Assessing Farmers’ Attitudes towards Rural Land Circulation Policy Changes in the Pearl River Delta, China

Abstract

An emerging and pressing issue in China’s economic reform is the intensified conflict between arable land protection and the encroachment of urban development into fertile farmlands that threaten food security and urban sustainability. New policies were issued to encourage rural land circulation as an attempt to ensure urban development and a sustainable food system, but farmers’ willingness to adopt the policies is largely unknown. A total of 4500 farmers within 9 cities’ boundaries in the Pearl River Delta were surveyed, and the theory of planned behavior and statistical tools were used to determine key factors affecting farmers’ attitudes towards the new sustainability policy. The results indicate that farmers’ cognition of the policies positively influenced farmers’ willingness to participate in land circulation. Attitude toward the Behavior (AB), Subjective Norm (SN), and Perceived Behavioral Control (PBC) were the dominant factors affecting the policies’ implementation. PBC had the most significant influence on sustainable policy participation, followed by SN and AB. AB alone could not determine the actual participation behavior because of external factors such as family, community, and other policy-related considerations. In conclusion, the successful implementation of the rural land-use policy will be primarily determined by the farmers’ cognition and behavior.

1. Introduction

One of the most important components of China’s economic reform was the land-use policy that motivated farmers to unleash the full potential for maximum production. The iconic, pioneer land-use reform region is the Pan-Pearl River Delta or Pearl River Delta (PRD, blue area in Figure 1), where economic growth and urban development have been booming, regarded as a flagship in China’s economic reform. Conflict arose recently, however, between rapid urban expansion and farmland preservation in the PRD that challenged the regional sustainability, particularly the agricultural food security, economic prosperity, and livelihoods of millions of farmers living in the peri-urban fringe or near megacities. Therefore, the land-use policy must be reevaluated and revised to ensure sustainable economic growth while addressing this emerging conflict.

As the pioneer region of China’s economic reform, the PRD has gone through numerous changes in land-use policy over the past decades. The impacts on the livelihoods of local farmers and their cognitive levels and behavior toward these ongoing land-use policy changes are largely unknown. Still, farmers’ attitudes would have significant implications for policy implementations. In this study, an extensive field survey was conducted to analyze local farmers’ cognition and behavior towards these policies in the PRD, with an overall objective to better understand the key factors and concerns affecting the policy implementation and, thus, regional sustainability.

2. Study Area Statements

In 2008, the PRD local government demanded to actively explore the scientific guidance to protect arable land, stop land grabbing, and improve land-use efficiency, while innovating land management to synergize urban development and farmland protection [1]. As a result, the PRD launched the land marketization initiative in 2014, “Stabilizing contract rights and releasing operation rights” [2] and passed the Amendment to Rural Land Contracting Law of the People’s Republic of China in December 2018 to grant farmers the legal status of Three Rights Division. The Three Rights Division was an attempt to clarify the legal terms of “right to own,” “right to contract,” and “right to manage” lands, aiming at a long-term, more effective, and relatively independent land-use policy [3].

The formation of the Greater Bay Area (PRD, Hong Kong and Macao; Figure 1) initiative launched in China’s 13th Five-Year Plan in 2016 [4] further escalated the conflict between urban development and rural arable land protection, by pushing the urban development into the fringe and converting the rural quality arable croplands into concrete and buildings, threatening the region’s sustainability. An initiative was issued in 2018 to assess land resources availability and zoning options to restrict construction land allocations within the inner area of the PRD but moderately expand in the outer region [5]. According to this zoning plan, it was estimated that by 2035, all zoned construction lands would be exhausted, and any new constructions would be at the cost of rural farmlands. Thus, the conflict between rapid urban expansion and farmland preservation is to continue, threatening economic growth and food sustainability.

To identify critical factors affecting farmers’ attitudes towards the new sustainability policy and explore the effectiveness of policy changes in conflict resolution, this study conducted a questionnaire survey on farmers in the PRD and analyzed farmers’ cognition, attitude, and participation behavior towards land-use policy changes using the theory of planned behavior (TPB) and statistical tools.

