Assessing the impact of knowledge management strategies announcements on the market value of firms

Although there is much literature on the relationship between KM strategies and organizational performance, the benefit of KM strategies is not well understood. We addressed this issue by exploring how KM strategies influence a firm's market value using event study methodology. We evaluated the cumulative abnormal returns for KM strategies announced by U. S. firms from 1998 to 2003. Our findings supported the hypothesis that firms’ announcements about their KM strategies provoked positive reactions in the market. More specifically, strategies that focus on either (i) knowledge reusability through IT or (ii) knowledge sharing through informal discussions among employees contributed to higher performance than strategies that emphasized both. This outcome empirically supported our argument that the emphasis on either tacit or explicit knowledge results in a better market value of the firm. Furthermore, the market's reaction to the announcement is dependent on the firm's industry classification. The findings of this study offer insights that may help managers maximize the market impact of their KM strategies.     

Knowledge management systems and organizational knowledge processing challenges: A field experiment

This paper investigates the appropriateness of knowledge management system (KMS) designs for different organizational knowledge processing challenges. Building on the theory of task-technology fit (TTF), we argue that different KMS designs are more effective for different knowledge tasks. An exploratory field experiment was conducted in the context of Internet-based knowledge sharing services to provide empirical support for our hypotheses. The results of our experiment show that a KMS designed to support the goal GENERATE is more appropriate for divergent type knowledge problems because of its affordances for iterative brainstorming processes. Conversely, for convergent type knowledge processing challenges, a KMS with the goal CHOOSE that supports the ability to clarify and to analyze is more effective.     

Towards an evaluation framework for knowledge management systems

In this paper we develop an evaluation framework for Knowledge Management Systems (KMS). The framework builds on the theoretical foundations underlying organizational Knowledge Management (KM) to identify key KM activities and the KMS capabilities required to support each activity. These capabilities are then used to form a benchmark for evaluating KMS. Organizations selecting KMS can use the framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KMS portfolio meet the KM needs of the organization. Other applications of the framework are also discussed.

Social relationship and its role in knowledge management systems usage

The KMS has been widely implemented in organizations. However, its availability does not guarantee that employees have been willing to spend time and effort using it. We explored the use of KMS with emphasis on social relationship. Specifically, social capital theory was employed to establish the social relationship construct and its three dimensions: tie strength, shared norms, and trust. By studying a company that had implemented a KMS, we explored the dimensions of social relationship and its importance in the use of a KMS by employees. A theoretical framework was used to depict the antecedents of employee's usage behavior. Implications for both researchers and practitioners are discussed, especially for companies expecting to exploit knowledge sharing in the Chinese business environment.     

Parallels in knowledge cycles

Knowledge management as an academic discipline is realizing phenomenal growth and international acceptance. However, there still exists no universally accepted framework or model. This paper reviews three of the most well known KM models from similar epistemological and ontological views. The three models reviewed are: Nonaka’s SECI (Japan), March’s Ex-Ex (USA) and Boisot’s I-space (Europe). A number of recommendations for future research based on the similarities and differences among these models pertaining to knowledge management are presented.     

Measuring user satisfaction with knowledge management systems: scale development,purification, and initial test

The shift from a product-based to a knowledge-based economy has resulted in an increased demand for knowledge workers who are capable of higher-order thinking and reasoning to solve intricate problems in the workplace. This requires organizations to introduce knowledge management systems (KMS) for employees and has fueled predictions and speculations about what makes KMS effective. Unfortunately, there are very few empirical studies that examine this issue. Thus, this paper develops a validated instrument to measure user satisfaction as a surrogate measure of KMS effectiveness. Based on a survey of 147 respondents practicing mostly in four international semiconductor manufacturing companies in the Hsin-Chu Science-based Industrial Park in Taiwan suggests a 16-item instrument that measures four dimensions of user satisfaction with knowledge management systems (USKMS) is well-validated. The instrument and comprehensive model proposed in this paper would be valuable to researchers and practitioners interested in designing, implementing, and managing knowledge management systems.     

