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The short/fast-food and perishable food supply chains (PFSC) have similar characteristics of lower lifespan and variable demand, leading to significant waste. However, the global population surge and increased health awareness make it impossible to continue wasting food because it is responsible for the loss of economy, resources, and biodiversity. A sustainable transition in short and PFSC is necessary; thus, addressing challenges is critical to explore the best strategy for redesigning PFSC.

An extensive literature review helped to identify 40 challenges, while a Delphi study highlighted 21 critical challenges. The fuzzy decision-making trial and evaluation laboratory method establishes a causal relationship between sustainable development (SD) challenges to help redesign PFSC.

From a strategic development perspective, frequent transportation disruption is the main critical challenge. Lack of supplier reliability is the most substantial cause of independence, with a causal value of 2.878. Overhead costs and lack of green maintenance strategies are part of the performance-oriented challenges. As it belongs to the driving zone, the second quadrant requires control while transforming PFSC for better sustainable development.

The study has several implications, such as lack of supplier reliability and frequent transportation disruption, which have the most robust causal value used as short-term strategy development. For short- and fast-food supply chains, it is necessary to study market and consumer behavior patterns to optimize inventory and customer service. Combating transportation disruption and supplier reliability challenges is vital in both PFSC and short and fast-food supply chains to reduce waste and promote sustainability.

The study’s findings are unique and put value toward the sustainable transition of PFSC by revealing critical challenges and their impact.

The objective of this study is to analyse the integration of technology in Human Resources Management (HRM) with a special focus on Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT) and Big Data.

This study aims to contribute to the understanding of these trends by conducting a thorough bibliometric analysis using the Scopus database, encompassing research on HRM and Technology from 1991 to 2022. By employing citation analysis, co-citation analysis and co-word analysis, the study uncovers key patterns and trends in the field.

The findings indicate that AI, Big Data and ML are the focal points of research when exploring the intersection of Technology and HRM. These technologies offer promising prospects for enhancing Human Resource processes, such as Talent Acquisition, Performance Management and Employee Engagement.

In our study, we showcase the practical implications that offer guidance for HR researchers and professionals, enabling them to make informed decisions regarding the adoption and implementation of Information Technology.

This research can provide valuable insights to HR managers on the use of cutting-edge technology in HRM. It aims to enhance the manager’s awareness of how technology-enabled HRM can improve HR performance.

This study adds to the existing body of knowledge on how Modern Technology empowers HRM. It also proposes a conceptual framework for the use of Modern Technology along with Strategic Management and Knowledge Management to improve Human Resource Performance.

The purpose of this study is to develop a protective coating system on mild steel panel incorporating epoxidized natural rubber with acrylic polyol resin.

In this work, a novel attempt is made to develop binder coatings using epoxidized natural rubber-based material and an organic resin (acrylic resin) for corrosion protection on metal substrate. Seven different samples of multifunctional coatings are developed by varying the compositions of epoxidized natural rubber (ENR) and acrylic resin. The properties of the developed coatings have been characterized using analytical methods such as Fourier transform infrared spectroscopy (FTIR) and electrochemical impedance spectroscopy (EIS). EIS has been carried out for 30 days to evaluate the corrosion resistance after immersing into 3.5 wt.% of sodium chloride. Cross hatch cut tester (CHT) has been used to study the adhesive properties. UV–Visible Spectroscopy (UV–Vis) was also used to assess changes in the coating-film transparency of the natural rubber-based coating systems in this study.

The developed coatings have formed uniform layer on the substrate. CHT results show excellent adhesion of the coatings. Higher concentrations of ENR have higher transparency level, which reduces when the acrylic concentration increases. FTIR analysis confirms the crosslinking that occurred between the components of the coatings. Based on the impedance data from EIS, the incorporation of natural rubber can be an additive for the corrosion protection, which has the coating resistance values well above 108Ω even after 30 days of immersion.

