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The escalating volume of electronic waste (e-waste) presents a significant environmental and health hazard, emphasizing the importance of promoting e-waste recycling. Therefore, this study aims to utilize a valence theory approach to comprehensively understand the factors influencing individuals' intention to recycle e-waste.

A survey-based research approach was employed to examine the factors influencing consumers' e-waste recycling intention. Data were collected through an online survey questionnaire from Malaysian individuals aged 18 and above. The hypotheses were tested using a sample of 300 respondents, employing partial least squares structural equation modeling as a symmetric analysis technique. Additionally, fuzzy-set Qualitative Comparative Analysis (fsQCA), an asymmetric analysis approach, was used to gain deeper insights. Non-probability purposive sampling was utilized in the sampling process.

The PLS-SEM analysis revealed that subjective norms and willingness to change significantly impact e-waste recycling intention. Furthermore, perceived convenience, environmental concerns and social media usage were found to support the intention to recycle e-waste. The fsQCA results enhanced the interpretation by uncovering intricate relationships among the antecedents and identifying specific configurations that accurately predict consumers' recycling intentions.

The practical implications of this study emphasize the need for policymakers and practitioners to raise awareness regarding the benefits of e-waste recycling, enhance convenience in the recycling process and strengthen personal and subjective norms to encourage individuals to recycle their e-waste.

This study's originality lies in its adoption of a valence theory framework to comprehend the intentions behind e-waste recycling, as well as its inclusion of control variables during the analysis. This unique approach enhances the understanding of factors influencing e-waste recycling intention and provides valuable insights for policymakers and practitioners in developing effective strategies to promote e-waste recycling behavior.

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.

In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.

The preferences and adoption of recycled materials by consumers are subject to a variety of factors, such as enablers and barriers. Despite this, there exists a paucity of research concerning stakeholders' perceived value and real purchase decision towards recycled products. Consequently, this research study aims to fill this gap by investigating stakeholders' perceived value of recycled products derived from construction and demolition (C&D) waste and its effect on purchase decisions.

Research data were collected from 219 valid questionnaires completed by Chinese stakeholders. Structural equation modeling (SEM) was then employed to test eight hypotheses.

The results show intrinsic cue (materials) and extrinsic cue (brand) influence the stakeholders’ judgment on C&D waste recycled products’ value and then their purchase intention. However, cues such as quality, word-of-mouth, price, policy and advertised have not play a significant role in practice.

This research study verified the significance of brand and material cues on decision making for purchasing C&D waste recycled products, providing new insights to policy making to enhance the uptake of C&D waste recycled products in construction industry.

Circular economy (CE) is guided by principles, the key being the R-framework. All R-frameworks have a hierarchy. Although several studies have prioritized these principles, there is still an urgent call for country-specific prioritization. This study prioritized circular economy (CE) principles among Ghana's built environment (BE) professionals.

An explanatory sequential mixed methods approach was adopted. Six principles of CE were identified through a review of related literature and incorporated into a questionnaire. In total, 162 questionnaire responses were received. The quantitative data were analyzed through descriptive and inferential analyses. The data were further validated via semi-structured interviews with eight interviewees of different professional backgrounds in the BE.

The findings revealed that BE professionals in Ghana highly perceived CE principles as important. The findings further revealed the order of prioritization of the CE principles as follows: (1) recycle, (2) reuse, (3) repair/remanufacture, (4) renewable energy usage, (5) redesign and (6) reduce. To further elaborate on these prioritized principles via the qualitative phase, the interviewees agreed to and confirmed the importance of the identified principles through their verbatim comments.

Although there is a growing interest in research regarding CE in the Ghanaian construction industry, its principles have yet to be prioritized and ranked by professionals in the Ghanaian construction industry. This study unearths why, in terms of prioritization of the CE principles, the construction industry in Ghana does not follow the well-known hierarchy (i.e. reduce, reuse and recycle) in the order of high to low level of circularity.

The main objective of the quantitative study is to ascertain the relationship between the circular economy (CE) and carbon emissions. And also, the study examines the threshold beyond which the quality of governance reduces carbon emissions.

The autoregressive distributed lag approach is employed for the econometrics analysis. The study employed quarterly data from 2006Q1 to 2017Q4 on Ghana.

