The Real Impact of Digital Agricultural Technology Extension on Pesticide Reduction Behavior Among Wheat Farmers in Henan, China

Abstract

In the context of sustainable development, the behavior of reducing pesticide use in the agricultural sector is crucial for environmental protection and ecological balance. However, there are two divergent views on whether digital agricultural technology extension can promote farmers’ behavior in reducing pesticide use: one is supportive, and the other is doubtful. Based on interviews with 20 typical wheat growers in Henan, this paper re-examines this issue. The results show that the extension of digital agricultural technology has no significant impact on the pesticide reduction behavior of wheat growers. This paper further employs fuzzy-set qualitative comparative analysis (fsQCA) to explore the mechanisms influencing pesticide reduction behavior among wheat growers. The findings indicate that digital agricultural technology extension can only enhance growers’ ecological value cognition, but the ecological value cognition of pesticide reduction does not significantly promote the pesticide reduction behavior of wheat growers. Instead, rational economic value cognition plays a dominant role in promoting this behavior, with resource endowment serving as a supplementary factor. Therefore, this paper suggests integrating the characteristics of farmers’ resource endowment, fully leveraging the productive functions of digital agricultural technology extension, and focusing on enhancing farmers’ rational economic value cognition of pesticide reduction to further promote the application of pesticide reduction among farmers and provide strong support for sustainable agricultural development.

1. Introduction

The reduction in pesticide use is one of the key measures to achieve sustainable agricultural development. In recent years, with the increasing global emphasis on environmental protection and ecological balance, the importance of reducing pesticide use has become more and more prominent. From the perspective of economic development, the reduction in pesticide use directly enhances the quality and safety of agricultural products, which is conducive to improving human health levels. It also helps to reduce the cost of agricultural production and increase farmers’ income [1]. From an ecological point of view, the reduction in pesticide use can reduce pollution to soil, water, and air, protect biodiversity, and effectively achieve sustainable agricultural development, contributing to the realization of global sustainable development goals [2]. Relevant data show that China’s agricultural production still faces the problem of excessive pesticide application. In 2018, China was the world’s largest consumer of chemical pesticides [3]. In 2019, China’s per capita pesticide consumption was 3.83 times the global average, and its per unit area chemical pesticide usage was 2.5 to 5 times higher than that of developed countries [4]. In 2021, the pesticide utilization rate for China’s three major grain crops was only 40.6%, significantly lower than the over 60% rate seen in developed countries. In modern agricultural production, wheat, as one of the world’s major food crops, plays a crucial role in safeguarding food security. Its production efficiency and quality are of paramount importance. Studies have shown that the application of precision pesticide application and biological control techniques, such as intelligent pesticide application technologies and biopesticides, can significantly reduce the amount and frequency of pesticide use. The pesticide residue levels can be lowered by 30–70%, and the cost of pesticides can be reduced by 30–50%. While contributing to the protection of the environment and the development of sustainable agriculture, the reduction in pesticide use also enhances the production efficiency and quality of wheat [5]. For instance, in the wheat production of Sishui County, the application of green prevention and control technologies can reduce the amount of chemical pesticide use by about 15% per year, with an average cost-saving and efficiency improvement of 80 yuan per mu. Based on the reality of excessive pesticide use and the greater benefits of pesticide reduction, promoting pesticide reduction among farmers has become a focal issue. The existing literature suggests that the lack of effective information and scientific guidance is one of the fundamental reasons for farmers’ excessive pesticide use [6].

Digital agricultural technology extension, as the most extensive channel for mass information dissemination at present, has two different views on its role in promoting farmers’ pesticide reduction behavior: supportive and skeptical. The mainstream view holds that digital agricultural technology extension can effectively promote farmers’ pesticide reduction behavior by disseminating relevant information on pesticide reduction in a trans-temporal and spatial, highly timely manner. First, the extension of digital agricultural technology promotes the selection of green pesticide alternatives by reducing farmers’ search costs, acquisition costs, and negotiation costs for information [7]. Secondly, the internet promotes agricultural production information, thereby transforming farmers’ subjective willingness and enhancing their objective skills, which in turn encourages them to reduce pesticide use [8]. Thirdly, digital agricultural technology extension helps improve environmental literacy and awareness, thereby promoting farmers’ pesticide reduction behavior [9]. In contrast to the mainstream view, the skeptical view argues that the extension of digital agricultural technology does not promote farmers’ pesticide reduction behavior in China’s agricultural production. For example, some scholars found that rural residents’ information literacy is generally low, and farmers use modern communication technologies more for leisure and entertainment than for learning or searching for agricultural information, resulting in the ineffective dissemination of pesticide reduction information [10]. Farmers’ overall level of complex operations, such as searching for, filtering, creating, and sharing content, is relatively low. Their ability to obtain, process, and share information through the internet is also weak, and their use of digital tools remains at a rather basic level [11]. Moreover, farmers’ relatively low level of education, combined with the fact that the internet is a skill-biased technology, means that workers with lower education and skills are less able to receive and utilize pesticide reduction information effectively, which affects the probability of pesticide reduction behavior occurring [12]. In addition, Mao Hui et al. further demonstrated that the generally low digital literacy of farmers means that digital agricultural technology extension has not significantly promoted the reduction in chemical agricultural inputs [13]. As farmers learn from advanced practices and gain access to cutting-edge agricultural information, their digital literacy improves. This, in turn, inclines them more towards cultivating cash crops [11]. However, cash crops are often associated with a high input of chemical pesticides, which further increases the application of chemical pesticide inputs. In addition to the above controversial external factors of digital agricultural technology extension, farmers’ micro-characteristics are also important factors influencing farmers’ pesticide reduction behavior. Specifically, it includes two aspects: on the one hand, the impact of individual characteristics of growers on pesticide reduction, such as the age of growers [14], risk perception [4], value perception [15], the quantity of labor force, and the area of farmland. On the other hand, there are external factors such as the market [16].

