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This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.

The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.

The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.

Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.

This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

The purpose of this research is to primarily understand how crypto traders can use the Bitcoin as a hedge or safe haven asset to reduce their losses from crypto trading. The study also aims to provide insights to crypto investors (portfolio managers) who wish to maintain a crypto portfolio for the medium term and can use the Bitcoin to minimize their losses. The findings of this research can also be used by policymakers and regulators for accommodating the Bitcoin as a medium of exchange, considering its safe haven nature.

This study applies the cross-quantilogram (CQ) approach introduced by Han et al. (2016) to examine the safe-haven property of the Bitcoin against the other selected crypto assets. This method is robust for estimating bivariate volatility spillover between two markets given unusual distributions and extreme observations. The CQ method is capable of calculating the magnitude of the shock from one market to another under different quantiles. Additionally, this method is suitable for fat-tailed distributions. Finally, the method allows anticipating long lags to evaluate the strength of the relationship between two variables in terms of durations and directions simultaneously.

The Bitcoin acts as a weak safe haven asset for a majority of new crypto assets for the entire study period. These results hold even during greed and fear sentiments in the crypto market. The Bitcoin has the ability to protect crypto assets from sharp downturns in the crypto market and hence gives crypto traders some respite when trading in a highly volatile asset class.

This study is the first attempt to show how the Bitcoin can act as a true matriarch/patriarch for crypto assets and protect them during market turmoil. This study presents a clear and concise representation of this relationship via heatmaps constructed from CQ analysis, depicting the quantile dependence association between the Bitcoin and other crypto assets. The uniqueness of this study also lies in the fact that it assesses the protective properties of the Bitcoin not only for the entire sample period but also specifically during periods of greed and fear in the crypto market.

As the foundation for understanding the dynamics of the construction sector's corruption, this study examines building contractors' experiences of the stifling of moral, communal and cultural values in the name of modern social and religious principles.

This study's objective was accomplished in two phases. First, a theoretical model was constructed. The theory is then tested using structural equation modeling in the second section. The theory suggests that, based on social norm and institutional theories, social disquietude and religious manipulation influence the interaction and types of corruption in the Nigerian construction sector. From this theory, it was deduced that social malaise (hypothesis 1) and religious manipulations (hypothesis 2) mediate the processes and forms of corruption in the construction sector. To validate the hypotheses, a structural equation model (SEM) was developed and tested.

Native intelligence, new values, social quests and poverty are the social malaises that are profoundly responsible for corruption manifestations in the construction industry. The findings confirmed that construction stakeholders are heavily influenced financially and spiritually by religious organizations. Construction stakeholders engage in corrupt activities as a result of the ravenousness and self-interest bestowed on them by religious manipulation and the significant contribution of social malaise. The study admits that social engineering is required to integrate local wisdom and values into Nigerian society in order to mitigate the negative consequences of social unrest and religious manipulations.

This study has contributed to a branch of the literature on corruption in the construction industry that aims to identify the hidden factors that drive the sector's corruption dynamics. It has shown how many different problems in society and religious beliefs can make building contractors more likely to be dishonest. In order to improve project delivery, this study emphasized the importance of investigating the relationship between religious affiliations, religious doctrines and domination and religious competition on corruption in the construction industry.

Following the findings of this study, the majority of construction stakeholders place their trust in unmerited favor, “spirit money,” prosperity gospels and the payment of offerings and “seed money” to win contracts. This implies that construction stakeholders will most likely be deceptive in their dealings, increasing the quantity of certified work, increasing variation claims and engaging in collusion. This is because their faith in inconceivable favors and the exchange of offerings for blessings would lead them to perceive fraudulent practices as a favor.

This study is unique in that it sought to determine whether construction stakeholders' corrupt tendencies stem from religious manipulations and complex social systems.

The primary objective of this research is to provide a precise interpretation of the constructed machine learning model and produce definitive summaries that can evaluate the influence of investor sentiment on the overall sales of non-fungible token (NFT) assets. To achieve this objective, the NFT hype index was constructed as well as several approaches of XAI were employed to interpret Black Box models and assess the magnitude and direction of the impact of the features used.

The research paper involved the construction of a sentiment index termed the NFT hype index, which aims to measure the influence of market actors within the NFT industry. This index was created by analyzing written content posted by 62 high-profile individuals and opinion leaders on the social media platform Twitter. The authors collected posts from the Twitter accounts that were afterward classified by tonality with a help of natural language processing model VADER. Then the machine learning methods and XAI approaches (feature importance, permutation importance and SHAP) were applied to explain the obtained results.

The built index was subjected to rigorous analysis using the gradient boosting regressor model and explainable AI techniques, which confirmed its significant explanatory power. Remarkably, the NFT hype index exhibited a higher degree of predictive accuracy compared to the well-known sentiment indices.

The NFT hype index, constructed from Twitter textual data, functions as an innovative, sentiment-based indicator for investment decision-making in the NFT market. It offers investors unique insights into the market sentiment that can be used alongside conventional financial analysis techniques to enhance risk management, portfolio optimization and overall investment outcomes within the rapidly evolving NFT ecosystem. Thus, the index plays a crucial role in facilitating well-informed, data-driven investment decisions and ensuring a competitive edge in the digital assets market.

The authors developed a novel index of investor interest for NFT assets (NFT hype index) based on text messages posted by market influencers and compared it to conventional sentiment indices in terms of their explanatory power. With the application of explainable AI, it was shown that sentiment indices may perform as significant predictors for NFT sales and that the NFT hype index works best among all sentiment indices considered.

To critically examine the holistic implementation of green supply chain management (GSCM) practices in entrepreneurial ventures in Thailand.

