Publication

@article{latukha_3902,

title = {The double bind: Human resource management under sanctions and skilled labor exodus},

author = {Marina Latukha and Desislava Dikova and Andrei Panibratov and Nikita Kuleshov},

url = {https://www.sciencedirect.com/science/article/pii/S0969593125001337?via%3Dihub},

year  = {2026},

date = {2026-02-01},

journal = {International Business Review},

volume = {35},

number = {1},

pages = {102520},

abstract = {This paper examines how human capital (HC) outflows, triggered by economic sanctions imposed on Russia, constitute a profound environmental disruption with long-term consequences for firms. Drawing on HC theory and based on case studies of three companies in the Russian IT sector, the study analyzes how large-scale talent relocation, referred to as brain-drain, undermines firms' strategic investments in HC development. We find that in the face of sustained uncertainty, human resource (HR) managers adopt reactive approaches, leading to the widespread abandonment of professional development initiatives. We argue that this shift risks eroding orga- nizational capabilities and placing firms at a long-term competitive disadvantage. By moving beyond macro- economic discussions of sanctions and focusing on firm-level human resource management (HRM) responses, this study offers new theoretical insights into how geopolitical shocks reshape HRM practices and disrupt the un- derlying logic of HC investment in high-skill industries.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jaffal-moutarda_3868,

title = {On the well-posedness of the Second-grade compressible fluid model},

author = {Basma Jaffal-Moutarda and Raafat Talhouk},

url = {http://dx.doi.org/10.1016/j.jmaa.2025.130030},

year  = {2026},

date = {2026-02-01},

journal = {Journal Of Mathematical Analysis And Applications},

volume = {554},

number = {2},

pages = {130030},

abstract = {In this paper, we investigate the well-posedness of Grade-two compressible fluid model in the non-steady case. To our knowledge, the existing literature provides only one result that addresses the existence of solutions for the compressible case, which is limited to steady-state flows.

We establish the local existence and uniqueness of solutions in the Sobolev space $H^m$, for $m  geq 3$ . We notice that in the incompressible case, the best known existence result requires $m  geq 5$, unless specific thermodynamic conditions are satisfied (their effect is to reduce the high nonlinearity of the model), in which case $m geq 3$ suffices.

Finally, we analyze the linearized system around the constant state and establish the global well-posedness of the solution, as well as its exponential decay in time toward the steady state. In addition, we prove the persistence of regularity for the solution.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mali_3855,

title = {DaMoOp: A global approach for optimizing denormalized schemas through a multidimensional cost model},

author = {Jihane Mali and Ahvar Shohreh and Faten Atigui and Ahmed Azough and Nicolas Travers},

url = {https://doi.org/10.1016/j.is.2025.102598},

year  = {2026},

date = {2026-02-01},

journal = {Information Systems},

volume = {136},

pages = {102598},

abstract = {The complexity of database systems has increased alongside the exponential growth of data, necessitating Information Systems (IS) architects to continuously refine data models and meticulously select storage and management options that align with requirements. While existing solutions focus on data model transformation, none offer guidance in selecting the most suitable data model for a given use case. In this context, we propose DaMoOp, an automated approach for leading data model selection process. DaMoOp starts from a conceptual model and associated use case comprising queries, settings and infrastructure constraints, to generate relevant logical data models. A cost model, considering environmental, financial, and temporal factors, facilitates comparison and selection of the most suitable data model. Our cost model incorporates both data model and queries costs. Additionally, we suggest a data model selection process that enhances the ability to choose the optimal data model(s) for a specific use case, while also adapting to rapidly evolving use cases. We provide a strategic optimization approach designed to identify the most cost-efficient and stable data model as use case scenarios evolve. Moreover, we offer a simulation tool for the entire process, which enables visualizing the impact of use case variations on data model costs, thus empowering IS architects to make informed decisions.},

note = {The complexity of database systems has increased alongside the exponential growth of data, necessitating

Information Systems (IS) architects to continuously refine data models and meticulously select storage and

management options that align with requirements. While existing solutions focus on data model transformation,

none offer guidance in selecting the most suitable data model for a given use case. In this context, we propose

DaMoOp, an automated approach for leading data model selection process. DaMoOp starts from a conceptual

model and associated use case comprising queries, settings and infrastructure constraints, to generate relevant

logical data models. A cost model, considering environmental, financial, and temporal factors, facilitates

comparison and selection of the most suitable data model. Our cost model incorporates both data model and

queries costs. Additionally, we suggest a data model selection process that enhances the ability to choose the

optimal data model(s) for a specific use case, while also adapting to rapidly evolving use cases. We provide a

strategic optimization approach designed to identify the most cost-efficient and stable data model as use case

scenarios evolve. Moreover, we offer a simulation tool for the entire process, which enables visualizing the

impact of use case variations on data model costs, thus empowering IS architects to make informed decisions},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{takhirov_3854,

title = {Pressure Poisson splitting scheme for Navier-Stokes Equations with open boundaries},

author = {Aziz Takhirov and Driss Yakoubi},

url = {https://www.sciencedirect.com/science/article/pii/S0378475425003489?via%3Dihub},

year  = {2026},

date = {2026-02-01},

journal = {Mathematics And Computers In Simulation},

volume = {240},

pages = {968-981},

abstract = {This paper presents a novel time-stepping algorithm for solving incompressible flows in domains with open boundaries. The scheme is based on the pressure Poisson reformulation of the system. A new boundary condition is proposed for the pressure variable on the open boundary. Unconditional stability is shown for a stabilized scheme. Numerical tests indicate excellent stability and accuracy of the proposed algorithm.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{takhirov_3921,

title = {Upwind iterative decoupling scheme for steady two-dimensional Grade-Two Fluid Equations},

author = {Aziz Takhirov and Basma Jaffal-Moutarda and Driss Yakoubi},

url = {https://doi.org/10.1016/j.cnsns.2025.109412},

year  = {2026},

date = {2026-01-01},

journal = {Communications In Nonlinear Science And Numerical Simulation},

volume = {152},

number = {Part E},

pages = {109412},

abstract = {This paper presents an efficient splitting scheme for solving steady second-grade flow equations in two-dimensional space. The proposed algorithm decouples the system into a separate equation for each flow variable. Uniform boundedness and convergence results are established under a reasonable set of assumptions. Numerical tests are presented to demonstrate the method's efficiency and accuracy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chu_3793,

