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This study aims to present state-of-the-art research on circular economy (CE) implementation in construction and demolition waste management (CDWM) within the construction sector.

A mixed-method (scientometric and critical analysis) review strategy was adopted, involving scientometric and critical analysis to uncover the evolutionary progress within the research area, investigate key research themes in the field, and explore ten issues of CE in CDWM. Moreover, avenues for future research are provided for researchers, practitioners, decision-makers, and planners to bring innovative and new knowledge to this field.

A total of 212 articles were analyzed, and scientometric analysis was performed. The critical analysis findings reveal extensive use of surveys, interviews, case studies, or mixed-method approaches as study methodologies. Furthermore, there is limited focus on the application of modern technologies, modeling approaches, decision support systems, and monitoring and traceability tools of CE in the CDWM field. Additionally, no structured framework to implement CE in CDWM areas has been found, as existing frameworks are based on traditional linear models. Moreover, none of the studies discuss readiness factors, knowledge management systems, performance measurement systems, and life cycle assessment indicators.

The outcomes of this study can be utilized by construction and demolition sector managers, researchers, practitioners, decision-makers, and policymakers to comprehend the state-of-the-art, explore current research topics, and gain detailed insights into future research areas. Additionally, the study offers suggestions on addressing these areas effectively.

This study employs a universal approach to provide the current research progress and holistic knowledge about various important issues of CE in CDWM, offering opportunities for future research directions in the area.

This paper investigates strategies for addressing the global challenge of food loss and waste (FLW) within the food industry. It examines the relationship between corporate social responsibility (CSR) initiatives and state regulatory interventions for reducing FLW.

This mixed method study utilizes a unique panel dataset which includes the 150 largest food industry companies in Italy, Norway and the UK. It combines quantitative data analysis with qualitative insights derived from corporate strategies and corporate communications.

The analysis reveals that food companies with an established CSR strategy and in particular companies whose CSR reports highlight their environmental and social achievements are more likely to achieve in effective FLW reduction. Additionally, national-level regulatory interventions guided by European Union waste strategies act as pivotal benchmarks and encourage stricter corporate food waste management policies.

This research underscores the significance of CSR strategies and effective state regulation in the fight against FLW and offers policymakers and businesses valuable insights enabling development of robust strategies.

By emphasizing the interplay between CSR and regulatory intervention, this research contributes to the achievement of a more sustainable and efficient global food system that addresses both economic and ethical concerns and could have far-reaching societal and environmental implications.

The paper sheds light on the interplay between CSR initiatives and regulatory interventions for tackling FLW and emphasizes their synergistic impact on sustainable practices within the food industry.

In this case study, we examine how a citrus peel valorising company based in the Netherlands was able to adopt a circular business model while navigating regulatory, managerial, and supply chain-related barriers.

In-depth, semi-structured interviews with key personnel in the company, notes from field observations, photographs of the production process, and documents from a legal judgement served as data for this single, qualitative case study. Data were coded inductively using the in vivo technique and were further developed into four themes and a case description.

Results from our study indicate that the regulatory and political contexts in the Netherlands were critical to the company’s success. Like in the case of most fruitful industrial symbioses, partnerships founded on mutual trust and economically appealing value propositions played a crucial role in ensuring commercial viability. Collaborating with larger corporations and maintaining transparent communication with stakeholders were also significant contributing factors. Lastly, employees’ outlook towards circularity combined with their willingness to learn new skills were important driving factors as well.

In addition to expanding the scholarship on the adoption of circular business models, this research offers novel insights to policymakers and practitioners. It provides empirical evidence regarding the importance of public awareness, adaptable legislation, and harmonised policy goals for supporting sustainable entrepreneurship in the circular economy.

In the Global North, affordable housing has evolved and thrived, and it is now gaining traction in the Global South, where governments have been vocal supporters of the concept. Therefore, this paper aims to investigate the important criteria for selecting affordable housing units in Ghana.

A quantitative research approach was used, and a survey was administered to the residents. The data was analysed using both descriptive and inferential statistics. The relative importance index technique was used to rank the important criteria, and the EFA technique was used to create a taxonomy system for the criteria.

