Sustainable Futures最新文献_第3页

Perception and safety behaviors in pesticide usage among farmers in Brebes regency: Efforts to enhance pesticide safety 布里布省农民农药使用认知与安全行为：加强农药安全的努力

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-10 DOI: 10.1016/j.sftr.2026.101643

Sukarjo , Hidayatuz Zu’amah , Cicik O. Handayani , Elisabeth S. Harsanti , Leny Latifah , Muhamad A. Musoddaq , Sri Handayani , Heny S.P. Rahayu , Suhartono

Pesticides are harmful substances that are highly regulated by government. Farmers’ understanding of pesticide management should align with their actions, but for various reasons, their behaviors often differ from their perceptions. This research aims to examine how farmers’ views influence their habits in managing pesticides in shallot cultivation in Brebes Regency and recommends solutions for modifying this behavior. Furthermore, the study analyzes farmers’ perspectives on pesticide management and their actual practices. The results show that 80.6% of farmers had positive perceptions . Moreover, their behaviors were good in pesticide storage (PS), pesticide mixing (PM), PPE safety (PPE), post-pesticide application (PPA), packaging destruction (PD), and personal hygiene (PH), with rates of 56.5%, 93.5%, 31.5%, 82.2%, 39.0%, and 81.8%, respectively. By examining the perception and behavior index, it was revealed that farmers had a perception index of 0.73, indicating safe pesticide management, while the safe behavior index was achieved in PS (0.54), PM (0.87), PPA (0.75), and PH (0.82). Conversely, unsafe behavior was noted in PPE (0.34) and PD (0.41). The discrepancy between perception and behavior in PPE and PD highlights the need for government assistance to provide the necessary facilities for proper implementation.

农药是受政府严格管制的有害物质。农民对农药管理的认识应与行动相一致，但由于种种原因，他们的行为往往与认识不同。本研究旨在研究农民的观点如何影响他们在布里布摄政的葱种植中管理农药的习惯，并建议改变这种行为的解决方案。此外，本研究还分析了农民对农药管理的看法和实际做法。结果显示，80.6%的农民对农业发展持积极态度。在农药储存（PS）、农药混合（PM）、防护用品安全（PPE）、农药施后（PPA）、包装销毁（PD）和个人卫生（PH）方面表现良好，分别为56.5%、93.5%、31.5%、82.2%、39.0%和81.8%。通过对感知和行为指数的检测，发现农户对农药安全管理的感知指数为0.73，而对PS（0.54）、PM（0.87）、PPA（0.75）和PH（0.82）的感知指数均达到安全行为指数。相反，PPE（0.34）和PD（0.41）存在不安全行为。个人防护装备和个人发展计划的认知和行为之间的差异突出表明，需要政府提供援助，为适当实施提供必要的便利。

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引用次数: 0

Optimizing environmental performance of rice production in semi-arid Iran: An Life Cycle Assessment (LCA)-Multi-Objective Particle Swarm Optimization (MOPSO) approach 伊朗半干旱地区水稻生产环境绩效优化：生命周期评价-多目标粒子群优化方法

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-10 DOI: 10.1016/j.sftr.2026.101645

Mohammad Amiryousefi , Amin Lotfalian Dehkordi , Behzad Elhami

Rice production in water-scarce regions faces severe environmental and resource efficiency challenges that threaten long-term sustainability. This study introduces a novel integrated framework combining Life Cycle Assessment (LCA) with Multi-Objective Particle Swarm Optimization (MOPSO) to simultaneously minimize environmental impacts and optimize input use without compromising yield. A cradle-to-mill gate LCA was performed in a semi-arid region of Iran using the CML₂-baseline method across ten environmental categories. Results showed that electricity (34 %), diesel fuel (16 %) and irrigation equipment (14 %) were the dominant contributors to overall environmental burdens, particularly to global warming potential and fossil resource depletion. Through MOPSO-based optimization, total environmental damage was reduced by 48 %, while rice yield increased substantially (from 6299 to 10,422 kg ha⁻¹). Although the energy ratio declined from 1.13 to 0.47, the integrated model effectively demonstrated trade-offs between productivity and sustainability. These findings provide a quantitative decision-support framework for policymakers and environmental managers to promote technology-driven, resource-efficient, and climate-resilient rice farming systems in arid and semi-arid regions.