Based on the above analysis, farmers’ pesticide application behavior is the result of the combined effects of multiple factors. Existing studies have largely focused on analyzing the outcomes of farmers’ pesticide reduction behavior through a single influencing factor, a single pathway of influence, and a single research method. There is a lack of in-depth exploration of the factors and mechanisms at play. The behavior of farmers is a complex outcome woven from multiple factors, and relying solely on quantitative analysis makes it difficult to capture the rich context and deeper meaning behind the data. Does the extension of digital agricultural technology have a promoting effect on farmers’ pesticide reduction behavior? Further analysis is needed. At present, most studies characterize digital agricultural technology extension as “the use of smartphones” and “the use of the internet”, without delving into the productive functions that digital agricultural technology extension plays in pesticide reduction. In addition, the existing research mostly focuses on cash crops such as cotton, vegetables, and fruits, while studies on the current status of pesticide application in staple crops with larger planting areas are relatively scarce. In light of this, this paper selects typical farmer surveys in traditional wheat-growing areas. This study employs two research methods: case interviews and fuzzy-set qualitative comparative analysis. By conducting an in-depth analysis of actual cases to reveal the essence behind complex phenomena and then using quantitative analysis to verify the results of the qualitative analysis, this study aims to gain a more comprehensive and in-depth understanding of the intrinsic logic and driving factors of farmers’ behavior, in the hope of discovering the existing difficulties of digital agricultural technology extension on farmers’ pesticide reduction behavior and solving practical problems.

2. Conceptual Definition and Theoretical Analysis

2.1. Conceptual Definition

The FAO emphasizes that digital agricultural technology extension is based on both digital agriculture and agricultural technology extension [17]. Digital agriculture refers to the use of advanced network transmission equipment to digitally and intelligently transform various aspects of agricultural production management and services, aiming to improve the effectiveness of agricultural technology extension and achieve high-quality, sustainable agricultural development [18]. Osman T et al. suggest that agricultural technology extension services include not only physical agricultural technologies implemented through the purchase of machinery, fertilizers, pesticides, and other material resources, but also non-physical agricultural technologies supported by information technology, big data, artificial intelligence, and other software and services [19]. Gao et al. propose a new model for agricultural technology extension through digital agriculture, utilizing new media such as WeChat official accounts and applications [20]. Based on detailed research by scholars both domestically and internationally on digital agricultural technology extension, from the perspective of farmers, it can be concluded that if farmers use modern information and communication devices to obtain information related to pesticide applications, they are using digital agricultural technology extension services aimed at pesticide reduction.

The definition of pesticide reduction value perception is derived from the deeper meaning of perceived value. Perceived value refers to the overall benefit assessment formed by customers after comprehensively evaluating and judging a product or service [21]. According to farmer behavior theory, cognition is the foundation of willingness and behavior formation; the higher the level of cognition, the more likely the corresponding behavior will occur. Based on the concept of perceived value and related research, pesticide reduction value perception is measured and assessed from ecological and economic dimensions, namely the economic value perception and ecological value perception of pesticide reduction. Specifically, there is a clear difference between the expected ecological benefits and the economic benefits of pesticide reduction, leading to different pesticide use behaviors among farmers with different endowments in the same region [22]. Since pesticide reduction directly affects crops and has a direct impact on crop yields, farmers are absolute risk-takers in terms of the value perception of pesticide reduction. Specifically, the more rational farmers’ ecological value perception of pesticide reduction, the more likely they are to form a willingness to reduce pesticide use to ensure the safety of their living environment; similarly, the more significant the perceived economic value of pesticide reduction, the more likely farmers are to engage in pesticide reduction behavior.

2.2. Theoretical Analysis

Behavioral economics indicates that farmers’ decision-making behaviors are influenced by multiple factors such as the endowment effect, anchoring bias, and aversion to uncertainty about future states, leading to a diversity of behaviors in pesticide reduction among farmers. Neoclassical economics assumes that decision-makers are rational economic agents who pursue the maximization of personal utility. That is to say, farmers will weigh the potential economic benefits of pesticide reduction for themselves and seek to maximize their interests on the premise of ensuring controllable risks. Only when farmers believe that the expected benefits of pesticide reduction significantly outweigh the potential risks faced will they form the intention to reduce pesticide use and engage in behaviors that reduce pesticide application.

Hypothesis 1.

Rational economic value cognition of pesticide reduction promotes farmers’ pesticide-reduction behavior.

The sustainable development theory can be summarized as a framework based on economic sustainability, conditional on ecological sustainability, and aimed at achieving social sustainability. This framework emphasizes the coordinated development of economic, environmental, and social dimensions for long-term stability and prosperity. Within this theory, the principle of sustainability is crucial. It highlights that sustainable resource use and system sustainability are key to safeguarding human society. Farmers must adjust their farming practices according to sustainable requirements. When they fully recognize the positive impacts of reducing pesticide use on food safety, environmental protection, and product quality, they are more likely to reduce pesticide application.

Hypothesis 2.

Rational ecological value cognition of pesticide reduction promotes farmers’ pesticide reduction behavior.