A knowledge engineering approach to knowledge management

Knowledge management facilitates the capture, storage, and dissemination of knowledge using information technology. Methods for managing knowledge have become an important issue in the past few decades, and the KM community has developed a wide range of technologies and applications for both academic research and practical applications. In this paper, we propose a knowledge engineering approach (KMKE) to knowledge management. First, a knowledge modeling approach is used to organize and express various types of knowledge in a unified knowledge representation. Second, a verification mechanism is used to verify knowledge models based on the formal semantics of the knowledge representation. Third, knowledge models are classified and stored in a hierarchical ontology system. Fourth, a knowledge query language is designed to enhance the dissemination of knowledge. Finally, a knowledge update process is applied to modify the knowledge storage with respect to users’ needs. A knowledge management system for computer repair is used as an illustrative example.     

Determinants of firms' knowledge management system implementation: An empirical study

As knowledge becomes an increasingly valuable and important organizational asset, many firms anticipate that implementing the knowledge management systems (KMS) will effectively support and enhance organizational knowledge management activities. Even some firms regard KMS as an emerging and powerful source of competitive advantages.However, the implementation of KMS differs from that of traditional enterprise information systems. The implementation of KMS is difficult and risky since these systems are unstructured and so technologically innovative. Thus, effort is required to identify determinants affecting KMS implementation in businesses.Based on innovation diffusion theory and technology-organization-environment framework, this study develops and tests an integrated model of knowledge management systems implementation for businesses. Survey data were collected from 291 businesses in Taiwan. Confirmatory factor analysis and logistic regression technique were used test the hypothesized relationships. The results show that technological innovation factors (perceived benefits, complexity, and compatibility), organizational factors (top management support, organizational culture), and environmental factors (competitive pressure) are significant influences on KMS implementation in firms. Finally, the implications and future research on KMS implementation are discussed.     

High Performance Knowledge Bases: four approaches to knowledge acquisition, representation and reasoning for workaround planning

As part of the DARPA-sponsored High Performance Knowledge Bases program, four organisations were set the challenge of solving a selection of knowledge-based planning problems in a particular domain, and then modifying their systems quickly to solve further problems in the same domain. The aim of the exercise was to test the claim that, with the latest AI technology, large knowledge bases can be built quickly and efficiently. The domain chosen was ‘workarounds’; that is, planning how a convoy of military vehicles can ‘work around’ (i.e. circumvent or overcome) obstacles in their path, such as blown bridges or minefields.

This paper describes the four approaches that were applied to solve this problem. These approaches differed in their approach to knowledge acquisition, in their ontology, and in their reasoning. All four approaches are described and compared against each other. The paper concludes by reporting the results of an evaluation that was carried out by the HPKB program to determine the capability of each of these approaches.     

A new process knowledge representation approach using parameter flow chart

Knowledge in various stages of the product development process has become increasingly important for manufacturing companies to improve their performance, especially for those One-of-a-Kind Production (OKP) companies producing highly customized products. Process knowledge is a very special type of knowledge that controls how products are best manufactured. This knowledge can help OKP companies produce high value-added products with better quality at shorter times and at a competitive cost. Process knowledge is normally hard to capture and manage and is even more difficult to represent. This paper proposes a Parameter Flow Chart (PFC) based new knowledge representation method which efficiently combines parameter information, flow chart technology, and visualization technology. The goal of this research is to provide a user-friendly and effective way of representing process knowledge for OKP companies so they can develop and accumulate their own process knowledge repository. The basic definition and principle of the approach will be introduced first and the software system model then proposed. Two related key issues, the modeling of various chart units used in the PFC approach and dealing with expressions containing various parameters, are discussed in detail. The prototype version of the system has been developed and demonstrated with case studies, which has proven the feasibility of the proposed approach.     

Building knowledge base management systems

Advanced applications in fields such as CAD, software engineering, real-time process control, corporate repositories and digital libraries require the construction, efficient access and management of large, shared knowledge bases. Such knowledge bases cannot be built using existing tools such as expert system shells, because these do not scale up, nor can they be built in terms of existing database technology, because such technology does not support the rich representational structure and inference mechanisms required for knowledge-based systems. This paper proposes a generic architecture for a knowledge base management system intended for such applications. The architecture assumes an object-oriented knowledge representation language with an assertional sublanguage used to express constraints and rules. It also provides for general-purpose deductive inference and special-purpose temporal reasoning. Results reported in the paper address several knowledge base management issues. For storage management, a new method is proposed for generating a logical schema for a given knowledge base. Query processing algorithms are offered for semantic and physical query optimization, along with an enhanced cost model for query cost estimation. On concurrency control, the paper describes a novel concurrency control policy which takes advantage of knowledge base structure and is shown to outperform two-phase locking for highly structured knowledge bases and update-intensive transactions. Finally, algorithms for compilation and efficient processing of constraints and rules during knowledge base operations are described. The paper describes original results, including novel data structures and algorithms, as well as preliminary performance evaluation data. Based on these results, we conclude that knowledge base management systems which can accommodate large knowledge bases are feasible. Edited by Gunter Schlageter and H.-J. Schek. Received May 19, 1994 / Revised May 26, 1995 / Accepted September 18, 1995     

