Systems

31 pages, 2027 KB

Open AccessArticle

How Does Digital–Physical Technological Integration Drive Corporate Green Innovation? The Role of Knowledge Integration Capability

by Wenyi Luo and Zongjun Wang

Systems 2026, 14(9), 1048; https://doi.org/10.3390/systems14091048 - 25 Aug 2026

Abstract

As interactions between digital and physical technologies intensify, understanding their implications for corporate green innovation has become increasingly important. Using panel data on Chinese A-share listed firms from 2008 to 2024, this study investigates the relationship between digital–physical technological integration and both the [...] Read more.

As interactions between digital and physical technologies intensify, understanding their implications for corporate green innovation has become increasingly important. Using panel data on Chinese A-share listed firms from 2008 to 2024, this study investigates the relationship between digital–physical technological integration and both the quantity and quality of green innovation while considering potential endogeneity concerns. The empirical evidence shows that firms with a higher degree of digital–physical technological integration tend to generate more green innovation outputs and achieve higher green innovation quality. Additional analyses show that digital–physical technological integration is positively associated with knowledge depth, knowledge breadth, receipt of general government support, and environmental information disclosure quality, providing evidence consistent with the proposed knowledge, resource, and information explanations. Heterogeneity analysis reveals that the relationship is more pronounced for digital product manufacturing and digital technology applications, and among larger, more mature, and less financially constrained firms. At the regional level, the relationship is stronger in regions with more advanced digital infrastructure, stronger intellectual property protection, and a more favourable business environment. This study advances current understanding of the relationship between digitalisation and green innovation and offers implications for designing differentiated innovation policies across firms and regions. Full article

(This article belongs to the Special Issue Economic System Management, Sustainability, and Innovation in Digital Environments)

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22 pages, 1874 KB

Open AccessArticle

How Risk Attitudes Shape Consumer Preferences: An Interpretable Learning Framework

by Xia Wu, Fumin Deng and Xuedong Liang

Systems 2026, 14(9), 1047; https://doi.org/10.3390/systems14091047 - 25 Aug 2026

Abstract

Consumers’ risk attitudes shape how they evaluate and trade off product attributes, yet most preference estimation approaches overlook risk attitudes, assuming risk neutrality. The resulting preference structures may fail to capture the heterogeneity essential for effective market segmentation and product strategy. We propose [...] Read more.

Consumers’ risk attitudes shape how they evaluate and trade off product attributes, yet most preference estimation approaches overlook risk attitudes, assuming risk neutrality. The resulting preference structures may fail to capture the heterogeneity essential for effective market segmentation and product strategy. We propose a risk-driven preference learning framework that reconceptualizes risk attitude as an integral factor shaping preference structures. Its core is a risk-contingent value function in which risk attitude determines how attributes are traded off. This function infers risk attitudes through deviations from full compensation among attributes under risk neutrality, endogenizing risk-attitude inference within preference estimation, and yields preference structures from behavioral data. The method also identifies distinct preference subtypes within the same risk-attitude category. Validated on 114,317 vehicle reviews from Edmunds, an automotive e-commerce platform, the approach achieves strong in-sample fit to behavioral data. Results show that risk-averse, risk-neutral, and risk-seeking consumers exhibit different preference structures, and the risk-averse group shows pronounced internal heterogeneity. The proposed framework offers a structurally interpretable tool for intelligent decision support in consumer segmentation and product strategies. Full article

(This article belongs to the Section Systems Practice in Social Science)

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36 pages, 2934 KB

Open AccessArticle

Three Decades of Energy Efficiency in Chile: Institutional Path Dependence and the Systemic Limits of Decoupling

by Axel Bastián Poque González and Ana Julieth Calderón Márquez

Systems 2026, 14(9), 1046; https://doi.org/10.3390/systems14091046 - 25 Aug 2026

Abstract

Energy efficiency (EE) is widely promoted as a climate-mitigation strategy, yet improvements in energy intensity emerge from interactions among institutions, technologies, economic structures, and environmental conditions and cannot be attributed to efficiency policies alone. This study examines the evolution of EE governance in [...] Read more.