title = {A general framework and an individual dominance realization model for efficient fixed cost allocation based on DEA},

author = {Junfei Chu and Yanhua Dong and Zhe Yuan and Weijiao Wang},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0305048325001082?via%3Dihub},

year  = {2026},

date = {2026-01-01},

journal = {Omega-International Journal Of Management Science},

volume = {138},

pages = {103382},

abstract = {Data Envelopment Analysis (DEA) has become a powerful tool for addressing fixed cost allocation (FCA) problems. Among the numerous DEA-based FCA studies, a significant category seeks to make all Decision-making Units (DMUs) efficient under a set of common weights after cost allocation, falling under the common-weights FCA framework. However, the classical DEA efficiency evaluation mechanism does not require all DMUs to be evaluated based on a set of common weights. Instead, a DMU is considered efficient if it can choose its favorable weights to achieve an efficiency score of one while ensuring that the efficiencies of other DMUs do not exceed one. Motivated by this, we develop a novel and general efficient FCA framework that allocates the total fixed cost by allowing each DMU to select its preferred weights to be efficient. We prove that the FCA possible set under the traditional common-weights framework is a subset of that under this new framework. Then, an Assurance Region (AR) constraint on fixed costs is introduced to avoid extreme allocation schemes. Moreover, an individual dominance realization strategy and a FCA model based on it are proposed within this framework, aimed at minimizing each DMU's cross-efficiencies from the perspective of all other DMUs while ensuring its self-assessed efficiency remains at one. Additionally, an algorithm is introduced to guarantee the uniqueness of the FCA scheme. A numerical example and a case study from the Shanghai Automotive Industry Corporation are used to validate the effectiveness of this approach and compare it with other classic methods.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{el-amrani_3898,

title = {An efficient second-order scalar auxiliary variable approach for unsteady non-Newtonian incompressible fluids},

author = {Mofdi El-Amrani and Anouar Obbadi and Mohammed Seaid and Driss Yakoubi},

url = {https://www.sciencedirect.com/science/article/pii/S0010465525003674?via%3Dihub},

year  = {2025},

date = {2025-12-01},

journal = {Computer Physics Communications},

volume = {317},

pages = {109865},

abstract = {A novel second-order time-splitting method is proposed for the numerical solution of non-Newtonian fluid flows governed by the incompressible Navier-Stokes equations with a shear-rate dependent viscosity. In many applications, this class of fluid flows is challenging to numerically solve using the conventional monolithic methods. The proposed approach belongs to a family of viscosity-splitting methods and it separates the convection term from the incompressibility

constraint into two steps using the second-order implicit backward differentiation formula for the time integration. To ensure the stability of this method, we introduce a numerical scheme based on the scalar auxiliary

variable approach an efficient pressure incrementation is introduced using the scalar auxiliary variable approach. Unlike most projection methods for solving incompressible Navier-Stokes equations, the proposed method is free of any numerical inconsistencies generated by the treatment of boundary conditions in the pressure solution. A rigorous stability analysis is also carried out in this study and the proposed method is demonstrated to be consistent and stable with no restrictions on the time step. Numerical results are presented for three flow problems to validate the second-order convergence rates and to illustrate the performance of the proposed time-splitting scheme for unsteady

non-Newtonian incompressible fluids.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{xiao_3803,

title = {Metric learning-enhanced semi-supervised Graph Convolutional Network for multi-view learning},

author = {Huaiyuan Xiao and Fadi Dornaika and Jinan Charafeddine and Bi Jingjun},

url = {https://www.sciencedirect.com/science/article/pii/S1566253525004932?via%3Dihub},

year  = {2025},

date = {2025-12-01},

journal = {Information Fusion},

volume = {124},

pages = {103420},

abstract = {Multi-view learning utilizes data from diverse perspectives or modalities, integrating complementary infor

mation from various sources. It plays a crucial role in intelligent systems and finds extensive applications in 

fields such as computer vision, recommender systems, and natural language processing. With the increasing 

complexity and heterogeneity of real-world data, the integration of Graph Convolutional Networks (GCNs) in 

multi-view learning scenarios is becoming increasingly important. Despite the advances in GCNs, it remains a 

major challenge to effectively generalize models and improve their stability across different data views. In this 

paper, we present a novel framework, the Enhanced Triplet Loss Based Semi-Supervised Graph Convolutional 

Network for Multi-View Learning (MV-TriGCN), which addresses these challenges through three primary 

innovations. First, we propose an enhanced triplet loss for deep metric learning tailored to the hidden features 

of GCNs based on semi-hard negative sample selection. Second, view graphs are constructed using the classical 

KNN scheme and a semi-supervised flexible method to improve the diversity of data structure representation 

resulting in a more stable hypothesis space. Moreover, we learn an end-to-end multi-view GCN by merging all 

available graphs and utilizing the aggregated cross-entropy losses and deep metric losses. Finally, we introduce 

a stepwise training strategy that allows the model to adapt to the losses during different optimization phases. 

