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Conventional isolated dc–dc converters offer an efficient solution for performing voltage conversion with a large improved voltage gain. However, the small-signal analysis of these converters shows that a right-half-plane (RHP) zero appears in their control-to-output transfer function, exhibiting a nonminimum-phase stability. This RHP zero can limit the frequency response and dynamic specifications of the converters; therefore, the output voltage response is sluggish. To overcome these problems, the purpose of this study is to analyze, model and design a new isolated forward single-ended primary-inductor converter (IFSEPIC) through RHP zero alleviation.

At first, the normal operation of the suggested IFSEPIC is studied. Then, its average model and control-to-output transfer function are derived. Based on the obtained model and Routh–Hurwitz criterion, the components are suitably designed for the proposed IFSEPIC, such that the derived dynamic model can eliminate the RHP zero.

The advantages of the proposed IFSEPIC can be summarized as: This converter can provide conditions to achieve fast dynamic behavior and minimum-phase stability, owing to the RHP zero cancellation; with respect to conventional isolated converters, a larger gain can be realized using the proposed topology; thus, it is possible to attain a smaller operating duty cycle; for conventional isolated converters, transformer core saturation is a major concern, owing to a large magnetizing current. However, the average value of the magnetizing current becomes zero for the proposed IFSEPIC, thereby avoiding core saturation, particularly at high frequencies; and the input current of the proposed converter is continuous, reducing input current ripple.

The key benefits of the proposed IFSEPIC are shown via comparisons. To validate the design method and theoretical findings, a practical implementation is presented.

This study examines the relationship between multi-layer supply chain flexibility (MSCF) and Supply chain resilience (SCR). Further, it looks at the moderating effect of environmental dynamism (ED) and supply chain risks (SCRI) on the relationship between MSCF and SCR.

Executives from the pharmaceutical, agri-food, electronics, automobile and textile industries were invited to complete a self-administered questionnaire. We received feedback from a total of 302 participants. Prior to conducting the primary analysis, we addressed the potential for nonresponse bias and verified the assumptions of homoscedasticity and normal distribution of the data. The reliability and validity of the constructs were established through confirmatory factor analysis. Structural equation modelling is employed for the purpose of conducting hypothesis testing.

The results demonstrate a notable influence of MSCF on SCR, particularly in settings characterized by high levels of ED and SCRI. The study highlights the importance of flexibility in multiple aspects of the supply chain to build resilience against a range of disruptions and uncertainties.

The study presents the fundamental role of Multi-Layer Flexibility in building up SCR. The results of this study reinforce the existing literature and offers empirical evidence for how ED, SCRI moderates the influence between MSCF to SCR. These results offer valuable information to both supply chain specialists and researchers for building comprehensive strategy to bring resilience in supply chains.

Despite the susceptibility of cotton crops to pest attacks in the Malwa Region of Indian Punjab, no crop insurance policy has been implemented there– not even the Pradhan Mantri Fasal Bima Yojana (PMFBY), which is a central scheme. Therefore, this paper attempts to gauge the likely impact of the PMFBY on Punjab cotton farmers and assess the changes needed for greater uptake and effectiveness of PMFBY.

The authors have conducted a primary survey to conduct this study. Initially, the authors compared the costs of cotton production with the returns in two scenarios (with and without insurance). Additionally, the authors have applied a logistic regression framework to examine the determinants of the willingness of farmers to participate in the crop insurance market.

The study finds that net returns of cotton crops are conventionally small and insufficient to cope with damages from crop failure. Yet, PMFBY will require some modifications in the premium rate and the level of indemnity for its greater uptake among Punjab cotton farmers. Additionally, using the logistic regression framework, the authors find that an increase in awareness about crop insurance and farmers' perceptions about their crop failure in the near future reduces the willingness of the farmers to participate in the crop insurance markets.

The present study looks for the viability of PMFBY in Indian Punjab for the cotton crop, which can also be extended to other crops.

Punjab could also use crop insurance to encourage diversification in agriculture. There is a need for special packages for diversified crops under any crop insurance policy. Crops susceptible to volatility due to climate-related factors should be identified and provided with a special insurance package.

There exist very scant studies that have discussed the viability of a central crop insurance scheme in the agricultural-rich state of India, i.e. Punjab. Moreover, they do not also focus on crop losses accruing due to pest and insect attacks.

Efforts to implement supplier selection and order allocation (SSOA) approaches in small and medium-sized enterprises (SMEs) are quite restricted due to the lack of affordable and simple-to-use strategies. Although there is a huge amount of literature on SSOA techniques, very few studies have attempted to address the issues faced by SMEs and develop strategies from their point of view. The purpose of this study is to provide an effective, practical, and time-tested integrated SSOA framework for evaluating the performance of suppliers and allocating orders to them that can improve the efficiency and competitiveness of SMEs.

