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The purpose of this study is to identify organisational homeostasis factors in the context of healthcare organisations and to develop a conceptual model for green transformation.

The organisational homeostasis factors were determined by review of literature study and the opinions of healthcare experts. Scheduled interviews and closed-ended questionnaires are employed to collect data for this research. This study employed “TISM methodology” and “MICMAC analysis” to better comprehend how the components interact with one another and prioritise them based on their driving and dependence power.

This study identified 10 factors of organisational homeostasis in healthcare organisation. Recognition of interdependence, hormesis, strategic coalignment, consciousness on dependence of healthcare resources and cybernetic principle of regulations are the driving or key factors of this study.

The study's primary focus was on the organisational homeostasis factors in healthcare organisations. The methodological approach and structural model are used in a healthcare organisation; in the future, these approaches can be applied to other industries as well.

The key drivers of organisational homeostasis and the identified factors will be better comprehended and understood by academic and important stakeholders in healthcare organisations. Prioritizing the factors helps the policymakers to comprehend the organisational homeostasis for green transformation in healthcare.

In this study, the TISM and MICMAC analysis for healthcare is proposed as an innovative approach to address the organisational homeostasis concept in the context of green transformation in healthcare organisations.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

Policymakers are developing government-level pandemic response strategies (GPRS) to assist architecture, engineering and construction (AEC) enterprises. However, the effectiveness of the GPRS has not been assessed. Therefore, this study aims to investigate the interrelationships between GPRS and AEC enterprises. To achieve that aim, the study objectives are to compare GPRS effectiveness between small-medium and large AEC enterprises, develop groupings to categorize interrelated GPRS and evaluate the effectiveness of the GPRS and interrelated constructs.

A systematic literature review and semi-structured interviews with 40 AEC industry professionals were carried out, generating 22 GPRS. Then, questionnaire survey data was collected among AEC professionals. In total, 114 valid survey answers were received and analyzed using the Kruskal–Wallis H test, normalized mean analysis, factor analysis and fuzzy synthetic evaluation.

Small-medium enterprises have four distinct critical GPRS: “form a special task force to provide support in maneuvering COVID-19,” “provide infrastructure investment budgets to local governments,” “develop employee assistance programs that fit all types of working groups” and “diversify existing supply chain.” Large enterprises have two distinct critical GPRS: “provide help in digitalizing existing construction projects” and “mandate COVID-19 as force majeure.” Eighteen GPRS can be categorized into the following five constructs: “market stability and financial aid,” “enterprise capability management,” “supply chain improvement,” “law and policy resources” and “information and workforce management.” The former two constructs are more effective than other GPRS constructs.

This is the first paper that evaluates the effectiveness of GPRS for AEC enterprises, providing new evidence to policymakers for well-informed decision-making in developing pandemic response strategies.

The present study aims to gauge the experience of gender non-binary (NB) employees in the context of employee value propositions (EVP) in Indian enterprises and make suggestions for organizations to align their gender-aligned interventions with the EVP framework.

Qualitative methodology was used for collecting data through semi-structured interviews and subsequent analysis of the transcripts. The data was gathered from 10 NB participants working in Indian enterprises with the use of non-probabilistic purposive snowball sampling.

The analysis revealed eight themes representing the good, bad and ugly experiences of NB individuals within the context of EVP. These findings underscore the potential of enriching value propositions for employees to promote gender inclusion in corporate settings, contributing to long-term organizational success.

The study offers both theoretical and practical implications for fostering inclusivity at the workplace. It suggests that policymakers and organizations should align EVP with diversity and inclusion initiatives, re-evaluate hiring processes and promotion policies to ensure equal opportunities for NB individuals, provide regular staff training to address biases and implement inclusive insurance policies and representation in employee resource groups (ERGs).

This study provides unique insights into the experiences of NB employees within the framework of EVPs in Indian organizations.

Given the limited literature on depression as a contributing factor to compulsive social media use, the present research examines the role of perceived depressive mood (PDM) in developing compulsive social media use behavior. The authors also identify and hypothesize channels such as contingent self-esteem (CSE), social interaction anxiety (SIA) and fear of negative evaluation (FNE), which may explain how PDM affects compulsive social media use.

The research model was empirically tested with a survey of 367 Chinese university students using structural equation modeling by drawing on the escape and self-presentation lenses.

The findings indicate that PDM contributes to compulsive social media use behavior both directly and indirectly through CSE. Furthermore, the impact of CSE on compulsive social media use is mediated by the FNE, whereas SIA fails to mediate this effect.