Extensive experiments show that our method outperforms existing state-of-the-art approaches in terms of  accuracy and stability},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{taher_3860,

title = {SHREC 2025: Protein surface shape retrieval including electrostatic potential},

author = {Yacoub Taher and Depenveiller Camille and Tatsuma Atsushi and Barisin Tin and Rusakov Eugen and Göbel Udo and Peng Yuxu and Deng Shiqiang and Kagaya Yuki and Park Joon Hong and Kihara Daisuke and Guerra Marco and Palmieri Giorgio and Ranieri Andrea and Fugacci Ulderico and Biasotti Silvia and Ruiwen He and Benhabiles Halim and Cabani Adnane and Hammoudi Karim and Li Haotian Li and Huang Hao and Li Chunyan and Tehrani Alireza and Meng Fanwang and Zadeh Farnaz Heidar- and Yang Tuan-Anh and Montes Matthieu},

url = {http://dx.doi.org/10.1016/j.cag.2025.104394},

year  = {2025},

date = {2025-11-01},

journal = {Computers & Graphics-Uk},

volume = {132},

pages = {104394},

abstract = {This SHREC 2025 track dedicated to protein surface shape retrieval involved 9 participating teams. We evaluated the performance in retrieval of 15 proposed methods on a large dataset of 11,565 protein surfaces with calculated electrostatic potential (a key molecular surface descriptor). The performance in retrieval of the proposed methods was evaluated through different metrics (Accuracy, Balanced accuracy, F1 score, Precision and Recall). The best retrieval performance was achieved by the proposed methods that used the electrostatic potential complementary to molecular surface shape. This observation was also valid for classes with limited data which highlights the importance of taking into account additional molecular surface descriptors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ouchdiri_3897,

title = {Turing patterns in a morphogenetic model with single regulatory function},

author = {Mohamed Amine Ouchdiri and SAAD BENJELLOUN and Adnane Saoud and Irene Otero-Muras},

url = {http://dx.doi.org/10.1016/j.mbs.2025.109536},

year  = {2025},

date = {2025-11-01},

journal = {Mathematical Biosciences},

volume = {389},

pages = {109536},

abstract = {Confirming Turing's theory of morphogens in developmental processes is challenging, and synthetic biology has opened new

avenues for testing Turing's predictions. Synthetic mammalian pattern formation has been recently achieved through a reaction-

diffusion system based on the short-range activator (Nodal) and the long-range inhibitor (Lefty) topology, where a single function

regulates both morphogens. In this paper, we investigate the emergence of Turing patterns in the synthetic Nodal-Lefty system.

First, we prove the existence of a global solution and derive conditions for Turing instability through linear stability analysis.

Subsequently, we examine the behavior of the system near the bifurcation threshold, employing weakly nonlinear analysis, and

using multiple time scales, we derive the amplitude equations for supercritical and subcritical cases. The results demonstrate the

ability of the system to support various patterns, with the subcritical Turing instability playing a crucial role in the formation of

dissipative structures observed experimentally.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dornaika_3847,

title = {Towards Dynamic Self-Training for Scalable Semi-Supervised Learning on Graphs},

author = {Fadi Dornaika and Zoulfakar IBRAHIM and Jinan Charafeddine and Alireza Bosaghzadeh},

url = {http://dx.doi.org/10.1016/j.neucom.2025.131223},

year  = {2025},

date = {2025-11-01},

journal = {Neurocomputing},

volume = {654},

pages = {131223},

abstract = {In the realm of graph-based semi-supervised learning (GSSL), traditional methodologies often struggle to effectively handle labeled samples and scale to accommodate large datasets. To increase supervision information in semi-supervised learning, the self-training paradigm is often used, mainly in datasets with moderate sizes. On the other hand, the use of anchors was adopted with large datasets. In this research endeavor, we propose a novel framework for GSSL that leverages a novel self-training principle tailored for very large datasets, and introduces an advanced method for automatic graph construction using anchors. Our approach focuses on utilizing generated labels of random batches of unlabeled samples, subsequently incorporating these predictions into the training set to enhance the model's accuracy. Pseudo-labeling, a specific instance of self-training, assigns pseudo-labels to the most confidently predicted unlabeled examples, treating them as ground truth during the training phase. By constructing anchor-to-anchor affinity graphs that incorporate both feature and label information, our method facilitates robust learning on large-scale datasets. Through comprehensive experimentation across diverse large datasets, our approach demonstrates its efficacy in achieving scalable and reliable semi-supervised learning outcomes. These findings represent a significant advancement in the field of GSSL, with wide-ranging implications for various applications across different domains. Our method not only addresses the scalability issue but also ensures the effective integration of both labeled and pseudo labeled data, thereby enhancing the overall learning process.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bitar_3856,

title = {Can CSR in banking reduce corruption?},

author = {Mohammad Bitar and Hassan Obeid and Imane El Ouadghiri and Jonathan Peillex},

url = {https://doi.org/10.1016/j.frl.2025.107939},

year  = {2025},

date = {2025-11-01},

journal = {Finance Research Letters},

volume = {85},

pages = {107939},

abstract = {This study examines the impact of bank involvement in corporate social responsibility (CSR) on corruption. Using a sample of banks from 40 countries, the results show that CSR initiatives significantly reduce corruption, with consistent findings across tests. Mechanism analysis reveals that CSR mitigates corruption by strengthening regulatory frameworks, improving stakeholder protection, diversifying resources, and enhancing transparency. These findings emphasize the importance of integrating CSR into banking strategies and regulatory requirements to address social and environmental priorities and combat corruption.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{lacour_3784,

title = {Capillary properties of natural fibre assembly for evaporative purposes},

author = {Stéphanie Lacour and Véronique Aguié-Béghin and Brigitte Chabbert and Mario Scheel and Damien Thomas and Pascal Clain},

url = {http://dx.doi.org/10.1016/j.colsurfa.2025.137145},

year  = {2025},

date = {2025-11-01},

journal = {Colloids And Surfaces A-Physicochemical And Engineering Aspects},

volume = {724},

pages = {137145},

abstract = {Natural fibres are well known for their high efficiency in evaporation and humidification applications, making them a promising solution for cooling processes during heat waves. Mimicking the evapotranspiration mechanisms of trees is essential for designing optimal fibre wicks in canopy-like devices. Such devices are designed by their capillary rising height and water storage capacity. This study examines the water retention properties and capillary rise height of various yarns: retention tests for surface properties and tomographies for topographical aspects are combined to explain observed water rising height in samples. Tomographic analyses document pore sizes, fibre diameters, and water distribution within the wicks. Water retention properties among the samples range from less than 10% to over 20% of dry mass, reflecting significant wettability differences. However, the ultimate height of water ascension primarily depends on the structural yarn properties. Repeated tomographic scans during the rise reveal that water initially ascends in fibre-dense regions. The competition between capillary and tensile forces causes displacements, redistributing fibre densities. In plant fibres, swelling amplifies these displacements and propagates them along the wick axis. Water envelops individual fibres or bundles, penetrating into the lumens. The size of wet lumens increases due to internal capillary pressure, which is influenced by the convexity of the internal walls. This pressure drives a creeping progression of the water front along the fibre axis. The study finds that a high number of strings with intermediate porosities, which accommodate swelling, enhances the capillary rise height. However, further research is needed to fully understand the role of lumens. While they provide additional water storage capacity and facilitate capillary action through small diameters, they may also reduce the flow rate of water ascent.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{courtioux_3448,

