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This paper aims at developing a multi-objective mathematical model of circular economy that integrates key concept of leasing as a strategy in addition to reuse, refurbishing, primary recycling, secondary recycling and disposal.

This paper proposes multi-objective fuzzy mixed integer linear programming mathematical model considering multi-product, multi-echelon and multi-capacitated concepts of the circular economy. The three objectives of the proposed model, namely, economic, environmental and social are solved simultaneously using constraint approach to obtain balanced trade-off between the objective functions. The model is validated by solving a case study from the literature. The proposed model is made pragmatic for industrial application by considering multi-external suppliers multi-customer zones, multi-disassembly centers, multi-collection centers and multi-refurbishing centers and accounting for purchasing, processing, transportation, set-up costs and capacity constraints at the same time.

The results show that the leasing of the products improves the economic function in addition to the known environmental improvements. The proposed model also shows that the circular economy can generate the jobs for the unskilled people at different locations.

The proposed model can be further improved by considering the non-linearity due to economy of scale at various centers and in transportation. The model can be further extended to make it multi-period model.

The proposed model of circular economy can be used by the organizations as a policy tool to decide the optimum number of collection centers, disassembly centers, refurbishing centers, recycling centers and disposal centers and their optimum locations and allocations. The organizations can also trade-off among economic, environmental and social benefits of their proposed decisions in circular economy.

The originality of the proposed mathematical model is consideration of leasing as a strategy to have better control over the supply chain for circularity; considering the training of unskilled people for backward supply chain jobs and accounting for primary recycling and secondary recycling separately for economical computation.

This study aims to propose and apply a sustainability assessment model (SAM) for the mineral extraction industry developed on the basis of elements of dialogic accounting.

Distinct from other similar exercises, ours is also one in external accounting that focuses on a set of mining companies operating in a specific geographical location. It was undertaken based on different perspectives from various stakeholders, including mining workers and city dwellers, retrospectively, using publicly available information, entirely independently of the set of companies regarding which impacts the authors try to offer an account and without their approval. Twenty indicators were identified from the perspective of value for society.

The results for all environmental externalities appeared to be negative, as companies’ attitudes continue to be reactive and on the threshold of legal requirements. This assessment of the selected social indicators emphasizes that accelerated expansion of mining activities poses a threat to the mining area in the long term, as it reduces the useful lives of mineral deposits and expands social and environmental externalities.

The authors propose to expand the horizon of accounting through a framework that combines elements of the SAM technology, dialogic accounting and external accounting. This investigation contributes to the development of social and environmental accounting practices through the discussion, proposal and use of an SAM, built with the cooperation of several social actors and from the perspective of the other rather than the entity.

The authors tried to show how an SAM approach can be used in combination with dialogic accounting processes, increasing the accountability and awareness of the different groups of stakeholders, focusing on marginalized stakeholders, to offer an external account of the impacts of a set of companies from the mining sector operating in a specific geographical area.

This study’s findings suggest there are opportunities for accountants to support social and environmental accounting, thereby contributing to community awareness and empowering transformative action.

This study proposes an assessment framework for improving smart building performance in the broader context of smart city development, considering dimensions like environmental sustainability, building characteristics, intelligence, computation management and analytics. The framework is crafted to guide future research, aligning with the growing emphasis on sustainability and intelligence in evolving urban landscapes within smart cities.

In the initial phase, the concepts of “Smart City” and “Smart Buildings” are analyzed through a systematic literature review, considering the impact of governance on city sustainability and growth, along with the role of public policies in transforming buildings and cities. The empirical research evaluates innovation levels in small and medium-sized European cities, proposing a new framework with validated dimensions and sub-dimensions. This validation involves input from international experts through a Focus Group.

The key research findings validate the new proposed assessment framework for smart buildings within smart city development. The experts’ insights align with and support the dimensions identified in the bibliographic research, providing a comprehensive understanding of the role of smart buildings in sustainable urban development.

This framework not only provides insights for a new model with specific dimensions and sub-dimensions but also serves as a guide for formulating strategies and policies to enhance innovation in these settings. The value of this approach is strengthened by the validation and consolidation process involving international experts in the field.

Entrepreneurship education (EE) through innovative teaching techniques (ITEE) and entrepreneurial intention (EI) are two essential components of entrepreneurship development. Using the assumptions of the Theory of Planned Behavior (TPB), we took three constructs: attitude (ATT), subjective norms (SUBNs), and perceived behavioral control (PBC), and from the assumption of Human Capital (HC) theory, we constructed another variable, ITEE. Thus, the fundamental objective of this study is to find out the essential predictor of EI between entrepreneurial antecedents (ATT, SUBNs, PBC) and ITEE through an artificial neural network (ANN).

