资源科学 ›› 2020, Vol. 42 ›› Issue (2): 286-297.doi: 10.18402/resci.2020.02.08

• 土地资源 • 上一篇    下一篇

基于SEM-SD模型的城市近郊区农户土地投入行为决策机制仿真研究

任立1, 吴萌2, 甘臣林3, 陈银蓉4()   

  1. 1. 湖北经济学院财政与公共管理学院,武汉 430205
    2. 湖北经济学院会计学院,武汉 430205
    3. 湖北经济学院财经高等研究院,武汉 430205
    4. 华中农业大学公共管理学院,武汉 430070
  • 收稿日期:2019-07-26 修回日期:2019-10-14 出版日期:2020-02-25 发布日期:2020-04-25
  • 通讯作者: 陈银蓉
  • 作者简介:任立,男,湖北武汉人,讲师,研究方向为行为经济学。E-mail: renli@hbue.edu.cn
  • 基金资助:
    教育部人文社会科学青年基金项目(19YJCZH132)

Decision-making mechanism simulation of farmers’ land investment behavior in suburbs based on structural equation modeling-system dynamics

REN Li1, WU Meng2, GAN Chenlin3, CHEN Yinrong4()   

  1. 1. School of Public Finance and Administration, Hubei University of Economics, Wuhan 430205, China
    2. College of Accounting, Hubei University of Economics, Wuhan 430205, China
    3. Institute of Advanced Studies in Finance and Economics, Hubei University of Economics, Wuhan 430205, China
    4. College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China
  • Received:2019-07-26 Revised:2019-10-14 Online:2020-02-25 Published:2020-04-25
  • Contact: CHEN Yinrong

摘要:

在农村土地制度改革和劳动力向城市转移的双重背景下,农户群体正经历由传统“农业生产劳动力”向新型“农业经营决策者”的转型。面对土地投入“高成本、高劳耗和低效益”的现实特征,小型农户是典型的“风险规避者”,其土地投入行为对风险因素更加敏感,但其背后的认知机理和决策逻辑尚未明确。本文基于分布式认知理论和感知价值理论,结合武汉城市圈近郊区483名小型农户的微观调查数据,采用结构方程模型和系统动力学模型的分析方法,对农户土地投入风险认知的影响因素和土地投入行为的发展趋势分别进行了静态分析和动态仿真。研究表明:①农户土地投入感知风险遵循分布式认知的基本框架,受到“个人力”“地域力”和“文化力”3个认知功能系统的影响,其效应排序为“地域力>个人力>文化力”,农户对土地投入的风险认知主要来源于土地投入行为本身,同时也是个体内部因素和外部环境因素综合作用的结果;②“高风险、低收益→弱化感知价值→降低投入意愿→减少投入行为→较高风险、更低收益”的“递弱回路”是制约农户土地投入的基本逻辑,在一定的政策引导和禀赋约束条件下,农户能够在短期内保持土地投入行为,但传统的低效土地利用方式终将难以持续,对于小型农户而言,土地资源作为生产资料的功能性衰退将不可逆转。助力培育新型农业经营主体、加快促进农业现代化转型是未来农村土地制度改革的发展目标。

关键词: 土地投入, 农户行为, 分布式认知理论, 感知价值理论, 结构方程模型, 系统动力学模型, 武汉城市圈

Abstract:

Under the background of rural land institution reform and labor force transfer into cities, farmers are undergoing the transformation from the traditional role of agricultural production labor force to the new role of agricultural management decision makers. Given the characteristics of high cost, high labor input, and low benefit of land investment, small-scale farmers are typical risk avoiders whose land investment behavior is more sensitive to risk factors, but their cognitive mechanism and decision-making logic are not clear yet. Based on the distributed cognition theory and perceived value theory, we conducted a survey of 483 small-holder farmers in the suburbs of the Wuhan metropolitan area. Then we used the methods of structural equation model and system dynamics model to perform the static analysis and dynamic simulation of the influence of farmers’ land investment risk perception and the development trend of investment behaviors. The research shows that: (1) Farmers’ perceived risk of land investment follows the basic framework of distributed cognition theory and is affected by the three cognitive function systems of “human power” “regional power” and “cultural power”, indicating that farmers’ risk perception of land investment mainly comes from the behavior itself, which is also the result of the combined effect of individual internal factors and external environmental factors. (2) High risk and low benefits lead to weakened perceived value, which in turn lead to reduced investment willingness, then to reduced investment behavior response, and finally higher risk and lower benefits, which form a vicious circle that restrict farmers’ land investment. Under certain policy guidance and endowment constraints, farmers can maintain their land investment behavior in a short term, but the traditional inefficient land use mode will eventually be unsustainable and for small-holder farmers the decline of productive function of land resources will be irreversible, thus the goal of rural land system reform should focus on cultivating new agricultural operators and accelerating the transformation of agricultural modernization.

Key words: land investment, farmers’ behavior, distributed cognitive theory, perceived value theory, structural equation modeling, system dynamics model, Wuhan Metropolitan Area