In the context of the global transition toward carbon neutrality and the circular economy, remanufacturing has emerged as a vital strategy for enhancing resource efficiency and reducing environmental impact. However, the remanufacturing sector faces significant uncertainties—including fluctuations in market demand, variability in the quality of returned products, and dynamic policy changes. These factors collectively challenge production decision-making and system sustainability. Following the preferred peporting items for systematic reviews and meta-analyses (PRISMA) guidelines, this study conducted a systematic review and bibliometric analysis of 98 core articles published between 2015 and 2024, with a focused examination of three interdisciplinary themes: (1) decision-making and optimization under uncertainty, (2) supply chain coordination and policy mechanisms, and (3) digital transformation and the application of emerging technologies. A novel micro–meso–macro analytical framework is proposed to integrate fragmented findings. The results highlight a paradigm shift from static models to dynamic, real-time decision-making systems, facilitated by digital twins (DTs), blockchain, and intelligent algorithms. Furthermore, the study identifies the synergistic effects of carbon-financial instruments and policy incentives in aligning economic and environmental objectives. This research develops a systematic framework to understand and address uncertainties in remanufacturing, offering policymakers and industry practitioners actionable insights to enhance the resilience, sustainability, and global applicability of remanufacturing systems.

The sustainable advancement of agriculture stands as the fundamental cornerstone of sustainable human progress. This study introduces a data-centric methodological framework founded upon the holistic delineation of measurement, feature assessment, and pathway enhancement for agricultural sustainability. Initially, the research articulates a comprehensive evaluative schema incorporating sub-dimensions encompassing agricultural production, agricultural economics, the agricultural resource environment, and rural society, grounded in sustainable development theory. Subsequently, it devises a methodological apparatus for assessing and enhancing sustainable development capabilities, employing entropy evaluation methods and exploratory spatial data analysis techniques. Employing North Anhui as a case study, the viability of this approach is substantiated. The empirical inquiry conducted within this article operationalizes comprehensive evaluation and explores pathways for optimizing agricultural sustainability, focusing on the period spanning 2011 to 2020 in Northern Anhui. The findings affirm the feasibility and efficacy of the data-driven approach. Recommendations derived from the empirical exploration of agricultural sustainability pathways at the local level offer valuable insights for governmental authorities and policymakers. This research endeavor could be extrapolated to other geographical locales worldwide, fostering innovative strides in the sustainable development of regional agriculture.

In this study, we developed a data-driven approach for the evaluation and optimisation of livelihood improvement efficiency (LIE) to address slowing global economic growth and the decline in well-being in the broader population, enhance the quality of people’s livelihoods, and promote sustainable social development. We designed a questionnaire survey and constructed an evaluation index system based on a comprehensive consideration of economic resources, social security and employment, education, and health. Using principal component analysis, entropy weighting, and data envelopment analysis, we optimised the evaluation indicators and quantitatively assessed LIE. We used a Tobit regression model to analyse the factors influencing LIE and provide decision-making support for proposing countermeasures to optimise LIE. Based on the research data, we administered the questionnaire survey to 3125 residents in 16 cities in China’s Anhui Province and demonstrated the applicability of the aforementioned method. The results indicate that there is room for optimising LIE in cities in Anhui Province, which needs to be achieved through the following steps: controlling costs and avoiding waste, encouraging entrepreneurship, increasing income, guiding the direction of industrial growth, optimising regional population structure, and promoting public participation to enhance people’s livelihoods.