The Impact of Government Subsidies and Quality Certification on Farmers’ Adoption of Green Pest Control Technologies

Abstract

Shandong and Henan provinces face significant pest and disease issues, creating a strong demand for green pest control technologies. This paper analyzes the impact of government subsidies and quality certification on farmers’ adoption of green pest control technologies, based on 419 survey responses collected through stratified sampling in Shandong and Henan provinces in 2024, using the Heckman two-stage model. The results show the following: (1) Government subsidies and quality certification significantly promote farmers’ adoption of green pest control technologies, with regression coefficients of 0.260 and 0.493, respectively. (2) An interaction effect exists between government subsidies and quality certification on farmers’ adoption of green pest control technologies, with a coefficient of 0.454. For a given government subsidy, higher quality certification levels increase the likelihood of farmers adopting green pest control technologies. (3) From the perspective of human capital quantity, there is obvious heterogeneity in the impact of government subsidies and quality certification on farmers’ adoption of green pest control technologies. (4) From the perspective of generational differences, quality certification has obvious heterogeneity on farmers’ adoption of green pest control technologies, while there is no obvious generational difference in government subsidies. Therefore, it is necessary to establish a stable and multi-channel government transfer payment system, improve the construction of the agricultural product quality traceability system, take a two-pronged approach, and complement each other’s strengths to build a targeted incentive mechanism based on different groups of farmers.

1. Introduction

For a long time, excessive use of chemical pesticides has brought about a series of negative impacts [1,2], such as increased agricultural production costs and aggravated agricultural non-point source pollution [3,4]. Green control technology has excellent characteristics such as economical production and environmental friendliness and has become an effective way to reduce the use of chemical pesticides and promote green agricultural development [5,6,7]. At the 2006 National Plant Protection Conference, the adoption of various green control measures, including agricultural control and physical trapping, was encouraged. In 2015, the Ministry of Agriculture launched the Zero Growth Action for Chemical Fertilizers and Pesticides, which highlighted the full promotion of green pest control technologies. However, in actual agricultural production, green pest control technologies have not been widely adopted by micro-farmers, and the coverage rate is still low. Therefore, how to quickly promote green control technology remains a key issue of concern to the academic community.

Scholars have examined factors influencing the adoption of green pest control technologies and have advocated for government intervention and market mechanisms to mitigate their positive externalities [8,9]. Most scholars argue that government subsidies, as a key intervention, are an important policy tool for addressing public risks and have a direct impact on technology adoption. Regarding green pest control technologies [10], Sahar et al. (2013) [11] found that government subsidies can encourage farmers to adopt green pest control technologies, while the research results of Xiong et al. (2020) [12] show that government subsidies had no obvious effect on promoting farmers to adopt green pest control technologies. Moreover, government subsidies are funded through expenditures, and government finances are limited [13]. As another approach to mitigating the positive externalities of green pest control technologies [14,15], market mechanisms can play a more effective long-term role in guiding farmers towards sustainable production. In recent years, as the green agricultural product market has developed [16], scholars have increasingly focused on quality certification [17], recognizing it as a key factor influencing farmers’ adoption behavior [18]. Research by Xiong et al. (2021) [19] and others found that green certification has a positive impact on farmers’ decision-making in adopting green pest control technologies. Zhang (2020) [20] research indicates that quality certification significantly encourages farmers to adopt green pest control technologies.

Many scholars’ research on the adoption of green control technology provides a basis for reference for this article. Existing literature mostly focuses on the impact of one of the factors, government subsidies or quality certification, on the adoption of green pest control technologies. Few studies explore the adoption of green pest control technologies by farmers from the dual perspectives of government subsidies and quality certification. This study constructs an analytical framework to assess the impact of government subsidies and quality certification on farmers’ adoption of green pest control technologies. It first clarifies the basis for their effects and then explores potential interactions between the two. Finally, it analyzes the heterogeneity in green pest control technologies adoption behaviors across different types of farmers, providing a basis for effective decision-making in promoting green pest control technologies.

