Relationship within capital endowment, technology cognition and farmers’ low carbon use intention of cultivated land

doi:10.3969/j.issn.1004-1524.2021.12.23

Acta Agriculturae Zhejiangensis ›› 2021, Vol. 33 ›› Issue (12): 2423-2434.DOI: 10.3969/j.issn.1004-1524.2021.12.23

• Agricultural Economy and Development • Previous Articles Next Articles

Relationship within capital endowment, technology cognition and farmers’ low carbon use intention of cultivated land

WU Yaqun(), DONG Jie^*()

College of Public Administration, Huazhong Agricultural University, Wuhan 430070, China

Received:2020-12-12 Online:2021-12-25 Published:2022-01-10
Contact: DONG Jie

Abstract

Abstract:

Low carbon utilization of cultivated land is of positive significance to the reduction of greenhouse gas emissions and sustainable and healthy development of agriculture. In the present study, the theoretical analysis model and research hypothesis of capital endowment and farmers’ cognition were established first. Based on the survey data of 347 households in Hubei Province, China, farmers’ capital endowment and cognition of low-carbon utilization of cultivated land were measured. On this basis, Logit model, intermediary effect model and adjustment effect test method were adopted to reveal the relationship within capital endowment, technology cognition and farmers’ low-carbon use intention of cultivated land. It was shown that the capital endowment not only had a significant (at 1% level) direct positive impact on low-carbon use intention of cultivated land, but also had a significant (at 1% level) indirect positive impact via the intermediary variable of farmers’ cognition of low-carbon use of cultivated land. Environmental literacy played a positive moderating role between farmers’ self-efficacy cognition and low carbon use intention of cultivated land. Therefore, it was necessary to improve the farmers’ capital endowment from aspects of economic capital, social capital and cultural capital, to improve farmers’ awareness of low-carbon utilization of cultivated land through various channels, and to strengthen the popularization of environmental protection related knowledge to improve farmers’ environmental literacy.

Key words: capital endowment, technology cognition, low carbon utilization of cultivated land, farmers’ willingness, mediating effect model

CLC Number:

S-9
F301.2

WU Yaqun, DONG Jie. Relationship within capital endowment, technology cognition and farmers’ low carbon use intention of cultivated land[J]. Acta Agriculturae Zhejiangensis, 2021, 33(12): 2423-2434.

