Publication

@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},

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{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{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{ul_haq_3813,

title = {Unpacking the link between servant leadership and followers' helping behavior: The mediating role of followers' servant attitude and the moderating effect of relational identity},

author = {Inam Ul Haq and umair tanveer and Muhammad Umer Azeem},

url = {https://www.sciencedirect.com/science/article/pii/S0278431925001860?via%3Dihub},

year  = {2025},

date = {2025-09-01},

journal = {International Journal Of Hospitality Management},

volume = {130},

pages = {104263},

abstract = {https://www.sciencedirect.com/science/article/pii/S0278431925001860?via%3Dihub},

note = {Given the importance of service orientation in the hospitality sector, this study investigates the process through which servant leaders develop follower's servant attitude and helping behavior. In particular, we argue that followers observe and emulate their servant leaders' service-oriented approach, leading them to internalize this attitude and engage in helping behaviors toward their colleagues. Furthermore, this process is stronger among followers who develop a strong relational identity with their leader. In such cases, the followers' relational need for close association with the leader compels them to adopt a service attitude. To test these predictions, we draw from time-lagged, multi-source field survey data collected from 222 leader-follower dyads across several hospitality sector organizations in Pakistan. The results support our predictions: servant leadership positively predicts followers' servant attitude, which in turn steers them to engage in helping behaviors. Additionally, followers' relational identity invigorates the positive effects of servant leadership on followers' servant attitudes. These findings provide important insights for organizations and leaders in cultivating a service climate and eliciting helpful behavior at work.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mhiri_3672,

title = {Optimization of a Macrofiber Piezoelectric Energy Harvester Using Artificial Neural Networks},

author = {Mohamed Taha Mhiri and Walid Larbi and Mnaouar Chouchane and Mohamed Guerich},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0263822325004349},

year  = {2025},

date = {2025-09-01},

journal = {Composite Structures},

volume = {367},

pages = {119269},

abstract = {This paper addresses the challenge of finding the optimal design parameters for a

piezoelectric energy harvester. It presents an advanced simulation-driven optimization

approach to determine the optimal geometric and circuit configuration for maximizing energy

harvesting efficiency. Additionally, it enhances power output at an excitation frequency within

the 10-100 Hz range, which is commonly found in the environment. The harvester consists of

a cantilever beam partially coated with a macrofibre composite (MFC) piezoelectric patch,

connected to a resistance load and subjected to base excitation. The optimization platform is

built upon both analytical and finite element (FE) models of the energy harvesting system. For

beams with a large aspect ratio (length/width), the analytical model based on Euler-Bernoulli

beam theory is used, while for those with a small aspect ratio, a 3D FE model is employed to

simulate the entire energy harvesting process. This approach enhances the accuracy of

piezoelectric energy prediction. Due to the high computational cost and the significant time and

memory required for running numerous simulations to evaluate the objective function (OF)

used in the optimization, a more efficient solution is implemented based on a Neural Networks

(NNs) model. Initially, the NNs is trained using a dataset derived from simulations and its

performance and accuracy are rigorously assessed through various statistical methods. Once

trained, the NNs serves as a surrogate model for OF evaluation, allowing for more efficient

black-box optimization via a Genetic Algorithm (GA). Finally, a thorough analysis of the

optimal design parameters obtained from the optimization process is conducted.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chu_3501,

title = {Data envelopment analysis fixed cost allocation based on dynamic bargaining game and the Nash equilibrium},