Using the snowball sampling technique, a highly structured questionnaire was sent to respondents. Finally, a sample size of 397 business graduate students was chosen.

The findings revealed that two dimensions of entrepreneurial antecedents (attitude and subjective norm) positively impacted EI. Furthermore, ITEE partially mediated the relationship between two dimensions of entrepreneurial antecedents (attitude and subjective norm) and EI. Moreover, through ANN, we found that attitude (ATT) was a crucial predictor of EI among business graduate students in Bangladesh.

In this study, only business graduate students were included as respondents; thus, further research should include students from other departments or disciplines to generalize the findings.

This study covers numerous actors in terms of practical contributions, including students, academics, the government, and the state. This article should draw the attention of Bangladesh government policymakers regarding the significance of ITEE for developing entrepreneurship. The research framework of this study proposed that ITEE should implement antecedents of entrepreneurship into business education, boosting the ability of students to make judgments, which will also enhance EI in the future.

Integrating the TPB theory with human capital theory represents a significant scholarly advancement in business education for graduate students in Southeast Asia, namely Bangladesh. Furthermore, we developed a novel ITEE scale by synthesizing information from many literary sources, providing valuable insights for future researchers.

Brewer's spent grain (BSG) is the main by-product of the brewing industry, holding significant potential for biomass applications. The purpose of this paper was to determine the effective thermal conductivity (k_eff) of BSG and to develop an Artificial Neural Network (ANN) to predict k_eff, since this property is fundamental in the design and optimization of the thermochemical conversion processes toward the feasibility of bioenergy production.

The experimental determination of k_eff as a function of BSG particle diameter and heating rate was performed using the line heat source method. The resulting values were used as a database for training the ANN and testing five multiple linear regression models to predict k_eff under different conditions.

Experimental values of k_eff were in the range of 0.090–0.127 W m⁻¹ K⁻¹, typical for biomasses. The results showed that the reduction of the BSG particle diameter increases k_eff, and that the increase in the heating rate does not statistically affect this property. The developed neural model presented superior performance to the multiple linear regression models, accurately predicting the experimental values and new patterns not addressed in the training procedure.

The empirical correlations and the developed ANN can be utilized in future work. This research conducted a discussion on the practical implications of the results for biomass valorization. This subject is very scarce in the literature, and no studies related to k_eff of BSG were found.

Using the resource-based view and dynamic capabilities theory, we explore the impact of strategic management practices, innovation and social capital on small and medium-sized enterprises’ (SMEs) performance in three developing Arab countries, namely, Egypt, Morocco and Tunisia.

Drawing upon firm-level data derived from the standardized World Bank Enterprise Surveys, we use quantile regressions and the marginal effects analysis to test our hypotheses.

Our results show heterogeneity among the three countries as to the factors affecting firm performance. The configuration of performance determinants also differs among firms within each country, depending on their level of performance.

Our findings further the understanding of the performance determinants of SMEs in developing countries within their own local context. They imply important theoretical, methodological, managerial and policy implications.

This study is the first to investigate simultaneously strategic management practices, innovation and social capital as determinants of SMEs’ performance in developing countries. We confirm an important premise of the resource-based view and dynamic capabilities theory, which has not been thoroughly investigated in the literature, claiming that strategic management, innovation and social capital cannot be separately investigated as determinants of firm performance. We do so by going beyond the mere inclusion of interaction terms in regression equations to computing marginal effects.

The growing interest on ecosystems on both managerial and academic side reflects a vibrant field of study, nevertheless, the subject is very heterogeneous and in particular concerning a particular form of ecosystems: collaborative ecosystems, the purpose of this study is to shed light on these.

The definition gap existent and the multiplicity of fields and composite studies on collaborative ecosystems have made it necessary to conduct a systematic literature review of the phenomenon, a bibliometric analysis and content analysis.

The research offers an overview of the phenomenon, three main cluster categories emerged: ecosystem, competition and open innovation; this cluster offers a comprehensive schematization of the research topics.

Limitations of this research are that the investigation has been confined to specific keywords related to collaborative ecosystems that led to a strict selection of papers to be analyzed and in having confined the investigation to publications in the managerial area. Further research will be able to expand the selection of keywords or use more strings and proceed to a comparative analysis of results. Another limitation is the small number of databases assessed (only Scopus and Web of Science) and have confined the analysis to specific clusters that emerged from the quantitative analysis of papers.