Figures/Tables 6

References 35

[1]	周嘉, 王钰萱, 刘学荣, 等. 基于土地利用变化的中国省域碳排放时空差异及碳补偿研究[J]. 地理科学, 2019, 39(12): 1955-1961. DOI
	ZHOU J, WANG Y X, LIU X R, et al. Spatial temporal differences of carbon emissions and carbon compensation in China based on land use change[J]. Scientia Geographica Sinica, 2019, 39(12): 1955-1961.(in Chinese with English abstract)
[2]	董莹莹. 农户异质性视角下低碳生产行为研究[D]. 杨凌: 西北农林科技大学, 2019.
	DONG Y Y. Study on low carbon production behavior from the perspective of farmers’ heterogeneity[D]. Yangling: Northwest A & F University, 2019. (in Chinese with English abstract)
[3]	韩雅清, 杜焱强, 苏时鹏, 等. 社会资本对林农参与碳汇经营意愿的影响分析: 基于福建省欠发达山区的调查[J]. 资源科学, 2017, 39(7): 1371-1382.
	HAN Y Q, DU Y Q, SU S P, et al. Social capital and farmers’ willingness for forest carbon sequestration management in underdeveloped regions of Fujian[J]. Resources Science, 2017, 39(7): 1371-1382.(in Chinese with English abstract)
[4]	张童朝, 颜廷武, 何可, 等. 资本禀赋对农户绿色生产投资意愿的影响: 以秸秆还田为例[J]. 中国人口·资源与环境, 2017, 27(8): 78-89.
	ZHANG T C, YAN T W, HE K, et al. Impact of capital endowment on peasants’ willingness to invest in green production: taking crop straw returning to the field as an example[J]. China Population,Resources and Environment, 2017, 27(8): 78-89.(in Chinese with English abstract)
[5]	沈雪, 张露, 张俊飚, 等. 稻农低碳生产行为影响因素与引导策略: 基于人际行为改进理论的多组比较分析[J]. 长江流域资源与环境, 2018, 27(9): 2042-2052.
	SHEN X, ZHANG L, ZHANG J B, et al. Influencing factors and guiding strategies for low-carbon production in rice planting: multiple-group analysis using interpersonal behavior improvement theory[J]. Resources and Environment in the Yangtze Basin, 2018, 27(9): 2042-2052.(in Chinese with English abstract)
[6]	单玉红, 王琳娜, 刘梦娇. 社会化小农趋势下农户低碳经营的路径分析: 以湖北省为例[J]. 长江流域资源与环境, 2020, 29(11): 2479-2487.
	SHAN Y H, WANG L N, LIU M J. Path analysis of socializing household farmers’ lower-carbon management: take Hubei Province as a case study area[J]. Resources and Environment in the Yangtze Basin, 2020, 29(11): 2479-2487.(in Chinese with English abstract)
[7]	黄晓慧. 资本禀赋、政府支持对农户水土保持技术采用行为的影响研究 : 以黄土高原区为例[D]. 杨凌: 西北农林科技大学, 2019.
	HUANG X H. Effect of capital endowment and government support on farmers’ adoption behavior of soil and water conservation technology: evidence form the Loess Plateau[D]. Yangling: Northwest A & F University, 2019. (in Chinese with English abstract)
[8]	刘丽, 褚力其, 姜志德. 技术认知、风险感知对黄土高原农户水土保持耕作技术采用意愿的影响及代际差异[J]. 资源科学, 2020, 42(4): 763-775.
	LIU L, CHU L Q, JIANG Z D. Influence of technology cognition and risk perception on the willingness to adopt soil and water conservation tillage technologies and its intergenerational differences[J]. Resources Science, 2020, 42(4): 763-775.(in Chinese with English abstract)
[9]	BOURDIEU P. Handbook of theory and research for the sociology of education[M]. New York: Greenwood Press, 1986.
[10]	罗岚, 李桦, 许贝贝. 绿色认知、现实情景与农户生物农药施用行为: 对意愿与行为悖离的现象解释[J]. 农业现代化研究, 2020, 41(4): 649-658.
	LUO L, LI H, XU B B. Green cognition, reality, and farmers’ biological pesticide application behaviors: explaining the deviation between farmers’ willingness and their behaviors[J]. Research of Agricultural Modernization, 2020, 41(4): 649-658.(in Chinese with English abstract)
[11]	刘丽, 苏玥, 姜志德. 社会资本对农户保护性耕作技术采用的影响及区域差异研究: 基于技术认知的中介效应分析[J]. 长江流域资源与环境, 2020, 29(9): 2057-2067.
	LIU L, SU Y, JIANG Z D. Effects of social capital on farmers’ conservation tillage and regional differences-intermediate effect analysis based on technical cognition[J]. Resources and Environment in the Yangtze Basin, 2020, 29(9): 2057-2067.(in Chinese with English abstract)
[12]	何可, 张俊飚, 张露, 等. 人际信任、制度信任与农民环境治理参与意愿: 以农业废弃物资源化为例[J]. 管理世界, 2015(5): 75-88.
	HE K, ZHANG J B, ZHANG L, et al. Interpersonal trust, institutional trust and farmers’ willingness to participate in environmental governance: a case study of agricultural waste recycling[J]. Management World, 2015(5): 75-88.(in Chinese)