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

url = {https://www.sciencedirect.com/science/article/abs/pii/S0377221725002061},

year  = {2025},

date = {2025-09-01},

journal = {European Journal Of Operational Research},

volume = {325},

number = {2},

pages = {317-328},

abstract = {Fixed cost allocation (FCA) poses a significant challenge for decision-making units (DMUs) contributing to a shared cost. Each DMU aims to allocate the minimum possible cost to itself. As a result, different DMUs hold varying and often conflicting allocation proposals and preferences, which prevents them from reaching a consensus on the FCA outcome. This paper develops a dynamic bargaining game-based fixed cost allocation (DBG-FCA) approach within the data envelopment analysis (DEA) framework to address this issue. The DBG-FCA approach employs an iterative process where each DMU proposes its preferred allocation during each iteration. All DMUs gradually converge on a consensus FCA outcome through dynamic negotiations and gradual compromise. Notably, this consensus upholds the individual rationality of each DMU, allowing them to align their proposals with their specific interests. Furthermore, the analysis establishes that the resulting FCA solution constitutes a Nash equilibrium, guaranteeing stability and universal acceptance among the DMUs. The effectiveness of the proposed approach is further illustrated through a numerical example and a case study involving FCA across 14 bank branches, along with a comparison to existing FCA methods.},

note = {In press JOURNAL PRE PROOF. 04/06/2025 : demande pdf final par ACA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{vanaei_3797,

title = {3D Printing Process and Local Preheating Technique Study Using a Laser?Based Method},

author = {Hamidreza Vanaei and Kaddour Raissi and Frédéric Coste and Alain Guinault and Abbas Tcharkhtchi and Sofiane Khelladi},

url = {http://dx.doi.org/10.1002/pen.70000},

year  = {2025},

date = {2025-08-01},

journal = {Polymer Engineering And Science},

volume = {65},

number = {8},

pages = {4335-4346},

abstract = {This study addresses the challenge of enhancing inter-filament

bonding in Fused Filament Fabrication (FFF) 3D printing, where

conventional methods often result in suboptimal mechanical strength or structural distortions. A novel local preheating technique

was introduced using a laser-based

approach to precisely control the temperature of previously deposited filaments. An

experimental setup integrating a 3D printer with a 30 W diode laser and an optical system was developed to evaluate key parameters,

including laser power, PLA color effects on laser absorptivity, and the relationship between preheating temperature and

bonding strength. Results demonstrate that preheating to 180°C increases mechanical bonding strength by up to 35% without

distortion, highlighting the technique's potential to improve FFF part quality.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{platania_3789,

title = {Bridging AI innovation and sustainable Development: The effect of AI technological progress on SDG investment performance},

author = {Federico Platania and Celina Toscano Hernandez and Imane El Ouadghiri and Jonathan Peillex},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0166497225001117?via%3Dihub},

year  = {2025},

date = {2025-08-01},

journal = {Technovation},

volume = {146},

pages = {103279},

abstract = {In the age of AI-driven innovation, Artificial Intelligence (AI) has become a transformative force in financial markets, reshaping investment strategies and sustainability-driven asset allocation. This study examines the impact of AI-driven innovation on the financial performance of sustainability-focused investments by analyzing the relationship between AI patent activity and the market returns of exchange-traded funds (ETFs) aligned with the United Nations Sustainable Development Goals (SDGs). Employing a state-space framework and a Kalman Filter model, we capture the dynamic influence of AI advancements on SDG-aligned ETFs, revealing that technological progress significantly enhances excess returns, particularly in the clean energy and water resource sectors. However, our analysis also uncovers sectoral variations in AI's financial impact, indicating that the benefits of AI innovation are unevenly distributed across industries. These findings bridge the gap between sustainable finance and technological innovation, demonstrating that AI serves as both a financial accelerator and a sustainability enabler. By integrating AI-driven innovation into asset pricing models, this study provides actionable insights for investors, policymakers, and corporate strategists, emphasizing the need to incorporate AI-based metrics into investment decision-making, risk assessment frameworks, and regulatory policies to foster sustainable economic growth.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{makki_3409,

title = {Asymptotic behavior of the coupled Allen-Cahn/Cahn-Hilliard system with proliferation term},

author = {Ahmad Makki and RIM MHEICH and Madalina Petcu and Raafat Talhouk},

url = {https://doi.org/10.1016/j.jmaa.2025.129382},

year  = {2025},

date = {2025-08-01},

journal = {Journal Of Mathematical Analysis And Applications},

volume = {548},

number = {1},

pages = {129382},

abstract = {In this article, we investigate the coupled Allen-Cahn/Cahn-Hilliard equations with

a proliferation term, which can model the growth of cancerous tumors and other

biological entities. We focus on establishing the existence, uniqueness, and regularity

of solutions, as well as analyzing their asymptotic behavior, with particular attention

to the existence of finite-dimensional attractors. The system is considered under