2. Theoretical Analysis and Research Hypotheses

Government subsidies play a crucial role in promoting the adoption of green pest control technologies through government intervention [21,22,23]. Government subsidies influence adoption through two main pathways: first, by reducing the additional costs for farmers to adopt green pest control technology [24,25]. This occurs because government subsidies reduce farmers’ costs by providing funds and supplying green pest control products such as yellow boards and sex attractants. As a result, farmers’ expected benefits from continued use of green pest control technologies increase [26], thereby reshaping the cost–benefit balance and internalizing the technologies’ positive externalities [27,28]. Second, it boosts farmers’ confidence in adopting green pest control technologies. By subsidizing green pest control technologies, the government strengthens its comparative advantage over traditional agricultural methods, thus enhancing farmers’ confidence and encouraging the adoption of new technologies [10]. Based on this, the following hypothesis is proposed:

H1. 

Government subsidies positively influence farmers’ adoption of green pest control technologies.

Quality certification, represented by the “three products”—pollution-free, green, and organic certification—is the primary form of the current agricultural product certification system [29,30,31,32,33,34,35]. Quality certification conveys agricultural product quality information through certification labels, reduces information asymmetry, and plays a key role in guiding farmers toward green production [17,33]. Regarding green pest control technologies, quality certification influences adoption through two main pathways: First, it influences farmers’ adoption behavior through product premiums. Compared to conventional agricultural products, quality-certified products offer greater price advantages, and the premium incentive motivates farmers to adopt green pest control technologies [19,36,37]. Second, it influences farmers’ adoption behavior through information acquisition. During quality certification, farmers interact with certification centers and certified entities, broadening their access to agricultural production technologies and helping them understand and adopt green pest control technologies [18,38,39]. Based on this, the following hypothesis is proposed:

H2. 

Quality certification positively influences farmers’ adoption of green pest control technologies.

Government subsidies are a key tool for government intervention, while quality certification serves as an important mechanism for market regulation. Improving resource allocation efficiency requires coordinated governance between these two approaches [40,41]. Government subsidies primarily encourage farmers’ to adopt new technologies through a top-down governance mechanism that compensates them for adoption costs. However, due to factors like small-scale farming and inefficient policy implementation, the coverage of government subsidies remains limited [42]. Quality certification effectively complements government incentives, especially when the latter are insufficient, boosting farmers’ motivation to adopt new technologies. In the context of this study, quality certification increases farmers’ expected benefits from adopting green pest control technologies, thereby enhancing adoption behavior [43,44,45,46]. Based on this, the following hypothesis is put forward:

H3. 

The combined effect of government subsidies and quality certification significantly influences farmers’ adoption of green pest control technologies.

3. Materials and Methods

3.1. Sampling Strategy, Data Sources, and Data Collection

The data in this study primarily comes from a field survey of farmers conducted in Shandong and Henan provinces between July and September 2024. The reasons for selecting Shandong and Henan provinces as survey areas are as follows: First, the development of green control technology in Shandong and Henan provinces is promising. In the first batch of national “green control demonstration counties” for crop pests and diseases announced by the National Agricultural Technology Center in 2020, 10 counties in Shandong and 8 in Henan were recommended, reflecting the positive development and application of green control technology in both provinces. Second, Shandong and Henan are major agricultural provinces in China and also among the hardest hit by pests and diseases. Pest and disease control is a major challenge in these provinces, with pesticide use consistently ranking among the highest in China. The pressure for agricultural pollution control is high, creating a strong demand for green control technology.

Based on this, the research team designed a survey questionnaire that included farmers’ personal and family information, adoption of green control technologies, subsidies received, and quality certification. Next, a preliminary survey was conducted in Dezhou and Linyi cities in Shandong Province and Nanyang and Xuchang cities in Henan Province. Based on this, the questionnaire was modified and improved. The final survey questionnaire is detailed in

Table A1. Survey form.

