No abstract

No abstract

Simulations provide a useful methodological approach for studying the behavior of complex socio-technical information systems (IS), in which humans and IT artefacts 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 adequately. Therefore, this paper first analyses the particularities of simulation-based IS research that distinguish this approach from other, more conventional approaches. Based on this analysis, we then conduct a structured literature review of the status quo of simulation-based IS research, to understand how IS researchers currently employ simulation. In combination, a comparison of the theoretical potential of simulation-based research in IS with its current status quo enables us to derive a set of propositions, which provide guidance for prospective simulationbased research.

While there is a general agreement on the need for tools, which guide the evolution of complex organizational systems, and while there already exists a wealth of tools and approaches for the measurement and management of complexity, it seems that in practice these approaches often fail to achieve the desired impact during transformation processes. Based on focus group data and based on related literature, we analyze the factors that hinder current complexity management systems from guiding enterprise transformations and contribute a set of design principles, which address these factors. In particular, it is important to be aware of the context, to use a consistent ontology, to pay attention to visualization and to raise awareness and support.

Significant investments in information systems (IS) over the past decades have led to increasingly complex IS architectures in organisations, which are difficult to understand, operate, and maintain. We investigate this development and associated challenges through a conceptual model that distinguishes four constituent elements of IS architecture complexity by differentiating technological from organisational aspects and structural from dynamic aspects. Building on this conceptualisation, we hypothesise relations between these four IS architecture complexity constructs and investigate their impact on architectural outcomes (i.e., efficiency, flexibility, transparency, and predictability). Using survey data from 249 IS managers, we test our model through a partial least squares (PLS) approach to structural equation modelling (SEM). We find that organisational complexity drives technological complexity and that structural complexity drives dynamic complexity. We also demonstrate that increasing IS architecture complexity has a significant negative impact on efficiency, flexibility, transparency, and predictability. Finally, we show that enterprise architecture management (EAM) helps to offset these negative effects by acting as a moderator in the relation between organisational and technological IS architecture complexity. Thus, organisations without adequate EAM are likely to face large increases in technological complexity due to increasing organisational complexity, whereas organisations with adequate EAM exhibit no such relation.