Knowledge re-use for decision support

Effective decision support has already been identified as a fundamental requirement for the realisation of Network Enabled Capability. Decision making itself is a knowledge-intensive process, and it is known that right decisions can only be reached based on decision maker's good judgement, which in turn is based on sufficient knowledge. It is not unusual for decision makers to make incorrect decisions because of insufficient knowledge. However, it is not always possible for decision makers to have all the knowledge needed for making decisions in complex situations without external support. The re-use of knowledge has been identified as providing an important contribution to such support, and this paper considers one, hitherto unexplored, aspect of how this may be achieved. This paper is concerned with the computational view of knowledge re-use to establish an understanding of a knowledge-based system for decision support. The paper explores knowledge re-use for decision support from two perspectives: knowledge provider's and knowledge re-user's. Key issues and challenges of knowledge re-use are identified from both perspectives. A structural model for knowledge re-use is proposed with initial evaluation through empirical study of both experienced and novice decision maker's behaviour in reusing knowledge to make decisions. The proposed structural model for knowledge re-use captures five main elements (knowledge re-uers, knowledge types, knowledge sources, environment, and integration strategies) as well as the relationships between the elements, which forms a foundation for constructing a knowledge-based decision support system. The paper suggests that further research should be investigating the relationship between knowledge re-use and learning to achieve intelligent decision support

Towards a Framework for Discovering Project-Based Knowledge Maps

Managing enterprise knowledge for decision support is crucial for enterprises to gain competitive advantages in knowledge-based economy. The valuable knowledge patterns hidden in numerous projects are important assets of enterprises. The management of such project knowledge is becoming increasingly important and challenging for organizational adaptation and survival in the face of continuous environmental change. This work proposes a project-based knowledge map framework to capture project knowledge and discover valuable knowledge patterns from previous projects. A collaborative two-phase data mining approach is applied to extract valuable project attributes, and discover their associations. Moreover, the discovered knowledge patterns are organized in a well-structured knowledge map, which facilitates effective navigation of project knowledge

A Design Theory for Knowledge Transfer in Business Intelligence

Information Systems (IS) have often been the mechanism by which Knowledge Transfer (KT) has beenaccomplished within organizations. However, in the case of Business Intelligence (BI) it is also often the source or theknowledge required to be transferred. While the IS profession has effectively studied explicit knowledge, the conversion oftacit to explicit knowledge (Champika et al. 2009; Parent et al. 2007; Swee 2002) or knowledge creation (Nambisan et al.1999; Nonaka 1994) a gap remains in regards to knowledge adoption and application of transferred tacit knowledge. Thispaper will contribute a design theory to support future research for KT in BI

The Role of Business Information Visualization in Knowledge Creation

Past research suggests that one of the reasons causing Business Intelligence (BI) systems to fall short of expectations could be that certain BI capabilities may not be appropriate for individuals’ or organizational challenges. Our research proposes the need to enhance our understanding of information and knowledge processes to address the issue. We evaluate the appropriateness of adopting the implications of information and knowledge processes to Business Information Visualization (BIV) as one of BI capabilities by exploring how data interaction and data representation reduce information-based challenges of uncertainty and complexity, thus enabling the creation of new insights. Formal model and resulting propositions are offered. Research implications suggest that effective and efficient insight generation can be achieved by deploying BI visualization capabilities only if those capabilities result in knowledge workers’ perception of lower information uncertainty and complexity. Larger implications of this study for BI, BIV and knowledge creation process are discussed

Increasing Research Relevance in DSS: Looking Forward by Reflecting on 40 years of Progress

Decision Support Systems (DSS) is a field that has made rapid progress in establishing itself and maturing into seven key sub-fields. However, there are continued concerns about the relevancy and growing disconnect between academic contributions and professional applications of DSS. This paper serves to review the existing literature, and propose a Research Relevance Framework meant to serve as a guideline to ensure future DSS research has a consistent standard upon which relevance can be assessed

Knowledge Management System’s Characteristics that facilitate Knowledge Sharing to Support Decision Making Processes in Multinational Corporations

Nowadays we are living an era which is marked by efforts for originality, innovation, collaboration, accumulation ofexperience and integration with and through many inventions such as computers, the internet, and technologies that havefacilitated knowledge sharing and communication among people. This research seeks to extend the existing literature onKMS and knowledge sharing by proposing a conceptual framework, namely ECCCT (Evolution, Collaboration, Connection,Codification and Technical) that can be used to study how knowledge management systems (KMS) facilitate knowledgesharing to support decision making processes in multinational corporations (MNC). In this research, 42 semi-structuredinterviews have been conducted with participants from 35 MNC in 11 countries. All participants are KMS professionals,managers and employees in MNC who are using KMS in different sectors and at different levels. The work will assistmanagers in MNC in finding new ways of leveraging and sharing knowledge

Intelligent Agents to Support Information Sharing in B2B E-Marketplaces

This article proposes an architecture to support information and knowledge exchange between collaborating business partners. The focus is on knowledge representation and exchange by intelligent agents to support collaborative business functions through agents that exchange problem-specific information in standardized formats. The article then shows the application of the proposed architecture in the context of an infomediary-based B2B E-marketplace

DEVELOPMENT OF ERP AND OTHER LARGE BUSINESS SYSTEMS IN THE CONTEXT OF NEW TRENDS AND TECHNOLOGIES

This paper presents an overview of terms, concepts, trends and technologies that are relevant to today\u27s business. It describes the basics of data and information integration and flow in a company through a central ERP system with concepts of CRM and SCM. The emergence of big data as a tributary of a huge number of often unstructured data from different sources can become a central problem or opportunity for advancement and achievement of competitive advantages of a company. Ignorance of key figures and/or the non-acceptance of new business conditions, new technologies and possible deployment solutions are the main reasons for non-productivity and poor business performance. To demonstrate the dynamics of appearance and popularity of terms, concepts, trends and technologies this paper offers a tabular overview of the frequencies based on the data from 3 global databases. Meta analysis shows the expected future development of analytical trends and technologies. This paper is intended for those who lead, run and participate in projects of implementation of large software systems, dealing with quality management of business, or want to understand the complexity of this area and the future directions of development

Integration of decision support systems to improve decision support performance

Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes