• Energy Research

Sustainable waste management (SWM) is an important goal for the plastic manufacturing industry, which is aiming toward enhancing its economic, environmental, and social sustainability in recent years. However, plastic manufacturing industries in developing countries like Bangladesh are yet to establish efficient SWM systems despite the amount of solid plastic waste continually rising across all sectors. This paper investigates the underexplored barriers to implementing SWM in the Bangladeshi plastic industry. First, it employs the Delphi method to identify the 16 most relevant barriers to SWM through a literature review and expert feedback. Then, using an integrated grey theory and decision-making trial and evaluation laboratory (DEMATEL) method-based framework, it evaluates these 16 barriers to examine their interrelationships in the context of emerging economies. The findings show that the five most significant barriers are as follows: lack of awareness of and knowledge about plastic waste disposal, lack of compliant waste management, lack of a sense of environmental responsibility on the part of manufacturers, lack of systematic waste collection and effective dumping-ground utilization and lack of proper environmental policies, legislations, and regulations. This study presents valuable insights that can deeply contribute to the literature on SWM, enabling scholars, policymakers, and industrial managers to practice sustainability more effectively in the plastic manufacturing industry.

Climate change is a significant risk multiplier and profoundly influences the transmission dynamics, geographical distribution, and resurgence of vector-borne diseases (VBDs). Bangladesh has a noticeable rise in VBDs attributed to climate change. Despite the severity of this issue, the interconnections between climate change and VBDs in Bangladesh have yet to be thoroughly explored. To address this research gap, our review meticulously examined existing literature on the relationship between climate change and VBDs in Bangladesh. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach, we identified 3849 records from SCOPUS, Web of Science, and Google Scholar databases. Ultimately, 22 research articles meeting specific criteria were included. We identified that the literature on the subject matter of this study is non-contemporaneous, with 68% of studies investing datasets before 2014, despite studies on climate change and dengue nexus having increased recently. We pinpointed Dhaka and Chittagong Hill Tracts as the dengue and malaria research hotspots, respectively. We highlighted that the 2023 dengue outbreak illustrates a possible shift in dengue-endemic areas in Bangladesh. Moreover, dengue cases surged by 317% in 2023 compared to 2019 records, with a corresponding 607% increase in mortality compared to 2022. A weak connection was observed between dengue incidents and climate drivers, including the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). However, no compelling evidence supported an association between malaria cases, and Sea Surface Temperature (SST) in the Bay of Bengal, along with the NINO3 phenomenon. We observed minimal microclimatic and non-climatic data inclusion in selected studies. Our review holds implications for policymakers, urging the prioritization of mitigation measures such as year-round surveillance and early warning systems. Ultimately, it calls for resource allocation to empower researchers in advancing the understanding of VBD dynamics amidst changing climates.

The recent geopolitical events, such as the conflict between Russia and Ukraine, have strained the available resources worldwide. In emerging economies like Bangladesh, which is heavily reliant on imported gas, oil, and coal, this has created a severe energy crisis. In response to the energy crisis and to support eco-friendly waste management, converting waste into energy is being recognized as a promising solution. However, introducing waste-to-energy systems in developing economies faces many intricate challenges that require careful examination. This study, therefore, aims to explore and evaluate the challenges associated with adopting a waste to energy (WtE) conversion system in emerging economies like Bangladesh. The research methodology involves identifying challenges from an extensive review of existing literature and expert feedback and then combining Bayesian theory with Best Worst Method (BWM) to evaluate the challenges. Among the 21 challenges analyzed, the ‘need for well-developed planning and incentivized policymaking’, ‘ineffectiveness in waste segregation at the source’, and ‘high cost for installation, maintenance, and infrastructure development’ appear to be the most significant challenges with weight values 0.071, 0.067, and 0.066, respectively. The study can enhance managers' understanding of the challenges faced by this sector and thus facilitate informed decision-making. The outcomes of this study are expected to enrich the existing body of knowledge, promote the diffusion of WtE technology in emerging economies, reduce dependency on the international energy market, and achieve global sustainable development goals (SDGs) such as affordable and clean energy (SDG 7), sustainable cities and communities (SDG 11), and climate action (SDG 13).

The emerging technologies of Industry 4.0 (I4.0) are crucial to incorporating agility, sustainability, smartness, and competitiveness in the business model, enabling long-term sustainability practices in the pharmaceutical supply chain (PSC). By leveraging the latest technologies of I4.0, pharmaceutical companies can gain real-time visibility into their supply chain (SC) operations, allowing them to make data-driven decisions that improve SC performance, efficiency, resilience, and sustainability. However, to date, no research has examined the critical success factors (CSFs) that enable the pharmaceutical industry to adopt I4.0 successfully to enhance overall SC sustainability. This study, therefore, analyzed the potential CSFs for adopting I4.0 to increase all facets of sustainability in the PSC, especially from the perspective of an emerging economy like Bangladesh. Initially, sixteen CSFs were identified through a comprehensive literature review and expert validation. Later, the finalized CSFs were clustered into three relevant groups and analyzed using a Bayesian best-worst method (BWM)-based multi-criteria decision-making (MCDM) framework. The study findings revealed that "sufficient investment for technological advancement", "digitalized product monitoring and traceability", and "dedicated and robust research and development (R&D) team" are the top three CSFs to adopt I4.0 in the PSC. The study’s findings can aid industrial practitioners, managers, and policymakers in creating effective action plans for efficiently adopting I4.0 in PSC to avail of its competitive benefits and ensure a sustainable future for the pharmaceutical industry.

