1. Introduction
Farmland utilization not only affects food security, but also social stability of a country [
1]. China is a large agricultural country that is feeding a fifth of the global population [
2]; hence, farmland utilization has always been an important concern of the government. In the recent years, with the rapid growth of human population, and the booming development of urbanization and industrialization, the shortage and damage of farmland are worsening continuously [
3,
4,
5,
6]. According to the State Statistical Bureau of China, both the world’s and China’s arable land area showed a downward trend from 2011 to 2017 (
Figure 1a). Furthermore, high intensity farmland utilization activities in China release a lot of carbon dioxide [
7] and seriously pollute the ecological environment around the farmland [
8]. Referring to the data from the Food and Agriculture Organization of the United Nations in 2021, the utilization of chemical fertilizers and pesticides per unit area in China is much higher than the world average, resulting in a dramatic decline in the quality of farmland (
Figure 1b). Hence, the Chinese government has released a series of policies and laws related to farmland green utilization, such as the Land Administration Law of the People’s Republic of China and Regulations on Farmland Protection, so as to improve farmland green utilization efficiency. Low-carbon green utilization efficiency of farmland is an efficiency measurement concept that takes the output of economic and social dimensions as the desirable output and the environmental pollution as the undesirable output, and its goal is to promote the maximization of economic and social outputs and the minimization of environmental pollution through scientific evaluation [
9]. The improvement of low-carbon green utilization of farmland has become the top priority of Chinese agricultural development [
10].
Digital financial inclusion, characterized by digitalization and inclusiveness [
11], has been generally recognized as a significant promoter of efficiency, effectiveness and sustainability of agricultural production [
12,
13,
14]. Digital financial inclusion is defined as a financial system that can provide effective and comprehensive services to all sectors and groups of society. Its purpose is to emphasize the continuous improvement of financial infrastructure and the availability of financial services, so as to provide convenient financial services to people from all walks of life, especially those in underdeveloped areas and low-income society, at a relatively low cost [
15]. According to the Peking University Digital Financial Inclusion Index of China, the coverage breadth, the usage depth, and the digitalized level of inclusive finance increased dramatically from 2011 to 2020 in China [
16]. The extant literature has identified that digital financial inclusion can enhance the development of the agricultural supply chain [
14], agricultural industrial structure optimization and green total factor productivity [
17], agricultural high-quality development [
18], agricultural production for rural households [
19], etc. It seems that the rapid development of digital financial inclusion brings opportunities for the green development of agricultural production. Nevertheless, research on the relationship between digital financial inclusion and low-carbon green utilization of farmland is scarce.
Accordingly, this paper attempts to investigate whether (directing effects), how (mediating effects) and when (moderating effects) digital financial inclusion can promote low-carbon green utilization of farmland. On the basis of the existing literature, digital financial inclusion can facilitate the development of farmland transfer [
18,
20], which refers to farmers having the rights to transfer their land use rights to other farmers or economic organizations who are capable and willing to manage it [
21]. Further, the existing literature also identified that farmland transfer can enhance low-carbon green utilization of farmland [
22,
23]. Hence, farmland transfer seems to be a mediator in the relationship between digital financial inclusion and low-carbon green utilization of farmland, while the extant literature ignores the mediating effect mechanism. Moreover, the existing literature verified that farmland management scale seems to be a significant factor that influences low-carbon green utilization of farmland [
24,
25,
26], and it also has close connection with farmland transfer [
23,
27], while the extant literature ignores exploring their in-depth relationships.
To address these gaps, this paper attempts to investigate the following questions:
Can digital financial inclusion improve low-carbon green utilization of farmland directly?
How can farmland transfer mediate the relationship between digital financial inclusion and low-carbon green utilization of farmland indirectly?
How can farmland management scale moderate the relationship between farmland transfer and low-carbon green utilization of farmland?