[13]	颜廷武, 何可, 张俊飚. 社会资本对农民环保投资意愿的影响分析: 来自湖北农村农业废弃物资源化的实证研究[J]. 中国人口·资源与环境, 2016, 26(1): 158-164.
	YAN T W, HE K, ZHANG J B. Analysis of social capital influencing farmers’ willingness of environmental protection investment: evidence from empirical study on reusing agricultural wastes in Hubei rural areas[J]. China Population,Resources and Environment, 2016, 26(1): 158-164.(in Chinese with English abstract)
[14]	谢先雄, 李晓平, 赵敏娟, 等. 资本禀赋如何影响牧民减畜: 基于内蒙古372户牧民的实证考察[J]. 资源科学, 2018, 40(9): 1730-1741.
	XIE X X, LI X P, ZHAO M J, et al. How does capital endowment affect herdsman to reduce livestock?: an empirical analysis based on 372 herdsmen in Inner Mongolia[J]. Resources Science, 2018, 40(9): 1730-1741.(in Chinese with English abstract)
[15]	EHEAZU C L, EZEALA J I. Environmental adult education for mitigating the impacts of climate change on crop production and fish farming in Rivers State of Nigeria[J]. Journal of Education & Practice, 2017, 8(3): 98-107.
[16]	应瑞瑶, 朱勇. 农业技术培训方式对农户农业化学投入品使用行为的影响: 源自实验经济学的证据[J]. 中国农村观察, 2015(1): 50-58.
	YING R Y, ZHU Y. The impact of agricultural technology training on farmers’ use behavior of agricultural chemical inputs: evidence from experimental economics[J]. China Rural Survey, 2015(1): 50-58. (in Chinese with English abstract)
[17]	李辉婕, 胡侦, 陈洋庚. 资本禀赋、获得感与农民有序政治参与行为: 基于CGSS2015数据的实证研究[J]. 农业技术经济, 2019(10): 13-26.
	LI H J, HU Z, CHEN Y G. Capital endowment, sense of gains and peasant’s orderly political participation: an empirical analysis based on CGSS2015[J]. Journal of Agrotechnical Economics, 2019(10): 13-26.(in Chinese with English abstract)
[18]	刘可, 齐振宏, 黄炜虹, 等. 资本禀赋异质性对农户生态生产行为的影响研究: 基于水平和结构的双重视角分析[J]. 中国人口·资源与环境, 2019, 29(2): 87-96.
	LIU K, QI Z H, HUANG W H, et al. Research on the influence of capital endowment heterogeneity on farmers’ ecological production: analysis from horizontal and structural perspectives[J]. China Population,Resources and Environment, 2019, 29(2): 87-96.(in Chinese with English abstract)
[19]	吴萌, 甘臣林, 任立, 等. 分布式认知理论框架下农户土地转出意愿影响因素研究: 基于SEM模型的武汉城市圈典型地区实证分析[J]. 中国人口·资源与环境, 2016, 26(9): 62-71.
	WU M, GAN C L, REN L, et al. Analysis on influencing factors of farming households’ willingness to land conversion under the distributed cognition theory: an empirical evaluation of Wuhan Urban Circle by SEM[J]. China Population, Resources and Environment, 2016, 26(9): 62-71.(in Chinese with English abstract)
[20]	AJZEN I. The theory of planned behavior[J]. Organizational Behavior and Human Decision Processes, 1991, 50(2): 179-211. DOI URL
[21]	杨兴杰, 齐振宏, 陈雪婷, 等. 政府培训、技术认知与农户生态农业技术采纳行为: 以稻虾共养技术为例[J]. 中国农业资源与区划, 2021, 42(5): 198-208.
	YANG X J, QI Z H, CHEN X T, et al. Government training, technology cognition and farmer eco-agricultural technology adoption behavior: taking rice and shrimp co-culture technology as an example[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2021, 42(5): 198-208.(in Chinese with English abstract)
[22]	陈雪婷, 黄炜虹, 齐振宏, 等. 生态种养模式认知、采纳强度与收入效应: 以长江中下游地区稻虾共作模式为例[J]. 中国农村经济, 2020(10): 71-90.
	CHEN X T, HUANG W H, QI Z H, et al. Farmers’ cognition, adoption intensity and income effect of ecological breeding mode: a case study of rice-shrimp co-cultivation mode in the middle and lower reaches of Yangtze River[J]. Chinese Rural Economy, 2020(10): 71-90.(in Chinese with English abstract)
[23]	李子琳, 韩逸, 郭熙, 等. 基于SEM的农户测土配方施肥技术采纳意愿及其影响因素研究[J]. 长江流域资源与环境, 2019, 28(9): 2119-2129.
	LI Z L, HAN Y, GUO X, et al. Analysis of influencing factors on farmer’s willingness to adopt soil testing and formula fertilization technology based on SEM[J]. Resources and Environment in the Yangtze Basin, 2019, 28(9): 2119-2129.(in Chinese with English abstract)
[24]	颜廷武, 何可, 崔蜜蜜, 等. 农民对作物秸秆资源化利用的福利响应分析: 以湖北省为例[J]. 农业技术经济, 2016(4): 28-40.
	YAN T W, HE K, CUI M M, et al. Analysis of farmers’ welfare response to crop straw resource utilization: a case study of Hubei Province[J]. Journal of Agrotechnical Economics, 2016(4): 28-40.(in Chinese)
