Study on the Impact of Internet Use on Farmers’ Straw Returning to the Field: A Micro Survey Data from China

Abstract

Promoting the use of straw returning technology in rural areas is of great value to improve the use of agricultural technology and to reduce agricultural carbon emissions. However, the low proportion of straw recycling has also attracted more attention all over the world. An effective measure to solve this problem is to increase farmers’ internet use to encourage them to participate in straw recycling. Based on micro survey data from 2126 households obtained from China, this paper uses an ordered probability model (OPM) and seeks to measure the impact of internet use on farmers’ active use of straw returning and its heterogeneity. It aims to answer two questions: what the impact of internet use on farmers’ willingness to participate in straw recycling is, and whether there is heterogeneity. The study found that the use of the internet can significantly drive farmers to use straw to return to the field. Specifically, farmers using the internet are less likely to become non-adoption (−2.95%) or non-voluntary (3.09%), but have a greater probability of becoming voluntary (6.04%). Moreover, the heterogeneity analysis showed that older groups and lower income groups could improve their willingness to actively adopt straw returning technology after using the internet. According to this research, it is suggested to improve local network resources, guide farmers to effectively entertain, study, live, and better enjoy the dividends brought by the internet. In terms of environmental publicity and education, the government should make policy adjustments for older groups and low-income groups to promote the use of technology.

1. Introduction

China is actively promoting the construction of beautiful villages. Building beautiful villages is an important part of the rural revitalization strategy and an important means to increase farmers’ happiness [1]. It has a positive impact on the high-quality development of China’s rural areas [2]. It is worth noting that some agricultural production methods have caused environmental pollution in rural areas and increased rural carbon emissions [3]. Among them, the traditional treatment of crop straw has caused damage to the rural ecological environment [4]. As a historical issue, straw burning has always existed. Although this method allows farmers to use less time and economic costs, straw burning has brought a series of damages [5]. For example, it directly leads to a large increase in atmospheric nitrogen oxides, sulfur dioxide, hydrocarbons, and other pollutants, which reduces air quality, threatens people’s health, and even indirectly causes fires, urban smog, vehicle congestion, and airport closures [6]. From the perspective of farmland alone, it will also lead to a decline in land fertility [7]. Studies have shown that every incidence of burning straw will reduce soil organic matter by 0.2 to 0.3%, increase the risk of cultivated land moisture, destroy farmland biodiversity, and increase the risk of certain diseases and insect pests, causing crop yields to decrease [8]. Given that China is a large agricultural country, the per capita arable land resources are few and the utilization efficiency is high, which will increase the harm of straw burning. China produces a large amount of crop stalks every year [9]. The burning of stalks puts tremendous pressure on China’s environment, and the damage can be unimaginable [10].

In fact, China has attached great importance to the improvement of the agricultural ecological environment, and has taken a large number of effective measures to control rural straw burning [11]. In 2007, the Ministry of Agriculture of China issued the “Emergency Notice on Further Strengthening the Comprehensive Utilization of Straw and Prohibiting Straw Burning”, banning the burning of straw nationwide to strengthen resource utilization [12]. Article 119 of the Air Pollution Prevention and Control Law of the People’s Republic of China stipulates that the open burning of straw, fallen leaves, and other substances that cause smoke and dust pollution in populated areas shall be ordered by the relevant department to make corrections, and a fine of CNY 500 to CNY 2000 may be imposed [13]. At the same time, the “Criminal Law of the People’s Republic of China”, “Public Security Administration Penalty Law of the People’s Republic of China”, “Administrative Measures on Prohibition of Burning and Comprehensive Utilization of Straw”, “Interim Provisions on Sanctions for Violations of Laws and Discipline in Environmental Protection”, and other laws all have provisions on the punishment of straw burning [14]. Local governments have also taken measures to prohibit straw burning, such as using drones to cruise, rewarding reports, setting up propaganda slogans, and using broadcasts to enter the village for publicity. This has greatly improved the problem of straw burning in recent years [15]. However, farmers still take advantage of weak supervision to adopt night burning, morning burning, and small-scale burning [16]. To implement a complete ban may require greater policy enforcement, which has a lot to do with the farmers’ own understanding [17]. Furthermore, strengthening the utilization of agricultural straw resources is also the direction that the Chinese government has always advocated [18]. On 27 July 2008, the State Council of China issued the “Opinions on Accelerating the Comprehensive Utilization of Crop Straws” to encourage the collection of straw, the comprehensive utilization of straw resources, and the strengthening of straw.

After more than ten years of practice in straw treatment and utilization, returning straw to the field has become the most common and effective measure for straw treatment [19]. Straw returning to the field generally refers to the mechanical cutting of straw, which is crushed and then directly turned into the soil. This method is widely promoted along with the use of agricultural mechanization. Returning straw to the field is a means to develop agricultural waste resource utilization, which can effectively maintain the fertility of cultivated land, improve the quality of cultivated land, reduce greenhouse gas emissions, and may also decrease the probability of epidemics [20]. On the whole, returning straw to the field is a practical and feasible method, widely used internationally and promoted in China as a technology for arable land protection [21].

