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This study develops a model and algorithm to solve the decentralized resource-constrained multi-project scheduling problem (DRCMPSP) and provides a suitable priority rule (PR) for coordinating global resource conflicts among multiple projects.

This study addresses the DRCMPSP, which respects the information privacy requirements of project agents; that is, there is no single manager centrally in charge of generating multi-project scheduling. Accordingly, a three-stage model was proposed for the decentralized management of multiple projects. To solve this model, a three-stage solution approach with a repeated negotiation mechanism was proposed.

The experimental results obtained using the Multi-Project Scheduling Problem LIBrary confirm that our approach outperforms existing methods, regardless of the average utilization factor (AUF). Comparative analysis revealed that delaying activities in the lower project makespan produces a lower average project delay. Furthermore, the new PR LMS performed better in problem subsets with AUF < 1 and large-scale subsets with AUF > 1.

A solution approach with a repeated-negotiation mechanism suitable for the DRCMPSP and a new PR for coordinating global resource allocation are proposed.

The goal of this study was to understand which employee-focused workplace practices and priorities – more formally known as human resource (HR) practices and priorities – employees with mental health and/or addiction challenges (MHAC) valued and how they perceived the day-to-day implementation of those practices and priorities in the workplace integration social enterprises (WISEs) that employed them.

Twenty-two WISE workers who self-identified as having serious MHAC participated in semi-structured interviews. Interviews were transcribed and coded to identify ways that employees did or did not feel supported in their WISEs.

Participants identified three HR practices and two HR priorities as important to establishing an inclusive workplace that accommodated their MHAC. The extent to which individual participants felt included and accommodated, however, was shaped by interactions with their supervisors and coworkers.

By evaluating the salience of WISEs’ employee-focused workplace practices and priorities through the lens of the employees themselves, our study articulates the critical role that interactions with coworkers and supervisors have in determining whether HR practices and priorities have the intended effect on worker experience.

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

This paper aims to establish an efficient maintenance management system tailored for healthcare facilities, recognizing the crucial role of medical equipment in providing timely and precise patient care.

The system is designed to function both as an information portal and a decision-support system. A knowledge-based approach is adopted centered on Semantic Web Technologies (SWTs), leveraging a customized ontology model for healthcare facilities’ knowledge capitalization. Semantic Web Rule Language (SWRL) is integrated to address decision-support aspects, including equipment criticality assessment, maintenance strategies selection and contracting policies assignment. Additionally, Semantic Query-enhanced Web Rule Language (SQWRL) is incorporated to streamline the retrieval of decision-support outcomes and other useful information from the system’s knowledge base. A real-life case study conducted at the University Hospital Center of Oran (Algeria) illustrates the applicability and effectiveness of the proposed approach.

Case study results reveal that 40% of processed equipment is highly critical, 40% is of medium criticality, and 20% is of negligible criticality. The system demonstrates significant efficacy in determining optimal maintenance strategies and contracting policies for the equipment, leveraging combined knowledge and data-driven inference. Overall, SWTs showcases substantial potential in addressing maintenance management challenges within healthcare facilities.

An innovative model for healthcare equipment maintenance management is introduced, incorporating ontology, SWRL and SQWRL, and providing efficient data integration, coordinated workflows and data-driven context-aware decisions, while maintaining optimal flexibility and cross-departmental interoperability, which gives it substantial potential for further development.

A new triage method, MBCE (Medical Bio Social Ethics), is presented with social justice, bio, and medical ethics for critical resource distribution during a pandemic. Ethical triage is a complex and challenging process that requires careful consideration of medical, social, cultural, and ethical factors to guide the decision-making process and ensure fair and transparent allocation of resources. When assigning priorities to patients, a clinician would evaluate each patient’s medical condition, age, comorbidities, and prognosis, as well as their cultural and social background and ethical factors.

