User Compensation as a Data Breach Recovery Action:  An Investigation of the Sony PlayStation Network Breach

Goode, Sigi; Hoehle, Hartmut; Venkatesh, Viswanath; Brown, Susan A.

doi:10.25300/misq/2017/41.3.03

Cited by 111 publications

(166 citation statements)

References 79 publications

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“…Particularly interesting in this regard is that the previously mentioned work of Haesevoets, Van Hiel, Onraet, et al () on low‐price guarantees showed, across a set of four empirical studies, that overcompensating price differences in fivefold is not more effective to enhance customer loyalty than equally compensating price differences. In line with the results of this recent study (and those of various other compensation studies; e.g., see Estelami & De Maeyer, ; Garrett, ; Haesevoets, Van Hiel, Pandelaere, et al, ; Noone & Lee, ; for a meta‐analysis, see Gelbrich & Roschk, ; for a recent field study, see Goode, Hoehle, Venkatesh, & Brown, ), the present findings indicated that, in general, large overcompensation does not improve customer loyalty beyond the level that is already reached by equal compensation. Given the high incremental costs of large overcompensation and its lack of positive effects, overcompensation can be considered a cost‐ineffective business strategy for companies to enhance loyalty.…”

Section: Discussionsupporting

confidence: 91%

Towards identifying customer profiles in reactions to financial overcompensation: The role of self‐interest and fairness sensitivity in explaining who prefers more money

Haesevoets

Hiel

Pandelaere

et al. 2019

J of Consumer Behaviour

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In the aftermath of a product failure, companies often offer a financial compensation. The present research compares the effects of equal compensation (i.e., a refund that is equivalent to the purchase price) and large overcompensation (i.e., a refund that is five times larger than the purchase price) on customer loyalty, which was hypothesized to be moderated by individual differences in self‐interest and fairness sensitivity. Our results, first of all, revealed that, overall, large overcompensation does not result in higher customer loyalty than equal compensation. Although overcompensation does not appear to be a worthwhile strategy in general, our results also showed that large overcompensation nonetheless entails positive effects for a particular type of customer. Indeed, relative to equal compensation, overcompensation had an incremental effect on customer loyalty for customers low on perpetrator fairness sensitivity and for customers high on victim fairness sensitivity. Variables related to self‐interest (i.e., materialism and greed) did not demonstrate such a moderation effect. Theoretical and practical implications are discussed.

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Section: Discussionsupporting

confidence: 91%

Towards identifying customer profiles in reactions to financial overcompensation: The role of self‐interest and fairness sensitivity in explaining who prefers more money

Haesevoets

Hiel

Pandelaere

et al. 2019

J of Consumer Behaviour

View full text Add to dashboard Cite

show abstract

“…In the financial industry, which is the object of our study, in July 2017, a data breach on Equifax, one of the largest credit bureaus in the U.S., exposed the personal and financial information of more than 140 million American consumers, which was more than 55% of the adult population of the United States at that time (Census, 2017). These large-scale data breaches can be quite costly for a company's customer perceptions in the marketplace (Goode, Hoehle, Venkatesh, & Brown, 2017).…”

Section: Discussionmentioning

confidence: 99%

Replication of Internet Privacy Concerns in the Mobile Banking Context

Terlizzi¹,

Brandimarte²,

Sanchez³

2019

AIS TRR

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This study is a conceptual replication of the work of Hong and Thong (2013), who developed the Internet Privacy Concerns scale to measure individuals' concerns regarding how personal information is handled by websites. We adapt the wording of the original survey items to the context of mobile banking and follow the same procedures to assess the scale. The replication results reinforce the stability and applicability of the scale over the years and in different scenarios.In contrast with the original study, however, we detect a high correlation between the Control and Awareness dimensions, suggesting the design of an additional second-order dimension that we label "exposure management" (individuals' consciousness about existing controls that mitigate the risks of personal data loss).

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“…Belief was measured using a two-item Likert scale. We measured our second dependent variable, intention to share, using a two item 7-point Likert scale adopted and modified from intention to share knowledge [47] and repurchase intention [48] surveys. All scales, definitions and demographics summary have been reported in Appendix (section 7)…”

Section: Methodsmentioning

confidence: 99%

How does Information Spread? An Exploratory Study of True and Fake News

Suntwal¹,

Brown²,

Patton³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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The intentional and non-intentional use of social media platforms resulting in digital wildfires of misinformation has increased significantly over the last few years. However, the factors that influence this rapid spread in the online space remain largely unknown. We study how believability and intention to share information are influenced by multiple factors in addition to confirmation bias. We conducted an experiment where a mix of true and false articles were evaluated by study participants. Using hierarchical linear modelling to analyze our data, we found that in addition to confirmation bias, believability is influenced by source endorser credibility and argument quality, both of which are moderated by the type of informationtrue or false. Source likeability also had a positive main effect on believability. After controlling for belief and confirmation bias, intention to share information was affected by source endorser credibility and information source likeability. Prior Theory and ResearchAs fake news has broad definitions and purposes, understanding it is emerging as a significant research challenge. Technical and behavioral scientists are looking at this problem from multiple perspectives. Behavioral scientists have made significant progress in understanding how readability, placement of titles, etc. affect belief. However, a key aspect of fake news is its ability to persuade readers that it is true. The Elaboration Likelihood Model (ELM) is a key theory for understanding persuasive communication better. The two key routes of ELM, the central and the peripheral routes, explain how persuasive communication affects both individual belief and intention to share.

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User Compensation as a Data Breach Recovery Action: An Investigation of the Sony PlayStation Network Breach

Cited by 111 publications

References 79 publications

Towards identifying customer profiles in reactions to financial overcompensation: The role of self‐interest and fairness sensitivity in explaining who prefers more money

Towards identifying customer profiles in reactions to financial overcompensation: The role of self‐interest and fairness sensitivity in explaining who prefers more money

Replication of Internet Privacy Concerns in the Mobile Banking Context

How does Information Spread? An Exploratory Study of True and Fake News

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