Based on the fact that China is rich in straw resources and the current proportion of straw returning to the field is not high, many scholars explain from different angles how to improve the utilization efficiency of straw returning technology. (1) Some studies reveal the impact of farmers’ individual characteristics and their subjective perceptions on returning straw to the field. Existing research has revealed that individual characteristics of farmers, such as individual age, gender, years of education, and income, have a significant impact on their use of straw returning technology [22]. Zeng et al. (2019) analyzed the influence of conformity tendencies on farmers’ adoption of straw resource utilization technology; the conclusion was that conformity to relatives, neighbors, and village cadres has a significant positive impact, but conformity to rich villagers has a negative impact [23]. He et al. (2020) introduced the variables of “interpersonal trust” and “institutional trust” to improve perceived value. The research on the psychological mechanism of farmers using straw utilization shows that strengthening technical services and improving the level of villagers’ mutual trust is an effective method [24]. (2) Some studies explore the impact of government policy subsidies on returning straw to the field. The government supports the use of new machines to speed up the efficiency of returning straw to the field [25]. For example, Hou et al. (2019) used evidence from Northeast China to verify that the use of straw shredders increased the willingness to choose straw returning to the field [26]. Government subsidies can also significantly increase residents’ willingness to adopt straw returning. (3) Some studies have shown that external conditions, such as plot characteristics, social norms, and geographic characteristics have affected farmers’ return of straw to the field [27].

Although research on the influencing factors of farmers’ adoption of straw recycling has been abundant, there is still room for in-depth discussion in combination with the characteristics of the new era [28]. In particular, the influence of internet use in rural China on farmers’ willingness to adopt straw-returning is rarely studied. In addition, the mechanism and empirical verification of the use of the internet on farmers’ straw returning to the field are not yet mature. Due to the influence of sample acquisition and other factors, there will be differences in the research on the use of internet use of farmers’ straw returning to the field. In fact, information acquisition is an important basis for economic entities to make decisions [29]. When information does not match, it is easy to cause adverse selection and moral hazard. With fewer information channels, farmers rely heavily on village-level organizations, broadcasters, neighbors, and other groups to obtain information, which will also affect people’s willingness to return straw to the field [30]. However, this kind of information inequality has greatly improved with the advent of the internet era [31]. Farmers can obtain a large amount of agricultural information through the internet with increasingly easy access, which largely changes people’s perception of new technologies [32]. Existing research has proved that the acquisition of information can improve farmers’ awareness of the technology of returning straw to the field, thereby increasing the degree and level of adoption of this technology [33].

Therefore, based on existing research and advanced data collection, this paper analyzes the impact of internet use on farmers’ adoption of straw-returning technology, and explores the heterogeneity of technology adopted by different groups to support the deeper understanding of this research topic. This study uses the valid sample data of 2126 rural households obtained from random surveys in Eastern, Central, and Western China from April 2020 to July 2020. (1) There is little literature on the impact of the internet on farmers’ straw exchange. The variable of internet use also takes into account the era background of China’s rural digitization, which has a certain perspective of innovation. (2) We aim to theoretically and comprehensively sort out the influence mechanism of internet use on farmers’ straw returning to the field, and use empirical data to verify it to provide policy recommendations and document support for the internet to better serve the use of rural resources. At present, the internet is widely available in rural China. In previous studies, most of the perspectives focused on the rural business opportunities brought about by the internet, and the impact of the internet on the return of rural straw to the fields was largely neglected. This is actually an important aspect of the beautiful countryside. Through this analysis, we can more closely grasp the impact of China’s digitalization on the construction of beautiful villages and the utilization of rural ecological resources. (3) Using an OPM to analyze the marginal effect of internet use on farmers’ willingness to use straw to return to the field can avoid endogenous problems to a certain extent and improve the accuracy of the conclusions.

Based on this, the structure of this paper is organized as follows: Section 2 introduces the background of rural internet development, and analyzes the theoretical framework of the impact of internet use on farmers’ adoption of straw returning technology. Section 3 introduces the research data sources, research design, research methods, and descriptive statistics. Section 4 introduces the empirical conclusions of the article and analyzes the heterogeneity of internet use on farmers’ use of straw returning to the field. Section 5 contains the conclusions and puts forward policy suggestions.

2. Background and Theoretical Framework

2.1. Background

Promoting the use of straw returning technology is a necessary way to reduce agricultural pollution and improve the quality of agricultural development. It is worth paying attention to the internal relationship between farmers’ straw returning to the field and internet use. Some studies believe that increasing farmers’ internet use can effectively encourage them to participate in straw recycling [12]. In this part, we will introduce the trend of rural Internet use and analyze the convenience of rural internet use to farmers’ straw returning.

In recent years, China has positioned broadband network construction as a strategic public infrastructure, and has incorporated it into an important strategic position to promote economic and social development and narrow the gap with developed countries. For this reason, in order to promote the development of rural internet, China has adopted many policies. For example, the “Broadband China” Strategy and Implementation Plan issued by the Chinese government in August 2013 proposed that by 2015, there would be urban fiber-to-the-home access to households, rural broadband access to villages, the ratio would reach 95%, and the broadband access capacity of urban and rural households would reach 20 Mbps and 4 Mbps. By 2020, broadband networks would fully cover both urban and rural areas. The household penetration rate of fixed broadband would reach 70%, and the proportion of administrative villages with broadband access would exceed 98%. The broadband access capacity of urban and rural households would reach 50 Mbps and 12 Mbps, respectively. In order to complete the broadband China strategic mission, in June 2014, China’s National Development and Reform Commission, the Ministry of Finance, and the Ministry of Industry and Information Technology jointly implemented the “Broadband Village” pilot project in a joint document organization, and tried to explore and promote useful experiences in the construction of “broadband villages” in some provinces in western China. In order to promote digital transformation and drive rural development, the Chinese government issued the “Digital Village Development Strategy Outline” in 2019, taking digital villages as an important aspect of the construction of digital China, and trying to drive the modernization of rural development through digitalization. The goal is to make preliminary progress in digital village construction by 2020. The 4G coverage rate in administrative villages across the country has exceeded 98%, and the internet penetration rate in rural areas has increased significantly. By 2025, important progress will have be made in the construction of digital villages. With the deepening of the popularization of 4G in rural areas and the innovative application of 5G, the “digital gap” between urban and rural areas has been significantly reduced.