缺水地区的水稻生产面临严重的环境和资源效率挑战，威胁到长期可持续性。本研究提出了一种结合生命周期评估（LCA）和多目标粒子群优化（MOPSO）的集成框架，以在不影响产量的情况下最小化环境影响和优化投入使用。在伊朗的半干旱地区，使用cml2 -基线方法在十个环境类别中进行了从摇篮到磨坊门的LCA。结果表明，电力（34%）、柴油（16%）和灌溉设备（14%）是造成总体环境负担的主要因素，特别是对全球变暖潜势和化石资源枯竭的影响。通过基于mopso的优化，总环境破坏减少了48%，而水稻产量大幅增加（从6299公斤ha增加到10422公斤ha）。虽然能量比从1.13下降到0.47，但综合模型有效地展示了生产力与可持续性之间的权衡。这些发现为决策者和环境管理者在干旱和半干旱地区推广技术驱动型、资源节约型和气候适应型水稻种植系统提供了定量决策支持框架。

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引用次数: 0

A-ppropriation in theory of language, mind, and technology: Reveals the epistemological problem in the development of learning machines 语言、思维和技术理论中的“占有”：揭示学习机发展中的认识论问题

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-09 DOI: 10.1016/j.sftr.2025.101621

Christian Delesep Ruhupatty, Lilawati Kurnia, Herdito Sandi Pratama

This article explores the foundational theories that underlie the development of learning machines and identifies a core epistemological problem within prevailing conceptions of language, mind, and technology. These domains, which frequently inform the design of learning systems, are typically grounded in representationalist assumptions. In contrast, this article advances a distinct framework through the theory of a-ppropriation, which refers to the mind-body capacity to appropriate—or manipulate—the essence of reality into personal perspectives and actions. Within this framework, human understanding is conceived as a direct engagement with the essence of reality, unmediated by representational structures, and expressed within comprehensible, articulable, and utilizable forms such as language, art, and technology. Accordingly, the learning machine is not understood as a mirror of human cognition, but as an embodiment of appropriation: a system designed to interpret data and prompts directly by locating their equivalent and parallel forms within both the data center and user input. As a result, the machine generates responses within a mode of “personal understanding.” In other words, it does not rely on representational modeling or conventional machine learning systems based on binary syllogism, but instead functions as an agentic machine—capable of interpreting novel data and prompts beyond its initial training parameters.

本文探讨了学习机器发展的基础理论，并在流行的语言、思维和技术概念中确定了一个核心认识论问题。这些领域经常为学习系统的设计提供信息，通常以表征主义假设为基础。相比之下，本文通过“挪用”理论提出了一个独特的框架，它指的是身心将现实的本质挪用或操纵成个人观点和行动的能力。在这个框架中，人类的理解被认为是与现实本质的直接接触，不受具象结构的中介，并以语言、艺术和技术等可理解、可表达和可用的形式表达。因此，学习机不应被理解为人类认知的镜子，而应被理解为占有的体现：一种通过在数据中心和用户输入中定位数据和提示的等价和平行形式来直接解释数据和提示的系统。因此，机器在“个人理解”模式下产生响应。换句话说，它不依赖于基于二元三段论的表征建模或传统机器学习系统，而是作为一个代理机器，能够解释新数据并提示超出其初始训练参数。

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引用次数: 0

Breaking ground: A new theoretical proposition for subsistence entrepreneurship through a personalist lens 突破：个人视角下的自给创业新理论命题

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-08 DOI: 10.1016/j.sftr.2025.101640

