Enterprise Knowledge Structures

Retraction statement We, the Editors and Publisher of the journal Knowledge Management Research & Practice (the “Journal”), have retracted the following articles that were published in the Special Issue titled “ The Impact of Artificial Intelligence on Knowledge Management and Business Strategic Planning ” guest-edited by Gunasekaran Manogaran: Fu, C., Jiang, H., & Chen, X. (2022). Modeling of an Enterprise Knowledge Management System Based on Artificial Intelligence. Knowledge Management Research & Practice, 1–13. https://doi.org/10.1080/14778238.2020.1854632 Wu, H., Gu, X., Zhao, Y., & Liu, W. (2020). Research on the Relationship between Structural Hole Location, Knowledge Management and Cooperative Innovation Performance in Artificial Intelligence. Knowledge Management Research & Practice, 1–10. https://doi.org/10.1080/14778238.2020.1813642 Wang, M. (2020). Financing support strategy of green manufacturer for financially constrained retailer. Knowledge Management Research & Practice, 1–15. https://doi.org/10.1080/14778238.2020.1771224 Elashkar, E., Aldeek, F., & Shoukry, A. (2020). Business predictive analysis from business insurance data using business strategic planning techniques. Knowledge Management Research & Practice, 1–10. https://doi.org/10.1080/14778238.2020.1776172 Huang, Z., He, J., & Ren, X. (2021). Application of artificial intelligence in enterprise knowledge management performance evaluation. Knowledge Management Research & Practice, 1–9. https://doi.org/10.1080/14778238.2020.1850187 Lei, Z., & Wang, L. (2020). Construction of organisational system of enterprise knowledge management networking module based on artificial intelligence. Knowledge Management Research & Practice, 1–13. https://doi.org/10.1080/14778238.2020.1831892 Li, Z., & Mo, T. (2020). Early warning of engineering project knowledge management risk based on artificial intelligence. Knowledge Management Research & Practice, 1–11. https://doi.org/10.1080/14778238.2020.1834885 Yang, J., Wen, C., & Gan, L. (2021). Model of an Enterprise Knowledge Chain Management System Based on Multiagent Technology in Distributed Artificial Intelligence. Knowledge Management Research & Practice, 1–12. https://doi.org/10.1080/14778238.2020.1850188 Bai, X., & Li, J. (2020). The best configuration of collaborative knowledge innovation management from the perspective of artificial intelligence. Knowledge Management Research & Practice, 1–13. https://doi.org/10.1080/14778238.2020.1834886 Following publication, the Publisher identified concerns regarding the editorial handling of the Special Issue and the peer review process. An investigation by the Taylor & Francis Publishing Ethics & Integrity team in full cooperation with the Editors-in-Chief concluded that the articles included in this Special Issue were not peer-reviewed appropriately, in line with the Journal’s peer review standards and policy. As the stringency of the peer review process is core to the integrity of the publication process, the Editors-in-Chief and Publisher have decided to retract all of the articles within the above-named Special Issue. The Editors-in-Chief and the Publisher have not confirmed if the authors were aware of this compromised peer review process. The Journal is committed to correcting the scientific record and will fully cooperate with any institutional investigations into this matter. The authors have been informed of this decision. We have been informed in our decision-making by our editorial policies and the COPE guidelines. The retracted articles will remain online to maintain the scholarly record, but they will be digitally watermarked on each page as ‘Retracted’. © 2019 Informa UK Limited, trading as Taylor & Francis Group/Journal owner

This paper presents a Knowledge Management Capability framework based upon an empirical case study conducted at a CMM Level 5 software project organisation. The paper discusses the development of the organisation’s knowledge management (KM) initiative from its initial state, to an organisational state where the KM practices are institutionalised and embedded within the daily activities and work methods of the organisation. The organisation’s KM initiative is analysed through the development of two KM capabilities, namely infrastructure and processes, which were examined in depth while conducting the case study, and form the basis for the KM Capability Framework. The resulting framework helps organisations to analyse any imbalance that may exist in their KM initiative and needs to be addressed. In doing so, the framework benefits organisations in making corrections and restoring balance between their KM infrastructure and process capabilities, thereby improving the path of successful KM implementation towards a state of organisational KM capability.