A statistical analysis shows no interactions among the ethical triage factors. It implies the ethical components have no moderation effect; hence, each is independent. The result also points out that medical and bioethics may have an affinity for interactions. In such cases, there seem to be some ethical factors related to bio and medical ethics that are correlated. Therefore, the triage team should be careful in evaluating patient cases. The algorithm is explained with case histories of the selected patient. A group of triage nurses and general medical practitioners assists with the triage.

The MBCE triage algorithm aims to allocate scarce resources fairly and equitably. Another ethical principle in this triage algorithm is the principle of utility. In a pandemic, the principle of utility may require prioritizing patients with a higher likelihood of survival or requiring less medical care. The research presents a sensitivity analysis of a patient’s triage score to show the algorithm’s robustness. A weighted score of ethical factors combined with an assessment of triage factors combines multiple objectives to assign a fair triage score. These distinctive features of the algorithm are reasonably easy to implement and a new direction for the unbiased triage principle.

The idea is to make decisions about distributing and using scarce medical resources. Triage algorithms raise ethical issues, such as discrimination and justice, guiding medical ethics in treating patients with terminal diseases or comorbidity. One of the main ethical principles in triage algorithms is the principle of distributive justice.

The purpose of this paper is to scrutinise the effectiveness of four derivative exchanges’ enforcement efforts since 2007. These exchanges include the Commodity Exchange Inc. and ICE Futures US from the United States and ICE Futures Europe and the London Metal Exchange from the UK.

The paper examines 799 enforcement notices published by four exchanges through a behavioural science lens: HUMANS conceived by Hunt (2023) in Humanizing Rules: Bringing Behavioural Science to Ethics and Compliance.

The paper finds the effectiveness of the exchanges’ enforcement efforts to be a mixed picture as financial markets transition from the digital to artificial intelligence era. Humans remain a key cog in the wheel of market participants’ trading operations, albeit their roles have changed. Despite this, some elements of exchanges’ enforcement regimes have not kept pace with the move from floor to remote trading. However, in other respects, their efforts are or should be, effective, at least in behavioural terms.

The paper’s findings are arguably limited to exchanges based in Anglophone jurisdictions. The information published by the exchanges is variable, making “like-for-like” comparisons difficult in some areas.

The paper makes several recommendations that, if adopted, could help exchanges to increase the potency of their enforcement programmes.

A key aim of the paper is to shift the lens through which the debate concerning the efficacy of exchange-level oversight is conducted. Hitherto, a legal lens has been used, whereas this paper uses a behavioural lens.

The Takāful (Islamic insurance) industry operates on the principles of Maqāṣid al-Sharī’ah, and of late, the industry has witnessed significant market growth. The purpose of this study is to develop a performance measurement model based on Maqāṣid al-Sharī’ah to evaluate the performance of Takāful firms.

A mixed-method research approach was adopted to conduct the present study. Priorities were assigned to various dimensions of the Maqāṣid model using analytic hierarchy process and by taking inputs from 18 Takāful experts. On the contrary, six experts were involved in identifying the elements and measures for the operationalization of the Maqāṣid dimensions.

Maṣlaḥa (0.359) was found to possess the highest priority, followed by Justice (0.345) and Educating Individuals (0.295). Furthermore, under Necessity, protection of religion (0.398) and protection of life (0.388) are assigned almost similar priorities. These two are followed by the protection of progeny (0.107), protection of wealth (0.058) and protection of intellect (0.047). The final outcome of this study is a hierarchical model for the evaluation of performance of Takāful firms.

The application of the performance evaluation model will provide information to the management of Takāful firms on where they stand in terms of fulfilling Maqāṣid al-Sharī’ah principles. If any firms are found to have a deficiency in a certain part of Maqāṣid components, then proper and adequate measures can be taken to ameliorate the situation.

It is necessary to have a performance evaluation model based upon Maqāṣid al-Sharī’ah to evaluate the performance of Takāful firms as these firms operate on the principles of Maqāṣid al-Sharī’ah. Because there does not exist any such model, this study fills up this gap. Details of the measures that can be used to evaluate the performance of Takāful firms are also provided.