The blending method provides a simple and practical solution to improve the strength and adhesion properties of acrylic polyol resin with epoxidized natural rubber. There is still improvement needed for long-term applications.

The work has been conducted in our laboratory. The combination of natural rubber-based materials and organic resins is a new approach in coating research.

This study aims to propose that the corrosion resistance of the neat epoxy coating can be further enhanced by incorporating reinforcing agents.

Chitosan, silica and their hybrid compound were used to study the subject of corrosion resistance of epoxy coating systems. This work used 3.5 Wt.% NaCl solution as the electrolyte, and electrochemical impedance spectroscopy (EIS) was used to investigate the electrochemical behaviour of the studied coating systems. Standard and accelerated states were used without and with scratch on the coating layer.

It was found that the impedance value of composite coating incorporated with the hybrid compound was significantly higher at 10¹⁰ Ω after 14 days of exposure in both testing states. The breakpoint frequency (f_b) determination also proves with large capacitive region at low-to-high frequency of impedance plots corresponding to the high corrosion resistance.

The hybrid compound consisting of chitosan as organic biopolymer and silica as inorganic material, respectively, served as a promising reinforcing agent for composite coating as a promising corrosion inhibitor. Different states of EIS measurement were used which are standard (without scratch) and accelerated (with scratch) states associated with the f_b values.

To achieve changing customer demands, organizations are striving hard to embrace cutting-edge technologies facilitating a high level of customization. Industry 4.0 (I4.0) implementation aids in handling big data that could help generate customized products. Lean six sigma (LSS) depends on data analysis to execute complex problems. Hence, the present study aims to empirically examine the key operational characteristics of LSS and I4.0 integration such as principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 technologies and performance measures.

To stay competitive in the market and quickly respond to market demands, industries need to go ahead with digital transformation. I4.0 enables building intelligent factories by creating smart manufacturing systems comprising machines, operators and information and communication technologies through the complete value chain. This study utilizes an online survey on Operational Excellence professionals (Lean/Six Sigma), Managers/Consultants, Managing Directors/Executive Directors, Specialists/Analysts/Engineers, CEO/COO/CIO, SVP/VP/AVP, Industry 4.0 professionals and others working in the field of I4.0 and LSS. In total, 83 respondents participated in the study.

Based on the responses received, reliability, exploratory factor analysis and non-response bias analysis were carried out to understand the biasness of the responses. Further, the top five operational characteristics were reported for LSS and I4.0 integration.

One of the limitations of the study is the sample size. Since I4.0 is a new concept and its integration with LSS is not yet explored; it was difficult to achieve a large sample size.

Organizations can utilize the study findings to realize the top principles, workforce skills, critical success factors, challenges, LSS tools, I4.0 tools and performance measures with respect to LSS and I4.0 integration. Moreover, these operational characteristics will help to assess the organization's readiness before and after the implementation of this integration.

The authors' original contribution is the empirical investigation of operational characteristics responsible for I4.0 and LSS integration.

This research introduces an innovation strategy aimed at bolstering the reliability of a renewable energy resource, which is hybrid energy systems, through the application of a metaheuristic algorithm. The growing need for sustainable energy solutions underscores the importance of integrating various energy sources effectively. Concentrating on the intermittent characteristics of renewable sources, this study seeks to create a highly reliable hybrid energy system by combining photovoltaic (PV) and wind power.

To obtain efficient renewable energy resources, system designers aim to enhance the system’s reliability. Generally, for this purpose, the reliability redundancy allocation problem (RRAP) method is utilized. The authors have also introduced a new methodology, named Reliability Redundancy Allocation Problem with Component Mixing (RRAP-CM), for optimizing systems’ reliability. This method incorporates heterogeneous components to create a nonlinear mixed-integer mathematical model, classified as NP-hard problems. We employ specially crafted metaheuristic algorithms as optimization strategies to address these challenges and boost the overall system performance.