This paper considers the current problems of knowledge and information systems management, which are solved with the help of digital institutes for the purpose of the development of high-tech production in the conditions of Industry 4.0. The paper identifies the role of knowledge in the innovative development of industrial production, characterises the specifics of the influence of digital technologies on the technological development of companies and production processes, and focuses on the sensitivity of high-tech production to the level of intellectual support of production processes. Emphasis is made on the necessity of using comprehensive digital institutes, which can expand the boundaries of production companies and use the potential of digital platforms and systems in full. The research methodology combines traditional and new scientific directions and institutional theories in disciplines that study the research problem in the context of an increase in the intellectualisation of labour in the conditions of Industry 4.0. The research methodology covers general scientific methods of synthesis, analysis, the monographic method, observation, generalisation, and comparison. The paper contains important thoughts regarding the features of digital institutes from the position of their formation and influence on knowledge management in high-tech companies. It considers the structure and functions of the digital institutes of knowledge and information systems management in the conditions of Industry 4.0 and characterises selected institutes in the context of their influence on the digital transformation of the economy and the improvement of the state of knowledge management.

PurposeThe purpose of this paper is to distinguish and describe knowledge management (KM) technologies according to their support for strategy.Design/methodology/approachThis study employed an ontology development method to describe the relations between technology, KM and strategy, and to categorize available KM technologies according to those relations. Ontologies are formal specifications of concepts in a domain and their inter‐relationships, and can be used to facilitate common understanding and knowledge sharing. The study focused particularly on two sub‐domains of the KM field: KM strategies and KM technologies.Findings”KM strategy” has three meanings in the literature: approach to KM, knowledge strategy, and KM implementation strategy. Also, KM technologies support strategy via KM initiatives based on particular knowledge strategies and approaches to KM. The study distinguishes three types of KM technologies: component technologies, KM applications, and business applications. They all can be described in terms of ”creation” and ”transfer” knowledge strategies, and ”personalization” and ”codification” approaches to KM.Research limitations/implicationsThe resulting framework suggests that KM technologies can be analyzed better in the context of KM initiatives, instead of the usual approach associating them with knowledge processes. KM initiatives provide the background and contextual elements necessary to explain technology adoption and use.Practical implicationsThe framework indicates three alternative modes for organizational adoption of KM technologies: custom development of KM systems from available component technologies; purchase of KM‐specific applications; or purchase of business‐driven applications that embed KM functionality. It also lists adequate technologies and provides criteria for selection in any of the cases.Originality/valueAmong the many studies analyzing the role of technology in KM, an association with strategy has been missing. This paper contributes to filling this gap, integrating diverse contributions via a clearer definition of concepts and a visual representation of their relationships. This use of ontologies as a method, instead of an artifact, is also uncommon in the literature.

DESIGNING A CONCEPTUAL PERFORMANCE MEASUREMENT FRAMEWORK OF KNOWLEDGE MANAGEMENT INITIATIVES

The implementation of knowledge management in our country's IT enterprise is at the preliminary stage basically. Data mining is a very crucial part of knowledge management which is an effective knowledge management process of using data and which can quickly-efficiently explore effective information and knowledge on management and decision-making and improve the efficiency of enterprise's knowledge management. Using data mining technology in Small-and-medium-sized IT enterprises is very necessary.

Public organizations are increasingly investing in knowledge management (KM) initiatives. However, most KM concepts, practices, and tools have mainly been developed and studied in the private sector and there is a lack of understanding of KM in public organizations. This paper addresses the gap by discussing the differences between public and private organizations in their KM endeavors. Specifically, KM drivers in the context of public organizations are first identified. Salient KM enablers and how they may differentially affect the success of KM initiatives in public and private organizations are then discussed. Finally, tools for assessing KM performance in public organizations are suggested, in view of their unique organizational objectives.