Energy efficiency (EE) is widely promoted as a climate-mitigation strategy, yet improvements in energy intensity emerge from interactions among institutions, technologies, economic structures, and environmental conditions and cannot be attributed to efficiency policies alone. This study examines the evolution of EE governance in Chile between 1992 and 2022, treating national energy intensity as an emergent property of a path-dependent sociotechnical system. A two-component mixed-methods approach combines a historical-institutional reconstruction of governance with a parsimonious econometric analysis of short-run changes in energy intensity, integrated through a causal loop diagram. The historical analysis shows EE governance evolving through path dependence, critical junctures, layering, and policy feedback, strengthening state coordination without transforming the underlying market-oriented regime. Across four specifications, only carbon intensity is robustly associated with short-run changes in energy intensity; structural, extractive, and sociotechnical variables show no robust association. A comparison of the two strands reveals an asymmetry: the institutional trajectory coincided with aggregate change in the carbon–energy dimension, while no comparable short-run signature was detected along the direct demand-side routes examined. These findings reframe energy intensity as a system-level property and indicate that efficiency policies should be complemented by demand-side governance, structural change, and sufficiency to support sustainability transitions. Full article

(This article belongs to the Special Issue Systems Approaches to Sustainable Development)

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28 pages, 751 KB

Open AccessArticle

ESG Rating Divergence and Banks’ Loan Decision-Making Process: A Psychological Perspective

by Gaomiao Wang and Yonghai Wang

Systems 2026, 14(9), 1045; https://doi.org/10.3390/systems14091045 - 25 Aug 2026

Abstract

Using data from Chinese listed non-financial firms from 2015 to 2023, this study examines how environmental, social, and governance (ESG) rating divergence affects banks’ loan limit decisions and the underlying decision-making mechanisms within the sustainable finance system. Drawing on cognitive psychology, we conceptualize [...] Read more.

Using data from Chinese listed non-financial firms from 2015 to 2023, this study examines how environmental, social, and governance (ESG) rating divergence affects banks’ loan limit decisions and the underlying decision-making mechanisms within the sustainable finance system. Drawing on cognitive psychology, we conceptualize bank lending as an organizational decision-making process in which conflicting ESG signals create information ambiguity and influence banks’ risk assessments. Greater ESG rating divergence is associated with significantly lower total annual bank loan limits. Mechanism analyses provide evidence consistent with heightened bank concerns about firm default risk, whereas we find no supporting evidence for the information-quality channel captured by discretionary accruals. Further analysis reveals an asymmetric response to conflicting ESG information: banks appear to place greater weight on relatively unfavorable ESG ratings, while favorable ratings do not exert a comparable moderating effect. The negative association between ESG rating divergence and bank loan limits is more evident among non-state-owned enterprises, firms with weaker repayment capacity, firms with lower financial information disclosure quality, and firms without third-party ESG assurance. These findings extend the literature on ESG rating divergence and sustainable finance by showing how conflicting ESG information is associated with contractual credit allocation through banks’ risk assessment and asymmetric information-processing behavior. They also highlight the importance of improving ESG information governance and banks’ capacity to evaluate inconsistent sustainability signals. Full article

(This article belongs to the Section Systems Practice in Social Science)

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19 pages, 338 KB

Open AccessArticle

Beyond Aid Volumes: Multidimensional Aid Dependency, Institutional Quality and Economic Growth in Sub-Saharan Africa

by John Soko Bopape, Patricia Lindelwa Makoni and Jude Igyo Ali

Systems 2026, 14(9), 1044; https://doi.org/10.3390/systems14091044 - 24 Aug 2026

Abstract

Economic growth and the effectiveness of official development assistance (ODA) have long been a topic of debate, with the current concern being that there are high levels of aid dependency in Sub-Saharan Africa, despite low levels of structural transformation. The study analyses the [...] Read more.

Economic growth and the effectiveness of official development assistance (ODA) have long been a topic of debate, with the current concern being that there are high levels of aid dependency in Sub-Saharan Africa, despite low levels of structural transformation. The study analyses the growth impacts of multidimensional ODA dependency, the moderating effect of institutional quality and the possible thresholds of aid dependency in an unbalanced panel of 48 Sub-Saharan African countries over the period 2000–2025. Two-way fixed effects, System Generalized Method of Moments, Difference Generalized Method of Moments, and Common Correlated Effects Pooled are used to analyze a principal component-based ODA Dependency Index, and least-squares threshold regression is used to investigate multiple thresholds. These results show that there is a strong negative correlation between aid dependency and economic growth, while institutional quality is consistently positive to growth, but does not significantly moderate the aid–growth relationship. There are no stable thresholds for aid dependency as a function of the specification of the index. The findings highlight the need to improve domestic resource mobilization, productive investment and institutional capacity to decrease reliance on structural aid and ensure sustainable economic growth in the long term. Full article

