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Asset specificity and farmers’ intergenerational succession willingness of apple management
ZHANG Qiang-qiang, GAO Xi-xi, Nazir Muhammad ABDULLAHI, WANG Yue, HUO Xue-xi
2023, 22 (8): 2553-2566.   DOI: 10.1016/j.jia.2023.04.016
Abstract153)      PDF in ScienceDirect      
Understanding the factors behind apple farmers’ willingness to pass on the management of their farms to their descendants is crucial to the continuity of apple production. Due to the high specificity of the human capital, physical assets, land assets, and geographical location in apple production, this study used a binary logistic regression and a mediating effect model to explore the impact of asset specificity on farmers’ intergenerational succession willingness of apple management (FISWAM) and to examine the mediating effects of loss aversion in the impact of asset specificity on the FISWAM. The results showed that about 18.68% of the respondents expressed willingness to transfer their apple business between generations, and the FISWAM was generally weak. In addition to the negative impact of geographical location specificity (GLS), human capital specificity (HCS), physical assets specificity (PAS), and land assets specificity (LAS) can enhance the FISWAM. Loss aversion plays a partial mediating role in the impact of PAS, LAS, and GLS on the FISWAM
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Technical efficiency of hybrid maize growers: A stochastic frontier model approach
Imad Ali, HUO Xue-xi, Imran Khan, Hashmat Ali, Khan Baz, Sufyan Ullah Khan
2019, 18 (10): 2408-2421.   DOI: 10.1016/S2095-3119(19)62743-7
Abstract158)      PDF in ScienceDirect      
This study investigated the effect of credit constraints and credit unconstraints on the technical efficiency of hybrid maize growers in the Khyber Pakhtunkhwa Province (KPK) of Pakistan. The primary data were collected by a direct elicitation method from 510 maize growers of KPK Province. Stochastic frontier model techniques were used for technical efficiency analyses. The results revealed that the mean technical efficiency difference between the two groups was 10.2%. The results of technical inefficiency effect modeling demonstrated that education of the household head, family size, number of married family members, off-farm income, farming experience, tractor drill, water irrigation through a lined course, certified seed, extension services, household saving variables, and a credit size variable had positive effects on technical efficiency for both credit constrained farmers (CCFs) and credit unconstrained farmers (UCCFs). In addition, age of household head and fragmented land values had negative effects on technical efficiency for both groups. However, the interest rate had positive and negative impacts on the technical efficiency of CCFs and UCCFs, respectively. Our results have significant implications for policies related to land use, interest rate, and banking sector expansion in the rural areas of Pakistan.
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