The hierarchical ranking of the most significant criteria for selecting affordable housing includes community safety, waste management and access to good-quality education. Furthermore, the important criteria for selecting affordable housing are classified into two groups, namely, “sustainability criteria” and “housing demand and supply and social service provision”.

This study has implications for the real estate industry and construction stakeholders, as this will inform decision-making in terms of the design of affordable housing and the suitability of the location for the development.

These findings provide a baseline to support potential homeowners and tenants in their quest to select affordable housing. Furthermore, these findings will aid future longitudinal research into the indicators or criteria for selecting suitable locations for the development of low- and middle-income housing.

This paper contributes to the field of public services’ performance measurement systems by proposing a benchmarking-based methodology that improves the effective use of big and open data in analyzing and evaluating efficiency, for supporting internal decision-making processes of public entities.

The proposed methodology uses data envelopment analysis in combination with a multivariate outlier detection algorithm—local outlier factor—to ensure the proper exploitation of the data available for efficiency evaluation in the presence of the multidimensional datasets with anomalous values that often characterize big and open data. An empirical implementation of the proposed methodology was conducted on waste management services provided in Italy.

The paper addresses the problem of misleading targets for entities that are erroneously deemed inefficient when applying data envelopment analysis to real-life datasets containing outliers. The proposed approach makes big and open data useful in evaluating relative efficiency, and it supports the development of performance-based strategies and policies by public entities from a data-driven public sector perspective.

Few empirical studies have explored how to make the use of big and open data more feasible for performance measurement systems in the public sector, addressing the challenges related to data quality and the need for analytical tools readily usable from a managerial perspective, given the poor diffusion of technical skills in public organizations. The paper fills this research gap by proposing a methodology that allows for exploiting the opportunities offered by big and open data for supporting internal decision-making processes within the public services context.

This study aims to address the critical challenge of implementing lean manufacturing (LM) in emerging economies, where sustainability complexities on the production floor hinder production efficiency and the transition towards a circular economy (CE). Addressing a gap in existing research, the paper introduces a path analysis model to systematically identify, prioritize and overcome LM implementation barriers, aiming to enhance performance through strategic removal.

The authors used a mixed-method approach, combining empirical survey data with literature reviews to pinpoint key LM barriers. Using the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) along with the Network Knowledge (NK) method, they mapped causal relationships and barrier intensities. This formed the basis for developing a path simulation algorithm, integrating heuristic considerations for practical decision-making.

This analysis reveals that the primary barriers to LM adoption is the negative perception and inadequate understanding of lean tools and CE principles. The study provides a strategic framework for managers, offering new insights into barrier prioritization and overcoming strategies to facilitate successful LM adoption.

This research provides a strategic pathway for overcoming LM implementation barriers, empowering managers in emerging economies to enhance sustainability and competitive advantage through LM and CE integration. It emphasizes the significance of structured barrier management in the manufacturing sector.

This research pioneers a systematic exploration of LM implementation barriers in the CE context, making a significant contribution to the literature. It identifies, evaluates barriers and proposes a practical model for overcoming them, enriching sustainable manufacturing practices in emerging markets.

Growing research attention has been given to both the circular economy and digitalisation in accounting research in recent years, but there are few studies exploring how digital tools are used to develop, analyse and respond to information for circular decision-making in industrial organisations. Therefore, this paper addresses how the data from digital technologies are leveraged in the aftermarket of an industrial firm for circular control.

The paper develops an analytical framework that is then used to frame the findings through a single case study of an international heavy equipment manufacturer for circular control.

The case provides examples of how digital technologies are used for circular control, framed within the analytical model as the key contribution. The study illustrates the different ways through which the accounting information from such technologies supports the service marketing function through circular control and the types of controls needed for this.

Managers in large industrial organisations should ensure customer-facing staff have adequate digital competences and knowledge of circular products and services for marketing, product design improvements and material recovery that can help decrease costs and improve customer satisfaction. The digital systems need to be integrated with upstream and downstream partners.

Understanding the transition towards increasingly circular product-service systems in industrial firms is important for current and future generations.

The originality lies in providing an empirical example of how digital technologies can be used to facilitate circular control and support the service marketing function in the aftermarket of an industrial firm.