Supplier selection is one of the most important multi-criteria problems in supply chain management (SCM). Most of the existing decision-making frameworks for selecting suppliers in the construction industry have given priority to criteria such as cost, delivery, and quality. However, due to the current emphasis on achieving sustainability and reducing environmental impact, organizations are increasingly embracing circular economy (CE) principles. In this study, thereby, we proposed an integrated multiple-criteria decision-making (MCDM) framework, which is comprised of a fuzzy analytical hierarchy process (FAHP) and a preference ranking organization method for enrichment of evaluations II (PROMETHEE II) for circular supplier selection in the construction industry from the perspective of countries with emerging economies. In the proposed framework, FAHP was used to first identify the weight of each criterion and sub-criteria, and PROMETHEE II was used to rank the suppliers from best to worst. Results showed that on-time delivery, conformance to specifications, and rejection rate are the top three criteria for supplier selection. Additionally, the top three circular supplier selection criteria included pollution control initiatives, green packaging, and responses toward environmental regulations and standards. The result of this approach has been compared with another MCDM method, namely the weighted aggregated sum product assessment (WASPAS) method, which validated the accuracy and efficiency of the proposed approach. Through the implementation of circular supplier selection, the proposed research is expected to reinforce the circular supply chain model, which can help managers in the construction sector to improve the sustainability of their overall business.

Floating Solar Photovoltaic (FSPV) plants have emerged as a promising solution, harnessing solar energy while utilizing water bodies effectively, especially for emerging economy countries with limited land resources like Bangladesh. However, selecting an optimal location for such a solar plant requires a comprehensive evaluation of multiple criteria. This research, therefore, proposes a multi-criteria decision-making framework that integrates the Fuzzy Best Wort Method (F-BWM) and Fuzzy Combined Compromise Solution (F-CoCoSo) method to determine the optimal location for establishing a floating solar photovoltaic plant in Bangladesh. Through literature review and expert validation, ten key criteria were identified for suitable site selection for FSPV. Relative weights of the identified evaluation criteria were calculated using the F-BWM method. Following that, the F-CoCoSo approach was employed to rank the eight alternative potential sites in Bangladesh based on the F-BWM weights. The F-BWM result indicates that solar irradiance, terrain elevation, and conflicts over water access are the three most significant factors in selecting the site for FSPV installation. F-CoCoSo results identified the Kaptai Lake, located in southeastern Bangladesh, and Barapukuria Coal Mine's Lake, located in northwestern Bangladesh, as the two most preferable sites for installing FSPV plants. The research findings are expected to help academicians, policymakers, energy planners, and investors by offering a nuanced understanding of the significance of various technical, environmental, and social criteria for FSPV installation projects. Additionally, it offers a robust framework for site selection that enhances the efficiency, sustainability, and feasibility of FSPV projects in Bangladesh.

Changing customer demand, globalization, pandemics, and the ongoing Russia-Ukraine war have introduced a lot of complexities, uncertainties, risks, and challenges in various global businesses, especially in the small and medium enterprises (SMEs) of emerging markets. This sector plays a significant role in fostering economic growth, generating employment, and reducing poverty. In such a situation, proper identification of supply chain risk (SCR) factors is pivotal for this sector to achieve a resilient and sustainable SC, specifically since a sustainable and resilient supply chain can withstand the impacts of various uncertain situations. However, no studies have yet explored these risk factors from an emerging economy perspective. This study fills this research gap by identifying the SCR factors and analyzing their interactions using an integrated approach, including Pareto analysis, fuzzy theory, total interpretive structural modeling (TISM), and a Matriced' Impacts Cruoses Multiplication Applique a un Classement (MICMAC) analysis. The findings from the fuzzy TISM imply that the “lack of enthusiasm in top management regarding sustainable practices” is the most significant factor. Besides that, lack of skilled and educated workers, lack of knowledge about modern technologies, labor strikes, and political instabilities are also some crucial risks that may hinder the sustainable development and smooth operation of SMEs. Fuzzy MICMAC analysis confirms that all identified risk factors are interrelated. The study insights can guide managers to successfully identify the risk factors for achieving long-term sustainability and operational resilience and can enhance policymakers’ ability to formulate proactive and efficient mitigation strategies.

The heavy reliance of the transportation and power generation sector on fossil fuels is seriously impacting the environment. Transitioning towards more sustainable transportation modes is necessary to reduce this dependency on fossil fuels. Even though shifting toward electric vehicles (EVs) can reduce harmful emissions, due to the lack of adequate charging infrastructures, underdeveloped power transmission systems, and increased cost of power generation, it is difficult for a developing country to adopt and rely heavily on EVs. However, developing countries like Bangladesh can adopt a different strategy to address this issue. Harmful emission reduction is also possible by transitioning from conventional internal combustion engine (ICE) vehicles to hybrid electric vehicles (HEVs). The drivers that can promote the expansion of HEV adoption have not been extensively studied to date, which inspired the proposed study. This study explores the drivers for the growth of HEV adoption in emerging economies. First, the study identifies seventeen drivers from the literature review and expert feedback. Then the identified drivers were assessed using the Bayesian Best-Worst method (BWM). The study findings indicate that no requirement for a charging station, incentivizing consumers through policy measures, and enhanced fuel efficiency are the top three drivers influencing the growth of HEV adoption in developing or emerging economies. This study can help the decision-makers and end users in developing counties to gradually shift towards a low-carbon emission-based economy and ensure a greener and more sustainable future.