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This study aims to address three research questions pertaining to climate neutrality within the supply chain of metal and mining industry: (1) How can an organization implement practices related to climate neutrality in the supply chain? (2) How do members of the supply chain adopt different measures and essential processes to assist an organization in responding to climate change-related concerns? (3) How can the SAP-LAP framework assist in analyzing and proposing solutions to attain climate neutrality?

To address the proposed research questions concerning climate neutrality, this study employs a case study approach utilizing the SAP-LAP (situation, actor, process–learning, action, performance) framework. Within the SAP-LAP framework, adopting a natural resource-based perspective, the study thoroughly examines the intricacies and interactions among existing situations, pertinent actors and processes that impact climate initiatives within a metal and mining company.

The study's findings suggest that organizations can achieve the objective of climate neutrality by prioritizing resources and capabilities that lead to reduced GHG emissions, lower energy consumption and optimal resource utilization. The study further proposes key elements that significantly influence the pursuit of climate neutrality within enterprises.

This study is one of the earliest contributions to the development of a holistic understanding of climate neutrality in the supply chain of the metal and mining industry.

The study will assist practitioners and policymakers in comprehending the present circumstances, actors and processes involved in enterprises' supply networks in order to attain climate neutrality in supply chains, as well as in taking the right steps to enhance performance.

This study presents a climate neutrality model and provides valuable insights into emission management, contributing to the achievement of the climate neutrality objective.

This study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.

The current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.

The results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.

Instead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

This paper aims to investigate whether the establishment of commodity futures can effectively hedge systemic risk in the spot network, given the context of financialization in the commodity futures market.

Utilizing industry association data from the Chinese commodity market, the authors identify systemically important commodities based on their importance in the production process using multiple graph analysis methods. Then the authors analyze the effect of listing futures on the systemic risk in the spot market with the staggered difference-in-differences (DID) method.

The findings suggest that futures contracts help reduce systemic risks in the underlying spot network. Systemic risk for a commodity will decrease by approximately 5.7% with the introduction of each corresponding futures contract, since the hedging function of futures reduces the timing behavior of firms in the spot market. Establishing futures contracts for upstream commodities lowers systemic risks for downstream commodities. Energy commodities, such as crude oil and coal, have higher systemic importance, with the energy sector dominating systemic importance, while some chemical commodities also have considerable systemic importance. Meanwhile, the shortest transmission path for risk propagation is composed of the energy industry, chemical industry, agriculture/metal industry and final products.

The paper provides the following policy insights: (1) The role of futures contracts is still positive, and future contracts should be established upstream and at more systemically important nodes in the spot production chain. (2) More attention should be paid to the chemical industry chain, as some chemical commodities are systemically important but do not have corresponding futures contracts. (3) The risk source of the commodity spot market network is the energy industry, and therefore, energy-related commodities should continue to be closely monitored.

This paper aims to evaluate the outcome effectiveness of the global reporting initiatives (GRI) transitions by understanding how companies have responded to the changes from G3.1 to G4 and finally to the GRI Standards.

A quality disclosure score is developed that incorporates assessments of both the quality of disclosures and the materiality of Australian companies. To analyse materiality, survey data were collected from 187 companies. Disclosure scores are based on a content analysis of the sustainability reports of 12 mining and metals companies and 12 financial services companies that used the GRI Standards from 2011 to 2019 (a total of 213 reports).

The study found that the GRI transitions have not led to companies improving the quality of their disclosures on areas considered important for them to achieve their social and environmental goals. Instead, the companies tended to use a greenwashing strategy, where the quality of disclosure of material issues declined or fluctuated over time.

From a practical perspective, the disclosure score developed in this paper enables managers of companies to recognize a threshold of completeness and to summarize the areas that are not materially relevant to their business.

The results are potentially helpful for investors, shareholders and other stakeholders, enabling them to better understand sustainability reports.

This study contributes to the body of research in sustainability reporting by providing evidence on the outcome effectiveness of the latest updates in the GRI framework.

The global resolution of embracing dynamic and intertwined production systems has made it necessary to adopt viable systems like circular economy (CE) to ensure excellency in the business. However, in emerging countries, it is challenging to implement the CE practices due to the existing problems in the supply chain network, as well as due to the vulnerable financial condition of the business after the deadly hit of COVID-19. The main aim of this research is to determine the barriers to implementing CE considering the recent pandemic and suggest strategies to organizations to ensure CE for a cleaner environment and greener economy.

After an extensive literature review and validation from experts, 24 sub-barriers under the class of 6 main barriers are finalized by Pareto analysis, which is further analyzed via the best-worst method to determine the weight and rank of the barriers Further, fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the proposed startegies to overcome the analysed barriers.