Dirichlet boundary conditions, and we introduce assumptions on the proliferation

term to ensure dissipativity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{jingjun_3817,

title = {Linear projection fused graph-based semi-supervised learning on multi-view data},

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

url = {http://dx.doi.org/10.1007/s10462-025-11313-8},

year  = {2025},

date = {2025-07-01},

journal = {Artificial Intelligence Review},

volume = {58},

pages = {309},

abstract = {In recent years, the surge in data-driven applications across various domains has spurred heightened interest in semi-supervised learning applied to graphs. This surge is attributed to the ubiquitous presence of graph data structures in real-world contexts, such as social networks' interpersonal relationships, recommender systems' user behavior graphs, and bioinformatics' molecular interaction networks. However, for certain data types like images, not only is there a dearth of explicit graph structure, but also the existence of multiple view description methods complicates matters further. The intricacies of multi-view data pose challenges in directly applying traditional semi-supervised learning techniques to graphs. Consequently, researchers have begun exploring the fusion of semi-supervised learning with deep learning to leverage its wealth of information and enhance model efficacy. Effectively amalgamating graph structures with multi-view data remains a challenging problem necessitating further research. This paper introduces the Linear projection Fused Graph-based Semi-supervised Classification (LFGSC) method tailored for multi-view data, building upon the Graph Convolutional Network (GCN) architecture. Firstly, for each view, we leverage a semi-supervised approach that provides the concurrent estimation of the corresponding graph and the flexible linear data representations in a low-dimensional feature space. Subsequently, an adaptive and unified graph is generated, followed by the utilization of a fully connected network to fuse the projected features further and reduce dimensionality. Finally, the fused features and graph are inputted into a GCN to conduct semi-supervised classification. During training, the model incorporates cross-entropy loss, manifold regularization loss, graph auto-encoder loss, and supervised contrastive loss. Leveraging linear transformation significantly diminishes the input feature dimensions for GCN, thereby achieving high accuracy while substantially reducing computational overhead. Furthermore, experimental results conducted on various bench-marked multi-view image datasets demonstrate the superiority of LFGSC over existing semi-supervised learning methods for multi-view scenarios. (Source code: https://github.com/BiJingjun/LFGSC.)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{peng_3810,

title = {Multi-view learning with graph convolution networks adopting diverse graphs and genuine deep feature fusion},

author = {Guowen Peng and Fadi Dornaika and Jinan Charafeddine},

url = {http://dx.doi.org/10.1007/s10462-025-11301-y},

year  = {2025},

date = {2025-07-01},

journal = {Artificial Intelligence Review},

volume = {58},

pages = {290},

abstract = {Multi-view data significantly enhances the accuracy of machine learning algorithms by providing a comprehensive representation of object features. Despite their potential, research on the use of Graph Convolutional Networks (GCNs) for processing node connectivity and data features remains limited. Existing methods mainly focus on weighted summation of graph matrices, with only a few approaches effectively integrating the feature information into the graph structures. To overcome these limitations, this paper proposes a novel deep learning architecture: the Feature Fusion and Multi-Graph Fusion Learning Framework (MGCN-FN). The framework consists of two core modules: Feature Fusion Network (FFN): Designed to extract and consolidate key features from multiple views. Multi-Graph Fusion Network (MGFN): Constructs multiple graphs for each view and jointly optimizes both the graph weights and the GCN model. Extensive experiments on various multi-view datasets show that MGCN-FN achieves superior performance compared to state-of-the-art methods, especially on semi-supervised multi-view classification tasks.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sokolova_3814,

title = {Can Information and Entertainment Compensate for Affection? A Cross-Sectoral Analysis of Social Media Influencers},