As the country continues to promote the development of rural revitalization strategies, and with the continuous support of national policies, such as Digital Village and Broadband China, China’s rural internet has developed rapidly. According to the “Statistical Report on the Development of the Internet in China” (Figure 1 and Figure 2), the number of rural internet users in 2012 was estimated to be 156 million, and by 2017 this figure exceeded 200 million, reaching 209 million. By December 2020, rural netizens have exceeded 309 million, an increase of 153 million over 2012, and the growth rate has reached nearly 100%. The internet penetration rate in rural areas has also increased from 27.7% in 2012 to 59.9% in December 2020.

With the popularization of the internet in rural areas, the internet lifestyle has become a lifestyle for farmers. Short videos, WeChat communications, mobile payments, and other methods are profoundly changing all aspects of life among rural residents. (1) The convenience of information access has been improved, and rural residents can obtain information through very convenient means. (2) The convenience of communication between rural residents and the outside society is greatly improved, and rural residents can use social networks to communicate. (3) The convenience of obtaining training, personal growth, job hunting, shopping, etc., has been greatly improved, allowing rural residents to have more opportunities to participate in social competition.

This article focuses on the use of internet to reshape the farmers’ information and value orientation, which changes their choices for straw returning to the field. By selecting data from field surveys in rural China, we try to provide empirical verification of the impact of internet use on the willingness of rural residents to return straw to the field.

2.2. Theoretical Framework

According to the economic man hypothesis, farmers who adopt the technology of returning straw to the field will consider maximizing personal benefits, and make rational decisions after measuring costs and benefits. When the benefit of straw returning technology is greater than the opportunity cost borne by other disposal methods, it may be preferred; otherwise straw returning technology may not be adopted. In farmers’ decision making, information is an important resource. Information asymmetry may lead to adverse selection. The more convenient information acquisition is, the more it reduces the uncertainty of farmers’ cognition and promotes the rationalization of decision-making. From the perspective of farmers, the use of the internet has greatly innovated the original behavioral paradigm of villagers.

First, the cost of obtaining information has been greatly reduced, which has promoted the upgrading of the channels for farmers to obtain information. When farmers use straw to return to the field, information technology plays a real role. The use of the internet has changed the weak position of farmers’ information, greatly reduced the uncertainty of farmers’ decision making, and improved the rationality of their decision making. Through the use of the internet, farmers can obtain massive amounts of information about returning straw to the field, and have a more comprehensive understanding of the benefits of using pictures, short videos, and online cases, as well as develop an in-depth understanding of the behavioral hazards, such as straw burning, so that the results of decision making tend to be in line with rational expectations.

Second, the rapid expansion of network communication boundaries has promoted the upgrading of the exchange paradigm among farmers. Rural blood relationships and kinship have a greater impact on farmers’ behavior. Specifically, farmers will have a tendency to follow one another when returning straw to the field. Using social networks, farmers can communicate with rural cadres, large farmers, and neighbors, maintain information exchanges, make the resulting tendency more effective, and improve straw returning to the field. The frequency of communication between older farmers and their children and relatives will increase. During the communication, children and relatives will pass on knowledge related to straw returning to the field, environmental protection, and other concepts, and farmers tend to choose straw returning to the field. Furthermore, through short video platforms, farmers can communicate with internet experts and related groups more easily to obtain the propaganda of returning straw to the field, thus changing their understanding.

Third, the convenience of access to resources has been greatly improved, which has promoted farmers’ participation in the upgrade to digital lifestyles. Farmers can participate in learning about agricultural technology and obtain relevant agricultural technology training through the internet, so that they have a certain understanding of the increase in income of their own farmland after returning straw to the field. They are able to learn that returning straw to the field has the effect of maintaining soil fertility and the continuous productivity of cultivated land, which makes it easier to increase the willingness to use straw. Farmers can also learn about the harm caused by straw burning through the internet and reflect on their previous behaviors to avoid such behaviors again. In addition, farmers can obtain information from all over the world through the internet without going out. They can use international and domestic resources to broaden their horizons, deepen their understanding of the use of straw resources, improve the efficiency of straw resource utilization, and strengthen their understanding of straw returning to the field.

Fourth, non-economic benefits are becoming more important, making farmers cherish their reputation more. In the internet age, the spread and influence of good and bad incidents in rural areas have greatly increased. Farmers who burn straw are not only known to the villages around them, but may be known to a wider range of people. The impact on their lives will be greatly increased and their reputation will be damaged. In addition, returning straw to the field is a key technology promoted by the state, which has an impact on the rural ecological environment and rural carbon emissions. After farmers have a certain understanding of these policies and propaganda through the internet, they will naturally behave consciously.

Fifth, the cost of violations has greatly increased. The state uses drones and cadres to control straw burning. These advanced technical means are effective in catching violations, making the farmers not only financially penalized, but also legally penalized. Farmers live in the countryside. Once they are punished for straw burning in the village, they feel humiliated in front of the village and neighbors. Villagers can also understand the possible illegal costs of their actions through the internet, and they are less likely to take speculative actions themselves, and are more conducive to the use of straw recycling.

Based on the above analysis, we believe that the use of the internet will have a positive impact on farmers’ willingness to return straw to the field. In Eastern and Central as well as Western China, different regions have different economic and social conditions, so the impact of Internet use on farmers’ participation in straw returning may be different. In order to ensure the accuracy of the results, it is also necessary to control different regional variables in the follow-up analysis, and pay attention to the effect of Internet use on straw recycling in different regions.

