Christiane Lehrer

Physical inactivity is a global public health problem that poses health risks to individuals and imposes financial burdens on already strained healthcare systems. Wearables that promote regular physical activity and a healthy diet bear great potential to meet these challenges and are increasingly integrated into the healthcare system. However, extant research shows ambivalent results regarding the effectiveness of wearables in improving users’ health behavior. Specifically important is understanding users’ systematic behavior change through wearables. Constructive digitalization of the healthcare system requires a deeper understanding of why some users change their behavior and others do not. Based on self-leadership theory and our analysis of narrative interviews with 50 long-term wearable users, we identify four wearable use patterns that bring about different behav- ioral outcomes: following, ignoring, combining, and self-leading. Our study contributes to self-leadership theory and research on individual health information systems and has practical implications for wearable and healthcare providers.

Wearables provide great opportunities for improving personal health, but research challenges their capacity to evoke behavioral change effectively. Realizing the full potential of wearables requires a better understanding of users’ behavior change processes. Based on self-efficacy theory, we investigate how wearables influence users’ perceptions of their self-efficacy and subsequent health behavior. Using narrative interviews with twenty-five long-term wearable users, we show that wearables can have both positive and negative effects on users’ perceptions of their self-efficacy and that these perceptions are subject to internal and external contexts, which can positively or negatively affect users’ compliance. We also find that the internal context may have a compounding or neutralizing effect on self-efficacy, despite an adverse external context. Our study shows the contextual and transient nature of self-efficacy, thus contributing to self-efficacy theory and research on wearables and offering practical design implications.

The proliferation of digital devices and services has fundamentally changed customer behavior and needs and thus the manner in which customers engage with firms. Many customers want to engage with firms across both online and offline channels, enjoying seamless switching and simultaneous use. In this changing environment, the omnichannel concept has been proposed as an appropriate approach to satisfy these customer demands. In practice, however, only a few firms have successfully initiated a transition from a multichannel business to an omnichannel business by integrating channels. One major challenge associated with channel integration is that of deploying the necessary dynamic capabilities that enable management to reconfigure the organization. Against this backdrop, we draw on the dynamic capability perspective to examine how firms transitioned to omnichannel management by the combination of adaptive organization principles and omnichannel retail information systems. For this purpose, this study sheds light on the microfoundations of the firms’ IT-enabled dynamic capabilities. The research is based on two qualitative case studies of a click-and-mortar retailer and an insurance firm that have transitioned to an omnichannel approach by successfully integrating their online and offline distribution channels. The findings make four primary contributions to theory and practice. First, they extend the literature on omnichannel business by discussing microfoundations related to channel integration grounded in empirical data. Second, our results provide relevant insights for information systems scholars on IT’s contribution to achieving the target of an omnichannel business. Third, the study contributes to research regarding dynamic capabilities by providing empirical insights into how firms deploy dynamic capabilities in practice. Fourth, for practitioners, this research provides valuable decision support on how to transform their organizations toward an omnichannel approach.

This paper reports on an exploratory, multisite case study of four organizations from the insurance, banking, telecommunications, and e-commerce industries that implemented big data analytics (BDA) technologies to provide individualized service to their customers. Grounded in our analysis of these four cases, a theoretical model is developed that explains how the flexible and reprogrammable nature of BDA technologies provides features of sourcing, storage, event recognition and prediction, behavior recognition and prediction, rule-based actions, and visualization that afford (1) service automation and (2) BDA-enabled human-material service practices. The model highlights how material agency (in the case of service automation) and the interplay of human and material agencies (in the case of human-material service practices) enable service individualization, as organizations draw on a service-dominant logic. The paper contributes to the literature on digitally enabled service innovation by highlighting how BDA technologies are generative digital technologies that provide a key organizational resource for service innovation. We discuss implications for research and practice.

Digital Nudging can influence user behavior in the digital context by the targeted design of user interfaces. Based on behavioral economics, psychological effects can be utilized or counteracted to support users in decision-making. If applied systematically, digital nudging can enhance the user experience and add significant value to the business.

The goal of digital nudging, a concept based on insights from behavioural economics, is to influence decision-making in digital choice environments. Information systems scholars increasingly see digital nudging as a promising research field, as do practitioners in the field of user interface, user experience, and digital service design. However, the use of digital nudging is not widespread because practitioners are often unaware of the concept or they do not have a systematic approach with which to apply it. Using a design science research approach, we develop the Digital Nudge Design method and evaluate its applicability and usefulness in practice. The method is based on requirements deduced from literature on digital nudging and persuasive systems and frominterviews with practitioners from five case organizations. The study contributes to research that seeks to develop methods for influential user interface design, and the method supports researchers and practitioners in designing digital nudges.

The paper presents guidelines for education in business and information systems engineering (BISE) at tertiary institutions, which were designed by a working group comprising domain experts, both from academia and practice. The guidelines contain the learning outcomes in Bachelor’s and Master’s degree programs, in particular, the key subject-specific, social, and personal skills needed by BISE graduates. Moreover, corresponding occupational profiles, the specific skills required, as well as the essential and typical learning content for BISE education are described. Furthermore, detailed recommendations for the design of Bachelor’s and Master’s degrees curricula and sub-curricula in BISE, business administration, and com- puter science, respectively, are provided. The presented guidelines serve several purposes. Providing common directions for BISE education is aiming to support per- sonnel in charge of curriculum development and to assist students in program and career choice.

Linking social networks with government applications promises various benefits, such as improving citizens’ public engagement, increasing transparency and openness in government actions, and new or enhanced government services. The research goal is to drive innovation in governments through the integration of user activities from social networks into government applications. Instead of using third-party social media tools, we call for self-developing integration software, so that the government retains full control of the sensitive government data that is linked to social network user data. Following a design science approach, we developed a data model of user activities in social networks. Our 40 user activity types conceptualize the common fundamental data structure and are a means for comparing current features of ten prominent social networks. We find that a substantial share of user activities can be mutually integrated by wrapping social network Application Programming Interfaces (APIs).