Knowledge Management in Supply Chain Networks

This article reviews current research and practice of knowledge management (KM) and inter-organizational learning in supply chain networks. Knowledge management is the organizational process for acquiring, organizing, and communicating the knowledge of individual employees so that the work of the organization becomes more effective (Alavi & Leidner, 1999). Knowledge management is an increasingly important process in business organizations because “managing human intellect—and converting it into useful products and services—is fast becoming the critical executive skill of the age” (Quinn, Anderson & Finkelstein, 1998). Grover and Davenport (2001) state that KM becomes “an integral business function” when organizations “realize that competitiveness hinges on effective management of intellectual resources.” Grover and Davenport also argue that knowledge management works best when it is carried out by all the employees of the organization and not just KM specialists. Business organizations frequently partner with other firms to complement their core competencies. To collaborate effectively, partner firms have to communicate with each other information about business processes as well as share ideas of how to design or improve business processes. This phenomenon of knowledge sharing across organizational boundaries is called inter-organizational learning (Argote, 1999). Knowledge management, we posit, is necessary to facilitate inter-organizational learning and direct it in a way that supports the organization’s overall objectives. Supply chain systems are an example of business networks. Supply chains involve not only multiple corporate entities but also organizational units within a single organization. We present practices used in business organizations and networks of businesses to manage the information and knowledge sharing processes using the context of supply chain systems.

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

Under the globalized and fiercely competitive external environment, manufacturers have to enhance the organizational learning capability to cope with the challenge of Environmental Education. In addition to developing and cultivating the knowledge management capability, manufacturers have to co-develop, share, and spread relevant knowledge among different bodies in the external network. The theoretical relationship among manufacturers’ knowledge management in global manufacturing network, knowledge management in supply chain network, and organizational learning capability is proposed in this study, and the moderation effect of Environmental Education is further discussed. Based on 2013 International Manufacturing Strategy Survey VI (IMSS VI) of 463 manufacturers in 22 countries and regions. The empirical research results are concluded as below. (1) Manufacturers’ knowledge management in global manufacturing network and knowledge management in supply chain network present remarkably positive effects on the organizational learning capability. (2) Manufacturers’ knowledge management in supply chain network shows mediation effects on the relationship between knowledge management in global manufacturing network and organizational learning capability. (3) Environmental Education reveals notable moderation effects on the relationship between manufacturers’ knowledge management in supply chain network and organizational learning capability.

Purpose The purpose of this study is to advance the understanding of innovation offshoring by integrating knowledge management (KM) practices. It aims to identify how KM contributes to strategic offshoring, sourcing decisions for innovation and the utilization of knowledge-intensive business services. By doing so, it seeks to provide a framework that enhances both theoretical insights and practical applications in the field of innovation offshoring. Design/methodology/approach This study uses a tri-method approach – bibliometric analysis, co-citation analysis and text mining – to examine the intersection of innovation offshoring and KM. Data from Web of Science (WoS), analyzed using Leximancer and Bibexcel, reveal key KM practices, such as absorptive capacity and knowledge-sharing, that enhance offshoring-driven innovation. Integrating KM with global sourcing strategies is shown to manage complexities, lower transaction costs and boost innovation performance. Addressing the limitations of prior single-method studies, this research presents a structured KM-offshoring integration framework, mapping the thematic interconnections between KM practices and global sourcing strategies to enhance innovation performance and cross-border knowledge transfer. Findings This study finds that effective KM practices are crucial for optimizing innovation offshoring strategies. Key KM elements such as internal knowledge creation, absorptive capacity and knowledge-sharing routines significantly enhance innovation outcomes. The integration of KM practices with global sourcing strategies helps firms manage complexities, reduce transaction costs and improve innovation performance by leveraging global talent and resources. Research limitations/implications The study’s reliance on data from the WoS and the Association of Business Schools journal ranking may introduce selection bias, limiting the generalizability of findings. Future research should incorporate additional databases such as Scopus to validate the results. Moreover, the study predominantly uses bibliometric methods, which could benefit from being complemented by qualitative analyses to provide deeper insights into KM practices in innovation offshoring. Practical implications For practitioners, this study underscores the critical role of KM in optimizing innovation offshoring strategies. Effective KM practices enable firms to capture, share and use knowledge efficiently across global operations, mitigating the risks associated with geographical and cognitive distances in offshoring arrangements. Social implications The integration of KM in innovation offshoring has significant social implications. By effectively managing knowledge, firms can contribute to the development of global knowledge economies, promote cross-border collaborations and support the growth of local talent pools. This can lead to increased innovation, economic development and the creation of high-value jobs in emerging markets. Originality/value This study is original in its comprehensive approach to examining the intersection of innovation offshoring and KM. It provides valuable insights into how KM practices can enhance innovation performance in global sourcing contexts. The findings contribute to both academic literature and practical applications, offering a nuanced understanding of the strategic role of KM in innovation offshoring.

