服务外包与我国南方地区农业机械化发展——理论逻辑与经验分析

SERVICE OUTSOURCING AND AGRICULTURAL MECHANIZATION IN CHINA ——THEORETICAL LOGIC AND EMPIRICAL ANALYSIS

关键词:  土地规模 劳动力 机械技术 服务外包 南方地区

Key words:  land scale  labor  mechanical technology  outsourcing service  southern area

摘要:

文章通过梳理已有文献针对土地规模对农户机械技术采纳行为影响的相关观点，理顺其中问题与逻辑，指出我国南方地区在人多地少的特殊农情与农地流转高交易成本的约束下，单纯追求经营个体增加土地面积的发展惯性并不能有效解决机械技术应用的规模性要求，过度依赖农地流转集中扩大经营规模从而推进农业机械化的道路存在一定理论与政策上的误导，需转向以“服务流动”聚合众多小农户机械服务需求的农机服务外包的机械化发展路径。进而，利用广东农户问卷数据，采用Logistic模型，实证考察影响农户农机服务外包行为的因素。研究发现：土地经营规模与土地流转面积对农户农机服务外包影响不显著，但土地细碎化是农户选择农机服务外包的重要制约因素；务农劳动力“老龄化”与“女性化”对农户农机外包的影响并不显著，但农业雇工市场工价、农户的受教育水平、组织化程度及非农收入等禀赋因素及区域政策环境与经济环境变量的区域因素有显著的正向作用。

Abstract:

Combining related ideas of the existing literature on the effect of land scale on mechanical technology adoption behaviors，this paper straightened out the theoretical logic and problemsIt pointed out that simply increasing the land area of individual operator cannot effectively meet the scale requirement of mechanical technology application in southern China because of the constraint of the special agricultural problems of many people with little land and high cost of farmland circulationThe path relying on expanding land scale by farmland circulation to promote agricultural mechanization may become certainly misleading in theory and policyAgricultural mechanization needed to be transferred from relying on centralized land circulation to service outsourcing business by aggregating small farmers' demand and enlarging social transaction scaleAnd then，it empirically analyzed the specific factors of farmers' agricultural machinery service outsourcing behaviorThe results showed that scale of land management and land circulation area had no significant impact on the farmers' agricultural machinery service outsourcing，but land fragmentation was one of the important obstacles for farmers'farm machinery outsourcing selectionAging and feminine agricultural labor force had no significant impact on farmers'farm machinery outsourcing，but agricultural market wages of employees，farmer's education level，organizational degree，non-agricultural income，regional policy environment and economic variable had significant positive effects.