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Based on the attention-based view (ABV), this study examines the mechanism of external pressure and internal managerial interpretation affecting the promotion of green entrepreneurial orientation (GEO) of agricultural enterprises.

Based on data collected from 208 agricultural enterprises in China, the conceptual model was tested by using hierarchical regression.

The results show that managerial interpretation can affect the promotion of GEO. Command and control regulation, market-based regulation and green market pressure are important external pressures that affect the promotion of GEO. In addition, managerial interpretation mediates the relationship between command and control regulation and GEO, market-based regulation and GEO, as well as green market pressure and GEO.

This study proposes a key path for promoting the adoption and implementation of GEO by agricultural enterprises. The research results provide experience for emerging and developing countries to promote the GEO of agricultural enterprises, which is helpful to alleviate the environmental problems caused by the development of agricultural enterprises.

For the first time, this study introduced the ABV into the research of GEO. The research results enrich the theoretical perspective of GEO and expand the research field of the ABV. In addition, this study fills the research gap that existing research has not paid enough attention to the internal driving factors of GEO and opens the black box between the external pressure and GEO.

In recent years, sustainable supply chain practices (SSCPs), including corporate social responsibility (CSR), have been recognised as important means of developing firms’ sustainability performance (SP). However, empirical findings on the SSCP–SP interaction are inconsistent and even contradictory. This research presents a quantitative meta-analysis that aims to uncover SSCP–SP interactions based on the correlations found in previously published empirical studies.

Based on the main and moderating variables and selection criteria, 64 sample studies were selected after a systematic literature review and meta-analysis.

The findings confirm a positive correlation (0.438) between SSCP and SP. The results also reveal various critical moderators identified through meta-regression.

This study provides insights for operations managers and policymakers regarding the significance of control variables (e.g. ISO certification, type of economy, innovation approach, data collection method) on the relationship between SSCP and SP for business operations. This research uncovers the impacts of ISO regulations and proposed hypotheses through the lens of the natural resource-based view (NRBV) and institutional-based view (IBV).

This research is unique in that it provides a systematic view of the SSCP–SP interaction, validates the results through a theoretical lens (NRBV and IBV) and generalises the results by evaluating the moderation effects via checking prior literature.

This study builds on knowledge-based view (KBV) research and the natural resource-based view of the firm (NRBV) to examine the effect of knowledge absorptive capacity on innovative performance. It also investigates the mediating role of three dimensions of the cluster environment: degree of network, institutional environment and access to factors of production.

By means of partial least squares-based structural equation modelling method, the study validated and analysed the responses of 503 owners and managers of small and medium-sized enterprises (SMEs) in the wood industrial cluster of Cote d'Ivoire, a developing economy.

The analysis and results reveal that knowledge absorptive capacity strongly predicts cluster environment and innovation performance. Moreover, the cluster environment emerged as a powerful determinant of innovation performance and a mediator of the effect of knowledge absorptive capacity on innovation performance. Unequivocally, institutional support has no significant impact on knowledge absorptive capacity (KAC) and innovative performance mediation relationship and is not a key determinant of innovative performance.

This study offers a key departure from past studies by linking knowledge absorptive capacity to innovative performance and the cluster environment in SMEs. It also extends knowledge concerning the role of KBV, NRBV and relational theory in innovation performance.

The study explores manufacturers' supply chain social capital (SCSC) (structural social capital and relational social capital) and supply chain performance, respectively, as drivers and outcome of green supply chain management practices (GSCMPs). Additionally, the study explores the direct relationship between SCSC and supply chain performance of manufacturers.

The author develops and tests a research model grounded in the resource-based view and the natural resource-based view theory using survey data from 100 manufacturing firms operating in Ghana. The measurement model and hypothesized paths were examined using partial least squares structural equation modeling.

The findings revealed that relational social capital of manufacturers has a positive and significant relationship with supply chain performance, but structural social capital does not. Additionally, manufacturers' structural social capital and relational social capital were found to have a positive and significant relationship with GSCMPs. Lastly, GSCMPs were found to have a positive and significant relationship with supply chain performance.

The study contributes to the limited literature demonstrating the contribution of intangible relational assets, specifically SCSC, toward GSCMPs implementation.

Despite the wide use of quantitative assessment to identify the relationship between green logistics (GL) practices and the sustainability performance (SP) of firms, results of these studies are inconsistent. A lack of theoretical foundation has been cited as a potential reason for these contradictory findings. This study aims to explore the relationship between GL practices and SP qualitatively and to provide a theoretical foundation for this link.

Following a multi-methodology approach, the authors used the grounded theory method (GTM) to investigate perceived relationships through qualitative analysis and adopted the system thinking (ST) approach to identify causal relationships using causal loop diagrams (CLDs).

The authors identified different sustainability practices under three major categories: logistics capabilities, resource-related practices and people-related practices. This analysis showed the relationships among these practices are non-linear. Based on the results, the authors developed three propositions and introduced a theoretical foundation for the relationship between GL practices and SP.

Managerial personnel can use the theoretical foundation provided by this study when making decisions on GL practices adoption. This theoretical foundation suggests applying a holistic approach that can help optimize SP by selecting suitable practices. On the other hand, researchers can use a multi-methodology approach suggested by this study to explore complex social issues.