The sustainability of the construction industry is associated with the productivity, profitability and competitiveness of the firms, which are significantly affected by inefficient site supervision and labour management approaches. This study aims to use a case study with mixed methods to evaluate the site supervisory characteristics in labour management, labour performance assessment and labour productivity measurement towards developing meaningful guidelines in polishing construction supervision attributes.

Well-developed modern apprenticeship elements were applied to 62 construction supervisors who were selected using the snowball sampling method, and their relevant competency characteristics were assessed using a comprehensively developed grading mechanism connected with useful training manuals/tools. Academic reviews, experts’ consultations and other meticulous mixed approaches were applied at different stages of the research plan’s sequential layout.

The mean performance scores of supervisors indicate proficient-level grades in the competency characteristics related to applying efficient labour management procedures and developing-level grades in designing productivity measurement tools, performing assessments on efficiency and productivity and proposing enhancement practices on efficiency and productivity for site operations. The findings point to a modern generalised guideline that establishes the ranges of supervisory attributes within the scope of the study. The validity, reliability, adaptability and generalisability of the findings were assured by using pertinent statistical tests and professional assessments.

Though the study’s conclusions/findings are primarily applicable to the construction environment of a developing country comparable to the Sri Lankan context, they will considerably impact current/future industrial practices in various other countries and emerging industries.

The research has produced a conceptualised modern tool that guides determining the capacity levels of supervisory attributes for carrying out labour management, labour performance assessment and labour productivity measurement aspects in construction. The research has opened a pump that inflows new values of highly workable supervision features for strengthening the site management structures and filling the industry’s knowledge vacuum in the methodical execution of apprenticeships.

Food waste is generated along the entire agricultural supply chain. From farm overproduction to lack of cold chain infrastructure, waste occurs for multiple reasons and negatively impacts the environment and society while generating economic losses. Although various supply chain actors and institutions have made attempts to reduce it, the activity is often confined to a single farm or to a retailer and charity dyad, without a systematic resolution of the problem. The environment is not only negatively impacted by the reduction of soil, water and biodiversity but also human beings suffer from malnutrition and food insecurity and finally, the entire supply chain faces considerable economic losses. Various supply chain actors have attempted to reduce this waste, but the results are often limited. The purpose of this paper is to consider systematic resolution by proposing a reconceptualisation from an alternative Operations and Supply Chain Management (O&SCM) perspective.

The proposed paper is problem-based research, which merges the research and industry perspectives derived from the authors’ field experience interviewing different supply chain stakeholders in Italy, the UK, the USA and France with an analysis of O&SCM literature related to food loss and waste.

In order to address the food waste problem, we propose a new perspective in dealing with food loss and waste through the lens of O&SCM. By reconceptualising O&SCM theories and methods with the unique aspects of food loss and waste and taking into account the multitude of stakeholders involved, we propose five research avenues.

The perspective of O&SCM management is missing when dealing systematically with food loss and waste, as researchers neglect its unique characteristics.

In this article, the authors draw-upon an extended unified theory of acceptance and use of technology (UTAUT) and propose a research model involving performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC) and competitive pressure (CP) as potential salient factors explaining the adoption of digitalization in European SMEs. The authors also postulate that there may be cross-cultural differences, thereby leading us to include the country as a moderator in the model.

The authors validate this model with a cross-cultural sample involving 188 owner-managers from the Czech Republic and Slovakia and through the partial least square structural equation modeling (PLS-SEM) techniques as well as multi-group analysis.

The results using the study’s global dataset indicate that PE, FC and CP significantly affect owner-managers intentions toward digitalization in SMEs. The authors’ application of the multi-group analysis also suggests that although the two countries differ in digitalization adoption intention, the differences are statistically insignificant. In the conclusion, the authors highlight several implications these findings have for theory and practice.

The authors recommend that the providers of emerging digital technologies should improve on the performance features of those technologies and ensure they are relevant to the SMEs. By doing so, the adoption of digitalization will grow, because owner-managers of SMEs will have the confidence that adopting such technologies will improve their operations. Second, SMEs are required to provide adequate organizational and technical infrastructure to support digitalization adoption.

Aside from being among the few attempts to extend the explanatory power of UTAUT with PE, EE, FC and CP in investigating digitalization adoption in SMEs context, this study also validates its model with rigorous methodological approach as well as three datasets (global, Czech Republic and Slovakia) thereby strengthening the validity of the results.