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.

Environmental Education (EE) programs are of crucial importance. EE are aimed at global citizenship to generate new knowledge and new, more participatory and conscious ways of acting in the environment. This study, therefore, wants to verify the effectiveness of a training intervention that is based on education on climate change issues and on the active participation of subjects in the dimension of the small psychological group. At the intervention 309 students took part, equally distributed by gender (52.1% males), 64.4% enrolled in primary school, 35.6% enrolled in lower secondary school. A quantitative protocol was administered to evaluate the effectiveness of the intervention. The study shows an increase in pro-environmental behaviors and their stability even after 15–30 days. The intervention seems to be effective in triggering pro-environmental behaviors and maintaining them in the following weeks. The results of this study highlight the need to develop environmental education pro-grams in schools to increase levels of knowledge and awareness on the issue of climate change.

Blockchain technology is poised to significantly transform the corporate world, heralding a new era of innovation and efficiency. Over the past few years, its impact has been noted by leaders, academics, and government representatives around the globe this growing interest underscores businesses’ need to evolve and reconsider traditional operational models. To remain competitive, organizations must embrace this change. Before introducing such ground-breaking technology, it is crucial to assess the motivations of primary stakeholders concerning its implementation. This study looks into what influences the use of Blockchain technology in the oil and gas sector, primarily using a quantitative survey of Iraqi oil and gas companies. A questionnaire was distributed among 250 top-level managers, senior executives, project managers, and IT managers for analyzing the data, the study employs the Structural Equation Modelling-Partial Least Squares (SEM-PLS) technique, with Smart PLS for data processing. The findings suggest that the intention to utilise blockchain technology is influenced by one’s attitude towards it. Competitive pressure (environmental factors), functional benefit, and privacy/security (technological factors) significantly affect blockchain adoption intention. Nevertheless, there was no discernible correlation between regulatory backing and the desire to use Blockchain. Additionally, cost concern and perceived risk (organizational factors) two factors contribute negatively to the perception of blockchain technology. Besides the direct relationship, the findings revealed that attitude toward blockchain technology mediate the relationship between cost concern, perceived risk, and intention to adopt Blockchain. Built upon the Technology-Organization-Environment (TOE) model and the Theory of Reasoned Action, this research offers a comprehensive framework for investigating the intention to adopt blockchain technology. The results enhance both theoretical understanding and practical implementation by providing valuable insights into the emerging area of blockchain adoption intentions.

Interest in the impact of environmental innovations on firms’ financial performance has surged over the past two decades, but studies show inconsistent results. This paper addresses these divergences by analyzing 74 studies from 1996 to 2022, encompassing 4,390,754 firm-year observations. We developed a probability-based meta-analysis approach to synthesize existing knowledge and found a generally positive impact of environmental innovations on financial performance, with a probability range of 0.85 to 0.97. Manufacturing firms benefit more from environmental innovations than firms in other industries, and survey-based studies report a more favorable relationship than those using secondary data. This study contributes to existing knowledge by providing a comprehensive aggregation of data, supporting the resource-based view (RBV) and the Porter hypothesis. The findings suggest significant policy implications, highlighting the need for tailored incentives and information-sharing mechanisms, and underscore the importance of diverse data sources in research to ensure robust results.

Plastic products, including plastic packaging, were products whose increasing demand continued because the community still needed plastic as packaging. On the other hand, plastic waste, which was increasingly high and difficult to decompose, was a problem that needed to be solved together. This study aims to understand how plastic company packaging implements TQM, its environmental impact, and how plastic packaging companies are taking steps towards green manufacturing. This research used a qualitative phenomenological method to understand the problem based on the actor’s perspective. The data collection method was in-depth interviews with informants from 3 plastic companies in East Java, Indonesia, followed by observation and FGD. We carried out Triangulation, member checking, and professional involvement to determine the data’s validity, reliability, and trustworthiness. The results of this study indicated a management system that promotes quality as a business strategy and is oriented towards customer satisfaction by involving all members of the organization. TQM emphasized continuous improvement, customer satisfaction, and employee involvement. By implementing aspects of TQM, plastic packaging companies could improve their production processes and reduce waste, increasing efficiency and profitability. In addition, TQM could also contribute to the company’s green performance by promoting environmentally friendly practices, including using electric machines to replace hydraulic machines, thereby reducing the use of electrical energy and CO₂ emissions. The use of solar panels was a step towards green manufacturing. Companies that adopt TQM principles are more likely to implement environmentally friendly initiatives such as reducing energy consumption and using recyclable materials and can demonstrate a commitment to corporate social responsibility. The company’s membership in EcoVadis and SMETA further strengthens the company’s direction towards Green Manufacturing and competitive advantage.

This study evaluated the performance of several machine learning classifiers—Decision Tree, Random Forest, Logistic Regression, Gradient Boosting, SVM, KNN, and Naive Bayes—for adaptability classification in online and onsite learning environments. Decision Tree and Random Forest models achieved the highest accuracy of 0.833, with balanced precision, recall, and F1-scores, indicating strong, overall performance. In contrast, Naive Bayes, while having the lowest accuracy (0.625), exhibited high recall, making it potentially useful for identifying adaptable students despite lower precision. SHAP (SHapley Additive exPlanations) analysis further identified the most influential features on adaptability classification. IT Resources at the University emerged as the primary factor affecting adaptability, followed by Digital Tools Exposure and Class Scheduling Flexibility. Additionally, Psychological Readiness for Change and Technical Support Availability were impactful, underscoring their importance in engaging students in online learning. These findings illustrate the significance of IT infrastructure and flexible scheduling in fostering adaptability, with implications for enhancing online learning experiences.