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This paper aims to analyse the weekday effect on the Nifty Shariah indices as per the Islamic calendar. The study is intended to know about the return and volatility of these indices during Ramadhan and non-Ramadhan days.

The study focuses on analysing the Nifty Shariah indices and Sensex daily returns collected from NSE India and BSE India, respectively, during the period of 1 August 2016 to 31 July 2022. Descriptive statistics are used to analyse the data, while the Ordinary Least Square method is used to determine the impact of weekdays on the Nifty Shariah indices. Additionally, the study applies the GARCH statistical model to examine the influence of Ramadhan on the returns and volatility of the Nifty Shariah indices.

All of the Nifty Shariah indices produced positive returns during the overall sample period. According to the study, Tuesday index returns outperform other weekdays. The GARCH model indicated that the coefficient values for the Nifty 50 Shariah and Nifty 500 Shariah indices were negative. Ramadhan has a strong negative effect on volatility, according to this study.

The outcomes of the research are beneficial for investors aiming to exploit daily or weekly price fluctuations, rather than pursuing extended investment periods. Furthermore, fund managers can employ these findings to shape trading strategies, and academics can examine the performance of Shariah indices in the Indian context. This enables devout investors to make significant financial choices, thus advancing ethical values in society and upholding standards of both public and private morality.

The purpose of this study of M&A in relation to sustainability aims to create synergies that drive both financial performance and positive environmental and social outcomes, aligning business objectives with broader societal goals. The study can help in understanding the structure, collaborations and recent keywords and topics that are related to M&A in relation to sustainability.

This study applies comprehensive bibliometric analysis on performance analysis and science mapping of the scholarly literature related to M&A in relation to sustainability published between 2004 and 2024 in 196 publications on Web of science and Scopus by leveraging biblioshiny within R Studio and the VOS viewer software for enhanced visualization and interpretation of the bibliometric data.

This study helps to find out the co-occurrence analysis, bibliographical coupling and keyword analysis. Moreover, it scrutinizes patterns of collaboration among researchers, institutions and nations, shedding light on the global reach and influence of scholarly contributions in the field of M&A in relation to sustainability.

This study identified trends can help scholars, policymakers and business experts to study M&A through the lens of sustainability.

This bibliometric study of M&A in relation to sustainability can drive positive change by promoting responsible business practices, fostering innovation and creating value for both shareholders and society as a whole.

The paper concludes by finding emerging topics of the research and future directions, it gives a good input to extend the line on the graph. This study provides overview of 20 years of research on M&A in relation to sustainability and discusses its findings to identify the research gap.

The world of investing has changed drastically. Investors are willing to invest the companies that give high priority to environmental, social and governance issues (ESG). This study delves into the performance of the BSE CARBONEX index in comparison to the BSE 100, BSE Sensex, BSE Energy and BSE Oil & Gas. It seeks to examine the impact of calendar anomalies, particularly focusing on the day-of-the-week effect, on these indices. To accomplish this, daily closing prices of the BSE CARBONEX, BSE 100, BSE Sensex, BSE Energy and BSE Oil & Gas were gathered from the BSE official website. The study period was divided into three segments: the full period, period I (2017–2020) and period II (2020–2022). The study's findings reveal that throughout the full period, period I and period II, BSE Energy exhibited the highest mean daily return compared to the other selected indices. There appears to be a discernible Tuesday effect on the daily average mean returns of BSE CARBONEX, BSE 100, BSE Sensex, BSE Energy and BSE Oil & Gas in both the full sample period and period II. Results from ordinary least squares (OLS) analysis by day indicate a notably high positive and statistically significant daily return on Tuesdays, particularly during the full sample period and period II. Furthermore, the GARCH (1,1) model suggests a significant Tuesday effect on the BSE Energy and BSE Oil & Gas indices.

Long-term forecasts about commodity market indicators play an important role in informing policy and investment decisions by governments and market participants. Our study examines whether the accuracy of the multi-step forecasts can be improved using deep learning methods.

We first formulate a supervised learning problem and set benchmarks for forecast accuracy using traditional econometric models. We then train a set of deep neural networks and measure their performance against the benchmark.

We find that while the United States Department of Agriculture (USDA) baseline projections perform better for shorter forecast horizons, the performance of the deep neural networks improves for longer horizons. The findings may inform future revisions of the forecasting process.

This study demonstrates an application of deep learning methods to multi-horizon forecasts of agri-cultural commodities, which is a departure from the current methods used in producing these types of forecasts.

The construction business is widely recognised for its inherent complexity and dynamic nature, which stems from the nature of the job involved. The industry is often regarded as one of the most challenging industries globally in terms of implementing environmental, health and safety (EHS) practices. However, in the absence of EHS, the construction industry cannot be considered sustainable. Therefore, this study aims to identify the trends, knowledge gaps and implications of EHS research to enhance construction activities and knowledge.

The study adopted a science mapping approach involving bibliometric and scientometric analysis of 407 construction EHS publications from the Scopus database with the VOSviewer software. The study is based on journal articles from the Scopus database without restriction to any time range.

The main focus of construction EHS research identified in the study includes sustainability-related studies, risk-related, environmental issues, EHS management, integrated management systems studies, health and safety related and EHS in the construction process. Some emerging areas also identified include productivity, design, culture, social sustainability and machine learning. The most influential and productive publication sources, countries/regions and EHS publications with the highest impact were also determined.