Carlos M. Jardon , Elena Rapoport , Xose L. Pastoriza-Rozas , Xavier Martinez-Cobas

Considering evolving economic and social conditions, there is an increasing need for entrepreneurial concepts that align with changing demands. While subsistence entrepreneurship has been recognized for its potential to alleviate poverty in developing countries, this paper proposes a theoretical framework that integrates existing ideas and incorporates sustainable development objectives from a personalist viewpoint. This novel theoretical grounding is derived from a comprehensive review of the interdisciplinary literature on subsistence entrepreneurship and includes diverse entrepreneurial approaches: Simon's satisfaction theory, and sustainable development objectives. The paper concludes by presenting practical guidance and potential avenues for future research.

考虑到不断变化的经济和社会条件，越来越需要与不断变化的需求相一致的创业概念。虽然自给创业在发展中国家减轻贫困的潜力已得到承认，但本文提出了一个理论框架，该框架整合了现有思想，并从个人主义的角度纳入了可持续发展目标。这一新颖的理论基础源于对生存型创业的跨学科文献的全面回顾，包括多种创业方法：西蒙的满意度理论和可持续发展目标。文章最后提出了今后研究的实践指导和可能的途径。

引用次数: 0

AI on the path to good decisions 人工智能在正确决策的道路上

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-08 DOI: 10.1016/j.sftr.2026.101644

Mindaugas Kiškis

This article examines objections to the use of artificial intelligence (AI) in decisions affecting humans and argues that most objections rest on anthropocentric assumptions rather than evidence about decision quality. Critics often presume that human decision makers are uniquely capable of moral and contextual judgment, while AI systems are inferior, opaque or hostile. The article challenges this view arguing that modern AI systems are an expression of collective human intelligence and ethics, built on the image of human cognition, trained on curated human decisions and operating on best decision making frameworks. Drawing on empirical studies the article shows that modern AI systems offer unique advantages in decision-making, thus may already in some domains be as good at making good decisions as an average individual human. The article deconstructs main criticisms of AI decision-making and introduces the novel argument of inseparability between human and AI decisions. Human and AI contributions are increasingly intertwined, AI involvement is latent and appropriated by humans, making existing accountability frameworks based on a clear human–AI boundary obsolete. The article advocates for the development of agnostic decision-making frameworks that apply universal accountability to both human and non-human agents and provide a path to better decisions.

本文研究了在影响人类的决策中使用人工智能（AI）的反对意见，并认为大多数反对意见基于人类中心主义假设，而不是关于决策质量的证据。批评者通常认为，人类决策者具有独特的道德和情境判断能力，而人工智能系统则较低、不透明或充满敌意。这篇文章挑战了这一观点，认为现代人工智能系统是人类集体智慧和伦理的表达，建立在人类认知的形象之上，在精心策划的人类决策上进行训练，并在最佳决策框架上运行。本文通过实证研究表明，现代人工智能系统在决策方面具有独特的优势，因此在某些领域可能已经与普通人一样擅长做出正确的决策。本文解构了对人工智能决策的主要批评，并介绍了人与人工智能决策不可分割的新论点。人类和人工智能的贡献日益交织在一起，人工智能的参与是潜在的，被人类占用，使现有的基于明确的人类-人工智能边界的问责框架过时。本文倡导发展不可知论决策框架，将普遍问责制应用于人类和非人类代理人，并提供更好决策的途径。

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引用次数: 0

From waste to wear: ANN-driven optimization of 100% sustainable tri-blend yarns from recycled cotton, recycled PET, and ecovero 从废物到穿着：由人工神经网络驱动的100%可持续三混纺纱线的优化，由再生棉、再生PET和再生棉制成

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-08 DOI: 10.1016/j.sftr.2026.101652