The Environmental Kuznets Curve (EKC) reveals an inverted U-shaped relationship between environmental quality and per capita income. In the early stages of economic development, environmental pollution intensifies with economic growth. However, once the economy reaches a certain level of development, environmental quality improves with increasing income. This theoretical framework can be employed to elucidate the dynamic shifts in farmers’ economic and ecological value perceptions regarding pesticide reduction behaviors [23]. In the initial phase of economic development, farmers, constrained by their income levels, tend to focus more on the immediate economic benefits brought about by pesticide application. For instance, to prevent crop yield losses due to pests and diseases, they may excessively use pesticides. Nevertheless, as their income levels rise, farmers’ economic value perceptions of pesticide reduction gradually become more rational. They start to recognize that reducing pesticide use can lower costs, making them more inclined to adopt relevant technologies. Concurrently, the more rational a farmer’s ecological value perception is, the more likely they are to engage in pesticide reduction practices. However, in China, which is in the primary stage of socialism and characterized by a typical smallholder farming model, farmers’ value perceptions of pesticide reduction are predominantly dominated by economic considerations, with a greater focus on the immediate economic benefits derived from reduction.

Hypothesis 3.

Farmers’ economic value perception of pesticide reduction dominates their pesticide reduction application behavior.

In agricultural practice, the moral economy of farming emphasizes that cultivation techniques have been refined over centuries of trial and error, ultimately ensuring the most stable and reliable yields in specific environmental conditions [24]. The excessive use of pesticides is a long-standing strategy employed by farmers to avoid crop failure, driven by the need for survival. Farmers’ aversion to the risks associated with pesticide reduction is compounded by their anchoring bias, and the generally low levels of education among farmers further influence their decision-making [25]. Moreover, short-term initiatives such as digital agricultural technology extension, which rely on information dissemination, are insufficient to alter the deeply ingrained beliefs and risk-averse attitudes that farmers have developed over time. Based on this analysis, this study concludes that the extension of digital agricultural technology does not significantly encourage farmers to reduce pesticide use.

Hypothesis 4.

Digital agricultural technology extension does not significantly promote farmers’ pesticide reduction behavior in the short term.

3. Overview of the Study Area and Interview Survey

3.1. Research Area Overview

Henan Province is a major wheat-producing region in China, with its total wheat output accounting for over 28% of the national total [26]. Qi County, a key grain-producing county in Henan, is home to Zhao Zhai Village, whose scale of wheat cultivation and production model is highly representative. Located in Pingcheng Township, Henan Province, on the Huang-Huai-Hai Plain, a traditional wheat-growing area in China, Zhao Zhai Village’s economy, dominated by wheat and corn cultivation, is typical of the agricultural characteristics of the main grain-producing areas in northern China. Pingcheng Township, where Zhao Zhai Village is situated, boasts a well-developed agricultural and modern infrastructure, including a comprehensive irrigation system, the application of modern agricultural machinery, and internet infrastructure that has reached ordinary households. According to the “Overview of the Basic Situation of Modern Agricultural Development in Henan Province” (2018), the popularization rate of agricultural science and technology in the area has reached over 95%, and the application rate of agricultural scientific and technological achievements has exceeded 90%. This endows Zhao Zhai Village with a relatively high level of agricultural modernization, providing a solid basis for studying the effectiveness of agricultural technology extension. Meanwhile, recognized as a “Model Village for Democracy and Rule of Law” in Henan Province, Zhao Zhai Village enjoys significant advantages in rural governance. This governance model facilitates the dissemination and application of agricultural technology and can better reflect changes in farmers’ behavior under the influence of certain technologies. The sound governance environment offers a stable backdrop for studying farmers’ behavior, ensuring the reliability of research findings. In addition, farmers in Zhao Zhai Village have a high degree of participation, and the local government and research institutions have detailed records of the village’s agricultural production and farmers’ behavior. This provides abundant data for better analyzing the actual impact of digital agricultural technology extension on farmers’ behavior [27].

Zhao Zhai Village’s scale of cultivation is diversified, with both small-scale self-cultivating farmers and large-scale operators who have achieved economies of scale through land transfer. This diversified structure of cultivation scale reflects the development trend of China’s rural areas in the process of agricultural modernization, that is, the coexistence of small farmers and large-scale operators. The economic income level of farmers in Zhao Zhai Village covers a wide range, including subsistence farmers who highly depend on agricultural income, part-time farmers with low dependence on agricultural income, farmers who regard agricultural land as a fallback option, and large-scale farmers with high dependence on agricultural income. The diversified income structure of farmers in Zhao Zhai Village reflects the actual situation of China’s rural areas in the economic transformation period and provides rich cases for the study of farmers’ behavior.

In summary, Zhao Zhai Village has significant advantages in terms of geographical location, characteristics of agricultural cultivation, rural governance model, farmers’ income level, and data availability, making it an ideal subject for studying the impact of digital agricultural technology extension on farmers’ behavior.

3.2. Question Design

The design of the survey questionnaire follows the principles of clear objectives, logical structure, and appropriate item selection. First, based on a review of the relevant literature and expert consultations, a questionnaire was designed to investigate farmers’ pesticide reduction practices. The questionnaire consists of four main sections: firstly, basic information about the farmers is collected. This section collects data on gender, age, education level, years of wheat cultivation, and the area of wheat cultivation. Secondly, the degree of digital agricultural technology extension (DATE). This section assesses the extent to which digital agricultural technologies are promoted in farming, through questions such as, “Do you use the internet to browse information related to pesticide reduction?” and “Do you access pesticide application techniques through third-party apps such as WeChat or Douyin?”. Thirdly, the farmers’ value perception of pesticide reduction, that is, “Are you aware of the impact of pesticide reduction on food safety, ecological environment, agricultural product quality, as well as yield and income?”. Fourth, farmers’ pesticide reduction (PR) practices: this section explores farmers’ actual pesticide reduction behaviors, primarily through questions such as, “Compared to the recommended pesticide usage by agricultural input dealers, do you tend to increase, maintain, or reduce the amount of pesticide you apply?”. Finally, based on the pilot survey and expert opinions, the questionnaire was revised and improved to enhance its scientificity, rationality, and effectiveness.