The study observed 121 organizations (or respondents) covering 13 industries from both the public and private sectors. The research process started with a semi-structured interview and observation, followed by focus group interviews. The data collected were then analyzed using content and thematic analysis methods.

Respondents (chiefly entrepreneurial ventures) have good eco-knowledge. Most have more than 3–10 years of experience implementing eco practices that have significantly reduced their eco-impacts and costs. The study also revealed that firms’ directors developed environmental management systems (EMS) and cultures of their firms. This study rejected previously held beliefs that factors including country, firm size, industry type, years of activity and certification, impact both positively and negatively on green performance. However, the influence of top management, green entrepreneurial orientation (GEO), respondents’ different perceptions of the GSCM boundary and the COVID-19 pandemic have impacted the success of GSCM’s implementation.

The COVID-19 pandemic obstructed observing GSCM implementation at the respondents’ workplaces. This could reduce the validity of the research, as all evidence obtained was selectively provided by the respondents, not the researchers.

New practitioners are encouraged to focus on green logistics (GL) at a firm level as opposed to the broader supply chain. Effective GL practices recommended utilities usage reduction, reuse/recycle waste and green procurement.

GSCM researchers should focus on patterns of over-consumption, over-trading and relevant institutions that cause environmental unsustainability, rather than specific units in supply chains. The Buddhist sustainable sufficiency concept should be considered as a viable lens to analyze GSCM as it complements existing theories.

This study aims to empirically examine the influence of Islamic corporate social responsibility (ICSR) on social welfare moderated by financial fraud.

The method used was the mix method. The number of respondents was 410. They combined the moderate regression analysis with PROCESS Andrew F Hayes to test the research hypothesis. After conducting the survey, it was continued by conducting interviews with the village community and the head of the village.

The first finding of this study is that ICSR has a significant positive effect on social welfare. The second finding is that financial fraud weakens the influence of ICSR on social welfare. The results of the interviews also confirmed the two findings of this study.

The high level of bias in answering the questions is due to the low public knowledge of ICSR. In addition, the interviews still needed to involve the oil and gas companies and government.

The main implication is improving social welfare, especially for those affected by offshore oil drilling. Furthermore, stakeholders are more sensitive to the adverse effects of financial fraud. Finally, to make drilling companies more transparent and on target in implementing ICSR.

The main novelty in this research is using of the mixed method. In addition, applying financial fraud as a moderating variable is rarely studied empirically.

This study aims to investigate the negative interpersonal antecedents, emotional mediators and boundary conditions of knowledge sabotage behavior.

The authors collected data from 275 Chinese employees using convenience sampling and snowball sampling across three stages. Subsequently, the authors used both hierarchical regression and bootstrap methods to test the proposed hypotheses.

The results confirmed that workplace ostracism has positive effects on employee knowledge sabotage behavior both directly and via employee anger. In addition, the authors found that employee bottom-line mentality (BLM) moderates not only the direct effect of workplace ostracism on employee anger but also the indirect effect of employee anger in this context. Employee conscientiousness moderates only the direct effect of workplace ostracism on employee anger and does not moderate the indirect effect.

To the best of the authors’ knowledge, this study not only explores the influence of workplace ostracism on employee knowledge sabotage behavior for the first time but also elucidates the underlying emotional mechanisms (anger) and boundary conditions (employee BLM and conscientiousness) by which workplace ostracism influences employee knowledge sabotage behavior, thus deepening the understanding of how knowledge sabotage emerges in organizations.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.

This paper aims to investigate how narrative is constructed to create connections with fat readers, how books function to envision spaces of fat liberation for young readers and to highlight the incredible importance of providing bigger mirrors (Bishop, 1990) for fat representation in children’s literature.

This paper analyzes and reflects on two texts that contain counternarratives of fatness: The (Other) F Word: A celebration of the fat and fierce edited by Angie Manfredi (2019) and Big by Vashti Harrison (2023) to interrogate how these two narratives intentionally disrupt anti-fat bias.

Body size and fatness are identities that need to be included in diversity efforts within education. Books like The (Other) F Word: A celebration of the fat and fierce (Manfredi, 2019) and Big (Harrison, 2023) offer positive representations of fatness, disrupt biases around body size and provide spaces that allow fat students to find joy, hope, connection and, more than anything, imagine a way toward liberation.

This paper highlights the need to include more narratives of positive fat representation within children’s literature and calls for educators to interrogate their own anti-fat biases and practices.

There is a lack of research on fat representation specifically within children and young adult literature. This paper provides an analysis of two pieces of literature with fat representation that brings attention to the need for this type of future research.

In the M'Zab Valley, women have long remained confined to their domestic sphere and are invisible in outdoor spaces. This study aims to analyse the use of public and private spaces by the women of Ksar El Atteuf, particularly after the significant changes that society has undergone.

This study examines the role of gender in the daily life of an urban community in the M'Zab Valley in Algeria through semi-structured interviews with relevant experts and a survey of 100 Mozabite women. It focuses on their roles and views regarding using spaces and maintaining Mozabite heritage.

Social and religious norms influence women's utilisation, behaviour and roles in gendered spaces. Most women consider their place to be within the house but refuse to live primitively. Education and work have enabled them to emerge outdoors. The results also showed that owing to the restrictions imposed on women, 60% of them emphasised the need to express their opinions and make decisions, and 26% asked for more opportunities and spaces.

This study broadens understanding of Mozabite society and its architectural and urban heritage. The empirical study surveyed women and conducted interviews with experts. This is valuable, particularly, given the challenges of studying gender in conservative cultural settings.