(This article belongs to the Section Systems Practice in Social Science)

35 pages, 603 KB

Open AccessArticle

The Visibility Paradox: A Socio-Technical Systems Perspective on the Empowering and Surveillance Effects of Production Data Transparency in Smart Manufacturing

by Wenxi Guo, Haiyun Liu and Haiquan Chen

Systems 2026, 14(9), 1043; https://doi.org/10.3390/systems14091043 - 24 Aug 2026

Abstract

Production data transparency in smart manufacturing simultaneously enhances and impairs employee performance across organizational contexts. Existing research has not resolved this theoretical contradiction. Drawing on socio-technical systems theory, cognitive appraisal theory, and conservation of resources theory, this study develops a dual-pathway model. Data [...] Read more.

Production data transparency in smart manufacturing simultaneously enhances and impairs employee performance across organizational contexts. Existing research has not resolved this theoretical contradiction. Drawing on socio-technical systems theory, cognitive appraisal theory, and conservation of resources theory, this study develops a dual-pathway model. Data transparency influences adaptive performance through a bright empowerment pathway and a dark surveillance pathway mediated by EPM-induced strain. Procedural justice of data governance and digital self-efficacy operate as a perceived-institutional boundary condition and an individual-capability boundary condition, respectively. Latent moderated structural equations were applied to survey data from 412 employees in Chinese smart manufacturing enterprises. Results support both pathways and reveal a theoretically consequential asymmetry between these boundary conditions. Johnson–Neyman analysis indicates that institutional justice attenuates the strain pathway to non-significance within the observed distribution of responses. Conversely, digital self-efficacy requires near-ceiling levels to achieve the same pattern. This asymmetry indicates that continuous moderation produces sharply different practical outcomes across the observed data range. Institutional and individual remedies therefore address the visibility paradox on different practical scales. Governance adequacy represents a more attainable managerial lever than individual capability development. These findings advance socio-technical systems theory by detailing the asymmetric buffering capacities of different organizational resources. Full article

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22 pages, 986 KB

Open AccessArticle

Navigating Complexity of 3PL-Led Low-Carbon Supply Chains: A Two-Stage Dynamic Coordination Mechanism for Sustainability and Resilience Under Information Asymmetry

by Jinde Jiang, Junding Yang, Wenping Liu, Yingjing Gu, Jing Gu and Yiling Zhu

Systems 2026, 14(9), 1042; https://doi.org/10.3390/systems14091042 - 24 Aug 2026

Abstract

To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This [...] Read more.

To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation. Full article

(This article belongs to the Special Issue Navigating Complexity in a Changing World: Challenges and Opportunities for Sustainable and Resilient Supply Chains)

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34 pages, 10376 KB

Open AccessArticle

An MBSE-Driven Digital Twin Framework with Semantic Enhancement for Cross-Phase Collaborative Management in Complex Product Systems

by Zhu Xiang, Minghao Li, Tianyang Lei, Kewei Yang, Guopeng Song and Jiang Jiang

Systems 2026, 14(9), 1041; https://doi.org/10.3390/systems14091041 - 24 Aug 2026

Abstract

Cross-phase collaborative management in complex product systems (CoPS) development is inherently challenged by heterogeneous organizational coupling and stochastic disturbances. Although digital twin (DT) and model-based systems engineering (MBSE) technologies provide foundations for physical–virtual synchronization and model traceability, existing approaches remain fragmented in three [...] Read more.

Cross-phase collaborative management in complex product systems (CoPS) development is inherently challenged by heterogeneous organizational coupling and stochastic disturbances. Although digital twin (DT) and model-based systems engineering (MBSE) technologies provide foundations for physical–virtual synchronization and model traceability, existing approaches remain fragmented in three respects: insufficient requirements-traceable architectural integration, limited cross-phase semantic interoperability and runtime evolution, and weak operational links between semantic reasoning and adaptive decision models. To address these gaps, this paper proposes an MBSE-driven digital twin framework with semantic enhancement. First, a four-layer architecture is derived using the MagicGrid methodology, encompassing physical–virtual mapping, semantic reasoning, decision support, and service interaction. Second, a collaboration-oriented SysML profile is developed to standardize the representation of tasks, resources, materials, disturbances, and management constraints across engineering phases. Third, a knowledge-driven adaptive collaboration mechanism maps runtime disturbance inputs into semantic states, propagates their cross-phase impacts, supports process-topology reconfiguration, and generates decision-ready constraints for adaptive management. A case-based prototype for aero-engine turbofan blade development demonstrates the feasibility of the mapping–reasoning–decision chain and provides case-level evidence of improved cross-phase coordination under controlled disturbance scenarios. The results indicate a feasible engineering pathway from perceptive DT functions toward reasoning-enabled collaborative decision support. Full article