A synthetic method for knowledge management performance evaluation based on triangular fuzzy number and group support systems

The purpose of this paper is to propose a systematic method to solve knowledge management performance evaluation (KMPE) problems. This method includes an integrated evaluation process starting from the measurement to the output of KMPE and combines subjective and objective indicators together. Firstly, we established an index system, involving the process of knowledge management, the organizational knowledge structure, economic benefits and efficiency. And based on this index system, a synthetic evaluation method is presented, using triangular fuzzy number to measure indexes and facilitating the KMPE with a group support system (GSS). To know better of the proposed method, we have an example to illustrate. Finally, the empirical study conducted in this paper indicates that the evaluation method has strong practicability and operability. Besides, the evaluation is enabled by using a group support system: the more objective scoring can be achieved due to synchronic/asynchronous and anonymous participation; Decision-makers improve their efficiency by the clear demonstration analysis results. The systematic method of KMPE based on the index system is able to improve organizations’ efficiency in performance evaluation process.     

Development of a knowledge management initiative and system: A case study

As knowledge emerges as the primary strategic resource in the 21st century, many firms in the manufacturing and service sectors alike are beginning to introduce and implement Knowledge Management (KM). Organisations can certainly benefit from its application for enhanced decision support, efficiency and innovation, thus helping them to realise their strategic mission. However, KM is an emerging paradigm, and not many organisations have a clear idea of how to proceed with it. This paper presents the results of a case study conducted in one company in the United Kingdom (UK), the major aim being to identify how it has developed a KM initiative and system. Hopefully, the information extracted from this study will be beneficial to other organisations that are attempting to implement KM or to those that are in the throes of adopting it.     

Restructuring decision tables for elucidation of knowledge

Decision tables are widely used in many knowledge-based and decision support systems. They allow relatively complex logical relationships to be represented in an easily understood form and processed efficiently. This paper describes second-order decision tables (decision tables that contain rows whose components have sets of atomic values) and their role in knowledge engineering to: (1) support efficient management and enhance comprehensibility of tabular knowledge acquired by knowledge engineers, and (2) automatically generate knowledge from a tabular set of examples. We show how second-order decision tables can be used to restructure acquired tabular knowledge into a condensed but logically equivalent second-order table. We then present the results of experiments with such restructuring. Next, we describe SORCER, a learning system that induces second-order decision tables from a given database. We compare SORCER with IDTM, a system that induces standard decision tables, and a state-of-the-art decision tree learner, C4.5. Results show that in spite of its simple induction methods, on the average over the data sets studied, SORCER has the lowest error rate.     

MRM: A matrix representation and mapping approach for knowledge acquisition

Knowledge acquisition plays a critical role in constructing a knowledge-based system (KBS). It is the most time-consuming phase and has been recognized as the bottleneck of KBS development. This paper presents a matrix representation and mapping (MRM) approach to facilitate the effectiveness of knowledge acquisition in building a KBS. The proposed MRM approach, which is based on matrix representation and mapping operations, comprises six consecutive steps for generating rules. The procedure in each step is elaborated. A case study on primarily diagnosing an automotive system is employed to illustrate how the MRM approach works.     

Knowledge management of product design: A requirements-oriented knowledge management framework based on Kansei engineering and knowledge map

For the knowledge management of product design, knowledge innovation is the foundation and motivation for the independent innovation and enhancing the core competitiveness. Most of the product knowledge exists in the brain of designers. How to obtain the required knowledge accurately in massive knowledge database becomes the key to knowledge innovation. However, the design knowledge based on consumer’s requirement has not been extensively studied. There is no consensus on the reasonable and effective implementation of the knowledge management framework to select the optimum design knowledge based on the consumer’s requirements. In this study, to efficiently realize the knowledge acquisition and knowledge selection, a requirements-oriented knowledge management model is established, with the advantage of Kansei engineering in knowledge acquisition and multi-objective decision-making in knowledge selection. Finally, the outdoor leisure chairs design is used as a case study to explain the implementation of the knowledge management framework. To reveal the advantages of the framework, it was compared with other frameworks. The results show that the proposed knowledge management framework is more efficient and provided a method of designers to acquire design knowledge based on the consumer’s requirements.     

