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Vulnerability of the Ecological Agricultural Product Industry Chain under Digital Technology Empowerment: Archetype Analysis and Resilience Governance
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Cuixia WANG1, Tao HU1, Yaqin LI1, Xiong DING2
Smart Agriculture | 2026, 8(4) : 255 - 267
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Smart Agriculture | 2026, 8(4): 255-267
• Digital Economy •
Vulnerability of the Ecological Agricultural Product Industry Chain under Digital Technology Empowerment: Archetype Analysis and Resilience Governance
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Cuixia WANG1, Tao HU1, Yaqin LI1, Xiong DING2
Affiliations
  • 1.School of Information Management and Mathematics, Jiangxi University of Finance and Economics, Nanchang 330032, China
  • 2.School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang 330032, China
  • WANG Cuixia, E-mail:

About Author:

WANG Cuixia, E-mail:

Published: 2026-07-30 doi: 10.12133/j.smartag.SA202604024
Outline
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[Objective] The ecological agricultural product industry chain is subject to deep-seated vulnerabilities during scale expansion, quality improvement, and premium growth, yet its structural roots remain inadequately understood. Although digital technologies are expected to relieve these vulnerabilities, recent evidence suggests that digitalization may also induce new suppression loops, resulting in smallholder exclusion, profit squeeze, and homogenized competition. Existing studies have largely addressed this subject from isolated perspectives such as brand governance, industrial chain resilience, or policy evaluation, without offering a systematic diagnosis of the evolutionary mechanism of vulnerability. The aim of this study is to identify the operational logic of growth ceiling archetypes under digital empowerment, exploring how digital technologies interact with feedback structures, and proposing resilience governance strategies that move beyond "technological fixes". [Methods] The Limits to Growth archetype was employed as the analytical framework. Variable selection followed a three-stage procedure integrating theoretical deduction, bibliometric analysis, and case validation. First, constraining factors were identified across multiple dimensions, including natural resource endowment, ecological carrying capacity, market saturation, and trust thresholds, grounded on the theoretical proposition that growth processes endogenously activate restraining forces. Second, a systematic literature search was conducted using search terms such as ecological agriculture, agricultural product industry chain, and system dynamics. Candidate variables that appeared with high frequency in relevant empirical studies were screened, yielding an initial pool of over 20 variables. Third, field investigations of typical cases such as Gannan navel orange, Wuchang rice, and Hengzhou digital jasmine were performed to test, consolidate, and refine the initial pool, ultimately producing 14 core variables. Causal linkages among these variables were established upon three forms of evidence, namely theoretical logic derived from established economic principles, literature evidence drawn from prior empirical findings, and case facts observed during field investigations. Loop polarities were determined by the parity of negative causal chains, where even numbers indicate reinforcing loops (R) and odd numbers indicating balancing loops (B). On this basis, and in combination with field data from the typical cases, four reinforcing loops that drive growth and seven balancing loops that constrain growth were identified. The moderating effects of three categories of digital tools, namely digital agricultural technology platforms, quality traceability systems, and e-commerce platforms, on these loops were then separately assessed. [Results and Discussions] The results indicated that the sustained growth of the ecological agricultural product industry chain was underpinned by four positive feedback loops: the scale-income loop, the quality-demand loop, the premium-income loop, and the quality-reputation loop. At the same time, however, the growth process activated seven negative feedback loops that imposed constraints from multiple directions, including cost erosion, quality dispersion, market saturation, homogenized competition, low-price substitute diversion, trust erosion, and reputation damage—thus locking the system into three types of Limits to Growth dilemmas relating to scale expansion, quality improvement, and premium growth. Digital technology empowerment enhanced the operational efficiency of the industrial chain by reinforcing the positive loops and weakening the negative ones, yet it failed to remove the structural roots of the growth ceiling. More importantly, digitalization unexpectedly triggered three new suppression loops, namely the smallholder exclusion loop, driven by digital and certification barriers, illustrated by the Hengzhou digital jasmine case where elderly flower farmers were marginalized due to the digital divide; the profit squeeze loop, driven by platform cost transference, as shown in the Shanghai Hema village cooperative case, where high equipment costs and loss rates eroded profit margins; and the homogenized competition loop, driven by standardization orientation, as evidenced in the Gannan navel orange case where farmers abandoned flavor-differentiated production practices to comply with platform specifications. These three loops respectively weakened the operational foundations of the scale-income, premium-income, and quality-reputation loops, thereby shifting the locus of vulnerability from traditional constraints to digitally-induced risks. These findings revealed a dual effect of digital technology empowerment, as mitigating certain existing constraints, digital technologies may simultaneously generate new vulnerabilities through digital divides, cost transference, and standardization pressures. The essential task for resilience governance, therefore, lay in identifying and intervening in the dominant balancing loops that constrains growth, rather than relying exclusively on technological inputs. [Conclusions] First, the three limits to growth archetypes, namely scale expansion, quality improvement, and premium growth, constitute the shared structural roots of vulnerability in the ecological agricultural product industry chain. Second, digital technology empowerment cannot eradicate these structural roots and may give rise to new vulnerabilities. Third, enhancing industrial chain resilience should be grounded in leverage point interventions derived from the system's feedback structure. Corresponding governance strategies for the three types of newly identified risks, namely smallholder exclusion, profit squeeze, and homogenized competition, should include lowering technological entry barriers, establishing benefit-sharing mechanisms, and strengthening differentiated certification and geographical indication protection. Overall, this study provides a system dynamics-based analytical tool and policy leverage points for resilience governance of the ecological agricultural product industry chain in the context of digital technology empowerment.

ecological agricultural products  /  digital technology  /  vulnerability  /  limits to growth archetype  /  resilient governance  /  system dynamics  /  industry chain resilience
王翠霞, 胡涛, 李雅琴, 丁雄. 数字技术赋能下生态农产品产业链脆弱性的基模分析与韧性治理. 智慧农业(中英文), 2026 , 8 (4) : 255 -267 . DOI: 10.12133/j.smartag.SA202604024
Cuixia WANG, Tao HU, Yaqin LI, Xiong DING. Vulnerability of the Ecological Agricultural Product Industry Chain under Digital Technology Empowerment: Archetype Analysis and Resilience Governance[J]. Smart Agriculture, 2026 , 8 (4) : 255 -267 . DOI: 10.12133/j.smartag.SA202604024
  • National Natural Science Foundation of China(71961009, 72261013)
Year 2026 volume 8 Issue 4
168
82
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Article Info
doi: 10.12133/j.smartag.SA202604024
  • Receive Date:2026-04-16
  • Online Date:2026-10-16
  • Published:2026-07-30
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  • Received:2026-04-16
Funding
National Natural Science Foundation of China(71961009, 72261013)
Affiliations
    1.School of Information Management and Mathematics, Jiangxi University of Finance and Economics, Nanchang 330032, China
    2.School of Software and Internet of Things Engineering, Jiangxi University of Finance and Economics, Nanchang 330032, China

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HU Tao, E-mail:
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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