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The field of supply chain management (SCM) evolves dramatically due to factors of globalization, innovation, sustainability, and technology. These changes raise challenges not only to higher education institutions, but also to students, employing organizations, and third parties like SCM-related professional bodies. To understand the challenge, the purpose of this paper is to examine the gap between demand and supply of SCM-related knowledge areas, answer-related design questions, and make recommendations to close the gaps.

To compare the demand and supply of SCM-related knowledge areas, demand data is collected from a professional career website and supply data is gathered from operations management (OM) and SCM course syllabi from AACSB-accredited business schools in the USA. Cluster analysis identifies how supply and demand are matched on the data collected.

First, gaps exist between SCM talent requirements from industry and the knowledge/skill training by US business schools. This paper identifies matching, under-supplying, and over-supplying knowledge areas. Under-supply in emerging areas such as SCM information technology and certain logistics management topics are found. Some traditional OM topics are over-supplied due to out-of-date industry applications and should be revised to reflect the field’s transition from an OM to SCM view. Last, this paper makes recommendations to different stakeholders in this matching supply with demand process.

This study contributes to the literature in two ways. First, it provides an up-to-date understanding on demand and supply of SCM talent in USA. Second, it provides insights and recommendations not only to educators on curriculum design, but also to potential candidates interested in SCM careers, to companies’ job recruiters, and to professional organizations (such as APICS and Council of Supply Chain Management Professionals) to reduce the gaps between demand and supply.

The literature on knowledge management in sustainable supply chain (KMSSC) has witnessed significant growth in the past two decades. However, a scientometric review that consolidates the primary trends and clusters within this topic has been notably absent. This paper aims to scrutinize recent advancements and identify the intellectual underpinnings of KMSSC research conducted between 2002 and 2022.

The present review employs a scientometric analysis approach via visualization maps of prolific contributions, co-citation, co-occurrence and thematic networks to examine a total of 114 articles and conference papers on KMSSC.

Emerging research frontiers and hotspots are revealed and a state-of-the-art framework of KMSSC research structure is developed.

The review provides significant implications that guide KMSSC research and better inform sustainability decisions in the supply chain context.

To the best of the authors' knowledge, this is the first review to thoroughly synthesize the intersected domain of KMSSC using scientometric analysis.

The purpose of this paper is to propose performance measures for supply chain knowledge management (SCKM) performance.

This is a conceptual study. State of performance measurement has been analyzed on the basis of a comprehensive review of literature in field of SCKM. Based on principles of double and triple loop learning, performance measures have been identified for measuring the success of KM practices in SCs.

Principles of double and triple loop learning have been utilized to suggest KPI’s for SCKM performance, i.e. supply chain identity and knowledge supply chain stratum. The relevance and justification of these KPI’s is also discussed.

This study is limited to conceptualized measures for SCKM only. Further research is required to test the benefits of these performance measures based on industry applications.

These proposed KPI’s will facilitate the development of the new processes through re-engineering, i.e. problem identification and then rectification. Further, these KPI’s will provide some essential insights as to how supply chains can develop their performance evaluation systems to become more effective and learning oriented.

This study aims to not only identify the gaps present in the SCKM performance measurement literature but also aims to fill the knowledge gap by suggesting suitable performance metrics.

Understanding the factors that advance green innovation is crucial for firms to deal with the complexity of green innovation. In light of this, this study aims to explore the influence of supply chain knowledge, non-supply chain learning and corporate reputation on green innovation.

This study uses a quantitative research approach where data is gathered from managers of 208 small and medium enterprises in Ghana using survey questionnaires. The structural equation modeling is used to analyze the survey data.

The findings reveal supply chain knowledge relates positively with non-supply chain learning, corporate reputation and green innovation. Corporate reputation also impacts green innovation positively and provides partial mediation effect between supply chain knowledge and green innovation. Meanwhile, non-supply chain learning does not relate positively with green innovation as well as fails to mediate the impact of supply chain knowledge on green innovation.

This study contributes to knowledge in the mediating mechanisms of corporate reputation and non-supply chain learning between supply chain knowledge and green innovation. Through this, the authors propose a theoretical model to explain how firms can leverage supply chain knowledge, corporate reputation and non-supply chain learning to improve green innovation and can serve as the basis for further theoretical and empirical research in innovation and external sources of knowledge.

The purpose of this paper is to examine the effect of knowledge management capabilities (KMCs) on organizational learning (OL) and supply chain management practices (SCMPs). In addition, to study the effect of OL, KMC and supply chain management on organizational performance (OP).

To study the relationships between KMC, OL, SCMP and OP, different techniques such as factor analysis, correlation analysis and structural equation modeling were used to verify the validity of the proposed conceptual model, and to test the suggested hypotheses, data collected from 165 companies in the Saudi food industry (representing a response rate of 64.9 per cent) were used.

According to the study’s findings, SCMP and OL are positively affected by KMC. Moreover, OP is directly affected by KMC, OL and SCMP.

Owing to the specific nature of the sample, the findings of the current research are applicable only to the food industry.

The current research introduced a conceptual model, which has been tested and verified in the Saudi food industry. The findings recommend that both KMC and OL as well as SCMP will contribute to improving the OP. In addition, KMC will improve the SCMP and OL.

Taking a social network perspective, the purpose of this paper is to develop a framework for the assurance of food safety via relational networking.

The authors consider both informal and formal relational networking, and explore a firm’s learning orientation, risk aversion and consumer pressure as potential precursors to such relational networking. It is further hypothesized that relational networking generates both industry and supply chain knowledge, which is suggested to be beneficial for contamination detection. The model is tested with survey data collected among food-producing firms in India, the world’s second largest food producer.

