Analysis of farmers’ participation in e-commerce of agricultural products from perspective of social network: based on 349 household survey data from Hubei, Shandong, Anhui and Gansu in China

doi:10.3969/j.issn.1004-1524.2021.10.21

Acta Agriculturae Zhejiangensis ›› 2021, Vol. 33 ›› Issue (10): 1971-1981.DOI: 10.3969/j.issn.1004-1524.2021.10.21

• Agricultural Economy and Development • Previous Articles Next Articles

Analysis of farmers’ participation in e-commerce of agricultural products from perspective of social network: based on 349 household survey data from Hubei, Shandong, Anhui and Gansu in China

HU Yueli^a^,^b(), XIA Chunpinga^a^,^b^,^*(), JIA Cheng^a^,^b, WANG Cuicui^a^,^b

a. College of Economics and Management; b.Institute of E-Commerce, Huazhong Agricultural University, Wuhan 430070, China

Received:2020-09-27 Online:2021-10-25 Published:2021-11-02
Contact: XIA Chunpinga

Abstract

Abstract:

Based on 349 household survey data collected from Hubei, Shandong, Anhui and Gansu in China, a theoretical analysis of farmers’ participation in the e-commerce of agricultural products was conducted from the perspective of social network. The effect of social network and its four dimensions on farmers’ participation in the e-commerce of agricultural products was revealed by using the Binary Logistic model. On the basis, group regressions were conducted according to the gender, education, and e-commerce training status of the interviewed farmers, to examine the influences of the social network in different groups.The results showed that the social network and its two dimensions, namely, network interaction and network learning, had significant (P<0.01) impact on farmers’ participation in the e-commerce of agricultural products, and the impact of network learning was greater than that of network interaction. Compared with the male farmers and highly-educated farmers, the promotion effect of social network, network interaction and network learning was stronger for female farmers and lowly-educated farmers. In addition, other factors such as the farmland quality, and the e-commerce promotion level of government or e-commerce platform, also had significant (P<0.1 at least) impact on farmers’ participation in the e-commerce of agricultural products.

Key words: social network, network interaction, network learning, e-commerce of agricultural products

CLC Number:

S-9
F304.3

HU Yueli, XIA Chunpinga, JIA Cheng, WANG Cuicui. Analysis of farmers’ participation in e-commerce of agricultural products from perspective of social network: based on 349 household survey data from Hubei, Shandong, Anhui and Gansu in China[J]. Acta Agriculturae Zhejiangensis, 2021, 33(10): 1971-1981.

Figures/Tables 5

References 32

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维度 Dimension	指标 Index	平均值 Mean	标准差 Standard deviation
F1	F1-1	3.788	0.878
	F1-2	3.782	0.921
F2	F2-1	4.284	0.756
	F2-2	4.132	0.743
F3	F3-1	3.358	0.929
	F3-2	3.668	0.776
F4	F4-1	2.052	0.853
	F4-2	2.086	0.958

维度 Dimension	指标 Index	平均值 Mean	标准差 Standard deviation
F1	F1-1	3.788	0.878
	F1-2	3.782	0.921
F2	F2-1	4.284	0.756
	F2-2	4.132	0.743
F3	F3-1	3.358	0.929
	F3-2	3.668	0.776
F4	F4-1	2.052	0.853
	F4-2	2.086	0.958

变量类别 Variable type	变量名称 Variable	平均值 Mean	标准差 Standard deviation
被解释变量 Dependent variable	农户农产品电商参与行为 Farmer's participation in e-commerce of agricultural products	0.490	0.501
核心解释变量	社会网络Social network	0	0.502
Independent variable	网络互动Network interaction	0	1.000
	网络信任Network trust	0	1.000
	网络学习Network learning	0	1.000
	网络互惠Network reciprocity	0	1.000
控制变量Control variable	性别Gender	0.527	0.500
	年龄Age	40.585	14.894
	健康状况Health	4.312	0.790
	学历Education	2.699	1.131
	家庭经营耕地面积Area of family-owned farmland	6.975	6.117
	耕地质量Farmland quality	2.418	0.779
	快递物流便利程度Express delivery convenience	4.057	0.872
	政府或电商平台对电商的宣传力度	3.814	1.068
	E-commerce promotion level of government or e-commerce platform