Background: State-owned enterprises (SOEs) in South Africa face a serious challenge of knowledge loss caused largely by resignations, the ageing workforce and a lack of knowledge management (KM) practices. Objective: This article explores KM practices in the South African SOEs to mitigate the risks inherent in tacit knowledge loss. Methods: The study adopted a mixed methods research strategy using an exploratory sequential design to identify KM practices and their effectiveness in addressing the issue of tacit knowledge loss. The qualitative data was collected through the interviews and document analysis of 2018 annual reports in nine SOEs across five market sectors. A survey questionnaire was distributed to 585 respondents, with a 25% response rate (145) for quantitative data in three SOEs. Results: The results revealed that the majority of the SOEs lacked KM practices in their structures. The lack of KM practices implies that the SOEs are lagging behind in knowledge protective capacities to mitigate the risks inherent in the organisational tacit knowledge loss. With many South African SOEs, facing all these sorts of knowledge loss risks and a lack of KM practices to mitigate them, achieving the objectives of a developmental state remains a far-fetched idea. Conclusion: The absence of KM practices negatively affected knowledge transfer and retention in most of the SOEs. A lack of KM practices will negatively affect their performance and their sustainability to deliver on their developmental mandate. Investment in KM practices will assist SOEs to mitigate the risks associated with loss of organisational tacit knowledge.

Researchers and practitioners have emphasised the need for advances in knowledge management (KM) research to better understand how organisations add value from their KM practices. Thus, a comprehensive framework, rooted in two main theoretical streams of KM practices, objectivist and practice-based perspective, is proposed. We believe this explains how KM practices add value, and will assist organisations to obtain a more accurate picture of their KM practices, the factors that influence KM implementation, and how KM can be measured. The framework also serves as a means to identify how well KM practices meet organisational strategies. This paper begins with a review of different KM perspectives and then reports the findings of qualitative in-depth interviews with UK car manufacturers. The results indicate that most organisations adopt different types of KM practices, with the findings revealing that top management commitment, strategy, IT, people involvement and organisational culture were the factors that most influenced KM implementation. In conclusion, the paper advocates an integrated view of KM perspectives and mechanisms for KM practice in UK car manufacturing.

PurposeThis study aims to identify the key contributing factors of knowledge management (KM) practices with respect to an employee benefit. The research is designed to gain insight into the KM practices of Indian information technology (IT) firms and evaluate its effects on employee perceived benefit (EPB) and employee satisfaction (ES).Design/methodology/approachThis study focuses on the cause and effect relationship between the variables. In this research study, a structured questionnaire is administered and accumulated responses from executives, software developers and knowledge managers from five IT firms with the help of google form. The sample size was 339 for this study. Confirmatory factor analysis and partial least square (PLS)-structural equation modeling have been used to analyze the data with the help of SMART-PLS software.FindingsThe well-fitted model describes the importance of KM practices with respect to increasing employee benefit and satisfaction. The hypothesized model is empirically investigated and it is also supported by the analysis. The KM practices have significant effects on EPBs. Employee benefits have a significant effect on ES. The result shows that the benefits of KM practices are more intended toward the sources of motivation where they can increase their capability with the help of KM practices.Research limitations/implicationsBenefit leads to the motivation and satisfaction of employees. The work itself can be a highly motivating dimension with the help of proper KM practices. The managers’ prime responsibility is to focus on collaborative work with regularizing the exchange of knowledge, where new knowledge can be created and, do better for the organization.Originality/valueThis research study offers a new direction of motivation to work. The employee can be highly motivated if he can be benefited from the work itself. This study gives an approach to satisfy the employee with the help of KM practices. Perceived benefit is considered as an essential element for this study.