The concept of Knowledge Management concerns the creation of structures that combine the most advanced elements of technological resources and the indispensable input of human response and decision making. This chapter addresses a very interesting topic—Knowledge Management (KM) and e-business initiatives within global organizations. It compares and contrasts the experiences of two global corporations as they have conceived and implemented KM initiatives. After in-depth secondary research on the subject, both companies developed their own KM in e-business strategy. The two case studies discussed in this chapter highlight Business-to-Business (B2B), Business-to-Consumer (B2C), and Business-to-Employee (B2E) initiatives at these two global organizations. This provides concepts and viewpoints related to the drivers of KM, the hurdles to KM in an organization, the elements of KM philosophy and process, how KM can come to be understood as a critical part of a company’s competitive strategy, and how to deploy a sustainable KM system that suits the business needs of an organization.

This paper seeks to contribute to the on-going research in knowledge management (KM) by presenting a study conducted in six public service agencies in Singapore. The study was guided by three research foci, namely, (1) to elucidate the nebulous nature of KM initiatives, (2) to uncover the motivation behind KM measurement and (3) to identify the various elements of a KM initiative that can be measured. Data collected from the public service agencies revealed that KM initiatives were generally top-down and technology-focused. Project management and the need to quantify the value of KM initiatives drove KM measurement. The measurement indicators adopted by the agencies encompassed four elements of measurement: activities, knowledge assets, organizational processes and business outcomes. In conclusion, this paper highlights two practical implications for the design of a KM measurement regime and suggests a number of possible directions for further research.

The ability to manage efficiently the flow of knowledge has becoming a crucial requirement to boost the organizational learning and competitiveness along the knowledge era. However, a lack of consensus and confusion may still exist regarding what comprise the Knowledge Management (KM) and its importance to improve the overall organizational performance in Egypt. Moreover, there is generally a lack of an observable organizational KM initiatives’ progress in Egypt. This study highlights the significance of KM and explores the key drivers that can support organizational KM initiative in Egypt which requires organizational management and human orientation in terms of setting supportive human resource management, organizational culture and organizational structure. The study also alarms the attention to the various challenges that may hinder the successful implementation of KM initiative in Egypt. Based on the case study approach, this study sheds the light on a good model of IBM Egypt as a guidance supporting the crucial significance of KM for booming innovation and organizational performance.

The article examines the features of renewable energy development at the macro and micro levels in Ukraine. The role of knowledge and innovation management in the field of renewable energy has been defined. The subject of the research is the processes of knowledge and innovation management at renewable energy enterprises. The purpose of the article is to identify key factors in the development of renewable energy and approaches to knowledge and innovation management at renewable energy enterprises. General scientific methods have been used, the main of which are: system analysis – application of a comprehensive two-level approach to the analysis of the role of knowledge in the field of renewable energy and correlation and regression analysis. The following results have been obtained: based on the conducted analysis, the expediency of forming an innovation infrastructure for developing such a high-tech sector as renewable energy has been justified. The application of methods and tools of knowledge and innovation management at renewable energy enterprises has been substantiated. Recommendations concerning the formation and development of a knowledge and innovation management system at renewable energy enterprises in Ukraine have been made, as this system will increase the competitiveness of renewable energy in relation to traditional one. Conclusions: the role and features of knowledge and innovation management in renewable energy enterprises are shown. Prospects for the development of renewable energy in Ukraine on the basis of knowledge and innovation management are identified.KeywordsKnowledge managementRenewable energyInnovations

This paper aims to identify and articulate critical research issues in the emerging area of real‐time knowledge management (RT‐KM) in enterprises, in order to stimulate other researchers to further pursue them. The paper creates a framework around which it identifies and examines research issues and challenges that become salient and critical when knowledge sharing and creation need to happen in near real‐time. The framework is based on two drivers: increasing the requirements to plan for quickening the action‐learning loop in the enterprise, and increasing requirements in planning for emergence. The action‐learning loop is further articulated through the “observe, orient, decide, and act” (OODA) framework that is suited to sense‐and‐respond environments. Through the framework six sets of critical research challenges are identified around RT‐KM in enterprises: challenges around managing the quality of information in RT‐KM, challenges around improving the selective and intensive aspects of managerial attention in RT‐KM, challenges around making core business processes better suited to RT‐KM, challenges around integrating multiple distributed perspectives unpredictably in RT‐KM, challenges around developing heuristics in a way that allow real‐time emergence, and challenges around effectively capturing actions and learning for later reuse in RT‐KM. The issues and challenges identified are suggestive rather than exhaustive. Based on observations from real field case studies in industry, and driven by an industry need for better RT‐KM. This paper brings together the concepts of vigilant information systems, OODA loops, and emergence and applies them through a framework to identify research issues and challenges in this new emerging area of RT‐KM.