title = {How Tax Credit Shapes Firm R&D Strategies?},

author = {Pierre COURTIOUX and François Métivier and Antoine Rebérioux},

url = {https://www.degruyter.com/document/doi/10.1515/ael-2022-0098/html},

year  = {2025},

date = {2025-11-01},

journal = {Accounting, Economics and Law: A Convivium},

volume = {15},

number = {3},

pages = {437-470},

abstract = {This study extends the definition of firms' R&D strategies to integrate fiscal considerations related to R&D tax credits. Using French company data, we identify six types of ?extended' R&D strategies. We then examine the relationships of these strategies with the effective rate of R&D tax credits, defined as the ratio of total tax reliefs obtained by a firm through R&D tax credit to real R&D spending. This study contributes to a better understanding of the heterogeneity of companies' R&D strategies.},

note = {publication online de 2023 intégrée à un numéro en 2025},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{saba_3877,

title = {The DeLone and McLean Information Systems Success Model: What is the Future Evolution for Its Foundations, Components, and Applications?},

author = {Peter Saba and William H. DeLone and Noor Ul-Ain and Antoine Harfouche and Imed Ben Nasr and Guillaume Biot-Paquerot and Sabrine Mallek},

url = {https://doi.org/10.17705/1CAIS.05738},

year  = {2025},

date = {2025-10-01},

journal = {Communications of the AIS},

volume = {57},

pages = {878-898},

abstract = {The DeLone and McLean (D&M) Information Systems (IS) Success Model has served as a dominant framework for evaluating IS effectiveness for over three decades. This panel report synthesizes insights from a scholarly panel held at ICTO 2025 that convened the model's co-creator and experts in AI, digital transformation, user behavior, governance, and sustainability to reimagine the model's future evolution. We first recount the model's foundations, then examine how contemporary societal, technological, political, and environmental forces challenge its traditional formulation. The panel discussion revealed both consensus and healthy tensions: panelists agreed the six core dimensions of success remain largely timeless, yet underscored the need to adapt how these dimensions are defined and measured considering new realities. We highlight emerging themes such as the criticality of human-centric design to ensure information quality and trust in AI systems, the reconceptualization of ?use? and ?user satisfaction? as rich user experience constructs encompassing enjoyment and well-being, the incorporation of negative outcomes as part of success evaluation, and the broadening of ?net benefits? to include societal and environmental impacts. We discuss how the panel's insights extend recent literature, including new measures for social IS success and frameworks for multi-stakeholder value. We also outline directions for future research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{aajal_3928,

title = {Autonomous On-Street Parking Slot Detection: A Comprehensive Systematic Review of Vision-Based Approaches},

author = {Chaimae AAJAL and Othmane Sebban and Nada FAQIR and Ahmed Azough and Khalid Alaoui Zidani},

url = {https://ieeexplore.ieee.org/document/11207589},

year  = {2025},

date = {2025-10-01},

journal = {Ieee Access},

abstract = {Finding an available parking space remains a significant challenge, particularly in major international cities, where rapid population growth and increasing traffic congestion exacerbate this problem. To address this issue, numerous sensor-based systems have been developed to manage parking infrastructures. However, these systems are often expensive and impractical because their sensors are susceptible to damage from adverse weather conditions. Consequently, in-vehicle camera-based parking-slot detection methods have emerged as more effective and scalable alternatives. Rapid advances in artificial intelligence in recent decades have facilitated the development of diverse methods and tools for autonomous parking detection. This systematic review examines state-of-the-art parking detection techniques, including image processing, machine learning, deep learning, and reinforcement learning approaches. It considers various imaging perspectives such as the driver's point of view, bird's-eye view, and around-view monitoring (AVM). The reviewed methods are evaluated using widely adopted benchmark datasets, with a focus on their performance in identifying parking slots and determining the occupancy status. Key challenges, including real-time implementation constraints and performance robustness across diverse environmental conditions, were critically analyzed. The findings suggest that hybrid models that integrate reinforcement learning with supervised learning hold substantial promise for future research and applications. This study offers a comprehensive assessment of current methodologies, identifies persistent research gaps, and proposes actionable recommendations to advance the development of robust autonomous parking detection systems.},

note = {22/10/2025TELECHARGER LA VERSION AVEC MENTION DATE PUBLISHED ASAP},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{taleb_3917,

title = {A flexible decision method for holonic smart grids},

author = {Ihab Taleb and Guillaume Guérard and Frédéric Fauberteau and Nga Nguyen and Pascal Clain},

url = {https://doi.org/10.32604/cmes.2025.070517},

year  = {2025},

date = {2025-10-01},

journal = {Cmes-Computer Modeling In Engineering & Sciences},

abstract = {Isolated power systems, such as those on islands, face acute challenges in balancing energy demand with limited generation resources, making them particularly vulnerable to disruptions. This paper addresses these challenges by proposing a novel control and simulation framework based on a holonic multi-agent architecture, specifically developed as a digital twin for the Mayotte island grid. The primary contribution is a multi-objective optimization model, driven by a genetic algorithm, designed to enhance grid resilience through intelligent, decentralized decision-making. The efficacy of this architecture is validated through three distinct simulation scenarios: (1) a baseline scenario establishing nominal grid operation; (2) a critical disruption involving the failure of a major power plant; and (3) a localized fault resulting in the complete disconnection of a regional sub-grid. The major results demonstrate the system's dual resilience mechanisms. In the plant failure scenario, the top-level holon successfully managed a global energy deficit by optimally reallocating shared resources, prioritizing grid stability over complete demand satisfaction. In the disconnection scenario, the affected holon demonstrated true autonomy, transitioning seamlessly into a self-sufficient islanded microgrid to prevent a cascading failure. Collectively, these findings validate the holonic model as a robust decision-support tool capable of managing both systemic and localized faults, thereby significantly enhancing the operational resilience and stability of isolated smart grids.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{vanaei_3920,

