A rapidly expanding field, sustainable agriculture aims to produce food and energy for people today and future generations. The sustainability concept is different in every field; thus, the indicators are unique in any area and country. Sustainable agriculture contains three main dimensions: economic, environmental, and social. Sustainable agriculture has been the focus of researchers for the past twenty-five years and has attracted much attention. Many researchers tried to identify these dimensions, but there is a lack of new research concerned with grouping all indicators together. Moreover, the indicators will change every year, so the indicators list needs to be frequently updated. This study follows the protocol for SALSA (Search, Appraisal, Synthesis, and Analysis) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Web of Science (WoS) was used for the literature search. A total of 101 indicators were found from previous studies for the three dimensions: social, environment, economic. In order to measure the most important indicators for sustainable agriculture, the paper proposes an appropriate set of indicators, as well as providing the previous papers analyzed by year of publication, continent, and topic.

Sustainable agriculture strives to ensure future food and energy supply while safeguarding natural resources. The interpretation of sustainability varies by context and country, yielding distinct indicators. Researchers have studied sustainable agriculture for the past 25 years and have developed several indicators. Renewable energy holds a vital role in sustainable agriculture, aiding energy needs and mitigating environmental harm tied to agriculture. It curbs fossil fuel dependency and harnesses agricultural waste for energy. However, a consistent update of renewable energy indicators for agricultural sustainability is needed. Employing SALSA (Search, Appraisal, Synthesis, and Analysis) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodologies within the PRISMA protocol, this study extracts 84 indicators from 420 papers via SCOPUS. These indicators span social, environmental, economic, institutional, and technical dimensions. The study refines these indicators based on significance and influence, offering an enriched perspective. Furthermore, the analysis categorizes papers by publication year, continent, and topic, providing insights for stakeholders, policymakers, and researchers. By ensuring periodic indicator updates, this research promotes sustainable agriculture, informs priority areas, and guides strategic decisions. This contributes to global resilience and food security aspirations in a changing world. The future of renewable energy and sustainable agriculture will involve cutting-edge technologies, refined policy frameworks, and inclusive cross-sector collaboration to address pressing global challenges and create a greener, more resilient world.

Manufacturing companies are facing rapid and unanticipated changes in their business environment. Most of these companies need to find new strategies to remain competitive in the market. Therefore, the main purpose of this study is to integrate the Fuzzy Analytical Network Process (ANP) and VIKOR methods to evaluate the green agile factors and sub-factors in the dairy companies in Iran. To find the green agile factors and sub-factors, this study used the expert’s opinions and literature review. Data is collected from four dairy companies. The results of this study showed that the most important green agility factors are: trust-based relationship with suppliers, flexible production capacity, versatile workers, compliance with quality standards for a new product, and workers’ willingness to learn. In addition, the results indicated that the green agility organization is one of the strategies that help companies to stay in the market. To validate the results, this study used four methods, including TOPSIS, ARAS, EDAS, and MABAC. The necessity of a reaction to the increasing customer choices, environmental concerns, and competitiveness among manufacturers across the globe has engaged the industry to embrace innovative manufacturing strategies.

The integration of Industry 4.0 and Artificial Intelligence (AI) technologies has redefined global supply chain operations, with increasing emphasis on sustainability as a strategic priority. Despite this evolution, there remains a significant gap in the literature regarding the structured prioritization of sustainability-related indicators influenced by digital transformation. This study addresses that gap by identifying and ranking key sustainability enablers across environmental, operational, strategic, and social dimensions using the Best–Worst Method (BWM), a robust multi-criteria decision-making (MCDM) technique. Based on expert input from 37 professionals in the fields of supply chain management, sustainability, and digital technologies, twenty indicators were evaluated within four separate thematic groups. Results reveal that Emissions Monitoring and Reduction and Energy Efficiency are the most critical in the environmental dimension, while Supply Chain Traceability and Smart Inventory Management dominate the operational category. Supply Chain Resilience is identified as the top strategic factor, and Ethical Sourcing is deemed most vital from a social sustainability standpoint. These findings provide actionable insights for policymakers and practitioners, supporting data-driven decision-making and strategic alignment of digital investments with sustainability goals. This research contributes to both academic discourse and practical frameworks by offering a replicable approach to prioritizing sustainability indicators in the context of digital transformation. This study also identifies limitations and proposes future research directions to enhance the integration of digital and sustainable development in global supply chains.

This article examines the significance of Sustainable Supply Chain Management (SSCM) within the Iranian automotive sector, emphasizing the assessment of suppliers’ sustainability performance in light of increasing global environmental concerns and regulatory demands. This study employs the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method to evaluate five principal suppliers—SAPCO, MEGA Motor, Crouse Company, Sazehgostar, and ITMCO—based on twelve criteria: green initiatives, quality, waste reduction, eco-design, reverse logistics, sustainable investments, financial costs, management commitment, strategic capabilities, customer satisfaction, innovation, and trust. Findings indicate that SAPCO and Sazehgostar demonstrate superior sustainability owing to their strong environmental policies, whereas MEGA Motor, Crouse Company, and ITMCO reveal aspects requiring enhancement. The results underscore the imperative of incorporating SSCM principles to improve supply chain efficiency and sustainability. Despite the apparent high costs of SSCM implementation, research indicates that the advantages include enhanced productivity and regulatory compliance. The research additionally advocates for more investigation into SSCM-related variables and the influence of upcoming technologies. Adopting SSCM enables automotive firms to comply with regulatory mandates and satisfy consumer demands, promoting a more sustainable and competitive sector.