In a cooperative game with a coalition structure and augmenting system (CAS game), players within each priori union are restricted by an augmenting system. Some worths of coalitions (infeasible coalitions) are unknown, such as coalitions across multiple priori unions and certain sub-coalitions within each priori union. By regarding a CAS game as an incomplete information game, we evaluate unknown worths of infeasible coalitions through feasible coalitions, obtaining both the lower and upper worths of infeasible coalitions. Therefore, the interval Owen-augmenting value is proposed, which is an extension of the Owen value. By setting the Harsanyi dividends of unformed coalitions to zero, we introduce another value (i.e., the restricted Owen-augmenting value). Furthermore, we prove that the restricted Owen-augmenting value is a special case of the interval Owen-augmenting value. All proposed values can be used to solve a CAS game.
This study examines retailers' information sharing aimed at enhancing product greenness within green supply chains, with consumer participation as a pivotal factor and the overarching goal of advancing the sustainable development of the whole supply chain ecosystem. Each supply chain comprises a green product supplier and a retailer with uncertain demand information. A tripartite evolutionary game model involving manufacturers, retailers, and consumers is constructed to analyze the factors influencing information sharing behavior, which serves as a critical pathway to achieve environmental and economic sustainability in green supply chain operations. The findings highlight two key insights: First, strong consumer willingness to purchase green products may inhibit retailers' inclination towards information sharing, a counterintuitive outcome that needs to be addressed to align individual stakeholder behaviors with long-term sustainable development goals. Second, lower information sharing costs can motivate retailers to share information with manufacturers; otherwise, manufacturers must adopt technological measures to assist retailers in reducing information sharing-related costs, thereby achieving win-win outcomes across the supply chain and fostering a sustainable and collaborative green supply chain system that balances ecological benefits, economic gains, and social value co-creation.
This study examines how audit partner workload influences CAM disclosures in Chinese listed firms. We find that heavier partner workload is associated with systematically lower CAM disclosure quality, including fewer CAMs, less detailed and less firm-specific disclosures and weaker conclusive statements. This negative effect, primarily driven by cross-industry workload, is mitigated when partners have longer tenure, serve more important clients or face stricter regulatory scrutiny. The lower CAM disclosure quality associated with heavier workload is linked to higher stock price synchronicity. Overall, our findings highlight the role of audit partner workload in shaping audit communication quality and capital market transparency.
Amidst global economic volatility and technological disruption, enhancing supply chain efficiency remains critical, yet the fragmented theoretical frameworks, opaque mediation mechanisms, and neglected contextual heterogeneity in understanding how new quality productivity forces (NQPFs) drive this transformation constitute a critical research gap. This study empirically examines NQPF's impact on supply chain efficiency and its underlying mechanisms, addressing three core problems: first, the lack of a holistic NQPF framework integrating digital, green, and talent dimensions; second, insufficiently explored mediating roles of technological innovation; and third, unaddressed heterogeneity across ownership types, industries, and regions. Using 2012-2022 panel data from Shanghai and Shenzhen A-share listed companies, we employ robustness tests, mediating effect models, and heterogeneity analyses. The results reveal that the NQPF significantly improves supply chain efficiency, primarily through technological innovation-which accounts for 84.6% of the variance-acting via technological innovation, management restructuring, and digital transformation. Crucially, heterogeneity analysis reveals stronger effects in state-owned enterprises, nonhigh-tech industries, and Eastern China, whereas high-tech sectors face integration challenges. Our originality lies in three aspects: integrating the NQPF's multiple dimensions into a unified theoretical framework; empirically clarifying the "black-box" mediation of innovation; and providing granular evidence for differentiated regional/industrial policies to bolster supply chain resilience.
The mean-square exponential synchronization (MSES) for delayed memristive neural networks (DMNNs, MNNs) subject to deception attacks is addressed in this paper. To reduce communication burdens and resist the effects of deception attacks, the switching event-triggered (SET) scheme is proposed that alternates between aperiodic sampled intervals and event trigger intervals. Considering the characteristics of the drive-response systems, an error system is formulated by incorporating the interval matrix method (IMM) to model memristive connection weights. In the construction of the controller, residual terms within the error system and mathematically characterized deception attacks are thoroughly considered, resulting in a novel secure controller. Based on this, piecewise Lyapunov functionals are constructed. Through the inequality techniques and Lyapunov stability theory, two MSES criteria are established under deception attacks. Additionally, an easily implementable algorithm is proposed to solve the maximum deception attack rate allowed by the system. Finally, the validity of the interval-dependent functionals and the superiority of the SET control scheme are verified by numerical examples.