3. Basic Theory

3.1. Theory of Planned Behavior

TPB was developed by Icek Ajzen [6] (pp. 15–25) based on the Theory of Reasoned Action (TRA), whose core view is that human behavior results from deliberate planning. Attitude towards the Behavior (AB), Subjective Norm (SN), and Perceived Behavioral Control (PBC) are the three main variables that determine behavioral outcomes. Among them, AB refers to the positive or negative evaluation of a specific behavior by an individual [7], and SN refers to the pressure that an individual feels from salient individuals or groups that they should or should not carry out a particular behavior [6] (pp. 259–262). PBC refers to the degree of difficulty individuals can control when they anticipate carrying out a specific behavior [8].

TPB has been widely used in the fields of public relations [9], exercise [10], advertising [11], healthcare [12], and sustainable development [13] to study the beliefs, attitudes, intentions, and behaviors of actors. It has good cross-cultural adaptability and explanatory ability. As early as 1995, Lynne used TPB to study farmers’ decision-making behavior [14]. After entering the 21st century, TPB has been initially used in land use [15], agricultural production [16], land management [17], and other research.

Recently, TPB was used to study the circulation behavior of farmland and forest land in China [18,19,20,21,22,23]. These studies went beyond simple relationships between influencing factors and farmers’ willingness to focus on the formation process of the willingness and understanding of farmers’ psychological decision-making. However, these previous studies were conducted in a small geographic area within the PRD, but not at the large Greater Bay Area scale to assess farmers’ cognitive level and behavior of much more diverse farmers, economic status, social groups, and geographically different landscapes and accessibility.

3.2. TPB Applicability

Although individual cognition is the basis of behavior [24], it is not conclusive whether farmers’ cognition can directly affect farmers’ behavior. Some studies believe that improving farmers’ cognition will lead to corresponding changes in behavior [25,26], but others suggested that the two are not correlated [27,28]. In this study, the TPB was used to analyze farmers’ cognition specifically toward rural land circulation policy, a major component of the agrarian reform. Rural land circulation (RLC) refers to farmers’ behavior towards transferring land management rights (use rights) to other farmers or organizations [29]. Land circulation can be implemented through subcontracting, land-use rights transfer, shareholding, cooperation, leasing, exchange, or other types of agreements. In the land circulation process, farmers’ attitudes, beliefs, and external factors determine their behavior, which affects the implementation of the new rural land circulation policy.

According to the Law of Value of commodities, increases in income from land circulation generally promote further circulation [30]. If legal systems are established and farmers’ livelihoods are guaranteed in the land circulation process, there will be enthusiasm to participate in the land circulation [31]. In this study, attitudes towards land circulation, arable land protection, change, and appropriation, and attitudes towards urban development, living condition, land management rights transfer, and land policies as key AB attributes (

Table 1. Observation indicators of research targets on land circulation cognition.