3.3. Interview Survey

The case data used in this study were sourced from farmer interviews conducted in January 2024, and the survey process consisted of three stages. Stage 1: Pre-survey. In this phase, a pre-survey was conducted in the selected study areas based on the questionnaire content. Preliminary interviews were carried out with small-scale farmers to identify potential issues in the questionnaire design. The feedback from the farmers helped to pinpoint areas where the questionnaire could be improved. Stage 2: Questionnaire revision. Following the pre-survey, the questionnaire was revised. Specialized terms were simplified into more accessible language, and both the structure and content of the questionnaire were adjusted and streamlined to enhance clarity and focus. Stage 3: Formal Survey. In the final stage, formal surveys were conducted with a selected group of typical wheat farmers. A one-on-one semi-structured interview method [28] was employed to explore the farmers’ attitudes toward pesticide reduction and their willingness to adopt such practices. A total of 21 farmer questionnaires were collected, of which 20 were valid, resulting in a response rate of 95.24%.

4. Digital Agricultural Technology Extension Failed to Encourage Pesticide Reduction

4.1. The Extension of Digital Agricultural Technology Has a Limited Effect on the Reduction in Pesticide Usage

The central region of Henan Province has a high internet coverage rate, but the promotion of digital agricultural technology is relatively low, and its role in promoting the reduction in pesticide use by farmers is limited. In the sample, the internet coverage rate is 95%, indicating that the construction of internet infrastructure is relatively complete, which provides a good basic condition for the dissemination of agricultural technology. However, the promotion degree of digital agricultural technology is only 60%, and the probability of digital agricultural technology promotion affecting the occurrence of farmers’ pesticide reduction behavior is 50%, the specific data are shown in

Table 1. Demographics of the household.

Type	Frequency of Pesticide Reduction	%	Frequency of No Pesticide Reduction	%
Digital agricultural technology extension	6	50	6	50
No digital agricultural technology extension	3	37.5	5	62.5

Data Source: Created by the author.

., which is equivalent to the probability of pesticide reduction behavior occurring among farmers who have not received digital agricultural technology promotion. This shows that digital agricultural technology promotion has not yet fully exerted its due role in practical application. The author, through interviews with wheat growers, has explored in depth the connection between the promotion of digital agricultural technology and the reduction in pesticide use. Among them, the views of wheat grower G are highly representative. The grower mentioned the following: “I once browsed a pest control technology using a special formula online and followed the tutorial to operate it twice. However, after observing for some time, there was no significant control effect, and the number of pests did not decrease. So, I quickly sprayed chemical pesticides. Since I missed the best control time, compared with the amount of chemical pesticides used from the beginning, more pesticides were used later”. This case reflects many problems in the practical application of digital agricultural technology promotion, such as inaccurate technical guidance, which leads to a decrease in farmers’ trust in new technologies and thus affects the implementation of their pesticide reduction behavior. It can be seen that although the internet provides a convenient channel for the dissemination of agricultural technology, the effectiveness of digital agricultural technology promotion still faces many challenges. To truly achieve the goal of reducing pesticide use, it is not only necessary to increase the internet coverage rate but also to improve the quality and accuracy of digital agricultural technology promotion and strengthen the promotion model that combines offline and online methods to enhance the coverage of new technologies.

During the interview process, we closely observed the attitudes and behaviors of farmers towards information in the process of digital agricultural technology extension, which is mainly reflected in the following aspects: First, farmers are skeptical about alternative technologies for pesticide reduction. Many farmers are skeptical about the effectiveness of alternative technologies for pesticide reduction disseminated through the internet and other online means. They generally believe that these alternative technologies may not be as effective as traditional chemical pesticides in controlling pests and diseases. This perception partly stems from a lack of in-depth understanding of new technologies and is also constrained by past experiences, leading farmers to prefer traditional chemical pesticides and to be cautious or even resistant to agricultural technologies spread through digital means; second, the digital literacy of farmers is generally low. This directly affects their ability to receive and apply information from digital agricultural technology extension. Research findings show that farmers mostly use the internet for entertainment and communication, with only a small number of farmers actively seeking information on digital agricultural technology extension. Studies by Luo Mingzhong and Liu Ziyu have shown that the longer the time spent on leisure and entertainment on the internet, the lower the acceptance of new technologies [12], which in turn reduces the likelihood of pesticide reduction behavior occurring. This phenomenon reflects that digital agricultural technology extension still faces significant challenges in stimulating farmers’ proactiveness and enthusiasm; third, farmers’ entrenched beliefs hinder the adoption of new technologies and the emergence of new behaviors. Many farmers firmly believe that reducing pesticide use will inevitably lead to a decrease in yield. This deep-seated belief often prevents them from trying new technologies due to concerns about potential yield losses. This cognitive bias largely restricts the extension of new technologies and the probability of pesticide reduction behavior occurring. Overall, farmers’ reactions and behaviors in the context of digital agricultural technology extension are mainly characterized by conservative and passive acceptance. They are skeptical about the extension of digital agricultural technology and lack the enthusiasm to actively participate and practice, which validates Hypothesis 4.

