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Indian financial sector has seen a dramatic change in recent years, with digital finance unlocking new possibilities for financial inclusion. This paper investigates the factors influencing the continuous usage intention and advocacy intention, regarding digital finance, in the Indian economy. Utilizing the Stimulus-Organism-Response (S-O-R) model, the study examines how ease of use, credibility and ubiquity (stimulus) could influence user trust, satisfaction, and engagement (organism), ultimately affecting their intention to use and recommend the service (response) continuously. Non-probability convenience sampling technique was used to select the study sample. Based on the results, features of digital financial platforms such as ease of use, credibility and ubiquity, were found to have a significant impact on user trust, satisfaction, and engagement. These factors partially mediate the stimulus and response variables. The research findings provide Digital Financial Service Providers (DFSPs) with practical guidance on creating and implementing user-centric platforms that create engagement and trust. User experience should be prioritized and making sure that platform should be accessible, easy to use and compatible with a variety of devices.

This study undertakes a bibliometric examination of the literature on supply chain sustainability (SCS). The analysis includes exploring co-authorship, examining keyword co-occurrences, conducting citation analysis, bibliographic coupling, co-citation analysis for performance evaluation, and employing science mapping techniques. The paper thus explores the significant facets of the literature on SCS. We studied the literature on SCS management from 1996 to 2024 and extracted 6898 articles retrieved from the Scopus database. In the preliminary phase, the investigation employs the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flow methodology alongside a designated search strategy. Secondly, it employs Biblioshiny, an RStudio package, and VOSviewer. The study finds that the SCS field has evolved with a major focus on collaboration, innovation, and sustainability. Furthermore, the findings indicate that China, the USA, the UK, and India lead in research contributions, emphasizing the importance of international collaboration. Additionally, the findings signpost that technology such as blockchain enhances sustainability efforts. Social sustainability also gains recognition alongside environmental concerns. These findings can inform researchers, highlighting the need for international cooperation, technology integration, and emphasis on social sustainability in advancing the management of supply chains. This study makes novel contributions by providing global coverage of publications, adopting an inclusive approach encompassing case studies and empirical research articles, addressing social desirability bias by reporting positive as well as negative aspects of sustainability in supply chain practices, and identifying alternative areas for future research within the discipline.

Energy is the most important factor for our daily lives, but traditional energy sources like coal, petroleum and gas were polluting the environment. To address this issue, people are considering energy-efficient technologies, which consume less energy and eco-friendly in nature. This paper investigates the factors influencing the intention to purchase of energy-efficient appliances in India. Utilizing the Technology Acceptance Model (TAM), the study examines how perceived ease of use, perceived usefulness, functional value, perceived cost, environmental concern affects their intention to purchase. Non-probability convenience sampling technique was applied. Based on the results, perceived ease of use, perceived usefulness, functional value, perceived cost, environmental concern positively influences the intention to purchase energy-efficient appliances. The eco-friendly purchasing behaviour has significant societal implications, including reduced carbon emissions, conservation of natural resources and environmental sustainability.

Cryptocurrency is rapidly emerging as a prominent player in the global financial system, characterized by its decentralized nature and the absence of centralized government oversight. However, this autonomy raises significant environmental concerns primarily stemming from the energy-intensive mining process. Crypto mining, central to the creation of new coins and transaction validation, results in substantial carbon emissions and energy consumption. This study employs bibliometric analysis using RStudio to scrutinize the data sourced from the Scopus database. Data selection adhered to specific inclusion criteria, focusing on research articles and documents in the English language. Exclusion criteria targeted the elimination of review papers, conference reviews, short surveys, notes, and articles in languages other than English. China emerges as the foremost contributor with a frequency of 348 and a total citation count of 1259, followed by the USA with 594 citations. Notably, the keywords ''blockchain'' and ''bitcoin'' surface most frequently, occurring 293 and 148 times, respectively. The study posits that China's decision to ban cryptocurrency due to economic concerns has likely contributed to heightened global awareness of cryptocurrencies. In contrast, the USA has actively embraced cryptocurrencies, fostering their widespread circulation. Consequently, these two countries have emerged as leading contributors to energy consumption in the cryptocurrency sector. Blockchain, originally a broad concept, has found applications in diverse domains such as marketing, finance, healthcare, supply chain, and the Internet of Things (IoT). This widespread adoption has expanded the scope of energy consumption considerations from cryptocurrencies to encompass blockchain technology as a whole. Future research should focus on mining regulation, alternative mechanisms, renewable energy sources, technological advancements, and carbon offsetting solutions. The article also addresses its limitations and the future scope of the study in detail.