Code	Observation Indicators	Options
Y	actual participation in land circulation	neutral behavior * = 1, negative behavior = 2, passive behavior = 3, active behavior = 4, positive behavior = 5
AB1	tendency of rural land use in the next year	continue farming = 1, abandon farming = 2, land circulation = 3, give up contracting = 4, settle in cities = 5
AB2	tendency of rural land use in the next 5 year	continue farming = 1, abandon farming = 2, land circulation = 3, give up contracting = 4, settle in cities = 5
AB3	tendency of homestead use in the next year	continue living = 1, renovation & expansion = 2, circulation = 3, demolition = 4, settle in cities = 5
AB4	tendency of homestead use in the next 5 year	continue living = 1, renovation & expansion = 2, circulation = 3, demolition = 4, settle in cities = 5
AB5	attitudes towards soil and water conservation	no measures = 1, basic measures = 2, regular measures = 3, active measures = 4, other measures = 5
AB6	attitudes to avoid land pollution	no measures = 1, basic measures = 2, regular measures = 3, active measures = 4, other measures = 5
AB7	attitudes towards the circulation of the right to operate rural land	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB8	attitudes towards the circulation of the right to operate homestead	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB9	attitudes towards urban production and living conditions	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB10	attitudes towards partial expropriation of rural land in the next 5 years	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB11	attitudes towards full expropriation of rural land in the next 5 years	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB12	attitudes towards partial expropriation of homestead in the next 5 years	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB13	attitudes towards full expropriation of rural land in the next 5 years	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB14	attitudes towards the renovation and expansion of homestead	no extension = 1, no application = 2, oral negotiation = 3, application approval = 4, policy process = 5
AB15	attitudes towards the current rural land system	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
AB16	attitudes towards the reform of rural land system	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN1	contracting rural land situation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN2	rural land use situation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN3	rural land investment	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN4	rural land income	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN5	household income	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN6	rural land geography	plain = 1, basin = 2, hill = 3, mountain = 4, tidal = 5
SN7	rural land farming situation	grain = 1, vegetable = 2, fruit = 3, forest = 4, other = 5
SN8	difficulties in farming	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN9	rural land expropriation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN10	compensation for rural land expropriation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN11	difficulties in household	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN12	homestead situation	1 = 1, 2 = 2, 3 = 3, 4 = 4, 5 = 5
SN13	expropriation of homestead	none = 0, 1 = 1, 2 = 2, 3 = 3, 4 = 4, 5 = 5
SN14	compensation for expropriation of homestead	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN15	community land use	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN16	change of rural land use	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
SN17	community land circulation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC1	education level	elementary = 1, middle = 2, high = 3, college = 4, graduate = 5
PBC2	cognition of the dependence of contracting rural land	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC3	cognition of the income of contracting rural land	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC4	cognition of the circulation of the right to operate rural land	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC5	cognition of land expropriation compensation	0–0.2 = 1, 0.2–0.4 = 2,0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC6	cognition of compensation methods for land expropriation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC7	cognition of land expropriation and resettlement	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC8	cognition of the use of land expropriation compensation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC9	cognition of homestead expropriation compensation	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC10	cognition of homestead expropriation and resettlement	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5
PBC11	cognition of regional economy	0–0.2 = 1, 0.2–0.4 = 2, 0.4–0.6 = 3, 0.6–0.8 = 4, 0.8–1.0 = 5

* No actual participation, do not support nor object.

) are summarized and analyzed to understand the attitudes towards land circulation policy implementation.

Farmers’ psychological decision-making is inevitably influenced by families, neighborhoods, and communities and bound by government regulations and policies [32]. We, therefore, regard the use, income, expenditure, planting, expropriation, compensation of family-owned land, family conditions, and the use, change, and circulation of communal land as key attributes of SN variables (Table 1) in the subsequent analysis. The key attributes of perceived behavior control or PBC include farmers’ broad knowledge, land dependence, income, requisition, compensation, circulation, resettlement, and regional economy (Table 1).

4. Methodology

4.1. Survey Design and Data Collections

A nested random survey was carried out using the Multi-stage Sampling Design [33] (pp. 182–191) to cover the broad geographic area of the PRD [34]. The survey design included three stages: (1) From all towns or streets in the city, select some as the samples in the first stage; (2) from all villages or neighborhood committees of the selected towns or streets in the first stage, select some villages or neighborhood committees as the samples in the second stage; (3) from all the farmers in the selected villages or neighborhood committees in stage two, select some as the research samples. The first- and second-stage sampling used the Cluster Sampling Method [33] (pp. 192–196), while the third stage used the Systematic Sampling Method [33] (pp. 197–199). Specifically, in this study, the nested surveys included nine (9) cities within the PRD (Figure 2). Within each city, five (5) towns were sampled, within each township, ten (10) villages were sampled, and within each village, ten (10) farmers were interviewed to arrive at a total of 4500 farmer interviews. The survey was conducted in five periods: 17 July to 3 September 2017; 16 October to 29 October 2017; 6 November to 3 December 2018; 29 January to 11 February 2018; and 24 March to 8 April 2018.