title = {A hybrid genetic algorithm-neural network model for optimizing thermal and mechanical characteristics of 3D-printed parts},

author = {Hamidreza Vanaei and Mohammad Moezzibadi and Abbas Tcharkhtchi and Sofiane Khelladi},

url = {http://dx.doi.org/10.1108/RPJ-02-2025-0085},

year  = {2025},

date = {2025-10-01},

journal = {Rapid Prototyping Journal},

abstract = {Fused filament fabrication (FFF) optimization remains a critical challenge due to the complex interplay of process parameters affecting the physicochemical and mechanical properties of printed parts. This study aims to optimize the FFF process by analyzing the effects of liquefier temperature, platform temperature and print speed using artificial neural networks (ANNs) and genetic algorithms (GAs).

A hybrid approach combining ANNs and GAs was employed to model and optimize the process parameters. The GA systematically explored the parameter space to identify optimal settings that maximize material properties such as degree of crystallinity, tensile strength, Young's modulus and elongation at break. The ANN, trained on an extensive experimental dataset, provided predictive insights into these properties, enabling a more efficient and precise optimization. A heat transfer model was utilized to predict the temperature profile of the filaments during deposition, validating the optimized conditions and offering insights into the thermal history of the printed parts.

The results demonstrate that the optimized process parameters significantly enhance material properties and improve inter-layer bonding. The study identifies the critical influence of liquefier temperature and print speed on mechanical performance, while also revealing limitations in traditional optimization methods. Furthermore, the thermal model predictions align well with experimental findings, reinforcing the validity of the proposed optimization strategy.

This study provides a novel hybrid approach to optimizing FFF process parameters by integrating machine learning techniques with traditional experimental and analytical models. The findings offer valuable insights into improving 3D printing efficiency and part quality, with potential applications in various industrial and research domains. Future work may explore the generalizability of the findings to different materials and incorporate real-time process monitoring for enhanced adaptability and precision.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{mammeri_3919,

title = {Aeroacoustic and aerodynamic evaluation of SLA-printed cross-flow fans: desktop vs. industrial-grade fabrication},

author = {Amrid Mammeri and Hamidreza Vanaei and Ouiza Saddaoui and Issiaka Traore and Messipssa Aoudjit and Ivan Dobrev and Kamel Azzouz and Sofiane Khelladi},

url = {https://doi.org/10.1108/RPJ-06-2025-0226},

year  = {2025},

date = {2025-10-01},

journal = {Rapid Prototyping Journal},

abstract = {The application of stereolithography (SLA) for functional turbomachinery components remains a developing area of interest, particularly regarding the performance impact of fabrication scale. This study aims to evaluate the aerodynamic and aeroacoustic performance of cross-flow fan (CFF) rotors fabricated using desktop and industrial-grade SLA machines, highlighting how geometric fidelity and mechanical behavior influence fan efficiency and noise.

Design/methodology/approach - CFF rotors were 3D printed using both desktop and industrial SLA printers. Mechanical properties were evaluated based on layer orientation and post curing temperature. Aerodynamic performance was assessed experimentally via static efficiency and pressure coefficient, while aeroacoustic behavior was characterized using sound pressure level (SPL) measurements across various flow coefficients and rotational speeds. Geometry distortions were linked to observed performance discrepancies using theoretical modeling grounded in Euler's equation and blade angle analysis. The results show that post curing at 80 °C significantly improved tensile strength, with up to 110% gain at 0° orientation. The desktop printed rotor exhibited a 10-15% reduction in peak aerodynamic efficiency and a ?1 dB increase in SPL, primarily due to blade deformation and altered inlet/outlet angles. Theoretical analysis confirmed the sensitivity of CFF performance to blade alignment, validating the observed effects. Despite minor drawbacks, desktop SLA was found viable for rapid prototyping in fan design. This work offers a novel experimental-theoretical framework for evaluating desktop SLA in aerodynamic and acoustic applications. It provides insights into the relationship between manufacturing fidelity, mechanical properties and functional performance of CFFs. These findings can inform the design and validation of 3D-printed turbomachinery components using accessible laboratory-scale equipment.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{elhadri_3893,

title = {Comparison of Self?Heating Behavior Between Continuous and Interrupted Control Modes},

author = {Hamza Elhadri and Johann Petit and Naila Hfaiedh and Danièle Wagner and Olivier Polit},

url = {http://dx.doi.org/10.1111/ffe.70038},

year  = {2025},

date = {2025-10-01},

journal = {Fatigue & Fracture Of Engineering Materials & Structures},

volume = {48},

number = {10},

pages = {4517-4527},

abstract = {In gigacyclic fatigue testing, reaching 109 cycles within a reasonable duration is challenging, leading to the use of ultrasonic

fatigue machines operating at 20 kHz (UFT). However, the high testing frequency causes significant temperature rises, potentially

enhancing microplasticity and leading to premature failure. This study compares two control modes in gigacyclic fatigue:

continuous and interrupted (pulse-pause)

during self-heating

tests on UFT. Two materials with distinct thermal properties, steel

42CrMo4 and aluminum alloy AA2024-T351,

were tested. The temperature evolution was measured using an infrared camera.

