A Study on the Compatibility between the Digital Reform of Agricultural Insurance and the Needs of Farmers: A Case Study of Ningbo City, Zhejiang Province

. Agricultural insurance of China has covered all fields of agriculture, including forestry, animal husbandry and fishery. Although great progress has been made in the digital reform of agricultural insurance, the degree of digitalization of agricultural insurance is still slow. Farmers' understanding and participation in agricultural insurance is the important consideration of promoting digital degree of agricultural insurance in Zhejiang Province. Focusing on the supply-side reform, the digital reform of agricultural insurance also needs to consider the situation of the demand-side of farmers, promote traditional agriculture to have been transformed from "relying on the weather" to "working with the weather".


Introduction
By August 2023, agricultural insurance of China has covered all fields of agriculture, including forestry, animal husbandry and fishery.From January to August 2023, 140 million rural households will be covered, providing 3.7 trillion RMB (506.7 billion dollars) of risk protection.From the perspective of natural geography, Ningbo is located in the southeast coast, and the agricultural natural risk is relatively prominent.Typhoons and other natural disasters occur frequently.Typhoon Haikui in 2012, Fitow in 2013, Chan-hong in 2015 and Leqima in 2019 all caused serious impacts on the agricultural field [1].From the perspective of agricultural industry, the main body of agricultural production in Ningbo is still small-scale decentralized operation.In the process of operation, there are price fluctuations caused by backward management methods, untimely information update, and changes in market supply and demand, which ultimately affect the income level of farmers.The *Corresponding author: zhangqingyi1983@zjgsu.edu.cnimbalance between market supply and demand leads to the occurrence of grain and vegetable cheap which is harmed to farmers.In addition, the deep processing of agricultural products lags is not good enough, the cold chain storage and transportation capacity of agricultural products is weak, and the ability to resist market risks is not strong.Therefore, it is necessary to vigorously develop agricultural insurance to hedge the risk of agricultural product market price fluctuations.Risk reduction is not only an important manifestation of the social value created by insurance, but also an inevitable requirement for the high-quality development of insurance companies.Insurance institutions should focus on improving the digital level of insurance services, keep pace with the times and respond accurately to the constantly updated and iterated risk demand, and give full play to the role of modern social "stabilizer" and economic "booster".Frequency analysis was used to analyze the basic information of gender, age and education level of the respondents, as shown in Table 1: (1) Research Hypothesis When using SEM for analysis, we should not make assumptions about the path of each model, but evaluate the compatibility between the overall SEM model and the sample data.However, in order to ensure that there is no significant difference in the relevant paths of the adjusted model, the following research hypotheses are proposed: There is no difference between the expected covariation matrix of the model and the sample covariation matrix; It is assumed that the implementation of government policies has a positive and significant impact on consumer satisfaction; It is assumed that consumer expectations positively and significantly affect consumer satisfaction; It is assumed that after-sales service positively and significantly affects consumer satisfaction; It is assumed that the insurance effect positively and significantly affects consumer satisfaction; It is assumed that after-sales service positively and significantly affects the implementation of government policies; It is assumed that the insurance effect positively and significantly affects the implementation of government policies; It is assumed that the implementation of government policies positively affects consumer expectations.
(2) Variable Setting According to the basic principle of structural equation modeling, the four variables of government policy, insurance effect, after-sales service and consumer expectation directly affect consumer satisfaction, and there is an interaction relationship among these four variables.Through literature review and in-depth interviews with relevant parties, the subordinate variables of each variable are sorted out.The Alpha coefficient of each latent variable was above 0.7, indicating that the latent variable was highly reliable and could be included in the model path diagram [4].The fitting indices of this model are satisfactory.

Initial Setting of the Model
However, there may be some problems in the preliminary model, so it is necessary to modify the model and establish a new model that is more suitable for the data.

Model Compatibility Evaluation
In  The goodness-of-fit index (CFI) =0.962>0.9indicated that the model fit was good, and the goodness-of-fit index (GFI) =0.901>0.9indicated that the

Conclusion:
Although great progress has been made in the digital reform of agricultural insurance, the degree of digitalization of agricultural insurance is still slow.The degree of government policy implementation is the biggest factor affecting the implementation of digital reform of agricultural insurance.Considering of farmers are the main participants and beneficiaries of agricultural insurance, digital reform of agricultural insurance should meet the needs of farmers.The government should strengthen publicity, and insurance companies should provide thoughtful services to farmers in order to make sure they understanding the complex policy of agricultural insurance vert well.In the process of insurance service, insurance institutions ensure that post-disaster exploration and insurance compensation are timely and fully in place, so that agricultural insurance can bring real benefits to farmers, promote traditional agriculture to have been transformed from "relying on the weather" to "working with the weather".