(This article belongs to the Special Issue Advancing Digital Engineering: Transforming Industries with Model-Based Systems Engineering and Digital Twin Technology)

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26 pages, 3316 KB

Open AccessArticle

A Multi-Source Data Fusion Framework for Emerging Technology Topic Identification: Integrating Publications, Patents, and GitHub Open-Source Data

by Ge Wang and Ruoxi Wu

Systems 2026, 14(9), 1040; https://doi.org/10.3390/systems14091040 - 24 Aug 2026

Abstract

Emerging technology topic identification is an important research task in the field of scientific and technological intelligence. To achieve a more comprehensive identification of emerging technology topics, this study proposes a multi-source data fusion framework that integrates three types of data sources: academic [...] Read more.

Emerging technology topic identification is an important research task in the field of scientific and technological intelligence. To achieve a more comprehensive identification of emerging technology topics, this study proposes a multi-source data fusion framework that integrates three types of data sources: academic publications, patent data, and data from the GitHub open-source platform. In addition, an evaluation indicator system is constructed from four dimensions: growth, novelty, continuity, and impact. During the identification process, the BERTopic topic modeling approach is employed to uncover latent topics within the data, while the entropy weight method is applied for objective weighting, ultimately enabling the identification of emerging technology topics. The results indicate that the identified emerging technology topics include, but are not limited to, large language model-driven intelligent interaction, embodied intelligence perception, context memory management, and multimodal generation. Among the data sources, GitHub data provide earlier signals of technological evolution. Incorporating open-source platform data into the framework can effectively alleviate the lagging issues associated with traditional data sources. The proposed framework provides a more comprehensive research perspective for emerging technology topic identification. Full article

(This article belongs to the Section Artificial Intelligence and Digital Systems Engineering)

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33 pages, 2236 KB

Open AccessArticle

T-Spherical Fuzzy-Valued Neutrosophic MEREC-EDAS Framework for Evaluating Low-Carbon Cooling and Energy Management Technologies for Data Centers

by Nhat-Luong Nhieu and Hoang-Kha Nguyen

Systems 2026, 14(9), 1039; https://doi.org/10.3390/systems14091039 - 24 Aug 2026

Abstract

Fuzzy multi-criteria decision-making is important for technology assessment when expert judgments contain uncertainty, hesitation, and inconsistent evidence. This study develops a T-Spherical Fuzzy-Valued Neutrosophic Set (T-SFVNS)-based MEREC-EDAS framework for evaluating low-carbon cooling and energy-management technologies for data centers. Expert linguistic assessments are represented [...] Read more.

Fuzzy multi-criteria decision-making is important for technology assessment when expert judgments contain uncertainty, hesitation, and inconsistent evidence. This study develops a T-Spherical Fuzzy-Valued Neutrosophic Set (T-SFVNS)-based MEREC-EDAS framework for evaluating low-carbon cooling and energy-management technologies for data centers. Expert linguistic assessments are represented by T-Spherical Fuzzy-Valued Neutrosophic Numbers and aggregated before a score function is used at the explicit scalarization boundary. Standard MEREC then derives objective criterion weights from criterion-removal effects, and standard EDAS ranks alternatives by their positive and negative distances from the average score profile. The application evaluates nine technologies against ten criteria using assessments from thirty domain specialists. The corrected MEREC calculation assigns the greatest weights to carbon reduction potential (0.127), electricity demand reduction (0.125), maintenance complexity (0.124), operational cost efficiency (0.123), and cooling efficiency (0.123). The final ranking is Direct-to-Chip Liquid Cooling, Liquid Immersion Cooling, AI-Enabled Energy Management, Water-Side Free Cooling, Free-Air Cooling, Rear-Door Heat Exchanger Cooling, Hot/Cold Aisle Containment, Renewable-Powered Cooling, and Thermal Storage-Assisted Cooling. Weight perturbation, q-parameter, leave-one-expert-out, alternative-deletion, dominated-alternative, and multi-method comparisons show that the leading tier is robust, although the exact order of the two liquid-cooling technologies is sensitive in some scenarios. The findings provide a transparent and reproducible decision-support basis while explicitly acknowledging the information compression and rank-reversal limitations of score-based MCDM. Full article

