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The priority giving to green practices in today's competitive market has made green logistics management practices (GLMPS) a significant driver of organizational performance. The purpose of this study is to explore the influence of GLMPS, logistics ecocentricity and supply chain traceability on sustainability performance.

The study uses structured questionnaires to gather data from 274 managers of manufacturing firms in Ghana. The partial least square structural equation modeling approach is used to analyze the data to test the proposed hypotheses.

The results obtained from the analysis indicate that GLMPS positively influence social sustainability and environmental sustainability. However, GLMPS negatively influence business performance. The results further reveal that logistics ecocentricity and supply chain traceability augment GLMPS to achieve significant improvement in both business performance and environmental sustainability through the mediation effect approach.

The study proposes a conceptual framework that tests the combined effect of GLMPs, logistics ecocentricity and supply chain traceability on environmental sustainability, social sustainability and business performance from the Ghanaian perspective.

This study aims to examine the relationship between green supply chain management (Green SCM) practices and environmental performance, and develop an integrated model to explain the mediating role of ecocentricity on the relationship between Green SCM practices and environmental performance in the context of the Ghanaian downstream petroleum industry.

To address the objectives of the study, a survey had been conducted among companies in the Ghanaian downstream value chain. The paper used the structural equation modeling approach and smart partial least squares (Smart-PLS) analytical tool.

The study revealed that Green SCM practices had a significant and positive relationship with supply chain ecocentricity and environmental performance. The study further revealed that supply chain ecocentricity significantly mediated the relationship between Green SCM practices and environmental performance.

The study has developed a new integrated model to enhance oil and gas marketing and distribution company's adaptation and implementation of Green SCM practices.

The study had successfully applied the natural resource-based view and the stakeholder theory in the context of Ghana's downstream petroleum industry. Specifically, these theories had been integrated to form a new model to explain the relationship between Green SCM practices, supply chain ecocentricity and environmental performance in the context of Ghana's downstream petroleum industry. The newly developed integrated model has wider predictability as compared to the individual theories.

The growing relevance of environmental sustainability calls for identification of factors that contribute to green innovation and build green corporate reputation. Drawing on the resource-based view theory, this study aims to explore the influence of green logistics knowledge, green customer knowledge, green supplier knowledge, green competitor knowledge, non-supply chain learning on green innovation and green corporate reputation.

This study adopts the quantitative research method where questionnaire is used to gather data from managers of the sampled 208 small and medium enterprises (SMEs). The structural equation modelling is used to analyse the survey data and test the proposed hypotheses.

The findings reveal that non-supply chain learning, green customer knowledge and green competitor knowledge have both direct and indirect impact on green innovation and green corporate reputation. However, green supplier knowledge and green logistics knowledge directly impact green innovation but indirectly impact green corporate reputation through green innovation.

Despite the growing literature exploring the relationship between learning, innovation and reputation, their literature in emerging economies remains underdeveloped. This study provides empirical evidence to confirm the role of non-supply chain learning and green supply chain knowledge in building green corporate reputation and developing green innovation of SMEs in an emerging economy.

Through the “Going Digital Initiative,” the Ghanaian government has introduced policies that aim at improving the information and communication technology (ICT) infrastructure of the country. These ICT policies have benefited numerous sectors of the Ghanaian economy. In logistics management, ICT has impacted drone medical delivery in the healthcare and maritime sectors. However, the importance of ICT is not realized in the motorcycle goods transport (MGT) industry, regardless of its popularity and high economic dependency. Second, all research on motorcycles is focused on diverse social concerns, and no study has attempted to analyze ICT implementation for MGT operations. This is a significant gap in logistics management. Hence, the study aimed to investigate the impact of ICT on Ghana's MGT industry empirically.

The study adopts a two-phase data collection approach to collect the data. The authors use partial least square structural equation modeling to analyze the study's measurement and structural assessment model.

ICT positively impacts MGT and the drivers considered. The drivers positively influence MGT. The study further analyzes novel results on the relationships between the drivers and their mediating roles in enhancing MGT performance.

The study's originality is the extension of ICT adoption and usage in MGT. The lack of literature on the importance of ICT for MGT services makes this study the primary source of literature, and the relationships investigated are unique as the research area is unexplored.

This study aims to examine management attitude and awareness towards green logistics, explores the external conditions that drive and restrict its positive behaviour, investigates the level of its adoption amongst logistics service providers (LSPs) and determines the major barriers affecting its application in the industry.

This research investigates the key decision-making process on green logistics attitude and behaviour through in-depth interviews and thematic analysis.

This study explores both institutional and individual-level attitudes/awareness. Then, the driving and restraining forces and the challenges that influence the industry’s adoption of green initiatives are determined. Finally, this study constructs a framework following a behavioural driving route with interactions among green “attitude”, sustainable “subjective norms”, “behavioural control” and “external context” factors.

Findings can enlighten the practitioners who are struggling to adopt the green or low-carbon practice and provide valuable insights and constructive advice to LSPs and their stakeholders.

Findings can draw the government and policy-makers’ attention to provide necessary financial or non-financial support for the practitioners to improve their green operations.

To the best of the authors’ knowledge, this study is one of the first attempts to adopt the hybrid theoretical lens on the green behaviour of the logistics industry. New insights are added to existing environmental management literature with a wider understanding and deeper investigation of the decision-making on green logistics in the industry. The theoretical framework in this study can offer future applications to a relevant large-scale study.