[25]	朱庆莹, 陈银蓉, 胡伟艳, 等. 社会资本、耕地价值认知与农户耕地保护支付意愿: 基于一个有调节的中介效应模型的实证[J]. 中国人口·资源与环境, 2019, 29(11): 120-131.
	ZHU Q Y, CHEN Y R, HU W Y, et al. A study on the relationship between social capital, cultivated land value cognition and farmers’ willingness to pay for cultivated land protection: an empirical analysis based on a moderated mediator model[J]. China Population,Resources and Environment, 2019, 29(11): 120-131.(in Chinese with English abstract)
[26]	黄晓慧, 王礼力, 陆迁. 资本禀赋对农户水土保持技术价值认知的影响: 以黄土高原区为例[J]. 长江流域资源与环境, 2019, 28(1): 222-230.
	HUANG X H, WANG L L, LU Q. Capital endowment influencing on farmers value perception of soil and water conservation technology: take the Loess Plateau as an example[J]. Resources and Environment in the Yangtze Basin, 2019, 28(1): 222-230.(in Chinese with English abstract)
[27]	严奉宪, 柳颖. 农村社区减灾公共品供给中农户认知研究: 基于湖北省农户调查数据[J]. 农业技术经济, 2015(1): 75-83.
	YAN F X, LIU Y. Research on farmers’ cognition in the supply of public goods for disaster reduction in rural communities: based on the survey data of farmers in Hubei Province[J]. Journal of Agrotechnical Economics, 2015(1): 75-83.(in Chinese)
[28]	吴雪莲, 张俊飚, 丰军辉. 农户绿色农业技术认知影响因素及其层级结构分解: 基于Probit-ISM模型[J]. 华中农业大学学报(社会科学版), 2017(5): 36-45.
	WU X L, ZHANG J B, FENG J H. Research on factors influencing framers’ cognition of green agricultural technologies and the stratification: based on probit-ISM model[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2017(5): 36-45. (in Chinese with English abstract)
[29]	李紫娟, 孙剑, 陈桃. 农户绿色防控技术采纳行为影响因素: 基于湖北省265户柑橘种植户调查数据的分析[J]. 科技管理研究, 2018, 38(21): 249-254.
	LI Z J, SUN J, CHEN T. Influencing factors of farmers’ green control techniques adoption behaviors: analysis of 265 citrus growers’ investigation data in Hubei Province[J]. Science and Technology Management Research, 2018, 38(21): 249-254.(in Chinese with English abstract)
[30]	冯潇, 薛永基, 刘欣禺. 生态知识对林区农户生态保护行为影响的实证研究: 生态情感与责任意识的中间作用[J]. 资源开发与市场, 2017, 33(3): 284-288.
	FENG X, XUE Y J, LIU X Y. An empirical study on impact of ecological knowledge on ecological protection behavior of forest farmers: based on middle role of ecological emotion and sense of responsibility[J]. Resource Development & Market, 2017, 33(3): 284-288. (in Chinese with English abstract)
[31]	蒋琳莉, 张露, 张俊飚, 等. 稻农低碳生产行为的影响机理研究: 基于湖北省102户稻农的深度访谈[J]. 中国农村观察, 2018(4): 86-101.
	JIANG L L, ZHANG L, ZHANG J B, et al. Study on the influence mechanism of low carbon production behavior of rice farmers: based on in-depth interviews with 102 rice farmers in Hubei Province[J]. China Rural Survey, 2018(4): 86-101.(in Chinese with English abstract)
[32]	田云. 认知程度、未来预期与农户农业低碳生产意愿: 基于武汉市农户的调查数据[J]. 华中农业大学学报(社会科学版), 2019(1): 77-84.
	TIAN Y. Cognition degree, future expectation and farmers’ low-carbon willingness in agricultural production: based on the survey data of farmers in Wuhan[J]. Journal of Huazhong Agricultural University (Social Sciences Edition), 2019(1): 77-84.(in Chinese with English abstract)
[33]	张露, 郭晴, 李文静, 等. 农户对水稻低碳生产技术的采纳意愿研究[J]. 西南大学学报(自然科学版), 2018, 40(11): 94-103.
	ZHANG L, GUO Q, LI W J, et al. Farmers’ willingness to adopt rice low-carbon production technology: influencing factors and intervention paths[J]. Journal of Southwest University (Natural Science Edition), 2018, 40(11): 94-103.(in Chinese with English abstract)
[34]	郭清卉, 李世平, 南灵. 环境素养视角下的农户亲环境行为[J]. 资源科学, 2020, 42(5): 856-869.
	GUO Q H, LI S P, NAN L. Farming households’ pro-environmental behaviors from the perspective of environmental literacy[J]. Resources Science, 2020, 42(5): 856-869.(in Chinese with English abstract)
[35]	温忠麟, 叶宝娟. 中介效应分析:方法和模型发展[J]. 心理科学进展, 2014, 22(5): 731-745.
	WEN Z L, YE B J. Mediating effect analysis: method and model development[J]. Advances in Psychological Science, 2014, 22(5): 731-745. (in Chinese with English abstract) DOI URL