The questionnaires included three parts. The first part concerned the basic demographic characteristics of farmers, including gender, age, education, family population, and administrative position. The second part was related to farmers’ land, including land area, use, annual input and income, geographical environment, and planting situation. The third part was related to farmers’ cognition and behavior on land circulation (

Table 2. Characteristics of research targets.

Characteristics of Farmers				Characteristics of Family Farmland				Characteristics of Collective Land
	Category	Quantity	Rate/%		Category	Quantity	Rate/%		Category	Quantity	Rate/%
gender	male	2307	51.3	land area	≤0.33	1686	37.5	use rate	≤0.3	33	0.7
	female	2193	48.7	Hm 2	0.33–0.5	2670	59.3		0.4–0.6	1213	27
age	≤25	273	6.1		>0.5	144	3.2		0.7–0.9	2819	62.6
	26–40	994	22.1	use rate	≤0.3	18	0.4		1.0	435	9.7
	41–55	2184	48.5		0.4–0.6	1127	25.0	use	planting	4172	92.7
	≥56	1049	23.3		0.7–0.9	2546	56.6		livestock	144	3.2
education	elementary	1707	37.9		1.0	809	18.0		fishery	90	2.0
	middle	2259	50.2	investment/yr	≤0	828	18.4		forestry	76	1.7
	high	480	10.7	yuan/hm 2	0–3 K	2129	47.3		other	18	0.4
	college	54	1.2		3–6 K	1255	27.9	economic	≤0.3	176	3.9
family members	≤3	422	9.4		>6 K	288	6.4		0.4–0.5	670	14.9
	4–6	3934	87.4	income/yr	≤7.5 K	1895	42.1		0.6–0.7	2259	50.2
	≥7	144	3.2	yuan/hm 2	7.5–15 K	1707	37.9		0.8–0.9	1089	24.2
political station	people	4148	92.2		15–22.5 K	736	16.4		1.0	306	6.8
	CPC 1	349	7.8		>22.5 K	162	3.6	co-op 2	No	2831	62.9
	party member	3	0	income rate	≤0.3	367	8.2		Yes	1669	37.1
administration	No	4066	90.4		0.4–0.6	1769	39.3	-	-	-	-
	Yes	434	9.6		0.7–0.9	1031	22.8	-	-	-	-
-	-	-	-		1.0	1333	29.6	-	-	-	-

¹ Communist Party of China. ² Rural cooperatives.

).

For example, in Foshan city, the distance to the city center was taken as the clustering standard (Figure 3).

There were 32 towns or streets as of 2017 in Foshan [35], and they were divided into five (5) groups. The groups were labeled with the letters A–Z (

Table 3. Towns or streets of Foshan after grouping.

Group No.	Towns or Streets
a	1	2	3	4	5	6
	Lecong	Nanzhuang	Shiwan	Shishan	Zumiao	Zhangcha	-
b	7	8	9	10	11	12	13
	Beijiao	Chencun	Dali	Guicheng	Longjiang	Leliu	Xiqiao
c	14	15	16	17	18	19	20
	Daliang	Danzao	Hecheng	Jiujiang	Lunjiao	Lishui	Xingtan
d	21	22	23	24	25	26
	Baini	Junan	Ronggui	Xinan	Yundonghai	Yanghe	-
e	27	28	29	30	31	32
	Datang	Genghe	Lubao	Leping	Mingcheng	Nanshan	-

). After randomly removing Guicheng and Hecheng counties from Group b and Group c, respectively, the remaining towns or streets (

Table 4. Towns or streets of Foshan after regrouping.

