Exploring the Relationships Between Knowledge Management and Information Systems: No Decomissioning

In recent years the discipline of Knowledge Management (KM) has emerged as a supposedly useful approach to leveraging organisational assets in order to obtain a variety of business benefits. However, this is easier said than done. For KM to be effective organisations must reflect on three key issues - infrastructure, culture and technology. While some may chose to emphasise the socio-cultural issues over the technology issues, more recent research (Gallagher & Hazlett, 2000) has pursued a path of normalization in relation to these three key aspects. Regardless of where KM has originated from it is clear that Information Systems (IS) and associated Information Technology (IT) can and will play an important role, if only as an enabler. This paper concentrates on the difficulties associated with implementing and evaluating KM in practice. It explicitly advocates the use of IS/IT and associated models as a response to the problems faced. The results of an exploratory interview study indicate that (a) many firms are relying heavily on IS/IT to support their KM strategies and (b) IS techniques offer a useful response to some of the problems encountered

Evaluation of Conceptual Models - A Structuralist Approach

The quality and thus the validation of conceptual models are of high economic importance. However, only little empirical work has focused on their evaluation so far. This raises the question whether a holistic approach to determining the quality of conceptual models is available yet. In order to describe the current state of research and to expose the so far neglected research fields we develop a two dimensional framework. With the help of this framework we can identify a notable shortcoming on conceptual model evaluation. Contrary to models on theories a lot of empirical work has been performed. Therefore we apply the structuralist approach from philosophy of science in order to develop an inner structure of conceptual models. Based on these findings we deduce the structural requirements that conceptual models shall meet. We explain the practical implications of our proposal and sketch an outlook to future scientific inquiries

Towards a Strategy Design Method for Corporate Data Quality Management

Large, multidivisional enterprises need corporate data of high quality in order to meet a number of strategic business requirements, such as enterprisewide process harmonization, integrated customer management or compliance. Therefore, many enterprises today are in the process of establishing Corporate Data Quality Management (CDQM), which requires an overarching CDQM strategy. This paper presents a method for the development and implementation of a CDQM strategy. On the one hand the method provides guidance to a CDQM team. On the other hand, for corporate executives the method ensures that the CDQM strategy is derived from their objectives and that their requirements are systematically taken into account and fulfilled. Besides the method itself, the paper illustrates the entire design process which encompasses, among others, focus group and expert interviews, participative case studies and a multiperspective evaluation

Dealing with Complexity: A Method to Adapt and Implement a Maturity Model for Corporate Data Quality Management

Reference models usually serve as starting points for developing company specific models. Unfortunately, successful usage of reference models is often impeded by various aspects, such as a lack of acceptance among employees, incorrect model implementation, or high project costs - all of which more often than not are resulting from an imbalance between the model\u27s complexity and the complexity of a company\u27s specific structures. The paper at hand develops a methodical approach for taking a given reference model (the Maturity Model for Corporate Data Quality Management) and transforming it into a company specific model, with a particular focus on the specific complexity of a company\u27s structures. Corporate Data Quality Management describes the quality oriented organization and control of a company\u27s key data assets such as material, customer, and vendor data. Two case studies show how the method has been successfully implemented in real-world scenarios

Digital Business Engineering: Methodological Foundations and First Experiences from the Field

Digitization is affecting almost all areas of business and society. It brings about opportunities for enterprises to design a digital business model. While a significant amount of research exist examining the conceptual foundation of business models in general, no comprehensive approach is available that helps enterprises in designing a digital business model. This paper addresses this gap and proposes Digital Business Engineering as a method for digital business model design. The activities are structured into six phases, namely End-to-End Customer Design, Business Ecosystem Design, Digital Product/Service Design, Digital Capability Design, Data Mapping, and Digital Technology Architecture Design. The method development follows principles of design-oriented research. Five case studies are used to analyse method requirements and evaluate it within is natural context

