An Information Systems Design Theory for Digital Broker Platforms

Authors accepted manuscriptService platforms are becoming dominant drivers of daily business operations in a digitalized environment. Research focuses on technological and network effects of such platforms, while socio-technical opportunities remain limited. Guidance support in selecting appropriate digital services on a multisided market platform may help companies with low domain knowledge as it increases their benefits by reducing existing barriers in adopting emerging technologies. We adapt the concept of a broker to a digital platform, which instantiates guidance support on multisided markets as core platform element. Further, we abstract the concept of a digital broker platform as an Information Systems (IS) design theory. By providing the necessary components of an IS design theory, we offer the possibility to derive digital broker platform artifacts, which are theoretically and conceptually grounded. We provide design principles for the method artifact and describe their applicability in an exemplary instantiation of the design theory in the domain of cloud computing. Lastly, we present the artifact’s mutability as well as its testable propositions.An Information Systems Design Theory for Digital Broker PlatformsacceptedVersio

A Configurational Approach to Maturity Model Development – Using fsQCA to Build a Multiple-Pathway Maturity Model

Maturity models can be used as tools which depict the developmental trajectories of entity classes in domains and evaluate the relative position of an entity within this framework. However, their development process has been the focus of researchers and practitioners ever since, resulting in different procedures, development approaches, and conceptual models. Thus, a major criticism of maturity models is the often missing conceptual and theoretical grounding when it comes to the interpretation of the concept of maturity. To address this shortcoming, our research approach focuses on the rigorous development of a multiple-pathway maturity model. By following a sequential, theoretically grounded process, the resulting maturity model can be viewed as an instantiation of the predefined conceptual components and characteristics in a predefined domain. We present and discuss the instantiated sector and size-specific maturity model for innovation capability in small industrial firms, which is developed by applying configurational methods on a dataset and thereby offers multiple pathways to maturity. This concept of equifinality is central to our approach. It has rarely been considered in maturity model development research, although it offers the potential to build more realistic models with greater applicability, especially in domains with many interdependencies

Is Motivation always the Key? – Antecedents of Employee-Driven Digital Innovation

Understanding the factors that can explain innovation has received a lot of attention among researchers in the last decades. During the same period, different approaches to innovation have also seen the light of day, among them employee-driven innovation and digital innovation. In this study our aim is to look at a concept that merges these two types of innovation and see how motivation affects employee-driven digital innovation. In our research model we look at how intrinsic, social, and internalized extrinsic motivation affects employee-driven digital innovation, and how variables like strategy and organizational culture can act as explanatory and moderating variables

The Missing Piece – Calibration of Qualitative Data for Qualitative Comparative Analyses in IS Research

Over the last years, configurational research has become increasingly popular in the Information Systems (IS) discipline. Researchers value configurational methods like Qualitative Comparative Analysis (QCA) as their application contributes to a better understanding of complex phenomena. QCA helps to uncover interrelations of conditions that lead to an outcome, building on the principles of equifinality, conjunctural causation, and asymmetry. More recently, IS researchers have started to analyze qualitative data, like case study data, with QCA. However, there is a lack of methodological guidance on how to calibrate qualitative data into set membership values for QCA. Therefore, this paper structures methodological steps and the associated options to calibrate qualitative data from an interdisciplinary perspective and critically reviews the observed methodological choices in IS research. This paper also gives recommendations for calibrating qualitative data to support informed methodological choices for future research

The Potential of Big Data Analytics for Decision Support in Sports – The Case of Soccer

Compared to other popular sports, soccer is quite a fluid sport with high degrees of freedom, which is why evaluating games or single players\u27 performance is more demanding and complex. Even though the availability of different types of soccer data has increased steadily over the last few years, the process of strategic and tactical decision-making is still traditionally done by single specialists. In this context, the potentials of big data analytics (BDA) provide an advantage in automatically assessing and assembling data from various sources and generating insights that exceed the analytical capability of individual human experts. We focus on this potential by developing a design science research-based BDA artifact, which aims at providing strategic decisional support for managers and experts. In several evaluations with different soccer and sports experts, we are able to show advanced usability of the artifact\u27s instantiation over traditional tools provided by large stats providers

From Knowing to Data-Driven Organizations: Review and Conceptual Framework

With companies and other organizations increasingly striving to become (more) data-driven, there has been growing research interest in the notion of a data-driven organization (DDO). In existing literature, however, it seems that different understandings of such an organization emerged. The study at hand sets forth to synthesize the fragmented body of research through a review of DDO understandings in the IS and related literatures. Based on the review results and drawing on the concept of the ‘knowing organization,’ our study identifies five core elements of a DDO (data sourcing & sensemaking, data capabilities, data-driven culture, data-driven decision-making, and data-driven value creation), which we integrate into a conceptual DDO framework. Most notably, the proposed framework suggests that an ideal-typical DDO combines an outside-in view with an inside-out view, thereby setting itself apart from its predecessor, the knowing organization. Theoretical and practical contributions as well as directions for future research are discussed

The Role of Citizens’ Familiarity, Privacy Concerns, and Trust on Adoption of Smart Services

Smart city solutions and applications are considered as a strategic means to cope with multiple global and local challenges such as pollution, energy expenditure and digitalization to name a few. Although these solutions are driven by advanced information technologies such as IoT and Big data, their success is dependent on user engagement and trust. We seek to examine how citizens' awareness and perception of smart cities affect their adoption of smart services.To answer this, we conducted a study in Norway and employed a questionnairereceiving 103 responses. Furthermore, we conducted 12 semi-structured interviewsto obtain further insights. The results show how citizens value the benefitof smart services and how their adoption is influences by engagement and trusttowards them.

Data-Driven Organizations: Review, Conceptual Framework, and Empirical Illustration

With companies and other organizations increasingly striving to become (more) data-driven, there has been growing research interest in the notion of a data-driven organization (DDO). In existing literature, however, different understandings of such an organization emerged. The study at hand sets forth to synthesize the fragmented body of research through a review of existing DDO definitions and implicit understandings of this concept in the information systems and related literatures. Based on the review results and drawing on the established concept of the “knowing organization,” our study identifies five core dimensions of a DDO—namely, data sourcing & sensemaking, data capabilities, data-driven culture, data-driven decision-making, and data-driven value creation—which we integrate into a conceptual DDO framework. Most notably, the proposed framework suggests that—like its predecessor, the knowing organization—a DDO may draw on an outside-in view; however, it may also draw on an inside-out view, or even combine the two views, thereby setting itself apart from the knowing organization. To illustrate our conceptual DDO framework and demonstrate its usefulness, we apply this framework to three empirical examples. Theoretical and practical contributions as well as directions for future research are discussed

Navigating within the Digitalization Journey: Results and Implications of the First Maturity Assessment of German Public Health Agencies

The Covid 19 pandemic revealed the need for Public Health Agencies to mature digitally. To help those agencies with their digitalization endeavor, a public health agency maturity model (PHAMM) has been developed, evaluated, and employed by 366 institutions to determine their digital maturity and to prior-itize actions within digitalization projects. This paper discusses the digital ma-turity of German public health institutions and derives first insights into compo-nents spanning the PHAMM dimensions. Public health agencies can use these components to leverage their digital maturity in future digitalization projects. Im-plications are discussed for how digitalization projects with an enhanced impact can be defined and for future maturity modeling research