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Several waste bin sanitation initiatives have been introduced in Ghana to address the surge in indiscriminate solid waste disposal in households. What is not known are the behavior factors that determine the acceptability and use of waste bins. This study aimed to identify the determinants of waste bin acceptability and use in Ghana using the theory of planned behavior (TPB).

Data on waste bin acceptability and usage were collected from 881 households in the Volta and Oti regions of Ghana. The data were analyzed using the partial least squares-structural equation modeling technique in SmartPLS 3 software.

The coefficient of determination (R-squared value) of the original TPB and the extended model explained 39.9 and 44.7% of the variance in waste bin acceptability and use intentions, respectively. The results revealed that attitudes (ß = 0.114, t = 3.322, p < 0.001), subjective norms (ß = 0.306, t = 6.979, p < 0.001) and perceived moral obligation (ß = 0.352, t = 8.062, p < 0.001) significantly predicted household waste bin acceptability and use behavior intentions, but perceived behavioral control (ß = −0.003, t = 0.064, p < 0.949) did not influence behavior intentions significantly.

The study provides valuable insights into the behavioral factors to be prioritized by waste management service providers to improve household waste bin acceptability and usage.

This is one of Ghana's first studies investigating the behavioral determinants of waste bin acceptability and usage.

This study aims to develop an overall project success (OPS) model by investigating the mediation impact of value management (VM) implementation between VM critical success factors (CSFs) and OPS as well as the moderation impact of VM CSFs between VM implementation and OPS.

In total, 335 structured questionnaires were administered to relevant stakeholders in the study area. The research used a partial least square structural equation modeling (PLS-SEM) to model the relationship among VM implementation, CSFs and OPS.

The results revealed that there is an indirect positive and significant correlation among the variables. The model prediction analysis also significantly impacted with 59.9% on OPS by setting VM implementation as a mediator variable and 61% by setting VM CSFs as a moderation variable.

This research work will serve as a guide or benchmark for decision-makers who want to use VM to improve the success of their building projects.

This study fills the knowledge gap by identifying and emphasizing the impact of VM CSFs and activities on OPS.

This study aims to identify the most significant barriers and the stationary barrier to modular construction (MC) implementation and promote MC widespread use. By doing so, the construction industry can leverage the benefits of MC, such as faster construction times, improved quality control, reduced waste and increased sustainability.

This study uses a Gini’s mean analysis approach to identify the stationary barriers hindering the MC adoption in residential projects. The research focuses on the Egyptian context and uses a questionnaire survey to gather data from professionals in the construction industry.

According to the survey findings, the top five significant MC barriers are inability to modify the design; contractors asking for high bidding prices (higher initial cost); scepticism, conservation and resistance of clients to innovation and change; transportation restrictions; and lack of a one-size-fits-all tool for the design. In addition, Gini’s mean of dispersion demonstrated that the stationary barrier that faces MC adoption is the apprehension that architectural creativity will suffer because of MC.

The identified obstacles could be useful for decision makers in countries that have not yet adopted MC and may aid in the planning process to manage the risks associated with MC projects. The paper stresses the significance of devising techniques to overcome these barriers and proposes several methods to tackle these challenges.

This study fills the knowledge gap by identifying the stationary barrier and emphasising the potential risks associated with MC barriers. Furthermore, it suggests several strategies for overcoming and reducing these barriers in developing countries residential projects.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

In many societies, environmental problems have had some negative impacts on both social and economic features with issues like capital structure seriously affected. In this write-up, an attempt has been made to pinpoint the influence of the combined effects of integrated reporting and financial leverage on the value of a firm. In most emerging markets, investment is heavily dependent on foreign capital inflow which is mainly in the form of financial leverage. It is, therefore, necessary to know how this shapes the net worth of firms in which they are invested. Shareholders' fund is a major factor in determining the level of investment and economic stability of a nation and consequently improvements in sustainable development. Hence, the moderating role of financial leverage in the integrated reporting-shareholders’ funds relationship aims to warrant this research.

