Supply chains are vulnerable to various disruption risks that can adversely affect their overall performance and objectives. This study addresses the challenge of designing a resilient and environmentally sustainable mixed open and closed-loop supply chain network that can withstand both operational and disruption risks. The research employs a bi-objective stochastic mathematical model to examine the balance between environmental sustainability and profitability within the SC. To mitigate the impact of disruptions, several resilience strategies are incorporated into the model, significantly reducing their adverse effects. Due to the inherent complexity of the problem, the study introduces a novel hybrid metaheuristic algorithm that combines ant colony optimization with teaching and learning-based optimization, named ACO-TLBO. Additionally, two other enhanced hybrid metaheuristics are proposed. The performance of these solution methods is assessed through various test problems, using specific performance metrics for comparison. Results reveal that the ACO-TLBO algorithm excels in generating high-quality, non-dominated solutions. The model's practical applicability is demonstrated through a case study in the tire industry, validating its effectiveness. The findings indicate that the proposed resilience strategies are crucial for minimizing the negative impacts of disruptions on SC objectives. Furthermore, the results underscore the importance of resilience in maintaining both sustainability and profitability within supply chains.

The Climate Disclosure Standards Board (CDSB) initiated the standards for sustainability and transparency in corporate reporting, which may be termed Green Accounting Standards (GAS). GAS encourages sustainable decision-making among businesses and practitioners. The present study explores the role of GAS on environmental sustainability in the firms located in the Alkharj governorate. Moreover, the mediating of social performance is also investigated in the relationship between GAS and environmental sustainability. For this purpose, a questionnaire is used to collect the data from accounting practitioners, and 224 valid responses are collected from the survey. The results of PLS-SEM show that GAS improves the environmental sustainability and social performance of the firms. Moreover, social performance also improves environmental sustainability. Thus, GAS promotes resource efficiency by tracking resource use and waste generation, which could be helpful in identifying opportunities for reducing environmental footprints. Thus, it also facilitates monitoring environmental performance in Alkharj to identify the areas needing improvement. Furthermore, GAS also improves social performance by recognizing social costs and engaging stakeholders, which are also facilitating more socially responsible decisions. Based on the results, the study recommends the firms in Alkharj governorate adopt GAS to improve environmental sustainability and social performance.

Incorporating sustainability principles into Supply Chain Management (SCM) has received considerable attention in recent years, with a particular emphasis on Green Supply Chain Management (GSCM), which aims to reduce environmental consequences. Saudi Arabia has launched sustainability initiatives; however, the application of green SCM methods in SMEs in Saudi Arabian manufacturing has yet to be explored. Therefore, this research aimed to empirically assess the effect of GSCM in promoting environmental sustainability in Saudi manufacturing SMEs, focusing on the mediating function of operations analytics. Therefore, this study used a quantitative research technique to discover the link between the study variables—a rigorous questionnaire obtained primary data from managers and team leaders. SPSS was used for descriptive statistics, while SMARTPLS was used for structural equation modelling. The measurement model, path analysis, and indirect impact analysis were used to validate the research constructs and analyze the hypothesized associations. The findings support the evidence of direct positive links between green manufacturing, green business practices, eco-design and environmental sustainability in Saudi manufacturing SMEs. Conversely, no evidence was found to support the function of operations analytics as a bridge between green SCM and environmental sustainability. Although operations analytics can improve green SCM processes, more studies are needed to understand its full impact on environmental sustainability outcomes.

This study aims to explore the interrelationships between Green Open Spaces, Ecological Patterns, the Ecological Supply Chain, and Environmental Sustainability in urban ecosystems. A quantitative research approach employing a cross-sectional design was utilized. Data were collected through surveys and field observations from urban residents with access to green spaces. Structural Equation Modeling (SEM) with Smart PLS was used for data analysis. The findings indicate significant impacts of Green Open Spaces and Ecological Patterns on both the Ecological Supply Chain and Environmental Sustainability. Moreover, the Ecological Supply Chain mediates the relationship between Green Open Spaces/Ecological Patterns and Environmental Sustainability. Limitations include the focus on a specific geographical area and potential biases in self-reported data. This study contributes to ecological theory by emphasizing the interconnectedness between ecological elements and their influence on Environmental Sustainability. Practically, it provides insights for urban planning and conservation efforts, highlighting the importance of preserving natural habitats within urban environments. The findings also underscore the need for holistic approaches to ecosystem management and sustainability. The novel aspect of this study lies in its examination of the mediating role of the Ecological Supply Chain in the relationship between ecological elements and Environmental Sustainability, offering new insights into the mechanisms driving ecosystem dynamics in urban settings.

Betawi Ora is an indigenous tribe that lives in Bekasi which is a region of West Java. In terms of cultural distribution, Betawi itself is a tribe originating from Jakarta, but geographically it spreads to the West Java region. The existence of Eco-culinary products cannot be separated from the supply chain management system and environmental sustainability because Eco-culinary is a food that represents the existence of raw materials provided by the environment where the community exists. Based on the background and urgency of this research, the purpose of this research is to find out the relationship between Supply Chain Management, Eco-culinary Product and Environmental Sustainability both directly and indirectly where Eco-culinaru Product mediates the relationship between Supply Chain variables Management and Environmental Sustainability variables. The respondents in this study were 210 managers of Betawi Ora restaurants in Bekasi West Java, Indonesia and employees who maintain supply chain management in that restaurant. Data collection and processing were carried out using the Generalized Structured Component Analysis (GSCA) method. The analytical approach uses the least squares method in the parameter estimation process. The research method is a quantitative survey, analysis of research data is performed using structural equation modeling partial least squares (SEM-PLS) with statistical data processing tools, namely Smart PLS 4.0 software. Results of this research show that supply chain management had a significant effect on environmental sustainability which is mediated by eco-culinary products. Thus, it can be concluded that good quality of supply chain management will be able to produce quality products, and it must be an important consideration that the goal of everything is to create and maintain Environmental Sustainability.