4.2. The Mechanism of the Extension of Digital Agricultural Technology and Farmers’ Awareness in Reducing Pesticide Usage

The sample data indicate that farmers who receive digital agricultural technology extension services are more likely to form a rational ecological value cognition of pesticide reduction. According to the theory of farmers’ cognition, behavior is formed after a comprehensive weighing of various factors and is constrained by individual cognitive levels. Therefore, this study set two key questions in the survey questionnaire: “Are you aware of the impact of pesticide reduction on the ecological environment?” and “Are you aware of the impact of pesticide reduction on yield and income?” to assess whether farmers have rational value cognition. The results show that among farmers who receive digital agricultural technology extension services, 66.67% of farmers show a rational cognition of the ecological value of pesticide reduction, and 58.33% of farmers show a rational cognition of the economic value of pesticide reduction; in contrast, among farmers who do not receive digital agricultural technology extension services, the proportion of farmers with rational ecological value cognition and rational economic value cognition is both 62.5%, The specific data on the impact of digital agricultural technology extension on farmers’ value cognition of pesticide reduction are shown in Figure 1. Farmer J said: “I will occasionally browse relevant pesticide reduction application consultation videos, so I will understand some information that pesticide reduction is beneficial to food safety and the ecological environment, but I think that pesticide reduction will reduce agricultural yield and income. Because the toxicity of chemical pesticides, will harm human health and the environment. But it is this toxicity that can produce a control effect. If it is reduced compared with the amount recommended by agricultural material dealers, it will lead to a decrease in yield and income. Therefore, the amount of pesticides applied to my wheat is slightly increased, and the yield will be higher than that of other farmers”. In addition, farmers with the characteristics of digital agricultural technology extension show a more rational cognition of the ecological value of pesticide reduction. In conclusion, this study believes that digital agricultural technology extension helps farmers form a rational ecological value cognition, but has no significant effect on the formation of rational economic value cognition.

This study finds that among farmers with rational ecological and economic value cognitions, 53.85% and 75%, the data distribution between pesticide reduction behavior and farmers’ value cognition of pesticide reduction is shown in Figure 2, respectively, have engaged in pesticide reduction behavior. During the interview process, it was a common belief among farmers that “pesticide reduction will improve the environment”, a view frequently mentioned when they discussed the value of pesticide reduction. However, despite a clear understanding of the ecological value of pesticide reduction, the interview results indicate that many farmers still engage in the overuse of pesticides. In contrast, when farmers have a rational economic value cognition of pesticide reduction, the probability of their implementing pesticide reduction behavior significantly increases. Farmer T’s statement reflects this contradictory mindset: “We all know that pesticide reduction is environmentally friendly, but even so, we will not reduce the amount of pesticide sprayed. The environmental quality now is far worse than before, especially regarding pesticide application. Although pesticide reduction can improve air and water quality, the overuse of pesticides is now widespread, and I alone cannot achieve any substantial environmental improvement”. Further interviews revealed that those who implemented pesticide reduction behavior mostly demonstrated a rational economic value cognition of pesticide reduction. Farmer E said: “After learning that a moderate reduction in pesticides will not affect yield and income, I will judge the actual amount of pesticide needed based on my years of planting experience, which is usually less than the amount recommended by agricultural material dealers”. In conclusion, rational economic value cognition plays a dominant role in promoting pesticide reduction behavior, while ecological value cognition has a relatively limited effect on promoting pesticide reduction.

This study posits that the failure of digital agricultural technology extension to fully realize its potential is primarily attributable to two key factors: On one hand, there is an imbalance in the impact of digital agricultural technology extension on farmers’ cognition regarding pesticide reduction. While it has achieved some success in enhancing farmers’ rational ecological value cognition and significantly bolstered their recognition of the ecological merits of pesticide reduction, its efficacy in fostering rational economic value cognition among farmers is relatively inadequate. Despite farmers’ awareness of the positive ecological impacts of pesticide reduction, in actual decision-making, they are more concerned about the potential economic risks associated with it, such as reduced yields and lower incomes. The deficiency in rational economic value cognition leads farmers to forgo pesticide reduction. On the other hand, the limitations imposed by farmers’ qualities and literacy. The generally low digital literacy among farmers severely hampers the deeper impact of digital agricultural technology extension. Relying on the internet and other emerging technologies, digital agricultural technology extension aims to disseminate advanced agricultural techniques and concepts to farmers through convenient information channels. However, farmers predominantly utilize it for entertainment and social interactions, rather than proactively seeking agricultural technical knowledge, resulting in a “blockage” in the transmission of digital agricultural technology extension information, which fails to truly translate into a driving force for pesticide reduction.

5. Mechanisms Analysis Using fsQCA

To further analyze the mechanisms influencing pesticide reduction behavior among wheat farmers, this study employs the fsQCA (Fuzzy Set Qualitative Comparative Analysis) method, which combines the strengths of both quantitative and qualitative analysis. This approach not only provides additional insights but also helps to validate the reliability of the aforementioned conclusions.

5.1. fsQCA Method

fsQCA combines the “breadth” of quantitative analysis and the “depth” of qualitative analysis. It focuses on the complexity of research questions, emphasizing the holistic perspective while also paying attention to the role of individual variables. This method uses Boolean algebra and set theory to conduct comparative studies on medium- and small-scale cases, analyzing the logical relationships between multiple conditions and a single outcome. Through integrating case data, testing existing hypotheses, refining current theories, or developing new ones, fsQCA offers insights into social phenomena. Its key features include the following: First, it classifies social problems as outcomes and various complex factor assets, exploring the membership relationships between different sets and outcomes, which are asymmetric. Second, based on this asymmetry, fsQCA provides multiple possible pathways to the same outcome, focusing on revealing the impact of multiple concurrent conditions on social phenomena. Third, combining theory with real-world cases, fsQCA emphasizes qualitative changes in factors rather than simple quantitative changes, aiming to clarify the underlying logic behind observed phenomena. fsQCA is widely used in fields such as political science and sociology and is particularly effective in reflecting the complexity of real-world social phenomena.

