机遇与认知如何促进家庭农场低碳生产行为:来自中国的证据

IF 6.1 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Lei Zhu, Shaocong Yan, Lili Geng, Xiaomeng Liang, Yongji Xue
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引用次数: 0

摘要

气候变暖被广泛认为是众多全球挑战的关键驱动因素,对人类的生存和发展构成重大威胁。在导致气候变暖的各种因素中,高碳农业实践(如过度使用化肥、农药和塑料薄膜)产生的温室气体排放尤其令人担忧。因此,研究农业生产者的低碳生产决策行为对缓解农业对气候变化的负面影响至关重要。目的探讨家庭农场实施低碳生产行为是受个体情感意愿驱动还是受外部环境机遇驱动,构建家庭农场低碳生产行为决策模型,分析直接或间接驱动家庭农场实施低碳生产行为的因素,从而更准确地描述和解释农业生产者的行为选择。方法本研究将动机-机会-能力模型与认知-情感-思维模型相结合,形成家庭农场低碳生产行为决策的综合理论框架。同时,利用偏最小二乘结构方程建模分析技术对假设模型进行实证检验。结果与结论慢碳生产机会对低碳生产行为有直接的积极影响。低碳生产认知也会影响低碳生产行为,但这种影响是积极的、间接的。低碳生产能力、低碳生产动机、低碳生产情感和低碳生产意图在各假设中起中介作用。因此,本研究得出结论:低碳生产机会而非认知是直接触发家庭农场低碳生产行为反应的关键因素。然而,低碳生产认知的内部化过程在家庭农场低碳生产决策中仍然发挥着重要作用。基于家庭农场中“经济人”和“社会人”的双重身份属性,本研究不仅拓展了分析农业低碳生产行为的理论框架,而且强调了个体情感意愿和外部环境机会对家庭农场低碳生产实施的积极影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

How opportunity and cognition improve family farms' low-carbon production behavior: Evidence from China

How opportunity and cognition improve family farms' low-carbon production behavior: Evidence from China

CONTEXT

Climate warming is widely regarded as a crucial driver of numerous global challenges, posing a significant threat to human survival and development. Among the various factors contributing to climate warming, the greenhouse gas emissions from high-carbon agricultural practices—such as the excessive use of fertilizers, pesticides, and plastic films—are particularly concerning. Therefore, it is essential to study the low-carbon production decision-making behaviors of agricultural producers to mitigate the negative impacts of agriculture on climate change.

OBJECTIVE

To investigate whether the implementation of low-carbon production behaviors in family farms is driven by individual emotional willingness or by external environmental opportunities, this study constructs a decision-making model of low-carbon production behaviors in family farms to analyze the factors that directly or indirectly drive the implementation of low-carbon production behaviors, and then more accurately describes and explains the behavioral choices of agricultural producers.

METHODS

This study links the Motivation-Opportunity-Ability model with the Cognitive-Affective-Conative model to form a comprehensive theoretical framework for decision-making on low-carbon production behavior in family farms. Meanwhile, this study empirically tested the hypothesized model using the partial least squares structural equation modeling analysis technique.

RESULTS AND CONCLUSIONS

Low-carbon production opportunity and has a direct and positive effect on low-carbon production behavior. Low-carbon production cognition also affects low-carbon production behavior, but this effect is positive and indirect. Low-carbon production ability, low-carbon production motivation, low-carbon production affection, and low-carbon production intention play a mediating role in all hypotheses. Therefore, this study concludes that low-carbon production opportunity rather than cognition is the crucial element that directly triggers the behavioral response to low-carbon production in family farms. However, the internalization process of low-carbon production cognition still plays an important role in low-carbon production decision-making on family farms.

SIGNIFICANCE

Based on the dual identity attributes of “economic man” and “social man” in family farms, this study not only expands the theoretical framework for analyzing low-carbon production behaviors in agriculture but also emphasizes the positive impacts of the individual's emotional will and external environmental opportunities on the implementation of low-carbon production in family farms.
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来源期刊
Agricultural Systems
Agricultural Systems 农林科学-农业综合
CiteScore
13.30
自引率
7.60%
发文量
174
审稿时长
30 days
期刊介绍: Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.
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