Nowadays investors are measuring the performances of a business organization not only based on their operating efficiency but also fulfilling their social responsibility. At least the investors need to know whether the activities of the business have any adverse impact on the society and environment. This study explores the accountability of the business from the social and environmental context. This empirical study tends to investigate the nature of the ownership structure that influences the environmental disclosure of a business entity. Based on the sample of fifty-five DSE-listed textile companies, this study used multiple regression to assess the causal relationship between the ownership structure and corporate environmental disclosure. Moreover, this cross-sectional study also considers the agency theory and stakeholder theory to explain the relationship between the ownership structure and environmental disclosure. The findings indicate that corporate environmental disclosure is positively influenced by foreign ownership and institutional ownership whereas director ownership and public ownership have no significant association with the environmental disclosure. These insightful results challenge conventional assumptions and highlight the need for a nuanced understanding of the factors that drive environmental reporting practices in the context of an emerging economy. The main contribution of this article lies in its provision of empirical evidence from an emerging economy, Bangladesh, which helps in understanding sustainable practices in a global context. Additionally, it aids in developing effective corporate governance policies and strategies tailored to similar emerging economies by recognizing the role of ownership structures in influencing environmental accountability. These findings further assist policymakers, managers, and other sustainability advocates in understanding how different ownership structures affect corporate environmental disclosure.
This study investigates the role of property quality in shaping booking intentions within the dynamic landscape of the hospitality sector. A comprehensive approach, integrating qualitative and quantitative methodologies, is employed, utilising Airdna’s dataset spanning from July 2016 to June 2020. Multiple regression models, including interaction terms, are applied to scrutinise the moderating role of property quality. The study unveils unexpected findings, particularly a counterintuitive negative correlation between property quality and booking intentions in Model 7, challenging conventional assumptions. Theoretical implications call for a deeper exploration of contextual nuances and psychological intricacies influencing guest preferences, urging a re-evaluation of established models within hospitality management. On a practical note, the study emphasises the significance of continuous quality improvement and dynamic strategies aligned with evolving consumer expectations. The unexpected correlation prompts a shift towards more context-specific approaches in understanding and managing guest behavior, offering valuable insights for both academia and the ever-evolving landscape of the hospitality industry.
The problem of the current study is to study the moderating role of Blockchain technology on the impact of the use of financial technology (FinTech) on the competitive advantage of Jordanian banks. Quantitative analysis is appropriate. The study population consists of (600) employees in three banks at Jordan (Arab Bank, Islamic Bank, Ahli Bank) with its branches in various governorates. A questionnaire was developed to collect study data and distributed electronically. The number of participants was (240) respondents. The study confirms that there is an impact of the mediating role of Blockchain technology in the impact of the use of financial technology (FinTech) on competitive advantage. The study recommends increasing spending on financial technology applications to improve banking services provided to customers, especially through electronic applications and technologies. The study also recommends rebuilding current banking systems using Blockchain technology, which will remove the central database structure and replace it with a decentralized data environment via the blockchain, thus reducing the risk of database hacking. Since transactions via blockchain technology are verified by every node of the chain, it will make transactions more secure which will make the world’s banking systems faster and more secure.
Conspiracy theories during Covid-19 pandemic spread worldwide, including in Indonesia. What political and religious factors explain their spread in Indonesia with particular reference to the DKI Jakarta province, its surrounding municipalities, and West Sumatera province? This study aimed to answer the questions. It employed a qualitative approach with multi-data collection methods, including those from media, documents, and interviews. The spread of Conspiracy theories benefited from the democratic system that promotes the freedom of information in using social media. First, the government officials initially spread conspiracy theories to satisfy people’s anxiety about the obscured Pandemic. However, they resulted in the government’s ambiguous, controversial, and reckless policies leading to people’s distrust of the government. Jokowi-Makruf Amien, political opponents capitalized on the government’s poor policies to spread conspiracy theories which partly discredited the Jokowi-Amien administration. Both government officials and the opposition capitalized on politics and religious teaching or supra-natural pretexts to posit their conspiracy theories.
Monitoring marine biodiversity is a challenge in some vulnerable and difficult-to-access habitats, such as underwater caves. Underwater caves are a great focus of biodiversity, concentrating a large number of species in their environment. However, most of the sessile species that live on the rocky walls are very vulnerable, and they are often threatened by different pressures. The use of these spaces as a destination for recreational divers can cause different impacts on the benthic habitat. In this work, we propose a methodology based on video recordings of cave walls and image analysis with deep learning algorithms to estimate the spatial density of structuring species in a study area. We propose a combination of automatic frame overlap detection, estimation of the actual extent of surface cover, and semantic segmentation of the main 10 species of corals and sponges to obtain species density maps. These maps can be the data source for monitoring biodiversity over time. In this paper, we analyzed the performance of three different semantic segmentation algorithms and backbones for this task and found that the Mask R-CNN model with the Xception101 backbone achieves the best accuracy, with an average segmentation accuracy of 82%.
This study explores the influence of human resource empowerment on the establishment of green human resource management (GHRM) within Tehran's 14th district municipality. Utilizing a descriptive-analytical research approach, the study targets the practical implications of empowerment strategies on GHRM implementation. The research population consists of 1500 employees from the 14th district, based on the 2017 census. A sample of 306 respondents was selected using Morgan's table. Data were collected via a structured questionnaire developed from the study's conceptual framework and research hypotheses. The questionnaire's validity and reliability were confirmed through expert review and Cronbach's alpha (0.9). Descriptive statistics outline the background and primary variables, while inferential statistics, particularly the Pearson correlation test, were used to evaluate the hypotheses. Results indicate that human resource empowerment positively affects the establishment of GHRM in Tehran's 14th district municipality.
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