3. Materials and Methods

3.1. Data and Variable Selection

Household surveys are a means to understand first-hand information of rural areas and obtain the latest and most authentic information at the grassroots level [18]. Although this survey method is cumbersome and costly, it can collect more accurate and reliable information, obtain abundant sample data, and support research work [9]. This survey was mainly conducted from April 2020 to July 2020, mainly to understand farmers’ utilization of rural ecological resources, and returning straw to the field was an important part of the content. We selected some provinces in Eastern, Central, and Western China to conduct surveys, including Hebei, Shandong, Zhejiang, Jiangsu, Hubei, Henan, Hunan, Anhui, Guizhou, Sichuan, Yunnan, for a total of 11 provinces. These are provinces that produce relatively more straw, and have experience in using straw-to-field technology, so they were used as sample collection areas. Based on the information of returning straw to the field in specific counties and the economic and social conditions in these provinces, 2–3 representative counties were selected from each province. Random sample villages are selected from in each county with randomly selected farmers. During the data collection, we distributed questionnaires to more than 2200 households, and the actual sample collected and sorted out was 2126 households. This effective sample also constituted the main source of data used in the article.

Through the questionnaire, data on individual characteristics of farmers, business characteristics, external characteristics, geographical characteristics, and straw returning to the field were collected. Two questions have been set up on the issue of returning straw to the field. The first question is: “Have you returned straw to the field on cultivated land?” It is used to measure the farmers’ choices of returning straw to the field. If the answer of the first question is “yes”, then they must answer the second question: “In the absence of government subsidies and supervision, are you willing to adopt the technology of returning straw to the field?” According to the responses, the answers are “very willing” and “more willing”, which are considered active choices and assigned a value of 1; the answers “very unwilling” and “relatively unwilling” are considered passive choices and assigned a value of 0; if the answer is general, and after analysis, the willingness to use straw to return to the field is not high, then we consider it as a passive choice and assign a value of 0. Therefore, the willingness degree is used to distinguish whether the farmer adopts the straw returning technique and three kinds of orderly responses are constructed, namely, non-adoption, non-voluntary, voluntary adoption. According to the statistics of 2126 farmers (Figure 3), 238 people did not use straw to return to the field, accounting for 11.19%; 1008 were involuntary adopters, accounting for 47.41%; and 880 were voluntary adopters, accounting for 41.39%.

The core explanatory variable of the article is the use of the internet by farmers. In order to measure the use of the internet by farmers, a question was designed in the questionnaire as follows: “Do you use mobile phones, computers and other equipment to obtain information about agricultural production?” If the farmer’s answer is “yes”, we think that he uses the internet. On the contrary, if the answer is “no”, we think that he does not use the internet. Among the farmers surveyed (Figure 4), 1683 people used the internet to obtain agricultural production information, accounting for 79.16%; 443 people did not use the internet to obtain agricultural production information, accounting for 20.84%. The proportion of the survey sample using the internet is higher than the internet penetration rate in Figure 4. The possible reason is that the eastern and central parts of the survey sample are provinces that produce more stalk. Compared with some western provinces, these provinces have relatively better economic and social conditions, and use the internet more frequently.

The relationship between the use of the internet and farmers’ adoption of straw return technology are further explored. According to the obtained data, the frequency of the data is shown in

Table 1. The relationship between internet use and farmers’ use of straw returning adoption.

	Non-Adoption		Non-Voluntary		Voluntary Adoption
	Obs.	Proportion(%)	Obs.	Proportion(%)	Obs.	Proportion(%)
Non-Internet Use	66	14.90	231	52.14	146	32.96
Internet Use	172	10.22	777	46.17	734	43.61

Source: Author analysis.

. Compared with the farmers who do not use the internet, the farmers who use the internet exhibited a lower proportion of non-use of straw recycling, and the active use of straw recycling is higher, indicating that farmers using the internet may be more inclined to use straw returning to the field, and are more inclined to take the initiative. This provides preliminary evidence that the use of the internet can improve the situation of returning straw to the field, and it has promoted farmers to actively choose straw returning to the field.

We are also taking into account that farmers’ straw returning may also be related to farmers’ individual characteristics, operational characteristics, external characteristics, and geographical characteristics. When collecting data, these data are also collected and controlled as control variables in the model. Some of these variables are assigned values of 0 or 1, and some are measured using the five-point Likert scale. See

Table 2. Descriptive statistics.

Variables	Explanation	Mean	Sd	Min	Max
Internet use	Do you use mobile phones, computers, and other equipment to obtain information about agricultural production? Yes = 1. No = 0	0.792	0.406	0	1
Internet cable	Does your home have an internet cable? Yes = 1, No = 0	0.84	0.366	0	1
Internet signal	Your evaluation of home network signal: Very bad = 1; Poor comparison = 2; General = 3; Better = 4; Very good = 5	3.673	0.901	1	5
Gender	Female = 0; male = 1	0.535	0.499	0	1
Age	Under 18 = 1; 18~25 = 2; 26~30 = 3; 31~40 = 4; 41~50 = 5; 51~60 = 6; Above 60 = 7	4.687	1.586	1	7
Degree	Primary school and below = 1; Junior high school = 2; High school/technical secondary school/technical school = 3; College/undergraduate = 4; Graduate and above = 5	2.432	1.084	1	5
Village cadres	Yes = 1, No = 0	0.0588	0.235	0	1
Party member	Yes = 1, No = 0	0.163	0.37	0	1
Comes from planting	Does the family’s main income come from farming? Yes = 1, No = 0	0.17	0.376	0	1
Net income	The average net income of your family: about Less than CNY 5000 = 1; RMB 5000–10,000 = 2; 10,000–15000 = 3; 15,001–20,000 = 4; 20,001–30,000 = 5; Over 30,000 = 6	3.655	1.904	1	6
Know prohibition burning	Do you know that burning straw in the open air is prohibited? Yes = 1, No = 0	0.879	0.327	0	1
Agro-technical station	Distance to Township Agricultural Technical Service Station: within 1 km = 1; 1 km–3 km = 2; 3 km–5 km = 3; 5 km–10 km = 4; Over 10 km = 5	2.713	1.009	1	4
Publicity of environmental protection policies	Your views on the publicity of environmental protection policies: very dissatisfied = 1; relatively dissatisfied = 2; general = 3; relatively satisfied = 4; very satisfied = 5	3.456	0.864	1	5
East	Yes = 1, No = 0	0.587	0.492	0	1
Middle	Yes = 1, No = 0	0.265	0.441	0	1
West	Yes = 1, No = 0	0.148	0.355	0	1