Group No.	Towns or Streets
a	1	2	3	4	5	6
	Lecong	Nanzhuang	Shiwan	Shishan	Zumiao	Zhangcha
b	7	8	9	10	11	12
	Beijiao	Chencun	Dali	Longjiang	Leliu	Xiqiao
c	13	14	15	16	17	18
	Daliang	Danzao	Jiujiang	Lunjiao	Lishui	Xingtan
d	19	20	21	22	23	24
	Baini	Junan	Ronggui	Xinan	Yundonghai	Yanghe
e	25	26	27	28	29	30
	Datang	Genghe	Lubao	Leping	Mingcheng	Nanshan

) were relabeled. From these relabeled towns and streets, according to systematic sampling, with a random starting point of Group a Lecong, Lecong, Beijiao, Daliang, Baini, and Datang towns were subsequently selected for interviews.

In the second stage, taking Beijiao town (20 villages or neighborhood committees) as an example, ten (10) villages were selected to include Gaocun, Malong, Sangui, Shangliu, Taocun, Xijiao, Huanglong, Xincun, Shuikou, and Xihai, to be passed onto the third sampling stage. In the third stage, taking the Malong village (797 families) as an example, ten (10) farmers were systematically selected and labeled as 56, 135, 214, 293, 372, 451, 530, 609, 688, and 767 for interviews.

4.2. Data Processing

The survey data included categorical and numerical variables. The categorical variables gradually draw up answers according to questions assigned on a numerical scale of 1, 2, 3, 4, and 5. The numerical variables are continuously distributed from 0 to 1, and the results are outputs in the form of a Likert five-level scale [36], ranging from 0.0–0.2, 0.2–0.4, 0.4–0.6, 0.6–0.8, 0.8–1.0 intervals, which are then translated/assigned values of 1, 2, 3, 4, and 5, respectively, to be comparable with categorical variables. The detailed information on the survey is summarized in Table 1. The farmers’ cognitive scores (AB, SN, and PBC) included both categorical and continuous variables.

4.3. Factor Analysis

The farmers’ cognition of land circulation policy was derived from AB, SN, and PBC and was assigned with specific observation indicators such as AB_i, SN_i, and PBC_i (Table 1). To calculate the final cognitive scores, it was first necessary to determine the weight of each variable. Factor analysis [37] was used to extract common factors from the surveyed data. Factor analysis is a technique that can identify hidden representative factors in many variables and put the same essential variables into one factor, which can reduce the number of variables [38] and be expressed as:

X_i = a₁F₁ + a₂F₂ + … + a_pF_p + U_i

(1)

where X_i is the observable variable (i = 1, 2, …, k), F_j is the common factor (j = 1, 2, …, p), and p < k. a_i is the factor loading representing the contributions of each factor to the observed variable. U_i is part of X_i that cannot be explained by F_j and satisfies cov (F_i, U_i) = 0, indicating F is not related to U.

A single question or a single measurement, AB alone, cannot determine farmers’ attitudes towards the land circulation policy. However, we can reflect the farmers’ behavior attitudes with 16 indicators, including attitudes toward policies on land use, protection, change, expropriation, urban production and living, land management rights transfer, and land ownership (Table 1), each having different weights. The weight was determined using the dimensionality reduction function built within the SPSS statistical software. The extracted values were then normalized to obtain the weights of the farmers’ AB, SN, and PBC scores (

Table 5. The indicators’ weights of research targets.