Then, a local expression of the heat equation is used to estimate the intrinsic dissipation, denoted as d1. Results showed that both

modes led to temperature increases with higher displacement, but pulse-pause

caused a smaller temperature rise. Reducing the

pulse time relative to the pause time decreased temperature variation. For 42CrMo4 steel, self-heating

was more pronounced

than for AA2024-T351,

and the d1 value increased with displacement amplitude.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{aftab_3837,

title = {Intermediating mechanisms and market conditions in big data knowledge management for enhanced market performance},

author = {Junaid Aftab and Feng Wei and Mohit Srivastava and Nabila Abid and Muhammad Ishtiaq ISHAQ},

url = {http://dx.doi.org/10.1016/j.techfore.2025.124266},

year  = {2025},

date = {2025-10-01},

journal = {Technological Forecasting And Social Change},

volume = {219},

pages = {124266},

abstract = {Big data has become a new reality, enabling organizations to gain novel insights and adjust strategies concerning competitors and consumer preferences. However, the hospitality industry still struggles to effectively leverage big data knowledge management to enhance performance and achieve a competitive advantage. Therefore, this study examines the impact of big data knowledge management on market performance, drawing on the knowledge-based view as its theoretical foundation. Additionally, it investigates the mediating roles of big data analytical capability and sustainable marketing in the relationship between big data knowledge management and performance while considering market turbulence as a boundary condition. Using a survey-based research design, data were collected in two waves from 323 managerial-level employees in the Pakistani hospitality industry and analyzed using structural equation modeling. The findings confirm the mediating roles of big data analytical capability and sustainable marketing while revealing that market turbulence weakens the positive association between sustainable marketing and performance. From a theoretical perspective, this study provides empirical support for the proposed hypotheses, offering insights into how big data knowledge management and analytical capability contribute to sustainable marketing and performance in emerging markets. From a managerial standpoint, the findings provide practical guidance for top management on effectively utilizing big data to maximize returns in the hospitality industry.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rezaee_vessal_3779,

title = {Embracing pain in pursuit of growth: a qualitative study of chronically ill patients' mountain climbing experiences},

author = {Saeedeh Rezaee Vessal and Judith Partouche-Sebban and Alain Toledano and Fabien Bernhard and Francesco Schiavone},

url = {https://www.sciencedirect.com/science/article/pii/S014829632500311X},

year  = {2025},

date = {2025-10-01},

journal = {Journal Of Business Research},

volume = {199},

pages = {115488},

abstract = {Recently, experiences that incorporate elements of pain and discomfort alongside pleasure-seeking have received

considerable attention in terms of practice and research. This qualitative study delves into this phenomenon by

examining the consumption journey of a unique consumer group?chronically ill patients?who intentionally

choose mountain climbing as a means of Post Traumatic Growth. Through in-depth interviews and participant

observations conducted in France, we explore the multifaceted journey of cancer patients as they navigate pain

while engaging in mountain climbing. Our findings shed light on the transformative power of embracing pain

within consumption experiences and contribute to the evolving discourse on pain marketing. Three stages of this

consumption journey are explored: 1) the pre-encounter stage and the motivations to embark on this experience,

reinforced by therapeutic guidance, surrounding support, and personal preparation; 2) the encounter stage and

the interplay between physical and psychological conditions in which cognitive, emotional and social resources

are at stake; and 3) the post-encounter stage with the lasting impact and consequences of this transformative

experience of self-reflection on both individuals and service providers. It clarifies the transformative potential

inherent in embracing pain, guiding patients towards personal growth, and empowerment, and the cultivation of

meaningful connections with brands aligned with their values.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ahmad_3775,

title = {Humblebragging and post purchase dissonance: A multi-study approach},

author = {Rehan AHMAD and Muhammad Ishtiaq ISHAQ and Ali RAZA and Qurat-ul-ain Talpur and Junaid Aftab},

url = {https://www.sciencedirect.com/science/article/pii/S0278431925002440},

year  = {2025},

date = {2025-10-01},

journal = {International Journal Of Hospitality Management},

volume = {131},

pages = {104321},

abstract = {Individuals use social media platforms to gratify their self-presentation needs. However, due to the challenges

associated with overt bragging, people may resort to humblebragging (i.e., boasting disguised as a complaint).

The effectiveness of humblebragging is a subject of debate in literature. Therefore, this study uses multi-study

approach (survey and experimental study design) aimed to identify: (i) the conditions under which humblebragging can generate positive outcomes in a tourism context, (ii) whether humblebragging can be used as an

effective strategy to mitigate post-purchase dissonance, and (iii) the role of opinion leaders in tourism. The

findings revealed that opinion leadership plays a robust moderating role, such that humblebragging can generate

positive outcomes and can be an effective strategy to mitigate post-purchase dissonance, but only among individuals with high levels of opinion leadership.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{el-amrani_3670,

title = {Error analysis of a fractional-step method for reactive fluid flows with Arrhenius activation energy},

author = {Mofdi El-Amrani and Anouar Obbadi and Mohammed Seaid and Driss Yakoubi},

url = {https://www.sciencedirect.com/science/article/abs/pii/S1007570425002783},

year  = {2025},

date = {2025-10-01},

journal = {Communications In Nonlinear Science And Numerical Simulation},

volume = {149},

pages = {108867},

abstract = {Propagation problems of reaction fronts in viscous fluids are crucial in many industrial and chemical engineering processes. The interactions between the reaction properties and the fluid dynamics yield a complex and nonlinear model of Navier-Stokes equations for the flow with a strong coupling with two reaction-advection diffusion equations for the temperature and the

degree of conversion. To alleviate difficulties related to the numerical approximation of suchsystems, we propose a fractional-step method to split the problem into several substeps, and based on a viscosity-splitting approach that separates the convective terms from the diffusion

terms during the time integration. A first-order scheme is employed for the time integration of each substep of the proposed fractional-step method. The proposed method also preserves the full original boundary conditions for the velocity which eliminates any potential inconsistencies

on the pressure, and it allows for nonhomogeneous Dirichlet and Neumann boundary conditions

for the temperature and degree of conversion that are physically more appealing. In the present work, we perform an error analysis and provide error estimates for all involved solutions in their relevant norms. A rigorous stability analysis is also carried out in this study and the

proposed method is demonstrated to be consistent and stable with no restrictions on the time step. Numerical results obtained for a problem with known analytical solutions are presented to verify the theoretical analysis and to assess the performance of the proposed method. The method is also implemented for solving a two-dimensional flame-like propagation problem in

viscous fluids. The obtained computational results for both examples support the theoretical expectations for a stable and accurate numerical solver for reactive fluids with Arrhenius activation energy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{hamdache_3631,

title = {Asymptotic behavior of thin ferroelectric models},

author = {Kamel Hamdache and Djamila Hamroun},

url = {www.elsevier.com/locate/nonrwa},

year  = {2025},

date = {2025-10-01},

journal = {Nonlinear Analysis-Real World Applications},

volume = {85},

number = {1},

pages = {104379},

abstract = {It was pointed out in Shaw et al. (2000) that the boundary conditions satisfied by the

polarization play an important role in the description of the thin-limit of ferroelectric materials.