In order to deal with these research questions, this paper collects Chinese provincial panel data from 2011 to 2020 and conducts equation model analyses in STATA 16.0. Our research contributes to the extant literature in the following aspects. To our knowledge, it is one of the first to theoretically and empirically identify that digital financial inclusion can dramatically improve low-carbon green utilization of farmland. Additionally, we integrate digital financial inclusion, farmland transfer, and farmland management scale in the analytical framework of low-carbon green utilization of farmland. This study can provide some practical guidance for governments, financial institutions, and farmland households. Based on the study, governments are suggested to increase the investments in the research and development of digital financial technologies, improve farmland transfer regulations and rules, regulate and control farmland transfer procedures, and increase the farmland transfer subsidy to improve low-carbon green utilization of farmland. The financial institutions are recommended to accelerate the establishment of the rural digital financial credit system and optimize agricultural digital financial insurance services. In addition, the farmland households can strengthen the study of Internet knowledge and expand the utilization of the Internet platform to promote low-carbon green utilization of farmland.
The remainder of the paper is structured as follows. The second section focuses on the literature review and hypothesis development. In the third section, we discuss the methodology. In the fourth section, the results and analyses are reported. Then, we demonstrate our conclusions, contributions, and future research directions in the fifth section. Finally, we make a conclusion.
3. Materials and Methods
3.1. Sample Selection and Data Sources
In order to test the proposed hypotheses, we use the sample of Chinese provincial panel data. There are 34 provincial administrative units in China. Limited by the availability of data, Hong Kong, Macao, Taiwan, and Tibet are excluded from empirical research. Hence, the research objects of this paper are the 30 provinces in mainland China, including Beijing, Tianjin, Chongqing, Hebei, Shanxi, Henan, Inner Mongolia, Liaoning, Jilin, Heilongjiang, Guangxi, Shanghai, Jiangsu, Guizhou, Zhejiang, Anhui, Qinghai, Fujian, Jiangxi, Guangdong, Shandong, Hubei, Hunan, Ningxia, Hainan, Sichuan, Yunnan, Tibet, Shaanxi, Gansu, and Xinjiang.
This paper uses the “China Statistical Yearbook”, “China Land and Resources Statistical Yearbook”, “China Rural Management Statistical Yearbook”, “China Rural Statistical Yearbook”, “China Environmental Statistical Yearbook”, and the website of the National Bureau of Statistics to collect the data indicators of low-carbon green utilization efficiency of farmland, farmland transfer, and farmland management scale. Meanwhile, this paper uses the interpolation method to fill the gaps caused by missing data in each year. The data source of digital financial inclusion is collected from the Peking University China digital financial inclusion index. Due to the statistical data of the digital financial inclusion index from 2011, the observation period is selected from 2011 to 2020.
3.2. Measurements of Variables
3.2.1. Measurements of Explained Variable
The explained variable in the research is low-carbon green utilization of farmland. Referring to Xie et al. [
69] and Ke et al. [
22], the measurement of low-carbon green utilization efficiency of farmland consists of three significant components: input indicators, desirable output indicators, and undesirable output indicators. Wherein input indicators involve labor inputs, land inputs, and capital inputs; desirable output indicators include economic outputs, social outputs, and environmental outputs; undesirable outputs refer to pollutant emissions and carbon emissions. The specific measurement variates and descriptions are presented (
Table 1). In terms of the measurement method, the SBM-Undesirable-VRS model was used (Formulas (1) and (2)). We suppose that the number of decision-making units (DMUs) in farmland utilization is
n, the number of input factor types is
m, the number of desirable output types and undesirable output types are
S1 and
S2, respectively, and the three sets of vectors
,
,
represent inputs, desirable outputs, and undesirable outputs, respectively; we define
,
,
.
In Formulas (1) and (2), D−, Dg, and Db represent the slack variables of inputs, desirable outputs, and undesirable outputs, λ is the weight vector, and represents the index of low-carbon green utilization efficiency of farmland.