2 SHS
Leqima caused severe losses to agricultural production and operation in Ningbo City.PICC Ningbo Branch called seven drones, including large drones rented from a third party.The staff compared and corrected the loss determination results of the insured land parcels with the relevant data of "Yinong Insurance" APP and satellite remote sensing technology, carried out spatial standardization processing of the claim information of the insured varieties, integrated and processed various data information such as policy information, disaster information and claim information, so as to settle claims according to the figure and truly realize the rapid and convenient claim settlement to households.Give full play to the role of agricultural insurance in reducing the loss of natural disasters.Using meteorological data to develop new agricultural meteorological index insurance is another practical innovation to improve the digital level of agricultural insurance.Zhejiang province has set up a working group on agrometeorological index insurance to strengthen guidance and supervision for the insurance industry and policy-holders, and promote the orderly development of agrometeorological index insurance.Agricultural and rural departments in Ningbo, together with meteorological departments, financial departments and financial departments, have launched a variety of agrometeorological index insurance such as rice planting, bayberry planting and aquaculture, and applied meteorological data to the whole process of agricultural insurance underwriting and claim settlement.Zhejiang Province has carried out a pilot project of catastrophe insurance in agricultural and rural areas.Ningbo Meteorological Bureau has taken the lead in introducing meteorological parameters into insurance products, and reasonably setting trigger points for claims such as typhoon, rainstorm and blizzard.Xiangshan County of Ningbo city, together with the Bureau of Agriculture and Rural Areas, the Meteorological Bureau and insurance institutions, has built a "meteorological + agricultural insurance" platform to expand the insurance coverage of agrometeorological index.A large number of planting and breeding households, such as portunid, white prawn, giant freshwater prawn and flower seedlings, have benefited from the insurance of related meteorological index, and the comprehensive benefit of meteorological service has been continuously improved.The comprehensive benefits of meteorological services have been continuously improved.Traditional agriculture has been transformed from "relying on the weather" to "working with the weather".Although great progress has been made in the digital reform of agricultural insurance, the degree of digitalization of agricultural insurance is still slow.In addition to focusing on the supply-side reform, the digital reform of agricultural insurance also needs to consider the situation of the demand-side of farmers.Centered on the needs of farmers in agricultural production and operation, guided by the risk needs faced by agricultural and rural areas, guided by agriculure related insurance policies, and driven by digital information, we should comprehensively promote the development of agricultural insurance to serve modern agriculture, increase farmers' income and get rich, and the process of rural modernization.What are Web of Conferences 181, 04039 (2024) https://doi.org/10.1051/shsconf/202418104039ICDEBA 2023 the weak links in the agricultural production and operation needs of farmers?This study focuses on the compatibility between agricultural insurance digital reform and farmers' needs.Through field investigation and research, this study explores the direction of agricultural insurance digital reform and development from the perspective of farmers' agricultural production and operation needs, and puts forward countermeasures and suggestions.This paper focuses on two questions:1.Farmers' willingness to participate agricultural insurance; 2. The role of digital technology in the process of high-quality development of agricultural insurance.2 Analysis of Questionnaire Data This paper provides an empirical analysis of farmers' understanding and participation in agricultural insurance in Qiujiashan Village, Danxi Street, Xiangshan County, Ningbo City.A total of 340 questionnaires were distributed through random survey, of which 302 were valid, with an effective rate of 88.82%.38 invalid questionnaires were excluded due to too many missing answers (3/2 of the missing questions) and the options of the whole questionnaire were the same.SPSS was used for frequency analysis and cross analysis, and the questionnaire indicators were classified.SPSS was mainly used for frequency analysis and cross analysis, and questionnaire indicators were classified.
AMOS software was used in this modeling.After setting the causal relationship path diagram as required, the results were obtained by running the program, as shown in the figure below:

Fig. 1
Fig.1 Initial Setting Diagram of the Model structural equation modeling, statistical methods (such as maximum likelihood method) are used to find the model parameters that minimize the difference between the sample variance covariance matrix and the theoretical variance covariance matrix.On the other hand, if the theoretical model structure is reasonable for the collected data, then the sample variance covariance matrix and the theoretical variance covariance matrix have little difference, that is, each element of the residual matrix is close to 0, and the model is considered to fit the data.The model compatibility index is a statistical index to investigate the fitting degree of the theoretical structure model to the data.Different types of model fit indices can be used to measure the theoretical model from the aspects of model complexity, sample size, relativity and absolute.Amos provides a variety of model fit indices for model testing.Using a variety of model fitting indexes provided by Amos software, combined with the indicators commonly used by experts and scholars in various academic circles over the years, eight main indicators were selected for model testing.The specific test results are shown in the following table:

Table 1 .
Basic Information Analysis

Table 2 .
Shows the Setting of Observation Variables

Table 3 .
Table of Alpha coefficient of each latent variable

Table 4 .
Table of Fitting Indices of Various Models