Understanding Farm Households’ Participation in Nong Jia Le in China

Tie Wang, Wei Wang, Zhongjun Wu, Ching-Hui Su and Ming-Hsiang Chen
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Tie Wang: Department of Tourism Management, School of Geography and Tourism, Research Center of Tourism Development and Planning, Qufu Normal University, Rizhao 276826, China
Wei Wang: School of Marketing, College of Business and Economic Development, The University of Southern Mississippi, Hattiesburg, MS 39406-0001, USA
Zhongjun Wu: College of Tourism and Landscape Architecture, Guilin University of Technology, Guilin 541006, China
Ching-Hui Su: Department of Apparel, Events, and Hospitality Management, College of Human Sciences, Iowa State University, Ames, IA 50011-1078, USA
Ming-Hsiang Chen: School of Hospitality Business Management, Carson College of Business, Washington State University, Pullman, WA 99164-4742, USA

Sustainability, 2019, vol. 11, issue 5, 1-18

Abstract: As the dominant form of rural tourism (RT) in China, Nong Jia Le (NJL) has made it possible for local farm households to benefit. In this article, a four-step strategy based on binary logistic regression was introduced to identify the most important factors influencing the participation of farm households in NJL. Next, a comparative study based on data from two NJL communities was conducted to test the approach and identify the most important influential factors as well as the differences. The results showed that the approach could identify the optimal model and the most influential factors in different rural communities. The comparative study indicated that for Pinglou Village, the most influential factors were “education years” and “gender ratio”, while in Baozi Village, the three most influential factors were “education years”, “consumption level”, and “land area”. Implications were put forward to improve the level of participation and hospitality of NJL.

Keywords: Nong Jia Le; farm household; binary logistic regression; influential factor (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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