变量类别 Variable type	变量名称 Variable	平均值 Mean	标准差 Standard deviation
被解释变量 Dependent variable	农户农产品电商参与行为 Farmer's participation in e-commerce of agricultural products	0.490	0.501
核心解释变量	社会网络Social network	0	0.502
Independent variable	网络互动Network interaction	0	1.000
	网络信任Network trust	0	1.000
	网络学习Network learning	0	1.000
	网络互惠Network reciprocity	0	1.000
控制变量Control variable	性别Gender	0.527	0.500
	年龄Age	40.585	14.894
	健康状况Health	4.312	0.790
	学历Education	2.699	1.131
	家庭经营耕地面积Area of family-owned farmland	6.975	6.117
	耕地质量Farmland quality	2.418	0.779
	快递物流便利程度Express delivery convenience	4.057	0.872
	政府或电商平台对电商的宣传力度	3.814	1.068
	E-commerce promotion level of government or e-commerce platform

变量 Variable	模型1 Model 1		模型2 Model 2		模型3 Model 3		模型4 Model 4
变量 Variable	B	SE	B	SE	B	SE	B	SE
社会网络Social network	2.334^***	0.298	—	—	2.073^***	0.349	—	—
网络互动Network interaction	—	—	1.240^***	0.162	—	—	1.004^***	0.184
网络信任Network trust	—	—	0.035	0.130	—	—	0.088	0.147
网络学习Network learning	—	—	1.087^***	0.163	—	—	1.305^***	0.196
网络互惠Network reciprocity	—	—	0.270^*	0.139	—	—	0.081	0.16
年龄Age	—	—	—	—	-0.050^***	0.014	-0.058^***	0.015
性别Gender	—	—	—	—	0.403	0.274	0.412	0.298
健康状况Health	—	—	—	—	0.224	0.181	0.358^*	0.203
学历Education	—	—	—	—	0.459^***	0.160	0.457^***	0.174
家庭经营耕地面积	—	—	—	—	-0.003	0.024	-0.008	0.026
Area of family-owned farmland
耕地质量Farmland quality	—	—	—	—	0.424^**	0.187	0.462^**	0.201
快递物流便利程度	—	—	—	—	0.236	0.161	0.238	0.176
Express delivery convenience
政府或电商平台对电商的宣传力度	—	—	—	—	0.252^*	0.139	0.231^*	0.152
E-commerce promotion level of government or e-commerce platform
常数项Constant	0.177	0.180	0.479^***	0.208	-2.142	1.532	-1.443	1.621
χ²	85.942		103.59		148.88		192.594
最大似然估计值	397.735		350.086		334.796		290.082
Maximum likelihood estimator
Nagelkerke广义决定系数	0.291		0.424		0.463		0.566
Nagelkerke R²
正确预测率Correct prodiction rate/%	69.9		77.7		77.9		81.7

Analysis of farmers’ participation in e-commerce of agricultural products from perspective of social network: based on 349 household survey data from Hubei, Shandong, Anhui and Gansu in China

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变量 Variable	男性组 Male	女性组 Female	参加培训组 Trained	未参加培训组 Not trained	高学历组 Highly educated	低学历组 Lowly educated
社会网络 Social network	1.504^*** (0.464)	2.986^*** (0.600)	1.854^*** (0.642)	2.040^*** (0.496)	1.800^*** (0.480)	2.555^*** (0.579)
网络互动 Network interaction	0.846^** (0.258)	1.228^*** (0.305)	0.977^*** (0.345)	1.058^*** (0.275)	0.857^*** (0.260)	1.342^*** (0.340)
网络信任 Network trust	-0.026 (0.202)	0.204 (0.245)	0.164 (0.265)	0.042 (0.223)	0.162 (0.188)	-0.171 (0.302)
网络学习 Network learning	1.256^*** (0.275)	1.483^*** (0.304)	1.837^*** (0.456)	1.444^*** (0.285)	1.479^*** (0.310)	1.505^*** (0.318)
网络互惠 Network reciprocity	-0.081 (0.218)	0.405 (0.276)	-0.114 (0.289)	0.023 (0.223)	-0.415 (0.261)	0.566^** (0.238)

