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This paper aims to develop a grey decentralized bi-level multi-objective programming (MOP) model. A solution approach is also proposed for the given model. A production and transportation plan for a closed loop supply chain network under an uncertain environment and different scenarios is also developed.

In this paper, we combined grey linear programming (GLP) and fuzzy set theory to present a solution approach for the problem. The proposed model first solves the given problem using GLP. Membership functions for the decision variables under the control of the leader and for the goals are created. These membership functions are then used to generate the final solutions.

This paper provides insight for fomenting the decision-making process while providing a more flexible approach in uncertain logistics problems. The deviations of the final solution from the individual best solutions of the two levels are very little. These deviations can further be reduced by adjusting the tolerances associated with the decision variables under the control of the leader.

The proposed approach uses the concept of membership functions of linear form, and thus, requires less computational efforts while providing effective results. Most of the organizations exhibit decentralized decision-making under the presence of uncertainties. Therefore, the present study is helpful in dealing with such scenarios.

This is the first time, formulation of a decentralized bi-level multi-objective model under a grey environment is carried out as per the best knowledge of the authors. A solution approach is developed for bi-level MOP under grey uncertainty.

This study aims to investigate the determinants of localised corporate social responsibility (LCSR) activities in Pakistan. The present study explores factors influencing the corporate sector to promote the welfare of local areas where the company has located its manufacturing plants.

The authors selected 100 companies listed on the Pakistan Stock Exchange. Data were collected from the companies’ financial reports issued from 2012 to 2017 (N = 700). The authors analysed the data using fixed- and random-effects regression models to test the factors influencing LCSR activities.

The findings indicate that directors’ ancestry significantly enhances LCSR. This implies that boards with a greater number of directors whose names indicate their relevant ancestry are more likely to engage in LCSR. Moreover, environmental-protection activity by the corporate sector promotes LCSR initiatives. However, Pakistan’s corporate sectors are not promoting the essential aspects of their workers’ welfare, e.g. health and education.

The present study was limited to the directors’ ancestry, environmental corporate social responsibility (CSR), CSR for factory workers and donation. Other factors, such as culture and language, may play an important role in determining LCSR.

The results suggest that the Security and Exchange Commission of Pakistan should emphasise the importance of LCSR to develop rural areas and devise meaningful policy for CSR. These findings provide substantial evidence that regulators and policymakers should encourage the inclusion of LCSR by firms listed on the stock exchange to increase environmental protection through CSR policy.

To the best of the authors’ knowledge, this study is the first to explore the determinants of LCSR. Moreover, the present study investigates for the first time the influence of directors’ ancestry on rural development in any of Asia’s developing countries, including Pakistan. The findings of this study contribute theoretically and empirically to the literature.

The existence of intense competition in turbulent markets confirms the importance of using ethical employee practices in knowledge sharing behaviour (KSB) to ensure organisational growth. This is especially applicable in developing countries' markets where this intensive competition usually results in organisations following illicit practices. This paper aims to examine the relationship between the Big Five personality traits (i.e. openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) and KSB using Islamic work ethics (IWE) as the moderator.

A quantitative research method using a survey instrument collected 182 responses from employees in the Pakistani telecommunication industry. The partial least squares structural equation model (PLS-SEM) was used to analyse the collected data.

The results found that IWE has a positive impact on KSB and a positive moderating impact on the relationship between the Big Five personality traits except neuroticism and KSB. Also, openness to experience and agreeableness positively impacted KSB.

This paper contributes to the field of human resource (HR) management by helping managers in the hiring process or developing employee's personalities. Additionally, policymakers are encouraged to create Islamic values platforms to increase KSB amongst employees.

This study indicates the importance of IWE in boosting the impact of personality on KSB and provides insights into IWE's role in enhancing an organisation's competitive advantages in turbulent markets.

Human-induced changes in climate have affected the environment to the extent that any more economic development at the cost of the environment will be too costly. Thus, sustainable development options posing no additional harm to the environment are the only viable option. This study aims to examine the likely environmental impacts of infrastructural developments through the China–Pakistan Economic Corridor (CPEC).

There is a scarcity of academic debate and discussion on the environmental impact of CPEC developments in laws and policies on the environment. The qualitative approach is followed in this study and official documents and reports are used to investigate the environmental challenges posed by CPEC.

The findings show three possible environmental concerns which could increase the climate change vulnerability of Pakistan. The coal-fired power plants are the most prominent threat based on their CO₂ contributions and smog. Second, cutting more than 54,000 trees for roads infrastructure will increase CO₂ concentration along the CPEC route. Third, increasing vehicle trafficking by up to 7,000 trucks per day on Karakorum Highway alone will release 36.5 million tons of additional CO₂.

It is essential to rethink the environmental cost of CPEC. The study suggests economic and legal cooperation between Pakistan and China as a way forward to deal with climate change issues. Environmental laws should be a vital part of CPEC projects to ensure their safety, security and sustainability.

The coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.

To conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.

The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.

This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.

To the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.