No.	Question	Options
1	How old are you?	(  ) age
2	What is your gender?	0 = female; 1 = male
3	How many people are there in the labor force in your family?	(  ) people
4	What is your level of education?	1 = no schooling; 2 = primary school; 3 = junior high school; 4 = senior high school/vocational high school; 5 = college or above
5	How many acres of wheat are planted in your family?	(  ) mu
6	How do you think the green agricultural product market compares to the ordinary goods?	0 = pessimistic expectations; 1 = optimistic expectations
7	Is your wheat selling well?	1 = very difficult; 2 = quite difficult; 3 = moderate; 4 = quite easy; 5 = easy
8	Have you ever used crop rotation and grafting in your agricultural production process?	0 = no; 1 = yes
9	In your agricultural production process, have you used alternating pesticides, low-toxicity pesticides, and low-residue pesticides?	0 = no; 1 = yes
10	Have you ever used insect-proof nets, sticky insect boards, or silver-gray films in your agricultural production?	0 = no; 1 = yes
11	Have you ever used sex pheromones, artificially released ladybugs, and other natural enemies to control pests during agricultural production?	0 = no; 1 = yes
12	Have you enjoyed any government subsidies during the agricultural production process?	0 = no; 1 = yes
13	Is your wheat certified as a pollution-free agricultural product?	0 = no; 1 = yes
14	Is your wheat certified as a green agricultural product?	0 = no; 1 = yes
15	Is your wheat certified as an organic product?	0 = no; 1 = yes
16	What province do you live in?	1 = Henan; 2 = Shandong
17	Have you participated in technical training related to green pest control technologies?	0 = no; 1 = yes

in Appendix A. Finally, considering the geographical distribution of green control technologies and the need for pest control, seven cities from the two provinces were selected based on random sampling principles. In each city, 1–2 townships were randomly selected, followed by 2–3 villages from each township and 10–15 farmers from each village. A formal survey was conducted using the questionnaire method, yielding a total of 419 completed questionnaires, as shown in

Table 1. Sample quantity and regional distribution.

Province	City	Township	Village	Sampling Intensity (%)	Sample Size
Shandong Province	Binzhou City	Xiaobotou Town	Liangzhengwang Village	1.31	15
			Beigaojiazhuang Village	1.34	15
		Shimiao Town	Qingyangdian Village	1.47	15
			Liangjia Village	1.53	15
	Dezhou City	Qingyun Town	Houyu Village	1.07	10
			Zhou Yincun	1.15	15
			Shifosi Village	1.57	15
			Weijia Village	2.03	15
	Linyi City	Baishabu Town	Xiyi Village	1.05	13
			Mahezhuang Village	1.25	12
			Qianchuanliu Village	1.68	12
		Bancheng Town	Haobu Village	1.22	16
			Sungou Village	1.59	10
	Weifang City	Jiangzhuang Town	Donglijiazhuang Village	1.05	15
			Niejiaxizhuang Village	1.70	15
		Damoujia Town	Daxinjia Village	1.19	15
			Dasunjia Village	1.19	15
Henan Province	Nanyang City	Qutun Town	Qutun Village	1.56	15
			Qigang Village	1.50	15
		Huangtaigang Town	Liusongying Village	1.14	15
			Xiangzhai Village	1.67	15
	Xuchang City	Shantoudian Town	Dangmiao Village	1.07	15
			Duzhuang Village	1.52	15
		Shilipu Town	Shilipu Village	1.16	15
			Tongzhuang Village	1.35	14
	Zhoukou City	Zhangzhuang Town	Dongquzhuang Village	1.38	12
			Baliwang Village	1.20	12
		Lutai Town	Xiaoyaoying	1.20	18
			Haolou Village	1.01	20
Total					419

. According to the observed demographic data, the majority of the interviewed farmers are male (82.2%), with an average age of 48.9 years old; the education level is mostly junior high school graduates (64.0%); and the number of family laborers is mostly 4 (33.7%).

3.2. Variable Settings

3.2.1. Dependent Variable

The dependent variable is the farmers’ decision to adopt green pest control technologies and the degree of adoption, as shown in

Table 2. Variable type, variable name, and measurement method.

