It covers all aspects of BPM and KM: the functional, organizational, behavioral, informational, intentional and knowledge perspectives. This meta-model is semantically rich and well founded on COOP, a core ontology of organization’s processes. In this paper, we propose a new multi-perspective meta-model of business processes modeling for knowledge management (KM), called BPM4KI (Business Process Meta-Model for Knowledge Identification). the SLR itself, a context-aware roadmap, along with a context model inspired by the Zachman framework, and is a first step towards a decision support system for selecting the appropriate BPM formalism.īusiness process modeling (BPM) has become primary concern for any successful organization to improve the management of their individual and collective crucial knowledge. The contribution of this paper is threefold viz. To this end, a systematic literature review (SLR) of studies on BPM formalisms quality has been undertaken. Our aim in this paper, is to propose a context-aware roadmap with associated methodological guidelines underpinning the selection of the appropriate BPM formalism. Such an improper choice is due not only to the availability of a huge number of BPM formalisms but also to the lack of guidelines assisting in the selection process. This can take place, inter alia, when an inappropriate choice of a BPM formalism for a given BPM context has been made. The importance of BPM to Business Process Management can be justified by the serious problems, which may arise in the latter, if the former is not conducted correctly. The proposed methodological roadmap is specified using a modeling formalism (MAP) which considers the “decision” as a first-class citizen.īusiness Process Modeling (BPM) is the cornerstone of the Business Process Management field, which has become a crucial topic in the competitiveness of enterprise information systems. The results presented in the current paper stand for a first step toward a reference framework for helping researchers and practitioners in choosing the most appropriate BP modeling formalism given a set of contextual variables. It proposes a methodological roadmap as a basis for developing a selection support system. This paper is the first contribution toward responding to this need. Hence, there is a need for both a combination of these research labors into a single reference source and an approach to support such combination. Nevertheless, these research efforts still scattered throughout a wide range of publications, unlinked and often with a narrow scope. Many frameworks have therefore been proposed in order to guide the selection of the most suitable formalism. This can take place, for instance, in the case of an inappropriate choice of a BP modeling formalism. The importance of business process (BP) modeling to Business Process Management can be justified by the serious problems, which may arise in the latter, if the former is not conducted correctly. Based on our findings, we articulate a set of recommendations for improving its application, development, testing, and evaluation. We review Representation Theory, examine how it has been used, and critically evaluate its contributions and limitations. Given the burgeoning literature on the theory over time, both positive and negative, the time is ripe for a narrative, developmental review. Nonetheless, the theory has attracted repeated criticisms regarding its validity, relevance, usefulness, and robustness. The original theory has also inspired further development of its core premises and advances in methodological guidelines to improve its use and evaluation. 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. 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.

Business process modelling languages