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The primary objective of this research is to conceptualize the integration of enterprise risk management (ERM) as a mechanism to enhance the connection between corporate sustainability (CS) reporting and financial performance. This study suggests that future researchers should validate the proposed conceptualization by conducting a comprehensive content analysis of sustainability reports of Malaysian oil and gas companies. This analysis will allow for the collection of pertinent data regarding CS reporting and ERM implementation. The present study takes a comprehensive approach by integrating legitimacy, stakeholder, and resource-based view (RBV) theories, proposing a robust conceptual design that emphasizes the role of ERM in the connection between CS reporting and firm performance. Drawing on theoretical foundations, this study proposes that CS reporting will have a direct effect on financial performance. Moreover, the integration of ERM serves to strengthen the nexus between CS reporting and financial performance. This study offers valuable insights for stakeholders in the oil and gas sector by providing strategic guidance to enhance financial performance not only through CS reporting but also by implementing ERM. Moreover, the framework proposed in this study is expected to bring tangible and intangible benefits to corporations, including reducing information asymmetry, improving the quality of disclosure, and creating value within the field of CS. The proposed conceptual framework holds great significance as it enhances the applicability of legitimacy, stakeholder, and RBV theories, while also creating value for stakeholders through CS reporting and the adoption of risk management practices to enhance financial performance.

This study is the first to investigate the causal relationship between Bitcoin and equity price returns by sectors. Previous studies have focused on aggregated indices such as S&P500, Nasdaq and Dow Jones, but this study uses mixed frequency and disaggregated data at the sectoral level. This allows the authors to examine the nature, direction and strength of causality between Bitcoin and equity prices in different sectors in more detail.

This paper utilizes an Unrestricted Asymmetric Mixed Data Sampling (U-AMIDAS) model to investigate the effect of high-frequency Bitcoin returns on a low-frequency series equity returns. This study also examines causality running from equity to Bitcoin returns by sector. The sample period covers United States (US) data from 3 Jan 2011 to 14 April 2023 across nine sectors: materials, energy, financial, industrial, technology, consumer staples, utilities, health and consumer discretionary.

The study found that there is no causality running from Bitcoin to equity returns in any sector except for the technology sector. In the tech sector, lagged Bitcoin returns Granger cause changes in future equity prices asymmetrically. This means that falling Bitcoin prices significantly influence the tech sector during market pullbacks, but the opposite cannot be said during market rallies. The findings are consistent with those of other studies that have established that during market pullbacks, individual asset prices have a tendency to decline together, whereas during market rallies, they have a tendency to rise independently. In contrast, this study finds evidence of causality running from all sectors of the equity market to Bitcoin.

The findings have significant implications for investors and fund managers, emphasizing the need to consider the asymmetric causality between Bitcoin and the tech sector. Investors should avoid excessive exposure to both Bitcoin and tech stocks in their portfolio, as this may lead to significant drawdowns during market corrections. Diversification across different asset classes and sectors may be a more prudent strategy to mitigate such risks.

The study's findings underscore the need for investors to pay close attention to the frequency and disaggregation of data by sector in order to fully understand the true extent of the relationship between Bitcoin and the equity market.

This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

This paper aims to meta-analyze the results of the prior studies related to the relationship of human capital and financial performance in Islamic banking.

To examine the relationship between human capital and financial of Islamic banks, 23 empirical studies having sample of 15,607 are considered for the meta-analysis. Moreover, different measures related to financial performance including return on assets (ROA), return of equity (ROE) and Tobin’s Q have been taken as moderating for further subgroup analysis.

The results of meta-analysis reveal a positive correlation between human capital and financial performance with an effect size of 0.268. The subgroup analyses showed significant positive associations of human capital with ROA and ROE, insignificant with Tobin’s Q.

This study suggests Islamic banking should prioritize human capital development, maintain consistency and adopt a long-term perspective. Future research should consider context-specific factors and harmonize human capital and financial performance measurements for consensus.

This study aims to analyze the capacity of ecotourists to exhibit behavior that aligns with the ecotourist scale using the Rasch model measurement.

The data was gathered using an online survey incorporating the five tenets of ecotourism using a seven-point rating scale on domestic tourists in Indonesia. Descriptive statistics, cross-tabulation and Rasch model measurement were used to analyze the data.

The ecotourist identification scale measurement items were reliable and satisfactory. The most challenging behavior for ecotourists was using the services of a tour guide who was concerned about the environment. Meanwhile, respecting cultural differences around the tourist destination was the most accessible behavior. Most respondents demonstrated a fit response pattern and satisfactorily met the validity and reliability criteria.

This study did not compare ecotourists’ ability to behave by the type of conservation visited as its limitation. However, it provides a significant methodological contribution to developing a measurement of ecotourist behavior implemented in well-established behavioral theories.

Integrating ecotourism into education, incentivizing eco-friendly tourism practices, promoting awareness, supporting local businesses, respecting local values and ensuring safe travels.

To the best of the authors’ knowledge, this study is the first of its kind to be conducted in Indonesia. It uses a unique and innovative method to reveal the unobserved variables in ecotourists’ behavior. The findings confirm that tourists’ behaviors align with the five tenets of ecotourism.

This study aims to introduce and evaluate a model of host community support for sustainable tourism development (SSTD) based on the influential factors contributing to community support in a biosphere reserve.

Partial least squares structural equation modeling using SmartPLS 3 software is applied to analyze data collected from 473 residents of the Miankaleh Biosphere Reserve, Iran.