This study aims to develop a comprehensive insolvency model tailored to Islamic banks, ensuring alignment with Shariah principles throughout pre-insolvency, bankruptcy and post-bankruptcy stages.

The research adopts a qualitative research method, using a desktop research approach. Primary sources and secondary sources are examined to gather information and draw conclusions.

This study presents a comprehensive insolvency model designed for Islamic banks, rooted in Shariah principles. The model covers pre-insolvency, bankruptcy (taflis) and post-bankruptcy stages, incorporating key Shariah parameters to ensure adherence to Islamic finance principles. It addresses challenges such as adapting to dynamic financial landscapes and varying interpretations of Shariah principles. Notably, the model recognizes the separate legal personality of Islamic banks and emphasizes transparency, fairness and compliance with religious obligations. In the post-bankruptcy stage, directors are urged to voluntarily settle remaining debts, aligning with ethical and Shariah-compliant standards.

The study contributes to the stability and growth of Shariah-compliant financial systems by extending insolvency principles to Islamic banks, providing a foundation for future research and policymaking specific to this context.

A sense of collective free-thinking with tangible goals makes co-creation an enlightening experience. Yet despite the freedom and organic flow of the methodology, there remain barriers to deploying co-creation in the real-world context. The aim was to understand the barriers and solutions to co-creation, reflect on applying co-creation in practice and co-create an applicable framework for co-creation.

These reflections and conceptual developments were completed using a Participatory Action Research Approach through the co-creation of the Erasmus+ funded Co-creating Welfare course.

Results presented are centric to the experiences in the United Kingdom but led to application at an international level. Problem formulation led to solutions devised about who should co-create, what co-creation aims to achieve, how to receive management buy-in, co-creating beyond the local face to face context and evaluation.

The Three Co’s Framework is proposed using the outline of: Co-Define, Co-Design and Co-Refine. Those who take part in co-creation processes are recommended to be called co-creators, with less focus on “empowerment” and more about facilitating people to harness the power they already have. Utilising online and hybrid delivery methods can be more inclusive, especially in response to the COVID-19 pandemic. The use of co-creation needs to be evaluated more moving forwards, as well as the output co-created.

The aim of the paper is to rank and analyze the key strategies to sustainable finance adoption in the manufacturing sector using Fuzzy Delphi method (FDM), Interpretive Structural Modeling (ISM) and MICMAC (impact matrix cross-reference multiplication applied to a classification) analysis.

The study develops a novel framework to identify and analyze the mutual relationships among set of sustainable policies using extensive literature survey and experts opinion. Initially, the study found 14 strategies to implement sustainable finance with the help of vast literature. Then, the list of identified factors were screened through Fuzzy Delphi Method (FDM). Based on driving and dependence power, the final list of factors are divided into three categories.

The study findings reveal that “environmental rules and practices”, “financial incentives, tax reduction and subsidy”, have strongest driving power for promoting sustainable financial system in Pakistani manufacturing sector. Furthermore, “environmental awareness” and “long term vision” are found to be highly influenced by other corresponding elements in a system.

The ISM approach assists professionals, academics, and managers in identifying and ranking policies in implementing green business techniques. The hierarchical representation of ISM results provides a roadmap for decision-makers to navigate and prioritize factors effectively, facilitating the implementation of strategies that contribute to sustainable growth within organizations.

The study results provide interesting clues regarding green finance policies that provide the foundations, incentives, protections or other provisions that support the ecological conservancy’s mission. Specifically, the findings guide that government must offer research grants to private enterprises, research and development institutions, and universities to promote environmental protection and develop transformative technologies such as waste recycling, renewable energy, carbon capture, and power consumption.

The exploration of strategies for sustainable finance adoption with the help of mixed methodological approach and classification of these strategies on the basis of importance level is a new attempt in the field of manufacturing sector.