变量 Variable	模型5 Model 5			模型6 Model 6			模型7 Model 7
变量 Variable	B	SE	Exp(B)	B	SE	Exp(B)	B	SE	Exp(B)
社会网络Social network	1.159^***	0.301	3.186	—	—	—	—	—	—
网络互动Network interaction	—	—	—	0.432^***	0.146	1.541	0.832^***	0.215	2.299
网络信任Network trust	—	—	—	0.014	0.139	1.014	0.018	0.205	1.018
网络学习Network learning	—	—	—	0.692^***	0.164	1.997	1.302^***	0.219	3.677
网络互惠Network reciprocity	—	—	—	0.142	0.144	1.153	0.189	0.200	1.208
年龄Age	-0.034^**	0.015	0.967	-0.046^***	0.016	0.955	-0.041^**	0.017	0.960
性别Gender	0.492^*	0.271	1.635	0.514^*	0.278	1.672	0.400	0.301	1.492
健康状况Health	0.239	0.186	1.271	0.283	0.192	1.328	0.079	0.206	1.082
学历Education	0.410^**	0.164	1.506	0.407^**	0.166	1.503	0.489^***	0.184	1.630
家庭经营耕地面积	0.002	0.024	1.002	-0.001	0.025	0.999	-0.006	0.029	0.994
Area of family-owned farmland
耕地质量Farmland quality	0.308	0.188	1.360	0.340^*	0.193	1.405	0.450^**	0.209	1.569
快递物流便利程度	0.289^*	0.158	1.336	0.261	0.164	1.298	0.196	0.181	1.216
Express delivery convenience
政府或电商平台对电商的宣传力度	0.367^***	0.137	1.444	0.398^***	0.142	1.489	0.256^***	0.157	1.291
E-commerce promotion level of government or e-commerce platform
常数项Constant	-4.291	1.534	0.014	-4.206^***	1.561	0.015	-10.855^***	2.141	0
χ²	73.058			85.022			126.287
最大似然估计值	327.903			315.939			274.674
Maximum likelihood estimator
Nagelkerke广义决定系数	0.296			0.337			0.469
Nagelkerke R²
正确预测率 Correct prodiction rate/%	71.4			74.8			79.3

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[6]	CHEN Jiping, LIU Guoqiang, LIU Yuying, FU Xinhong. Evaluation on standardization of farmers’ professional cooperatives: evidence from fruit and vegetable cooperatives in Sichuan [J]. Acta Agriculturae Zhejiangensis, 2021, 33(6): 1117-1127.
[7]	CAI Jun, ZHOU Xiaoyu. Farmer’s behavior intention and behavioral response transformation paths in management and maintenance of land consolidation projects: empirical analysis from four typical towns of Huaining County in Anhui Province, China [J]. Acta Agriculturae Zhejiangensis, 2021, 33(6): 1128-1140.
[8]	LI Zhenhua, GU Yikang, LIU Longqing. Innovation of farmers training management system from perspective of quasi-public goods: based on investigation of Zhejiang Farmers University [J]. Acta Agriculturae Zhejiangensis, 2021, 33(6): 1141-1148.
[9]	MIAO Miao, ZE Hanlu, WU Yonghua. Spatio-temporal evolution characteristics of cultivated land use transition in Zhejiang Province [J]. Acta Agriculturae Zhejiangensis, 2021, 33(4): 753-760.
[10]	WANG Liying, DING Shuyu, LIU Houping. Impact of rural industrial convergence on farmers’ income growth: an empirical study based on spatial effect and threshold effect [J]. Acta Agriculturae Zhejiangensis, 2021, 33(4): 761-776.
[11]	JIN Liwen, LIU Zengjin, LIU Aijun. Participation behavior of pork seller in traceability system: empirical analysis of 636 sellers in Beijing, Shanghai and Jinan, China [J]. Acta Agriculturae Zhejiangensis, 2021, 33(3): 541-552.
[12]	ZHANG Shasha, ZHENG Xungang, ZHANG Bizhong. Transportation infrastructure, spatial spillover and rural poverty reduction:an empirical study based on panel data [J]. Acta Agriculturae Zhejiangensis, 2021, 33(3): 553-564.
[13]	WEN Changcun, SUN Yuzhu. Analysis on farmers’ willingness to buy agricultural accessory risk based on regional index in China: a case study on cotton growers in Hebei Province [J]. Acta Agriculturae Zhejiangensis, 2021, 33(2): 346-354.
[14]	FU Lisha, QIN Tao, PAN Huanxue, DENG Jing. Empirical analysis on scale effect of forest output of forest insurance premium subsidy policy in China: based on difference-in-differences model and event study model [J]. Acta Agriculturae Zhejiangensis, 2021, 33(2): 355-368.
[15]	LI Haitao, FU Linlin, HUANG Zuhui, PENG Wenhuan. Various forms of moderate-scale management of agriculture and development prospects [J]. Acta Agriculturae Zhejiangensis, 2021, 33(1): 161-169.