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The purpose of this study is to investigate the challenges before India for electric vehicle (EV) adoption by 2030. The study further looks into the measures taken by the Government of India (GOI) to promote research and development in EV sector and what is yet to be done.

In the present study, the challenges are identified allied to the commercialization of EVs in India. The data are collected, analyzed and compiled through secondary sources. The secondary data give a concise insight and comprehensive information regarding what is occurring around the globe as well as in the Indian context. Further, the challenges are investigated through a focus group study consisting of 11 participants from industry and academia.

The findings from the study are the critical roles of sharing economy and public utilities in the promotion of EV adoption, given the high cost of EV, lack of infrastructure and poor purchasing power of Indian customers. The sharing economy perspective provides various opportunities for the government to manage the resources (electric-powered transport system) optimally. Further, the study compares the global perspective in assigning the target figures.

The study highlights the facilitating role of the shared format in EV technology promotion but ignores the hurdles that can come in its implementations. Also, the focus group study has its limitation as it relies more on participants' perceptions and opinions.

The present study assists GOI and various stakeholders in having a realistic plan rather than daydreaming with overambitious goals. The diffusion of technology as a shared format (especially in the context of EV) has not been academically approached in the past literature.

The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).

Author first reviewed the related work, and then, the research model designed was explained. Furthermore, the details regarding Levels 1 and 2 were narrated.

By using the proposed technique, F_Score obtained for Twitter and Facebook data set was 96.22 and 94.63, respectively.

Four data sets were used for the experiment and the acquired outcomes demonstrate enhancement over the current existing frameworks.

This paper designed a multilevel framework that can be used to detect the anomalies present in the OSN.

As the COVID-19 epidemic ravages the world in the fourth industrial revolution era, the manufacturing sector faces its worst situation in a century. Lean philosophy, renowned as a “warrior philosophy,” can be an able rescuer to these industries. This study aims to identify the hurdles to lean strategy implementation and conduct an analysis to provide cognizance to policymakers, practitioners and decision-makers.

This study aims to identify the obstacles that obstruct lean implementation into seven primary barriers/components, with the fuzzy DEMATEL approach being used to evaluate the critical factors as well as the cause and effect factors among them. Expert opinions are sought to obtain the relevant data for evaluation purposes.

The results reveal that a firm should focus on firm cultural conflict scenario, resources–responses incapability, improve on suppliers’ attitude and execute a proper planning and logistics equation to alleviate the hindrances of implementing lean. As these causal factors influence the effect factors, namely, top management vision, management–employee relationship and human resource building, focusing on them automatically improves the effect factors; thus, the surge to overcome resistance to lean implementation is alleviated.

This research aids in identifying and analyzing lean implementation issues in the manufacturing and industrial sectors. The observations, results and insights drawn can act as a guiding force to rupture the resistance envelope covering the domain of lean implementation and possibly reinstating industries to survive and excel in the business post-COVID era.

This research introduces barriers to lean implementation in a unique way, as it articulates all sections of an industry and group the barriers based on the classification. It further prioritizes the barriers for their importance in the Indian industrial scenario. This would help the industry professionals and managers access the barriers and generate insight on how and where to start implementing lean.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The purpose of this paper is to evaluate the effect of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃) nanoparticles-reinforced pure aluminium (Al) on the mechanical properties of hybrid aluminium matrix nanocomposites (HAMNCs).

The HAMNCs were fabricated via a vacuum die-assisted stir casting route by a two-step feeding method. The varying weight percentages of TiO₂ and Y₂O₃ nanoparticles were added as 2.5, 5, 7.5 and 10 Wt.%.

Scanning electron microscope images showed the homogenous dispersion of nanoparticles in Al matrix. The tensile strength by 28.97%, yield strength by 50.60%, compression strength by 104.6% and micro-hardness by 50.90% were improved in HAMNC1 when compared to the base matrix. The highest values impact strength of 36.3 J was observed for HAMNC1. The elongation % was decreased by increasing the weight percentage of the nanoparticles. HAMNC1 improved the wear resistance by 23.68%, while increasing the coefficient of friction by 14.18%. Field emission scanning electron microscope analysis of the fractured surfaces of tensile samples revealed microcracks and the debonding of nanoparticles.