Mohammad Rashel Hawlader , Md.Raquibul Hasan Siddiky , Ahmed Jalal Uddin

The textile sector is rapidly transitioning toward recycled fibers, driven by environmental concerns, circular economy initiatives, fluctuating virgin fiber prices, and growing demand for sustainable clothing. This study aimed to develop a sustainable, high-performance tri-blend yarn composed of recycled cotton (r-cotton), recycled polyester (r-PET), and Ecovero (a certified sustainable viscose). The blend was designed to achieve a synergistic balance, with r-cotton providing softness, eco-friendliness, and cost efficiency; r-PET contributing durability, quick-drying, and wrinkle resistance; and Ecovero enhancing comfort, absorbency, luster, and drape. Optimizing fiber proportions to maximize recycled content while maintaining low unevenness, imperfections, and hairiness, along with adequate strength and elongation of yarns for industrial fabric production, posed a complex challenge. To address this, MATLAB software was employed, which generated thirteen experimental blends. The yarns were spun, and the yarn properties were evaluated using Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models. Both models developed predictive equations, and recommended optimized blend ratios with corresponding yarn characteristics. Final yarn samples were produced and compared against predicted values. The results showed that while both models demonstrated reliable predictive capability, the ANN model provided superior accuracy, with its optimized blends aligning more closely with the targeted yarn properties.

在环境问题、循环经济倡议、原始纤维价格波动以及对可持续服装需求不断增长的推动下，纺织行业正在迅速向再生纤维过渡。本研究旨在开发一种可持续、高性能的三混纺纱线，该纱线由再生棉（r-cotton）、再生聚酯（r-PET）和Ecovero（一种经认证的可持续粘胶）组成。混纺的设计是为了达到协同平衡，与r-棉提供柔软，环保和成本效益；r-PET有助于耐久性，快干性和抗皱性；和Ecovero提高舒适性，吸收性，光泽和悬垂。优化纤维比例以最大限度地提高回收含量，同时保持较低的不均匀度、不完美度和毛羽，以及用于工业织物生产的纱线的足够强度和伸长率，这是一个复杂的挑战。为了解决这个问题，使用MATLAB软件，生成了13个实验混合物。采用多元线性回归（MLR）和人工神经网络（ANN）模型对纱线性能进行评价。这两个模型都建立了预测方程，并根据相应的纱线特性推荐了优化的混纺比。生产最终纱线样品并与预测值进行比较。结果表明，虽然两种模型都具有可靠的预测能力，但人工神经网络模型提供了更高的准确性，其优化的共混物更接近目标纱线的性能。

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引用次数: 0

Strategic environmental investment under intergovernmental regulatory competition: An evolutionary game approach 政府间监管竞争下的战略环境投资：一个进化博弈方法

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-08 DOI: 10.1016/j.sftr.2026.101646

Lu Zhang , Yan Song , Ming Zhang

Competitive pressures among local governments have become an increasingly important factor shaping environmental governance. By integrating the Porter Hypothesis and the Pollution Haven Hypothesis within a unified analytical framework, this study develops an evolutionary game model involving local governments, external governments, and firms to examine how intergovernmental competition in environmental regulation influences corporate environmental investment behavior. Numerical simulations are conducted to explore the evolutionary trajectories of each actor’s strategy under different parameter settings. The results reveal that: (1) Firms are more likely to adopt environmental investment strategies when both levels of government effectively enforce stringent environmental regulations. However, as external governments tend to relax regulatory intensity, firms become more inclined to evade regulation rather than pursue innovation-driven investment. (2) Well-designed reward and punishment mechanisms further encourage firms to engage in environmental investment, whereas excessive growth in environmental subsidies weakens the enforcement capacity of local governments. (3) Strengthening penalties imposed by higher-level governments and increasing the weight of environmental quality indicators in performance evaluations enhance local environmental regulation and stimulate firms’ proactive environmental behavior.