		Variable Name	Meaning and Assignment Instructions	Mean	Variance
Dependent variable		Green control technology adoption decision	0 = not adopted; 1 = adopted	0.868	0.339
		Adoption rate of green control technologies	Number of categories adopting green control technologies	1.880	1.149
Key explanatory variables	Government subsidies	Government subsidies	Have you ever received government subsidies? 0 = no; 1 = yes	0.080	0.264
	Quality Certification	Quality Certification	0 = no certification; 1 = pollution-free certification; 2 = green certification; 3 = certified organic	0.576	1.023
Control variables	Farmer characteristics	age	Actual age of household head/years	48.906	9.877
		gender	0 = female; 1 = male	0.822	0.383
		Agricultural labor	Number of laborers engaged in agriculture	3.856	2.689
		Education	1 = no schooling; 2 = primary school; 3 = junior high school; 4 = senior high school/vocational high school; 5 = college or above	2.833	0.757
		Planting area	Planting area/mu	7.553	7.666
		Market expectations	0 = pessimistic expectations; 1 = optimistic expectations	0.796	0.404
		Sales	1 = very difficult; 2 = quite difficult; 3 = moderate; 4 = quite easy; 5 = easy	3.969	1.111
	Regional variables	Regional variables	1 = Henan; 2 = Shandong	1.687	0.765
Identify variables	Technology Perception	Technical training	Have you participated in technical training related to this technology? 0 = no; 1 = yes	0.483	0.500

. Green pest control technologies are divided into four categories (agricultural pest control technologies, physical pest control technologies, scientific pesticide application technologies, and biological pest control technologies) [14].

3.2.2. Independent Variables

Key explanatory variables: The key explanatory variables are government subsidies and quality certification. Referring to existing research [16], the quality certification level is divided into four levels according to the strictness of the certification requirements: no certification, pollution-free certification, green certification, and organic certification.

Control variables: Referring to existing studies [17,18,19,20], the gender, age, education level, agricultural labor force, planting area, market expectations, sales situation, regional variables, and variety variables of the interviewed farmers were selected as control variables.

Identify variables: To effectively identify the equation, this paper uses “technical training” as the identification variable to measure the effectiveness of technology.

3.3. Model Construction and Statistical Methods

In order to ensure the reliability of the model estimation results, this article first used stata17.0 software to conduct a multicollinearity test on all independent variables in the regression equation. The results showed that the variance inflation factor was far less than 10, indicating that there is a certain degree of independence between the independent variables. In addition, the inverse Mills ratio of each model also passed the significance test, which proves the existence of the sample self-selection problem and also illustrates the rationality of choosing the Heckman two-stage model.

“Adoption decision” and “adoption degree” represent two distinct but closely related stages in farmers’ adoption of green pest control technologies. Different adoption degrees arise only after farmers have made the decision to adopt the technologies. Consequently, this paper uses the Heckman two-stage model to analyze farmers’ adoption decisions in the first stage and the adoption degree in the second stage [47,48,49,50].

First, we construct the farmer adoption decision model for the first stage and use the full survey sample data for binary Probit regression. The equation is as follows:

$$\mathit{Pr}\left(\mathit{di}=1\right)=\varphi ({\beta }_0+\sum _{i=1}^n{\beta }_i{x}_i)$$

(1)

$Pr$ is the dependent variable, representing the probability of an event, specifically the probability of farmers’ adoption decisions ($d_i$ = 1, indicating that green pest control technologies have been adopted; $d_i$ = 0, indicating that green pest control technologies have not been adopted). The right side of the formula is the cumulative normal distribution function, ${\beta }_0$ is the constant term of the regression equation, and $x_i\left(i=1\dots n\right)$ refers to the n factors that affect the sample farmers, ${\beta }_i$ is the corresponding parameter to be estimated. This paper uses the Probit model to estimate the adoption probability for each sample farmer and constructs a correction factor as shown below:

$$\lambda =\phi ({\beta }_0+\sum _{i=1}^n{\beta }_i{x}_i)/[1-\varphi ({\beta }_0+\sum _{i=1}^n{\beta }_i{x}_i\left)\right]$$

(2)

Among these, $\lambda$ is the inverse Mills ratio representing the sample deviation. The statistical significance is that only when $\lambda$ is significantly different from 0, the selectivity bias of the sample cannot be ignored. $\phi \left(x_i\right)$ is the density function of the standard normal distribution, $\varphi \left(x_i\right)$ is the cumulative distribution function.