The findings reveal that the locals’ community support is affected by their level of environmental awareness, opportunity and attitudes toward SSTD. However, the results do not reveal an influence of environmental knowledge and community attachment on SSTD. The findings enrich the existing literature on community attitude predictors by showing that locals’ SSTD level is not consistently based on common predictors. Such support strongly depends on host communities’ attitudes toward supporting tourism, which is definitely not the same among residents. It is imperative to know whether people’s attitudes arise from a desire to protect the area or for reasons of self-interest.

The findings provide further support for the tenets of the segmentation approach and challenge existing knowledge on host communities’ attitudes about factors influencing residents toward SSTD. The findings have several practical implications regarding community participation for regional and national authorities and destination policymakers.

采用SmartPLS3软件建立偏最小二乘结构方程模型, 对从伊朗米安卡莱生物圈保护区的473名居民获得的数据进行分析。

本研究旨在介绍和评估基于影响促进生物圈保护内社区支持的可持续旅游发展(SSTD)的东道社区支持模型。

结果表明, 本地社区的环境意识水平、机会和对SSTD的态度影响着社区支持。然而, 研究结果并没有揭示环境知识和社区依恋对SSTD的影响。

这一发现丰富了现有的关于社区态度预测因子的文献, 表明当地人的SSTD并不一致基于共同的预测因子。这种支持很大程度上取决于东道社区对支持旅游的态度, 这在居民中肯定是不一样的。有必要了解人们的态度是出于保护该地区的愿望还是出于自身利益的原因。此外, 研究结果为细分方法的原则提供了进一步的支持, 并挑战了关于东道社区对影响居民SSTD态度的现有认知。

Se aplica un modelo de ecuaciones estructurales por mínimos cuadrados parciales con el programa SmartPLS 3 para analizar los datos recogidos de 473 residentes de la reserva de la biosfera de Miankaleh (Irán).

Esta investigación pretende introducir y evaluar un modelo de apoyo de la comunidad anfitriona al desarrollo del turismo sostenible (SSTD) basado en los factores que contribuyen al apoyo de la comunidad en una reserva de la biosfera.

Los resultados revelan que el apoyo de la comunidad local se ve afectado por su nivel de concienciación medioambiental, sus oportunidades y sus actitudes hacia el desarrollo del turismo sostenible. Sin embargo, los resultados no muestran una influencia del conocimiento medioambiental y el apego de la comunidad sobre el desarrollo turístico sostenible.

Los resultados enriquecen la literatura existente sobre predictores de la actitud de la comunidad al mostrar que el nivel de desarrollo turístico sostenible de los autóctonos no se basa únicamente en factores tradicionales. Dicho apoyo depende en gran medida de las actitudes de las comunidades anfitrionas hacia el apoyo al turismo y éste no es el mismo entre los residentes. Es necesario conocer si la actitud de los individuos surge de un deseo de proteger la zona o por razones de interés propio. Además, los resultados corroboran los principios del enfoque de segmentación y retan los conocimientos existentes sobre las actitudes de las comunidades anfitrionas acerca de los factores de los residentes sobre el desarrollo turístico sostenible.

The purpose of this study is to analyze the potential mediating role of employee engagement in the relationship between gratitude and subjective well-being (SWB) of employees working in the information technology (IT) sector in India. The study investigated a moderated mediation model for gratitude and SWB, treating employee engagement as a mediator and gender as a moderator.

Data was collected from 162 professionals working IT sector in India. Process Macro, AMOS and IBM SPSS 22 were used to analyze the mediation and moderation effects.

The results depicted that employee engagement fully mediates the positive association between gratitude practice and the SWB of employees as well as the demographic variable; gender also demonstrated a full moderation effect between them.

This research may be one of the few studies from the Indian context that explore whether gratitude practiced by employees working in the IT sector can play a significant role in impacting their SWB. Past research models had not introduced employee engagement’s indirect impact on the examined variables.

Both technological and human-centric perspectives need to be acknowledged when combining lean production practices and Industry 4.0 (I4.0) technologies. This study aims to explore and explain how lean production practices and I4.0 technologies may coexist to enhance the human-centric perspective of manufacturing operations in the era of Industry 5.0 (I5.0).

The research approach is an explorative and longitudinal case study. The qualitative data collection encompasses respondents from different job functions and organizational levels to cover the entire organization. In total, 18 interviews with 19 interviewees and five focus groups with a total of 25 participants are included.

Identified challenges bring forth that manufacturing organizations must have the ability to see beyond lean production philosophy and I4.0 to meet the demand for a human-centric perspective in socially sustainable manufacturing in the era of Industry 5.0.

The study suggests that while lean production practices and I4.0 practices may be considered separately, they need to be integrated as complementary approaches. This underscores the complexity of managing simultaneous organizational changes and new digital initiatives.

The research presented illuminates the elusive phenomena comprising the combined aspects of a human-centric perspective, specifically bringing forth implications for the co-existence of lean production practices and I4.0 technologies, in the transformation towards I5.0.

The study contributes to new avenues of research within the field of socially sustainable manufacturing. The study provides an in-depth analysis of the human-centric perspective when transforming organizations towards Industry 5.0.

This study aims to test the mean and volatility spill over from the environmental, social, and governance (ESG) market to the stock markets of G7 countries. The study used ARMA-GARCH model to predict the results. The findings of the study reveal that as the spill over exists in the markets, however the mean volatility does not exist showing efficiency of the market as significant results depict that past prices cannot predict the future prices. It provides new insights for the international portfolio investors and policymakers by shedding light on how cross-markets correlate in two different markets.