In this work we confirm the importance of this choice. In the present work, we consider the

limiting process as the thickness ? of a thin cylinder of R3 goes to 0, and when the polarization

satisfies two different boundary conditions. The first type of boundary conditions leads to an in-

plane model or 2?? 2? configuration while the second one leads to an (in-plane)-(out-of-plane)

model for the displacement and the polarization namely a 2?? 3? configuration. Moreover, the

thin-limit process in both cases induces a change of the Lamé coefficients in the displacement

equation, the coupling coefficient between the displacement and polarization equations, the

double wells potential of the polarization together to a new contribution in the equation of the

out-of-plane component of the polarization for the 2?? 3? model. The techniques used rely on

a rescaling method that penalizes the out-of-plane variable. Uniform bounds with respect to ?

are established, compactness techniques are employed, and the limits of the penalized terms

are identified.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kumar_3160,

title = {Mapping business ethics and society: A systematic journey into research and way forward},

author = {Vinod Kumar and Sachin Kumar and Ranjan Chaudhuri and Sheshadri Chatterjee and Demetris Vrontis},

url = {https://onlinelibrary.wiley.com/doi/10.1111/beer.12731},

year  = {2025},

date = {2025-10-01},

journal = {Business Ethics, the Environment and Responsibility},

volume = {34},

number = {4},

pages = {1487-1503},

abstract = {While the notion of business ethics has historical roots, previous research endeavours have refrained from consolidating the existing body of knowledge on the intersection of business ethics and society. This hesitance is attributed to the intricate and diverse nature of such studies. Thus, there is a gap in the literature on synthesizing the intimate relationship between business ethics and society. This gap in research serves as the impetus and motivation for the current investigation. However, limited empirical studies are found to have been conducted in the allied areas and there are limited studies that map business ethics and society in an extensive manner. In this context, this study systematically reviewed 87 scholarly works spanning a period of over 20?years in the realm of business ethics concerning society by considering articles included in the Scopus and Web of Science databases. Through the outcomes of this inquiry, an integrative and comprehensive framework detailing the interplay between business ethics and society at individual and organizational levels is introduced, with the potential to guide forthcoming scholars and practitioners in their pursuits. In this study, themes including employees' ethical behaviour, manufacturing strategy and ethics, leadership dynamics, consumer trust and so on have not been considered as critical societal dimensions that have not been included.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{guerard_2939,

title = {Tourism profile measure for data?driven tourism segmentation},

author = {Guillaume Guérard and Quentin Gabot and Sonia Djebali},

url = {https://doi.org/10.1007/s13042-024-02145-z},

year  = {2025},

date = {2025-10-01},

journal = {International Journal Of Machine Learning And Cybernetics},

volume = {16},

pages = {7107-7132},

abstract = {The digital revolution has brought about profound changes in research within the tourism segmentation field. The ease of grasping tourists' behaviors is facilitated by the digital traces left on social networks. Existing studies focusing on tourists' digital traces typically apply clustering algorithms to the tourism context. This paper introduces a novel measure, named tourism profile measure for determining tourism segmentation, also known as tourism profiling. The approach involves establishing a new clustering algorithm that centers on stays conducted by tourists, utilizing both the context and content of the trips. The proposed measure is then simulated and experimentally evaluated using a real dataset across various periods and diverse nationalities, particularly in the context of the French capital, Paris.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jedda_3908,

title = {How does managerial ability curb the cost of debt financing? The moderating role of information and business risks},

author = {Nour Jedda and Houssam Bouzgarrou and Faten Lakhal},

url = {https://philpapers.org/rec/LAKHDM},

year  = {2025},

date = {2025-09-01},

journal = {International Journal of Business Governance and Ethics},

abstract = {Prior evidence shows that higher managerial ability improves a

firm's information environment, but it remains unclear whether this also

influences creditors' perceptions of firms led by able managers. The purpose of

this paper is to investigate the effect of managerial ability on the cost of debt.

We also shed light on the moderating role of information and business risks.

Using a sample of 244 French listed firms over the period 2010-2020, we find

that managerial ability is negatively associated with the cost of debt. In

particular, able managers are likely to reduce the cost of debt through their

ability to effectively manage the firm, increase firm credibility and reduce

information asymmetry. The results also reveal that the negative effect of

managerial ability on the cost of debt is less pronounced in the presence of high

information and business risks. These findings suggest that risk components

play a vital role in lending decisions. Further evidence shows that the negative

effect of managerial ability on the cost of debt is more prevalent in firms with

better governance and audit quality but less prevalent in family-owned firms.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{guizani_3907,

title = {How Does Product Market Competition Influence Firm-Level Climate Change Exposure},

author = {Assil Guizani and Emna Brahem and Faten Lakhal},

url = {https://doi.org/10.1111/fire.70028},

year  = {2025},

date = {2025-09-01},

journal = {Financial Review},

volume = {0},

number = {0},

pages = {1-19},

abstract = {his study examines the impact of product market competition on firm-level exposure to climate change. Using a sample of 1441 US firms from 2001 to 2021, the findings indicate that climate change exposure increases with market competition. This suggests that competitive pressure drives firms to focus on core operations and cost-cutting measures to maximize shareholder value. Further analysis reveals that firms operating in competitive markets are less exposed to climate change risks when they possess substantial market share, exhibit high diversification, and face fewer financial constraints. The results also suggest that the positive relationship between competition and climate change exposure is more pronounced following the 2015 Paris Agreement, though this effect is weaker among firms with a CSR committee on the board. These findings offer important insights for market participants, highlighting the need to balance short-term competitive strategies with long-term sustainability under competitive pressure.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{guizani_3880,

title = {An Empirical Analysis of Waste Management Practices in French Family Firms},

author = {Assil Guizani and Emna Brahem and Faten Lakhal and Khaled Hussainey},

url = {https://doi.org/10.1108/JAL-03-2025-0140},

year  = {2025},

date = {2025-09-01},

journal = {Journal of Accounting Literature},

pages = {1-27},

abstract = {Purpose: This study examines the behavior of family firms in relation to corporate waste management practices. The study also explores the implementation of the Sustainable Development Goals (SDGs) in 2015 as an exogenous shock that may influence waste management in family firms.

