景区带村扶贫模式下农户参与旅游的经济效率——以秦巴山区旅游扶贫重点村为例

doi:10.18402/resci.2020.09.16

Abstract

Abstract:

Tourism poverty alleviation is an effective way to get rid of poverty in poverty-stricken areas in rural China. As an important poverty alleviation model, The economic efficiency of scenic spots in driving surrounding farmers to participate in tourism directly affects the effect of poverty alleviation in poor areas. In this study, farmers in key poverty alleviation villages around 3A and above scenic spots in the Qinling-Daba Mountains were used as the research objects, and the data envelopment analysis (DEA)-Tobit model was used to analyze the economic efficiency and influencing factors of farming household participation in tourism under the model of tourism-led village poverty alleviation. The results show that the overall economic efficiency of farming household participation in tourism around the scenic spots is low, but it is higher than the agricultural production efficiency of farming households, and 98.3 percent of farming households is mainly restricted by scale efficiency; Farming households’ tourism management is in the stage of increasing returns to scale. Increasing the factor input of tourism operation is the main way to improve scale efficiency; the characteristic variables of farming households have the most significant impact on tourism economic efficiency, followed by the variables of individual characteristics, and the influence of community characteristics is not significant. Based on these results, this article makes specific suggestions for improving the tourism economic efficiency of farming households: (1) Extend the tourism industrial chain of “tourism-led village poverty alleviation”, and expand the scale of investment to achieve the optimal combination of factors; (2) Increase human capital investment and improve technical management level; (3) Farming households should be differentiated to promote specialized community participation.

Key words: tourism-led village, tourism poverty alleviation, farmer participation, DEA-Tobit model, economic efficiency, Qinling-Daba Mountains

LI Ying, HUANG Dan, ZHU Ying, HE Wenhua, LI Jie. Economic efficiency of farmer participation in tourism-led village poverty alleviation：A case study of key poverty-stricken villages in the Qinling-Daba Mountains[J].Resources Science, 2020, 42(9): 1827-1836.

Figures/Tables 9

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Table 5

Figure 1

Figure 2

Table 6

Table 7

References 22

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	变量分类		变量名称	说明	变量类型
DEA模型变量	投入要素变量		旅游经营现金支出	支付员工工资+购买原材料+入股合作社+房屋租赁+其他/万元	连续变量
			政府旅游支持支出	政府产业补助+信贷贷款/万元	连续变量
			家庭旅游就业人数	旅游就业总人数/人	连续变量
			旅游经营时间	全家旅游经营时间/月	连续变量
			旅游经营房屋面积	面积/m²	连续变量
	产出要素变量		家庭旅游收入总额	住宿收入+餐饮收入+土特产零售收入+参与旅游接待服务收入+乡村旅游合作社入股分红+房屋出租收入+其他收入/万元	连续变量
Tobit模型	被解释变量		综合效率	DEAP2.1测算的综合效率值	截面数据
	影响因素	农户分化变量	水平分化	家庭劳动力非农生产活动的劳动时间/总劳动时间×100%	连续变量
		农户分化变量	垂直分化	家庭总支出/家庭食品消费支出	连续变量
		户主个人特征变量	年龄	实际观察值/岁	连续变量
			非农就业技能	1=有;0=无	虚拟变量
			受教育程度	1=大专、大学及以上;2=职业中学、高中;3=初中;4=小学;5=文盲	虚拟变量
		家庭特征变量	旅游开发征地	1=是;0=否	虚拟变量
			房子与景区距离	1=500 m之内;2=500~2500 m;3=2500 m以外	虚拟变量
			生产结构	旅游收入占家庭总收入的比例	连续变量
		社区属性变量	旅游开发参与度	1=很多;2=一些;3=较少;4=很少;5=无	虚拟变量
			农户社区属性认知	了解本村为旅游扶贫重点村：1=是;0=否	虚拟变量
			政府惠农补贴	农业补贴+生态补助+村干部工资+护林员工资+其他/万元	连续变量

调查市	抽样县	抽样镇	抽样村	景区
安康	宁陕县	筒车湾镇	许家城村、七里村	筒车湾景区（3A）
	石泉县	后柳镇	永红村、中坝村	中坝大峡谷（3A）
	汉滨区	瀛湖镇	清泉村、郭家河村	瀛湖（4A）
商洛	商南县	金丝峡镇	太子坪村、庙台子村	金丝峡（5A）
商洛	丹凤县	棣花镇	万湾村、棣花村、未知村	棣花古镇（4A）
汉中	西乡县	骆家坝镇	骆镇村、回龙村	骆家坝（3A）
宝鸡	陈仓区	香泉镇	南峪村、前锋村	大水川国际度假区（4A）
宝鸡	眉县	汤峪镇	上王村、闫家堡村	太白山景区（5A）

主成分	特征值	贡献率/%	累计贡献率/%
1	2.791	55.829	55.829
2	1.005	20.106	75.935
3	0.565	11.302	87.237

变量	指标	因子1	因子2	因子3
X1	旅游经营现金支出	0.698	-0.312	-0.015
X2	政府旅游支持支出	-0.020	0.488	-0.007
X3	家庭旅游就业人数	0.618	-0.225	0.035
X4	旅游经营时间	-0.390	0.836	-0.058
X5	旅游经营房屋面积	0.016	-0.065	1.003

效率类型	平均效率	分组
		[0,0.4]（较低效率组）		(0.4,0.6]（中等效率组）		(0.6,1]（较高效率组）
		样本量/个	百分比/%	样本量/个	百分比/%	样本量/个	百分比/%
综合效率	0.335	218	75.96	49	17.07	20	6.97
技术效率	0.870	0	0.00	13	4.53	274	95.47
规模效率	0.394	154	53.66	105	36.59	28	9.75

Economic efficiency of farmer participation in tourism-led village poverty alleviation：A case study of key poverty-stricken villages in the Qinling-Daba Mountains

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自变量	回归系数	标准误差	Z值	显著性水平
C	0.342784***	0.082361	4.161944	0.0000
水平分化（X₁）	0.071327*	0.036439	1.957411	0.0503
垂直分化（X₂）	0.063215*	0.035316	-1.790006	0.0735
户主年龄（X₃）	-0.001826*	0.000942	-1.938414	0.0526
户主非农就业技能（X₄）	0.03371*	0.019559	1.723536	0.0848
户主受教育程度（X₅）	-0.002875	0.011624	-0.247342	0.8046
旅游开发征地（X₆）	0.004655	0.020991	0.221777	0.8245
房子与景区距离（X₇）	0.006743	0.013266	0.508322	0.6112
家庭生产结构（X₈）	0.000001***	0.000000	5.428232	0.0000
旅游开发参与度（X₉）	-0.004571	0.006748	-0.677338	0.4982
农户社区属性认知（X₁₀）	-0.020199	0.019466	-1.037648	0.2994
政府惠农补贴（X₁₁）	0.000000	0.000002	0.278936	0.7803

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分组	irs（递增）	-（不变）	drs（递减）
样本数	281	5	1
百分比/%	97.91	1.74	0.35