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Sustainable development goals (SDGs) designed by the United Nations include ‘universal and equitable access to affordable, reliable and clean energy’ as one of the pathways to achieve a better and more sustainable future by 2030. Universal access to electricity, clean cooking fuel, increasing share of renewable resources and improving energy efficiency are the key components of SDG7. In India, the government has undertaken targeted programmes to ensure full electrification of households and greater use of liquid petroleum gas (LPG) for clean cooking replacing traditional solid biomass fuels in poor households. Installed capacity targets are set to raise the share of renewable resources in total energy mix along with the policies undertaken to make it cost-competitive (SDG India, 2019–2020). However, the economic crisis experienced by India during COVID-19 pandemic is likely to affect this ongoing drive towards clean energy use. Sudden fall in income and loss of employment particularly in the unorganised sector might have made the poor rural households vulnerable to reversion to their traditional cooking fuels. The renewable sector has also faced uncertainties due to halted construction works and disrupted global supply chains during lockdown. The present chapter discusses these pertinent issues crucial for achieving SDGs. It investigates how far the COVID-19-driven economic crisis has delayed India's clean cooking fuel programme for different states. It further examines the impact of COVID-19 lockdown on renewable energy sector, particularly on the solar energy sector. The study suggests some policy measures for a robust recovery, ensuring transition towards clean energy use and sustainable growth to protect the environment.

Websites, search engines, recommender systems, artificial intelligence and digital libraries have the potential to support serendipity for unexpected interaction with information and ideas which would lead to favored information discoveries. This paper aims to explore the current state of research into serendipity particularly related to information encountering.

This study provides bibliometric review of 166 studies on serendipity extracted from the Web of Science. Two bibliometric analysis tools HisCite and RStudio (Biblioshiny) are used on 30 years of data. Citation counts and bibliographic records of the papers are assessed using HisCite. Moreover, visualization of prominent sources, countries, keywords and the collaborative networks of authors and institutions are assessed using RStudio (Biblioshiny) software. A total of 166 papers on serendipity were found from the period 1989 to 2022, and the most influential authors, articles, journals, institutions and countries among these were determined.

The highest numbers of 11 papers were published in the year 2019. Makri and Erdelez are the most influential authors for contributing studies on serendipity. “Journal of Documentation” is the top-ranking journal. University College London is the prominent affiliation contributing highest number of studies on serendipity. The UK and the USA are the prominent nations contributing highest number of research. Authorship pattern for research on serendipity reveals involvement of single author in majority of the studies. OA Green model is the most preferred model for archiving of research articles by the authors who worked on serendipity. In addition, majority of the research outputs have received a citation ranging from 0 to 50.

To the best of the authors’ knowledge, this paper may be the first bibliometric analysis on serendipity research using bibliometric tools in library and information science studies. The paper would definitely open new avenues for other serendipity researchers.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

Electric Vehicles (EVs), owing to their low carbon emissions, have gained immense importance in achieving net-zero emissions by 2070. They have also appeared as viable substitute to conventional vehicles. Aligning with global initiatives, India has created a favourable ecosystem and has implemented several policies since 2011 to achieve its target. Consequently, the market share of EVs has surged, both globally and in India, over the past decade. Taking this into account, this study aims to identify the factors that influence EVs in a developing economy using the context of India.

This study identified important determinants of EV adoption from global literature and employed a multiple linear regression model (MLRM) using the ordinary least squares (OLS) technique. Secondary data were utilised to identify determinants in the Indian context, sourced from the Ministry, NITI Aayog, AQI, the Lok Sabha Question, and the Economic Survey of India.

This study found that the number of charging stations and local pollution levels significantly influence EV adoption in India. The insignificance of the other variables may be due to the emerging state of the Indian EV market.

This study adds to the growing body of literature on EV adoption in developing economies by analysing the factors that impact its adoption using regional data. In addition, this study provides a unique perspective on a developing economy and advocates a comprehensive policy for EV adoption that reflects long-term sustainability.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0479.