Search results

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as waste and environmental pollution, especially in developing countries. Due to the importance of the green supply chain management (GSCM) philosophy, for solving these problems, the current study aims to evaluate the drivers of GSCM adoption in the construction industry of Iran.

This research uses a descriptive and practical methodology. The participated experts in the study include senior managers of the construction department in Rasht municipality who had relevant academic education and suitable experiences in urban and industrial construction. The experts took part in both qualitative and quantitative phases of the research, namely verification of the drivers extracted from literature and ranking them in ascending order. In the quantitative phase, Step-Wise Weight Assessment Ratio Analysis (SWARA) as a new multi-criterion decision-making (MCDM) method is used to evaluate the drivers of GSCM adoption using MATLAB software.

The results show that environmental management systems, green product design and innovational capability with weights of 0.347, 0.218 and 0.143 are the most significant sub-drivers, respectively. The less important factor is an investment in environmental technology.

This study evaluated the motivational factors of GSCM in the construction industry. The findings help governments, companies and green supply chain (GSC) managers to improve their knowledge about GSCM and make the best decisions to decrease environmental pollution.

This study aims to understand the role of technology adoption (TA) in improving the efficiency and environmental sustainability (ENS) of humanitarian supply chains through collaboration and supply chain agility. This study made an attempt to explore how technological resources can be used strategically to achieve operational efficiency and contribute to sustainable humanitarian logistics.

The data collected from 274 respondents involved in humanitarian logistics is analyzed using the confirmatory factor analysis and the Partial Least Squares Structural Equation Modeling. These respondents include logistics managers, coordinators as well as other relevant personnel from different non-governmental organizations, international aid agencies and relief operations.

The results of this study show that TA plays a critical role in improving both collaboration and supply chain agility in humanitarian operations. It is evidenced that both collaboration and agility significantly moderate the relationship between TA and supply chain outcomes, respectively, improving the effectiveness and ENS of aid delivery. In particular, technology-facilitated collaboration and agility cut down operational costs, reduce the response time and minimize the environmental impact.

This study extends the application of dynamic capabilities view in humanitarian operations and supply chain and elaborates on how technological capability improves humanitarian supply chain performance. This study also highlights the mediation role of agility and collaboration to achieve aid delivery efficiency and ENS.

Supply chain practices play a major role in improving operational efficiency, enhancing resilience in industries and framing strategies for modern businesses. These practices are particularly crucial for the battery industry due to its complex supply chain network, stringent environmental compliance requirements and robust logistical operations required for effective distribution.

This study proposed 23 supply chain practices and investigated their relationship with the supply chain performance (SCP) of a selected battery industry. A structural equation modeling (SEM) approach is used to develop a structural measurement framework. Seven constructs and 23 latent variables are considered in this study. Hypotheses are formulated based on the conceptual framework, and the partial least squares-structural equation modeling (PLS-SEM) is employed to validate these hypotheses.

The results highlight significant interactions among supply chain integration (SCI), customer relationship management (CRM) and trust (TR), as well as their central roles in enhancing operational performance and other vital outcomes. CRM serves as the foundation for strong customer relationships and supports other operations. SCI acts as a central pillar; it ensures cohesive and efficient supply chain processes. TR functions as a catalyst, facilitating smoother interactions and cooperation among supply chain partners.

The study equips battery consultants and managers with insights to refine processes efficiently, allocate resources effectively and establish strategic partnerships. Furthermore, it proposes a systematic framework to enhance the battery industry’s performance.

This study comprehensively evaluates the battery industry’s SCP through novel supply chain practices. It uniquely integrates supply chain metrics into the performance evaluation framework. Furthermore, this research proposes 23 novel supply chain practices tailored to the battery industry.

This research aims to enhance understanding of outsourcing dynamics from emerging markets by employing a bibliometric analysis of relevant scholarly articles. The study explores publication patterns, citation networks, author collaborations and contributions by different countries, offering insights for researchers and practitioners investigating outsourcing in these markets.

A comprehensive bibliometric analysis was conducted using 197 articles from the SCOPUS database, spanning January 1999 to June 2023. Established bibliometric techniques were utilized to analyze publication patterns, citation networks, author collaborations and country contributions, identifying key research themes and influential authors and institutions.

The study identified eight distinct research clusters, highlighting interdisciplinary collaborations, influential authors like Thomas Frisanco and Erdener Kaynak, and significant contributions from the United States and the UK. Notable organizational collaborations include the Hong Kong Polytechnic University and the University of Miami. These findings provide valuable insights into outsourcing practices and research trends in emerging markets.