The combined effect of TiO₂ and Y₂O₃ nanoparticles with pure Al on mechanical properties has been studied. The composites were fabricated with two-step feeding vacuum-assisted stir casting.

The study aims to explore and test the integrated relationships between university reputation and its key antecedents. In doing so, theoretically derived antecedents of university reputation were examined. The study reports the complex interplay among image, quality, value, satisfaction and attachment and their subsequent effect on reputation.

A quantitative method was used to achieve research objectives. Data collected from students enrolled in major private university in Northern India were analysed to test the proposed model directly and indirectly using structural equation modelling (SEM).

The findings confirmed most of the hypothesised relationships. Prominently, image construct was found to be significantly affecting students' quality perceptions along with satisfaction, attachment, value and importantly reputation. The study found evidence for the impact of students' attachment on university reputation. Findings also indicated the presence of several indirect relationships among the considered dimensions.

Current research offers implications for universities that are met with the perpetual challenge of survival in the competitive higher education (HE) marketplace. Findings from the study not only help build theory on university reputation but make essential contribution towards guiding managers in developing effective strategies by building reputation via concentrating on the most crucial determinants.

Although research in HE marketing is growing, effects of student attachment towards building reputation has not garnered attention, which is theoretically a vital construct. The paper presents new framework to realise university reputation with the help of integrated relationships among select dimensions in the setting of an emerging HE market.

The purpose of this study is to increase the wear resistance of Mg alloy by adding hard ceramic particles to it. The inclusion of hard ceramic particles further strengthen the Mg alloy, resulting in higher wear resistance. Mg alloys containing Zn, rare earth and Zr exhibit high specific strength and excellent creep resistance, making them suitable for aerospace components such as aircraft gearboxes and generator housings.

In the present study, composites have been produced in situ by using RZ5 mg alloy as matrix and TiC as reinforcement by self-propagating high-temperature synthesis technique. The abrasive wear behavior of RZ5 Mg alloy matrix reinforced with TiC particulates has also been examined. The pin-on-disc apparatus has been used for the tests. The abrasive paper is used as a counter body, and the results are obtained by changing sliding distance and applied load.

A notable enhancement in the wear resistance and mechanical properties of tested composite has been observed as compared to the RZ5 Mg alloy as a matrix. There is a uniform increment in the change in weight loss of RZ5-TiC composite with increasing sliding distance and applied load, but it decreases with increasing TiC content. The coefficient of friction (µ) also decreases uniformly with an increase in the reinforcement of TiC, but it decreases with an increase in applied load and sliding distance. The investigation of the worn composite, which determines dominant wear mechanisms as abrasion and plowing grooves on tested samples, has been done using field emission scanning electron microscopy.

The current manuscript provides a detailed abrasive wear analysis of RZ5-TiC composite by using different wear parameters. Specifically, extensive experimental data have been provided for RZ5-TiC composite. The effects of parameters such as applied load, sliding distance and Wt.% of TiC on the weight loss and coefficient of friction of the composites have been analyzed and discussed thoroughly.

Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks. This study aims to assess how knowledge related to CSAPs, male out-migration, education and income contribute to the determinants of male out-migration and CSAPs adoption and how they respond to household food security.

Sex-disaggregated primary data were collected from adopter and non-adopter farm families. STATA 13.1 was used to perform principle component analysis to construct knowledge, yield and income indices.

Yield and income index of adopters was higher for men than women. The probability of out-migration reduced by 21% with adoption of CSAPs. An increase in female literacy by 1 unit reduces log of odds to migrate by 0.37. With every unit increase in knowledge index, increase in log-odds of CSAPs adoption was 1.57. Male:female knowledge gap was less among adopters. Non-adopters tended to reduce food consumption when faced with climatic risks significantly, and the probability of migration increased by 50% with a one-unit fall in the nutrition level, thus compelling women to work more in agriculture. Gender-equitable enhancement of CSAP knowledge is, therefore, key to safeguarding sustainable farming systems and improving livelihoods.