Documents published in the Scopus database were considered for analysis because of the wider coverage of the database. Journal articles written in English language represent the inclusion criteria, whereas other documents were excluded from the analysis. The study also limited the search to articles with the engineering subject area.

The research findings will enlighten stakeholders and practitioners on the focal knowledge areas in the EHS research domain, which are vital for enhancing EHS in the industry.

To the best of the authors’ knowledge, this review-based study is the first attempt to internationally conduct a science mapping on extant literature in the EHS research domain through bibliometric and scientometric assessments.

This study aims to examine how the Information Technology (IT) sector in India is changing sporadically to be relevant to be able to meet the changing demands. Companies are striving hard to be able to leverage any such factor that adds to the competitive advantage needed to survive in this dynamic market. Therefore, an organization has to be able to keep innovation as its primary objective.

This study used a cross-sectional research design and the data from 303 IT professionals were used to validate the relationships among psychological capital (PSC), cognitive diversity (COD), temporal ambidexterity (TEA), innovative work behaviour (IWB) and adaptive performance (ADP). Hypotheses testing was done through the SEM and mediation analysis was conducted using bootstrap estimation in SPSS AMOS.

The results suggest that PSC significantly affects both IWB and ADP. COD has a significant effect only on IWB. In addition, directly impacts ADP. Mediation analysis indicates that COD has full mediation between the relationship of IWB and ADP, whereas PSC has a partial mediation. However, TEA has no mediation indicating that an employee needs to have support from his organization to be ambidextrous.

This study shows how significant innovation and IWBs are in the context of the IT sector and how positive thinking, a diverse set of people and the balance between short-term and long-term goals could promote IWBs in an individual leading to better ADP.

This paper aims to analyze the time-varying dynamic connectedness among environmental, social and governance (ESG)-compliant firms, Fintech-based firms and artificial intelligence (AI) firm’s stocks.

To examine the spillover from globally leading companies that systematically follow ESG reporting and standards into their financial books to top AI-based and Fintech-based companies, we use the daily observation extending from December 31, 2019 to October 9, 2023. For the empirical investigation, Diebold and Yilmaz (2012) model and Baruník and Křehlík (2018) model are employed.

An intriguing observation is found for both recipient and transmission as Northrop Grumman remains the least shock transmitter and receiver among all constituent markets irrespective of two different used models. On this note, Northrop Grumman can be classified among the safest stock comparatively which has to be held in short, medium and long run to mitigate the risk.

After extensive existing literature review and to the best of the authors knowledge, it is a novel study that examines the dynamic connectedness among ESG, Fintech and AI stocks covering two unprecedented events like the COVID-19 outbreak and the Russia–Ukraine invasion.

This study uses the time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness approach to examine the interconnectedness between artificial intelligence (AI)-related financial assets and Islamic banking indices in financial markets. It reveals linkages across different market segments and their influence on spillovers between segments at different investment horizons.

The research methodology involves using the TVP-VAR model. This model allows the authors to analyze return spillovers across different time frames by capturing the dynamic nature of the relationships between variables. The authors also consider various global factors in the regression analysis for rigor (Chatziantoniou et al., 2023).

This research shows that short-term changes impact extreme risk interconnectedness more than medium- or long-term changes. Well-established market indices like AI-related stocks (MSFT, GOOG and NVDA) and Islamic banks (Saudi Arabia, UAE) consistently contribute to or transmit returns. In contrast, most AI-related tokens and Asian Islamic banks tend to receive shocks. Two indices related to gold and the uncertainty of the US dollar demonstrate potential for hedging and predictability in interconnectedness.

The results emphasize the vital role of short-term changes in diversifying a portfolio and managing risks, providing valuable insights for financial analysts and professionals in AI-related finance, Islamic banking and portfolio management.

The rising importance of AI-related stocks and tokens in investing has raised concerns about their compatibility with traditional financial instruments, especially in Islamic finance (Rabbani et al., 2023; Darehshiri et al., 2022; Yousaf et al., 2022). This paper examines the connections among AI-related stocks, AI-related tokens and Islamic banking indices to shed light on their correlations and potential impacts on the financial landscape.

Video gaming has become a popular leisure-time activity with two to three billion users worldwide (Newzoo, 2017; Vuong et al., 2021). Although existing knowledge shows its relationship with anger and aggression, the present study aims to extend this focus by assessing whether anger expression mediates the association of gaming addition with social interaction among Pakistani adolescent boys.

A sample of 300 adolescent boys (M age = 14.6, SD = 1.2) from private schools was selected. The participants were assessed on Anger Expression Scale (Shafaqat, 2016), Social Interaction and Technology Use Questionnaire (Henderson et al., 1999) and Game Addiction Scale (Lemmens et al., 2009) to assess their levels of anger expression, social interaction and gaming addiction.

Analysis revealed that gaming addiction and anger expression were significantly and negatively related to social interaction. Gaming addiction was positively correlated with anger expression. Mediation analyses showed that anger expression significantly explained the negative link between gaming addiction and social interaction.

The study highlights anger and lack of social interaction as important consequences of gaming addiction in adolescent boys.