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36 pages, 636 KB

Open AccessArticle

From Traceability to Closed-Loop Accountability: A Stackelberg Model of Evidence Quality and Recycling Compliance for Emerging Electric-Vehicle Battery Digital Identity Governance

by Yongjing Chen, Xin Liang, Xinrui Xu and Chuyan Cao

Systems 2026, 14(9), 1038; https://doi.org/10.3390/systems14091038 - 23 Aug 2026

Abstract

Digital identity and battery-passport systems can make electric-vehicle battery lifecycle records traceable, but traceability alone does not guarantee verifiable evidence or physical recycling compliance. We develop a normative two-stage Stackelberg model in which a regulator chooses audit intensity and verified incentives and a [...] Read more.

Digital identity and battery-passport systems can make electric-vehicle battery lifecycle records traceable, but traceability alone does not guarantee verifiable evidence or physical recycling compliance. We develop a normative two-stage Stackelberg model in which a regulator chooses audit intensity and verified incentives and a representative obligated firm jointly chooses pre-verification evidence quality and recycling compliance. The benchmark is stress-tested under reduced eligibility-confirmation effectiveness, alternative evidence–recycling interaction, decentralized manufacturer–recycler decisions, and implementation costs. Baseline traceability can leave evidence quality at the reporting floor and compliance incomplete, while additional responsibility exposure can conditionally increase recycling compliance while reducing evidence quality. Coordinated verified incentives improve both decisions and welfare in the benchmark complementarity domain. At zero eligibility-confirmation effectiveness, the fixed positive-rate package can become marginally welfare-inferior under finite capacity; adverse interaction can reverse a cross-effect, decentralization creates coordination underinvestment, and high payment or startup costs create single- or no-positive-payment regions. The model is therefore a forward-looking governance analysis rather than an empirical evaluation or legal calibration of current Chinese or European Union rules. Full article

(This article belongs to the Section Supply Chain Management)

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33 pages, 10482 KB

Open AccessArticle

Battery Swapping Stations for Grid Peak Shaving Under Virtual Power Plant Aggregation: A Complex-Network Evolutionary Diffusion Analysis

by Feifan Li, Qiuting Li and Ying Li

Systems 2026, 14(9), 1037; https://doi.org/10.3390/systems14091037 - 23 Aug 2026

Abstract

The rapid growth of distributed renewable generation and electric vehicles has increased the demand for flexible peak-shaving resources. Battery swapping stations (BSSs), which centrally manage standardized batteries under the battery-as-a-service model, can provide station-to-grid (S2G) services when aggregated by virtual power plants (VPPs). [...] Read more.

The rapid growth of distributed renewable generation and electric vehicles has increased the demand for flexible peak-shaving resources. Battery swapping stations (BSSs), which centrally manage standardized batteries under the battery-as-a-service model, can provide station-to-grid (S2G) services when aggregated by virtual power plants (VPPs). However, S2G adoption is influenced by contract design, market returns, subsidies, battery degradation, and heterogeneous consumer attitudes. This study develops a complex-network evolutionary diffusion model for VPP–BSS cooperation. The framework integrates a VPP profit-accounting module, a segmented Hotelling demand model, and an evolutionary game on a Newman–Watts small-world network. BSS strategies are updated through a partial asynchronous Fermi rule to reflect bounded rationality and investment inertia. Numerical simulations examine contract parameters, subsidy policies, consumer structures, exogenous variables, and network characteristics. The results show that S2G adoption follows an S-shaped trajectory but does not automatically reach full penetration. Successful diffusion requires a feasible combination of electricity prices, revenue sharing, settlement mechanisms, subsidies, consumer acceptance, and available battery capacity. The findings also reveal a trade-off between promoting BSS participation and maintaining VPP profitability, while robustness tests confirm the stability of the main conclusions. Full article

(This article belongs to the Section Complex Systems and Cybernetics)

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23 pages, 1053 KB

Open AccessArticle

Artificial Intelligence-Based Assessment of Real Estate Investment Strategies in the Context of Macroeconomic and Structural Factors

by Laima Okunevičiūtė Neverauskienė and Dominykas Linkevičius

Systems 2026, 14(9), 1036; https://doi.org/10.3390/systems14091036 - 22 Aug 2026

Abstract

Real estate investment decisions are shaped by a complex environment of macroeconomic, demographic, and structural factors, where traditional linear assessment methods often fail to capture nonlinear relationships influencing aggregate housing market performance. The aim of this article is to develop a data-driven artificial [...] Read more.

