Big data breaches and customer compensation strategies: Personality traits and social influence as antecedents of perceived compensation. Issue 1 (3rd January 2017) - Kude, Thomas; Hoehle, Hartmut; Sykes, Tracy Ann
Abstract : Purpose: Big Data Analytics provides a multitude of opportunities for organizations to improve service operations, but it also increases the threat of external parties gaining unauthorized access to sensitive customer data. With data breaches now a common occurrence, it is becoming increasingly plain that while modern organizations need to put into place measures to try to prevent breaches, they must also put into place processes to deal with a breach once it occurs. Prior research on information technology security and services failures suggests that customer compensation can potentially restore customer sentiment after such data breaches. The paper aims to discuss these issues. Design/methodology/approach: In this study, the authors draw on the literature on personality traits and social influence to better understand the antecedents of perceived compensation and the effectiveness of compensation strategies. The authors studied the propositions using data collected in the context of Target's large-scale data breach that occurred in December 2013 and affected the personal data of more than 70 million customers. In total, the authors collected data from 212 breached customers. Findings: The results show that customers' personality traits and their social environment significantly influences their perceptions of compensation. The authors also found that perceived compensation positively influences service recovery and customer experience. Originality/value: The results add to the emerging literature on Big Data Analytics and will help organizations to more effectively manage compensation strategies in large-scale data breaches.