The study acknowledges limitations such as sampling bias, language bias and publication bias, which may affect the generalizability of the findings. Future research should strive for more diverse and representative samples, including non-English publications and studies with non-significant results, to provide a more comprehensive understanding of outsourcing dynamics.

The findings offer practical insights for organizations considering outsourcing from emerging markets, guiding strategic decision-making and policy development. Understanding publication patterns and research themes can help organizations navigate location selection, vendor management, risk mitigation and performance evaluation in these markets.

Outsourcing can significantly impact employment, income generation, skill development and overall economic development in emerging markets. Policymakers can use these insights to foster business growth, infrastructure development and investment incentives, contributing to economic growth and employment opportunities.

This study provides a comprehensive bibliometric analysis of outsourcing from emerging markets, filling a gap in the existing literature. The insights gained can guide future research, inform strategic decision-making and enhance the understanding of outsourcing dynamics in these rapidly evolving markets.

The advent of a dynamic and uncertain environment has shifted organizational focus from reactive to proactive approaches to develop resilience against disruptions. Organizations can strengthen their supply chain networks through strategic changes in structure and processes. In this connection, this study explores the extant literature on supply chain resilience (SCRE) concerning soft organizational factors (leadership, organizational culture and knowledge management) to analyse recent trends in this domain and propose future research directions.

It is a bibliometric analysis and systematic literature review of research articles from 2004 to 2024, collected from ISI Web of Science with keywords searches such as “knowledge management and supply chain resilience,” “leadership and supply chain resilience” and “organizational culture and supply chain resilience.” “VOS viewer” and “ATLAS.ti” were utilized for the co-occurrence and co-authorship analysis of the articles along with focusing on aspects such as theoretical and practical implications, the collaboration institutions and the countries involved in relation to the topic of interest.

The review shows that the development of studies on SCRE was slow from 2004 to 2015 but grew significantly from 2015 onwards and rose exponentially after 2020. Most studies were published in 2023. Results reveal the development of proactive strategies for SCRE in the recent literature by focusing on organizational factors. The study highlights exploring the contextual interplay between environmental, social and governance (ESG) and soft organizational factors for mitigation of supply chain risk and resilience in large-scale projects.

The COVID-19 pandemic became the precursor to highlighting the antecedents of SCRE, but the study of soft organizational drivers is still an ongoing area of research. There is a need to map the nascent literature on the link between organizational soft drivers and SCRE.

This study identifies and ranks the barriers to manufacturing integrated circuit (IC) chips in the Indian semiconductor manufacturing industry by examining the causal relationships between the different barriers using an advanced causal modeling technique named the grey influence analysis (GINA). Moreover, IC plays a crucial function in reducing the size, boosting the speed and improving the dependability of electronic devices. The widespread use of these technologies has led to advancements in sectors such as communications, healthcare, transportation and entertainment.

This study investigates 12 factors related to the barriers to manufacturing IC chips. In addition, experts from an Indian semiconductor manufacturing organization have validated the presence of these barriers. In addition, the research employs a novel GINA to investigate and comprehend the influence relationships between these barriers.

To successfully manufacture IC chips in India, the “Government Policies and Regulations (B11),” “Lack of Semiconductor Fabrication Facilities (B1)” and “Dependence on Imported Raw Materials and Components (B2),” were the critical barriers that must be addressed and overcome, as per the GINA result.

The author highlighted that a lack of fabrication plants could lead to limited production of the semiconductor chips and that a lack of local fabs can hinder the development of advanced technologies. The complex policy can significantly affect the set-up of new semiconductor fabs, hamper the overall growth of the semiconductor market and divert away foreign investors. This further creates restrictions on employment creation and undermines the economy.

Although semiconductor applications have several benefits, more research is needed to identify the barriers to manufacturing IC chips in India, making this study unique. In addition, the advanced GINA method is also used to examine the critical barriers and their interconnection based on an expert response-based study from an Indian semiconductor organization.

The purpose of this study is to evaluate and enhance sustainable manufacturing practices across various industries, focusing on environmental, economic and social dimensions, to promote a comprehensive understanding and implementation of sustainability, thereby improving overall industry performance and fostering long-term ecological and economic health.

