Drivers and barriers to digital transformation in agriculture: An evolutionary game analysis based on the experience of China

IF 6.1 1区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Agricultural Systems Pub Date : 2024-09-19 DOI:10.1016/j.agsy.2024.104136

Yong Sun , Yiling Miao , Zhiju Xie , Runtian Wu

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Abstract

CONTEXT

The digital transformation of agriculture is a complex and dynamic process involving numerous stakeholders. Inadequate participation and collaboration from stakeholders are major factors contributing to the difficulties in agricultural digital transformation. However, there is a paucity of research that dynamically uncovers the driving forces and obstacles of agricultural digitization from the perspective of stakeholders.

OBJECTIVE

The purpose of this article is to systematically analyze the drivers and obstacles faced by government incentives, digital technology service providers, and agricultural operators in participating in the digital transformation of agriculture.

METHOD

This article employs evolutionary game theory to construct a model of the game between digital technology service providers and agricultural operators under the exogenous influence of the government. It also conducts stable strategy analysis and numerical simulation to explain and predict the behaviors and interaction mechanisms among multiple stakeholders in the digital transformation of agriculture.

RESULTS AND CONCLUSIONS

Our analysis reveals four potential equilibrium points under specific conditions, identifying that the increase in returns and the opportunity costs of not participating in agricultural digital transformation are key driving factors. Critical barriers include the high costs faced by digital technology service providers and agricultural operators, as well as the associated risks of non-participation. Government incentives emerge as a crucial exogenous factor in promoting agricultural digital transformation. To better facilitate this process, we propose policy recommendations and management insights.

SIGNIFICANCE

This study provides a new research perspective and methodology for agricultural digital transformation, offering a more comprehensive reflection of the complexity and multidimensionality of the driving and barrier factors influencing this process. It also provides theoretical support for explaining phenomena such as irrational behavior, multiple equilibria, and path dependence that exist in agricultural digital transformation.

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农业数字化转型的驱动力和障碍：基于中国经验的演化博弈分析

背景农业数字化转型是一个复杂而动态的过程，涉及众多利益相关者。利益相关者的参与和合作不足是造成农业数字化转型困难的主要因素。本文旨在系统分析政府激励机制、数字技术服务提供商和农业经营者在参与农业数字化转型过程中所面临的驱动力和障碍。方法本文采用演化博弈理论，构建了政府外生影响下数字技术服务提供商与农业经营者之间的博弈模型，并进行了稳定策略分析和数值模拟。结果与结论我们的分析揭示了特定条件下的四个潜在均衡点，发现收益的增加和不参与农业数字化转型的机会成本是关键的驱动因素。关键障碍包括数字技术服务提供商和农业经营者面临的高成本以及不参与的相关风险。政府激励措施是促进农业数字化转型的关键外生因素。本研究为农业数字化转型提供了新的研究视角和方法，更全面地反映了影响这一过程的驱动因素和障碍因素的复杂性和多面性。它还为解释农业数字化转型中存在的非理性行为、多重均衡和路径依赖等现象提供了理论支持。

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来源期刊

Agricultural Systems 农林科学-农业综合

CiteScore

13.30

自引率

7.60%

发文量

174

审稿时长

30 days

期刊介绍： Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments. The scope includes the development and application of systems analysis methodologies in the following areas: Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making; The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment; Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems; Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.