All listed firms on the Nigerian Stock Exchange (NSE) as of 31st December 2021 were affected by this research. Filtering resulted in the use of 77 companies as a sample for the study covering a period of 12 years (2010–2021) with a total of 788 observations. Analyses of data were done through line graphs to show the trend and flow of disclosures between 2010 and 2021. Furthermore, linear regression was also applied to help determine the multiple effects of financial leverage and integrated reporting on shareholders' funds.

The outcomes showed that economic disclosure was 100% throughout the period of observation as opposed to environmental and social disclosures which, fluctuate throughout the period with an average of slightly over 55%. It was also discovered that a low but significant financial leverage moderated the interaction of integrated reporting on shareholders' funds.

Stakeholders and policymakers should, therefore, put in place rules, regulations, standards, structures and administrative networks to enable firms to comply with local rules, guidelines and upgraded standards of international worth on sustainability issues.

This research explores the problem of the effects of integrated reporting on investment capital as it affects developing economies. Results from this study could go a long way in narrowing the lack of interest in sustainability issues by prospective investors coupled with the low level of environmental and social reporting by firms in African economies that are mostly underdeveloped.

The purpose of this study is to examine the impact of country-level governance on sustainability performance, taking into account the effect of sustainable development goals (SDGs) and board characteristics.

This study uses panel data analysis using fixed effect models to investigate the influence of country-level governance on sustainability performance while considering the effect of SDGs and board characteristics. The sample comprises 8,273 firms across 41 countries during the period spanning from 2016 to 2021. The sample is divided into two categories based on the score of SDGs.

The findings of this study show that countries with high SDGs score have better overall country-level governance and board attributes which have a statistically significant positive impact on sustainability performance. However, for those countries with low SDGs, political stability shows a statistically insignificant and negative impact on sustainability performance, while government effectiveness indicates a statistically insignificant positive impact on sustainability performance.

This study contributes to the literature by providing empirical evidence on the relationship between country-level governance, SDGs, board characteristics and sustainability performance. The study also highlights the importance of considering the effect of SDGs on the relationship between country-level governance and sustainability performance. The findings of this study could be useful for policymakers and firms in improving their sustainability performance and contributing to sustainable development.

This study aims to investigate the relationship between management support, quality infrastructure, staff training and the effectiveness of quality enhancement cells (QECs) established in higher education institutions.

Data were acquired via a structured questionnaire dispatched to faculty members across 12 public and private universities, primarily situated in Punjab, Pakistan. Among the 200 questionnaires distributed, 180 were retrieved and 140 were deemed valid. The proposed relationships were examined using SPSS–25 and PLS–SEM.

The results show a positive and significant relationship between management support, quality infrastructure and staff training with QECs' effectiveness. The study also highlights that the effectiveness of QECs is “Good” in only two of the 12 universities, while in most universities it is “Barely Acceptable”. Furthermore, QECs' effectiveness is slightly better in public universities compared to private institutions.

The study employs convenience sampling and a cross-sectional approach, focusing on faculty members from 12 universities, primarily in Punjab, Pakistan. To enhance future research, larger samples and probability-based sampling should be considered, while involving quality managers and students for a broader perspective.

The research suggests policymakers and university leaders should strengthen their support by providing resources, quality infrastructure and training for academic and administrative staff. This would enhance the effectiveness of QECs and improve the overall quality of education in both public and private universities.

This study contributes to the literature on quality assurance in higher education by emphasizing the significance of QECs concerning management support, quality infrastructure and staff training – areas that are often overlooked in Pakistani universities.

In less than a decade to Sustainable Development Goals, the urban solid waste (USW) emanating from households, especially in developing countries, calls for concern. Several policies have been suggested and some implemented, but the challenges facing USW management remain, especially in developing nations. Past studies demonstrated that the fourth industrial revolution (4IR) technologies can be used to improve urban public services. The role of 4IR in mitigating the challenges of USW is yet to receive in-depth research in Nigeria. Thus, the study investigated 4IR role regarding mitigating the challenges facing USW.

