Smartphone use and willingness to adopt digital pest and disease management: Evidence from litchi growers in rural China

Abstract

This study uses a dataset covering 928 small litchi growers in southern China to investigate the determinants of farmers' willingness to adopt digital pest and disease management (DPDM), focusing on smartphone use.

Smartphone use, off‐farm employment, and women's decision‐making power: Evidence from rural China

“…A common drawback of IPW, AIPW, and PSM estimators is that they can only address the endogeneity issue associated with observed factors. Rural households decide to use ICTs on the basis of both observed factors (e.g., age, education experience, and household size) and unobserved heterogeneities (e.g., innate abilities and motivations) (Cai, Qi, & Yi, 2022; Min et al, 2020; Zheng & Ma, 2021). However, we are unaware of any research in this area that accounts for the selection bias arising from observed and unobserved heterogeneities.…”

Factors Affecting the Adoption of Digital Technology by Farmers in China: A Systematic Literature Review

“…Formal education attainment is found to correlate positively with the adoption of DATs, as digital technologies require knowledge-based skills and interpretation [30,32,35]. A couple of studies have found a significant impact of health status on the adoption of on-farm digital technologies [30,32]. Farming experience likewise has a positive impact on farmers' adoption.…”

“…As such, the farmers' capacities and knowledge clearly influence their adoption decision to use DATs. Various socioeconomic factors have been incorporated into analytical models as explanatory variables [30,32,[34][35][36]. Significant socioeconomic factors identified in the reviewed papers include age, gender, education level, health status, income (including total income and percentage of agricultural income), farming experience, and cooperative membership.…”

“…Female farmers, often serving as agricultural assistants and lacking resources, may be less likely to accept new technologies [37]. Formal education attainment is found to correlate positively with the adoption of DATs, as digital technologies require knowledge-based skills and interpretation [30,32,35]. A couple of studies have found a significant impact of health status on the adoption of on-farm digital technologies [30,32].…”

“…In contrast to the aforementioned socioeconomic factors, there is no consensus in the literature on the impact of household income. Total household income could have either a positive [32,35], negative [36], or no significant influence [30,37] on DAT adoption. In view of this mixed picture, the total household income does not lend itself to an easy indicator for adoptive decisions.…”