AB				SN				PBC
	Initial	Extraction	Weight		Initial	Extraction	Weight		Initial	Extraction	Weight
AB1	1.000	0.773	0.06	SN1	1.000	0.728	0.06	PBC1	1.000	0.867	0.09
AB2	1.000	0.769	0.06	SN2	1.000	0.830	0.06	PBC2	1.000	0.876	0.09
AB3	1.000	0.862	0.06	SN3	1.000	0.919	0.07	PBC3	1.000	0.931	0.10
AB4	1.000	0.940	0.07	SN4	1.000	0.851	0.07	PBC4	1.000	0.935	0.10
AB5	1.000	0.821	0.06	SN5	1.000	0.808	0.06	PBC5	1.000	0.999	0.10
AB6	1.000	0.881	0.07	SN6	1.000	0.669	0.05	PBC6	1.000	0.867	0.09
AB7	1.000	0.915	0.07	SN7	1.000	0.828	0.06	PBC7	1.000	0.850	0.09
AB8	1.000	0.880	0.07	SN8	1.000	0.633	0.05	PBC8	1.000	0.857	0.09
AB9	1.000	0.625	0.05	SN9	1.000	0.794	0.06	PBC9	1.000	0.880	0.09
AB10	1.000	0.861	0.06	SN10	1.000	0.777	0.06	PBC10	1.000	0.690	0.07
AB11	1.000	0.873	0.07	SN11	1.000	0.737	0.06	PBC11	1.000	0.880	0.09
AB12	1.000	0.809	0.06	SN12	1.000	0.829	0.06	-	-	-	-
AB13	1.000	0.670	0.05	SN13	1.000	0.646	0.05	-	-	-	-
AB14	1.000	0.949	0.07	SN14	1.000	0.468	0.04	-	-	-	-
AB15	1.000	0.965	0.07	SN15	1.000	0.832	0.06	-	-	-	-
AB16	1.000	0.742	0.06	SN16	1.000	0.536	0.04	-	-	-	-
-	-	-	-	SN17	1.000	0.917	0.07	-	-	-	-

).

Further, using the regression method [39], we constructed a measurement model of participation behavior (Y) and AB, SN, and PBC:

Y = B₀ + (B₁ × AB + B₂ × SN + B₃ × PBC)

(2)

where Y represents the behavior of farmers participating in land circulation. AB, SN, and PBC are independent variables, B₀ is the model intercept, and B₁, B₂, and B₃ are the model slopes.

Substituting the output of SPSS into Equation (2), a linear regression model was obtained:

Y = −3.122 + (0.074 × AB + 0.232 × SN + 1.759 × PBC)

(3)

From the weights for each variable, we can see that farmers’ cognition has a positive linear impact on participation behavior. PBC has the largest weight, followed by SN and AB. This is not the same as the traditional survey results. Previous studies stated that AB had the most significant impact on actual participation behavior [40]. However, during our field surveys, it was found that in the economically developed PRD, farmers had a strong willingness to participate in land circulation, but the most important considerations are the permissibility of policies, the regional economic environment, and the resettlement after land circulation. The final participation behavior is most significantly affected by PBC and SN.

5. Results

5.1. Farmland and Household Dynamics

From the 4500 questionnaires, basic statistical characteristics of the farmers, farmlands, and communal (collective) land are summarized in Table 2. Among the surveyed farmers, the proportion of males (51.3%) engaged in agricultural labor is slightly larger than that of females (48.7%). Farmers over 41 years old accounted for 71.8%, while farmers under the age of 25 accounted for only 6.1%, which is far fewer than 18.2% of the number reported in The Statistical Communique of the Third National Agricultural Census of Guangdong (No. 5) [41]. Approximately 88.1% of the farmers are without a junior high school degree and had typically 4–6 family members. Approximately 7.8% are members of the Communist Party of China and 9.6% currently or formerly held administrative positions.

The rural farmlands are fragmented. Approximately 96.8% of the farmland is less than 0.5 hm² in size, with a use rate of more than 70% (versus fellow). Farmlands with an annual investment of less than 3000 yuan/hm² accounted for 65.7%, while those with an annual investment of more than 3000 yuan/hm² accounted for only 6.4%. The economic returns from these farmlands were rather variable too. Approximately 80% achieved an annual income of less than 15,000 yuan/hm², while less than 3.6% achieved a high income of 225,000 yuan/hm². More than 70% of household income comes from farmland operations, and this group accounts for 52.4% of the local farmers.

The collective or communal land uses were primarily crops. Specifically, 72.3% of the communal lands had a land-use rate of more than 70%, i.e., less than 30 percent of the land was left. Among the villages surveyed, 37.1% have established farmer cooperatives and 31.0% achieved good economic status.

5.2. Farmers’ Cognition of Land Circulation

Once the weight for each variable was determined, the farmers’ cognitive scores on land circulation were calculated by summarizing all scores. The results (Figure 4) suggest that the AB score is higher, which indicates that farmers have a better attitude toward land circulation and thus a positive role in rural land system reform. However, it is worth noting that the scores of SN and PBC are low, which indicates that farmers do not have proper cognition of land circulation and rural land system reform, and actual participation in land circulation will be significantly affected by communities and related policies.