地方政府之间的竞争压力已成为影响环境治理的日益重要的因素。本文将波特假说和污染避风港假说整合到一个统一的分析框架中，建立了一个涉及地方政府、外部政府和企业的演化博弈模型，以考察环境监管中的政府间竞争对企业环境投资行为的影响。通过数值模拟，探讨了不同参数设置下各行为体策略的演化轨迹。结果表明：(1)当两级政府有效执行严格的环境法规时，企业更有可能采取环境投资策略。然而，由于外部政府倾向于放松监管强度，企业更倾向于逃避监管，而不是追求创新驱动的投资。(2)合理的奖惩机制进一步鼓励企业参与环境投资，而环境补贴的过度增长削弱了地方政府的执法能力。(3)加大上级政府的处罚力度，提高环境质量指标在绩效评价中的权重，加强地方环境监管，激发企业积极主动的环境行为。

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引用次数: 0

Supply chain inefficiencies undermining smallholder farmer sustainability: Insights from a developing economy 供应链效率低下削弱了小农的可持续性：来自发展中经济体的见解

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-08 DOI: 10.1016/j.sftr.2025.101638

W. Madushan Fernando , R.M. Chandima Ratnayake , Amila Thibbotuwawa , H. Niles Perera

Smallholder farming is crucial for food security and rural livelihoods in developing economies; however, productivity and income remain bound by persistent inefficiencies along agri-food supply chains. This research explores how such inefficiencies impact crop yield, quality, and farmer livelihoods, using the Sri Lankan tea smallholder supply chain as the main case. Through the use of an abductive reasoning approach, we carried out a four-step analysis that consisted of a case study evaluation, development of a causal loop diagram, an analytic hierarchy process model construction, and insights synthesis. Our findings indicate that farm input supply (33.03%) and regulation (28.2%) are the most impactful value chain functions on smallholder performance. Inadequate investment, fragmented policies, limited digitisation and scalability of extension services, shortages of labour, and restricted access to finances, among other high-priority inefficiencies, emerge as structural barriers that hold down yields and incomes and increase vulnerability to livelihoods. These results illustrate how systemic inefficiencies self-reinforce to pose long-term risks for food security and rural development. Such challenges will need targeted investment in support of regulation and digital and financial inclusion strategies in strengthening the resilience of smallholders. This study hence provides a combined empirical framework through which to analyse inefficiencies of supply chains and their various impacts on sustainability within small-scale farming systems.

小农农业对发展中经济体的粮食安全和农村生计至关重要；然而，生产力和收入仍然受到农业食品供应链持续低效率的制约。本研究以斯里兰卡茶叶小农供应链为主要案例，探讨了这种低效率如何影响作物产量、质量和农民生计。通过使用溯因推理方法，我们进行了四步分析，包括案例研究评估、因果循环图的开发、分析层次过程模型的构建和见解合成。研究发现，农业投入供给（33.03%）和监管（28.2%）是对小农绩效影响最大的价值链功能。投资不足、政策分散、推广服务的数字化和可扩展性有限、劳动力短缺、融资渠道受限，以及其他高度优先的低效问题，都成为结构性障碍，压低了产量和收入，增加了生计的脆弱性。这些结果表明，系统性效率低下如何自我强化，对粮食安全和农村发展构成长期风险。这些挑战需要有针对性的投资，以支持监管以及数字和金融包容性战略，以加强小农的抵御能力。因此，本研究提供了一个综合的经验框架，通过该框架可以分析供应链的低效率及其对小规模农业系统可持续性的各种影响。

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引用次数: 0

Identifying accident and safety risks in urban micromobility: An analytical approach using machine learning 识别城市微交通中的事故和安全风险：使用机器学习的分析方法

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-07 DOI: 10.1016/j.sftr.2025.101452