Secondly, λ is substituted into the regression Equation (3) to eliminate selection bias due to self-selectivity in farmers’ adoption decisions. The least squares estimation method (OLS) is then used to estimate the factors influencing farmers’ adoption of green pest control technologies:

$$y={\alpha }_0+\sum _{i=2}^n{\alpha }_i{x}_i+\omega \lambda +\epsilon$$

(3)

In Formula (3), $y$ is the explained variable, representing the adoption degree of farmers, $x_i$ is the explanatory variable, ${\alpha }_0$ is the constant term, ${\alpha }_i$ and $\omega$ are the parameters to be estimated, and $\epsilon$ is the random error term.

4. Results

4.1. The Impact of Government Subsidies and Quality Certification on Farmers’ Adoption of Green Pest Control Technologies

The empirical results of Model 1 in

Table 3. Estimated results of government subsidies and quality certification on farmers’ adoption of green pest control technologies.

Variable	Model 1		Model 2		Model 3
	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level
Government subsidies	0.225 *** (0.077)	0.263 *** (0.230)			0.260 *** (0.091)	0.356 *** (0.281)
Quality certification			0.480 ** (0.034)	0.488 *** (0.178)	0.493 *** (0.046)	0.420 *** (0.176)
Government subsidy × quality certification					0.454 *** (0.062)	0.216 *** (0.299)
age	0.246 ** (0.111)	0.838 *** (0.259)	0.109 (0.114)	0.377 (0.279)	0.206 * (0.115)	0.915 *** (0.300)
gender	0.088 (0.085)	−0.470 (0.330)	0.028 (0.086)	−0.261 (0.274)	0.085 (0.085)	−0.455 (0.345)
Agricultural labor	0.329 *** (0.058)	0.684 *** (0.203)	0.386 *** (0.055)	0.669 *** (0.204)	0.339 *** (0.059)	0.670 *** (0.246)
Education	0.103 (0.012)	0.106 (0.019)	0.107 (0.012)	0.125 (0.019)	0.203 (0.012)	0.217 (0.019)
Planting area	0.018 *** (0.005)	0.005 (0.020)	0.016 *** (0.005)	0.021 (0.024)	0.018 *** (0.005)	0.008 (0.026)
Market expectations	1.099 *** (0.096)	−0.087 (0.286)	1.086 *** (0.100)	0.369 (0.356)	1.082 *** (0.098)	−0.010 (0.315)
Sales	0.064 * (0.036)	0.339 *** (0.085)	0.120 *** (0.034)	0.209 ** (0.083)	0.072 * (0.038)	0.387 *** (0.091)
area	0.144 ** (0.056)	0.835 *** (0.152)	0.203 *** (0.056)	0.899 *** (0.153)	0.148 *** (0.058)	0.897 *** (0.168)
Technical training		1.158 *** (0.205)		1.014 *** (0.227)		1.190 *** (0.215)
Constant term	0.186 (0.376)	−3.075 *** (1.050)	−0.353 (0.359)	−3.013 *** (1.026)	0.117 (0.387)	−3.214 *** (1.115)
Pseudo R2	0.5944		0.6093		0.6150

Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively, the same below.

show that government subsidies have a significant positive impact on farmers’ decision-making and adoption levels of green pest control technologies. Specifically, farmers who receive government subsidies are more likely to adopt these technologies and exhibit higher adoption levels compared to those who do not. This supports the validation of Hypothesis H1. The possible reason is that China’s agricultural production and management are mainly carried out by small-scale farmers, whose ability to bear production costs is limited. Government subsidies for farmers adopting green pest control technologies can effectively reduce the cost burden of technology adoption, enhance farmers’ confidence, and stimulate their enthusiasm for adopting the technology.

The regression results of Model 2 show that quality certification has a significant positive impact on both farmers’ green pest control technologies adoption decisions and adoption levels. This suggests that farmers who have undergone quality certification are more likely to adopt these technologies and exhibit higher adoption levels compared to those who have not. Hypothesis H2 is thus supported. The reason may be that quality certification serves as an important signal of product quality and safety, helping consumers identify high-quality, green agricultural products, which can generate a premium effect. Motivated by higher prices, farmers are more inclined to adopt green pest control technologies to produce certified products. Additionally, when farmers undergo quality certification, they broaden their channels for obtaining information, enhance their understanding of green pest control technologies knowledge, and their mastery of skills, thus helping them adopt green pest control technologies.