author = {Karina Sokolova and Saeedeh Rezaee Vessal and Charles Perez},

url = {https://onlinelibrary.wiley.com/doi/10.1111/ijcs.70085},

year  = {2025},

date = {2025-07-01},

journal = {International Journal Of Consumer Studies},

volume = {49},

number = {4},

pages = {e70085},

abstract = {Drawing on persuasion theory and the affect transfer hypothesis, this study explores how affection for social media influencers 

mediates and moderates followers' content perception (entertainment and informational value) and purchase intent. Using a 

dataset of 6633 French female followers across fashion, beauty, sports, news, and personal development sectors, and analyzed 

via PLS-SEM, results show affection's dual role. Information quality enhances affection, whereas entertainment compensates 

for low affection, especially among younger followers in beauty and fashion. Information quality, entertainment, and affection 

explain purchase intent across sectors, with older users valuing information quality more and showing higher purchase intent},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chevalier_3811,

title = {On security notions for encryption in a quantum world},

author = {Céline Chevalier and Ehsan Ebrahimi and Quoc Huy Vu},

url = {http://dx.doi.org/10.1007/s10623-025-01664-2},

year  = {2025},

date = {2025-07-01},

journal = {Designs Codes And Cryptography},

abstract = {Indistinguishability against adaptive chosen-ciphertext attacks (IND-CCA2) is usually considered the most desirable security notion for classical encryption. In this work, we investigate its adaptation in the quantum world, when an adversary can perform superposition queries. The security of quantum-secure classical encryption has first been studied by Boneh and Zhandry (CRYPTO'13), but they restricted the adversary to classical challenge queries, which makes the indistinguishability only hold for classical messages (IND-qCCA2). We extend their work by giving the first security notions for fully quantum indistinguishability under quantum adaptive chosen-ciphertext attacks, where the indistinguishability holds for superposition of plaintexts (qIND-qCCA2).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sinha_3808,

title = {More Than Meets the Eye - Decoding the Significance of Avatars: A Systematic Literature Review},

author = {Ankit Sinha and Ranjan Chaudhuri and Anjali Chopra and Subhro Sarkar},

url = {http://dx.doi.org/10.1080/08911762.2025.2524858},

year  = {2025},

date = {2025-07-01},

journal = {Journal of Global Marketing},

pages = {1-27},

abstract = {psychology, showing insights beyond the mere digital representation of users in a virtual 

Environment. This study aims for a holistic view of avatars across domains, using the 

miner-prospector continuum approach to develop a theoretical understanding through an 

extensive literature review. The study conducted a systematic literature review, analyzing 91 

peer-reviewed articles from 2005 to 2023, sourced from Scopus, EBSCO, and Web of Science. 

The thematic analysis identified six themes as the foundation for the proposed framework, 

which provides a comprehensive understanding of various variables involved in avatar 

domains such as anthropomorphism, trust, identity formation, and others. The study identified 

future research directions through thematic analysis, such as incorporating celebrity facial 

features into a brand's avatar. The study has several implications for managers and practitioners 

as they can utilize these findings to form enhanced strategies for implementing and 

understanding consumer behavior toward avatars.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{su_3659,

title = {Bridging uncertainty: A data-driven DRO approach for correcting censored demand in newsvendor problems},

author = {Xiaoli SU and Zhe Yuan and Chenghu Yang and Evren Sahin and Jie Xiong},

url = {http://dx.doi.org/10.1016/j.ijpe.2025.109626},

year  = {2025},

date = {2025-07-01},

journal = {International Journal Of Production Economics},

volume = {285},

pages = {109626},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zhang_3828,

title = {Can bilateral RMB swap reduce monetary policy spillovers from the United States to China?},