This result also confirms the progress of rural land system reform. Since the promulgation of Opinions on Trial Reforms in Rural Land Expropriation, the Marketization of Rural Collective Construction Land, and the Homestead Land System in 2015, the pilot effort of Three Reforms has been carried out in 33 counties (cities, districts) across China. The reform of the right to operate contracted lands and the right to mortgage a homestead (usually referred to as the Two Rights Mortgage Reform) have been piloted in 291 counties (cities, districts) [42]. However, the pilot reform was on hold from the end of 2017 to the end of 2018 [43] and again to the end of 2019 [44]. The reason was that, aside from failure warning lessons learned from many other pilot areas to grasp the deep meaning of reform and deployment [45], there are still unknowns in opening the land market. The rural land market is still in a government-controlled environment. When the reform started, it lacked relevant supporting systems and measures, and some places were in a dilemma of involution.

5.3. Correlation between Farmers’ Cognition and Behavior

To facilitate quantitative analyses of farmers’ land circulation behavior, the actual participation behavior was classified into neutral, negative, passive, active, and positive behavior, with assigned scores of 1, 2, 3, 4, and 5. The statistical results are provided in

Table 6. Statistics of actual participation from the survey data.

	Score	Frequency	Rate/%
neutral behavior	1	2984	66.3
negative behavior	2	202	4.5
passive behavior	3	423	9.4
active behavior	4	707	15.7
positive behavior	5	184	4.1
Total	-	4500	100.0

.

The Pearson Product-Moment Correlation Coefficient (PPMCC) was used to verify the correlation between farmers’ cognition and behavior on land circulation. The PPMCC was proposed by Karl Pearson in the 1880s to reflect the degree of linear correlation between two variables [46]. The greater the absolute value of the correlation coefficient, the stronger the correlation between the variables. The results showed that the correlation coefficients between participation behavior and AB, SN, and PBC were 0.544, 0.559, and 0.687, respectively (

Table 7. Correlation coefficients among participation and attitudes towards land circulation policy.

		Behavior	AB	SN	PBC
Pearson	behavior	1	0.544	0.559	0.687
	AB	0.544	1	-	-
	SN	0.559	-	1	-
	PBC	0.687	-	-	1

).

To analyze the correlation between farmers’ cognition and behavior more intuitively, each farmer’s (numbered from 1 to 4500) cognition score and behavior score on land circulation are processed in two dimensions, the horizontal axis represents the number of farmers, and the vertical axis represents the scores of farmers’ cognition and behavior. The results are shown in Figure 5, Figure 6 and Figure 7 (part, see Supplementary Materials for full images).

According to Figure 5, Figure 6 and Figure 7 (part, see Supplementary Materials for full images), it is evident that the trends of AB, SN, and PBC are consistent with the trend of participation behavior, indicating that there is a strong correlation between the two, which is also consistent with the PPMCC results.

6. Discussion

6.1. Protection of Farmers’ Rights and Interests

The farmers’ participation behavior is a complex decision-making process. In the economically developed PRD, participation behaviors are affected by agrarian reform policies and the regional economic environment. During the survey, enthusiastic farmers with a strong willingness to participate in land circulation often existed, but they were mostly concerned about the livelihoods after land circulation. Questions remain, such as the following: Is there a reference standard or a role model for land circulation? Can the transaction land (total areas) sustain the future livelihood of the family? If the land is expropriated or requisitioned, what is the compensation standard? Are there any other means of resettlement?

These questions implied that communication about grass-roots agrarian reform policy is not in place and suggested that the essence of agrarian reform is equivalent to the Economic Reform in farmers’ minds. The reform of economic resources to guarantee farmers’ production and livelihood is key in implementing the rural land circulation policy. Effective policy execution requires all levels of government to pay attention to the transaction cost of land circulation, which should meet the needs of both sides of land circulation and establish a standard reference. It is further suggested that each city establish transaction standards for land circulation, based on its level of economic development, which must protect the legitimate economic rights and interests of farmers and consider the benign development of urban development.