Developing a distributed knowledge model for knowledge management in collaborative development and implementation of an enterprise system

Recently, enterprise systems have been extensively adopted to boost enterprise competitiveness. The development and implementation of enterprise systems is a knowledge intensive procedure, being related to enterprise processes and involving information, system and software engineering technologies. Consequently, knowledge management is required to enhance the effectiveness of enterprise system development and implementation, thus helping to increase industrial competitiveness.This study aims to develop a distributed knowledge model for knowledge management, capable of supporting the collaborative development and implementation of enterprise systems. This objective can be obtained by performing the following tasks: (1) modeling and characterization of the collaborative development and implementation process, (2) identification, analysis and modeling of involved knowledge, and (3) development of a distributed knowledge model for knowledge management related to the collaborative development and implementation of enterprise systems.     

Understanding the effect of knowledge management strategies on knowledge management performance: A contingency perspective

The universalistic perspective research on employing a unidimensional knowledge management (KM) strategy has yielded conflicting findings and recommendations in different contexts. This study proposes a contingency model for investigating the effects of KM strategies on KM performance to resolve these contradictions. Drawing on the knowledge-based view (KBV) of the firm, which identifies knowledge type and origin as two key KM dimensions, this study first defines four KM strategies: external codification, internal codification, external personalization, and internal personalization. A multiple contingency model of KM strategy is then developed based on a technology–organization–environment framework. This study proposes that the effectiveness of each KM strategy depends on both external and internal contextual conditions, namely, environmental knowledge intensity and organizational information systems (IS) maturity. To test and validate the contingency model, we analyze data from 141 firms to explain the effects of KM strategies on KM performance. Our results reveal three KM strategies, not including the internal personalization strategy, which have a significant association with KM performance in their hypothesized contexts. This study expands KM strategy research by theoretically developing an advanced contingency model aligned with external and internal contexts and by providing valuable practical suggestions to managers for selecting a KM strategy based on multiple contingencies related to the external and internal conditions of a firm.     

A frame knowledge system for managing financial decision knowledge

Managing decision knowledge or expertise from domain experts is one of the most exciting challenges in today’s knowledge management field. The nature of decision knowledge in determining a firm’s financial health is context-dependent, intangible, and tacit in nature. Knowledge-based systems (KBS) have been recognized as a successful paradigm for managing financial decision knowledge attributed to possessing capabilities of reasoning and enhancing the consistency of decision-making. However, most present KBS adopt rules as the knowledge representation scheme, which cannot express the expert’s knowledge construct systematically when dealing with more numerous and disordered knowledge connotations. In addition, the standalone nature of the systems hinders them from deploying onto heterogeneous platforms and cannot accommodate to the emerging Web-enabled environment. To reduce these flaws, this study proposes a frame knowledge system in which the structural and procedural decision knowledge is encapsulated so that unnecessary interference can be avoided. A protocol analysis, before encapsulation, is conducted to elicit the tacit and unstructured knowledge from a senior CPA we cooperated with. The deployment and Web enabling issue is tackled by using Jess and Java interoperable computing. With these combined, it is possible to prompt the understandability, accessibility, and reusability of KBS. The effectiveness of the proposed system is validated in supporting the expert’s decision-making by conducting an empirical experimentation on 537 companies listed in the Taiwan Stock Exchange Corporation.     

Individualist and collectivist perspectives on knowledge in organizations: Implications for information systems research

Organization scholars differ in their understanding and application of the construct of “knowledge” in theorizing and empirical research. Over the past years, two perspectives have become prevalent in organization science. The individualist perspective assumes the locus of knowledge is people who learn, and that knowledge cannot extend beyond the physical limits of human beings. The collectivist perspective assumes the locus of knowledge is collective. Collective entities accumulate knowledge through forms of social learning. Boundaries of knowledge are drawn around social entities—groups, communities, networks, and organizational units, etc. Recent work in management and organization science has accentuated the differences, and argued against the widespread adoption of a collectivist perspective. This argument holds implications for information systems research. The current paper reviews selected contributions on the locus of knowledge, presents an argument for a combined collectivist and individualist perspective, and outlines future directions for information systems research. Drawing on two significant examples, I show that information systems research has a strategic role to play in greatly advancing this combined perspective.