author = {Mi Zhang and Ahmet Sensoy and Duc Khuong Nguyen and Feiyang Cheng},

url = {http://dx.doi.org/10.1016/j.intfin.2025.102157},

year  = {2025},

date = {2025-06-01},

journal = {Journal Of International Financial Markets Institutions & Money},

volume = {101},

pages = {102157},

note = {This study analyzes the impact of bilateral RMB swap agreements on the transmission of US monetary policy to China, while focusing on the underlying mechanisms and potential heterogeneous effects. Our findings demonstrate that these agreements significantly attenuate US monetary policy spillovers to China. Mechanistically, we show that bilateral swaps promote Chinese exports to trading partner countries, thereby mitigating the negative consequences of US monetary policy. Notably, agreements with emerging economies exhibit a stronger mitigating effect than those with advanced economies. These results offer policymakers valuable insights for managing international monetary policy spillovers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rejeb_3806,

title = {The behaviour of distressed firms towards earnings management in a competitive product market},

author = {Najet Rejeb and Houssam Bouzgarrou and Faten Lakhal},

url = {https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijmfa#128343},

year  = {2025},

date = {2025-06-01},

journal = {International Journal of Managerial and Financial Accounting},

pages = {1-26},

abstract = {his study investigates the influence of corporate financial distress on earnings management under competitive market pressure. Using a dataset of 146 non-financial French firms listed on the SBF-250 index from 2005 to 2020 and the generalised method of moments approach, the findings reveal a positive effect of financial distress on earnings management. Distressed firms exhibit a heightened inclination to employ both accruals and real earnings management, with a greater emphasis on accruals over real earnings management. Conversely, financial distress reduces the use of earnings management by classification shifting. This effect is more pronounced for distressed firms operating in competitive markets. This is the first study to explore product market competition as a main driver through which financial distress positively affects earnings management. It offers stakeholders valuable insights into the manipulative behaviours of distressed firms in competitive environments, helping in more informed risk management decisions.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{chaudhuri_3802,

title = {The way forward to promote the dynamic resources of family businesses to achieve SDGs: the mediating role of sustainability performance},

author = {Ranjan Chaudhuri and Sheshadri Chatterjee and Katarina Valaskova and Ciro Troise},

url = {https://www.emerald.com/insight/content/doi/10.1108/ijebr-03-2025-0261/full/html},

year  = {2025},

date = {2025-06-01},

journal = {International Journal Of Entrepreneurial Behavior & Research},

volume = {ahead-of-print},

number = {ahead-of-p},

abstract = {Purpose

The dynamic capabilities (DCs) of family firms help to respond to dynamic business environments. Presently, few studies have examined how DCs of family firms could achieve SDGs, especially in the context of economic, social and environmental performance. As such, the present research tries to investigate how DCs of family firms could help to achieve better SDG performance with the mediating role of the firms' sustainable performance.



Design/methodology/approach

Sustainable development goals (SDGs) are designed to achieve a more sustainable and better future for everyone on the planet. Different types of firms are expected to initiate efforts to contribute to these SDGs. Family businesses are key actors in this regard. With the dynamic capability view (DCV) as well as with the knowledge of stakeholder theory as well as with the support of extant literature, a model was prepared that was tested by CB-SEM technique to analyze the responses of 317 respondents.



Findings

This research found that the DCs of these businesses have a significant impact on their SDG performance. The study highlights that family firms are lagging in their reconfiguring capabilities regarding environmental and social performance, so it is a challenging task for family firms to improve on this aspect.



Research limitations/implications

This study deals with cross-sectional data. Therefore, its findings may not be generalizable. Additionally, this study does not address rival or alternative models, which could be seen as a limitation. Furthermore, because the analysis is based on feedback collected from a single geographic region, they may not be universally applicable to other areas.



Originality/value

This study has contributed to the prevailing body of knowledge on family business, sustainable development, firm performance, as well as dynamic resources. The highlights of this study can be used by the entrepreneurs, policymakers, as well as future researchers to further extend this study. Further, this study is also unique as it establishes the importance of the sustainable performance of family businesses with dynamic resources and could also be related to disruptive innovation for family businesses to achieve sustainable performance and to meet the sustainable development goals.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{courtioux_3800,

title = {The geographies of segregation in French universities from 2006 to 2016},