The results can advance the authors’ knowledge of the role and process by which depressive mood impacts compulsive social media use. These findings may add insights into psychological treatment and help in, for example, developing counseling programs or coping strategies for depressed people to protect them from using social media excessively.

This research identifies the pathway mechanism between PDM and compulsive use of social media. It also increases the understanding of how CSE and social interaction deficiencies contribute to compulsive social media usage (CSMU).

Lean management tools are becoming increasingly applied in different types of organizations around the world. These tools have shown their significant contribution to improving business performance. In this vein, the purpose of this paper is to examine the influence of lean management on both occupational safety and operational excellence in Tunisian companies.

A survey was conducted among Tunisian companies, and it resulted in the collection of 62 responses that were analyzed using the software SPSS. In addition, a conceptual model linking the practices of the three basic concepts was designed to highlight the hypotheses of the research. Subsequently, factor analysis and structural equation method analysis were conducted to assess the validation of the assumptions.

The results obtained have shown that lean management has a significant impact on occupational safety. Similarly, occupational safety has a significant impact on operational excellence. However, lean management does not have a significant impact on operational excellence.

This work highlighted the involvement of small and medium-sized enterprise’s managers from emerging economies in the studied concepts’ practices. Likewise, it testified to the impacts of lean management on occupational safety and operational excellence in the Tunisian context.

Renal failure is an end-stage consequence after persistent hyperglycemia during diabetic nephropathy (DN), and the etiology of DN has been linked to oxidative stress. The purpose of this research was to determine the beneficial synergistic effects of S-Allyl Cysteine (SAC) and Taurine (TAU) on oxidative damage in the kidneys of type 2 diabetic rats induced by hyperglycemia.

Experimental diabetes was developed by administering intraperitoneal single dose of streptozotocin (STZ; 65 mg/kg) with nicotinamide (NA; 230 mg/kg) in adult rats. Diabetic and control rats were treated with SAC (150 mg/kg), TAU (200 mg/kg) or SAC and TAU combination (75 + 100 mg/kg) for four weeks. The estimation of body weight, fasting blood glucose (FBG), oral glucose tolerance test (OGTT), oxidative stress markers along with kidney histopathology was done to investigate the antidiabetic potential of SAC/TAU in the NA/STZ diabetic group.

The following results were obtained for the therapeutic efficacy of SAC/TAU: decrease in blood glucose level, decreased level of thiobarbituric acid reactive substances (TBARS) and increased levels of GSH, glutathione-s-transferase (GST) and catalase (CAT). SAC/TAU significantly modulated diabetes-induced histological changes in the kidney of rats.

SAC/TAU combination therapy modulated the oxidative stress markers in the kidney in diabetic rat model and also prevented oxidative damage as observed through histopathological findings.

Contemporary technological disruptions are espoused as though they stimulate sustainable growth in the built environment through the Green Internet of Things (G-IoT). Learning from discipline-specific experiences, this paper articulates recent advancements in the knowledge and concepts of G-IoT in relation to the construction and smart city sectors. It provides a scoping review for G-IoT as an overlooked dimension. Attention was paid to modern circularity, cleaner production and sustainability as key benefits of G-IoT adoption in line with the United Nations’ Sustainable Development Goals (UN-SDGs). In addition, this study also investigates the current application and adoption strategies of G-IoT.

This study uses the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) review approach. Resources are drawn from Scopus and Web of Science repositories using apt search strings that reflect applications of G-IoT in the built environment in relation to construction management, urban planning, societies and infrastructure. Thematic analysis was used to analyze pertinent themes in the retrieved articles.

G-IoT is an overlooked dimension in construction and smart cities so far. Thirty-three scholarly articles were reviewed from a total of 82 articles retrieved, from which five themes were identified: G-IoT in buildings, computing, sustainability, waste management and tracking and monitoring. Among other applications, findings show that G-IoT is prominent in smart urban services, healthcare, traffic management, green computing, environmental protection, site safety and waste management. Applicable strategies to hasten adoption include raising awareness, financial incentives, dedicated work approaches, G-IoT technologies and purposeful capacity building among stakeholders. The future of G-IoT in construction and smart city research is in smart drones, building information modeling, digital twins, 3D printing, green computing, robotics and policies that incentivize adoption.

This study adds to the normative literature on envisioning potential strategies for adoption and the future of G-IoT in construction and smart cities as an overlooked dimension. No previous study to date has reviewed pertinent literature in this area, intending to investigate the current applications, adoption strategies and future direction of G-IoT in construction and smart cities. Researchers can expand on the current study by exploring the identified G-IoT applications and adoption strategies in detail, and practitioners can develop implementation policies, regulations and guidelines for holistic G-IoT adoption.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.