3.2.2. Measurements of Explanatory Variable
In the research, the explanatory variable is digital financial inclusion. We measure it using the digital financial inclusion index. The digital financial inclusion index consists of three dimensions: coverage breadth, usage depth, and digitalized level. The specific measurement indicators are presented in
Table 2. Detailed information about the measurement of this index can be found at
https://idf.pku.edu.cn/docs/20210421101507614920.pdf (accessed on 1 August 2022).
3.2.3. Measurements of Mediating Variable
The mediating variable of this research is farmland transfer. Referring to Liu and Liu [
70] and Kuang and Peng [
71], farmland transfer is measured by the proportion of total area of transferred farmland to total area of contracted farmland of farm households.
3.2.4. Measurements of Moderating Variable
The moderating variable of this research is farmland management scale. Referring to Zhou et al. [
23] and Chen and Wang [
72], farmland management scale is measured by the ratio of total planting area to total rural population (size per rural labor).
3.3. Model Construction
3.3.1. Models of Main Effects
The construction of structural equation models can not only deal with explicit variables and latent variables, but also analyze the relationship between multiple explanatory variables, multiple explained variables, and multiple mediation variables [
73]. Referring to the relationships between explanatory variable and explained variable, this paper constructs the following path model of the main effects (Formula (3)):
In Formula (3), lcgufi,t represents the low-carbon green utilization efficiency of farmland of the province i in the year t, difi,t represents the digital financial inclusion index of province i in the year t, ei,t represents the error term, and c1 is the path coefficient of digital financial inclusion influencing low-carbon green utilization efficiency of farmland. If the path coefficient c1 is significantly positive, H1 is verified.
3.3.2. Models of Mediating Effects
According to the relationships among explanatory variable, mediating variable, and explained variable, this paper constructs the following path model of the mediating effects (Formula (4)).
In Formula (4), flti,t represents farmland transfer ratio of the province i in the year t, a1 is the path coefficient of digital financial inclusion affecting farmland transfer, and b1 and represent the path coefficients of farmland transfer influencing low-carbon green utilization efficiency of farmland and digital financial inclusion affecting low-carbon green utilization efficiency of farmland, respectively. If the path coefficient a1 is significantly positive, H2 is verified. If the path coefficient b1 is significantly positive, H3 is supported. If the mediating path coefficient a1 × b1 (dfi→flt→lcguf) is significantly positive, H4 is verified.
3.3.3. Models of Moderated Mediating Effects
Based on the relationships among explanatory variable, mediating variable, moderating variable and explained variable, this paper constructs the following path model of the moderated mediating effects (Formula (5)).
In Formula (5), flmsi,t represents the farmland management scale of the province i in the year t, dflti,t and dflmsi,t represent the decentration value of farmland transfer and farmland management scale, respectively, and b4 represents the coefficient of the interaction term of farmland transfer and farmland management scale. If the coefficient b4 is significantly positive, H5 is verified.
5. Discussion and Implications
5.1. Discussion
With the rapid growth of human population and the booming development of urbanization and industrialization, the shortage and damage of farmland are worsening continuously. The high intensity farmland utilization activities in China release a lot of carbon dioxide and seriously pollute the ecological environment around the farmland. Given the development of digital financial inclusion, the associated economic, social, and environmental benefits in agricultural development have attracted extensive attention. In this case, this paper attempts to explore whether, how, and when digital financial inclusion can affect low-carbon green utilization of farmland. First, the results of the structural equation model of the main effects indicate that digital financial inclusion is positively related to low-carbon green utilization of farmland (path coefficient is 0.438, significant at 1% level). Accordingly, digital financial inclusion can directly facilitate low-carbon green utilization of farmland. Specifically, with the expansion of coverage breadth, usage depth, and digitalized level of financial services, farm householders can obtain efficient financing support, achieve large-scale agricultural modernization, improve agricultural product sales, reduce transaction costs, and introduce digital technologies and green finance, which consequently facilitates the low-carbon green utilization of farmland.