In the present dynamic and knowledge-driven business environment, Knowledge Management (KM) has emerged as a critical factor for enhancing organizational performance, fostering innovation, and ensuring long-term sustainability. Organizations increasingly rely on effective KM practices to systematically create, store, share, and apply knowledge, thereby improving decision-making processes, strengthening collaboration, and achieving strategic objectives. KM serves as a catalyst for managing intellectual assets and transforming them into valuable organizational outcomes, contributing significantly to competitiveness and growth . Despite its growing importance, the implementation of effective KM practices remains a significant challenge across organizations. Various barriers such as cultural resistance, technological limitations, lack of resources, and inadequate organizational support hinder the successful adoption of KM systems. Cultural dimensions, including organizational hierarchy, power distance, and communication patterns, play a crucial role in influencing knowledge-sharing behavior and the overall effectiveness of KM practices. In many cases, rigid organizational structures and resistance to change restrict open communication and limit the free flow of knowledge within organizations . Furthermore, the increasing emphasis on sustainability and digital transformation has highlighted the need for robust and adaptive KM frameworks. Emerging concepts such as Green Knowledge Management (GKM) emphasize the role of KM in achieving environmental, social, and economic sustainability. Organizations are increasingly integrating KM practices with sustainability goals to promote resource efficiency, environmental responsibility, and long-term development. At the same time, advancements in digital technologies, including artificial intelligence (AI), data analytics, and information systems, are transforming traditional KM processes by enhancing knowledge creation, storage, and dissemination capabilities . Although significant progress has been made in KM research, several gaps still exist in understanding its application across diverse organizational and industrial contexts. Existing KM frameworks often fail to adequately address cultural and contextual differences, which are critical for successful implementation. Moreover, while KM has been extensively studied in large organizations, its application in small and medium-sized enterprises (SMEs) remains relatively underexplored. SMEs face unique challenges such as limited resources, lack of structured KM systems, and informal management practices, which affect the effectiveness of KM initiatives . In addition, there is a need for more empirical and longitudinal studies to evaluate the long-term impact of KM practices on organizational performance, innovation, and sustainability. Many existing studies are conceptual in nature and lack practical validation across different industries and cultural settings. The integration of KM with emerging technologies and its role in supporting innovation and decision-making processes also require further exploration . This study adopts a literature review-based approach to examine the current landscape of Knowledge Management research, with a focus on its interrelationship with culture, innovation, and sustainability. By synthesizing findings from various studies, the research aims to provide a comprehensive understanding of KM practices, identify key challenges and research gaps, and suggest directions for future research. The study contributes to the existing body of knowledge by highlighting the importance of context-specific KM frameworks and the need for integrating technological, cultural, and sustainability dimensions in KM practices.

In Malaysia, there has been an argument that the Knowledge Management (KM) practice especially in construction industry has not been commensurable with its status as a developing country. Hence, an initiative that aims to appraise the KM practice amongst consultant firms working in industry of construction in Malaysia becomes the focal point of this study. This aim is achieved by fulfilling its objectives of delving into the understanding of consultant firms on KM practices and exploring the critical success factors (CSFs) of KM implementation in Malaysia. In this paper, the data is studied on a number of statistical analysis tools, namely descriptive analysis, reliability analysis and relative important index (RII). The results obtained from the questionnaire survey clearly showed that most respondents made a claim that KM enhances the decision making in the organization and KM spurs innovations. Few respondents disagreed with the components of KM practices, indicating that these respondents may not be well aware of the importance of KM. About the top ranking of CSFs for KM practices implementation, it is found that “continuous organization support”, “leadership demonstration by senior staff/management”, “knowledge and sharing cul-ture”, “execution of plan”, and “continuous learning” make the top five factors very vital to the effective execution of KM by the consultant firms in the construction industry.

