关键词：
family farm;financing willingness and behavior;Internet of Things;SEM model;water resource financing
摘要：
At present, China's rural water resources are in short supply and the water pollution situation is severe. Family farms are an important part of China's agricultural modernization, and their development level is an important indicator to measure the degree of modernization of a country and a region. The application of agricultural Internet of Things technology in the field of agriculture is helpful to solve the problem of water shortage in family farms in water shortage areas. Based on the questionnaire data, this paper used structural equation modeling (SEM) to study the relationship between family farm water financing willingness and behavior. The results showed that the standardization coefficients of Assumption 1, Assumption 2 and Assumption 3 were 0.332, 0.267 and 0.311, respectively. It can be seen that the water resource financing willingness of family farms was greatly affected by their water-saving technology ability, water management ability and government policy support. However, the standardization coefficient of Assumption 5 was 0.087. It can be seen that the water management capacity had no significant impact on the water resource financing behavior, and the water resource financing behavior of family farms was mainly affected by their water-saving technical capacity and government policy support.
作者机构：
[Xiong, Xiaoling; Li, Jizhi] Hunan Agr Univ, Sch Business, Changsha 410128, Peoples R China.;[Lin, Zejian; Xiong, Xiaoling] Inst Subtrop Agr, Chinese Acad Sci, Changsha 410125, Peoples R China.
通讯机构：
[Jizhi Li] S;School of Business, Hunan Agricultural University, Changsha 410128, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
heavy metal-contaminated cultivated land remediation;conflict of interest;evolutionary game;ladder multiple supervision
摘要：
The heavy metal pollution of cultivated land in China is severe, requiring remediation. Introducing third-party governance subjects representing market resources is inevitable to realize the specialization and socialization of cultivated land remediation. However, due to the public nature of cultivated land, the confusion about participating parties’ responsibilities and difficulty coordinating interests restrict the expected effect of cultivated land remediation. To this end, a three-party evolutionary game model among the grassroots government, governance enterprises, and supervisory enterprises is constructed and virtually simulated, taking into account the influence of random checks by the higher-level government. We found that the reward and punishment mechanism of the grassroots government, the frequency of random inspection by the higher-level government, and the amount of deduction will influence the strategy selection of the participating parties. Strengthening the awareness of the responsibility of the grassroots government, optimizing the incentive system, establishing a regular spot-check system, and improving the cost of non-compliance by enterprises can effectively resolve conflicts of interest among the participants. The study results have practical significance for further enhancing the remediation efficiency of heavy metal-contaminated cultivated land.
关键词：
behavior intention;Theory of Planned Behavior (TPB);Technology Acceptance Model (TAM);Innovation Diffusion Theory (IDT);Motivational Model (MM)
摘要：
Green control techniques (GCT) are an important supporting technology to ensure sustainable agricultural development. To advance the adoption of GCT, it is crucial to understand the intention of farmers to adopt GCT and its related determinants. However, current research is mostly limited to using a single theoretical model to explore farmers' intentions to adopt GCT, which is not conducive to revealing the determinants of farmers' intentions to adopt GCT. To address this gap, this study integrates the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), the Innovation Diffusion Theory (IDT), and the Motivational Model (MM) based on research data from 362 rice farmers in Heshan District, Yiyang City, Hunan Province, and uses partial least squares structural equation modeling (PLS-SEM) to empirically test and compare the above models. The model comparison results prove that the TPB (R-2 = 0.818, Q(2) = 0.705), TAM (R-2 = 0.649, Q(2) = 0.559), IDT (R-2 = 0.782, Q(2) = 0.674), and MM (R-2 = 0.678, Q(2) = 0.584) models all have explanatory power and predictive validity in the context of green control techniques. However, the integrated model (R-2 = 0.843, Q(2) = 0.725) is found to be superior to these individual theoretical models because it has larger values of R-2, Q(2), and smaller values of Asymptotically Efficient, Asymptotically Consistent, and provides a multifaceted understanding for identifying the factors influencing adoption intentions. The results of the path analysis show that attitude, perceived behavioral control, perceived usefulness, subjective norm, and visibility significantly and positively influence adoption intentions in both the single and integrated models and are determinants of farmers' intentions to adopt GCT.
