Trust and distrust in information systems at the workplace

Digitalization of work processes is advancing, and this is increasingly supported by complex information systems (IS). However, whether such systems are used by employees largely depends on users’ trust in these IS. Because there are few systematic studies on this topic, this research provides an initial exploration and validation of preconditions for trust in work-related IS. In Study 1, N = 30 professionals were asked to describe occupational incidents in which they had highly trusted or distrusted an IS. Content analysis of 111 critical incidents described in the in-depth interviews led to 12 predictors of trust and distrust in IS, which partly correspond to the structure of the established IS success model (Delone & McLean, 2003) but also exceed this structure. The resulting integrative model of trust in IS at work was validated in Study 2 using an online questionnaire with N = 179 professionals. Based on regression analyses, reliability (system quality) and credibility (information quality) of IS were identified as the most important predictors for both trust and distrust in IS at work. Contrasting analyses revealed diverging qualities of trust and distrust in IS : whereas well-being and performance were rated higher in trust events, experienced strain was rated higher in distrust events. Together, this study offers a first comprehensive model of trust in IS at work based on systematic empirical research. In addition to implications for theory advancement, we suggest practical implications for how to support trust and to avoid distrust in IS at work

Intentional Forgetting in Socio-Digital Work Systems:System Characteristics and User-related Psychological Consequences on Emotion, Cognition, and Behavior

Future work environments offer numerous technical applications to manage increasing amounts of information for organizations, teams, and individuals. Psychological concepts of intentional forgetting (IF) can be applied to improve the performance of work systems or to extend cognitive capacities of humans in technical systems. Different IF mechanisms have been suggested for assisting technology-aided IF, such as: (1) filtering of irrelevant or distressful information (e.g., by suppressing, deleting, or selecting), (2) delegating tasks from human to digital agents, changing roles, and reorganizing socio-digital work systems, or (3) systematic (re-)placement of retrieval cues or triggers to generate or suppress behavior. Due to these different underlying IF mechanisms, the implementation of IF at individual, team, and organizational level will differ substantially between work areas or systems. In order to gain a better understanding of how socio-digital applications of IF impact human behavior and reactions, it is necessary to (a) differentiate between relevant characteristics of socio-digital IF systems and (b) gain an understanding of how these characteristics impact users’ attitudes and performance. Thus, the present paper aims to classify and compare these characteristics of different applications of IF and introduces variables and methods to study psychological effects on users’ behavior, experience, and affective reactions