Stages of Information Systems in E-Government for Knowledge Management

2011 ◽  
pp. 270-280
Author(s):  
Petter Gottschalk
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Police Officers ◽  
Growth Models ◽  
Knowledge Work ◽  
Management Systems ◽  
Financial Crime ◽  
Knowledge Management Systems ◽  
Knowledge Intensive ◽  
Direction Information

A stage model for knowledge management systems in policing financial crime is developed in this chapter. Stages of growth models enable identification of organizational maturity and direction. Information technology to support knowledge work of police officers is improving. For example, new information systems supporting police investigations are evolving. Police investigation is an information-rich and knowledge-intensive practice. Its success depends on turning information into evidence. This chapter presents an organizing framework for knowledge management systems in policing financial crime. Future case studies will empirically have to illustrate and validate the stage hypothesis developed in this paper.

Semantic Integration of Structured and Unstructured Data in Data Warehousing and Knowledge Management Systems

2011 ◽  
pp. 81-105
Author(s):  
Liane Haak
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Data Warehousing ◽  
Semantic Integration ◽  
Unstructured Data ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Application Area ◽  
Ontology Integration ◽  
Basic Ideas

Nowadays, increasing information in enterprises demands new ways of searching and connecting the existing information systems. This chapter describes an approach for the integration of structured and unstructured data focusing on the application to Data Warehousing (DW) and Knowledge Management (KM). Semantic integration is used to improve the interoperability between two well-known and established information systems in the business context of nowadays enterprises. The objective is to introduce a semantic solution in the field of Business Intelligence based on ontology integration. The main focus of this chapter is not to provide a complete literature review of all existing approaches or just to point put the motivation for such an approach. In fact, it presents, under consideration of the most important research approaches, a solution for how a Semantic Integration could be technically achieved in this specific application area. After pointing out the motivation, a short introduction to Semantic Integration, the problems and challenges occurring from it, and the application area of Knowledge Management and Data Warehousing are given. Besides the basic ideas of ontologies and ontology integration are introduced. The approach itself starts with a short overview on the determined requirements, followed by a concept for generating an ontology from a Data Warehouse System (DWS) to be finally integrated with Knowledge Management Systems (KMS) ontology. Finally SENAGATOR, an exemplarily system for semantic navigation based on integrated ontologies, is shortly introduced.

MEASURING THE CONTRIBUTIONS OF KNOWLEDGE MANAGEMENT SYSTEMS TO THE STRATEGIC COMPETITIVENESS OF ORGANIZATIONS: A REVIEW AND A MODEL

2010 ◽  
Vol 07 (02) ◽  
pp. 89-107 ◽  
Author(s):  
ELIE GEISLER
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Absorptive Capacity ◽  
Knowledge Systems ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Multi Stage ◽  
Intermediate Outcomes ◽  
Stage Process ◽  
The Relationship

Why and how do Knowledge Management Systems (KMS) contribute to the strategic competitiveness of organizations? This paper reviews the literature and proposes a model in which KMS is viewed from three different perspectives: (1) crucial resource; (2) driver of absorptive capacity; and (3) innovation adopted by the organization. The paper critiques the method used by KMS researchers whereby co-variation of KMS and competitiveness is utilized to study the relationship between these variables. The model proposed here is a multi-stage process. The successful use of KMS generates intermediate outcomes that in turn impact the organization and produces improved strategic competitiveness. The different approaches to KMS and the stage-process allow for the unique attributes of knowledge systems, different from information systems. The advantages and limitations of the model are discussed.

Ontology

2017 ◽  
pp. 79-102
Author(s):  
Syed Raiyan Ghani
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Information Systems ◽  
Cognitive Process ◽  
Information Overload ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Library Users

Library requires mighty technologies to support, sort and categorize information in the shortest span of time for better knowledge-tasks and decision-making. Ontology is one of the needs and adroitness which helps library users in acquiring better standardized vocabulary, better routes and better search. The chapter discusses how ontology libraries can process as a connection in modifying versatile users and diligence to reveal, judge, utilize, and disseminate the information overload. The Ontology–based Information Systems (IS) and Knowledge Management Systems (KMS) helps cognitive process of reaching a decision which are used to draw out user information and fuzzy ontologies are applied to store the accumulated knowledge.

Knowledge Management Systems

2011 ◽  
pp. 181-205 ◽  
Author(s):  
Dick Stenmark ◽  
Rikard Lindgren
Keyword(s):  
Knowledge Management ◽  
Design Theory ◽  
Work Practice ◽  
Knowledge Work ◽  
Critical Issue ◽  
Lessons Learned ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Simple Question ◽  
The Relationship

This chapter is motivated by one simple question: Why do so many knowledge management systems (KMS) fail when implemented in organizational knowledge work practice? Indeed, imbalance between the desire for accurate content and the workload required to achieve this still appears to be a critical issue, resulting in KMS of little use for organizational members. Hence, KMS maintenance is an important research subject. With the objective to contribute recommendations for how to integrate KMS with everyday knowledge work, we apply general lessons learned from development of groupware applications as a theoretical lens to analyze empirical experiences of three implemented and evaluated KMS. Theorizing the relationship between the recommendations developed and extant KMS design theory, the chapter offers implications for IS research and practice.

