A conceptualisation of privacy risk and its influence on the disclosure of check-in services information. (April 2021)

• Record Type: Journal Article
• Authors: Kummer, Tyge-F.; Pelzl, Stephanie; Bick, Markus
• Is Part Of: International journal of information management. Volume 57(2021)
• Publication Date: 2021-04
• Subjects: Check-in services -- Location-based services -- Privacy risk -- Conditional value -- Construct development -- Mixed-method; Social sciences -- Information services -- Periodicals; Social sciences -- Research -- Periodicals; Information science -- Periodicals; Management information systems -- Periodicals; Knowledge management -- Periodicals; Sciences sociales -- Documentation, Services de -- Périodiques; Sciences sociales -- Recherche -- Périodiques; Sciences de l'information -- Périodiques; Systèmes d'information de gestion -- Périodiques; Information science; Management information systems; Social sciences -- Information services; Social sciences -- Research; Periodicals; Electronic journals; 025.52068
• DOI: 10.1016/j.ijinfomgt.2020.102266
• Languages: English
• ISSNs: 0268-4012

Abstract

Highlights: We explore privacy risk in relation to check-in services. We extend the privacy calculus model using a mixed-method design. We derive a third-order privacy risk construct entailing nine privacy concerns. We derive normative advice to reduce privacy concerns. Abstract: Check-in services (CISs) are a highly relevant part of location-based services that provide customer value greater than other mobile services due to their technical possibilities; conversely, CISs also create various risks to privacy, as they enable the continuous live tracking of users. We investigate these risks and develop a third-order privacy risk construct based on communication privacy management (CPM) theory to explain how a set of concerns violates privacy boundary mechanisms and generates perceived privacy risk. A developmental mixed-method design is used to qualitatively derive the construct qualitatively through 20 interviews and evaluate it quantitatively using a privacy calculus model with structural equation modelling (N = 431). The results confirm the third-order privacy risk construct and reveal new underlying concerns that create this risk. The results of this study are useful for both practitioners and academics, as they provide insights into how context-specific privacy concerns emerge in advanced mobile services, such as CISs.