Calculating with Unreliable Data in Business Analytics Applications

The success of operational and managerial decisions depends on the reliability of the information provided to decision makers by the respective business analytics applications. Thus, in this research-in-progress paper, we explain how the mathematical foundations of the Algebra of Random Varia-bles (AoRV) can be used to extend the capability of business analytics applications to process and report unreliable data. First, we present the theoretical foundations of the AoRV in a concise way that is tailored to business analytics. Second, we present and discuss two example cases, in which we evaluate an application of the AoRV to real-world business analytics scenarios. Initial results from this first design-and-evaluate feedback loop show that the additional reliability information provided by the AoRV is of high value for decision makers, since it allows to predict how uncertain-ties in complex business analytics scenarios will interact. As the next step of this research project, we plan to test the potential of the AoRV to extend business analytics applications through another evaluation loop in a fully natural setting

Simulation-Based Research in Information Systems - Epistemic Implications and a Review of the Status Quo

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 lit- erature review of the status quo of simulation-based IS research was conducted, to understand how IS scholars currently employ simulation. A comparison of the epis- temic 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

DRIVERS AND EFFECTS OF INFORMATION SYSTEMS ARCHITECTURE COMPLEXITY: A MIXED-METHODS STUDY

Today’s organizations deal with a significant complexity of their information systems (IS) architec-ture—a complex cobweb of heterogeneous IS with tight, mutual interrelations. With the constantly in-creasing number of IS along with the inherent complexity of the organizational context in which IS are embedded, organizations lose control of their IS architecture’s evolution. Through employing a se-quential mixed-methods research design, this study investigates the drivers and effects of IS architec-ture complexity. Based on the extant literature and on focus groups data, at the outset we develop a research model and derive its constitutive hypotheses. We subsequently test the research model follow-ing a partial least squares (PLS) approach to structural equation modelling (SEM) with survey re-sponses from 249 IT managers and architects. While differentiating structural and dynamic complexi-ty, this study confirms a high degree of integration, large size, high diversity, strong dynamics, and, in particular, inadequate planning as the main drivers of IS architecture complexity. Further, this study affirms the negative effect of IS architecture complexity on the efficiency, agility, comprehensibility, and predictability of the IS

On the Conceptualization of Information Systems as Socio-Technical Phenomena in Simulation-Based Research

Information Systems (IS) are specified as complex socio-technical systems that display dynamic and emergent behaviors. Simulation-based studies provide a useful tool for analyzing such systems; however, the current presence and impact of simulation-based IS studies is limited. The socio-technical interactions and inherent dynamics of information systems make the development of IS simulations attractive, but challenging. Building simulations in this context requires both accurate conceptualizations of the underlying socio-technical systems as well as a sound transfer of these conceptualizations into simulation models. This study proposes an analysis framework that conjointly captures both the socio-technical system models as well as the derived simulation models. This allows for a critical assessment of the status quo of the extant simulation-based IS research. The identified relations are analyzed and seven propositions are derived, which provide guidance for prospective simulation-based research

List of analyzed papers in "On the Conceptualization of Information Systems as Socio-Technical Phenomena in Simulation-Based Research"

Information Systems (IS) are specified as complex socio-technical systems that display dynamic and emergent behaviors. Simulation-based studies provide a useful tool for analyzing such systems; however, the current presence and impact of simulation-based IS studies is limited. The socio-technical interactions and inherent dynamics of information systems make the development of IS simulations attractive, but challenging. Building simulations in this context requires both accurate conceptualizations of the underlying socio-technical systems as well as a sound transfer of these conceptualizations into simulation models. This study proposes an analysis framework that conjointly captures both the socio-technical system models as well as the derived simulation models. This allows for a critical assessment of the status quo of the extant simulation-based IS research. The identified relations are analyzed and seven propositions are derived, which provide guidance for prospective simulation-based research

The Evolution of Information Systems Architecture: An Agent-Based Simulation Model

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

The impact of enterprise architecture management on information systems architecture complexity

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

Causes and Consequences of Application Portfolio Complexity – An Exploratory Study

Part 2: Regular PapersInternational audienceApplication Portfolio (AP) complexity is an increasingly important and strongly discussed issue by both researchers and practitioners. Application portfolios in large organizations have become more and more difficult to understand, resulting in costly efforts to maintain and operate them. Although this is an urgent topic in large organizations, researchers and industry experts do not yet have a common understanding of this phenomenon and lack appropriate methods to measure and manage the respective complexity. We conduct an exploratory case study with the central enterprise architecture management (EAM) governance team and ten application owners of a large European automotive company to identify and link root causes and consequences of AP complexity. Furthermore, we evaluate possible solutions to decrease or manage this complexity from an application owners perspective. The results are interpreted from a socio-technical systems perspective

Revisiting the Impact of Information Systems Architecture Complexity: A Complex Adaptive Systems Perspective

Organizations constantly adapt their Information Systems (IS) architecture to reflect changes in their environment. In general, such adaptations steadily increase the complexity of their IS architecture, thereby negatively impacting IS efficiency and IS flexibility. Based on a Complex Adaptive Systems (CAS) perspective, we present a more differentiated analysis of the impact of IS architecture complexity. We hypothesize the relation between IS architecture complexity on the one hand, and IS efficiency and IS flexibility on the other hand to be mediated by evolutionary and revolutionary IS change. Subsequently, we test our hypotheses through a partial least squares (PLS) approach to structural equation modelling (SEM) based on survey data from 185 respondents. We find that the direct negative impact of IS architecture complexity on IS efficiency and IS flexibility is no longer statistically relevant when also considering the mediating effects of revolutionary and evolutionary IS change