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Globalisation, trade barriers, unprecedented health crises and geo-political crises have forced organisations to revisit their performance measurement systems (PMS) to better prepare their supply chain against the risk and improve performance in times of crisis. This study aims to review the supply chain operation reference (SCOR)-based PMS and propose a dynamic SCOR-based PMS for supply chain risk management (SCRM).

Due to the need for multi-stakeholder perspectives on SCOR-based PMS for the SCRM, the authors aimed to develop a theory rather than to elaborate upon or test the theory. Hence, the authors adopted an inductive theory-building approach to build research propositions. The authors also gathered 12 semi-structured interviews with knowledgeable managers from B2B international companies.

The findings of the study highlight the challenges faced by the organisations during the implementation of the SCOR-based performance indicators and the positive impacts they have on decision-making and on the continuous improvement strategy of organisations to tackle supply chain risks and improve performance. The findings suggest that the effects of these indicators are more felt during risk management and risk monitoring stages.

Like any other study, this study has some rules, and, thus, the authors caution the readers that they must interpret the findings of the research considering these limitations. The study is based on semi-structured qualitative interviews. The interviews were conducted with 12 knowledgeable managers from France; thus, the insights drawn from the study cannot be generalised to other settings. Furthermore, the samples represent something other than small and medium enterprises. In the future, the samples from small and medium firms can offer a nuanced understanding of the performance indicators for SCRM.

To the best of the authors’ knowledge, this is one of the few studies which has attempted to revisit the SCOR-based PMS in the B2B supply chain for risk management. The study’s findings help expand the SCOR-based PMS literature and offer numerous insights to the management and consultants facing challenges in SCOR implementation.

One of the fundamental objectives of adopting digital supply chain (DSC) is to uplift the performance of an organization. Although a wide variety of literature confirms the impact of DSC on performance, it is hard to explore as to which dimensions of the performance is affected by DSC and how much. This chapter undertakes discussion on the impact of DSC on the various organizational performance indicators. The chapter also denotes some major key performance indicators (KPIs) that organization can track to gauge the impact of DSC on performance. A brief discussion on the challenges related to the development, adoption, and continuation of KPIs is also appeared in the later part of the chapter. The chapter concludes by denoting that the utilization of digital technologies (DTs) such as artificial intelligence (AI), the Internet of Things (IoT), and complex analytics in DSC has prospects for enhancing the operational efficiency, transparency, and agility of a supply chain (SC). Organizations that adopt these DTs have experienced better demand forecasting, reduced time order fulfillment time, and higher levels of consumer satisfaction. Nonetheless, the successful use of DSC requires development and implantation of KPIs regularly.

Grounded in contingency theory and strategic fit theory, the goal for this research was to determine if managers differentiate in terms of the degree of partnership when allocating resources for planning, joint operating controls, communication and other management components to relationships and if this differentiation is based on the Partnership Model (Lambert et al., 1996).

In total, 381 managers representing 31 relationships participated in one-and-a-half-day partnership meetings, and the authors analyzed how the management components were implemented in each relationship compared to the recommendations in the Partnership Model.

Managers did not differentiate types of partnerships which led to over-resourcing relationships with low potential and under-resourcing those with the highest potential for creating value. The principles of contingency theory and strategic fit were not used for managing relationships.

Contingency theory combined with the relationship view suggests that management components should not be implemented at the same level for all relationships, but in the 31 relationships studied different partnership types were not managed based on their potential.

The research reinforces the need for a formal structure like the Partnership Model to establish joint goals for a relationship and guide management in implementation.

Effective supply chain management depends on the ability of managers to differentiate among partnership types and fit relational mechanisms that are appropriate. However, researchers tend to generalize their findings to all partnerships regardless of potential. The authors found support for the Partnership Model published in IJLM in 1996 as a method to resource different types of partnerships following the contingency perspective and strategic fit theory.

This study examines the direct and indirect effects of social capital on supply chain performance via supply chain quality integration (SCQI), which refers to integrating supply chain partners from the perspective of quality management. It also examines the moderating role of environmental uncertainty in the link between social capital and SCQI and determines the conditional indirect effect of social capital on supply chain performance via SCQI.

Data were collected using a time-lagged research design through a self-administered survey of supply chain professionals in manufacturing firms in Pakistan. Hayes’ PROCESS Macro was used to test the hypotheses.

The results show a positive relationship between social capital and supply chain performance. SCQI partially mediates the relationship between social capital and supply chain performance. Environmental uncertainty significantly moderates that relationship in such a way that firms that operate under high environmental uncertainty are more likely to use their social capital to develop SCQI than firms that operate under low environmental uncertainty.

The study has practical implications for managers who seek to implement SCQI practices using social capital. Leveraging social capital across the supply chain fosters strong connections and a quality-oriented approach across the supply chain, and improves overall performance. Managers can use the power of social capital to navigate environmental uncertainty.

This study’s originality lies in its drawing on the dynamic capability theory and contingency theory and integrating the dispersed scholarly work on social capital, SCQI, and supply chain performance under the boundary condition of environmental uncertainty.