According to the results of the structural equation model of the mediating effects, digital financial inclusion is positively related to farmland transfer (path coefficient is 0.497, significant at 1% level), farmland transfer is positively related to low-carbon green utilization of farmland (path coefficient is 0.273, significant at 1% level), and the mediating effect test of farmland transfer is passed (path coefficient is 0.136, significant at 1% level). Hence, digital financial inclusion can indirectly enhance low-carbon green utilization of farmland through the increasing of farmland transfer. To be specific, with the development of the coverage breadth, usage depth, and digitalized level of digital financial inclusion, information asymmetry problems can be eased, transaction costs can be reduced, agricultural and non-agricultural incomes will be increased, and scale of agricultural mechanization can be expanded, which are significant drivers of farmland transfer. Further, farmland transfer facilitates low-carbon green utilization of farmland through transferring management rights from low-efficiency operators to high-efficiency operators, reducing carbon and other pollutant emissions and adjusting grain planting structure.
Based on the results of the structural equation model of the moderated mediating effects, the path coefficient of the interaction terms of farmland transfer and farmland management scale is 0.182, passing the significant tests at the 1% level. Moreover, the moderated mediating effect test of farmland management scale is passed (path coefficient is 0.330, significant at 1% level). It indicates that farmland management scale positively moderates the relationship between farmland transfer and low-carbon green utilization of farmland. Farmland management scale plays moderated mediating effects. With the increase in farmland management scale, the positive effects of farmland transfer on low-carbon green utilization of farmland will grow. When the management scale of household increases, operators are more likely to introduce green technologies and activities and optimize the grain planting structure. The combined effects of farmland transfer and management scales can achieve large-scale agricultural production and the reduction of fertilizer and pesticide utilization, which subsequently improves the low-carbon green utilization of farmland.
5.2. Theoretical Implications
The results of the research provide various insights into the relationship between digital financial inclusion and low-carbon green utilization of farmland. The extant literature has identified that digital financial inclusion is positively related to agricultural supply chain [
14], agricultural industrial structure optimization and green total factor productivity [
17], agricultural production for rural households [
18], agricultural high-quality development [
19], etc. Nevertheless, the research on the relationship between digital financial inclusion and low-carbon green utilization of farmland is scarce. Through empirical tests, this paper identified that digital financial inclusion can efficiently enhance low-carbon green utilization of farmland. Our findings provide new evidence on the relationship between digital financial inclusion and low-carbon green utilization of farmland.
Another contribution of this study is that it provides a deeper understanding of mechanisms of how digital financial inclusion can improve low-carbon green utilization of farmland through the mediator of farmland transfer. In the extant literature, scholars have verified that digital financial inclusion is positively related to farmland transfer [
19,
20]. There are also some studies verifying that farmland transfer is positively related to low-carbon green utilization of farmland [
22,
23]. However, scholars ignored the mediating effects played by farmland transfer in the relationship between digital financial inclusion and low-carbon green utilization of farmland. This paper identified that digital financial inclusion can promote low-carbon green utilization of farmland through the positive mediating effects of farmland transfer. Our research provides a deeper understanding of mediating mechanisms between digital financial inclusion and low-carbon green utilization of farmland.
Finally, our study is one of the first to empirically verify that the effect of farmland transfer is of increased relevance to low-carbon green utilization of farmland in the conditions of large farmland management scale. The extant literature pointed out that farmland management scale plays mediating effects on the relationship between farmland transfer and farmland green utilization efficiency [
23]. There is also some evidence identifying farmland management as positively related to the reduction of fertilizer and pesticide [
73,
74]. It ignored the possibility of moderating effects played by farmland management scale in the relationship among digital financial inclusion, farmland transfer, and low-carbon green utilization of farmland. Farmland scale management represents an inevitable trend toward global modern agriculture. Our research is one of the first to identify the positive moderating effects of farmland management scale played in the relationship between farmland transfer and low-carbon green utilization of farmland.