指标 Index	选项 Option	样本数 Number	占比 Proportion/%
性别	男Male	243	70.03
Gender	女Female	104	29.97
学历Education	文盲Illiterate	29	8.36
	小学Primary school	105	30.26
	初中Middle school	169	48.70
	高中High school	39	11.24
	高中以上	5	1.44
	Above high school
年龄Age	≤40	15	4.32
	41~50	100	28.82
	51~60	129	37.18
	>60	103	29.68
耕地规模	≤ 1 334	21	6.05
Cultivated	>1 334~3 335	49	14.12
land scale/m²	>3 335~6 667	115	33.14
	>6 667~13 340	125	36.02
	>13 340	37	10.66

指标 Index	选项 Option	样本数 Number	占比 Proportion/%
性别	男Male	243	70.03
Gender	女Female	104	29.97
学历Education	文盲Illiterate	29	8.36
	小学Primary school	105	30.26
	初中Middle school	169	48.70
	高中High school	39	11.24
	高中以上	5	1.44
	Above high school
年龄Age	≤40	15	4.32
	41~50	100	28.82
	51~60	129	37.18
	>60	103	29.68
耕地规模	≤ 1 334	21	6.05
Cultivated	>1 334~3 335	49	14.12
land scale/m²	>3 335~6 667	115	33.14
	>6 667~13 340	125	36.02
	>13 340	37	10.66

变量 Variable	变量符号 Variable symbol	变量含义与赋值 Variable definition and assignment	均值 Mean	标准差 Standard deviation
耕地低碳利用意愿 Low carbon use intention of cultivated land	Y	非常不愿意~非常愿意,1~5 Very reluctant-very willing, 1-5	3.418	0.877
资本禀赋 Total capital endowment	X	熵权法计算值 Calculated by entropy method	3.296	0.517
经济资本 Economic capital	A_CAP	熵权法计算值 Calculated by entropy method	3.576	0.731
社会资本 Social capital	B_CAP	熵权法计算值 Calculated by entropy method	3.684	0.758
文化资本 Cultural capital	C_CAP	熵权法计算值 Calculated by entropy method	2.489	0.590
技术认知 Technology cognition	M	根据因子得分综合计算而得 Comprehensive calculation of factor scores	0	0.707
效益认知 Benefit cognition	A_B	根据因子得分计算而得 Calculated by factor score	0	1.000
自我效能认知 Self-efficacy cognition	P_BC	根据因子得分计算而得 Calculated by factor score	0	1.000
环境素养 Environmental literacy	E	根据因子得分计算而得 Calculated by factor score	0	1.000
年龄Age	X₁	<35,1;35~45,2;46~55,3;56~65,4;>65,5	3.444	0.915
性别Gender	X₂	男,1;女,0 Male, 1; Female, 0	0.767	0.424
政治面貌 Politic countenance	X₃	中国共产党党员,1;非中国共产党党员,0 CPC member, 1; Not CPC member, 0	0.026	0.159
政策推广Policy promotion	X₄	是,1;否,0Yes, 1; No, 0	0.816	0.388
村庄中有提供低碳生产服务技能支持 There is skill support for low carbon production	X₅	非常不同意~非常同意,1~5 Very disagree-very agree, 1-5	3.640	0.833
in village
地区变量Regional variable	R	咸宁,0;武汉,1 Xianning, 0; Wuhan, 1	0.303	0.460