To further investigate the impact mechanism of government subsidies and quality certification on farmers’ adoption of green pest control technologies, this paper introduces an interaction term between government subsidies and quality certification into the model. Model 3 shows that both government subsidies and quality certification can promote farmers’ adoption of green pest control technologies. The interaction term between government subsidies and quality certification has a positive and significant effect on farmers’ decision-making and adoption levels at the 1% statistical level. This indicates a mutually reinforcing effect between the two factors in farmers’ adoption behavior, thus verifying hypothesis H3. This conclusion can be explained in two ways: first, under the same subsidy conditions, higher quality certification levels facilitate the adoption of green pest control technologies; second, under the same certification level, government subsidies help farmers adopt these technologies.

4.2. Heterogeneity Analysis: Different Human Capital Quantity Perspectives

From the perspective of human capital quantity, this paper selects the number of agricultural laborers as a measurement indicator, and according to the survey situation, it is divided into a high human capital quantity group and a low human capital quantity group according to the standard of agricultural labor quantity lower than and higher than the average value force (the average value is 3.856) to explore whether the difference in human capital endowment has an impact on the adoption behavior of farmers’ green pest control technologies. From the empirical results in

Table 4. Regression results of the low human capital group.

Variable	Model 4		Model 5		Model 6
	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level
Government subsidies	0.191 (0.174)	0.490 (0.488)			0.238 (0.100)	0.571 (0.281)
Quality certification			0.102 (0.072)	0.308 (0.087)	0.105 (0.045)	0.341 (0.152)
Government subsidy × quality certification					0.055 (0.064)	0.591 (0.564)
Control variables	control	control	control	control	control	control
Technical training		1.467 *** (0.520)		1.694 *** (1.581)		1.059 *** (0.213)
Constant term	−0.561 (0.910)	−6.728 *** (3.133)	−1.570 ** (0.864)	−0.184 (0.908)	−0.346 (0.357)	−2.648 *** (1.020)
Sample size	1 15		1 15		1 15
Pseudo R2	0.5218		0.4982		0.5187

Note: ** and *** indicate significance at the 5% and 1% levels, respectively.

and

Table 5. Regression results of the high human capital group.

Variable	Model 7		Model 8		Model 9
	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level
Government subsidies	0.310 *** (0.085)	0.575 *** (0.218)			0.386 *** (0.099)	0.340 * (0.241)
Quality certification			0.195 ** (0.037)	0.476 *** (0.181)	0.179 *** (0.049)	0.348 * (0.203)
Government subsidy × quality certification					0.142 ** (0.071)	0.217 *** (0.053)
Control variables	control	control	control	control	control	control
Technical training		1.227 *** (0.214)		1.243 *** (0.241)		1.190 *** (0.256)
Constant term	0.216 (0.427)	−3.658 *** (1.240)	0.145 (0.433)	−3.730 ***	0.293 (0.438)	−3.542 ** (1.582)
Sample size	304		304		304
Pseudo R2	0.4241		0.4270		0.4371

Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

, for the low-quantity group, government subsidies and quality certification do not significantly impact farmers’ adoption decisions or the extent of adoption of green pest control technologies. One possible explanation is that green pest control technologies require substantial labor and material resources for field management, which imposes certain labor force requirements. For the high-quantity group, government subsidies and quality certification significantly influence farmers’ decision-making and adoption levels of green pest control technologies. The possible reason is that with a larger agricultural labor force, more refined and standardized planting operations can be carried out through labor division. Additionally, the combined effect of government subsidies and quality certification further encourages farmers to adopt green pest control technologies.

4.3. Heterogeneity Analysis: The Perspective of Intergenerational Differences

This article selects the age of the household head to divide the generational differences, taking 1980 as the dividing line, dividing those born after 1980 into the new generation, and those born in 1980 and before into the older generation, to explore whether generational differences have an impact on farmers’ green pest control technologies. Judging from the empirical results in

Table 6. New generation regression results.

