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The current study explores the role of social psychological factors on organizational commitment. It examined the relationships between organizational fairness, inclusion, diversity, sexism, psychological safety and affective commitment.

The study adopted a cross-sectional survey method where data were collected from staff across six higher education institutions in the United Kingdom. A total of 416 responses were collected and the data were analyzed by employing independent sample t-tests to explore gender differences regarding organizational diversity, inclusion, fairness, sexism, psychological safety and affective commitment. The mediating role of psychological safety in the effects of organizational diversity, fairness, inclusion and sexism on staff’s commitment to the organization was evaluated through a series of simple mediation models. Finally, the mediated effect of organizational social psychological factors on affective commitment through psychological safety, moderated by gender was tested.

As hypothesized, men had higher perceptions of organizational inclusion and diversity and viewed their organization as less sexist. Psychological safety mediated the positive effects of organizational diversity, fairness, inclusion and sexism on staff’s affective commitment to the organization. Organizational diversity and sexism played a bigger part in how women evaluate their organizational environment as safe to take risks and be themselves and consequently on how they commit to the organization. On the other hand, organizational fairness and inclusion seem more closely tied to men’s evaluation of their organization as safe to be themselves and consequently stronger commitment.

The findings shed light on the underlying mechanisms that shape affective commitment, that can lead to more inclusive work environments and contribute to systemic change in the Higher Education context.

Although intellectual capital (IC) and human dynamic capabilities (HDCs) play a significant role in decarbonization processes, their measurement and reporting is under-researched. Hence, this study aims to identify the link between HDCs, carbon accounting and integrated reporting (IR) in the transition processes, investigating IC and HDCs in decarbonization processes to achieve net-zero business models (n-ZBMs).

A systematic literature review with a concise bibliometric analysis is conducted on 229 articles, published from 1990 to 2023 in Scopus database and Google Scholar. Reviewing data on publications, journals, authors and citations and analysing the article content, this study identifies the main search trends, providing a new conceptual model and future research propositions.

The results reveal that the literature has rarely focussed on carbon accounting in terms of IC and HDCs. Additionally, firms face pressure from institutions and stakeholders regarding legitimacy and transparency, necessitating a response considering IR and requiring n-ZBMs to be developed through IC and HDCs to meet social and environmental requirements.

Not only does this study link IC with HDCs to address carbon emissions through decarbonization practices, which has never been addressed in the literature to date, but also provides novel recommendations and propositions through which firms can sustainably transition to being net-zero emission firms, thereby gaining competitive advantage and contributing to the nation’s sustainability goals.

This study, a systematic literature review, aims to review the state-of-the-art literature on choice overload from 2000 to 2023.

The paper reviews 53 research articles published in peer-reviewed journals, using thematic and descriptive analyses. The literature was selected using the PRISMA framework.

Recent research in consumer behaviour has found that too many choices can be detrimental to decision-making. This paper reviews the development of choice overload literature, methodologies used by researchers to study choice overload, small and large choice sets, antecedents, moderators and outcomes of choice overload and the contexts in which choice overload exists.

Limited literature coverage because of the strict adherence to inclusion/exclusion criteria. The theory challenges the conventional choice models in psychology and economics according to which expanding a choice set cannot make decision-making worse and violates the regularity axiom, a cornerstone of classical choice theory. This review also identifies avenues for further research in the field.

A significant decrease in satisfaction or motivation because of too many choices would require marketers and public policymakers to rethink their practice of providing ever-increasing assortments to choose from because they could possibly boost their success by offering less.

This systematic review makes distinctive contributions by classifying the existing studies based on evidence “for” and “against” the existence of choice overload. The review also combines cross-context insights on assortment sizes, moderators and methodological commonalities and gaps to understand the multi-faceted nature and contextual nuances of choice overload.

The current research elucidates the role of empathy in design of artificial intelligence (AI) systems in healthcare context, through a structured literature review, analysis and synthesis of academic literature published between 1990 and 2024.

This study aims to advance the domain of empathy in AI by adopting theory constructs context method approach using the PRISMA 2020 framework.

The study presents a current state-of-the-art literature to review the connections between empathy and AI and identifying four clusters showing the emerging trajectories in the field of AI and empathy in healthcare setting.