The study uses multi-criteria decision-making-multivariate analysis technique to examine sustainable manufacturing practices (SMPs) in the Indian manufacturing sector. It identifies 11 SMP criteria through literature review and expert recommendations. Data are collected through questionnaires, expert committees and interviews. The study focuses on four key industries: automobile, steel, textile and plastic. Techniques like principal component analysis (PCA), technique for order preference by similarity to ideal solution (TOPSIS) and complex proportional assessment (COPRAS) are used to rank and assess performance.

The Indian automobile industry has shown the most effective SMPs compared to steel, textile and plastic sectors. The automobile sector is the benchmark for sustainable measures, emphasizing the importance of green practices for environmental, social and economic performance. Recommendations extend beyond the automobile sector to cement, electronics and construction.

The research emphasizes the importance of SMPs across various industries, focusing on economic, environmental and social considerations. It advocates for a holistic approach that enhances resource efficiency and minimizes ecological footprint.

The study uses ranking methods like PCA-integrated TOPSIS and COPRAS to evaluate performance in different industries, focusing on the benchmarked automobile sector. The research offers valuable insights and advocates for the widespread adoption of sustainable policies beyond the studied sectors.

The stormwater industry grapples with numerous environmental challenges resulting from producing and using storm materials. Green building materials (GBMs) offer a more ecologically friendly alternative to conventional construction materials. However, establishing criteria for selecting GBMs and assessing their sustainability has proven to be a complex endeavor. Therefore, this paper aims to assess the suitability of GBMs in stormwater management projects.

This study investigates and identifies the green storm drainage materials criteria based on previous literature and an extensive survey involving 140 stakeholders from the Egyptian industry, including facilities managers, asset managers, engineers and policymakers. A comprehensive model employing partial least squares structural equation modeling and artificial neural network is developed to assess the suitability of GBMs in stormwater management projects.

The study’s findings emphasize the pivotal role of social factors in the practical implementation of green material selection criteria. Understanding the intricate interplay among economic, environmental and social dimensions becomes crucial as stakeholders in the stormwater industry navigate the transition toward sustainable storm materials.

This research highlights the importance of integrating social factors into decision-making, contributing to more holistic and effective strategies for sustainable stormwater management. The study’s originality lies in its innovative approach to assessing the suitability of GBMs in stormwater management projects and its novel insights into the complex dynamics of sustainable materials selection, addressing a significant research gap in the field.

This research aims to identify and model metrics and sub-metrics that enhance sustainable performance measurement in agri-food supply chains.

The study evaluates five key metrics and 18 sub-metrics critical to this industry, establishing interrelationships among them to ensure a successful sustainable performance measurement system. The decision-making trial and evaluation laboratory technique was employed, integrated with fuzzy theory and expert opinions.

The findings suggest that metrics like information technology and organizational productivity, alongside the sub-metric of information integration, significantly contribute to sustainable supply chain performance.

This study proposes a performance measurement system that enables organizations to achieve optimal performance levels through a sustainable supply chain (SCC) and supply chain agility (SCA) framework, supported by digital technologies.

The growing pressure on businesses to balance environmental sustainability with profit maximisation has led to the development of green entrepreneurial orientation (GEO), which proactively integrates green practices into core business operations. Grounded in the ecological modernisation theory, GEO acts as a green management practice which helps in achieving competitiveness through environmental innovation. However, despite the growing emphasis on GEO, there remains a gap in understanding how specific drivers influence the organisational structures and processes that lead to GEO. Therefore, the study addresses this gap by analysing the key drivers of GEO using an integrated approach.

In this study, total interpretive structural modelling (TISM) and cross-impact matrix multiplication applied to classification (MICMAC) were used to identify and interpret the interrelationship between key drivers of GEO. Here, TISM technique aided in constructing a contextual relationship-based structural model of drivers, whereas MICMAC assisted in categorising the drivers based on their driving and dependence power. A case evaluation was also carried out in the Indian textile industry to validate the TISM model.

The result indicates that institutional pressure, managerial environment concern, organisational resilience and big data analytical capabilities are the most influential drivers of GEO at organisational level, and other drivers act as secondary and linked variables in this process. The MICMAC analysis further supports the results of TISM. In addition, the overall TISM model is validated in the Indian textile sector.

The study findings will assist researchers and policymakers in adopting a systematic approach to prioritise GEO in pollution intensive industries. Moreover, it will help managers in leveraging GEO to achieve strategic advantages amid environmental challenges.

This study is amongst the first to employ an integrated qualitative approach to analyse drivers of GEO.