Source: Author analysis.

for details. We use two variables, internet cable and internet signal, as substitute variables for the robustness test of the family internet variable. According to sample statistics, 84% of people’s homes have network cables installed, and many people’s homes have network signal ratings ranging from general to better. Other characteristics of farmers are as follows: their average age is about 40–50, the average annual personal income is slightly higher than CNY 15,000, 87.9% know about straw burning, and the average evaluation of the publicity of environmental protection policies is between general and relatively satisfied. The above information shows that the gap between the samples of farmers is relatively large, and the distribution is also relatively wide, indicating that the samples are relatively broadly representative.

3.2. Model Selection

To measure the choice of different subjects in two variables, the probit or logistic models are generally used. In this article, if two discrete binary selection models are constructed, the residual terms may be related. In view of the fact that the straw recycling technology adopted by farmers in the article is orderly and discrete, there are three choices, namely: not to adopt straw recycling, passive adoption, and active adoption, which represent the degree of willingness of farmers to adopt the technology. This is in line with the conditions for using the OPM, so we tried to use the OPM to evaluate the impact of internet use on farmers’ straw returning to the field. With reference to the research of Jiang et al. (2020) [12], the model is established as follows:

$$y_i^{*}={\beta }_0+{\beta }_1\mathrm{i}\mathrm{n}\mathrm{t}ernetuse+{\displaystyle {\sum }_{j=2}{\beta }_j}control{s}_j+{\mu }_i$$

(1)

In the formula $y_i^{*}$ is an unobservable latent variable; $\mathrm{int}ernetuse$ is a variable used by the internet, which is the core explanatory variable of this article; and $control{s}_j$ is the control variable of this article, which represents the variables listed in Table 1 that may have an impact on the return of straw to the field. By adding possible control variables, it is used to make the conclusion more robust. $\beta$ is the influence coefficient of each variable, and ${\mu }_i$ is the residual term of the model, which obeys the standard normal distribution. The relationship between the unobservable latent variable $y_i^{*}$ and the straw recycling behavior variable y of farmers that can be observed through the sample is:

$$\begin{array}{c}y=0,\mathit{Non}\mathit{adoption} y*\le {\gamma }_0\hfill \\ y=1, \mathit{Non}\mathit{voluntary} {\gamma }_0<y*\le {\gamma }_1\hfill \\ y=2, \mathit{voluntary}\mathit{adoption} {\gamma }_1<y*\hfill \end{array}$$

(2)

In the formula, ${\gamma }_0$<${\gamma }_1$,${\gamma }_0$,${\gamma }_1$, respectively, represent the unknown segmentation point of the farmers’ behaviors of returning straw to the field. Based on this, it can be said that farmers do not adopt straw returning to field, passively adopt straw returning to field, and actively adopt straw returning to field. The probabilities of the three kinds of orderly selection are:

$$\begin{array}{c}p(y_i^{*}=0|X)=\Phi ({\gamma }_0-{\beta }_1\mathrm{i}\mathrm{n}\mathrm{t}ernetuse+{\displaystyle {\sum }_{j=2}{\beta }_j}control{s}_j)\\ p(y_i^{*}=1|X)=\Phi ({\gamma }_1-{\beta }_1\mathrm{i}\mathrm{n}\mathrm{t}ernetuse+{\displaystyle {\sum }_{j=2}{\beta }_j}control{s}_j)-\Phi ({\gamma }_0-{\beta }_1\mathrm{i}\mathrm{n}\mathrm{t}ernetuse+{\displaystyle {\sum }_{j=2}{\beta }_j}control{s}_j)\\ p(y_i^{*}=2|X)=1-\Phi ({\gamma }_1-{\beta }_1\mathrm{i}\mathrm{n}\mathrm{t}ernetuse+{\displaystyle {\sum }_{j=2}{\beta }_j}control{s}_j)\end{array}$$

(3)

In the formula, $\Phi (\cdot )$ represents the cumulative density function of the standard normal distribution. The parameters of OPM in this article will all be estimated by the maximum likelihood estimation model.

It is worth noting that there are problems that are not easy to explain in the coefficients estimated by the OPM. Generally, its direction and significance are used as the basis of the analysis conclusion, and the marginal effect of the explanatory variable is calculated to estimate the selection probability of the explanatory variable. In order to ensure the uniformity and accuracy of the conclusion, the average marginal effect is used as the sample marginal effect estimation method.

4. Empirical Conclusions

4.1. Basic Conclusions and Robustness Test

According to the previous article about the OPM design, we use the collected data and the STATA software to perform a regression. The basic regression results are shown in

Table 3. Basic regression results of the OPM.

Variables	Straw Adoption
Internet use	0.166 **
	(0.07)
Gender	−0.086
	(0.05)
Age	0.063 ***
	(0.02)
Degree	0.029
	(0.03)
Village cadres	0.026
	(0.12)
Party member	0.095
	(0.08)
Comes from planting	−0.326 ***
	(0.07)
Net income	0.072 ***
	(0.01)
Know prohibition burning	0.200 **
	(0.08)
Agro-technical station	−0.169 ***
	(0.03)
Publicity of environmental protection policies	0.143 ***
	(0.03)
east	0.294 ***
	(0.07)
middle	0.047
	(0.08)
/cut1	−0.236
	(0.22)
/cut2	1.302 ***
	(0.22)
Observations	2126
Pseudo R-squared	0.05850
LR chi2 (15)	239.8 ***

Note: Standard errors in parentheses. **, *** indicates level of significance at the 5% and 1% level, respectively.

