Oct 2026· Journal of construction engineering and management· 0 citations· 25 references
TL;DR
This study proposes a dual-incentive mechanism that integrates model training performance with worker satisfaction, encouraging providers to allocate more resources to safety knowledge recommendation and shows that the dual-incentive mechanism yields stronger incentive intensity, higher provider effort, and greater requester benefits versus single-model training incentives, while remaining robust across cost and risk variations.
Abstract
Despite the effectiveness of personalized safety knowledge enhancement training, existing research overlooks the challenges posed by fragmented worker data and strict privacy regulations. To overcome these challenges, this study proposes a novel FedCSKR framework aimed at achieving privacy-preserving cross-organizational construction safety knowledge recommendation (CSKR). Nonetheless, the effectiveness of CSKR depends on the decisions of both requesters and providers. We develop a game model to capture their interactions and show, through evolutionary analysis, that spontaneous collaboration is unsustainable, leading the system to a noncooperative equilibrium without external incentives. To promote cooperation, we propose a dual-incentive mechanism that integrates model training performance with worker satisfaction, encouraging providers to allocate more resources to safety knowledge recommendation. Modeling and simulations show that the dual-incentive mechanism yields stronger incentive intensity, higher provider effort, and greater requester benefits versus single-model training incentives, while remaining robust across cost and risk variations. Specifically, incentive intensity can be increased by over 98.3% and provider effort levels by more than 197.4%, while simultaneously helping to mitigate the requester’s exposure to uncertainty arising from model performance variability. Theoretical contributions of this study include the integration of federated learning with incentive-driven contract design in CSKR, representing the first effort, to our knowledge, that incorporates worker satisfaction into the incentive mechanism of the FedCSKR. Practically, this study offers a structured decision-making framework to assist construction managers in implementing privacy-compliant, effective, and collaborative CSKR. Overall, this study facilitates cross-organizational collaboration in CSKR and contributes to advancing personalized safety training.
Despite extensive research on knowledge spillovers, existing literature has paid limited attention to the formation mechanism of innovation chains. To address this gap, this paper constructs a multi-party evolutionary game model including two innovators and one supporter, incorporating knowledge spillover effects, and...
Min Zhang, Xin Jin, Yinan Yu· Systems· 0 citations
Prior research suggests that similarity in pay-performance sensitivities (PPS) among top management team (TMT) members enhances their collaboration. Building on this, the authors aim to use PPS similarity as a proxy for TMT collaboration to investigate its impact on corporate underinvestment.
Using a sample...
Anting Li, Yong Ye, Lin Xiao· Accounting Research Journal· 0 citations
Frontline production units in high‐hazard industries face a persistent “knowing‐doing gap” in process safety management: despite formal hazard identification procedures, high reporting volumes coexist with persistent major risks. Through a mixed‐methods case study in a PetroChina Tarim Oilfield unit (survey
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Xing Chen, Dongxu Gao, Fanzeng Yang et al.· Process safety progress· 0 citations
The entry of JD.com into the food delivery sector and the ensuing subsidy competition have resulted in irrational competition, merchant profit squeezes, and food safety risks in China. This study therefore investigates the collaborative governance mechanisms for food delivery platforms under involutionary competition d...
As the global focus shifts toward sustainability, the demand for credible Environmental, Social and Governance (ESG) information has accelerated. In emerging economies like Vietnam, following the national commitment to Net Zero by 2050, the role of independent assurance has become critical for ensuring financial transp...
Hoai Thu Nguyen· International Research Journ...· 0 citations
This paper investigates the dynamic coopetition and capacity-sharing strategies between an Integrated Manufacturer and a Developer under R&D uncertainty, focusing on the governance of strategically scarce capacity. By constructing a two-stage game model, we analyze how government intervention and risk-hedging mechanism...
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
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Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
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