Due to the uniqueness of individual construction projects, identifying the dominant risk factors is needed for risk mitigation in ongoing and future projects. This study aims to identify the dominant construction supply chain risk (CSCR) factors, based on studies conducted between 2002 and 2022.

The study adopts the preferred reporting items for systematic reviews and meta-analysis (PRISMA) procedure to identify, screen and select relevant articles in order to provide a bibliography and annotation of the prevalent risks in the supply chains. A descriptive analysis of the findings then follows.

The study’s findings have highlighted the three most prevalent risks in the construction supply chain (poor communication across project teams, changes in foreign currency rate, unfavorable climate conditions) as reported in literature, that project teams need to pay closer attention to and take proactive steps to mitigate.

Due to limitations imposed by the chosen research methodology, tools, time frame and article availability, the study was unable to examine all CSCR-related papers.

The results will serve as a useful roadmap for risk/supply chain managers in the construction industry to take strategically proactive steps towards allocating resources for CSCR mitigation efforts.

Context-specific research on the impact of social and cultural risks on the construction supply chain would be beneficial, due to emerging social network risk factors and the complex socio-cultural settings.

There is presently no study that has reviewed extant studies to identify and compile the dominant risk factors (DRFs) associated with the supply chain of construction projects for ranking in the supply chain risk management process.

This study aims to examine the effect of Industry 4.0 technology on resilience in established cross-border supply chain(s) (SC).

A literature review provides insight into the resilience capabilities of cross-border SC. The research uses a case study of operational international SC: the producers, importers, logistics companies and UK Government (UKG) departments. Semi-structured interviews determine the resilience capabilities and approaches of participants within cross-border SC and how implementing an Industry 4.0 Internet of Things (IoT) and capitals Distributed Ledger (blockchain) based technology platform changes SC resilience capabilities and approaches.

A blockchain-based platform introduces common assured data, reducing data duplication. When combined with IoT technology, the platform improves end-to-end SC visibility and information sharing. Industry 4.0 technology builds collaboration, trust, improved agility, adaptability and integration. It enables common resilience capabilities and approaches that reduce the de-coupling between government agencies and participants of cross-border SC.

The case study presents challenges specific to UKG’s customs border operations; research needs to be repeated in different contexts to confirm findings are generalisable.

Operational SC and UKG customs and excise departments must align their resilience strategies to gain full advantage of Industry 4.0 technologies.

Case study research shows how Industry 4.0 technology reduces the de-coupling between the SC and UKG, enhancing common resilience capabilities within established cross-border operations. Improved information sharing and SC visibility provided by IoT and blockchain technologies support the development of resilience in established cross-border SC and enhance interactions with UKG at the customs border.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

This study investigates whether the underrepresentation of women in executive-level roles within the supply chain management (SCM) field is justified or the result of gender injustices. The analysis examines if there is a gender compensation gap within executive-level SCM roles and whether performance differences or other observable factors explain disparities.

Publicly reported executive compensation and financial data are merged to empirically test if gender differences exist and investigate whether the underrepresentation of women in executive-level SCM roles is unjust.

Women occupy only 6.29% of the positions in the sample of 447 SCM executives. Unlike prior studies, we find that women executives receive higher compensation. The analysis does not identify observable factors explaining the limited inclusion of women in top-level roles, suggesting that gender injustices are prevalent in SCM.

This study only considers observable factors and cannot conclusively determine if discrimination is occurring. The low level of inclusion of women in executive roles suggests that gender injustice is intrinsic within the SCM profession. These findings will hopefully motivate firms to undertake transformative actions that result in outcomes that advance gender equity, ultimately leading to social justice for female SCM executives.

The use of social justice and feminist theories, a focus on SCM roles, and an empirical methodology utilizing objective measures represents a novel approach to investigating gender discrimination in SCM organizations, complementing prior survey-based studies.

This paper aims to explore the significance of resource sharing in business to capture new market opportunities and securing competitive advantages. Firms enter strategic alliances (SAs), especially for designing new products and to overcome challenges in today’s fast changing environment. Research projects have dealt with the creation of SAs, however without concrete referencing the impact on selected supply chain resources. Furthermore, academia rather focused on elaborating the advantages and disadvantages of SAs and how this affects structural changes in the organization than examining the effects on supply chain complexity and performance.

The authors collected and triangulated a multi-industry data set containing primary data coming from more than 200 experts in the field of supply chain management along and secondary data coming from Refinitiv’s joint ventures (JVs) and SA database and IR solutions’ database for annual reports. The data is evaluated in three empirical settings using binomial testing and structural equation modeling.

The results show that nonequity SAs and JVs have varying degrees of impact on supply chain resources due to differences in the scope of the partnership. This has a negative impact on the complexity of the supply chain, with the creation of a JV leading to greater complexity than the creation of a nonequity SA. Furthermore, the findings prove that complexity negatively impacts overall supply chain performance. In addition, this study elaborates that increased management capabilities are needed to exploit the potentials of SAs and sheds light on hurdles that must be overcome within the supply network when forming a partnership. Finally, the authors give practical implications on how organizations can cope with increasing complexity to lower the risk of poor supply chain performance.

This study investigates occurring challenges when establishing nonequity SAs or JVs and how this affects their supply chain by examining supply networks in terms of complexity and performance.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.