PurposeThe food industry is crucial in delivering healthy products for life saving of the society. The identification of key barriers of knowledge management (KM) is desired to enhance the sustainability of the industry. KM has been seen as a part of sustainable development by reducing the bullwhip effect in the entire supply chain. The core objective of the existing research is to prioritize the essential factors of KM adoption in sustainable supply chain (SSC) based on fuzzy analytical hierarchy process (FAHP) method.Design/methodology/approachIn order to fulfill objectives of this study, an extensive review of literature and a questionnaire-based field visits were conducted. A total of five major barriers categories and 22 sub-barriers categories were identified in food sector of Pakistan using experts' inputs. This study employed fuzzy analytical hierarchy process (FAHP).FindingsManagerial barriers, innovation and technological barriers categories are found to be highly prioritized among others. Further, the sensitivity analysis is applied to check the incremental changes of ranked barriers. This prioritization of barriers and incremental changes in them is expected to serve food sector for long-term sustainability and competitive advantage for importers and exporters. Finally, the findings of this research are very helpful for industrial experts, practitioners, consultants and government officials in effectively developing policies regarding KM adoption in line with sustainable goals.Research limitations/implicationsThe present work is conducted in the Pakistani context; however, the benchmark model may be tested and applied to other developing countries to compare the outcomes. For further research, the identified barriers may also be evaluated to establish their inter-relationships, using ISM, DEMATEL, ANP, etc. Similarly, the results of this study can also be compared with that of other fuzzy multi-criteria techniques like fuzzy TOPSIS, fuzzy VIKOR, fuzzy ELECTRE, fuzzy PROMETHEE, or fuzzy VIKOR.Practical implicationsThis research study can facilitate policymakers, government bodies, stakeholders and supply chain professionals to recognize the key barriers they may encounter in adopting KM practices in their SSC. Additionally, this work helps managers to evaluate the identified barriers by computing their relative importance in adopting KM practices at managerial levels like strategically, tactically and operationally activities in business. This study also facilitates industrial management in formulating policies and action plans in case of implementation, eliminating the barriers in adoption of KM, and SSC successfully.Originality/valueFew research studies were conducted on KM adoption in industries of China, India, Turkey, Saudi Arabia and Malaysia, but due to workforce diversity these industries have dissimilar views of experts about KM adoption. This study significantly contributed to fill the existing literature gap for prioritization of key barriers against KM implementation in Pakistani context.

PurposeThe purpose of this paper is to report the results of an exploratory investigation of the organizational impact of knowledge management (KM).Design/methodology/approachA search of the literature revealed 12 KM practices whose performance impact was assessed via a survey of business organizations.FindingsKM practices were found to be directly related to organizational performance which, in turn, was directly related to financial performance. There was no direct relationship found between KM practices and financial performance. A different set of KM practices was associated with each value discipline (i.e. customer intimacy, product development and operational excellence). A gap exists between the KM practices that firms believe to be important and those that were directly related to organizational performance.Research limitations/implicationsThe majority of the research constructs were formative, thus improving the measurement of KM practices will prove vital for validating and extending these findings. The findings were based solely on organizations from North America and Australia and may not reflect KM practices in other geographic, economic or cultural settings.Practical implicationsThis study encourages practitioners to focus their KM initiatives on specific intermediate performance outcomes.Originality/valueThe paper examines the relationship between KM practices and performance outcomes. It was expected that a direct relationship between KM practices and organizational performance would be observed. It was also expected that organizational performance would mediate the relationship between KM practices and financial performance. These expectations were supported. KM practices showed a direct relationship with intermediate measures of organizational performance, and organizational performance showed a significant and direct relationship to financial performance. There was no significant relationship found between KM practices and financial performance.

This paper aims at highlighting technological dimensions for knowledge management (KM) practices in firms with the review of the potential conception of activities adopted by organizations to utilize the knowledge resources. The study systematically reviews the literatures available on KM practices with excluding articles based on keywords, abstracts, and full text. KM practices were incorporated in Heisig’s (J Knowl Manage 13(4):4–31, 2009 [1]) categorization format of human, technology, organization, and management process-oriented practices. The findings described that learning and sharing attitude in human are effectively directing adoption of technological tools for KM in firms. Top management support and strategy are also key KM practices supporting technology usage. In terms of originality and value, the paper reviews all the latest technologies and their integration for supporting KM in firms. The study promotes for faster and accurate business ideas with the accumulation of advanced technological tools for knowledge storing, sharing, and application. The famous Nonaka and Takeuchi (The knowledge-creating company—how Japanese companies create the dynamics of innovation. Oxford University Press, New York/Oxford, 1995 [2]) KM Model is adopted to integrate the technology and KM practices.KeywordsKnowledge managementKnowledge management practicesManagement processInformation and communication technology