变量 Variable	变量符号 Variable symbol	变量含义与赋值 Variable definition and assignment	均值 Mean	标准差 Standard deviation
耕地低碳利用意愿 Low carbon use intention of cultivated land	Y	非常不愿意~非常愿意,1~5 Very reluctant-very willing, 1-5	3.418	0.877
资本禀赋 Total capital endowment	X	熵权法计算值 Calculated by entropy method	3.296	0.517
经济资本 Economic capital	A_CAP	熵权法计算值 Calculated by entropy method	3.576	0.731
社会资本 Social capital	B_CAP	熵权法计算值 Calculated by entropy method	3.684	0.758
文化资本 Cultural capital	C_CAP	熵权法计算值 Calculated by entropy method	2.489	0.590
技术认知 Technology cognition	M	根据因子得分综合计算而得 Comprehensive calculation of factor scores	0	0.707
效益认知 Benefit cognition	A_B	根据因子得分计算而得 Calculated by factor score	0	1.000
自我效能认知 Self-efficacy cognition	P_BC	根据因子得分计算而得 Calculated by factor score	0	1.000
环境素养 Environmental literacy	E	根据因子得分计算而得 Calculated by factor score	0	1.000
年龄Age	X₁	<35,1;35~45,2;46~55,3;56~65,4;>65,5	3.444	0.915
性别Gender	X₂	男,1;女,0 Male, 1; Female, 0	0.767	0.424
政治面貌 Politic countenance	X₃	中国共产党党员,1;非中国共产党党员,0 CPC member, 1; Not CPC member, 0	0.026	0.159
政策推广Policy promotion	X₄	是,1;否,0Yes, 1; No, 0	0.816	0.388
村庄中有提供低碳生产服务技能支持 There is skill support for low carbon production	X₅	非常不同意~非常同意,1~5 Very disagree-very agree, 1-5	3.640	0.833
in village
地区变量Regional variable	R	咸宁,0;武汉,1 Xianning, 0; Wuhan, 1	0.303	0.460

变量 Variable	模型1 Model 1	模型2 Model 2	模型3 Model 3	模型4 Model 4	模型5 Model 5	模型6 Model 6	模型7 Model 7	模型8 Model 8
X	1.550^*** (0.255)	—	—	—	1.115^*** (0.265)	—	0.627^*** (0.145)	—
A_CAP	—	0.586^*** (0.165)	—	—	—	0.504^*** (0.179)	—	0.273^*** (0.096)
B_CAP	—	0.561^*** (0.183)	—	—	—	0.320^* (0.179)	—	0.170^* (0.096)
C_CAP	—	0.630^*** (0.205)	—	—	—	0.398^* (0.241)	—	0.259^** (0.130)
M	—	—	2.249^*** (0.238)	—	2.085^*** (0.237)	—	1.167^*** (0.127)	—
A_B	—	—	—	1.178^*** (0.145)	—	1.097^*** (0.144)	—	0.619^*** (0.077)
P_BC	—	—	—	1.080^*** (0.145)	—	0.971^*** (0.149)	—	0.543^*** (0.079)
X₁	-0.265^** (0.121)	-0.234^* (0.127)	0.004 (0.144)	0.003 (0.144)	0.083 (0.141)	0.093 (0.145)	0.042 (0.076)	0.053 (0.078)
X₂	0.894^*** (0.291)	0.861^*** (0.291)	0.841^*** (0.272)	0.838^*** (0.272)	0.689^** (0.269)	0.674^** (0.270)	0.434^*** (0.149)	0.417^*** (0.150)
X₃	2.786^*** (0.807)	2.558^*** (0.808)	2.513^** (1.138)	2.473^** (1.155)	2.729^** (1.195)	2.607^** (1.178)	1.484^** (0.631)	1.403^** (0.610)
X₄	1.562^*** (0.388)	1.485^*** (0.386)	1.292^*** (0.368)	1.282^*** (0.374)	1.119^*** (0.332)	1.090^*** (0.333)	0.690^*** (0.184)	0.667^*** (0.185)
X₅	0.115 (0.135)	0.083 (0.131)	0.080 (0.134)	0.078 (0.134)	0.064 (0.127)	0.050 (0.125)	0.039 (0.071)	0.028 (0.069)

Relationship within capital endowment, technology cognition and farmers’ low carbon use intention of cultivated land

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变量 Variable	模型9 Model 9	模型10 Model 10	模型11 Model 11	模型12 Model 12
X	0.379^*** (0.074)	0.318^*** (0.116)	0.440^*** (0.109)	1.129^*** (0.268)
A_B	—	—	—	1.114^*** (0.141)
P_BC	—	—	—	0.980^*** (0.150)

变量 Variable	模型13 Model 13	模型14 Model 14
A_B	1.160^*** (0.142)	1.160^*** (0.146)
P_BC	0.994^*** (0.151)	0.975^*** (0.153)
E	0.439^*** (0.139)	0.443^*** (0.141)
A_B×E	—	-0.003 (0.132)
P_BC×E	—	0.274^* (0.142)

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