The authors find a positive influence of consumer pressure on both a firm’s learning orientation and risk aversion, which in turn affect both informal and formal relational networking. Informal networking further generated industry knowledge and was beneficial for contamination detection. Formal relational networking influenced supply chain knowledge, which in turn enabled contamination detection.

Recent food product-related safety breaches, which have, in the worst case, led to fatalities, illustrate the importance of food safety in supply chains. This study represents the first systematic investigation of relational networking in the context of food safety from the perspective of social network theory.

A successful supply chain should ensure that all participating members benefit from the marketplace. To achieve this goal, the supply chain members need to improve their competences all the time, which requires a continuous learning process. Thus, mutual learning, through knowledge sharing between the different members, is a necessary approach to increase the competence of supply chain partners. To realise efficient and effective knowledge sharing in a supply chain, this paper aims to explore and formulate a model that supports an enterprise with its management of the supply chain members' knowledge resource sharing (herein referred to as “advanced practice” and includes two levels of knowledge – strategic and operational). The model is based on the theories of supply chain management (SCM) and case‐based reasoning (CBR).

This research follows a conductive and inductive cycle. Firstly, based on the learning expounded through an extensive literature survey regarding SCM and CBR, as well as available empirical applications, the conceptual model is designed. Then the primary stage evaluation will be discussed regarding the feasibility and refinement of the model towards its maturity.

To share knowledge along the supply chain is theoretically sound, but a difficult task to realise in practice, due to the complexity of knowledge sharing between the different organizations.

This research explores one of the important topics in SCM – knowledge sharing within a supply chain, and the model also extends and explores a new tool for this knowledge‐sharing process by applying CBR methodology.

The designed model in this research will provide a practice‐oriented vehicle allowing the supply chain members to share and apply their knowledge.

This research applies CBR in the domain of SCM, it both enriches the available approaches to supply chain performance enhancement and enlarges the application domains of CBR methodology.

The purpose of this paper is to examine the effect of knowledge management capabilities (KMCs) on supply chain management practices (SCMP) and organizational performance (OP) in firms, in addition to examining the effect of supply chain management on OP.

To demonstrate the effect of KMCs on SCMP, and OP, different techniques such as factor analysis, correlation analysis, and structural equation modeling were used to verify the validity of the proposed conceptual model and to test the suggested hypotheses, using data collected from 165 companies in the Saudi food industry (representing a response rate of 74.9 percent).

According to the study’s findings, SCMP are positively affected by KMCs. Moreover, OP is directly affected by KMCs and SCMP.

Due to the specific nature of the sample, the findings of the current research are applicable only to the food industry.

The current research introduced a conceptual model, which has been tested and verified in the Saudi food industry. The findings recommend that both KMCs as well as SCMP will contribute to improving the OP. In addition, KMCs will improve the SCMP.

This paper aims to analyze how organizational conditions, technology adoption, supplier relationship management and customer relationship management affect knowledge creation through socialization‐externalization combination, internalization (SECI) modes, and various ba, as proposed by Nonaka and Konno, in a supply chain.

A qualitative inquiry with thematic analysis, which focuses on a thin film transistor‐liquid crystal display (TFT‐LCD) panel manufacturer and an integrated circuits (IC) packaging and testing manufacturer, is presented in order to identify how these key factors affect knowledge creation in a supply chain environment through the SECI modes and ba.

The results show that these critical factors facilitate different types of knowledge conversion process in order to achieve successful knowledge creation in a supply chain. Knowledge of the significant factors that were found in this study may be applicable to countries or areas such as Hong Kong, Korea, Singapore or other developing countries, whose dominant businesses are similar to the original equipment manufacturers (OEMs)/original design manufacturers (ODMs) in Taiwan.

This paper considers the case study only as one empirical illustration of many other possible implementation processes. The study does not assume that these companies are a paradigm or that the specific situation is applicable to all other business enterprises. Future researchers interested in this field are therefore encouraged to triangulate its findings by examining variables generated from this study.

This study employs a quantitative approach to investigate critical knowledge creation factors for supply chain performance. Through empirical study, a better understanding of the dynamics of knowledge creation in a supply chain can be gained.

The literature on supply chain risk management (SCRM) has investigated a multitude of supply chain risks. This paper aims to make a case for the importance of managing the risk of knowledge loss in the supply chain management (SCM) function and incorporating knowledge loss as a critical risk within the SCRM process.

This paper adopts a knowledge-based view of the SCRM process and attempts to bring to light insights based on a synthesis of the relevant literature. The authors conducted a systematic literature review of peer-reviewed articles published between 1998 and 2019. Further, a case study was conducted to illustrate the significance of the risk of knowledge loss in the SCM function in terms of how it operates and why it has such a significant impact on performance.

Knowledge loss is a relatively neglected type of supply chain risk that can be added to the existing typologies. This paper argues that knowledge loss in the SCM function has the propensity to significantly impact the performance of the focal firm, exacerbate other types of supply chain risk and impede risk mitigation efforts. We put forth several strategies that supply chain managers can adopt to mitigate the risk of knowledge loss in their function.

This paper generates an exploratory opening that could pave the way for a systematic theory of knowledge loss as a supply chain risk and future empirical research. The study culminates in a number of important insights and initiatives for supply chain managers to recognize and manage the risk of knowledge loss.

This paper argues for the importance of incorporating the risk of knowledge loss in SCRM research and practice. It also provides an examination of some promising angles for future research in SCRM from a knowledge-based perspective.