Design/methodology/approach: This study uses ordinary least squares (OLS), propensity score matching (PSM), and two-stage least squares (2SLS) estimators on a longitudinal panel dataset of French firms observed between 2004 and 2020 to test the association between family firms and waste management. Additionally, difference-in-differences (DiD) estimation is employed to assess the influence of the implementation of the SDGs in 2015 on waste management practices in these firms.

Findings: The findings demonstrate that family firms are more engaged in reducing waste generation and improving waste recycling. This result suggests that these firms prioritize sustainable initiatives that aim to preserve social legitimacy and family reputation. Further analyses show that waste generation (waste recycling) decreases (increases) with the voting rights held by the family, for families in the first-generation stage, and if a family member holds the position of the CEO or the chairperson of the board of directors. Additionally, the effect of family firms on waste production and waste recycling is more accentuated after the implementation of the SDGs, and in ecologically innovative firms.

Practical implications: Our results provide valuable insights for family firms to maintain their environmental commitment, especially during generational transitions or when appointing non-family members in leadership positions. In addition, policymakers should consider expanding the implementation of regulations and incentives that encourage family firms to adopt sustainable waste management practices.

Originality/value: This study is the first to test the nexus between family firms and waste management practices, by focusing on family firms' dimensions, such as control, generational stage, and family involvement in management and the board.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{latukha_3904,

title = {Awkward Positioning of International Student: Concept Clarification for Developing International Student Talent},

author = {Marina Latukha and Yunxin Luo and Andrei Panibratov},

url = {https://doi.org/10.1177/15344843251382834},

year  = {2025},

date = {2025-09-01},

journal = {Human Resource Development Review},

volume = {0},

number = {0},

pages = {28},

abstract = {This paper unpacks the dominant concepts of international students, a demographic of increasing significance within the global talent pool. This study explore how past research identifies international students to reveal the contradictory nature of ter- minology that could serve as a barrier for talent identification and development within organizational settings. We propose the definition and introduce five criteria for discussing who international students are from the talent development lens. We also suggest avenues for future research. Clarifying the concept of international students is crucial for identifying and understanding their nature and characteristics, which in turn facilitates their development into valuable talent.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{chaudhuri_3900,

title = {A bibliometric, networked, and density-based content analysis of corporate social responsibility},

author = {Ranjan Chaudhuri and Apoorva A. and Demetris Vrontis and Alkis Thrassou and Sheshadri Chatterjee},

url = {https://doi.org/10.1504/GBER.2025.148359},

year  = {2025},

date = {2025-09-01},

journal = {Global Business Economics Review},

volume = {33},

number = {3-4},

pages = {394-422},

abstract = {Corporate social responsibility (CSR) models, from across the globe,

have been constructed using various factors; including CSR dimensions,

company credibility, CSR communication, CSR image, brand equity, and brand

preference. Despite receiving much attention over the years, however, there lies

a paucity of research that identifies paradigm shifts, future trends, emerging

fields and prevalent research clusters in the CSR domain; a knowledge gap

aimed to be filled by this research. The authors, through a quantitative

systematic review, investigated 1,615 research publications in CSR from

Scopus and Web of Science from 2000 to 2020. The results have been analysed

using bibliometric software tools such as VantagePoint® through outputs such

as (autocorrelation maps, bubble charts, and Aduna maps) and VOSviewer®

outputs such as (network visualisation, overlay visualisation and density

visualisation) to unveil the recent trend of CSR research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{levy_3895,

title = {PretopoMD: pretopology-based mixed data hierarchical clustering},

author = {Loup-Noé Levy and Guillaume Guérard and Sonia Djebali and Soufian Ben Amor},

url = {https://link.springer.com/article/10.1007/s10489-025-06770-1},

year  = {2025},

date = {2025-09-01},

journal = {Applied Intelligence},

volume = {55},

pages = {973},

abstract = {This article presents a novel pretopology-based algorithm designed to address the challenges of clustering mixed data without the need for dimensionality reduction. Leveraging Disjunctive Normal Form, our approach formulates customizable logical rules and adjustable hyperparameters that allow for user-defined hierarchical cluster construction and facilitate tailored solutions for heterogeneous datasets. Through hierarchical dendrogram analysis and comparative clustering metrics, our method demonstrates superior performance by accurately and interpretably delineating clusters directly from raw data, thus preserving data integrity. Empirical findings highlight the algorithm's robustness in constructing meaningful clusters and reveal its potential in overcoming issues related to clustered data explainability. The novelty of this work lies in its departure from traditional dimensionality reduction techniques and its innovative use of logical rules that enhance both cluster formation and clarity, thereby contributing a significant advancement to the discourse on clustering mixed data.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{saharti_3894,

title = {ESG Performance of Firms and the Structure of Loan Syndicates: Moderating Role of Relationship},

author = {Mohammed SAHARTI and Asif SAEED and Sajid M. CHAUDHRY and Rizwan Ahmed},

url = {http://dx.doi.org/10.1111/eufm.70019},

year  = {2025},

date = {2025-09-01},

journal = {European Financial Management},

abstract = {This study examines the impact of firms' environmental, social and governance (ESG) performance on borrower-lender relationships within syndicated loans. Analyzing a global panel of contracts, we examine the impact of ESG scores on the number of lenders and the ownership of lead arrangers. Utilizing theories of information asymmetry, agency, relational lending, and resource dependence, our findings indicate that high ESG performance decreases lead bank retention, thus broadening syndicates and distributing risk. However, prior borrower-led relationships can reverse this effect, emphasizing that ESG and relational trust act as complementary governance channels, shaping modern global credit markets and capital allocation across sectors.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}