Jannis Beese

Enterprise architecture management (EAM) is commonly employed by large organizations to coordinate local information system development efforts in line with organization-wide strategic objectives while simultaneously avoiding redundancies and inconsistencies. Even though EAM tools and processes have become increasingly mature over the past decade, many organizations still struggle to generate impact from their EAM initiatives. To this end, we describe how enterprise architects at Commerzbank, a major international bank, employed a control mechanism portfolio perspective to more effectively anchor EAM within the organization. This approach allows to purposefully combine a wide range of different formal and informal EAM control mechanisms, thereby going beyond the formal, topdown driven mechanisms predominantly discussed in EAM literature. Furthermore, such EAM control mechanism portfolios provide an effective means to purposefully realign EAM in reaction to major strategic shifts. The application of this perspective is demonstrated by tracing the evolution of EAM at Commerzbank for more than a decade (2008 to 2018) through a turbulent and challenging competitive environment, resulting in several major strategic realignments that required corresponding adjustments in EAM. We believe that such consciously designed and diversified EAM control mechanism portfolios also provide a useful means for other large organizations to more effectively conduct EAM.

Understanding how information systems (IS) architecture evolves and what outcomes can be expected from the evolution of IS architecture presents a considerable challenge for both research and practice. The evolution of IS architecture is marked by management’s efforts to keep local and short-term IS investments in line with enterprise-wide and long-term objectives, so they often employ coercive mechanisms to enforce enterprise-wide considerations on local actors. However, an organization is shaped by a multitude of heterogeneous local actors’ actions that pursue their own, sometimes conflicting, goals, norms, and values. This study offers a theory-informed simulation model that explores how IS architecture evolves and with what outcomes in various types of organizations. The simulation model is informed by institutional theory to capture various types of organizations that are characterized by different combinations of coercive, normative, and mimetic pressures, and by complex adaptive systems theory to capture the emergent character of IS architecture’s evolution. First, we outline the insights from simulation experiments. Then, building on the simulation model and theoretical insights, we discuss implications for both research and practice.

Simulations provide a useful methodological approach for studying the behavior of complex socio-technical information systems (IS), in which humans and IT artifacts interact to process information. However, the use of simulations is relatively new in IS research and the current presence and impact of simulation-based studies is still limited. Furthermore, simulation-based research is quite different from other approaches, making it difficult to position and evaluate it adequately. Therefore, this paper first analyses the epistemic particularities of simulation-based IS research. Based on this analysis, a structured literature review of the status quo of simulation-based IS research was conducted, to understand how IS scholars currently employ simulation. A comparison of the epistemic particularities of simulation-based research with its status quo in IS literature allows to critically examine epistemic inferences in the respective research process. The results provide guidance for prospective simulation-based IS research through discussing the theory-based derivation of simulation models, as well as different simulation techniques, validation techniques, and simulation uses.

Recent achievements of artificial intelligence (AI) have caused organizations to increasingly bring AI capabilities into their core business processes. Such AI-supported business processes often result in human-AI hybrid systems, which consist of an AI system, which performs most of the execution, and humans, who monitor this execution and occasionally provide additional inputs and overrides. Using sales data from Walmart, we conduct an online study to investigate if human supervision can improve upon state-of-the-art AI forecasts. Furthermore, we analyze the perceptions and behavioral intentions of the human participants over time. We find that human interventions consistently lead to less accurate forecasts and that participants initially underestimate the AI system’s accuracy and overestimate their own potential to improve upon AI forecasts. However, perceptions quickly shift over the course of the study, causing the participants to perceive the AI system increasingly favorably, which also leads to behavioral changes and better hybrid system performance.

In this paper, we define three key performance indicators (KPI) to measure the health of application portfolios (AP) and use the business capability map (BCM) as a visualization lens. Based on a literature review of AP management and BCM practices, we conduct a case study with a large European automotive company to develop three KPIs related to AP complexity, AP quality, and AP impact. The application of the KPIs is illustrated for the BCM of our case study partner and evaluated by conducting expert interviews with ten enterprise architecture experts of the company. Our results provide further insights on AP management practices that are enabled by using the BCM as a holistic visualization tool.