Stages of Knowledge Management Systems

2007 ◽  
pp. 71-93
Author(s):  
Petter Gottschalk
Keyword(s):  
Knowledge Management ◽  
Knowledge Work ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Stage Model ◽  
Organizational Evolution ◽  
Multistage Model ◽  
Storage And Retrieval ◽  
Management Technology ◽  
It Applications

Knowledge management systems refer to a class of information systems applied to manage organizational knowledge. These systems are IT applications to support and enhance the organizational processes of knowledge creation, storage and retrieval, transfer, and application (Alavi & Leidner, 2001). The knowledge management technology stage model presented in this chapter is a multistage model proposed for organizational evolution over time. Stages of knowledge management technology are a relative concept concerned with IT’s ability to process information for knowledge work. The knowledge management technology stage model consists of four stages (Gottschalk, 2005). When applied to law enforcement in the following chapters, the stages are labeled officer-to-technology, officer-to-officer, officer-to-information, and officer-to-application.

Knowledge Management Systems

2011 ◽  
pp. 442-450 ◽  
Author(s):  
Ronald Maier ◽  
Thomas Hadrich
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Content Management ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Future Trends ◽  
E Learning ◽  
Abstract Level ◽  
State Of Practice ◽  
Content Management Systems

Knowledge management systems (KMSs) are seen as enabling technologies for an effective and efficient knowledge management (KM). However, up to date the term knowledge management system has often been used ambiguously. Examples are its use for specific KM tools, for KM platforms, or for (a combination of) tools that are applied with KM in mind. So far, investigations about the notion of KMS remain on the abstract level of what a KMS is used for, for example, “a class of information systems applied to managing organizational knowledge” (Alavi & Leidner, 2001, p. 114). The following two sections define the term KMS and obtain a set of characteristics that differentiates KMS from traditional information systems, such as intranet infrastructures, document- and content-management systems, groupware, or e-learning systems. Then, two ideal architectures for KMS are contrasted. It is discussed which KMS architecture fits what type of KM initiatives, and some empirical findings on the state of practice of KMS are summarized. The last sections give an outlook on future trends and conclude the article.

Does Knowledge Management Systems Moderate Turnover Effects?

2013 ◽  
Vol 9 (4) ◽  
pp. 1-16
Author(s):  
Davi Nakano ◽  
Renato de Oliveira Moraes ◽  
Ana Paula Pereira de Moraes Ress
Keyword(s):  
Knowledge Management ◽  
Organizational Performance ◽  
Time Lag ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Negative Effects ◽  
Knowledge Assets ◽  
Software Development Teams ◽  
Knowledge Intensive ◽  
And Performance

Knowledge assets are key to innovative capability, but are perishable and may decay over time. Knowledge Management Systems (KMS) can prevent knowledge decay and maintain and enhance performance and innovation. This paper investigates if the use of a KMS mitigates employee turnover negative effects on organizational performance. Data on turnover and project performance from two software development teams from the same corporation were collected and compared. One team adopted and uses a KMS to support development, while the other did not implement a KMS. Paired t-tests were performed and confirmed that KMS usage moderate turnover impact on organizational performance. There is also evidence that, when KMS are not used, turnover and performance are correlated with a time lag. From a practical stance, results indicate that knowledge intensive firms can avoid knowledge assets loss by implementing a KMS.

Back to the future of Knowledge Management Systems off the beaten paths

2020 ◽  
Vol 58 (9) ◽  
pp. 1953-1984
Author(s):  
Roberto Cerchione ◽  
Piera Centobelli ◽  
Pierluigi Zerbino ◽  
Amitabh Anand
Keyword(s):  
Knowledge Management ◽  
Information Systems ◽  
Knowledge Translation ◽  
Management Systems ◽  
Knowledge Management Systems ◽  
Collaborative Relationships ◽  
Content Type ◽  
Research Questions ◽  
Forms Of Knowledge

PurposeThe evolution of Knowledge-Management (KM)-related literature has highlighted that Knowledge Management Systems (KMSs) have undergone massive changes in collaborative environments. Information-Systems-enabled KM seems to be the necessary response to the recent challenges posed by globalisation and technology dynamics to both large companies (LCs) and small and medium enterprises (SMEs).Design/methodology/approachThis paper provides a systematic review about KMSs to offer an analytical overview of their role in supporting innovative forms of knowledge translation occurring in collaborative relationships. A sample of 129 papers was selected and analysed according to three perspectives: unit of analysis (LCs, SMEs), phases of the KM process (adoption, translation) and topic area (KM Practices, KM Tools, KMSs).FindingsThe findings highlight five literature gaps: (1) the role of KM practices supporting knowledge translation; (2) the impact of the alignment among KM practices, firm's complexity, dimension and culture on KM process; (3) the effect of KM tools on knowledge translation; (4) the variety of KMSs exploited in both LCs and SMEs; and (5) the alignment between organisational structure and information systems in KM context. Accordingly, 13 research questions were formulated.Originality/valueThe proposed research questions define a formal research agenda that could steer further research efforts about the KMS topic for improving the body of knowledge in the KM field. Scientific literature is currently lacking a contribution assessing the role of KMSs in supporting innovative forms of knowledge translation that occur in collaborative relationships.

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