Stakeholders have become worried about the environmental problems of agricultural production activities. Therefore, there is pressure on smallholder farmers to observe environmental regulations and embed sustainable green technologies in their production. The literature on green production has thoroughly emphasized the critical role of behavioral factors in adopting environmental sustainability practices. We develop a probabilistic linguistic preference selection index method to assess the behavioral constructs that promote the adoption of agricultural green production technologies (AGPTs) among smallholder rice farmers in an emerging economy. The result shows that the five most-important factors promoting the adoption of AGPTs include knowledge (0.828), perceived cost and benefit (0.819), descriptive norm (0.810), moral and environmental concern (0.809), and injunctive norm (0.807). The study findings offer insightful directions for examining rice farmers’ decisions on the adoption of AGPTs. Our findings imply that policymakers should consider multiple behavioral factors when designing policies that promote AGPTs. This study enriches farmers’ adoption decisions by modeling the uncertainties in the decision-making process.

Farmland abandonment has become a significant challenge in global agriculture, with the issue being particularly severe in China. This phenomenon not only threatens food security but also contributes to various environmental problems. The rise of digital technology offers new opportunities to address this pressing issue. This study systematically analyzes the impact of digital technology on farmland abandonment from a micro-level perspective, using a nationwide survey of 3409 households. A multi-dimensional indicator framework is developed, incorporating digital general technology, digital information exchange, and digital functionality. Empirical models, including IV-Probit and 2SLS, were employed to analyze the data. The results show that digital technology plays a significant role in reducing farmland abandonment by increasing farmers’ income levels and encouraging the adoption of agricultural production services. Specifically, the use of digital tools enhances farmers’ income, which in turn strengthens their willingness to continue farming. Moreover, it facilitates access to agricultural production services, lowering production costs and improving land-use efficiency. The study also finds that the impact of digital technology on farmland abandonment varies depending on factors such as terrain, urban-rural divides, and farmer types. The suppressive effect of digital technology on farmland abandonment is more pronounced in non-plain areas, non-suburban regions, and among full-time or part-time farmers. Based on these findings, the study recommends expanding digital infrastructure, streamlining land transfers, implementing region-specific support, and enhancing policy incentives to integrate digital technologies with agriculture, reducing farmland abandonment. These measures are intended to effectively curb farmland abandonment and foster sustainable agricultural development.

This paper analyzes changes of the logistics development and economic growth from 1978 to 2007 in Sichuan Province. The paper develops a VAR (Vector Auto regression) model of logistics development and economic growth. In addition, this paper applies impulse response function and variance decomposition to portray the correlations between Development of Economic and Logistics. The results show that there exists a strong positive response between them. Therefore, under the current conditions accelerating pace of logistics is the fundamental approach choice to promote the economic development in Sichuan province.