The results indicated that, although the CE had a positive and significant effect on carbon emissions, the moderating term had an adverse and significant effect on carbon emissions. This result suggests that to mitigate carbon emissions, a robust and efficient quality of institutions should be sustained. Finally, the study also identified a quality of governance threshold of 1.155 beyond which a shift to a CE would result in a reduction in carbon emissions.

The study recommends that policymakers should initiate policies that would enhance quality governance.

The main contributions of the study are that the paper ascertained the threshold beyond which quality of governance assists circular economic practices to mitigate carbon emissions. Also, the study revealed that quality of governance is a catalyst to promote circular economic practices in reducing carbon emissions. Finally, the study ascertains the long-run effect of the variables of interest on carbon emissions.

Sustainability is a major challenge for India’s (Bharat’s) coal mining industry. The government has prioritized sustainable growth in the coal mining industry. It is putting forth multifaceted economic, environmental and social efforts to accomplish the Sustainable Development Goals (SDGs). This research aims to identify the factors for sustainable improvements in coal mining operations. Secondly, this study examines the intensity of causal relations among the factors. Thirdly, this study examines whether causal relations exist among the factors to be considered for sustainable improvement in coal mining operations. Lastly, the study aims to understand how the factors ensure sustainable improvement in coal mining operations.

An integrated three-phase methodology was applied to identify the critical factors related to coal mining and explore the contextual relationships among the identified factors. Fifteen critical factors were selected based on the Delphi technique. Subsequently, the fifteen factors were analyzed to determine the contextual and causal relationships using the total interpretive structural modelling (TISM) and DEMATEL methods.

The study identified “Extraction of Coal and Overburden” as the leading factor for sustainable improvement in coal mining operations, because it directly or indirectly influences the overall mining operation, environmental impact and resource utilization. Hence, strict control measures are necessary in “Extraction of Coal and Overburden” to ensure sustainable coal mining. Conversely, “Health Impact” is the lagging factor as it has very low or no impact on the system. Therefore, it requires fewer control mechanisms. Nevertheless, control measures for the remaining factors must be decided on a priority basis.

The proposed structural model can serve as a framework for enhancing sustainability in India’s (Bharat’s) coal mining operations. This framework can also be applied to other developing nations with similar sustainability concerns, providing valuable guidance for sustainable operations.

The current study highlights the significance of logical links and dependencies between several parameters essential to coal mining sustainability. Furthermore, it leads to the development of a well-defined control sequence that identifies the causal linkages between numerous components needed to achieve real progress towards sustainability.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

The paper aims to explore the model of circular economy for promotion of principles of social inclusion, empathetic governance, and economic sustainability environmental resilience by examining the research gap on how to employ Environment, Social and Governance (ESG) framework, principles of biomimicry and reimagining an economic model of resourcefulness.

The paper is a descriptive study based on review of literature. To analyse the research gaps, paper employs bibliometric research technique, well-accepted meta-analytical research of literature to find overlapping factors of relevance by examining most-cited authors, papers, as well as co-citation patterns (Kim, 2008). The method analyses the published data texts, information like authorship, citations, keywords, and illustrating linkages between and among articles about certain research topic (Fetscherin, 2012).

Data were sourced from collection archival database of JSTOR, Web of Science and J-Gate till December 2022, by searching with following string – “Circular Economy,” “ESG (Environment, Social and Governance),” “Biomimicry,” “Circular Economy and ESG,” “Circular Economy and Biomimicry,” “Circular Economy and Resourcefulness.” The selection of said string of words was based on the literature review, overlaps and the research questions formulated. The findings reflect common factors of overlaps and its coherence in domain of policy formulation for the circular economy.

The research approach needs to be tested for practical application with stakeholders which includes individual-community for necessary behavioural change/acceptance, policy measures, innovations for scalability and the new business models so that the changes become an integral part of DNA of new economic model.

Emphasis on reimagined alliance between the environment, economy, and society to achieve the triple bottom line for a sustainable future. In doing so mitigate the impact on nature, generate livelihood opportunities and institute a green industry with an emphasis on circularity by incorporating the principles of ESG, biomimicry and resourcefulness.

The paper addresses the developing frontier of circular economy by identifying and mapping the factors of overlap with principles of ESG and biomimicry with circular economy for a future which is sustainable and resourceful. It attempts to advance the domain of knowledge with suggestion for implementable policy initiative arising from the study.