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Systems, Volume 14, Issue 10 (October 2026) – 6 articles

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40 pages, 949 KB

Open AccessArticle

How Generative Artificial Intelligence Stimulates Technological Innovation in Biopharmaceutical Enterprises: Evidence from Chinese A-Share Listed Companies Around the Release of ChatGPT

by Yuan Tian, Nuoyan Li, Mo Li and Chengming Li

Systems 2026, 14(10), 1197; https://doi.org/10.3390/systems14101197 (registering DOI) - 22 Sep 2026

Abstract

This study examines whether and how generative artificial intelligence (AI) stimulates technological innovation in biopharmaceutical enterprises. We define the generative AI shock using the public release of ChatGPT in November 2022 and an unbalanced panel of 2002 firm-year observations for Chinese A-share listed biopharmaceutical firms from 2017 to 2024. We construct a firm-level pre-shock AI exposure index from 2021 annual reports and combine high versus low exposure with a post indicator for 2022–2024 in a difference-in-differences framework. Results show that firms with greater pre-shock AI exposure experience significantly stronger increases in invention patent output, with the findings remaining robust across alternative specifications, sample restrictions, treatment-timing definitions, and firm-level clustered inference. According to the mechanism analyses, generative AI promotes innovation through stronger resource acquisition, greater specialisation and focus, and increased external collaboration. Heterogeneity tests show that effects vary across resource endowments, organisational capabilities, and innovation conditions. Further analyses reveal improvements in innovation quality and technological search breadth, with stronger marginal gains among firms with weaker accumulated knowledge. These findings show how the release of ChatGPT, as a generative AI shock, can reshape innovation in a knowledge-intensive and high-uncertainty industry. Full article

51 pages, 1583 KB

Open AccessArticle

Two-Stage Pre-Sale Financing Strategy for Agricultural Products Supply Chain Considering Capital Constraints

by Yuxiu Liang and Lindu Zhao

Systems 2026, 14(10), 1196; https://doi.org/10.3390/systems14101196 - 22 Sep 2026

Abstract

In the agricultural production cycle, farmers face financial constraints both before planting and before harvesting, which can substantially restrict production decisions and operational efficiency. With the rapid development of agricultural e-commerce and supply chain finance, platform loans and pre-sale financing have become important channels through which farmers can obtain the funds needed for agricultural production. This study develops a two-stage financing portfolio decision model for an agricultural product supply chain and examines the farmer’s optimal financing strategy, planting quantity, and pricing decisions under exogenously given platform loan and pre-sale financing conditions. The results show that the loan interest rate and commission rate significantly influence the farmer’s choice of financing strategy. Specifically, holding other conditions constant, a higher loan interest rate increases the farmer’s incentive to adopt pre-sale financing, whereas a higher commission rate reduces the incentive to adopt it. Numerical simulations further identify the decision boundaries of the two-stage financing portfolio strategies under different parameter conditions. This study provides theoretical insights into farmers’ financing decisions and the selection of multi-stage financing strategies in agricultural product supply chains. Full article

(This article belongs to the Special Issue Optimization and Decision Analytics in Supply Chain Management)

20 pages, 10057 KB

Open AccessArticle

Complex Network Analysis Reveals Associations Between Physical Activity and Knee Arthroplasty Burden Across Brazilian State Capitals (2009–2023)

by Fabiola Socorro Silva Lisboa, Ivan Gustavo Masselli dos Reis, Luana Alves Silva, Pedro Paulo Menezes Scariot and Leonardo Henrique Dalcheco Messias

Systems 2026, 14(10), 1195; https://doi.org/10.3390/systems14101195 (registering DOI) - 22 Sep 2026

Abstract

Background: Total knee arthroplasty (TKA) is one of the most frequently performed procedures for advanced knee osteoarthritis. Demographic, cardiometabolic, behavioral, and socioeconomic factors may be associated with TKA demand and hospital outcomes, but these indicators are often investigated separately. Objective: To investigate the structural relationships between population-level indicators and major TKA hospital outcomes across Brazilian state capitals using complex network analysis. Methods: An ecological study was conducted using data from the Brazilian Unified Health System (SUS) and the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey (VIGITEL) between 2009 and 2023. Variables were residualized for state-capital and calendar-year effects, and undirected weighted correlation networks were constructed using FDR-retained Pearson correlations. Targeted eigenvector centrality was used to characterize the structural position of variables relative to hospital outcomes. Results: In the primary hospitalization network, physical activity frequency of 3–4 days/week showed the highest targeted eigenvector centrality (0.466) and the only FDR-retained direct association with hospitalization rates. In the primary cost network, hypertension (0.484), diabetes mellitus (0.457), and mean age (0.443) showed the highest centralities, while mean age showed the only FDR-retained direct association with cost. However, these direct associations were retained after FDR correction in only 58.7% and 52.3% of cluster-bootstrap replicates, respectively, and their 95% bootstrap confidence intervals included zero. The hospitalization association was also sensitive to alternative representations of exercise-frequency composition. Centrality rankings also showed only moderate resampling stability. No direct FDR-retained association was observed for hospital length of stay. Conclusions: TKA-related hospital outcomes were characterized by distinct population-level correlation structures, although the bootstrap analysis indicated uncertainty in individual associations and centrality rankings. Network centrality reflects structural position rather than causal influence or independent association with hospital outcomes. Undirected weighted correlation networks may complement conventional epidemiological approaches by characterizing interdependencies and generating hypotheses for future longitudinal and individual-level studies. Full article