Seven cities across Nigeria, including the Federal Capital Territory, were used as the study area to achieve the research objectives via a qualitative research design. Thirty-two semi-structured interviews were conducted from selected regulators, households, legislators, ICT experts, NGOs and waste managers. A thematic approach was adopted to analyse the collated data.

Findings group the USW challenges into five categories. The 4IR technologies can be used to manage USW; thus, they create an opportunity to integrate and promote sustainable clean cities.

This study is confined to the 4IR role concerning mitigating the encumbrances facing USW in Nigeria and proffered feasible policies to enhance a sustainable healthy environment.

Proffered policy solutions will stir policymakers and construction practitioners to think outside the box and offer and better understand how 4IR technologies can be utilised to mitigate those challenges. The outcome will create sustainable clean cities as part of the implication contribution to the body of knowledge.

Evidence from the reviewed literature shows a paucity of literature focussed on 4IR roles in mitigating the encumbrances facing USW in Nigeria. Therefore, this study contributes to the existing research work on 4IR concerning its role in enhancing USW in Nigeria and, by extension, to other developing countries.

A prime objective of the Swachh Bharat Abhiyan (SBA; Clean India Mission) is to motivate people to segregate their household waste. The purpose of this study is to assess the ground reality of waste management behaviour of Delhi residents with the help of a modified Value–Belief–Norm (VBN) model. Past researches point the need to include cost as a variable in the VBN model. This study fulfils this need and tests cost as one of the variables on the gathered data.

The research data were gathered by interacting with the people and the civic staff in the jurisdiction of the three Delhi municipalities through a stratified sampling technique (N = 250). The structural equation modelling was used to analyse the collected data.

The modified VBN model explains the waste management behaviour, but the variables do not follow the exact causal chain. Values, awareness of consequences, ascription of responsibility and personal norms all explain the resident's waste management behaviour. However, cost limits the resident's waste management behaviour.

The study could only achieve a moderate model fit; its sample size was small; and data were collected through self-reported questionnaire.

Three main practical implications of the study are: (1) While designing waste management solutions, due importance must be given to the cost to be borne by people for adopting these solutions. (2) Design such interventions that target residents' values to convince them to make the desired behavioural change. (3) People need be educated about the ways to sort waste and made aware of the importance of waste segregation in eradicating the urban waste mess.

The paper is an original contribution to testing a modified VBN model in predicting waste management behaviour. The modified model includes cost as a variable missing in the previous research. This research is useful in the backdrop of the SBA and provides suggestions for policymakers and pro-environment researchers.

Using bibliometric, this work aims to evaluate the current status of the body of research on the subject of supply chain resilience (SCR) in developing nations and to provide recommendations for potential lines of inquiry for additional research.

Three hundred and thirty-six articles published between 2011 and 2021 were retrieved in Scopus for this bibliometric analysis. This analysis focuses on SCR research conducted in developing countries, highlighting its key authors, countries, institutions, journals, articles and themes.

This bibliometric review seeks to enrich the discourse on SCR in developing nations through a comprehensive and detailed review of 336 articles covering 138 Journals, 73 countries, 877 authors, 743 organizations and 1,145 author keywords. The United Kingdom, India, and the United States provided a substantial share of the publications. Publication-wise, Hong Kong Polytechnic University and The University of Hong Kong play key roles. The author found that supply chain risk management, sustainability, agile management, artificial intelligence and blockchain are trending topics. Additionally, the author identified eight themes by page rank analysis.

This study's importance lies primarily in its examination of the current information about SCR in developing countries and significant cluster areas (themes). In the paths, it recommends for further study, which academics may take, and industry professionals should apply in their businesses to create a more resilient and sustainable supply chain.

Based on published studies, this study gives exploratory data on SCR in developing countries context. This is first of its kind bibliometric study that focuses on developing countries.