5.2. Variable Selection

Based on the previous analysis, it is evident that farmers’ behavior was affected by the interaction of multiple factors. This study draws on theories, such as the Theory of Planned Behavior, Farmers’ Cognitive Theory, and the endowment effect, to explore how factors like digital agricultural technology extension influence farmers’ pesticide reduction behaviors. Building on the existing research and relevant theories, this paper constructs a theoretical framework of “external factor-driven → internal value cognition → resource endowment modulation”. Through the analysis of this framework, the paper tests the aforementioned results and provides a reference for the formulation and implementation of agricultural policies.

In this study, digital agricultural technology extension is used to represent external factors. Regarding internal value cognition, the focus is on ecological value cognition and economic value cognition [9]. Based on Bourdieu’s [29] capital endowment theory and the related literature, the study primarily considers factors such as the proportion of agricultural income in the household, the number of family laborers, and the scale of family-owned farmland, as these factors influence farmers’ pesticide reduction behavior [30].

In summary, the formation of pesticide use behavior among wheat farmers is a result of the three-dimensional interaction of external factor drivers, internal value cognition, and resource endowment modulation. This study aims to explore these three levels—external factors, internal value cognition, and resource endowment modulation—and incorporates five antecedent conditions and the outcome variable, farmers’ pesticide reduction behavior, into the same analytical framework, as shown in Figure 3. It seeks to explain the influence of digital agricultural technology extension as an external driving factor on farmers’ pesticide reduction behavior, while attempting to analyze the pathways through which multiple influencing factors collaborate.

Based on the previous analysis, this study aims to explore the impact of factors such as the extension of digital agricultural technology on the pesticide reduction behavior of wheat farmers. The dependent variable is defined as “whether the wheat farmer reduces pesticide use”. The question from the survey, “In terms of pesticide application, do you use more, maintain, or reduce the amount compared to the amount recommended by the agricultural input distributor?” is used to determine whether pesticide reduction behavior is present. A value of 1 is assigned for a reduction in pesticide use, and 0 is assigned for no reduction or an increase. The level of digital agricultural technology extension is measured using the question, “Have you ever watched videos on pesticide reduction applications online?” A value of 1 is assigned for a positive response, and 0 for a negative response. Farmers’ value cognition regarding pesticide reduction is represented in two dimensions. First, ecological value cognition is measured by the question, “Do you think pesticide reduction is beneficial for the long-term sustainable development of the ecological environment?” A value of 1 is assigned for “Yes”, and 0 for “No”. Second, the economic value cognition is measured by the question, “Do you think pesticide reduction will lead to a decrease in crop yield?” A value of 1 is assigned for “Yes”, and 0 for “No”. Resource endowment is represented by two aspects. The first is the per capita cultivated land area for agricultural labor, where agricultural labor refers to the number of family members engaged in agricultural production. The cultivated land area refers to the actual farming area of the household. The ratio of these two factors indicates the level of natural resource endowment. The detailed survey data are shown in

Table 2. Descriptive data of the household survey.

	Variable Name	Descriptive Statistics
		Mean	Std. Deviation	Maximum	Minimum
Causal Conditions	Digital agricultural technology extension	0.6	0.5026	1	0
	Rational ecological value cognition	0.65	0.4894	1	0
	Rational economic value cognition	0.6	0.5026	1	0
	High natural resource endowment	4.675	2.6272	10	1.5
	High economic resource endowment	0.141	0.0759	0.35	0.04
Outcome	Pesticide reduction	0.45	0.5104	1	0

Data Source: Created by the author.

.

The calibration of the data is a key step in fsQCA analysis. In existing studies, common calibration methods include direct calibration and indirect calibration [31]. This study adopts the direct calibration method. Under the premise of theoretical consistency, and based on actual survey cases and data distribution, the agricultural labor per capita cultivated land area and the proportion of agricultural income were directly calibrated. Three calibration thresholds were selected at the 95%, 50%, and 5% percentiles. For the remaining antecedent variables, the full membership and non-membership points were assigned values of 1 and 0, respectively, with the crossover point set at the median value of 0.5. Due to space limitations, the calibration results are not presented.

5.3. Result Analysis from fsQCA

Analysis of necessary conditions: After data calibration, the first step is to analyze the necessity of individual conditions to determine whether each condition is a necessary condition for the outcome variable. According to Schneider and Wagemann [32], a condition is considered necessary for the outcome variable if its consistency exceeds 0.9. Using the fsQCA 3.0 software, the questionnaire data from 20 sample farmers were analyzed. As shown in the

Table 3. Analysis of the necessity for the outcome.

Causal Conditions	Outcome (Pesticide Reduction)		Outcome (Pesticide Reduction)
	Consistency	Coverage	Consistency	Coverage
Digital agricultural technology extension	0.6667	0.5000	0.5455	0.5000
~Digital agricultural technology extension	0.3333	0.3750	0.4545	0.6250
Rational ecological value cognition	0.7778	0.5385	0.5455	0.4615
~Rational ecological value cognition	0.2222	0.2857	0.4545	0.7143
Rational economic value cognition	1	0.75	0.2727	0.2500
~Rational economic value cognition	0.0000	0.0000	0.7273	1.0000
High natural resource endowment	0.7022	0.6653	0.2891	0.3347
~High natural resource endowment	0.2978	0.2552	0.7109	0.7448
High economic resource endowment	0.3122	0.3504	0.4736	0.6496
~High economic resource endowment	0.6878	0.5167	0.5264	0.4833

Data Source: Created by the author.

, “Non-digital agricultural technology extension” and “Non-sustainability perception” are necessary conditions for “pesticide reduction”.

Analysis of sufficient configurational conditions: The sufficiency analysis of configurations is a core component of fsQCA, aimed at exploring the sufficiency of different combinations of antecedent conditions in leading to an outcome. This study uses data calibrated with fsQCA 3.0, constructing truth tables for various variables. Following the methods outlined in existing studies, the consistency threshold is set at 0.80, and the case frequency threshold is set at 1 [33]. Standard analysis of the final truth table yields three solutions: complex solution, intermediate solution, and parsimonious solution. This paper focuses on interpreting the intermediate solution, distinguishing core conditions from peripheral conditions. In the intermediate solution, all antecedent conditions not appearing in the core solution are considered peripheral.