The results identified “unavailability of initial funding capital”, “need long time investment”, “lack of integrating production system using advance technology” and “lack of strategic planning” as the most acute sub-barriers to CE implementation. Further, fuzzy TOPSIS method is used to suggest the best strategy to mitigate the ranked barriers. The results indicated “integrated design facility to CE”, “ensuring large scale funding for CE facility” as the best strategy.

This study will motivate managers to implement CE practices to enjoy proper utilization of the resources, sustainable benefits in business, and gain competitive advantage.

Periodically, a lot of work is done on CE practices but none of them highlighted the issues in the domain of the leather products industry (LPI) and COVID-19 toward achieving sustainability in production and consumption. Thus, some significant barriers and strategies to implement CE for achieving sustainability in LPI are highlighted in this study, which is a unique contribution to the literature.

Although strategic scholars have made great effects to exploring the moderating roles of team interaction in explaining the effect of top management team (TMT) diversity, they have adopted seemingly conflicting theoretical perspectives to explain how it works. Drawing on ideas from the threat rigidity theory, the authors integrated these perspectives by proposing a contingency model in which the relationships between TMT diversity and adaptive firm performance depend on the matching between the internal context (i.e. overlapping team tenure) and external context (i.e. severity of threat).

This study sampled 579 Chinese A-share listed companies that have been severely affected by the COVID-19 pandemic, and multilevel linear regression analysis was used to test the hypothesis.

Results provided support for this hypothesis. Specifically, the interaction between TMT age/tenure diversity and overlapping team tenure is significant only when the severity of threat is high, while the interaction between TMT functional diversity and overlapping team tenure is significant only when the severity of threat is low.

The results of this study provide a comprehensive perspective to predict the performance impact of team diversity and contribute to diversity research and practice.

Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

This paper aims to examine how the use of environmental, social and governance (ESG) incentives intersects with top management power and various corporate governance mechanisms to affect excess annual cash bonus compensation.

The authors use a novel artificial intelligence (AI) technique to obtain data about ESG incentives use by firms in the S&P 500. The authors test the hypotheses with an endogenous treatment-regression and a contrast test.

When the top management team has power and uses ESG incentives, there is a 32% reduction in excess annual cash bonuses implying ESG incentives are an effective corporate governance tool. However, nuanced analyses reveal that when powerful management teams with ESG incentives are from environmentally sensitive industries, have a corporate social responsibility (CSR) committee or have long-term view institutional shareholders, they derive excess bonuses.

Stakeholders will better understand management’s motivations for the inclusion of ESG incentives in executive compensation contracts and be able to identify situations which require closer scrutiny.

Given the increased popularity of ESG incentives, society, regulators, boards of directors and management teams will be interested in better understanding when these incentives might be effective and when they might be abused.

To the best of the authors’ knowledge, this study is the first to examine the use of ESG incentives in relation to excess pay. The authors contribute to both the CSR and executive compensation literatures. The work also uses a new methodological technique using AI to gather difficult-to-obtain data, opening new avenues for research.

Scholars and practitioners increasingly recognize data as an important source of business opportunities, but research on the effect on small and medium-sized enterprises (SMEs) is limited. This paper empirically examines the complementary impact of SMEs' data capability and supply chain capability (SCC) and further tests the mediation effect of SCC between data capability and operational performance. The mediated effect of data capability is also moderated by competition.

This paper analyzes longitudinal data collected from 122 manufacturing SMEs in Finland. Hypotheses were tested by using structural equation modeling (SEM).

The results show that to benefit from the data capability, SMEs require a certain level of SCC to extract the value from the SMEs' data capability and support operational performance. Additionally, competition affects how SMEs benefit from data capability, as competitor turbulence moderates the complementary effect of data capability and SCC on operational performance.

This is one of the first studies examining the longitudinal effect of SMEs' data and SCC on operational performance in the current competitive environment.

Small- and medium-sized enterprises (SMEs) often operate in environments marked by high levels of turbulence. Such firms adopt digital technologies and platforms that provide access to external real-time information and establish digital connectivity between firms to remain competitive. This study aims to focus on SMEs’ downstream and upstream platform-based digital connectivity (PDC).

This study examines the effects of PDC on SMEs’ operational performance under conditions of environmental turbulence. The data was gathered from 192 SMEs operating in the manufacturing arena.

The results show that the adoption of PDC does not directly affect an SME’s operational performance. However, in highly turbulent environments, PDC can improve operational performance. The results indicate that the performance effects of PDC vary according to the level and type of environmental turbulence.

This research offers insights into the relationship between PDC among SMEs and operational performance and encourages future research examining other possible conditional effects that could explain the contradictory results found in previous research.

This study contributes to the knowledge of supply-chain digitalization among SMEs and its performance effects in varying environmental conditions. Further, this study contributes to the prior research by focusing on the interorganizational aspects of digitalization in SMEs.