The advent of technology has dramatically reshaped the ways in which we assimilate knowledge, teach, and access information. From online learning platforms to interactive educational games and virtual reality simulations, technology has transformed the traditional classroom into a vibrant, engaging, and inclusive educational landscape. A notable advancement in artificial intelligence technology is ChatGPT (Generative Pre-trained Transformer), which provides personalized and effective learning experiences by delivering customized feedback and explanations to students. Despite the considerable research on the adoption or acceptance of e-learning, there is a paucity of research on the acceptance and utilization of ChatGPT, highlighting the need for further investigation. This study aims to bridge this gap by proposing an integrated model that incorporates three key constructs: perceived learning value, perceived satisfaction, and personal innovativeness. A questionnaire survey was administered to 289 university students in the United Arab Emirates (UAE), and the data collected were analyzed using the partial least squares-structural equation modeling (PLS-SEM) approach. The results revealed that "perceived learning value, perceived satisfaction, and personal innovativeness" are the most influential and critical determinants of students' intentions to use learning platforms through ChatGPT. This research contributes to the existing body of literature on AI and environmental sustainability, providing invaluable insights for practitioners, policymakers, and AI product developers. These insights can guide the development and implementation of AI technologies to better align with users' needs and preferences, while also considering the broader environmental context.

Recent organizational trends give more importance to the social and responsible behavior of organizations to their sustainability. Numerous factors are responsible for prioritizing social responsiveness and pro-environmental or employee-green behavior for organizational sustainability. Nevertheless, no studies have yet considered how voluntary green behavior (VGB) and socially responsible human resource management (SRHRM) influence this perception. Hence, this study determines the explanatory link of VGB along with the impacts of SRHRM on organizational sustainability (environmental [EnS], social [SS], and economic [ES] sustainability). Data was collected from a developing nation context. An explanatory research strategy was used for the present study. To acquire data from 100 Bangladeshi pharmaceutical manufacturing organizations, structured questionnaires were used. For testing the proposed hypotheses of the study, we used partial least squares structural equation modeling (PLS-SEM). The outcomes of the analysis reveal that SRHRM has a considerable impact, both positively and significantly, on organizational sustainability (EnS, SS, and ES). Once again, SRHRM has a substantial positive effect on VGB. Furthermore, VGB plays an influential role as a mediator in the relationship between SRHRM and organizational sustainability. The findings have significant implications for pharmaceutical manufacturing organization management in Bangladesh and other Southeast Asian contexts. Based on the findings, pharmaceutical company managers will have a stronger rationale to invest in SRHRM while simultaneously establishing strong ties with employees and CSR-oriented green behavior to accomplish their organizational sustainability objectives. This study contributes to the existing body of research on the sustainability of organizations and the triple bottom line, along with SRHRM and VGB, by providing evidence from a country that is rapidly industrializing and developing. In this work, SRHRM was measured as a whole, even though it has three dimensions. Since the sample consists of Bangladeshi pharmaceutical manufacturing organizations, it is also uncertain whether the results can be generalized.

During the Covid-19 pandemic, when strict restrictions were imposed to protect public health, e-commerce played a significant role in providing products on time. E-commerce technology and big data analytics enable companies to gain competitive advantages and respond to customers more efficiently. To make e-commerce more sustainable, the three dimensions of sustainability must be met, otherwise it can have negative consequences that lead to ecosystem destruction. Thus, e-commerce must learn how to effectively manage certain aspects of sustainability and adapt its operations to achieve balance. E-commerce's impact on sustainability can be measured in three pillars: economic, social and environmental and achieving a balance among these is the ultimate goal of sustainable development. Although the sustainability issue and big data analytics have gained increasing popularity in recent years, there is still a gap in evaluating applications of big data based on sustainable development indicators. In this study, we used a hybrid multi-criteria decision-making technique combining fuzzy TOPSIS and BWM to assess big data applications in e-commerce considering sustainable development indicators. The results showed environmental sustainability and energy consumption efficiency received the highest weight for the main pillars and sub criteria of sustainability indicators. Coordinating and monitoring supply chain processes, innovating product, process and business models, and creating new products and services are the top three applications of big data in e-commerce considering sustainable development indicators. E-commerce managers and experts can make better decisions about sustainable approaches by prioritizing big data applications based on sustainable development indicators. In addition, the proposed approach can also be used to evaluate big data analytics in other industries that consider sustainable development indicators.

This research paper aims to explore the relationship between water pollution and sustainable development. Water pollution is a significant environmental challenge that threatens the sustainability of ecosystems, human health, and economic development. Sustainable development aims to meet the needs of the present generation without compromising the ability of future generations to meet their own needs. The research methodology involves a comprehensive review of relevant literature on water pollution and sustainable development, including empirical studies, theoretical frameworks, and policy documents. The research will explore the impact of water pollution on sustainable development, the drivers of water pollution, and the policy and regulatory frameworks that promote sustainable water management. The findings of this research paper will contribute to a deeper understanding of the complex relationship between water pollution and sustainable development and provide insights into effective strategies and policies that can promote sustainable water management. The research will also highlight the importance of public awareness and education in promoting sustainable practices and behaviors that can help to prevent and mitigate water pollution. This research paper will provide valuable insights into achieving sustainable water management practices that promote environmental sustainability and socio-economic development.