. In the model, the sign of the regression coefficient of internet use on straw adoption is positive, and it is obvious at the 10% significance level, indicating that internet use has a significant positive impact on farmers’ adoption of straw recycling. It clearly shows that the use of the internet has a considerable role in promoting farmers to actively adopt the technology of returning straw to the field. In view of the fact that the size of the variables in the OPM may not be well explained, and in order to more accurately measure the impact of internet use on the return of straw to the field, we calculated the marginal effect of model selection. The specific results are shown in

Table 4. The marginal effect of the main explanatory variable.

Variables	Marginal Effect
	Non-Adoption	Non-Voluntary	Voluntary Adoption
Internet use	−0.0295 **	−0.0309 **	0.0604 **
	(0.0121)	(0.0127)	(0.0247)
Gender	0.0152	0.0159	−0.0310 *
	(0.00925)	(0.00966)	(0.0189)
Age	−0.0111 ***	−0.0116 ***	0.0227 ***
	(0.00392)	(0.00408)	(0.00794)
Degree	−0.00513	−0.00537	0.0105
	(0.00575)	(0.00601)	(0.0118)
Village cadres	−0.00463	−0.00484	0.00947
	(0.0207)	(0.0216)	(0.0423)
Party member	−0.0168	−0.0176	0.0345
	(0.0139)	(0.0145)	(0.0283)
Comes from planting	0.0578 ***	0.0605 ***	−0.118 ***
	(0.0127)	(0.0134)	(0.0256)
Net income	−0.0127 ***	−0.0133 ***	0.0261 ***
	(0.00257)	(0.00264)	(0.00509)
Know prohibition burning	−0.0354 **	−0.0370**	0.0724 **
	(0.0140)	(0.0146)	(0.0284)
Agro-technical station	0.0300 ***	0.0313 ***	−0.0613 ***
	(0.00464)	(0.00474)	(0.00901)
Publicity of environmental protection policies	−0.0253 ***	−0.0265 ***	0.0518 ***
	(0.00530)	(0.00551)	(0.0106)
East	−0.0520 ***	−0.0544 ***	0.106 ***
	(0.0134)	(0.0140)	(0.0269)
Middle	−0.00838	−0.00876	0.0171
	(0.0144)	(0.0151)	(0.0295)
Observations	2126	2126	2126

Note: Standard errors in parentheses. *, **, *** indicates level of significance at the 10%, 5% and 1% level, respectively.

.

In Table 4, we measured the marginal effects of each explanatory variable under the three choices, the core of which was the influence of internet use on farmers’ willingness to take the initiative to recycle straw. According to the regression results, compared with farmers who do not use the internet, the probability of farmers using the internet but not returning straw to the field decreased by 2.95%, the probability of passively using straw to return to the field decreased by 3.09%, and the probability of actively using straw to return to the field increased by 6.04%. It shows that farmers who use the internet are less likely to become non-adopters and passive adopters, and more likely to become active adopters. As farmers increase their internet use, their willingness for straw returning also increases, which is consistent with the analysis of Jiang et al. (2020) [12]. Furthermore, it is verified that the use of the internet has increased the convenience of obtaining agricultural information and reduced the weak position of farmers. On one hand, it can support farmers to have a more comprehensive understanding of the technology of returning straw to the field and increase the probability of actively adopting information. On the other hand, through communication with village cadres, large families, and relatives, the farmers may gradually change their business philosophy and are more willing to make choices that are more conducive to long-term interests. We also see that the strengthening of the use of information increases the cost of illegal actions. When farmers can feel the possible risks of decision making, they are more inclined to make rational economic decisions, so as to promote the further use of straw returning to the field.

Observing other explanatory variables, there are some phenomena worthy of attention: first, for each increase in age, farmers are less inclined to become non-adoption (−1.11%) or non-voluntary (−1.16%), but are more inclined to voluntary adoption (2.27%). A possible reason is that the greater the age, the more important the cultivated land is conceptually, and the more sustainable development of the cultivated land protects the fertility of the cultivated land, so they may be more inclined to choose straw returning to the field. Second, compared to farmers whose main income is not derived from planting, farmers from planting are more inclined to become non-adoption (5.78%) or non-voluntary (6.05%), but have a lower probability of becoming voluntary adopters (−11.8%). The possible reason is that non-planting industry groups have been exposed to more information and have a good understanding of agricultural technology, so they can avoid adverse selection due to weak information in decision making. Third, for every increase in household income per capita, they are less inclined to become non-adoption (−1.27%) or non-voluntary (−1.33%), with a higher probability of becoming voluntary adoption (2.61%), which indicates that as the farmers’ income increases, they are more likely to accept the technology of returning straw to the field. The possible reason is that the greater the farmers’ income, the more resources they have to learn about the technology of returning straw to the field and obtain more information, thus increasing their willingness to adopt it actively. Fourth, compared to farmers who do not know about the prohibition of straw burning, farmers who know the prohibition of straw burning are less inclined to become non-adoption (−3.28%) or non-voluntary (−3.44%), but are more likely to become voluntary adoption (6.73%). The reason is that farmers’ understanding of the straw burning ban policy can enhance their risk perception ability, and they will consider possible risks when making decisions, so that they are more likely to avoid some behaviors that violate the policy and increase the initiative of returning straw to the field. Fifth, compared with residents closer to the agricultural technology service station, residents further away are more likely to become non-adoption (3.00%) or non-voluntary (3.13%), but have a lower probability of becoming voluntary adoption (−6.13%). The possible reason is that the further the distance to obtain agricultural technology services, the less the promotion of related information and the willingness to actively use it. Sixth, promoting the awareness of environmental policies in villages and households will help increase the probability of farmers using straw returning technology, which is about 7.24%. The possible reason is that the government is propagating policies to improve residents’ perception of environmental protection, and it can also affect farmers’ adoption of agro-ecological technology. Seventh, compared with farmers in the western region, the probability of actively adopting the technology of returning straw to the field in the eastern region is better, 10.6%. The possible reason is that farmers in the eastern region have easier access to relevant agricultural information and are more willing to adopt technology.