This study contributes to the knowledge from a methodology perspective as no previous studies have been conducted to identifying the relationship between GL practices and SP by combining GTM and ST approaches. This combination can be extended to build system dynamics models for sustainable logistics impacts bringing novelty to the research field of sustainable logistics.

This study examines green absorptive capacity as an important intervening variable that elucidates the relationship between green supply chain management (GSCM) practices (specifically, green purchasing, customer cooperation and investment recovery) and firm performance.

Drawing from the theoretical underpinnings of the natural-resource-based view theory and information processing theory, a research model is developed and tested using data obtained from 368 manufacturing firms in Ghana. Data analysis was conducted using structural equation modeling.

The results indicate that green purchasing, customer cooperation and investment recovery have a direct positive and significant effect on firm performance. Additionally, green purchasing and customer cooperation have a positive and significant effect on green absorptive capacity but investment recovery does not. Further, the results show that the paths from green purchasing and customer cooperation to firm performance are positively mediated by green absorptive capacity.

The study reveals to supply chain managers that green absorptive capacity is an important conduit through which firms can achieve enhanced firm performance from GSCM initiatives.

This study makes a contribution by integrating the absorptive capacity literature and green management literature and establishes green absorptive capacity as a mechanism through which GSCM practices enhance firm performance.

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 paper proposes a maturity model to indicate the operational excellence (OE) implementation status of businesses in emerging countries, considering its importance in Industry 4.0.

The study involves four steps. First, undertake a study of the literature to identify the variables to consider in the maturity model; second, identify how to organize the variables found in the first step; third, structure a questionnaire to define the maturity model; and lastly, validate the variables found in the literature and the maturity levels.

A total of 23 variables were validated through interviews with general managers, operation managers and experts within organizations. Interviews were carried out in 49 companies from different sectors. Five maturity levels were defined in this study: basic level, beginner level, training level, innovative level and champion level.

Many businesses are implementing OE as a practice to remain competitive in their industries, targeting economic, environmental and social sustainability. However, OE implementation in companies from developing or emerging countries is far below the average level of that in developed companies due to cultural, political or economic constraints. To the best of the authors’ knowledge, there is no model that indicates the status of OE implementation in companies from emerging countries or the different levels to implement OE. This study fills the mentioned gap.

This study aims to investigate how a firm's management team's capacity to efficiently use its resources affects the firm's exposure to climate change. Specifically, the authors investigate the intriguing question – does managerial ability affect a firm's climate change exposure?

The authors use an unbalanced panel dataset of 4,230 US based firms listed on Compustat from 2002–2019 and test the hypothesis by panel regression analysis. To mitigate endogeneity concerns, difference-in-differences and instrumental variable approaches are used.

The baseline analysis shows a negative, statistically significant impact of managerial ability on climate change exposure. The findings hold after controlling for endogeneity using two-stage least squares regression and difference-in-differences tests. The authors find the negative effect is stronger for managers engaged in socially responsible activities, and after climate change issues receiving greater public awareness following the 2006 release of the Stern Review and the 2016 signing of the Paris Accord.

Motivated by the resource-based theory and the natural resource-based view of the firm model, the empirical results support the view that greater managerial ability protects the firm against environmental challenges through efficient use of firm resources. Compared with traditional climate change measures that are plagued by disclosure issues, the use of the Sautner, Van Lent, Vilkov and Zhang's machine learning based dataset utilizing earning conference calls provides stronger, robust findings that will be useful to management and investors in environmental performance assessments.

Motivated by the resource-based theory and the natural resource-based view of the firm model, the empirical results support the view that greater managerial ability protects the firm against environmental challenges through efficient use of firm resources. Compared with traditional climate change measures that are plagued by disclosure issues, the use of the machine learning based dataset utilizing earning conference calls provides stronger, robust findings that will be useful to management and investors in environmental performance assessments.

This research attempts to explore how reverse logistics (RL) and sustainable supply chain initiatives (SSCI) affect sustainability performance (SP) in the manufacturing industry under the moderating effects of organisational learning capability (OLC). At the same time, this study is expected to allow manufacturers to advance towards a high level of model generation in the green economy.

The data for this study was obtained from 451 manufacturing companies in the Hebei Province, China. This study develops a model and tests all hypothesised relationships using partial least square–structural equation modelling (PLS-SEM) with two-step analytical procedures.

The results indicate that SSCI and RL have a positive relationship with SP, and SSCI is positively related to RL. Moreover, the OLC moderates the relationship between RL and SP as well as the relationship between SSCI and SP.

The findings of the study yield valuable managerial insights on how the effective implementation of green practices, coupled with the utilisation of learning capabilities, can contribute to improving the sustainability of manufacturing firms. The study has certain limitations that suggest potential avenues for future research, the most significant of which is our reliance on data from a single country, which may impede the generalisability of the findings.

This study contributes to the existing literature on SP by considering RL and SSCI and offers a unique theoretical argument that describes the relationships by considering the moderating effect of OLC, which has not been empirically explored.