Ontological Evaluation of Conceptual Models

The objective of this paper is to present a philosophically sound approach to conceptual model evaluation. Accordingly, the ontological evaluation of conceptual models is enriched with a linguistic interpretivist perspective. The need for such an approach to evaluation is justified by the substantial economic importance of conceptual models. The quality of a conceptual model has a significant impact on other IT artefacts and, thus, on the costs of IT projects. However, little research has so far focused on their evaluation. In the course of this paper, we develop a framework which describes the current state of research and recognizes neglected research fields. With the aid of this framework we identify a notable shortcoming in conceptual model evaluation research, especially with respect to philosophically sound evaluation procedures. Based on these findings we address the following research questions: What are the shortcomings in current evaluation research, what are the merits of ‘ontological evaluation’ in this context, and how can the linguistic interpretivist approach help to form a comprehensive and philosophically sound conceptual model evaluation approach

Requirements elicitation: A survey of techniques, approaches, and tools

Requirements elicitation is the process of seeking, uncovering, acquiring, and elaborating requirements for computer based systems. It is generally understood that requirements are elicited rather than just captured or collected. This implies there are discovery, emergence, and development elements in the elicitation process. Requirements elicitation is a complex process involving many activities with a variety of available techniques, approaches, and tools for performing them. The relative strengths and weaknesses of these determine when each is appropriate depending on the context and situation. The objectives of this chapter are to present a comprehensive survey of important aspects of the techniques, approaches, and tools for requirements elicitation, and examine the current issues, trends, and challenges faced by researchers and practitioners in this field. © 2005 Springer-Verlag Berlin Heidelberg

Emergency Response Information System Interoperability: Development of Chemical Incident Response Data Model

Emergency response requires an efficient information supply chain for the smooth operations of intra- and inter-organizational emergency management processes. However, the breakdown of this information supply chain due to the lack of consistent data standards presents a significant problem. In this paper, we adopt a theory- driven novel approach to develop an XML-based data model that prescribes a comprehensive set of data standards (semantics and internal structures) for emergency management to better address the challenges of information interoperability. Actual documents currently being used in mitigating chemical emergencies from a large number of incidents are used in the analysis stage. The data model development is guided by Activity Theory and is validated through a RFC-like process used in standards development. This paper applies the standards to the real case of a chemical incident scenario. Further, it complies with the national leading initiatives in emergency standards (National Information Exchange Model

An Open Platform for Modeling Method Conceptualization: The OMiLAB Digital Ecosystem

This paper motivates, describes, demonstrates in use, and evaluates the Open Models Laboratory (OMiLAB)—an open digital ecosystem designed to help one conceptualize and operationalize conceptual modeling methods. The OMiLAB ecosystem, which a generalized understanding of “model value” motivates, targets research and education stakeholders who fulfill various roles in a modeling method\u27s lifecycle. While we have many reports on novel modeling methods and tools for various domains, we lack knowledge on conceptualizing such methods via a full-fledged dedicated open ecosystem and a methodology that facilitates entry points for novices and an open innovation space for experienced stakeholders. This gap continues due to the lack of an open process and platform for 1) conducting research in the field of modeling method design, 2) developing agile modeling tools and model-driven digital products, and 3) experimenting with and disseminating such methods and related prototypes. OMiLAB incorporates principles, practices, procedures, tools, and services required to address the issues above since it focuses on being the operational deployment for a conceptualization and operationalization process built on several pillars: 1) a granularly defined “modeling method” concept whose building blocks one can customize for the domain of choice, 2) an “agile modeling method engineering” framework that helps one quickly prototype modeling tools, 3) a model-aware “digital product design lab”, and 4) dissemination channels for reaching a global community. In this paper, we demonstrate and evaluate the OMiLAB in research with two selected application cases for domain- and case-specific requirements. Besides these exemplary cases, OMiLAB has proven to effectively satisfy requirements that almost 50 modeling methods raise and, thus, to support researchers in designing novel modeling methods, developing tools, and disseminating outcomes. We also measured OMiLAB’s educational impact