author = {Pierre COURTIOUX and Tristan-Pierre Maury and Johan Seux},

url = {https://link.springer.com/article/10.1007/s10734-025-01473-5},

year  = {2025},

date = {2025-06-01},

journal = {Higher Education},

abstract = {Since the French university system is non-selective, the question of segregation has long remained unaddressed. However, the recent increase in enrolment, as well as the implementation of cluster-building policies, has brought the issue of university segregation and its geography to the forefront. This article proposes the first exhaustive geographical decomposition of segregation in French universities. Using a mutual information index, we identify the different local components and layers of social segregation and measure their contribution to the national level of segregation between 2006 and 2016. Our results show that in the French university system, segregation is quite low and tended to decrease over the period. However, we also show that only about 18% of the total segregation is due to macro-scale factors: i.e., social differences across regional areas: social segregation is mainly a local phenomenon that could be reduced with reforms of higher education enrolment policy, implemented at the regional level.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{jabbar_al-allaq_3796,

title = {A Comprehensive Review of Cutting-Edge Disaster Response: UAVs Equipped with FSO-Based Communications},

author = {Zaid Jabbar Al-Allaq and Wafaa Shakir and Jinan Charafeddine},

url = {https://link.springer.com/article/10.1007/s11277-025-11782-8#citeas},

year  = {2025},

date = {2025-06-01},

journal = {Wireless Personal Communications},

volume = {141},

pages = {29-394},

abstract = {Unmanned aerial vehicles (UAVs) equipped with free-space optical (FSO) communications have emerged as pivotal technological assets in disaster management. Traditional communication infrastructures often fail during severe disaster scenarios, resulting in delayed or ineffective emergency response efforts. Consequently, the integration of unmanned aerial vehicles with free-space optical communication technologies has emerged as an essential innovation in disaster response management. UAVs provide agile and rapidly deployable platforms, while FSO technology offers high-bandwidth, secure, and interference-resistant communication links. This comprehensive review systematically explores the current state and advanced integration strategies of UAVs equipped with FSO communication in disaster scenarios. Initially, the paper establishes the research context, identifying challenges associated with conventional disaster communications. Subsequently, the necessity for this review is articulated through a critical examination of the limitations faced by existing terrestrial systems. The paper clearly delineates various aspects of UAV-FSO integration by providing essential background information on disasters and conventional emergency communication systems, elaborating on the roles, benefits, and applications of UAVs specifically in disaster management contexts, and introducing FSO technology with its operational principles and advantages. Furthermore, it critically examines existing challenges and technical limitations of UAV-based FSO systems, including atmospheric disturbances and alignment issues. Recent technological advancements and mitigation strategies, such as intelligent reflecting surfaces, quantum key distribution, and machine learning integration, are discussed to enhance system reliability and performance. Detailed performance metrics such as bit error rate (BER) and outage probability are analyzed for evaluating UAV-FSO systems. Finally, the review addresses the latest contributions and innovations in the field, emphasizing future research directions and open challenges, and concludes by summarizing the transformative potential of integrating UAVs with FSO communications, advocating for continued research and practical application to improve disaster response capabilities globally.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dornaika_3790,

title = {Deep Feature Disentanglement for Supervised Contrastive Learning: Application to Image Classification},