The present study proposes to investigate the influence of the covid-19, on the adjusted closing price of the digital currency based on energy consumption during the process of mining. The study employed the secondary data analysis of top ten market capitalization of cryptocurrencies with the combination of high energy consume mechanism (proof of work) and low energy consume mechanism (proof of stake). Statistical tools like Descriptive analysis,Augmented Dickey-Fuller (ADF) test, ARCH, and GARCH models were used in the study. The present study finds that the prices of cryptocurrencies were highly volatile. This study could assist investors towards better understanding of the dynamics of the cryptocurrency market based on energy consumption which helps them to make more effective decisions, on investing cryptocurrencies with a scientific approach.

The aim of the study was to investigate the presence of volatility among the Energy Indices of Asia Pacific Stock Markets. To test the volatility among the daily returns of Energy Indices of Asia Pacific Stock Markets, the study selected five sample Asian Pacific stock markets’ Energy Indices on the basis of availability of data. The findings of descriptive statistics and the ADF Test revealed, that the daily returns of the sample energy indices of Asian Pacific stock markets were not normally distributed and achieved stationarity at level difference, over the research period. Hence the data may be used for additional analysis. The data were then analysed, by using the GARCH (1,1) model to assess the considerable volatility of daily returns of sample energy indices and the study, which revealed that during the study period, all of the sample energy indices were volatile.

The purpose of this research was to examine the dynamics of volatility spillover between energy and environmental, social, and sustainable indices. COVID19 prompted the research to select April 2019 to March 2022 as a sample period, and the respective data (Daily Prices) of the Nifty Energy and Nifty ESG indices were obtained from the National Stock Exchange of India Limited. The outcomes of the study confirmed that the daily returns of Nifty Energy and Nifty 100 ESG indices were not normally distributed and reached stationarity at level difference. Further, the study employed GARCH Models such as ARCH, GARCH (1,1), and GARCH-M to determine conditional volatility, and it validated the ARCH influence on the daily returns of the Nifty Energy and Nifty 100 ESG, during the study period

The research intends to assess the efficiency of NSE Energy Index-listed firms throughout the COVID-19 before and post pandemic phases, which run from 2019 to 2021. The primary goal of this article was to examine the price movement of corporations in the petroleum, gas, and electricity sectors by employing statistical methods such as descriptive statistics, ADF, and the GARCH (1,1) model, during the period of study. When comparing the post-COVID-19 pandemic era to the pre-COVID-19 pandemic period, certain firms experienced excessive volatility. The energy market's investor sentiment was significantly higher on the tail events, suggesting that anxious investors raced to put options and paid an exorbitant premium to shield them against unprecedented danger in the energy market.

The goal of this study is to look into how changes in crude oil prices affect GDP per capita and exchange rate fluctuations.to investigate the influence of crude oil price shocks on GDP per capita and exchange rate movements. This research employed yearly time series data for the price of crude oil, exchange rate (USD/INR), and GDP per capita, from 1990 to 2020. Arithmetical tools such as Descriptive, Unit Root, Granger Causality Test, and OLS Model were applied. The present study discovered a strong bi-directional Granger causality effect of Dubai crude oil prices on exchange rates, as well as a bi-directional Granger influence of exchange rates on WTI crude oil prices. The diagnostic tests were successfully passed by the estimated models. According to the OLS model, the exchange rate was driven only by the price of Dubai crude oil, although the price of WTI crude oil influenced both the GDP per capita and the exchange rate over the research period. The key policy recommendation derived from this analysis is that the Reserve Bank of India (RBI) must depreciate the rupee, first to restore much-needed exchange rate stability, then to stimulate domestic manufacturers, and finally, to attract foreign capital inflows.