Real estate investment decisions are shaped by a complex environment of macroeconomic, demographic, and structural factors, where traditional linear assessment methods often fail to capture nonlinear relationships influencing aggregate housing market performance. The aim of this article is to develop a data-driven artificial intelligence framework for assessing how macroeconomic and structural conditions influence aggregate housing market performance and for providing a conceptual basis for evaluating real estate investment strategies under different economic contexts. The study uses machine learning algorithms that allow for modeling complex relationships between investment return indicators and key macroeconomic factors, such as economic growth rates, price dynamics, population concentration, and long-term structural changes. Unlike traditional econometric methods, the proposed approach identifies nonlinear and regime-dependent relationships between macroeconomic conditions and housing market performance, providing insights that can support the interpretation of different investment strategies. The results show that the factors determining investment returns are not universal, and their significance depends on the broader economic regime and market structure. This allows us to examine how changing macroeconomic conditions influence aggregate housing market performance and to discuss the potential implications for different investment strategies. The study contributes by proposing an artificial intelligence-based methodological framework that combines predictive modelling with explainable AI to support the analysis of macroeconomic influences on housing markets and to inform strategic real estate investment decision-making within complex socioeconomic systems. Full article

(This article belongs to the Special Issue Systems Thinking and Modelling in Socio-Economic Systems)

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21 pages, 458 KB

Open AccessArticle

A Systems-Based Superior–Committee Group Decision-Support Method Under Linguistic Intuitionistic Fuzzy Uncertainty

by Yuantao Liu and Fei Gao

Systems 2026, 14(9), 1035; https://doi.org/10.3390/systems14091035 - 22 Aug 2026

Abstract

Decision-making in organizational and socio-technical systems often involves a responsible superior expert who must integrate committee judgments expressed under linguistic uncertainty, hesitation, and heterogeneous expertise. This paper proposes a systems-based superior–committee group decision-support method for criteria weighting under linguistic intuitionistic fuzzy uncertainty. First, [...] Read more.

Decision-making in organizational and socio-technical systems often involves a responsible superior expert who must integrate committee judgments expressed under linguistic uncertainty, hesitation, and heterogeneous expertise. This paper proposes a systems-based superior–committee group decision-support method for criteria weighting under linguistic intuitionistic fuzzy uncertainty. First, the best–worst method is extended by using linguistic intuitionistic fuzzy numbers to represent pairwise preference information with linguistic membership, non-membership, and indeterminacy degrees. A utility transformation is then introduced to convert linguistic intuitionistic fuzzy comparisons into numerical preference values, enabling criteria weights to be derived through linear programming models. Second, a two-stage group decision-support framework is developed for superior–committee decision structures. In the first stage, committee expert influence is calculated by integrating prior expert weights obtained from the superior expert’s evaluation with judgment-derived expert weights based on certainty and agreement. In the second stage, the final criteria weights are obtained by combining the superior expert’s judgments with the weighted committee judgments. A constructed UAV criteria-weighting case and complementary numerical analyses are presented to illustrate the calculation process and examine the behavior of the proposed method. The results show that the framework provides a transparent mechanism for representing uncertain preferences, assigning expert influence, and deriving interpretable criteria weights in superior–committee group decision systems. Full article

(This article belongs to the Special Issue Decision Making in Uncertain Environments via Advanced Analytical Methods: Second Edition)

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38 pages, 10356 KB

Open AccessArticle

When Do Competing New Energy Vehicle Manufacturers Cooperate Under Supply Disruption Risk? Emergency Procurement, Conversion Costs, and Market Outcomes

by Beile Feng, Wentao Zhan, Chencan Lin, Peilun Sun, Yitong Zhao and Minghui Jiang

Systems 2026, 14(8), 1034; https://doi.org/10.3390/systems14081034 - 21 Aug 2026

Abstract

Amid increasing upstream raw-material disruptions and battery supply uncertainty, NEV manufacturers may obtain emergency supply from vertically integrated competitors after a disruption, but must incur technology conversion costs. We develop a differentiated Cournot duopoly model with an outsourcing manufacturer and an integrated manufacturer [...] Read more.

