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Green innovation in supply chains is crucial for socioeconomic development and stability. Factors that influence collaborative green innovation in the supply chain are complex and diverse. Exploring the main influencing factors and their mechanisms is essential for promoting collaborative green innovation in supply chains. Therefore, this study analyzes how upstream and downstream enterprises in the supply chain collaborate to develop green technological innovations, thereby providing a theoretical basis for improving the overall efficiency of the supply chain and advancing green innovation technology.

Based on evolutionary game theory, this study divides operational scenarios into pure market and government-regulated operations, thereby constructing collaborative green innovation relationships in different scenarios. Through evolutionary analysis of various entities in different operational scenarios, combined with numerical simulation analysis, we compared the evolutionary stability of collaborative green innovation behavior in supply chains with and without government regulation.

Under pure market mechanisms, the higher the green innovation capability, the stronger the willingness of various entities to collaborate in green innovation. However, under government regulation, a decrease in green innovation capability increases the willingness to collaborate with various entities. Environmental tax rates and green subsidy levels promote collaborative innovation in the short term but inhibit collaborative innovation in the long term, indicating that policy orientation has a short-term impact. Additionally, the greater the penalty for collaborative innovation breaches, the stronger the intention to engage in collaborative green innovation in the supply chain.

We introduce the factors influencing green innovation capability and social benefits in the study of the innovation behavior of upstream and downstream enterprises, expanding the research field of collaborative innovation in the supply chain. By comparing the collaborative innovation behavior of various entities in the supply chain under a pure market scenario and government regulations, this study provides a new perspective for analyzing the impact of corresponding government policies on the green innovation capability of upstream and downstream enterprises, enriching theoretical research on green innovation in the supply chain to some extent.

Environmental pollution has increased as a result of modern settlements' expanding demand and rapid population growth. In Ebonyi State, Nigeria, quarrying is one of the activities that has an impact on the environment and ecosystem. The aim of the study is to assess stream water’s quality in order to ascertain how quarry operations affect the streams’ water quality. The present study investigated the environmental impact of quarrying on the physicochemical properties of surface water in Ebonyi State, Nigeria.

A total of 288 surface water samples were taken in 2018, 2019 and 2020 from quarry locations and a Control location for the determination of physicochemical properties and heavy metal contents using standard analytical methods. Datasets were analysed using Fisher’s significance least difference (F-LSD) at the 0.05 probability level.

This study discovered that surface waters around quarries are severely polluted, according to the results of the physico-chemical and heavy metal contents of the surface waters. Most of the physical and chemical properties of the water downstream of the Ishiagu, Umuoghara and Ngbo did not meet World Health Organisation (WHO) standards, such as colour and pH. The heavy metal levels in the Ishiagu, Umuoghara and Ngbo streams were above WHO criteria for Pb, Cd and Fe. The results point to the obvious conclusion, without prejudice to other unexplained factors that the pollution is most likely the result of quarry contamination. Strict measures should be taken to regularly monitor the water quality of the streams.

This study focused on the assessment of physicochemical properties using standard analytical methods to evaluate the environmental impact of quarrying on surface water qualities. The study used the World Health Organisation (WHO, 2011) water guideline as a standard to compare with the study dataset and control measures.

This study examines whether common directors are guilty of contagion of corporate frauds from the customer side and, if so, how contagion occurs. Moreover, it explores a way to mitigate it, which is the increased digital orientation of firms.

Secondary data analysis is applied in this paper. We extract supply chain relations from the China Stock Market and Account Research (CSMAR) database as well as corporate fraud data from the same database and the official website of the China Securities Regulatory Commission (CSRC). Digital orientations are estimated through text analysis. Poisson regression is conducted to examine the moderating effect of common directors and the moderated moderating effect of the firms’ digital orientations.

By analysing the 2,096 downstream relations from 2000 to 2021 in China, the study reveals that corporate frauds are contagious through supply chains, while only customers’ misconduct can contagion to upstream firms. The presence of common directors strengthens such supply chain contagion. Additionally, the digital orientation can mitigate the positive moderating effect of common directors on supply chain contagion.

This study highlights the importance of understanding supply chain contagion through corporate fraud by (1) emphasising the existence of the contagion effects of corporate frauds; (2) understanding the potential channel in the process of contagion; (3) considering how digital orientation can mitigate this contagion and (4) recognising that the effect of contagion comes only from the downstream, not from the upstream.

The purpose of this study is to explore the effect of backward supply chain information sharing (SCIS) on the performance of different parties along supply chains.

Using data collected from 617 Chinese manufacturers, this study examines the effect of information sharing from manufacturers to suppliers (ISMS) on supplier and manufacturer responsiveness in both two- and three-tier supply chains and the transferrable effect of information sharing from customers to manufacturers (ISCM) on supplier responsiveness. The authors use structural equation modeling and regression analysis to estimate the proposed relationships.