author = {Fadi Dornaika and B Wang and Jinan Charafeddine},

url = {https://link.springer.com/article/10.1007/s12559-025-10430-4},

year  = {2025},

date = {2025-06-01},

journal = {Cognitive Computation},

volume = {17},

pages = {117},

abstract = {In machine learning, deep metric learning from original data is essential, with supervised contrastive learning being a notable approach. This method aims to form a deep feature space where similar samples from the same class are clustered together, while dissimilar samples from different classes are separated. However, a common limitation of contrastive learning methods is that they utilize the entire feature space for data embedding and often neglect the within-class variability. To overcome this limitation, we propose a novel supervised contrastive learning method that decomposes deep features into two distinct components: common features, which encapsulate the essential, class-defining characteristics, and style features, which capture the within-class variability and nuanced differences. Additionally, we enhance this approach by introducing an overlapping field that synergistically integrates elements from both feature spaces, enabling a more comprehensive and robust feature representation. Our experiments with different image datasets and deep encoders, including CNNs and transformers, show that our approach outperforms traditional single-feature contrastive methods. On the CIFAR100 and PASCAL VOC databases, traditional supervised contrastive learning achieved accuracy rates of 75.5% and 51.41%, respectively, while our method improved them to 77.81% and 59.38%, respectively. We present an algorithm for deep contrastive learning that utilizes two feature spaces: one for encoding common class features and another for capturing within-class variability. This is achieved by partitioning the features of the last layer of the encoder into (i) a common field and (ii) a style field. Our loss function contrasts the common features while summarizing the style features within the same class so that the style field can capture the intra-class variability.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gasmi_3629,

title = {Coastal Countries' Economic Growth: What are the Potential Consequences on Mangrove Blue Carbon?},

author = {Farid Gasmi and Laura Recuero Virto and Denis Couvet},

url = {http://dx.doi.org/10.1561/112.00000586},

year  = {2025},

date = {2025-06-01},

journal = {Journal Of Forest Economics},

volume = {40},

number = {1-2},

pages = {1-45},

abstract = {This paper analyzes the determinants of economic growth in coastal economies with the purpose of

highlighting the impact of human activity pressure on mangrove blue carbon (BC). We use a Bayesian

Model Averaging-based estimation technique to fit alternative growth theories to 1960-2009 data on a

BC sample of 23 coastal countries and a worldwide (WW) sample of 83 countries. In addition to

having high mangrove blue carbon climate change mitigation potential, a representative country from

the BC sample possesses features commonly associated with developing countries. Moreover, such a

country's natural capital per capita has decreased by more than 50% during the half-century span of

our data and its dependence on natural capital is almost twice as high as that of its WW counterpart.

We find that the neoclassical theory, through income and investment in physical capital, demography,

macroeconomic policy, and natural capital theories perform well in explaining growth in BC

countries. In contrast, investment in physical capital and proxies for the macroeconomic policy and

natural capital theories are found not to be good predictors of growth when using the WW sample of

countries. These results put the finger on the critical problem of existing and potential anthropogenic

pressure that coastal areas with BC are and can be subject to due to land conversion for agriculture,

aquaculture, farming and other run-offs, marine resources exploitation, uncontrolled sewage, marine

resources direct exploitation, and coastal constructions and public works related to natural capital

exports. This admittedly grim picture of the coasts draws attention to at least two policy questions,

namely, whether central governments ought to give local policy makers and communities incentives to

promote nature-based solutions to climate change mitigation and the extent to which international

financial institutions should provide financial support for such initiatives in developing countries.

Keywords: Economic growth, coastal countries, mangrove blue carbon, developing countries},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{alharbi_3628,

title = {Board co-option and audit quality: Evidence from US},

author = {Samar S. Alharbi and Asif SAEED and Umer Iqbal and Najoua Elommal},

url = {http://dx.doi.org/10.1016/j.irfa.2025.104123},

year  = {2025},

date = {2025-06-01},

journal = {International Review Of Financial Analysis},

volume = {102},

pages = {104123},

abstract = {This study investigates the impact of board co-option on audit quality, a vital dimension of corporate governance

that has received limited attention. Using a dataset of 9605 firm-year observations from U.S. listed firms, we

examine the extent to which co-opted directors aligned with CEOs compromise audit quality, measured through

BIG4 auditor selection and audit fees. Results show that board co-option significantly reduces audit quality, a

finding robust to alternative co-option measures, propensity score matching, and IV-Probit models. Notably, the

presence of a CSR committee and stronger governance scores mitigate these negative effects - highlighting their

significant role. These findings accentuate the need for regulatory reforms to strengthen board independence and

institutionalize CSR committees, enhancing governance practices and accountability.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{peng_3611,

title = {CGCN-FMF:1D convolutional neural network based feature fusion and multi graph fusion for semi-supervised learning},

author = {Guowe Peng and Fadi Dornaika and Jinan Charafeddine},

url = {http://dx.doi.org/10.1016/j.eswa.2025.127194},

year  = {2025},

date = {2025-06-01},

journal = {Expert Systems With Applications},

volume = {277},

pages = {127194},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kumar_3606,

title = {AI capability and environmental sustainability performance: Moderating role of green knowledge management},