Amid increasing upstream raw-material disruptions and battery supply uncertainty, NEV manufacturers may obtain emergency supply from vertically integrated competitors after a disruption, but must incur technology conversion costs. We develop a differentiated Cournot duopoly model with an outsourcing manufacturer and an integrated manufacturer to compare equilibrium, profit, and welfare outcomes with and without emergency procurement cooperation. The results show that cooperation has a clear feasibility boundary jointly determined by market potential, relative costs, and conversion costs, giving rise to competition-only, cooperation-only, and coopetition regimes. The cooperation option reshapes pre-disruption quantity decisions: the outsourcing manufacturer increases regular procurement, while the integrated manufacturer reduces its own-brand output by a larger amount. Within the cooperation region, higher conversion costs continuously reduce the outsourcing manufacturer’s profit, whereas the integrated manufacturer’s profit can be U-shaped. Greater product substitutability makes cooperation more fragile and widens the divergence between private profit incentives and supply-chain resilience. Consumer surplus and social welfare may also move in different directions, depending on the outsourcing manufacturer’s benchmark market share and conversion cost. A Nash-bargaining extension confirms the robustness of the activation condition and pre-disruption quantity-adjustment mechanism, while reducing emergency markups and improving consumer surplus. Full article

(This article belongs to the Section Supply Chain Management)

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26 pages, 6091 KB

Open AccessArticle

Evaluation of Green Strategies for Inland Vessels and Government Subsidy Policies by Evolutionary Game Model

by Yong-Bo Ji, De-Chang Li, Wei Song, Yi Luo, Li-Peng Wang, Da-Zhuang Liu, Kun Li, Fang-Fang Jiao and Hua-Long Yang

Systems 2026, 14(8), 1033; https://doi.org/10.3390/systems14081033 - 21 Aug 2026

Abstract

Environmental sustainability has become an increasingly critical issue in the inland shipping sector. The adoption of green-fuelled vessels, data-driven speed optimization enabled by digital and intelligent technologies, and the use of shore power during berthing can substantially reduce harmful emissions from shipping activities [...] Read more.

Environmental sustainability has become an increasingly critical issue in the inland shipping sector. The adoption of green-fuelled vessels, data-driven speed optimization enabled by digital and intelligent technologies, and the use of shore power during berthing can substantially reduce harmful emissions from shipping activities and enhance environmental performance. This study investigates the evolutionary stable strategy (ESS) of inland shipowners’ green initiatives under government subsidy schemes. Firstly, a decision-making framework is developed by incorporating price elasticity, market competition, green investment, and subsidy intensity, through which pricing, subsidies, demand, and profit decisions are jointly modeled. Secondly, a game-theoretic model involving two market participants under three alternative strategies is constructed, together with an effective solution approach. Thirdly, based on evolutionary game theory, the equilibrium strategies ultimately adopted by the majority of inland shipowners are derived, and sensitivity analyses of key parameters are conducted. The results indicate that: (1) shipowners implementing green strategies can achieve higher economic returns, and green strategies are expected to be adopted by approximately 71.55% of inland shipowners in the long-term; (2) governments should increase subsidy intensity in the early stage of green strategy development, while gradually reducing subsidies once the market reaches a stable equilibrium. The findings provide theoretical insights for inland shipowners’ strategic decisions in environmentally conscious markets and offer policy implications for governments seeking to design stable and effective subsidy mechanisms to promote the green transition of inland shipping services. Full article

(This article belongs to the Section Supply Chain Management)

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21 pages, 444 KB

Open AccessArticle

How Digital Orientation Promotes Technology Standard Innovation: The Serial Mediating Role of Organizational Unlearning and Knowledge Re-Orchestration

by Hong Jiang, Chen Chen and Ye Yuan

Systems 2026, 14(8), 1032; https://doi.org/10.3390/systems14081032 - 21 Aug 2026

Abstract

Against the backdrop of digital transformation, enterprises take digital orientation as a strategic foundation and compete for standard-setting authority to gain core competitive advantages. Although prior research indicates that digital orientation positively influences innovation, research on how digital orientation affects technology standard innovation [...] Read more.

