The More, the Better? Compensation and Remorse as Data Breach Recovery Actions – An Experimental Scenario-based Investigation

Bibtex

Cite as text

						@Select Types{,
							 
							 
							 
							 
							 
							Journal   = "Band-1",
							 Title= "The More, the Better? Compensation and Remorse as Data Breach Recovery Actions – An Experimental Scenario-based Investigation", 
							Author= "Maike Greve, Kristin Masuch, and Simon Trang", 
							Doi= "https://doi.org/10.30844/wi_2020_l2-greve", 
							 Abstract= "With the increasing number of companies actively collecting data, the number of data breaches has exploded. It can be observed that affected often discontinue their relationship with the company. In order to avoid this kind of response, companies should develop and deploy their own recovery strategies. In our paper, we examined the effectiveness of different recovery strategies geared towards retaining customer satisfaction immediately after a data breach. We examine a data breach of a fitness tracker that varies in severity and tests the recovery actions compensation and remorse. The results found that customer satisfaction depends on the severity of the data breach, while combining compensation and remorse together demonstrates itself as the best strategy for increasing customer satisfaction in almost all cases. However, it was also discovered that in case of a severe data breach, customer satisfaction is difficult to restore and in the end remorse has virtually no effect.

", 
							 Keywords= "data breach, recovery action, severity, customer satisfaction, fitness tracker", 
							}
					
Maike Greve, Kristin Masuch, and Simon Trang: The More, the Better? Compensation and Remorse as Data Breach Recovery Actions – An Experimental Scenario-based Investigation. Online: https://doi.org/10.30844/wi_2020_l2-greve (Abgerufen 18.04.24)

Abstract

Abstract

With the increasing number of companies actively collecting data, the number of data breaches has exploded. It can be observed that affected often discontinue their relationship with the company. In order to avoid this kind of response, companies should develop and deploy their own recovery strategies. In our paper, we examined the effectiveness of different recovery strategies geared towards retaining customer satisfaction immediately after a data breach. We examine a data breach of a fitness tracker that varies in severity and tests the recovery actions compensation and remorse. The results found that customer satisfaction depends on the severity of the data breach, while combining compensation and remorse together demonstrates itself as the best strategy for increasing customer satisfaction in almost all cases. However, it was also discovered that in case of a severe data breach, customer satisfaction is difficult to restore and in the end remorse has virtually no effect.