Pires Abdullah , Domokos Esztergár-Kiss , Tibor Sipos

Micromobility has recently emerged as a popular and sustainable mode of transportation in urban areas. Understanding the accident-related factors of this new transport mode is crucial to ensure safe and enjoyable user experience. This study applies a machine learning approach, specifically the decision tree algorithm, to investigate those factors that lead to accidents by drivers using three types of micromobility devices: normal bicycle, e-bicycle, and e-scooter. This method can determine the relationship between various attributes and target variables. The research methodology adopted in this study includes a survey analysis involving questionnaires conducted among residents of Budapest, Hungary. The survey covers various aspects such as socio-demographics, mobility patterns, trip types, riding locations, and safety concerns. The attributes are analyzed with the elaborated method using the Python programming language. The results of the study demonstrate that the attitude of frequently wearing a helmet and the trip type are the primary elements related to accidents in the process. Moreover, variables such as age, gender, and riding location contribute to accident occurrence, as well. Policy implications include promoting helmet usage and enhancing the infrastructure to improve micromobility safety.

微型交通最近成为城市地区流行的可持续交通方式。了解这种新型交通方式的事故相关因素对于确保安全和愉快的用户体验至关重要。本研究应用机器学习方法，特别是决策树算法，来调查驾驶员使用三种类型的微移动设备（普通自行车、电动自行车和电动滑板车）导致事故的因素。该方法可以确定各种属性与目标变量之间的关系。本研究采用的研究方法包括对匈牙利布达佩斯居民进行问卷调查分析。这项调查涵盖了社会人口统计、出行模式、出行类型、骑行地点和安全问题等各个方面。利用Python编程语言，用阐述的方法对其属性进行了分析。研究结果表明，频繁佩戴头盔的态度和出行方式是导致事故发生的主要因素。此外，年龄、性别、骑行地点等变量也会影响事故的发生。政策影响包括促进头盔使用和加强基础设施，以提高微交通安全。

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引用次数: 0

Assessing the performance of smart cities in China: A TOPSIS and DEA approach 中国智慧城市绩效评估：TOPSIS和DEA方法

IF 4.9 2区社会学 Q2 ENVIRONMENTAL SCIENCES

Sustainable Futures

Pub Date : 2026-01-07 DOI: 10.1016/j.sftr.2026.101651

Wei Chen , Jing Quan , Yongjian Zhang , Yao Zhang

As an effective measure to solve the “urban disease”, smart cities have attracted great attention worldwide. A comprehensive and accurate evaluation of China’s smart cities not only helps to promote China’s smart city projects but also has important significance for other countries. This study first constructed an evaluation system widely applicable to China’s smart cities by reviewing the literature and policies. Then, TOPSIS and DEA were used to evaluate the performance and efficiency of 290 cities in China, and then AISM was used to classify 30 provinces to evaluate the construction levels of smart cities in China. The study results demonstrated that the overall performance of Chinese smart cities is insufficient, and the level of knowledge is low. There is no obvious relationship between urban performance and efficiency. Along different dimensions, there are significant differences between cities, presenting a polarized situation. The AISM results indicate that the adversarial hierarchy diagrams of 30 provinces are olive-shaped structures and pyramid-shaped structures. The evaluation results supplement comprehensive analysis of the development of smart cities in China. To some extent, the introduction of the AISM method promotes the development of smart city evaluation methods and improves the smart city evaluation system.

智慧城市作为解决“城市病”的有效措施，在世界范围内备受关注。对中国智慧城市进行全面、准确的评估，不仅有助于推动中国智慧城市项目的发展，对其他国家也具有重要意义。本研究首先通过对文献和政策的梳理，构建了一个广泛适用于中国智慧城市的评价体系。然后利用TOPSIS和DEA对中国290个城市的绩效和效率进行评价，然后利用AISM对30个省份进行分类，对中国智慧城市的建设水平进行评价。研究结果表明，中国智慧城市整体绩效不足，知识水平较低。城市绩效与效率之间没有明显的关系。在不同维度上，城市间存在显著差异，呈现两极分化的态势。结果表明，30个省区的对抗层级图呈现橄榄形结构和金字塔形结构。评估结果补充了中国智慧城市发展的综合分析。在一定程度上，AISM方法的引入促进了智慧城市评价方法的发展，完善了智慧城市评价体系。

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引用次数: 0