The analysis of the table below reveals that there are two configuration paths leading to the behavior of “pesticide reduction”, with an overall consistency of 0.9716 and an overall coverage of 0.4933. This means that these two configurations can explain 49.33% of the cases in the study. The consistency of the two configurations is 0.9868 and 0.8974, both exceeding the 0.80 threshold, thus, both configurations are sufficient conditions for promoting pesticide reduction among wheat farmers, and they are considered equivalent. The subsequent analysis will follow the logic of “configuration results—mechanism analysis—case regression”, the specific configuration information is shown in

Table 4. fsQCA findings.

Conditions (Predictors)	Solutions
	Configuration 1	Configuration 2
Digital agricultural technology extension	●	⊙
Ecological value cognition	●	⊙
Economic value cognition	●	●
Natural resource endowment	●	●
Economic resource endowment		⊙
Consistency	0.9868	0.8974
Raw coverage	0.4156	0.0778
Unique coverage	0.4156	0.0778
Overall solution consistency	0.9716
Overall solution coverage	0.4933

Notes: Black circles (●) represent the presence of a condition (factor), and the circle with the cross (⊙) indicates the absence of it. Blank spaces indicate that the “don’t care” condition may be either present or absent. Data Source: Created by the author.

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Configuration 1: Digital agricultural technology extension type. The corresponding configuration path is “Digital Agricultural Technology Extension × Rational Ecological Value Cognition × Rational Economic Value Cognition × High Natural Resource Endowment”. This configuration indicates that for wheat growers with a larger per capita planting scale, the core condition for pesticide reduction behavior is the farmers’ rational economic value cognition of pesticide reduction. This means that these growers, being relatively large-scale farmers, are more inclined to adopt agricultural technologies obtained through the internet, thereby engaging in pesticide reduction behavior, given that they are aware that reducing pesticide application not only improves the ecological environment but also does not decrease their economic returns. In this case, the extension of digital agricultural technology plays a promotional role in pesticide reduction behavior but does not appear as a core condition. The main reasons for the occurrence of pesticide reduction behavior are twofold. On the one hand, economies of scale drive pesticide reduction. Farmers with a larger per capita planting scale are more sensitive to agricultural production costs and value. They are more likely to optimize production methods to reduce unit costs and enhance overall value. In this context, pesticide reduction not only helps to lower production costs but also brings higher economic returns by improving the quality and market competitiveness of agricultural products. On the other hand, farmers have a rational economic value cognition of pesticide reduction. This rational economic value cognition of pesticide reduction is what propels the behavior. When farmers recognize that reducing pesticide use will not harm their economic returns and may even lead to cost reductions, they are more willing to take proactive measures to reduce pesticide application. Relevant cases show that digital agricultural technology extension, by providing alternative information on pesticide reduction, helps farmers better understand and apply pesticide reduction technologies, thereby promoting the occurrence of pesticide reduction behavior to some extent. However, it is the farmers’ rational economic value cognition of pesticide reduction that is key to driving behavioral change, which validates Hypothesis 1 and Hypothesis 3.

Configuration 2: Non-digital agricultural technology extension type. The corresponding configuration path is “~Digital agricultural technology extension × ~Rational ecological value cognition × Rational economic value cognition × High natural resource endowment × ~High economic resource endowment”. This configuration indicates that for farmers with a smaller per capita planting scale and a lower proportion of agricultural income in their total family income, the formation of pesticide reduction behavior is mainly based on rational ecological value cognition and rational economic value cognition, which validates Hypothesis 1 and Hypothesis 2. Among these, rational economic value cognition and the relatively low proportion of agricultural income in family income are the core conditions that validate Hypothesis 3. The results of this configuration show that in such farmers, digital agricultural technology extension has not played a significant role in promoting pesticide reduction behavior, which validates Hypothesis 4. The main reason for the occurrence of pesticide reduction behavior is that the relatively low proportion of agricultural income in total family income indicates that farmers have a relatively low dependence on agricultural income. Therefore, when facing the potential economic risks associated with pesticide reduction, their concerns are relatively minor. This economic independence makes farmers more inclined to try new pesticide-reduction alternative technologies in their decision-making. At the same time, rational economic value cognition is an important factor for farmers to engage in pesticide reduction behavior. Relevant studies have shown that farmers’ cognition of pesticide reduction formed through non-online means, such as practical experience, distrust of agricultural input dealers, communication with neighbors, and agricultural training, has a significant impact on their pesticide reduction behavior [34]. These rational cognitive pathways help farmers recognize that pesticide reduction can greatly reduce production costs, improve the quality of agricultural products, and increase economic returns [35].