Against the backdrop of digital transformation, enterprises take digital orientation as a strategic foundation and compete for standard-setting authority to gain core competitive advantages. Although prior research indicates that digital orientation positively influences innovation, research on how digital orientation affects technology standard innovation remains limited. Technology standard innovation under digital practices is more complex and knowledge-intensive than that in the traditional industrial era. The mechanism by which digital orientation drives technology standard innovation requires more attention. Drawing upon strategic management theory and resource orchestration theory, this study proposes a serial mediation model to reveal how digital orientation influences technology standard innovation. We collected survey data from 480 Chinese enterprises via questionnaires and tested the model using partial least squares structural equation modeling. The results indicated that digital orientation has a significant positive impact on technology standard innovation; organizational unlearning and knowledge re-orchestration play a serial mediating role in this relationship; and knowledge inertia negatively moderates the relationship between organizational unlearning and knowledge re-orchestration. This study offers insights for traditional enterprises establishing efficient organizational change and knowledge management mechanisms to gain standard influence and innovation benefits. Full article

(This article belongs to the Section Complex Systems and Cybernetics)

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19 pages, 849 KB

Open AccessArticle

Invisible Paradigms: A Critical Realist Analysis of Ontological, Epistemological, and Axiological Positioning in Three Engineering Education Research Journals

by Margaret A. L. Blackie and Jennifer M. Case

Systems 2026, 14(8), 1031; https://doi.org/10.3390/systems14081031 - 21 Aug 2026

Abstract

Engineering education research (EER) draws on a wide range of philosophical traditions, yet the ontological, epistemological, and axiological (OEA) commitments that shape how knowledge is produced are rarely made explicit in published work. This study investigated the prevalence and nature of OEA positioning [...] Read more.

Engineering education research (EER) draws on a wide range of philosophical traditions, yet the ontological, epistemological, and axiological (OEA) commitments that shape how knowledge is produced are rarely made explicit in published work. This study investigated the prevalence and nature of OEA positioning across a purposive sample of 54 papers published in 2024 in three Q1 engineering education journals: the Journal of Engineering Education, the European Journal of Engineering Education, and the Australasian Journal of Engineering Education. Using critical realism as a metatheoretical framework, we developed an OEA coding instrument and applied it through an AI-assisted abductive coding process, assigning ontological, epistemological, and two-level axiological codes to each paper and assessing their internal coherence. The overwhelming majority of papers carry implicit rather than declared OEA commitments, a pattern consistent across journals and methodologies. The field is genuinely philosophically plural, with ontological positions ranging from naïve realism to social constructionism and critical realism, but the lack of clarity in this space potentially has consequences for knowledge transfer to practice, cumulative knowledge-building, and the coherence of individual studies. Full article

(This article belongs to the Special Issue Sociotechnical Systems in Engineering Education)

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21 pages, 2701 KB

Open AccessArticle

How Travel-Scenario Factors Shape the Substitution of Ride-Hailing Services by “Metro+” MaaS Intermodal Trips: Evidence from Beijing MaaS

by Yan Xu, Chen Gao, Xiang-Long Liu, Xiang-Jing Li and Chang Wang

Systems 2026, 14(8), 1030; https://doi.org/10.3390/systems14081030 - 21 Aug 2026

Abstract

Mobility as a service (MaaS) has emerged as a means to promote multimodal public transport and shared mobility trips, with the “Metro+” integrated mobility approach being its primary form. However, it has recently witnessed major global providers’ bankruptcies. Therefore, this study aims to [...] Read more.

Mobility as a service (MaaS) has emerged as a means to promote multimodal public transport and shared mobility trips, with the “Metro+” integrated mobility approach being its primary form. However, it has recently witnessed major global providers’ bankruptcies. Therefore, this study aims to identify factors driving users’ substitution of ride-hailing by “Metro+” MaaS intermodal trips. Specifically, we took ride-hailing trips as the baseline and constructed a multinomial logit (MNL) model incorporating travel-scenario factors, including trip purpose, weather, and urgency. The results show that travel-scenario factors significantly affected “Metro+” MaaS intermodal trip adoption for urban medium–long-distance trips. Users preferred MaaS intermodal trips for long-distance trips amid clear weather and no time pressure, and they favored ride-hailing in extreme weather conditions or for time-sensitive trips. Therefore, MaaS providers should emphasize travel scenarios in their marketing messaging. Finally, marginal rate of substitution (MRS) and elasticity analyses were conducted, and several strategies were proposed: (1) increasing ride-hailing availability; (2) improving transfer facilities and conditions; and (3) implementing dynamic demand matching. The study facilitates the identification of market opportunities for MaaS instead of car usage, contributes to MaaS marketing and service strategy optimization, and promotes sustainable urban transportation system development. Full article

(This article belongs to the Special Issue Sustainable Urban Transport Systems)

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