(This article belongs to the Special Issue Complex Adaptive Systems Approaches for Health and Well-Being)

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34 pages, 1673 KB

Open AccessArticle

Robustness of a POI-Derived Urban EV Charging-Station Network Under Capacity-Constrained Cascading Failures: A Scenario Analysis of Six Districts in Chengdu, China

by Yijun Zhou, Huawei Duan, Ying Liu, Yi Liu and Rouyue Wang

Systems 2026, 14(10), 1194; https://doi.org/10.3390/systems14101194 (registering DOI) - 22 Sep 2026

Abstract

Reliable public electric-vehicle charging depends on whether operating stations can absorb demand displaced by local outages. This study develops a reproducible scenario-analysis framework for a charging network derived from a POI snapshot spanning six Chengdu districts. The framework represents potential local substitution through a spatial proximity graph and simulates synchronous, capacity-constrained load redistribution while conserving displaced demand and recording unmet service. Using 648 retained station POIs, we compare random failures with centrality-targeted attacks across attack scales, capacity headroom, topology, load, and redistribution assumptions. The network combines dense, locally clustered central districts with a partially fragmented wider structure. The modelled served-load ratio remains comparatively high under limited random disruption but deteriorates nonlinearly as failures expand and spare capacity is depleted. Targeted outcomes vary across centrality measures and modelling assumptions, showing that structural prominence alone does not identify stations with the greatest service consequences. The framework therefore supports scenario screening for redundancy, substitution pathways, and candidate critical nodes, while station-level planning requires operational and behavioural validation. Full article

(This article belongs to the Section Systems Engineering)

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22 pages, 616 KB

Open AccessArticle

Digital Future Orientation, Digital Capability, Ecosystem Openness, Innovation Intensity, and International Orientation as Correlates of Sustainable Business Model Orientation and Digital–Sustainability Alignment: Evidence from Slovenia

by Barbara Bradač Hojnik

Systems 2026, 14(10), 1193; https://doi.org/10.3390/systems14101193 - 22 Sep 2026

Abstract

Digitalisation and sustainability are increasingly expected to reinforce one another, yet firm-level evidence does not justify treating their convergence as automatic. This study examines how digital future orientation, current digital capability, open ecosystem orientation, innovation intensity, and international orientation are associated with sustainable business model orientation (SBMO) among entrepreneurial and technology- and knowledge-intensive firms in Slovenia. A secondary analysis evaluates digital–sustainability alignment as a derived co-presence indicator rather than an independent latent construct. The study uses a 2025 organisational survey with 110 firms in the core sample and a common regression sample of 103 firms. OLS with HC3 standard errors is retained as a transparent benchmark; fractional-logit and ordered-logit models with Huber–White robust standard errors address the bounded, discrete, and zero-heavy outcome. Model 1 estimates focal associations, Model 2 adds firm-profile controls, and post-estimation contrasts test the comparative hypotheses. Open ecosystem orientation is the most stable result: it is positively associated with SBMO across all three model families, more strongly associated than internal innovation intensity, and positive across four alignment definitions. Digital future orientation is consistently positive but less precisely estimated, whereas current digital capability is not independently positively associated with SBMO. The evidence therefore supports a bounded open-systems interpretation: boundary-spanning ecosystem engagement and strategic direction are more closely associated with sustainability entering the business-model agenda than digital readiness alone, while alignment remains a derived co-presence property. Full article

(This article belongs to the Special Issue Sustainable Business Models and Digital Transformation)

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25 pages, 674 KB

Open AccessArticle

Organizational Risk Management Under Global Uncertainty: A Structural Equation Modeling Approach to Economic Security and Resilience

by Anamaria-Cătălina Radu, Alina-Cerasela Aluculesei, Maria-Roxana Cosma, Marina Bădileanu, Luminița-Izabell Georgescu, Cristinel Bălan and Ciprian-Crăciun Codău

Systems 2026, 14(10), 1192; https://doi.org/10.3390/systems14101192 - 22 Sep 2026

Abstract

Recent financial crises, heightened geopolitical instability, sustained financial volatility, and broader global uncertainty have increased the exposure of private sector organizations to emerging and interconnected economic risks. In this context, systematic and sustainable approaches to organizational risk management are becoming increasingly important for maintaining organizational resilience and economic security. Given the persistent instability of markets and the prospect of structural economic changes toward 2030, this study examines how key organizational and risk-related factors influence perceived economic security under crisis conditions. The empirical investigation was conducted on a sample of 205 employees from private sector organizations. Exploratory factor analysis (EFA) was used to validate the structure of the constructs, while structural equation modeling (SEM) was applied to test the relationships among the variables and provide a model-driven assessment of the determinants of perceived economic security. The findings show that all factors included in the proposed model have a significant influence on perceived economic security during periods of crisis. The results highlight the importance of systematic risk identification, assessment, monitoring, and management, as well as organizational learning from previous crises, in responding to a changing and uncertain economic environment. Under conditions of continued global uncertainty, volatility, and structural transformation, the development and continuous improvement of organizational risk management systems can strengthen organizational resilience and support economic security over time. Full article

(This article belongs to the Special Issue Risk Engineering in an Era of Global Uncertainty)

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