6.2. Land Circulation and Sustainable Development of Urban-Rural Areas

The proportion of farmers in the PRD who do not participate in land circulation was as high as 66.3%, inseparable from the lack of publicity on land policy change. It was found that many town’s and village’s governments simply distributed the policy documents without the knowledge to inform what the policy is about, resulting from the lack of an understanding of the policy to address farmers’ concerns or questions. Some farmers even visited the county governments to consult specific policies. It was found to be difficult to implement the land circulation policy simply by relying on paper documents without interpretation from officials and thus challenging to implement an effective agrarian reform. During the agrarian reform in 1949, all levels of government dispatched land circulation teams to the countryside and established a land circulation executive structure composed of government officials, intellectuals, and farmer representatives to communicate with farmers on the policy and its implications. Within less than three years, the national land reform was completed [47]. The lessons from the past should be revisited to effectively carry out the new agrarian reform policy. It is suggested to set up a special agrarian reform-leading group in the pilot area composed of government leaders, academic and technical experts, and grassroots managers to organize on-site consultancies, including on-site presentations, on-site observances, on-site demonstrations, and on-site Q&A sessions.

On the other hand, there is a need to be vigilant that the result of land circulation is urban expansion. The idea of favoring urban over rural areas in the PRD has led to two simultaneous diseases over the past decades. One is the “urban diseases” characterized by overpopulation, overconsumption, waste of resources, and other issues in cities. The other is the “rural diseases” such as depopulation, abandonment, and environmental pollution in rural areas. The imbalanced and uncoordinated development of urban–rural areas is currently a significant barrier or bottleneck to the PRD’s sustainable social and economic development, and integrated, synergetic development of urban–rural areas has become the fundamental requirement for future urban–rural evolution and sustainability. To address this problem, the Degrowth movement [48] emphasizes the need to reduce consumption and production (social metabolism) and advocates a socially just and ecologically sustainable society with social and environmental well-being replacing GDP as the indicator of prosperity, which is also a point worth discussing.

In addition, the urban expansion has also created a conflict between urban development and food production as well as water resources protection. Input and output of food, energy, and water (FEW) resources between regions, spatial coupling, and feedback mechanisms between cities and rural communities are complex. Still, human resources and skills to sustainably manage these resources are lacking in the PRD. Current governments at all levels manage FEW resources in a fragmented and mechanical manner by adjusting regional economic structure and consumption. Yet, it is difficult to comprehensively address the resource and environmental issues caused by social and economic development. The European research project ROBUST (Rural–Urban Outlooks: Unlocking Synergies) suggests that there is a need to understand the spatial and temporal coupling between urban and rural areas through a multi-process, multi-system, and multi-regional approach to advance science for the sustainable development of regional urban–rural systems and provide essential information for policy- and decision-making [49]. In this study, we observed spatial patterns and their temporal variation, but we did not address the coupling nature of the two, which should be the future focus of this research.

7. Conclusions

Farmers’ cognition of land circulation in the Pearl River Delta played a key role in implementing policy reform. The most significant factor is the perceived behavior control or PBC, which explicitly includes the cognition of land expropriation compensation, the circulation of the right to operate, and the income of contracting rural land. Farmers’ subjective norm, or SN, including rural land investment, community land circulation, and rural land income, is the second most influential factor in policy adoption. The weakest factor is farmers’ attitudes towards behavior or AB, which included the attitudes toward the renovation and expansion of homesteads, the current rural land system, and the tendency of homestead use in the next five (5) years. Farmers’ AB alone is insufficient to determine the actual policy participation behavior because of other factors such as family, community, and related policies, self-knowledge reserve, regional economic environment, and the challenges that rural areas face. Regional sustainability is in question if farmers’ attitudes towards the new land circulation policy are low or negative.