This chapter aims to evaluate the application of knowledge management (KM) literature in supply chains. The underlying understanding derived from this evaluation can be used to devise a valid business strategy to encourage knowledge management practices in supply chains. The concept of a supply chain encompasses businesses organised around a common goal of delivering a product or service from the initial supplier to the end customers. In this respect, the importance of knowledge management within the boundaries of supply chain management has been iterated by many authors; some underline the strategic and tactical importance of knowledge management, whereas others focus on the advantages and tools used to create knowledge in supply chains. The difficulty of assessing knowledge management is twofold when considering supply chains–first, the underlying difficulty of locating the trail of knowledge creation in supply chains and secondly how this can be utilised to devise a business strategy. On close examination of the literature in this field, we can identify a salient need for the theoretical categorisation of existing theoretical frameworks of supply chain management (SCM) on KM-related practices. This chapter explicitly looks into three supply chains, namely learning chains, virtual chains and build-to-order supply chains, and the specific challenges that these create for knowledge management and devising a valid business strategy.

Knowledge management (KM) plays important roles in cybersecurity. This study collects five real-life cases of good practices of KM for the domain of cybersecurity in business organizations. Through an iterative process of team-based qualitative data analysis of the five cases, the study develops a model of KM for cybersecurity that conceptualizes three common aspects of KM practices for cybersecurity in business organizations. First, KM for cybersecurity in business organizations has clear specialized organizational structures that involve three inter-organizational tiers across the organization boundaries. Second, the knowledge flows of KM for cybersecurity in business organizations emphasize on explicit, declarative, and specific knowledge. Third, in comparison with KM for other domains, KM for cybersecurity has well-defined objective measures to assess the effectiveness of KM. The domain-specific KM model based on the good practice cases provides a road-map for KM practices in the domain of cybersecurity in business organizations.

<p>This research seeks to explore the characteristics, organisational culture and current knowledge management (KM) practice in a community enterprise (CE). Prae Pun - a hand weaving CE in the northeast rural area of Thailand - has typical CE characteristics - self-employed and collaborative management, and a home-based production system utilising local resources and knowledge. This research used a qualitative method. Data were collected through narrative inquiry, participant observation and document analysis. The 18 respondents were Prae Pun members, committee members, an advisory committee member and office staff members. The data were analysed through theme analysis. The findings of this research reveal that, although community members would not be aware of doing so, Prae Pun managed its knowledge through informal educational activities - learning by doing and observation - and work processes concerned with collaboration and informality. The current KM practice of Prae Pun entails three processes: basic skill development, competence building and new knowledge creation through creation, capture, sharing, transferring, verification, utilisation and codification. Significantly for this study, KM of Prae Pun focuses on organisational knowledge creation and indigenous knowledge systems. The current KM of Prae Pun also has four other components. Its knowledge resources come from members, other villagers, other hand weaving groups, support organisations and markets. Most of the knowledge is tacit and indigenous. The operation and management systems determine the knowledge processes and provide supportive and incentive systems. The organisational culture and resources, including funding, social capital and appropriate technologies, also provide supportive and incentive systems. The resources are also the tools that facilitate the knowledge processes. The knowledge assets encompass actual assets - products, cloth designs, techniques, and operation and management systems - and competencies including members' skills and abilities, social capital, and shared values, which are not registered as intellectual properties but are in the forms of organisational memories. The traditional KM practice of Prae Pun can be possibly strengthened by integrating modern KM concepts, including knowledge resources from academic and government agencies, appropriate technologies to facilitate knowledge codification and knowledge transfer, extrinsic reward and incentive systems, and facilitators or consultants to enhance members' communities of practice (CoPs). The findings of this study and the KM model contribute to both CE development and further research on KM in a CE context and indigenous KM.</p>