The purpose of paper is to explore the role of the learning organization as a mediating variable between knowledge management and service quality in these organizations, also the paper aims to review the concept of learning organization, and the different elements of knowledge management and service quality in service business organizations. In order to achieve the purposes of the study, researcher adopted a descriptive analytical method, valid research instrument was utilized to conduct a survey of (450) questionnaires which were distributed, and (398) questionnaires were retrieved for analysis, rating (88%) of the distributed questionnaires. Analyzing data was conducted using a set of statistical methods including a normality test along with Cronbach’s alpha, standard deviation, confirmatory factor analysis, exploratory factor analysis, multiple and simple linear regression using SPSS-V25 and AMOS-V25. The study reached a set of results, the most important of which are: 1) There is a statistically impact at significant level (α ≤ 0.05) of knowledge management on service quality through the learning organization as a mediating variable in Alexandria Water Company in Egypt. 2) There is a significant correlation between learning organization and knowledge management, also there is a significant correlation between knowledge management and service quality, and finally there is a significant correlation between learning organization and service quality. The study reached a set of recommendations, the most important of which are: 1) It is necessary to plan, organize, lead and monitor enterprise knowledge and process management with emphasis on efficiency and effectiveness of the right of access to it; 2) Managers and owners should pay attention to the learning organization, as it plays a major role in building and forming organization culture and knowledge structure of organizations.

With knowledge as the power source, enterprise’s innovation and transformation has its achievements directly linked to the ability and level of enterprise's knowledge management. In view of this, it is meaningful to evaluate the management capability and level. Targeted at problems existing in the current evaluation process, we studied the corresponding evaluation system and model. Firstly, a discussion was conducted on the connotation of enterprise knowledge management and the positive role of assessment on its ability and level. Then, we analyzed the management problems as well as their impact on our evaluation process. Afterwards, we referred to the evaluation index selection principle, and accordingly established the evaluation system of enterprise knowledge management ability and level. Finally, by combining grey relational analysis with fuzzy evaluation analysis, we built up a fuzzy grey relational comprehensive evaluation model on the basis of an initial decision-making analysis matrix, a normalized decision-making matrix and the weighted triangular fuzzy number distance. The algorithm implementation steps were also listed in the latter part.

PurposeThis paper focuses on the meanings attributed to the measurement of return on investment (ROI) in knowledge management (KM) initiatives in knowledge-intensive organizations. At the heart of this exploratory research is the introduction of a unique coherent perspective of discipline experts regarding the ROI metric, as part of their perception of assessing effectiveness in this field.Design/methodology/approachThe research begins with in-depth semi-structured personal interviews and continues with focus groups, as part of a qualitative research paradigm. The data were analyzed using a thematic analysis method, based on the grounded theory approach.FindingsThe findings provide empirical evidence regarding the significant challenges associated with the objective assessment of KM performance, which is deeply rooted in numerical-financial values. Despite the high status of ROI in the business environment, the authors find that decision-makers surprisingly avoid evaluating ROI for the most important resource of the organization, notwithstanding the immeasurable hopes that depend on this performance measure and the expectation of establishing the profitability of investment in organizational KM.Originality/valueThe uniqueness of this research is the adoption of the skeptical-critical research approach. For the first time, the authors interrogate the suitability and relevance of the general model of the ROI metric as a means of proving the value and contribution of well-managed knowledge to organizations. The authors call for adoption of a new integrative perspective for evaluating effectiveness, which will reflect the holistic set of KM in organizations.