ISMS is positively related to supplier responsiveness in both two- and three-tier SCIS, whereas its effect on manufacturer responsiveness is conditional, indicating that upstream receiving parties benefit more from backward SCIS. ISCM is positively related to supplier responsiveness, demonstrating the transferable effect of backward SCIS.

When designing SCIS strategies, managers should take into account the unequal distribution of benefits from SCIS and the transferable effect of backward SCIS. Specifically, companies should always motivate their downstream partners to engage in SCIS, while they themselves need to be cautious with information sharing. They should also be aware that their information sharing behavior may benefit a third upstream party.

This study provides deep insights into the distribution of the benefits from SCIS among supply chain partners and suggests that the direction and the role supply chain partners play (as receiving or disclosing parties) in SCIS matter.

This research examines the impact of governance structures within the Brazilian pork supply chain on the necessary controls for exportation. Specifically, the goal is to unravel the intricacies of this supply chain and decode its complexity.

Using transaction cost economics as a theoretical lens, we surveyed the main bodies responsible for the export and quality assurance sectors of Brazilian organizations that trade and export pork. Our sample comprises 53.5% of the country’s pork exporting companies during the period analyzed.

The presence of vertical and horizontal governance structures in the pork export chain stands out. While the vertical structure enables greater control due to command relations, there are trust and cooperation relations in the horizontal structure. This makes it possible to establish mechanisms to control health, quality, safety and traceability in both structures. We also identified each company’s characteristics: formation configuration (if the cooperative, publicly traded company, or other modality), capital stock, location, the average daily slaughter of pigs for export and sows per producer. We conclude that the organizations have concerns related to the food safety programs, as there are programs that seek transparency throughout the process in many supply chain stages.

Studies that relate the level of orientation to the export market with the occurrence or risk of corrupt and opportunistic behavior and the coordination mechanisms adopted may represent an interesting and important opportunity for studies.

This study helps to understand the complexity of the Brazilian pork supply chain.

The current research has developed a novel method to update the decisions regarding real-time data, named the dynamic adjusted real-time decision-making (DARDEM), for updating the decisions of a grocery supply chain that avoids both frequent modifications of decisions and apathy. The DARDEM method is an integration of unsupervised machine learning and mathematical modeling. This study aims to propose a dynamic proposed a dynamic distribution structure and developed a bi-objective mixed-integer linear program to make distribution decisions along with supplier selection in the supply chain.

The constantly changing environment of the grocery supply chains shows the necessity for dynamic distribution systems. In addition, new disruptive technologies of Industry 4.0, such as the Internet of Things, provide real-time data availability. Under such conditions, updating decisions has a crucial impact on the continued success of the supply chains. Optimization models have traditionally relied on estimated average input parameters, making it challenging to incorporate real-time data into their framework.

The proposed dynamic distribution and DARDEM method are studied in an e-grocery supply chain to minimize the total cost and complexity of the supply chain simultaneously. The proposed dynamic structure outperforms traditional distribution structures in a grocery supply chain, particularly when there is higher demand dispersion. The study showed that the DARDEM solution, the online solution, achieved an average difference of 1.54% compared to the offline solution, the optimal solution obtained in the presence of complete information. Moreover, the proposed method reduced the number of changes in downstream and upstream decisions by 30.32% and 40%, respectively, compared to the shortsighted approach.

Introducing a dynamic distribution structure in the supply chain that can effectively manage the challenges posed by real-time demand data, providing a balance between distribution stability and flexibility. The research develops a bi-objective mixed-integer linear program to make distribution decisions and supplier selections in the supply chain simultaneously. This model helps minimize the total cost and complexity of the e-grocery supply chain, providing valuable insights into decision-making processes. Developing a novel method to determine the status of the supply chain and online decision-making in the supply chain based on real-time data, enhancing the adaptability of the system to changing conditions. Implementing and analyzing the proposed MILP model and the developed real-time decision-making method in a case study in a grocery supply chain.

The purpose of this paper is to review studies on mathematical optimization of the sustainable gasoline supply chain to help decision-makers understand the current situation, the exact dimensions of the problem and the models provided in the literature. So, a more realistic mathematical optimization model can be achieved by fully covering all dimensions of the supply chain of this product.

To evaluate and comprehend the mathematical optimization of the sustainable gasoline supply chain research area, a systematic literature review is undertaken that covers material collection, descriptive analysis, content analysis and material evaluation steps. Finally, based on this process, 69 related articles were carefully investigated.

The results of the systematic literature review show the main areas of the published papers on mathematical optimization of sustainable gasoline supply chain problems and the gaps for future research in this field presented based on them.