The enhancement of gender equitable knowledge on CSAPs is key to safeguard sustainable farming systems and improved livelihoods.

This study is based on the robust data sets of 100 each of male and female from 100 households (n = 200) using well-designed and validated survey instrument. From 10 randomly selected climate-smart villages in Samastipur and Vaishali districts of Bihar, India, together with focus group discussions, the primary data were collected by interviewing both men and women from the same household.

The advancement in modern manufacturing technology generated the need to develop new materials for better wear resistance. The purpose of this paper is to use the Taguchi optimization approach to examine which wear parameter significantly affects weight loss and coefficient of friction for RZ5-TiC composite. It is a simple and efficient method to find performance of wear parameter using minimum experimental runs.

RZ5-TiC composites were prepared using RZ5 as matrix, reinforced with TiC through self-propagating high-temperature synthesis technique. In the present work, an attempt has been made to study the influence of wear parameters like applied load (AL), sliding distance (SD) and Wt.% of TiC (WTC) on responses like weight loss and coefficient of friction of RZ5/TiCp composites. The pin-on-disc apparatus used to conduct abrasive wear test. The wear process parameters are optimized for minimum wear based on L27 Taguchi orthogonal design. The Taguchi technique using design of experiments (DOE) is used to obtain the data. The ANOVA and an orthogonal array are used to examine the influence of wear parameters on responses. The purpose is to examine parametric significances which affect responses.

It observed that wear parameters have the significant influence on responses of RZ5/TiCp composites. The interaction of sliding distance/Wt.% of TiC is observed and found significant influence on both responses. The optimum level of the significant wear parameters is achieved based on the maximum S/N ratio for RZ5/TiCp composites. The optimal interaction for weight loss and coefficient of friction is AL1-SD1-WTC3 and AL3-SD1-WTC3, respectively. Finally, the confirmation test is conducted and the results are obtained within the confidence interval.

The current manuscript provides an optimization of wear parameters using Taguchi approach. The extensive experimental data are used for this purpose and effects of wear parameters on responses are analyzed from the presented results. The results obtained are useful in improving the wear resistance of the RZ5-TiC composite.

In the present scenario, the demand for additive manufacturing (AM) has increased. Taking into account environmental problems and sustainability, manufacturers are now also considering the environmental and sustainability criteria in their decision-making process. The sustainability concept is known as the triple-bottom line, namely, economic, social and environmental perspectives. Sustainable concept selection in the manufacturing organisation can be considered as the selection of sustainable material, product design, process, method and technology. This study aims to select an appropriate AM process by considering sustainability from various available techniques.

Appropriate sustainable performance indicators for the AM were identified based on literature as well as in discussion with experts and decision-makers. The model addresses all the major dimensions of sustainable concepts of AM such as material/product quality, machine performance, market stability, total cost and ecological values. A hybrid multi-criteria decision-making approach, i.e. stepwise weight assessment ratio analysis and complex proportional assessment methods, have been used to select the best AM technique. While selecting criteria affecting AM machines and processes, criteria based on the sustainable concept are considered.

Among the four selected AM processes, i.e. fused diffusion modelling (FDM), laminated object manufacturing (LOM), stereolithography apparatus (SLA) and selective laser sintering (SLS), the best alternative was found to be FDM.

The present study highlights some limitations in the selection of AM process and methodology used in this research. This study considers only four AM processes, i.e. FDM, LOM, SLA and SLS. Future work may include considering other AM processes and criteria that affect the sustainability of AM.

The present work will help researchers and production managers to decide the best AM alternatives to fabricate desired parts. Hence, AM can help in maximum energy utilisation, optimal consumption of resources, minimum material wastage and reduction of CO₂ emission.

The study considers some important criteria, including energy consumption, eco-friendly and wastage-free production, that help sustainable AM. This study can result in a good economic efficiency of AM industries and, therefore, positively impact customers using green products.