This configuration indicates that for farmers with a smaller per capita planting scale and a lower proportion of agricultural income in their total family income, the formation of pesticide reduction behavior is primarily driven by rational ecological value cognition and rational economic value cognition. Among these factors, rational economic value cognition and the relatively low proportion of agricultural income in family income emerge as the core conditions. The results of this configuration show that for such farmers, digital agricultural technology extension has not played a significant role in promoting pesticide reduction behavior. The main reason for the occurrence of pesticide reduction behavior is that the relatively low proportion of agricultural income in total family income indicates that farmers have a relatively low dependence on agricultural income. Therefore, when facing the potential economic risks associated with pesticide reduction, their concerns are relatively minor. Relevant cases show that for these farmers, rational economic value cognition of pesticide reduction is formed through non-digital means. These means include practical experience, distrust of agricultural input dealers, communication with neighbors, and participation in agricultural training programs. These non-digital channels provide farmers with the necessary information and confidence to adopt pesticide reduction practices, despite the lack of digital agricultural technology extension. Non-digital agricultural technology extension type. The corresponding configuration path is “~Digital Agricultural Technology Extension × ~Rational Ecological Value Cognition × Rational Economic Value Cognition × High natural resource endowment × ~High economic resource endowment”. This configuration indicates that for farmers with a smaller per capita planting scale and a lower proportion of agricultural income in their total family income, the formation of pesticide reduction behavior is mainly based on rational ecological value cognition and rational economic value cognition. Among these, rational economic value cognition and the relatively low proportion of agricultural income in family income are the core conditions. The results of this configuration show that for such farmers, digital agricultural technology extension has not played a significant role in promoting pesticide reduction behavior. The main reason for the occurrence of pesticide reduction behavior is that the relatively low proportion of agricultural income in total family income indicates that farmers have a relatively low dependence on agricultural income. Therefore, when facing the potential economic risks associated with pesticide reduction, their concerns are relatively minor. Relevant cases show that for these farmers, rational economic value cognition of pesticide reduction is formed through non-digital means, such as practical experience, distrust of agricultural input dealers, communication with neighbors, and agricultural training.

Robustness Test: fsQCA is a set-theoretic method. When minor changes are made to its operations and the results remain consistent without altering the substantive interpretation of the findings, the conclusions are considered robust [31]. The robustness test of the fsQCA method is mainly conducted by adjusting the consistency level threshold and the anchor points for membership value settings. In this paper, the robustness of the conclusions is primarily tested by increasing the consistency threshold. The consistency score threshold is raised from 0.80 to 0.85 to enhance the consistency and validity of the conclusions. After the test, it was found that the configuration paths remain unchanged, and thus the results are deemed robust. Due to space limitations, the results are not displayed.

6. Conclusions, Limitations, and Policy Recommendations

6.1. Conclusions

Based on interviews with 20 typical wheat growers using a semi-structured interview method, it was found that digital agricultural technology extension did not play a significant role in farmers’ pesticide reduction behavior. The main reasons can be summarized in three aspects: First, the information conveyed by digital agricultural technology extension in the short term is not sufficient to change the cognitive bias about pesticide reduction that farmers have formed over a long period due to anchoring mentality, that is, overuse of pesticides can effectively reduce the risk of reduced grain production. Second, the general digital literacy of farmers is relatively low, and digital platforms have not fully exerted their productive functions. Digital agricultural technology extension has not had an impact on helping farmers establish a rational economic value cognition. Third, due to the different interests pursued by the main bodies of digital agricultural technology extension and the geographical and climatic differences in various regions, the effectiveness and universality of the disseminated content are difficult to control. Using fsQCA for quantitative analysis further verified the results of the qualitative analysis, confirming the complexity of farmers’ pesticide reduction behavior, influenced by multiple factors, among which digital agricultural technology extension as an external factor did not significantly promote farmers’ pesticide reduction behavior. In contrast, farmers’ economic value cognition, the per capita arable land area of agricultural labor, and the proportion of family income from agriculture have a significant impact on pesticide reduction behavior.

6.2. Limitations

This study employs fuzzy-set qualitative comparative analysis (fsQCA), a method typically suitable for research with medium to small sample sizes, with the recommended sample size ranging between 10 and 80 cases. Given that the sample size of this study is 20, it lacks a certain degree of representativeness, thereby limiting the generalizability of the research findings. Moreover, as fsQCA is a configurational path analysis method, the natural resource endowment variable used in this study (measured by per capita planting area) fails to achieve heterogeneity analysis of the distinct planting behaviors that may occur among large, medium, and small-scale farmers. Future research may consider expanding the sample size to enhance the robustness and generalizability of the findings. It is also recommended to adopt a diversified research methodology to conduct a more in-depth exploration and analysis of the planting behaviors of large, medium, and small-scale farmers. This approach would provide more targeted policy recommendations.

6.3. Suggestion

The policy recommendations of the research conclusions include the following aspects. First, enhancing farmers’ digital literacy level. This can be achieved by conducting digital literacy training using a combination of online and offline methods and establishing a multi-party cooperation model. For instance, governments, research institutions, enterprises, and other parties can be encouraged to provide farmers with training on the application of digital technologies and the acquisition and processing of information through various means. These means include broadcasting and television, rural networks, mobile text messages, establishing two-way information communication channels, cultivating digital talent teams, and conducting demonstration training. Leveraging the existing network infrastructure in rural areas, an innovation-driven digital literacy and skills training system can be created. Second, to promote farmers’ rational economic value cognition of pesticide reduction. This can be performed by strengthening publicity and education through means such as brochures, training lectures, and informing farmers of the dangers of excessive pesticide application, as well as the economic benefits of pesticide reduction. Practical guidance can also be provided by organizing visits to demonstration sites where pesticide reduction has been successfully implemented, and showcasing the benefits and environmental improvements brought about by pesticide reduction through actual cases. The government can take the lead in promoting cooperation between townships and agricultural input dealers to establish a trust mechanism, ensuring that farmers have access to high-quality pesticide alternatives and reduction technologies. Third, to improve the regulatory mechanism for the sale of agricultural inputs and the incentive mechanism for pesticide reduction. This involves strictly implementing the pesticide business licensing system, strengthening integrated online and offline operations, and promoting information sharing between agricultural and rural departments and market supervision departments to improve the efficiency of agricultural input law enforcement. At the same time, farmers can be encouraged to reduce pesticide application through means such as financial subsidies and tax incentives, and agricultural input sellers can be encouraged to sell alternatives to chemical agricultural inputs and related technologies.