Variable	Model 13		Model 14		Model 15
	Adopt Decision	Adoption Level	Adopt Decision	Adoption Level	Adoption Decision	Adoption Level
Government subsidies	0.178 *** (0.110)	0.123 *** (0.665)			0.182 (0.131)	0.893 (0.114)
Quality certification			0.028 (0.043)	0.952 (0.176)	0.033 (0.051)	0.106 (0.201)
Government subsidy × quality certification					0.016 (0.091)	0.331 (0.517)
Control variables	control	control	control	control	control	control
Technical training		8.853 (0.650)		1.080 (1.448)		1.392 (3.392)
Constant term	3.890 (0.762)	2.301 (3.955)	3.736 (0.758)	5.970 (4.350)	3.938 (0.771)	8.428 ** (0.649)
Sample size	212		212		212
Pseudo R2	0.4700		0.4718		0.4910

Note: ** and *** indicate significance at the 5% and 1% levels, respectively.

, for the new generation, government subsidies significantly influence the adoption of green pest control technologies, indicating that subsidies can serve as incentives. Quality certification has no significant impact on their adoption of green pest control technologies. The possible reason is that the new generation is more likely to engage in part-time jobs, and their production focus is not on agriculture. The interaction between quality certification and government subsidies has no significant impact on the technology adoption behavior of the new generation, indicating that when the new generation is not optimistic about quality certification, government subsidies cannot effectively supplement the shortcomings of quality certification and thus cannot encourage the new generation to adopt green pest control technologies.

Judging from the empirical results in

Table 7. Older generation regression results.

Variable	Model 10		Model 11		Model 12
	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level	Adoption Decision	Adoption Level
Government subsidies	0.328 *** (0.105)	0.371 *** (0.306)			0.365 *** (0.115)	0.370 *** (0.375)
Quality certification			0.149 *** (0.045)	0.282 *** (0.178)	0.189 ** (0.070)	0.331 * (0.222)
Government subsidy × quality certification					0.100 * (0.084)	0.208 *** (0.077)
Control variables	control	control	control	control	control	control
Technical training		0.971 *** (0.289)		0.995 *** (0.284)		1.142 *** (0.331)
Constant term	0.137 (0.585)	−5.952 *** (2.076)	−0.235 (0.602)	−5.823 *** (2.092)	−0.237 (0.581)	−7.439 ** (2.385)
Sample size	207		207		207
Pseudo R2	0.4689		0.4676		0.4859

Note: *, **, and *** indicate significance at the 10%, 5%, and 1% levels, respectively.

, government subsidies have a significant impact on the adoption of green pest control technologies by the older farmers, indicating that subsidies have increased the adoption enthusiasm of older farmers. Quality certification has a significant impact on their green pest control technologies. The possible reason is that the older generation of farmers is at a disadvantage in non-agricultural employment. Quality certification is conducive to the increase of agricultural income, and they tend to adopt green pest control technologies in order to pass the quality certification. The interaction between quality certification and government subsidies has a significant positive impact on the green pest control technologies adoption behavior of the older generation of farmers. The interaction between quality certification and government subsidies significantly promotes the adoption of green pest control technologies by the older generation of farmers. This highlights the importance of considering the individual effects of these factors, but also their combined influence on the adoption of green pest control technologies by the older generation of farmers.

4.4. Discussion

At this stage, the gap between supply and demand of green agricultural products in China is gradually widening [51,52,53]. Increasing the proportion of farmers adopting green pest control technologies is of great significance to increasing the supply of green agricultural products. In the process of promoting the green transformation of agriculture, the government and the market can play a fundamental role. Therefore, this article uses field survey data from Shandong Province and Henan Province to expand the collaborative perspective of the government and the market to the adoption of green pest control technologies by farmers, and the Heckman two-stage model was used to analyze the impact of the two and their interaction, which is more comprehensive than the previous analysis of government subsidies or quality certification alone [54,55], and provides strong support for building and optimizing green pest control technologies promotion strategies.