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

url = {http://dx.doi.org/10.1016/j.techsoc.2025.102870},

year  = {2025},

date = {2025-06-01},

journal = {Technology In Society},

volume = {81},

pages = {102870},

abstract = {The capabilities of AI may not only foster green technology innovations but also enhance the environmental 

sustainability performance of organizations. Despite this, the interplay between AI capabilities, green technology 

innovations, and environmental sustainability performance largely remain unexplored in view of green knowledge management. The present study aims to fill this gap by examining the impact of AI capabilities on green 

technology innovations and ultimately on environmental sustainability performance. This study also examines 

how green technology innovations mediates between AI capabilities and environmental sustainability performance, and how green knowledge management moderates the relationships between AI capabilities and green 

technology innovations and between AI capabilities and environmental sustainability performance. To validate 

the proposed conceptual relationships, data were collected from IT companies of Pune, India from 237 respondents, and they were validated with PLS-SEM 3.0 software. The results of the present study contribute 

theoretically to the resources-based view, knowledge-based view, dynamic capability, and absorptive capacity 

theories. Moreover, this study has also contributed practically by revealing the potential of AI capabilities and 

green technology innovations to enhance environmental sustainability performance through green knowledge 

management. The insights of the study could also help managers to leverage the AI capabilities to enhance green 

technology innovations and to improve environmental sustainability performance of organizations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{benkraiem_2959,

title = {Access to finance and corporate tax avoidance: International evidence},

author = {Ramzi Benkraiem and Safa Gaaya and Faten Lakhal and Merve Kilic},

url = {https://www.sciencedirect.com/science/article/pii/S1061951824000740},

year  = {2025},

date = {2025-06-01},

journal = {Journal of International Accounting, Auditing and Taxation},

volume = {58},

pages = {100668},

abstract = {This paper investigates the relationship between access to finance and corporate tax avoidance. Using a sample of 63,443 firm-year observations from 37 countries, the results reveal that firms suffering from limited access to finance are more inclined to engage in tax avoidance practices. The results also show that increased levels of financial constraints are positively associated with tax avoidance for firms operating in countries with high economic and policy uncertainty and high government debt level. Further evidence shows that the difficulty to access finance increases tax avoidance in countries with weak investor protection. Our results are robust after addressing endogeneity concern and using different measures of financial constraints, tax avoidance, and countries' institutional environments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{arya_3724,

title = {AI-Enhanced Competency Transfer Hubs: A Conceptual Framework for University-Industry Engagement and Knowledge Sharing},

author = {Vikas ARYA and Ankita Saraf and Nikolai Chichkanov and Armando Papa and Marco Romano},

url = {https://link.springer.com/article/10.1007/s10961-025-10233-7},

year  = {2025},

date = {2025-05-01},

journal = {Journal Of Technology Transfer},

abstract = {This paper introduces a framework for AI-driven competency transfer hubs, designed to facilitate effective knowledge exchange and collaboration between universities and industries. These hubs leverage artificial intelligence technologies like machine learning and natural language processing to enhance the efficiency and effectiveness of information flows between academic institutions and industry partners, optimizing the whole knowledge-sharing process. Using the TCM-ADO framework the paper consolidates existing perspectives and offers practical suggestions on how to incorporate AI technologies into competency hubs. The discussion further delves into outlining key layers of such hubs including AI-powered knowledge extraction and enrichment, knowledge customization, adaptive project management as well as collaboration outcome enhancement and feedback optimization. A set of key elements for AI-enhanced competency transfer hubs was also developed and presented including the issues of technical alignment, advanced AI integration as well as value aspects. The study wraps up by exploring key areas of application in the establishment of AI-enhanced competency transfer hubs and their wider societal significance.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}