The study introduces six newly designed metaheuristic algorithms. Solve the optimization problem. When comparing results between the traditional RRAP method and the innovative RRAP-CM method, enhanced reliability is achieved through the blending of diverse components. The use of metaheuristic algorithms proves advantageous in identifying optimal configurations, ensuring resource efficiency and maximizing energy output in a hybrid energy system.

The study’s findings have significant social implications because they contribute to the renewable energy field. The proposed methodologies offer a flexible and reliable mechanism for enhancing the efficiency of hybrid energy systems. By addressing the intermittent nature of renewable sources, this research promotes the design of highly reliable sustainable energy solutions, potentially influencing global efforts towards a more environmentally friendly and reliable energy landscape.

The research provides practical insights by delivering a comprehensive analysis of a hybrid energy system incorporating both PV and wind components. Also, the use of metaheuristic algorithms aids in identifying optimal configurations, promoting resource efficiency and maximizing reliability. These practical insights contribute to advancing sustainable energy solutions and designing efficient, reliable hybrid energy systems.

This work is original as it combines the RRAP-CM methodology with six new robust metaheuristics, involving the integration of diverse components to enhance system reliability. The formulation of a nonlinear mixed-integer mathematical model adds complexity, categorizing it as an NP-hard problem. We have developed six new metaheuristic algorithms. Designed specifically for optimization in hybrid energy systems, this further highlights the uniqueness of this approach to research.

Workflow optimisation is crucial for establishing a viable acute stroke (AS) intervention programme in a large tertiary care centre. This study aims to utilise Lean Six Sigma (LSS) principles to enhance the hospital's workflow.

The Action Research methodology was used to implement the project and develop the case study. The study took place in a large tertiary care academic hospital in India. The Define-Measure-Analyse-Improve-Control approach optimised the workflow within 6 months. Lean tools such as value stream mapping (VSM), waste audits and Gemba were utilised to identify issues involving various stakeholders in the workflow. Sigma-level calculations were used to compare baseline, improvement and sustainment status. Additionally, statistical techniques were effectively employed to draw meaningful inferences.

LSS tools and techniques can be effectively utilised in large tertiary care hospitals to optimise workflow through a structured approach. Sigma ratings of the processes showed substantial improvement, resulting in a five-fold increase in clinical outcomes. Specifically, there was a 43% improvement in outcome for patients who underwent acute stroke revascularisation. However, certain sigma ratings deteriorated during the control and extended control (sustainment) phases. This indicates that ensuring the sustainability of quality control interventions in healthcare is challenging and requires continuous auditing.

The article presents a single case study deployed in a hospital in India. Thus, the generalisation of outcomes has a significant limitation. Also, the study encounters the challenge of not having a parallel control group, which is a common limitation in quality improvement studies in healthcare. Many studies in healthcare quality improvement, including this one, are limited by minimal data on long-term follow-up and the sustainability of achieved results.

This study pioneers the integration of LSS methodologies in a large Indian tertiary care hospital, specifically targeting AS intervention. It represents the first LSS case study applied in the stroke department of any hospital in India. Whilst most case studies discuss only the positive aspects, this article fills a critical gap by unearthing the challenges of applying LSS in a complex healthcare setting, offering insights into sustainable quality improvement and operational efficiency. This case study contributes to the theoretical understanding of LSS in healthcare. It showcases its real-world impact on patient outcomes and process optimisation.

Based on Indian conceptualisation of workplace spirituality, this study aims to examine the linkage between four dimensions of workplace spirituality (swadharma, authenticity, lokasangraha and sense of community) and work-to-family (WTF) enrichment. It also explored the mediating effect of psychological and social capital and the moderating effect of gratitude.