Despite a rise in empirical research, the potential pathways enhancing AI accountability by incorporation of empathy is unclear. The research aims to contribute to the existing literature on AI and empathy in the healthcare sector by carving out four distinct clusters depicting the future research avenues.

Productivity is often cited as a key barrier to the adoption of metal laser-based powder bed fusion (ML-PBF) technology for mass production. Newer generations of this technology work to overcome this by introducing more lasers or dramatically different processing techniques. Current generation ML-PBF machines are typically not capable of taking on additional hardware to maximise productivity due to inherent design limitations. Thus, any increases to be found in this generation of machines need to be implemented through design or adjusting how the machine currently processes the material. The purpose of this paper is to identify the most beneficial existing methodologies for the optimisation of productivity in existing ML-PBF equipment so that current users have a framework upon which they can improve their processes.

The review method used here is the preferred reporting items for systematic review and meta-analysis (PRISMA). This is complemented by using an artificial intelligence-assisted literature review tool known as Elicit. Scopus, WEEE, Web of Science and Semantic Scholar databases were searched for articles using specific keywords and Boolean operators.

The PRIMSA and Elicit processes resulted in 51 papers that met the criteria. Of these, 24 indicated that by using a design of experiment approach, processing parameters could be created that would increase productivity. The other themes identified include scan strategy (11), surface alteration (11), changing of layer heights (17), artificial neural networks (3) and altering of the material (5). Due to the nature of the studies, quantifying the effect of these themes on productivity was not always possible. However, studies citing altering layer heights and processing parameters indicated the greatest quantifiable increase in productivity with values between 10% and 252% cited. The literature, though not always explicit, depicts several avenues for the improvement of productivity for current-generation ML-PBF machines.

This systematic literature review provides trends and themes that aim to influence and support future research directions for maximising the productivity of the ML-PBF machines.

This work aims to integrate the concepts generated by a systematic literature review on patient flows in emergency departments (ED) to serve as a basis for developing a generic process model for ED.

A systematic literature review was conducted using PRISMA guidelines, considering Lean Healthcare interventions describing ED patients’ flows. The initial search found 141 articles and 18 were included in the systematic analysis. The literature analysis served as the basis for developing a generic process model for ED.

ED processes have been represented using different notations, such as value stream mapping and workflows. The main alternatives for starting events are arrival by ambulance or walk-in. The Manchester Triage Scale (MTS) was the most common protocol referred to in the literature. The most common end events are admission to a hospital, transfer to other facilities or admission to an ambulatory care system. The literature analysis allowed the development of a generic process model for emergency departments. Nevertheless, considering that several factors influence the process of an emergency department, such as pathologies, infrastructure, available teams and local regulations, modelling alternatives and challenges in each step of the process should be analysed according to the local context.

A generic business process model was developed using BPMN that can be used by practitioners and researchers to reduce the effort in the initial stages of design or improvement projects. Moreover, it’s a first step toward the development of generalizable and replicable solutions for emergency departments.

This study aims to provide an overview of the state-of-the-art in efficiency measurement within higher education (HE). Specifically, it seeks to gather all relevant articles on the topic and subsequently categorize these studies using a flowchart based on two core aspects of the topic.

This study employs bibliometric and content analyses to conduct a systematic literature review. The Preferred Reporting Items for Systematic Review (PRISMA) framework is used to identify the search protocol, followed by analyses to classify and categorize articles.

The bibliometric analysis identifies prominent themes, methodologies and literature gaps. The content findings highlight key insights on higher educational institution (HEI) efficiency, including organizational structures, services and operational activities.

This research contributes to the existing knowledge by synthesizing global literature on HEI’s efficiency. Utilizing the flowchart developed by the authors, the study captures the state-of-the-art based on two critical aspects: methodologies and content. Insights from the analysis and subsequent classification of previous literature provide valuable directions for future research.

The current paper aims to discuss the implementation of Green Lean Six Sigma (GLSS) in the food industry to improve sustainable practices. The focus is more specifically on dairy processors to ascertain the current state of the literature and aid future research direction.

Utilising a systematic literature review (SLR), the paper addresses various terms and different written forms in the literature. The study characterises the current deployment of GLSS in the food industry and explains the reported benefits of this approach.