By proposing a taxonomy of collaborative ecosystems, the paper highlights what solutions and architectures an ecosystem manager must consider when developing collaborative ecosystems, what factors he or she must pay attention to in order to ensure their development and survival, and what elements determine the development of an ecosystem, in particular, the management of innovation and knowledge and the scarcity of resources in a hyper-competitive environment.

A combination of research methods was used to identify the intellectual structure of collaborative ecosystems. In addition, we propose a taxonomy for collaborative ecosystems, opening the study to new lines of investigation and providing a new research agenda.

The aim of this research is to determine the price fairness of the social servicescape and the effect of price fairness on customer trust. In this context, first of all, the effect of the social servicescape on price fairness and then the effect of price fairness on customer trust were tested.

The universe of the research consists of people who visit Starbucks coffee stores. In the study, data were collected from 338 people who visited Starbucks coffee stores. The relationships between the variables were analyzed using the Structural Equation Modeling (SEM) Technique.

As a result of the research, it was concluded that employees, other customers and social crowds, which are from the dimensions of the social servicescape, do not have a significant effect on price fairness, the interaction between employee and customer, which is from the sub-dimensions of the social servicescape, has an effect on customers' perception of price fairness, and price fairness also has an effect on customer trust.

The important point in this research is to determine the effect of the social servicescape on price fairness, which has not been studied in the literature before. Although the effect of physical servicescape on price justice has been investigated, the effect of social servicescape on price justice has not been investigated. When evaluated from this point of view, it is thought that the research will have an important contribution to the literature.

The review paper aims to understand the development of workplace ostracism as a field in organizational studies from 2000 to the present. The study provides a comprehensive synthesis of the current state of the domain by exploring its antecedents, consequences, underlying mechanisms and buffering mechanisms.

The present study analyses 134 published peer-reviewed empirical and non-empirical articles retrieved from the Scopus database. A systematic literature review and bibliometric analyses (using VOS viewer) have been used to gain insights into the development and trends within the field. Bibliometric analyses involved science mapping techniques such as co-citation analysis, co-occurrence of keywords and bibliographic coupling. Combining these three techniques, the study aimed to provide a comprehensive overview of the workplace ostracism research domain's historical, current and future landscape.

In the present study, through descriptive analyses, the authors uncovered publishing trends, productive journals, countries and industries that contribute to this research field. The systematic review enabled the showcasing of the current landscape of workplace ostracism. The bibliometric analyses shed light on major authors, influential articles, prominent journals and significant keywords in workplace ostracism.

This study enriches the existing literature by offering a comprehensive research framework for workplace ostracism. It goes beyond that by presenting significant bibliographic insights by applying bibliometric analyses. Furthermore, this study identifies and emphasizes future research directions using the theory, characteristics, construct and methodologies framework, aiming to expand the knowledge base and understanding of this topic.

Energy consumption has increased significantly since the 1970s, which has increased demand for sufficient infrastructure in the oil and gas industry. Many top-notch oil and gas companies invested in and equipped their facilities with high-capacity electrical equipment to meet high demand and benefit from high revenues. This is becoming a challenge nowadays for old facilities in the oil and gas industry, as most of the electrical equipment installed has reached or even exceeded its lifetime. Moreover, many of the original equipment manufacturers (OEMs) for electrical equipment from the 1980s are no longer in market today. Therefore, the aim of this study is to develop a proactive, cost-effective obsolescence management framework for electrical equipment in the oil and gas industry, considering the aging factor of the equipment.

Firstly, the study begins with gathering available information and identifying criteria. Secondly, the data collection is evaluated by subject-matter-experts (SMEs) in asset management field to ensure compliance with updated international standards and relevant regulatory requirements. Thirdly, a multi-criteria decision-making process is used to rank criteria. Finally, a scoring system is developed to measure the electrical equipment obsoleteness.

The developed framework will assist decision-makers in making informed decisions about maintenance, replacement or upgrades, using knowledge from previous studies and experts’ input. The result finding indicates that considering aging correction factors when measuring equipment obsoleteness leads to accurately and correctly predicting the electrical equipment obsoleteness score.

Previous studies have addressed obsolescence management without taking equipment age into account, regardless of how the equipment is performing. Thus, the lack of a comprehensive obsolescence management framework that accounts for both cost-effectiveness and the aging factor in the oil and gas industry poses a critical challenge.