The purpose of this paper is to offer improvement in routing and collection load decisions for a green logistics system that delivers lunch boxes.

A mathematical model is introduced into the literature for the 130 years old logistics systems whose delivery accuracy is better than the Six Sigma standard without using sophisticated tools. A simulated annealing (SA) approach is then used to find the routing and collection load decisions for the lunch box career.

The findings establish that we can improve the world-class lunch box delivery (LBD) system. The suggested improvement in terms of reduction in distance travel is nearly 6%. This could be a huge relief for thousands of lunch box careers. The uniformity in collection load decisions suggested by the proposed approach can be more effective for the elderly lunch box carriers.

The research provides a mathematical framework to study an important logistics system that is running with a supreme level of service accuracy. Collecting primary data was challenging as there is no scope for recording and maintaining data in the present logistics system. The replicability of the system for some other city in the world is a challenging question to answer.

Better routing and collection load decisions can help many lunch box careers save time and bring homogeneity in workload into the system.

An efficient routing decision can help provide smoother traffic movements, and uniformity in collection load can help avoid unwanted injuries to about 5,000 lunch box careers.

The originality of this paper lies in the proposed mathematical model and finding the routing and collection load decisions using a nature-inspired probabilistic search technique. The LBD system of Mumbai was never studied mathematically. The study is the first of its kind.

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 aim of this study is to identify the critical factors of green supply chain (GSC) and to adapt these factors to the taxonomy of green practices in healthcare.

A qualitative multiple-case study approach was followed based on 60 interviews with nine French hospitals. An intra-case and a cross-case analysis were implemented.

The findings provide a taxonomy of healthcare GSC and show that regulation, cost reduction, top management commitment, employee training, information technology and measures of environmental performance are critical factors for GSC implementation. The study also underlines a few emergent critical factors including the purchasing group, environmental champion, building construction, combining safety and green approaches.

This study was conducted in France following a qualitative methodological approach. Future research can consider other national and cross-national investigations and other quantitative or mixed methods approaches.

The research provides managers and policy makers numerous invaluable suggestions for the implementation of GSC practices in healthcare facilities. To accelerate GSC implementation, managers can invest in the construction of new buildings, in information technology, and in the automation of flows.

To the authors’ knowledge, this is the first paper identifying the critical factors of GSC implementation in the healthcare sector. It is also the first attempt to provide a taxonomy of hospitals according to their green approaches (reactive, receptive, and proactive).

Sustainable supply chain management has become an increasingly important driver of business performance. Understanding the contingent nature of how performance is improved in this context is therefore a critical task for management. The purpose of this paper is to explore the moderating effects of two practices unique to sustainable supply chain – ecocentricity and supply chain traceability – on a firm’s environmental and operating cost performance.

Survey data were collected from 248 UK manufacturing firms and analyzed using moderated hierarchical regression.

The results suggest that green supply chain management (GSCM) practices are associated with improvements in both environmental and cost-based performance. Further, higher levels of ecocentricity and supply chain traceability are associated with stronger relationships between GSCM practices and cost performance. Contrary to expectations, high levels of supply chain traceability were found to negatively moderate the relationship between GSCM practices and environmental performance.

The research design was survey-based and cross-sectional. Future studies would benefit from longitudinal research designs that capture the effects of GSCM practices on performance over an extended period. The survey data is also perceptual; using secondary data to capture environmental performance outcomes, for example, would be another opportunity for future research.

The authors provide additional support to findings that GSCM practices benefit both environmental and cost performance dimensions. In this context, the authors show that investments by firms in working with a broader set of eco-system partners (ecocentricity) and building supply chain traceability and leads to improved environmental sustainability outcomes. The authors encourage managers to carefully consider how they conceptualize and monitor their supply chains.

This paper offers several contributions to the research in this area. First, the authors develop and validate a measurement scale for ecocentricity and supply chain traceability. Second, the authors show how these two variables – unique to sustainable supply chains – can positively influence firm and environmental performance.

The need to stay competitive amidst ever-changing business environment has shifted competitive strategies from firms to supply chains. Managers are now basing competitive strategies on supply chains acknowledging that supply chains present competitive advantages among other resources. The purpose of the study is to explore the predictive relevance of supply chain collaboration and the extent to which it influences supply chain visibility, stakeholder trust, environmental and financial performances. This study focused on manufacturing firms due to their supplier relationships, consumption of resources, energy and emissions of greenhouse gasses.

The study adopted a survey research design, a quantitative approach and partial least square structural equation modelling technique in making data analysis and interpretations due to its suitability for predictive research models as is the case in this study.

The study hypothesized that supply chain collaboration positively and significantly interacts with supply chain visibility, stakeholder trust, environmental and financial performances. The study results confirmed supply chain collaboration as a significant, positive and a robust influence on supply chain visibility, stakeholder trust, environmental and financial performances thereby projecting win-win scenarios for firms that engage in collaborative supply chain practices.

The study is among the few to indicate findings in relation to the scope of supply chain collaboration's potency in influencing performance from the perspective of manufacturing firms operational in an emerging economy. Thus, this study contributes to understanding the wider scope of supply chain collaboration, its interactions with other firm variables and how it informs decisions of managers, scholars and supply chain partners.