A sample of 387 women employees of Indian hospitality industry was collected in three waves. The collected data were analysed in three stages. Firstly, reliability, validity and multicollinearity were assessed using appropriate statistical measures like Cronbach’s alpha, composite reliability and average variance explained. Secondly, the relationship between four dimensions of workplace spirituality and WTF enrichment were examined using correlation and hierarchical regression. Several demographic variables like marital status, age, experience and income level were controlled. Thirdly, the moderating effect of gratitude and mediating effects of psychological and social capital were analysed using PROCESS macro.

The results showed adequate reliability and validity estimates. Also, four dimensions of Indian workplace spirituality were significantly related to WTF enrichment with these dimensions of workplace spirituality collectively explaining 46.8% variations in WTF enrichment. The results also concluded significant meditating effect of psychological and social capital. It also asserted significant moderating effect of gratitude.

The study is based on longitudinal data collected to test seven hypotheses of the study.

The purpose of this study is to examine the factors that drive superior social enterprise performance for women-led social enterprises. The authors examined the role of individual entrepreneur cognitive characteristics contributing to social enterprise performance and recommended a framework for women's social entrepreneur development.

The authors conducted an exploratory qualitative study of 22 women founders of social enterprises using a semi-structured questionnaire. In-depth interviews were conducted, and the transcripts were analyzed using thematic content analysis.

This study found a significant impact of self-efficacy on the performance of social enterprises among the studied subjects. Social support in the form of material, information and emotional support enhanced the ability of women social entrepreneurs to better achieve business sustenance and continuance of operations. The business skills of the women social entrepreneurs led them to move from just social impact generators to becoming thought leaders. The strong prosocial motivation of the founders contributed to building their resilience in the face of adversity.

This study extended the existing theories on social entrepreneurship by bringing the dimensions of entrepreneurial resilience in driving social enterprise performance along with business skills. Thus, it provided an enhanced explanation to the existing body of knowledge on contributors to superior social enterprise performance.

This study gathered insights into the role of entrepreneurship education focused on business skills, especially for women social entrepreneurs in achieving superior performance for their social ventures. This also reconfirmed the role of social support and how structurally this could be provided by educational systems to aspiring women social entrepreneurs.

The practice of social entrepreneurship by women social entrepreneurs has been growing. Its importance in developing economies because of its ability to make grassroots changes at the lower levels of society was substantive. Women have shown more inclination toward social business with an affinity for prosocial contribution. By focusing on nurturing these social enterprises, governments as well as global agencies like the United Nations and the World Economic Forum could accelerate social change. Furthermore, support for the current women social entrepreneurs as change-makers making a difference in society could be achieved.

To the best of the authors’ knowledge, this research study was one of the first studies on women social entrepreneurs focusing on the factors of self-efficacy, social support and entrepreneurial resilience contributing to social enterprise performance. This study combined the social entrepreneurship intention theory with entrepreneurial resilience and business skills to understand the factors leading to successful social enterprise performance for women social entrepreneurs.

The purpose of this paper is to examine the connectedness among Memecoin, Halal exchange traded funds (ETF) and environmental, social and governance (ESG) indexes in different quantiles.

The authors consider Dogecoin to measure Memecoin while Wahed FTSE USA Shariah ETF (HLAL) and SP Funds S&P 500 Sharia Industry Exclusions ETF (SPUS) are used to represent Halaf ETF. Similarly, iShares ESG Aware MSCI USA ETF (ESGU) and Vanguard ESG US Stock (ESGV) proxy the ESG index ETF. The daily price of these examined markets is considered from January 2, 2020, to January 18, 2024. The quantile vector autoregression is deployed for the empirical computation.

The result reveals that Memecoin (Dogecoin) emerges as the best diversifier irrespective of various quantiles because it is least connected in terms of recipient and transmission of shock. In addition, the authors observe an intriguing observation that the total connectedness in higher quantile is large, followed by lower quantile.

This study is undertaken considering the novelty in the form of the proxies of examined markets along with natural outbreak (COVID-19) and man-made outbreak (Russia–Ukraine invasion) periods.