Beyond the Dyad: Effects of Business Network Data Exchange on the Privacy Calculus (Revision)

• Applicants: Professor Dr. Jan Hendrik Schumann; Professor Dr. Thomas Widjaja
• Subject Area: Accounting and Finance
• Term: since 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 440654785

Prior research explains consumers’ data disclosure decision-making primarily employing the Privacy Calculus framework, which predicts that consumers decide to disclose personal digital data by engaging in a risk-benefit tradeoff. Those studies focus primarily on dyadic relationships between a customer and a firm. This assumption of dyadic constellations, however, requires reconsideration because technological advances enable firms to collect, store, and analyze consumer data on an unprecedented scale, which leads them to adopt new business models based on the collection and trade of personal digital data across commercial networks of firms. We refer to such practices as business network data exchange (BNDE). In business networks that practice BNDE, consumers that participate typically receive e-services based on providing personal data. In turn, the user data can be exploited to generate revenues by all network partners. For example, the music streaming service Spotify uses its users’ data in a business network of advertisers, concert providers, and other third-party companies. Traditional industries such as airline, automotive, and retailing seek to develop similar business models that will enable them to monetize customer data in firm networks. To explain whether consumers decide to disclose personal data to a network of firms or not, research employing a Privacy Calculus perspective must be extended from the dyadic to a network perspective. In addition, most research on privacy-related decision-making assumes a rational risk-benefit tradeoff and thus cannot account for decisions in the BNDE context, in which consumers face a high degree of uncertainty about possible consequences from disclosing data not only to one firm but an entire network of mostly unknown firms. This uncertainty implies a strong role of affective processes likely to influence consumer decision-making. In particular, we propose that rather than consumers engaging solely in high-effort processing to form their disclosure intention, affective consumer reactions may influence consumers’ disclosure intention via a low-effort affective processing route. Both routes will likely interact, yet interactions could vary for different BNDE-configurations depending on consumers’ distinct uncertainty perception.The proposed project will pursue four objectives. First, we aim to establish the important role of affect-driven low-effort processing for consumer data disclosure intentions in BNDE settings. Second, we strive to understand the effect of exchange process characteristics on high- and low-effort processing for consumer data disclosure intentions in BNDE settings. Third, we seek to identify and understand network characteristics as contingency factors for BNDE processing. Fourth, we aim to inform consumer decision-making and help firms configure BNDE business models that are likely to win consumer acceptance.

• DFG Programme: Research Grants