Keywords

Schlüsselwörter

data breach, recovery action, severity, customer satisfaction, fitness tracker

References

Referenzen

1. Wan, L., Zhang, C.: Responses to trust repair after privacy breach incidents. J. Serv. Sci. Res. 6, 193–224 (2014).
2. Kindervag, J., Holland, R., Shey, H.: Planning For Failure. Forrester Research, Cambridge (2015).
3. Dickey, M.R.: Under Armour says MyFitnessPal data breach affected 150 million users | TechCrunch, https://techcrunch.com/2018/03/29/under-armour-saysmyfitnesspal-data-breach-affected-150-million-users/. (Accessed 10.07.2019)
4. Goel, S., Shawky, H.A.: Estimating the market impact of security breach announcements on firm values. Inf. Manag. 46, 404–410 (2009).
5. Goode, S., Hoehle, H., Venkatesh, V., Brown, S.A.: User Compensation as a Data Breach Recovery Action: An Investigation of the Sony PlayStation Network Breach. MIS Q. 41, 703–727 (2017).
6. Spiegel Online: Capital One: Hacker erbeutet Daten von rund 100 Millionen Bankkunden – SPIEGEL ONLINE, https://www.spiegel.de/wirtschaft/unternehmen/capital-one-hacker-erbeutet-datenvon- rund-100-millionen-bankkunden-a-1279583.html. (Accessed 0.8.07.2019)
7. Cheng, L., Liu, F., Yao, D.D.: Enterprise data breach: causes, challenges, prevention, and future directions. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 7, 1–14 (2017).
8. Campbell, K., Gordon, L.A., Loeb, M.P., Zhou, L.: The economic cost of publicly announced information security breaches: Empirical evidence from the stock market. J. Comput. Secur. 11, 431–448 (2003).
9. Morse, E.A., Raval, V., Wingender, J.R.: Market Price Effects of Data Security Breaches. Inf. Secur. J. 20, 263–273 (2011).
10. Gordon, L.A., Loeb, M.P., Zhou, L.: The impact of information security breaches: Has there been a downward shift in costs? J. Comput. Secur. 19, 33–56 (2011).
11. Aivazpour, Z., Valecha, R., Chakraborty, R.: The Impact of Data Breach Severity on Post-Breach Online Shopping Intention. ICIS 2018 Proc. (2018).
12. Bolton, Ruth, N.: A Dynamic Model of the Duration of the Customer ’ s Relationship with a Continuous Service Provider. Mark. Sci. 17, 45 (1998).
13. Parasuraman, A., Zinkhan, G.M.: Marketing to and serving customers through the Internet: Conceptual frameworks, practical insights, and research directions – From the editor. J. Acad. Mark. Sci. 30, 286–295 (2002).
14. Parasuraman, A., Zeithaml, V.A., Malhotra, A.: E-S-QUAL a multiple-item scale for assessing electronic service quality. J. Serv. Res. 7, 213–233 (2005).
15. Grönroos, C.: New Competition in the Service Economy: The Five Rules of Service. Int. J. Oper. Prod. Manag. 8, 9–19 (1988).
16. Hart, C.W.L., Heskett, J.L., Sasser Jr, W.E.: The profitable art of service recovery. Harv. Bus. Rev. 68, 148–156 (1990).
17. Kelley, S.W., Davis, M.A.: Antecedents to customer expectations for service recovery. J. Acad. Mark. Sci. 22, 52–61 (1994).
18. Oliver, R.L., Swan, J.E.: Equity and Disconfirmation Perceptions as Influences on Merchant and Product Satisfaction. J. Consum. Res. 16, 372 (1989).
19. Smith, A.K., Bolton, R.N., Wagner, J.: A Model of Customer Satisfaction with Service Encounters Involving Failure and Recovery. J. Mark. Res. 36, 356 (1999).
20. Bitner, M.J., Booms, B.H., Tetreault, M.S.: The Service Encounter: Diagnosing Favorable and Unfavorable Incidents. J. Mark. 54, 71 (2006).
21. Fehr, R., Gelfand, M.J.: When apologies work: How matching apology components to victims’ self-construals facilitates forgiveness. Organ. Behav. Hum. Decis. Process. 113, 37–50 (2010).
22. Bolkan, S., Daly, J.A.: Organizational responses to consumer complaints: An examination of effective remediation tactics. J. Appl. Commun. Res. 37, 21–39 (2009).
23. Weiner, B.: Attributional Thoughts about Consumer Behavior. J. Consum. Res. 27, 382–387 (2001).
24. Bitner, M.J.: Evaluating Service Encounters: The Effects of Physical Surroundings and Employee Responses. J. Mark. 54, 69 (1990).
25. Kau, A.K., Loh, E.W.Y.: The effects of service recovery on consumer satisfaction: A comparison between complainants and non-complainants. J. Serv. Mark. 20, 101–111 (2006).
26. Morrisson, O., Huppertz, J.W.: External equity, loyalty program membership, and service recovery. J. Serv. Mark. 24, 244–254 (2010).
27. Hong, J., Lee, A.Y.: Feeling Mixed but Not Torn: The Moderating Role of Construal Level in Mixed Emotions Appeals. J. Consum. Res. 37, 456–472 (2010).
28. Yun, H., Lee, C.C., Kettinger, W.J.: Personal Information Breach as a Service Failure: Examining Relationships amng Recovery Efforts, Justice, and Customer Responses. In: International Conference on Information Systems (2012).
29. Adams, J.S.: Toward an understanding of inequity. Journal of Abnormal and Social Psychology. J. Abnorm. Soc. Psychol. 67, 422–436 (1963).
30. Tax, S.S., Brown, S.W., Chandrashekaran, M.: Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing. J. Mark. 62, 60 (2006).
31. Leventhal, G.: What should be done with equity theory? New approaches to the study of fairness in social relationships. Soc. Exch. theory Adv. theory Res. London, Springer.
32. Bies, R.., Shapiro, D..: Interactional justice: The influence of causal accounts. Soc. Justice Res. 1, 199–218 (1987).
33. Gelbrich, K., Roschk, H.: A meta-analysis of organizational complaint handling and customer responses. J. Serv. Res. 14, 24–43 (2011).
34. Prasongsukarn, K., Patterson, P.G.: An extended service recovery model: The moderating impact of temporal sequence of events. J. Serv. Mark. 26, 510–520 (2012).
35. Chebat, J.C., Slusarczyk, W.: How emotions mediate the effects of perceived justice on loyalty in service recovery situations: An empirical study. J. Bus. Res. 58, 664–673 (2005).
36. Maxham, J.G., Netemeyer, R.G.: Modeling customer perceptions of complaint handlich over time: the effects of perceived justice on satisfaction and intent. J. Retail. 78, 239–252 (2002).
37. Wirtz, J., Mattila, A.S.: Consumer responses to compensation, speed of recovery and apology after a service failure. Int. J. Serv. Ind. Manag. 15, 150–166 (2004).
38. Walster, E., Berscheid, E., Walster, G.W.: New directions in equity research. J. Pers. Soc. Psychol. 25, 151–176 (1973).
39. Maxham, J.G., Netemeyer, R.G.: Firms Reap what they Sow: The Effects of Shared Values and Perceived Organizational Justice on Customers’ Evaluations of Complaint Handling. J. Mark. 67, 46–62 (2003).
40. del Río-Lanza, A.B., Vázquez-Casielles, R., Díaz-Martín, A.M.: Satisfaction with service recovery: Perceived justice and emotional responses. J. Bus. Res. 62, 775–781 (2009).
41. Karatepe, O.M.: Customer complaints and organizational responses: the effects of complainants’ perceptions of justice on satisfaction and loyalty. Int. J. Hosp. Manag. 25, 69–90 (2006).
42. Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., Raghav Rao, H.: Online shopping intention in the context of data breach in online retail stores: An examination of older and younger adults. Decis. Support Syst. 83, 47–56 (2016).
43. Stiennon, R.: Categorizing Data Breach Severity with a Breach Level Index. 1–3 (2013).
44. Atzmüller, C., Steiner, P.M.: Experimental vignette studies n survey research. Methodology. 6, 128–138 (2010).
45. Kantsperger, R., Kunz, W.H.: Consumer trust in service companies: a multiple mediating analysis. Manag. Serv. Qual. An Int. J. 20, 4–25 (2010).
46. Cohen, B.H.: Three-Way ANOVA. In: Explaining Psychological Statistics. pp. 688– 746. John Wiley & Sons (2008).

Most viewed articles

Meist angesehene Beiträge

GITO events | library.gito