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The utilisation of renewable energy sources for generating electricity and potable water is one of the most sustainable approaches in the current scenario. Therefore, the current research aims to design and develop a novel co-generation system to address the electricity and potable water needs of rural areas.

The cogeneration system mainly consists of a solar parabolic dish concentrator (SPDC) system with a concentrated photo-voltaic module at the receiver for electricity generation. It is further integrated with a low-temperature thermal desalination (LTTD) system for generating potable water. Also, a novel corn cob filtration system is introduced for the pre-treatment to reduce the salt content in seawater before circulating it into the receiver of the SPDC system. The designed novel co-generation system has been numerically and experimentally tested to analyse the performance at Karaikal, U.T. of Puducherry, India.

Because of the pre-treatment with a corn cob, the scale formation in the pipes of the SPDC system is significantly reduced, which enhances the efficiency of the system. It is observed that the conductivity, pH and TDS of seawater are reduced significantly after the pre-treatment by the corncob filtration system. Also, the integrated system is capable of generating 6–8 litres of potable water per day.

The integration of the corncob filtration system reduced the scaling formation compared to the general circulation of water in the hoses. Also, the integrated SPDC and LTTD systems are comparatively economical to generate higher yields of clean water than solar stills.

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 paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.

Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.

The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.

The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.

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.

This study explores match related factors and their impact on the batting strike rate in Twenty20 cricket – an aspect which can generate excitement and fan engagement in cricket matches.

Data was collected from www.cricinfo.com using a web scraping tool based on R programming from February 17, 2005, to October 25, 2022, numbering 4,221 men’s Twenty20 international innings featuring 41 national teams that had taken place in 85 venues across 11 countries of play. Hypothesis testing was conducted using one-way ANOVA.

The findings indicate that batters score faster in the first inning of a match, and mean strike rates also vary significantly based on the country of play. Further, the study analyses the top performing national sides, venues and country of play in terms of mean batting strike rate, thus providing insights to cricket boards, international regulating bodies of cricket, sponsors, media companies and coaching staff for better decision-making based on batting strike rate.

The originality of the study lies in its focus on using non-marketing strategies to increase fan engagement. Further, this study is the first one to examine different venues from the perspective of batting strike rate in men’s Twenty20 international matches.

The present study aims to examine the relationship between green economic incentives (GEIs) and environmental commitment (EC) as drivers of the circular economy (CE) practices in small and medium enterprises (SMEs).

A cross-sectional study of 594 assistant managers and SME managers was used while data were analyzed through Smart PLS.

The results showed that GEIs positively affect the SMEs' EC and the CE practice model. Furthermore, EC is the mediator between GEIs and the three CE practices: internal environmental management, eco-design and corporate asset management and recovery (CAM&R).

The present study provided a basis for understanding the relevance of SMEs' CE practices and designing a strategic plan for its implementation. Also, it provides insight into that collaboration between triple helix (the government, SMEs and the community) is needed in increasing environmental awareness toward sustainability.

This study enhanced the natural resource-based view (NRBV), describing the mechanisms that view GEIs and EC as pollution prevention in CE practice.

This study aims to identify and prioritize the key practices and strategies for effective global sourcing and supply chain management (SCM).

The study uses a combination of Pareto analysis and multi-objective optimization based on ratio analysis research methodology to analyze and establish the relationships among the identified key practices and strategies. Pareto analysis enables organization to prioritize organizational efforts and resources by focusing on the most critical factors.

The study shows that the “eco-friendly sourcing strategy”, “lean manufacturing” and “tool cost analysis” are the top critical practices and strategy variables for global sourcing and SCM, whereas the “risk management”, “procurement strategy” and “leverage digital solutions” are the critical practices and strategy variables.

The findings of this research can also assist organizations in making informed decisions to optimize their global sourcing and supply chain operations.

By using these methods, this research paper gives valuable insights into the critical practices and strategies that can enhance efficiency, mitigate risks and drive success in global sourcing and SCM. The subjects and elements this study identified will serve as a framework and suggestions for further theoretical investigation and real-world implementations.

Industrialisation has contributed to global environmental problems, especially in developed countries, but increasingly so in developing ones as well. The rising public concern for the natural environment is compelling business entities to revise their business models towards green lean (GL) management. Most manufacturing firms have realised that GL implementation is a critical factor that drives their success. Therefore, keeping in view the above said aspects, the purpose of this paper is to empirically assess the complementary impact of GL practices on environmental performance.

Data from a sample of 124 Indian manufacturing industries are analysed using a structural equation modelling technique.

Evidence suggests that GL practices such as top management commitment, government support, human resource management, health and safety of employees and public pressure and legislature have significantly positive effect on environmental performance of manufacturing industries.

The sample is limited to Indian manufacturing industries situated in northern region, with a low response rate.

Successful implementations of GL practices can lead to improved environmental performance. Manufacturing industries within emerging economies like India can improve on their GL practices by incorporating these findings into their business models, while research could be guided to focus their inquiries on this and related genres of scholarly work.

To the best of the authors’ knowledge, this study is one of the first to empirically assess the complementary impact of GL practices on environmental performance within the Indian context.