4.2. Robustness Test

In view of the endogenous problems that may exist in the use of OPM, an attempt is made to conduct a robustness test. First, we tried to use internet cables and internet signals as substitute variables for internet use. The reason is that the behavior of home installation of the network and the quality of the network signal are important basic conditions for farmers to use the internet, and have a significant impact on the use of the internet. At the same time, the two substitution variables are not endogenous variables for farmers using straw returning to the field, will not cause endogenous problems, and meet the conditions as substitution variables. We use these two variables as core explanatory variables and perform OPM respectively. The results are shown in Model (1) and Model (2) in

Table 5. Model robustness test.

Variables	Model (1)	Model (2)	Model (3)	Model (4)
	Oprobit	Oprobit	OLS	Ologit
Internet use			0.092 **	0.290 **
			(0.04)	(0.12)
Internet cable	0.188 ***
	(0.07)
Internet signal		0.123 ***
		(0.03)
Gender	−0.085	−0.076	−0.044	−0.170 *
	(0.05)	(0.05)	(0.03)	(0.09)
Age	0.057 ***	0.051 **	0.033 ***	0.122 ***
	(0.02)	(0.02)	(0.01)	(0.04)
Degree	0.032	0.028	0.014	0.066
	(0.03)	(0.03)	(0.02)	(0.06)
Village cadres	0.024	0.054	0.012	0.080
	(0.12)	(0.12)	(0.06)	(0.20)
Party member	0.098	0.085	0.052	0.126
	(0.08)	(0.08)	(0.04)	(0.13)
Comes from planting	−0.329 ***	−0.338 ***	−0.184 ***	−0.587 ***
	(0.07)	(0.07)	(0.04)	(0.12)
Net income	0.070 ***	0.062 ***	0.039 ***	0.129 ***
	(0.01)	(0.01)	(0.01)	(0.02)
Know prohibition burning	0.201 **	0.213 ***	0.112 ***	0.315 **
	(0.08)	(0.08)	(0.04)	(0.14)
Agro-technical station	−0.166 ***	−0.162 ***	−0.091 ***	−0.299 ***
	(0.03)	(0.03)	(0.01)	(0.04)
Publicity of environmental protection policies	0.143 ***	0.123 ***	0.078 ***	0.234 ***
	(0.03)	(0.03)	(0.02)	(0.05)
east	0.274 ***	0.289 ***	0.163 ***	0.512 ***
	(0.08)	(0.07)	(0.04)	(0.13)
middle	0.029	0.045	0.032	0.042
	(0.08)	(0.08)	(0.05)	(0.14)
Constant			0.092 **
			(0.04)
/cut1	−0.240	−0.054		−0.423
	(0.22)	(0.23)		(0.38)
/cut2	1.298 ***	1.490 ***		2.226 ***
	(0.22)	(0.23)		(0.38)
Observations	2126	2126	2126	2126
R-squared			0.11
Pseudo R-squared	0.0587	0.0613		0.0626
LR chi2 (15)	240.70 ***	251.10 ***		256.50 ***

Note: Standard errors in parentheses. *, **, *** indicates level of significance at the 10%, 5% and 1% level, respectively.

. The influence coefficients of internet cable and internet signal are both positive and significant at the 1% significance level, indicating that both internet cables and internet signals increase the probability that farmers will adopt the initiative to return straw to the field, thus verifying that the use of the internet can improve farmers’ active use of straw returning technology, and the benchmark conclusion is accurate. Second, we tried to use the OLS model and the Ologit model as new models to re-regress. The regression results are shown in Model (3) and Model (4) in Table 5. It can be seen that whether it is the regression equation of OLS or Ologit model, the regression coefficient of internet use is positive and significant at the 5% significance level, which can indicate that the baseline regression conclusion is accurate. In the original model, we also considered adding control variables, etc. The overall model has a certain degree of robustness.

4.3. Analysis of Heterogeneity

Considering that the regression of some groups may be somewhat different from the whole, we tried to explore the heterogeneity. Some studies divide farmers into the new generation and the old generation and analyze the differences in their behavior. Based on China’s tremendous development in the past 40 years, there may indeed be differences in thinking between the new generation and the old generation of farmers, leading to differences in their choice of agricultural technology. We use 1980 as the boundary to divide the new generation and the old generation. This article distinguishes between 40 and above. The regression results of different samples are shown in Model (1) and Model (2) in

Table 6. Analysis of heterogeneity.

