Over the course of the past decades, technological advancements accompanied a plethora of new types of data and consumer insights (e.g., Erevelles, Fukawa, & Swayne, 2016). Companies value opportunities provided by the availability of large data sets for their business strategy. Customers, however, are wary, as these analyses require the collection and storage of large amounts of personal information. Therefore, it is vital for companies to understand what customers perceive to be fair with regard to their personal data (e.g., Malhotra, Kim, & Agarwal, 2004). However, research still lacks deeper insights into customers’ expectations of fair data handling (Marketing Science Institute, 2016). Yet, only few studies have covered the field of expectations regarding fair data collection and use (Earp, Antón, Aiman-Smith, & Stufflebeam, 2005; Milne & Bahl, 2010). Importantly, however, previous studies have frequently neglected how companies’ fulfillment of customers’ expectations translates into subsequent consumer behavior. Moreover, we have yet to understand if companies’ actual behavior meets customers’ expectations. Grounded on psychological contract and justice theory, we investigate how customers want their data to be handled and in which ways they want to be informed about its usage, while also exploring how customer expectations translate into subsequent behavioral intentions. Additionally, we shed light on current company behavior, thus analyzing if customers’ expectations of fair data collection and usage are aligned with company perspectives. Responding to calls for a mixed methods approach in business research (e.g., Harrison, 2013; Woodside, 2010), we undertook qualitative and quantitative studies to address our research goals. In Study 1, we conduct in-depth interviews with customers and experts to gain an overview of customer expectations with regard to fair data collection and usage. Based on these findings, we conducted a quantitative study (Study 2) investigating each of the customer expectations identified in the prior study. The findings of Study 2 reveal that customers expect a simplification of privacy statements as well as easier control options for their data. Moreover, customers are willing to switch to a competitor, if it better fulfills expectations. Study 3 applies a content analysis of company homepages and privacy statements. Aligning the results from Study 2 and Study 3, we demonstrate that companies currently do not sufficiently meet customers’ expectation of fair data collection and usage.

While companies in the field of e-commerce have long engaged in the collection of large amounts of customer data and consider them one of their most important assets, insurance companies have only recently started to collect customer data on a large scale (Smith, Dinev & Xu, 2011). Recently, insurance companies have developed tariffs which adjust premiums based on collected data about the insurant’s behavior (e.g. steps/day, visits to the gym etc.). Benefits like fitness courses or lower insurance rates are provided to encourage a healthy lifestyle and attract healthy customers. However, this model can only succeed, if customers are willing to disclose data. As many customers fear an intrusion of their privacy by companies and consider personal health data to be especially sensitive, this disclosure cannot be taken for granted (Anderson & Agarwal, 2011). The paper evaluates two main influencing factors for the willingness to disclose private health data (benefit offered to customers and sensitivity of data requested). It analyzes their effect by conducting an online scenario-based quasiexperiment with 408 participants. Participants are presented with six hypothetical offers by a health insurance (financial and non-financial benefits; low, medium, high data sensitivity) and indicate how they would respond to these offers in terms of data disclosure. We control for individual heterogeneity by including privacy concerns and trust as between-subject factors (Malhotra, Kim, & Agarwal, 2004). Our results indicate that the willingness to disclose health data can be increased by financial rewards at low and medium sensitivity levels. If information is highly sensitive, the willingness to provide data decreases and cannot be compensated by a tariff reduction. Health care providers should therefore carefully consider which data points they choose as mandatory to participate in personalized insurance tariffs, as they could easily scare off potential customers. In our study non-financial benefits (prevention courses) are not able to increase the willingness to disclose data as much as financial benefits. This could be due to a general preference for financial rewards or to the unknown quality of the courses offered.

Justice theory has emerged as a frequently used framework in theory and among service leaders to investigate reasons for customer complaints and their satisfaction with the handling of the complaint (Orsingher, Valentini, & Angelis, 2010; Tax, Brown, & Chandrashekaran, 1998). Whereas the complaint of a single customer used to be heard by only a small circle of acquaintances, with the rise of social media it can now be transferred to a large community of other customers as well. Theory suggests that justice perceptions might be able to explain the reactions of third parties to a complaint. Therefore, we analyze 400 complaints of 8 companies from 4 different retail and service industries and their related comments from a large German online complaint forum. We found that complaints addressing procedural justice issues receive the most attention and a lot of support from other users. Complaints regarding interactional justice, receive more opposition than support, evidenced by the negative comments from the other users. They seem to perceive the interactional complaints as less severe and even defend the company in many cases by attributing part of the blame to the complainant. Companies should consider these findings when they manage their complaint process and when they try to assess the criticality of complaints. In addition, this study once again confirms the danger of not reacting to customer requests in a timely manner as this can be interpreted by customers as intentionally ignoring them, which leads to positive reactions of other users and to solidarity with the complainant.