This approach is subject to limitations because the protocol of the systematic review of the research literature only included searching for the considered combination of keywords in the Scopus and ProQuest databases. Furthermore, the protocol used in this paper restricts documents to English.

The results have significant implications for both academicians and practitioners in this field. It can be useful for academics to comprehend the gaps and future trends in this field. Also, for practitioners, it can be useful to identify and understand the parts of the mathematical optimization model, which can help them model this problem effectively and efficiently.

No systematic literature review has been done in this field by considering gasoline to the best of the authors’ knowledge and delivers new facts for the future development of this field.

The global outbreak of COVID-19 and its subsequent varied impacts on different economic activities necessitate to examine its disruptions and impacts on livestock sector in India due to its recently surging potential as an unrivaled alternative to boost farmer’s income.

The studies for review were identified through search in different databases using relevant keywords. Only full text papers written in English language were reviewed. The review was organized and streamlined using Covidence software.

Analysis of the literature reveals adverse effects of COVID-19 on functioning of input and output stages of livestock supply chains. This has resulted in upstream and downstream economic losses that affect livelihoods of the producers.

Scale of unprecedented crisis due to COVID-19 pandemic requires creative policy decisions to make livestock production systems robust, resilient and sustainable. Organized production systems are required to integrate with livestock-tech startups to modernize their supply chains, whereas local supply chains are required to reorient with government’s intervention in terms of developing on-farm production and postproduction processing facilities.

Although there exist some evidence on COVID-19-related impacts on livestock sector of India, but an integrated review of evidence on COVID-19 related disruptions at all the stages (from input supply to marketing) of livestock supply chains was missing.

Stakeholders in complex capital projects are characterized by complicated interactions, adversarial short-term relationships and cooperative demand for deliverables. Unhealthy interfaces between stakeholders often lead to significant interface conflicts, which gradually become apparent in the construction stage. However, stakeholder interface health (SIH) has not been well understood and measured in the construction industry by either scholars or practitioners. It is essential to identify unhealthy interface relationships between stakeholders by comprehensively assessing SIH for enhancing project performance.

The study provided a comprehensive framework to assess SIH. The assessment was based on Wuli-Shili-Renli theory. Moreover, the CRITIC and Grey-TOPSIS methodologies were applied to precisely evaluate the SIH level. Besides, graph-based interface networks were developed to visualize SIH. At last, the framework was applied to a mass rapid transit project in China to test the validity of the study.

The result showed that stakeholder interfaces with strict contract constraints are healthier. On the other hand, IM behaviors make up for the soft coordination mechanism without contract constraints to a certain extent. The results of the case study were consistent with the actual project practices. The proposed framework provided a useful IM tool for assessing and visualizing SIH.

The limitation of this study is that only the mass rapid transit project was selected for empirical analysis to validate the effectiveness of the proposed framework. It is recommended that the proposed framework be applied to other types of complex capital projects to further discussions in IM.

Theoretically, this study introduces a comprehensive framework to measure the health of stakeholder interfaces in complex capital projects, which helps to provide a theoretical basis and methodological support for stakeholder interface management.

Practically, applying SIH assessment to existing interface management procedures can help the project manager identify interface conflicts between stakeholders in time and eventually contribute to the improvement of PM performance. At the same time, the interface management team tracks the responsibilities of unhealthy interface stakeholders and requires them to take measures to improve the SIH level. Stakeholder interfaces with lower health scores should be given more attention. The proposed framework can serve as a novel IM approach to identify weaknesses in IM and take targeted management measures to alleviate unhealthy stakeholder interface relationships.

The study provides an innovative method for scientifically and accurately assessing SIH. This research can help scholars and practitioners in the project management field facilitate the diagnosis of unhealthy interface relationships and provide decision support for the project management theoretical foundation.

This paper investigates the role of institutional pressures (IPs) and supply chain integration (SCI) in driving the adoption of circular economy (CE) practices. It is hypothesised that, responding to IPs, firms might adopt higher levels of SCI in the attempt to implement CE practices.

A research model is developed and tested on a cross-sectional sample of 150 multi-national enterprises (MNEs). Textual content from corporate sustainability reports is used to measure the constructs of interest through an advanced coding approach.

Findings show that IPs are driving the adoption of CE practices primarily through the mediation of SCI; the prominent roles of coercive regulatory pressures (CRPs) and normative pressures (NPs) are also highlighted. CRPs influence on CE practices is partially mediated by SCI, with NPs influence being fully mediated by it.

The study shows that SCI is a key mechanism that lies in between IPs and CE practices; as such, organisations interested in implementing CE practices need to be aware of requirements for achieving higher levels of SCI.

This empirical study is the first large scale analysis that conceptualises how MNE-driven supply chains adopt CE practices. The study empirically validates the model and identifies research avenues in supply chain management (SCM) research to support the adoption of CE practices.