	Straw Adoption
Variables	(1) Less Than 40 Years Old	(2) Over 40 Years Old	(3) Below Mean	(4) Above Mean
Internet use	0.022	0.208 ***	0.231 **	0.101
	(0.16)	(0.08)	(0.09)	(0.11)
Gender	−0.114	−0.067	−0.103	−0.065
	(0.08)	(0.07)	(0.07)	(0.07)
Age	0.130 ***	0.082 *	0.083 ***	0.048
	(0.05)	(0.05)	(0.03)	(0.03)
Degree	0.060	−0.004	0.084 *	−0.013
	(0.05)	(0.04)	(0.05)	(0.04)
Village cadres	0.251	−0.067	−0.029	0.061
	(0.22)	(0.14)	(0.17)	(0.16)
Party member	0.088	0.086	0.180	0.035
	(0.13)	(0.10)	(0.12)	(0.10)
Comes from planting	−0.395 **	−0.319 ***	−0.242 ***	−0.455 ***
	(0.18)	(0.08)	(0.09)	(0.12)
Net income	0.066 ***	0.077 ***	0.078	0.036
	(0.02)	(0.02)	(0.05)	(0.05)
Know prohibition burning	−0.074	0.380 ***	0.206*	0.180
	(0.13)	(0.10)	(0.11)	(0.12)
Agro-technical station	−0.145 ***	−0.188 ***	−0.204 ***	−0.138 ***
	(0.04)	(0.03)	(0.04)	(0.04)
Publicity of environmental protection policies	0.118 **	0.168 ***	0.132 ***	0.153 ***
	(0.05)	(0.04)	(0.04)	(0.04)
east	0.328 ***	0.258 ***	0.255 ***	0.383 ***
	(0.12)	(0.10)	(0.09)	(0.13)
middle	0.035	0.034	0.002	0.140
	(0.13)	(0.11)	(0.10)	(0.14)
/cut1	−0.368	0.035	−0.187	−0.371
	(0.36)	(0.35)	(0.32)	(0.39)
/cut2	1.175 ***	1.584 ***	1.506 ***	1.002 ***
	(0.37)	(0.35)	(0.32)	(0.39)
Observations	832	1293	1041	1084
Pseudo R-squared	0.052	0.0758	0.0517	0.040
LR chi2 (15)	87.98 ***	173.3 ***	103.40 ***	80.72 ***

Note: Standard errors in parentheses.*, **, *** indicates level of significance at the 10%, 5% and 1% levels, respectively.

. It can be seen that compared with younger groups, older groups are more willing to choose straw returning technology after using the internet. In fact, it shows the wide use of the internet in rural China, and the largest group is farmers over the age of 40. These groups have access to the internet to obtain more information, so that their decision making can more quickly keep up with policy trends and also be in line with the trend of the times. This is not only in line with the current status quo in China, but can also support the active popularization and promotion of straw returning in rural areas, with a focus on supporting the use of older groups.

Different income structures may also have an effect in the adoption of straw returning technology. In order to explore this difference, we set the per capita income of China’s rural areas in 2019 at CNY 16,021. Thus, the boundary between the low-income and high-income groups is set to be CNY 15,000. After performing the OPM regression respectively, the regression results are shown in Model 3 and Model 4 in Table 6. It can be seen that low-income groups are more willing to adopt the technology of returning straw to fields after using the internet, which has a high marginal impact. After using the internet to obtain information, lower-income groups have obtained more information, which has greatly weakened their original information weakness. They can strengthen technological learning through the internet, thereby forming their own developmental advantages, thus becoming more willing to increase their use of technology.

5. Conclusions and Policy Implications

5.1. Conclusions

China has done a lot of work to improve the use of agricultural technology and reduce agricultural carbon emissions. However, China still needs to continue to improve the use of agricultural technology to reduce rural carbon emissions. Therefore, there are continuous efforts to promote the use of straw returning technology in rural areas. Based onmicro-survey data from 2126 households obtained in Eastern, Central, and Western China, this paper uses an OPM to measure the impact of internet use on farmers’ active use of straw returning to the field and its heterogeneity. The current research found that internet use can significantly drive farmers to use straw returning to the field. Specifically, farmers who use the internet are less inclined to become non-adoption (−2.95%) or non-voluntary (3.09%), but they are more likely to become voluntary adoption (6.04%). This result is still valid after a rigorous robustness test, which verifies the conclusion of the theoretical hypothesis of the article. In addition, the heterogeneity analysis results show that the use of the internet by older groups and lower-income groups can increase their willingness to actively adopt the technology of returning straw to the field.

The research not only enriches the relevant research literature on the impact of the internet on agricultural technology, but also provides relevant countries and regions with empirical evidence of the use of the internet in rural areas to promote the use of agricultural technology. It still needs to be pointed out that there are many limitations in the article. For example, the selection of indicators could be more refined, and the research design could also refer to more peer research results. Additionally, how internet use changes the internal mechanism of farmers’ use of straw returning can be further studied.

5.2. Policy Implications

This article hopes to support the promotion of agricultural technology in some countries and regions. Therefore, the policy implications are as follows:

First, it is very necessary to popularize internet use in rural areas at present. We have observed that farmers have not used the internet extensively for a long time; as learning from the internet is relatively fragmented rather than a systematic process, the role of the internet in promoting farmers’ education has not been fully utilized. Therefore, for decision makers, it is possible to combine the characteristics of the internet in terms of policy promotion, and to develop high-quality online learning resources for agriculture skills, thereby increasing the tendency to use agricultural technology, and providing a little empirical verification for the current widespread promotion of digital villages in China.

Secondly, the promotion of straw returning technology needs to consider the group characteristics of older groups and lower-income groups, and promote the use of the internet according to the characteristics of different groups, improve local network resources, and guide farmers to effectively entertain, study, live, and better enjoy the dividends that the internet brings. This is in line with basic practical observations, and it also reflects the fact that the current rural age group in China is relatively large and the population with lower income is more common. From this point of view, the government can also make some policy adjustments for older groups and low-income groups in terms of environmental promotion and education to promote the use of technology.

Lastly, a variety of measures can be taken to improve the use of straw returning to the field. For example, it is necessary to actively improve local network infrastructures. The analysis also shows that increasing farmers’ income and improving agricultural technical services in rural areas far away from towns and villages can help farmers actively participate in straw returning to the field. Furthermore, increasing the popularization of the straw burning ban and promoting the promotion of local environmental policies to villages and families can effectively improve the straw returning rate, especially the willingness of farmers to actively adopt straw returning technology.