Novices’ Quality Perceptions and the Acceptance of Process Modeling Grammars

As Process Modeling Grammars provide a means to visualize and communicate complex business processes, it is crucial to convince novices to adopt them for every-day business. As their drivers of acceptance are widely unknown, my study develops a trans-disciplinary quality approach to investigate how quality perceptions affect novices’ adoption intentions. The survey data were analyzed using PLS-SEM. The main result of my study is that the identified quality dimensions are interrelated and differ in their impact on adoption intentions. This provides a ‘new’, coherent view on quality perceptions of modelling grammars and deeper insights into how they affect behavioral intentions

Information Systems as Representations: A Review of the Theory and Evidence

Representation theory proposes that the basic purpose of an information system (IS) is to faithfully represent certain real-world phenomena, allowing users to reason about these phenomena more cost- effectively than if they were observed directly. Over the past three decades, the theory has underpinned much research on conceptual modeling in IS analysis and design and, increasingly, research on other IS phenomena such as data quality, system alignment, IS security, and system use. The original theory has also inspired further development of its core premises and advances in methodological guidelines to improve its use and evaluation. Nonetheless, the theory has attracted repeated criticisms regarding its validity, relevance, usefulness, and robustness. Given the burgeoning literature on the theory over time, both positive and negative, the time is ripe for a narrative, developmental review. We review representation theory, examine how it has been used, and critically evaluate its contributions and limitations. Based on our findings, we articulate a set of recommendations for improving its application, development, testing, and evaluation

How do Individuals Interpret Multiple Conceptual Models? A Theory of Combined Ontological Completeness and Overlap

When analyzing or designing information systems, users often work with multiple conceptual models because each model articulates a different, partial aspect of a real-world domain. However, the available research in this area has largely studied the use of single modeling artifacts only. We develop a new theory about interpreting multiple conceptual models that details propositions for evaluating how individuals select, understand, and perceive the usefulness of multiple conceptual models. We detail implications of our theory development for empirical research on conceptual modeling. We also outline practical contributions for the design of conceptual models and for choosing models for systems analysis and design tasks. Finally, to stimulate research that builds on our theory, we illustrate procedures for enacting our theory and discuss a range of empirically relevant boundary condition

How Collaborative Technology Supports Cognitive Processes in Collaborative Process Modeling: A Capabilities-Gains-Outcome Model

We examine which capabilities technologies provide to support collaborative process modeling. We develop a model that explains how technology capabilities impact cognitive group processes, and how they lead to improved modeling outcomes and positive technology beliefs. We test this model through a free simulation experiment of collaborative process modelers structured around a set of modeling tasks. With our study, we provide an understanding of the process of collaborative process modeling, and detail implications for research and guidelines for the practical design of collaborative process modeling

Cognition Matters: Enduring Questions in Cognitive IS Research

We explore the history of cognitive research in information systems (IS) across three major research streams in which cognitive processes are of paramount importance: developing software, decision support, and human-computer interaction. Through our historical analysis, we identify “enduring questions” in each area. The enduring questions motivated long-standing areas of inquiry within a particular research stream. These questions, while perhaps unapparent to the authors cited, become evident when one adopts an historical perspective. While research in all three areas was influenced by changes in technologies, research techniques, and the contexts of use, these enduring questions remain fundamental to our understanding of how to develop, reason with, and interact with IS. In synthesizing common themes across the three streams, we draw out four cognitive qualities of information technology: interactivity, fit, cooperativity, and affordances. Together these cognitive qualities reflect IT’s ability to influence cognitive processes and ultimately task performance. Extrapolating from our historical analysis and looking at the operation of these cognitive qualities in concert, we envisage a bright future for cognitive research in IS: a future in which the study of cognition in IS extends beyond the individual to consider cognition distributed across teams, communities and systems, and a future involving the study of rich and dynamic social and organizational contexts in which the interplay between cognition, emotion, and attitudes provides a deeper explanation of behavior with IS

The Effects of Decomposition Quality and Multiple Forms of Information on Novices’ Understanding of a Domain from a Conceptual Model

Individuals can often use conceptual models to learn about the business domain to be supported by an information system. We investigate the extent to which such models can help novices (i.e., individuals who lack knowledge in the business domain and in conceptual modeling) to obtain an understanding of the domain codified in the model. We focus on two factors that we predict will influence novices’ understanding: (1) decomposition quality: whether the conceptual model manifests a good decomposition of the domain, and (2) multiple forms of information: whether the conceptual model is accompanied by information in another form (e.g., a textual narrative). We hypothesize that both factors will have positive effects on understanding and that these effects depend on whether the individual seeks a surface or deep understanding. Our results are largely in line with our predictions. Moreover, our results suggest that while novices are generally aware that having multiple forms of information affects their understanding, they are unaware that decomposition quality affects their understanding. Based on these results, we recommend that practitioners include complementary forms of information (such as a textual narrative) along with conceptual models and be careful to ensure that their conceptual models manifest a good decomposition of the domain

An Integrative framework of the factors affecting process model understanding : a learning perspective

Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies

An Integrative Framework of the Factors Affecting Process Model Understanding: A Learning Perspective

Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them actually being used. After all, what is not understood cannot be acted upon. Yet until now, understandability has primarily been defined as an intrinsic quality of the models themselves. Moreover, those studies that looked at understandability from a user perspective have mainly conceptualized users through rather arbitrary sets of variables. In this paper we advance an integrative framework to understand the role of the user in the process of understanding process models. Building on cognitive psychology, goal-setting theory and multimedia learning theory, we identify three stages of learning required to realize model understanding, these being Presage, Process, and Product. We define eight relevant user characteristics in the Presage stage of learning, three knowledge construction variables in the Process stage and three potential learning outcomes in the Product stage. To illustrate the benefits of the framework, we review existing process modeling work to identify where our framework can complement and extend existing studies

The Effect of Risk Representation Using Colors and Symbols in Business Process Models on Operational Risk Management Performance

The operational management of risk and internal controls (RIC) makes increasing use of visual representations to support tasks such as risk assessment and control activity definition. The strengths and weaknesses of different representations are typically assessed by cognitive theories that assume an analytical and an intuitive mode of information processing. Previous research has focused mainly on the analytical risk assessment while intuitive information processing has largely been neglected. We develop a theoretical argument based on dual-process theory, which explains why RIC representational alternatives influence different levels of information processing. We test our hypotheses with the help of an online experiment using accountants and operation managers recruited via MTurk (N = 166). Our results suggest that highlighting risk and controls in business process modeling and notation (BPMN) by using color improves risk understanding, control understanding, and the identification of control improvements, which help reduce the risk in a given process. Furthermore, we do not find evidence that the inclusion of color leads to perception biases. This has implications for information systems research, which has primarily addressed the analytical processing of conceptual models. Our findings extend cognitive research on such models by adding an intuitive processing path that can improve the user’s risk management performance. For practitioners, our findings are particularly relevant because colors can be easily added as a secondary notation element without disguising the factual risk situation in processes