2006; Li, 2014; Nam et al, 2006).…”

Section: Theoretical Framework and Hypothesis Developmentmentioning

confidence: 99%

Privacy concerns in e‐commerce: A multilevel meta‐analysis

Maseeh

Jebarajakirthy

Pentecost

et al. 2021

Psychology and Marketing

106

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Whilst the rapid advancement of technology in the 21st century has facilitated the online collection, storage, retrieval, manipulation, and transmission of individuals' personal information, it has also led to a concomitant rise in privacy concerns amongst e‐commerce users. Although privacy concerns have received considerable attention in the e‐commerce literature, to date, empirical research has tended to report somewhat erratic and inconsistent findings in the context of consumer privacy. Accordingly, the relationships between the antecedents, privacy concerns, and the outcome variables in e‐commerce contexts remains unclear. To remedy such deficiencies in the literature, this study adopts the meta‐analytic approach to gather and make sense of the inconsistent and mixed empirical findings reported in the literature. The findings show that risk perceptions trigger privacy concerns while benefit perceptions, familiarity, reputation, privacy policy, and trust mitigate privacy concerns which in turn affect customer attitude and usage of e‐commerce platforms. To investigate the possible reasons for inconsistent findings, we performed a moderation analysis which suggests that methodological moderators, that is, type of article, research methods, and sample type; and contextual moderators, i.e. country where the study was carried out, and gender dominance in a sample set, can cause inconsistencies in the findings. Theoretically, this meta‐analysis contributes to the Antecedents; Privacy Concerns; Outcome variables (APCO) Model, and the literature on consumer privacy in the context of e‐commerce. Practically, the findings provide guidelines to e‐commerce businesses to effectively address customers' privacy concerns.

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“…Since then, the concept of privacy calculus has been extended (cf. Dienlin & Metzger, 2016;Dinev et al, 2008;Plangger & Montecchi, 2020). One of the reasons for this is reflected in the fact that individuals disclose personal information even when they consider that the risks are high (commonly referred to as "privacy paradox" (Barnes & State University of New York at Buffalo, 2020;Taddicken, 2014)).…”

Section: Privacy Calculus Privacy Paradox and Communication Privacy Managementmentioning

confidence: 99%

Balancing privacy rights and surveillance analytics: a decision process guide

Power

Heavin

O’Connor

2021

Journal of Business Analytics

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The right to privacy has been discussed by scholars in multiple disciplines, yet privacy issues are increasing due to technological advances and lower costs for organisations to adopt smart surveillance. Given the potential for misuse, it seems prudent for stakeholders to critically evaluate Surveillance Analytics (SA) innovations. To assist in balancing the issues arising from SA adoption and the implications for privacy, we review key terms and ethical frameworks. Further, we prescribe a two-by-two Surveillance, Privacy, and Ethical Decision (SPED) Process Guide. SPED recommends the use of one or more of three ethical frameworks, Consequence, Duty, and Virtue. The vertical axis in the SPED matrix is the sophistication of an organisation's SA and the horizontal axis is an assessment of the current privacy level and the rights afforded to the target(s) of surveillance. The proposed decision process guide can assist senior managers and technologists in making decisions about adopting SA.

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Thinking beyond Privacy Calculus: Investigating Reactions to Customer Surveillance

Cited by 66 publications

References 63 publications

Data-driven digital advertising: benefits and risks of online behavioral advertising

Data-driven digital advertising: benefits and risks of online behavioral advertising

Privacy concerns in e‐commerce: A multilevel meta‐analysis

Balancing privacy rights and surveillance analytics: a decision process guide

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