GLSS, a concept that has yet to be fully explored in the food industry, as in other sectors, holds significant potential to enhance the food industry’s sustainability practices. The dairy sector, a subsector of the food industry known for its high greenhouse gas emissions, is a prime candidate for the application of GLSS. In instances where it has been applied, GLSS has demonstrated its effectiveness in improving sustainability, reducing waste, lowering greenhouse gas emissions and minimising water usage. However, the specific tools used and the model for GLSS implementation are areas that require further study, as they have the potential to revolutionise food industry operations and reduce their environmental impacts.

Benchmarking of this research by the food industry sector and by academics can aid understanding of the practical application of GLSS tools and aid implementation of these practices to evolve the dairy processing sector in the next decade as sustainability champions in the sector.

This study extensively analyses GLSS in the food industry, with a particular focus on dairy processors.

This study aims to draw lessons from the financial technology (FinTech) ecosystem literature through a systematic literature review.

This study systematically studied a sample of 134 articles from the Scopus database to assess the pattern of research development within the scope of the FinTech ecosystem over the last 15 years (2008–2023).

The results obtained indicated that the current research focus leads to several aspects: digital technology and financial inclusion, FinTech and customer behavior, FinTech ecosystem, business model, as well as aspects of governance and regulation. In the effort to develop Islamic FinTech, some aspects that might be targeted include aspects of business development and the Islamic FinTech ecosystem in general, extending financial inclusion to governance and managerial implementation of Islamic FinTech itself.

This research has limitations because it did not focus on the study of more specialized sectors, such as insurance or microfinance institutions, in adopting FinTech, requiring the use of other specifications of institutions in addition to Islamic banking.

This research has substantial theoretical implications in mapping the intellectual structure of Islamic FinTech research, which has been underexplored by previous researchers, as well as providing essential information about which sectors should be prioritized to encourage inclusiveness and overall performance of financial institutions.

This research explores more deeply with a comprehensive approach so that it becomes a pioneer in the study of FinTech ecosystem literature for the development of Islamic FinTech.

Public-private partnerships (PPPs) have become integral in delivering public services and infrastructure, particularly in the context of megaprojects. This paper focuses on the interplay between stakeholder management, challenges, critical success factors (CSFs), and the overall success of PPP-arranged civil infrastructure megaprojects.

Using the PRISMA methodology, we comprehensively analyze challenges and critical success factors (CSFs) influencing stakeholder engagement within PPP megaprojects. A focused search equation identified 595 papers, which were distilled down to 34 relevant papers and case studies. Qualitative analysis of these papers revealed 48 CSFs categorized into 11 challenges from a stakeholder management perspective, which were further delineated across public, private, and combined sectors, and then mapped along the PPP megaproject lifecycle.

Informed by a diverse amalgam of civil and project management literature, this research reveals the intricate dynamics of PPP megaprojects across the globe that emphasize the critical nature of stakeholder engagement, analysis, and management practices. Key findings highlighted conflicting interests between public and private stakeholders, manifesting in challenges like project performance versus profitability. The literature emphasized instances where neglect of local community culture led to adverse social outcomes. A universal conclusion underscored the context-specific nature of challenges and CSFs, stressing the need for a holistic understanding of stakeholders and project dynamics.

The paper acknowledges that it focused on 34 selected papers out of 595 identified. This sample focuses on civil engineering megaprojects which may not fully represent the breadth of research in the field, potentially missing out on valuable insights from excluded studies.

We believe that the compiled list of CSFs, organized according to stakeholder relationships and the project lifecycle, serves as a potent tool for managers and planners. By enabling the identification of complexity from diverse perspectives, this research allows elucidating the challenges faced by the management team in PPP megaproject.

This research identifies several social outcomes related to PPP megaprojects. Critical Success Factors identified as such should allow the project managers to maximize benefits for society and minimize risk and negative externalities.

This study contributes valuable insights for policies and practices by systematically describing challenges and related CSFs throughout the PPP megaproject lifecycle. Additionally, it addresses the nuanced aspects of internal and external stakeholder management, thereby contributing to the overall understanding and best practices required to confront complex megaprojects involving a wide range of stakeholder groups.