5.3. Practical Implications
Our findings also provide some practical insights to governments, financial institutions, and farm households. In terms of governments, first, they are suggested to increase the investments in the research and development of digital financial technologies, so as to reduce the cost of financing transactions, and continuously extend digital financial inclusion services to the wider population. Second, it is necessary for governments to improve farmland transfer regulations and rules, and regulate and control farmland transfer procedures, in order to ensure the processes of farmland transfer are more transparent and simpler. Third, governments are suggested to increase the subsidy for farmland transfer, widely publicizing the subsidy scheme for farmland transfer to encourage the farmland transferring actions. With the improvement of digital finance systems and the extension of farmland transfer, low-carbon green utilization of farmland can be efficiently achieved.
In terms of financial institutions, they are recommended to accelerate the establishment of the rural digital financial credit system and optimize agricultural digital financial insurance services. Specifically, first, they are suggested to use the digital platform to establish internal links between agricultural insurance and agricultural credit, forming an organic combination of online and offline agricultural digital financial models. Second, financial institutions are encouraged to develop big data technologies to ease the problems of information asymmetry between farmers and digital financing platforms, and effectively promote the process of high-quality agricultural development. Relying on digital inclusive financial platforms, financing for both transfer-out and transfer-in of farmland transfer will be smoother, which would jointly drive low-carbon green utilization of farmland.
As for farmland households, they are encouraged to strengthen the study of Internet knowledge and expand the utilization of the Internet platform. Hence, Internet knowledge will be gradually popularized and applied in rural areas, the digital divide between regions will narrow, and equalization of access to digital inclusive financial services in rural areas will be achieved. Consequently, the low-carbon green utilization of farmland can be efficiently achieved.
5.4. Limitations and Future Research Directions
Despite the contributions this research makes to the existing literature, it still has several limitations. First, we only used the data collected from China. It is difficult to generalize our findings to other settings. Second, due to time and resource constraints, other relevant mediating and moderating variables were not introduced into the conceptual model, the variables that can influence the mediating and moderating variables were not discussed, and the antecedent variables of the independent variable were not explored as well.
However, these limitations also create the opportunity for future studies. First, it would be of necessity to test the conceptual model using a sample from other countries and regions to expand its applicability. Second, it is interesting to explore the antecedents of digital financial inclusion and some other factors that may matter in the relationship between digital financial inclusion, farmland transfer, farmland management scale, and low-carbon green utilization of farmland.
6. Conclusions
Digital financial inclusion has been gradually regarded as a significant promoter of the efficiency, effectiveness, and sustainability of agricultural production. However, the literature focusing on the relationship between digital financial inclusion and low-carbon green utilization of farmland is scarce. Accordingly, this paper attempts to explore whether, how, and when digital financial inclusion can affect low-carbon green utilization of farmland. Using a sample of Chinese provincial panel data from 2011 to 2020 and SEM analyses in STATA 16.0, this paper draws the following conclusions. First, digital financial inclusion can directly facilitate low-carbon green utilization of farmland; second, digital financial inclusion can indirectly improve low-carbon green utilization of farmland through the mediator of farmland transfer; third, farmland management scale positively moderates the relationship between farmland transfer and low-carbon green utilization of farmland. Farmland management scale played moderated mediating effects on the relationship among digital financial inclusion, farmland transfer, and low-carbon green utilization of farmland. In theory, our findings provide new empirical evidence for the research on the relationship between digital financial inclusion and low-carbon green utilization of farmland. We also provide a deeper understanding of mechanisms of farmland transfer and the role of farmland management scale in the relationship between digital financial inclusion and low-carbon green utilization of farmland. In practice, governments are suggested to increase the investments in the research and development of digital financial technologies, improve farmland transfer regulations and rules, regulate and control farmland transfer procedures, and increase the farmland transfer subsidy. Financial institutions are recommended to accelerated the establishment of the rural digital financial credit system and optimize agricultural digital financial insurance services. Farmland households are encouraged to strengthen the study of Internet knowledge and expand the utilization of the Internet platform. With the cooperation of governments, financial institutions, and farmland households, the low-carbon green utilization efficiency of farmland can be dramatically improved.