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The Electric Vehicles Initiative (EVI) is a multi-government policy forum devoted to speed up the introduction and adoption of electric vehicles (EVs) worldwide. EVI key themes for sustainable development include energy-efficient transportation with e-mobility (drive-by science and technology), reduced greenhouse gas emissions, decreased oil dependence and improved local air quality. India's transport sector contributes around 142 million tons of CO₂ every year, with road transport contributing 123 million tons.

Review methodology forms a basis for knowledge development, creating guidelines for policy and practice. Quality assessment of review articles is by using mixed methods appraisal tool (MMAT).

The research trends on Sustainable Development Goal (SDG) technological and social aspects highlight the critical role of technology in economic and social development, emphasising infrastructure development and communication of government policy and rewards for awareness and end-user acceptance.

The scenario brings a school of thought if it is equally important to address a social perspective to improve India's perception and acceptance of technology-enabled EVs.

The purpose of this paper is to assess the training needs based on top management view point for the development of frontline managers (FLM) of Indian power distribution companies (DISCOMs).

DISCOMs’ top managers were interviewed to develop questionnaire items. A total of ten items were identified; the response from the middle managers and FLM were collected with the help of a questionnaire on a five-point Likert type. The Cronbach’s alpha, face and content validity of instrument were performed. The sample population was 364 based on stratified probability proportional to size (PPS) sampling. The statistical tool used for data analysis was chi square through SPSS package.

Top management of DISCOMs for developing training program emphasizes on 10 organizational items. Which when assessed with middle and FLM of DISCOM, the results indicated a disagreement between their opinions suggesting practical implications on training need analysis at these DISCOMs.

The emphasis of top management for identifying the FLM training needs only acknowledges the work environment and customer requirements, whereas the personal and task related factors (other than customer services) affecting their performance are overlooked.

Reforms in the Indian power sector have been introduced only 26 years back. This study explicitly focuses on the DISCOMs at the central India. Present viewpoint of top management on the competency and training needs of their FLM. The Cronbach’s alpha and discriminant validity has been performed.

The purpose of this paper is to analyse how the government, Lelija management and society realized the fact that being a global organization unethical labor practices will reflect badly on human resources management, the company, and the reputation of the country as a whole.

In the analysis of social facts, knowledge also consists of already existing ethical norms and values derived from practice, definitely designated, explicitly articulated and unambiguously evaluated. It especially applies to business, professional, and organizational practice. In case analyses, the authors usually deal with events that are presented from a certain viewpoint. However, it is essential to follow the objectivized knowledge and articulated standards. As it will be discussed later, the major parts of information sources for the Lelija's case are competing daily newspapers of Lithuania, their web sites.

Social realities associated with employment are relations between employers and employees, a labor agreement, working conditions, tasks and compensation for its fulfilment. Irrespective of contradictions of the subjective interests and opinions that accompanied the reality of poor working conditions at Lelija, media outlets have provided a verifiable information about violations of labor laws and payment of fines as restitution.

The present case is prepared for classroom teaching since resort to the journalist material is not very suitable for investigative analysis of cases. It is important to distinguish between facts, evaluation and real circumstances where the facts emerged. This factor is well taken care by the authors while preparing the case.

The purpose of this paper is to examine the impact of research and development (R&D) tax credit scheme on participating firm’s R&D expenditure in Indian manufacturing firms.

Tobit model is used to estimate the impact of R&D tax credit scheme on R&D expenditure.

The results suggest that there is a positive and significant effect of R&D tax incentive scheme on R&D. The introduction of the R&D tax credit scheme and the policy amendment are positively influencing R&D investment of the participating firms. However, industry-specific results suggest that these positive results are mainly driven by electronic and pharmaceutical industries. The study reveals that import of technology, import of raw materials, competition, profitability, age and leverage position of the firm also positively influence the R&D intensity of the firm.

The study is limited to the listed manufacturing firms in India.

The study evaluates the innovation policy to help the policymakers in designing an effective policy.

The paper provides evidence on the impact of R&D tax incentive scheme on firm innovation to explain the factors that contribute to the R&D expenditure of the participating firms. It also summarises the effectiveness of tax incentive scheme on different industry groups and firm size.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.