Tobias Mettler

The interest in digital identities has increased considerably in academia and practice in recent years. This can be seen by the many electronic identity projects worldwide and the numerous published studies that provide insightful narratives and descriptive case findings about success factors and barriers to the adoption of national authentication infrastructures. In this paper, we take a closer look to the role of trust on the design and implementation of a nation-wide e-credential market. We argue that trust in political and economic institutions can be an important factor to explain differences in the chosen cooperative arrangement which can range from monopolistic, purely state-controlled e-credential markets, to polypolistic, decentralized e-credential markets where also private vendors offer state recognized e-ID on their own or in partnership with the government. Following an inductive reasoning process, we develop three testable propositions which may inspire further empirical research and offer practitioners a new angle to rethink e-credential markets in the light of citizen trust in political and economic institutions.

Being among the largest creators and gatherers of data in many countries, public administrations are looking for ways to harness big data technology. However, the de facto uses of big data in the public sector remain very limited. Despite numerous studies aiming to clarify the term big data, for many public managers, it remains unclear what this technology does and does not offer public administration. Using the concept of technological frames, we explore the assumptions, expectations, and understandings that public managers possess in order to interpret and make sense of big data. We identify nine big data frames, ranging from inward-oriented techno-enthusiasts to outward-oriented techno-skeptics, each of which characterizes public managers' specific viewpoints relating to the introduction of big data in public administrations. Our findings highlight inconsistencies between different perceptions and reveal widespread skepticism among public managers, helping better understand why the de facto uses of big data in the public sector remain very limited.

There is a growing body of literature that addresses the importance of health and wellbeing in the workplace, and the effectiveness of corporate wellness programs. Following advancements in low-cost and unobtrusive computing technology, an emerging trend in corporate wellness programs is to offer wearable devices to employees. These devices monitor employees' physiological and environmental conditions in order to improve their awareness of their personal health. In addition, organizations can harness the aggregated anonymized data provided by such technology to investigate ways of improving the work environment. However, promoting digital health monitoring systems introduces new dynamic interactions between the social actors and technology. Three main categories of strain caused by the use of these systems in a work environment are value tensions (privacy vs. wellbeing); action tensions (work vs. leisure activities), and role tensions (leisure vs. work roles). Based on an analysis of these tensions, design principles for digital occupational health systems are derived that minimize strain and have much bigger chances to be accepted and thus to create value for all stakeholders. Consequently, this study follows the design science research paradigm to derive design principles.

Simulation has been adopted in many disciplines as a means for understanding the behavior of a system by imitating it through an artificial object that exhibits a nearly identical behavior. Although simulation approaches have been widely adopted for theory building in disciplines such as engineering, computer science, management, and social sciences, their potential in the IS field is often overlooked. The aim of this paper is to understand how different simulation approaches are used in IS research, thereby providing insights and methodological recommendations for future studies. A literature review of simulation studies published in top-tier IS journals leads to the definition of three classes of simulations, namely the self-organizing, the elementary, and the situated. A set of stylized facts is identified for characterizing the ways in which the premise, the inference, and the contribution are presented in IS simulation studies. As a result, this study provides guidance to future simulation researchers in designing and presenting findings.

Changing demands in society and the limited capabilities of health systems have paved the way for robots to move out of industrial contexts and enter more human-centered environments such as health care. We explore the shared beliefs and concerns of health workers on the introduction of autonomously operating service robots in hospitals or professional care facilities. By means of Q-methodology, a mixed research approach specifically designed for studying subjective thought patterns, we identify five potential end-user niches, each of which perceives different affordances and outcomes from using service robots in their working environment. Our findings allow for better understanding resistance and susceptibility of different users in a hospital and encourage managerial awareness of varying demands, needs, and surrounding conditions that a service robot must contend with. We also discuss general insights into presenting the Q-methodology results and how an affordance-based view could inform the adoption, appropriation, and adaptation of emerging technologies.

New digital services in consumer-facing organizations offer novel value propositions, closer consumer relationships and higher automation of consumer-facing processes. But transforming to fully digital services requires an organization to acquire specific capabilities. This article presents a digital services capability model that allows an organization to assess its current capabilities and identify gaps. Two in-depth case studies demonstrate the application of the model and show how it identifies the capabilities in urgent need of improvement. Our recommendations are built around four scenarios for using the model.

A high rate of work-related accidents or diseases around the world not only threatens the health and wellbeing of employees, but also causes a considerable annual economic burden for organizations. One promising use of information technology would therefore be the management and prevention of occupational accidents and employee absenteeism. Although some companies are starting to introduce digital occupational health initiatives, there is scarce evidence about the inhibiting factors which may discourage the wide adoption of such systems in the workforce. This paper presents qualitative and quantitative data of an exploratory study, which delves into the perceptions of employees towards the use of digital occupational health systems. Our results show that employees are usually aware of the enhanced possibilities for managing and improving their health and wellbeing through such corporate initiatives. However, privacy concerns and the additional mental pressure caused by such systems, significantly diminishes an employee’s willingness to adopt them.