This study found that government subsidies and quality certification can significantly promote the adoption of green pest control technologies by farmers, which is consistent with the conclusions of previous studies [56,57]. However, unlike previous studies [58,59], this paper incorporates government subsidies and quality certification into the same analytical framework and compares and analyzes the impact of the two. The results show that quality certification has a greater impact than government subsidies. The reason is that government subsidies mainly reduce farmers’ production costs through “comprehensive direct subsidies”. Therefore, for green pest control technologies that require large initial investments, government subsidies can effectively increase farmers’ willingness to adopt them. Quality certification mainly improves the recognition and market price of agricultural products through “high quality and high price”, thereby encouraging farmers to adopt green pest control technologies. In the early stages of promoting green pest control technologies, government subsidies are often more critical because they can directly reduce the economic pressure on farmers and promote the rapid promotion of technologies. In the middle and late stages of technology promotion, quality certification becomes even more important because it can help farmers stand out in the fierce market competition and achieve differentiation of agricultural products. Shandong and Henan provinces serve as demonstration areas for the promotion of green pest control technology in China. Green control technology has passed the initial stage and entered the stage of comprehensive development. Therefore, quality certification can play a greater role than government subsidies.

In addition, this paper also carried out heterogeneity analysis from the perspectives of human capital and generational differences, expanding the research of Gautam et al. (2017) [60] and Yu et al. (2024) [61]. The study found that, in the high human capital group, government subsidies and quality certification have a positive impact, whereas in the low human capital group, these variables no longer show a significant effect. Huang et al. (2024) [62] also argued that adopting green control technology requires greater labor input. This study also found that quality certification promotes the adoption of green pest control technologies only among the older generation of farmers, not the younger generation. These findings contrast with those of previous studies [63]. A possible reason is that the older generation of farmers still possesses strong physical strength and expects to work many more years in agriculture, making them more focused on the long-term benefits of farming. The younger generation of farmers typically holds concurrent jobs. With the shift of production focus, they are more inclined to pursue short-term benefits and reduce investment in agricultural production.

5. Conclusions and Policy Implications

5.1. Conclusions

The main conclusions drawn are as follows:

(1)

Government subsidies, quality certification, and the interaction between the two can promote farmers to adopt green pest control technologies. That is, when the government subsidies are the same, the higher the quality certification level, the more likely farmers are to adopt green pest control technologies. In other words, when the quality certification levels are the same, when farmers receive government subsidies, they are more likely to adopt green pest control technologies.

(2)

From the perspective of human capital quantity, in the high human capital quantity group, government subsidies and quality certification can promote farmers to adopt green pest control technologies, while in the low human capital quantity group, these two variables no longer play a significant role. Promotional effect, which may be related to the labor-intensive nature of green pest control technologies.

(3)

From the perspective of intergenerational differences, government subsidies have a significant role in promoting the adoption of green pest control technologies by both the older generation and the new generation of farmers. Quality certification only has a significant role in promoting the adoption of green pest control technologies by the older generation of farmers but no longer has a significant impact on the new generation of farmers. This may be related to the part-time operation of the new generation of farmers.

5.2. Policy Implications

Based on the above conclusions, the following policy recommendations are put forward: First, establish a stable and multi-channel government subsidy system to ensure the continuous issuance of government subsidies and meet the diversified needs of agricultural production and operation. Second, improve the construction of the agricultural product quality traceability system, alleviate information asymmetry, highlight the quality differences of agricultural products, and convey the market value of agricultural products. Third, take a two-pronged approach and complement each other’s advantages, fully combine government subsidies with quality certification, reduce the cost of agricultural production technology conversion through government subsidies, and increase the economic benefits of agricultural production and operation through quality certification. Finally, build a targeted incentive mechanism based on different groups of farmers. The country should fully consider the production and operation characteristics of the low labor force and the new generation group and formulate a targeted incentive mechanism to achieve the purpose of promoting green pest control technologies.

5.3. Limitations and Areas for Further Research

This study examined the impact of government subsidies and quality certification on farmers’ adoption of green pest control technologies, but it has two limitations. First, the analysis of government subsidies and quality certification focuses only on their effects, without exploring the underlying mechanisms. Second, while this study confirms the synergistic effect of government and market forces on the adoption of green pest control technologies, it does not investigate how the relative strength of these effects evolves over different stages of development. Therefore, future research could focus on the following areas: investigating the mechanisms behind the impact of government subsidies and quality certification on farmers’ adoption of green pest control technologies; conducting long-term follow-up surveys to create panel data; and examining the changing roles of government and market forces at different developmental stages. Additionally, future studies could explore the economic, social, and environmental impacts of green pest control technologies, providing a more comprehensive assessment of their overall value.