This study was conducted in two stages. First, an integrated supplier selection approach was designed, which consists of the analytic hierarchy process and newly developed measurement alternatives and ranking using compromise solution to evaluate supplier performance and rank them. Second, the Wagner-Whitin algorithm is used to determine optimal order quantities and optimize inventory carrying and ordering costs. The joint impact of quantity discounts is also evaluated at the end.

Insights derived from the case study proved that the proposed approach is capable of assisting purchase managers in the SSOA decision-making process. In addition, this case study resulted in 10.89% total cost savings and fewer stock-out situations.

Criteria selected in this study are based on the advice of the managers in the selected manufacturing organizations. So the methods applied are limited to manufacturing SMEs. There were some aspects of the supplier selection process that this study could not explore. The development of an effective, reliable supplier selection procedure is a continuous process and it is indeed certainly possible that there are other aspects of supplier selection that are more crucial but are not considered in the proposed approach.

Purchase managers working in SMEs will be the primary beneficiaries of the developed approach. The suggested integrated approach can make a strategic difference in the working of SMEs.

A practical SSOA framework is developed for professionals working in SMEs. This approach will help SMEs to manage their operations effectively.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

The objective of this research is to investigate the barriers impacting the integration of Industry 5.0 (I5.0) in supply chain sustainability. By understanding these challenges, this study aims to provide valuable insights that can guide organizations in successfully implementing the transformative potential of I5.0. The ultimate aim is to improve operational efficiency and advocate for sustainable practices within supply chains.

Research has used industry expert interviews, a comprehensive literature review and the decision-making trial and evaluation laboratory approach for analysis. Industry expert interviews serve to capture first-hand insights from professionals well versed in the field, providing practical perspectives on the barriers to I5.0 adoption.

This study identifies technological challenges, organizational barriers, regulatory impediments and economic constraints as pivotal factors inhibiting the widespread adoption of I5.0 in supply chain sustainability.

This research serves as a foundation for future investigations into overcoming barriers to I5.0 adoption, guiding scholars and practitioners in refining strategies for successful implementation.

The findings offer practical insights for organizations aiming to adopt I5.0, informing decision-makers on key challenges and facilitating the development of targeted strategies to overcome them.

The social implications lie in fostering sustainable business practices through the adoption of I5.0, contributing to environmental responsibility and societal well-being.

This research contributes original insights from practitioners, policymakers and researchers in navigating the complex landscape of I5.0 adoption, ensuring meaningful contributions to both academia and industry.

The pressing issues of climate change and environmental degradation call for a reevaluation of how we approach economic activities. Both leaders and corporations are now shifting their focus, toward adopting practices and embracing the concept of circular economy (CE). Within this context, the Food and Beverage (F&B) sector, which significantly contributes to greenhouse gas (GHG) emissions, holds the potential for undergoing transformations. This study aims to explore the role that Artificial Intelligence (AI) can play in facilitating the adoption of CE principles, within the F&B sector.

This research employs the Best Worst Method, a technique in multi-criteria decision-making. It focuses on identifying and ranking the challenges in implementing AI-driven CE in the F&B sector, with expert insights enhancing the ranking’s credibility and precision.

The study reveals and prioritizes barriers to AI-supported CE in the F&B sector and offers actionable insights. It also outlines strategies to overcome these barriers, providing a targeted roadmap for businesses seeking sustainable practices.

This research is socially significant as it supports the F&B industry’s shift to sustainable practices. It identifies key barriers and solutions, contributing to global climate change mitigation and sustainable development.

The research addresses a gap in literature at the intersection of AI and CE in the F&B sector. It introduces a system to rank challenges and strategies, offering distinct insights for academia and industry stakeholders.

The main aim of this study is to explore the relationship between information system flexibility and dynamic capabilities to build sustainable and net zero supply chains under the influence of environmental dynamism.

We have formulated a self-administered survey, with 359 participants contributing responses. Prior to delving into foundational assumptions, such as homoscedasticity and normality, a nonresponse bias analysis was executed. The integrity of the data, in terms of reliability and construct validity, was gauged using confirmatory factor analysis. Subsequent regression outputs corroborated all the proposed assumptions, fortifying the extant scholarly literature.

The empirical findings of this research underscore a positive correlation between Information system flexibility, dynamic capabilities and a net zero supply chain, especially in the context of environmental dynamism. Data sourced from the cement manufacturing sector support these observations. We also found that environmental dynamism moderates the relationship between data analytics capability and sustainable supply chain flexibility but does not moderate the relationship between Resource flexibility and sustainable supply chain flexibility. Additionally, this research strengthens the foundational principles of the dynamic capability theory.

The conceptual framework elucidates the interplay between information system flexibility, dynamic capabilities, and sustainable supply chain flexibility, emphasizing their collective contribution towards achieving sustainable chain net zero, introducing environmental dynamics as a moderating variable that augments the scholarly discourse with a nuanced layer of analytical depth.