Publication

@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 = {http://dx.doi.org/10.1016/j.is.2025.102598},

year  = {2026},

date = {2026-02-01},

journal = {Information Systems},

volume = {136},

pages = {102598},

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 = {http://dx.doi.org/10.1016/j.matcom.2025.08.007},

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{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{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 = {http://dx.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{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{vlad_3881,

title = {State of the art of gyrokinetic and hybrid MHD?kinetic codes through non?linear benchmarking to study reactor relevant burning plasmas},

author = {Gregorio Vlad and Xin Wang and Francesco Vannini and Hinrich Luetjens and Sergio Briguglio and Nakia Carlevaro and Matteo Valerio Falessi and Giuliana Fogaccia and Valeria Fusco and Fulvio Zonca and Alessandro Biancalani and Alberto Bottino and Thomas Hayward-Schneider and Philipp Lauber and Baruch Rofman and Laurent Villard},

url = {https://doi.org/10.1007/s41614-025-00199-2},

year  = {2025},

date = {2025-09-01},

journal = {Reviews of Modern Plasma Physics},

volume = {9},

pages = {27},

abstract = {After a brief introduction on present day simulation and modeling of burning plas-

mas in magnetically confined devices, the results of a non-linear benchmark are pre-

sented, undertaken among several state-of-the-art codes available to study the self-

consistent interaction of an Energetic Particle (EP) population with shear Alfvén

waves: HYMAGYC, MEGA, ORB5 and XTOR-K. The first two codes, HYMAGYC

and MEGA, are hybrid codes: HYMAGYC is a MHD-Gyrokinetic code (the bulk

plasma is represented by MHD equations, while the EP species is treated using

the gyrokinetic formalism), while MEGA is an MHD-Drift-Kinetic code (the bulk

plasma is represented by MHD equations, while the EP species is treated using the

drift-kinetic formalism, with the possibility of an ad-hoc gyroaveraging); ORB5

is a global electromagnetic gyrokinetic code (both bulk and EP species are treated

using the gyrokinetic formalism); XTOR-K is a non-linear kinetic-MHD code (the

bulk plasma is described by a set of non-linear resistive two-fluid MHD equations,

extended to include kinetic effects of multiple ion species with a fully kinetic PIC

module). The equilibrium of the so-called NLED-AUG reference case, in its version

with peaked off-axis EP density profile, has been used, while considering a |n| = 1

perturbation. This non-linear benchmark is the natural continuation of the linear

benchmark already considered in the recent past, and represent a first-ever code

comparison in the deep non-linear stage. In the present study fluid non-linearities

are omitted, and the focus will be on comparing wave-particle interactions effects

across codes. Characteristics of the non-linear saturation of the mode, self-consist-

ent modification to the EP density profile and other features are compared among

the considered codes. This brief review presents the state of the art of gyrokinetic

and hybrid MHD-kinetic codes emerging as tools for studying reactor-relevant burn-

ing plasmas in realistic conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{clain_3842,

title = {Flow behaviour of Pickering Hexadecane emulsion stabilized with CNC and AOT for sustainable refrigeration},

author = {Pascal Clain and Somia Haouache and Isabelle Capron and Anthony Delahaye and Laurence Fournaison},

url = {https://www.sciencedirect.com/science/article/pii/S2590123025025630},

year  = {2025},

date = {2025-09-01},

journal = {Results in engineering},

volume = {27},

pages = {106494},

abstract = {The rheological behaviour under flow conditions of hexadecane-in-water emulsions stabilized by cellulosic nanoparticles was studied with a capillary viscometer. The study investigated several volume fractions of hexadecane between 0 and 15 vol%. and the temperature was varied in situ to investigate the liquid and solid states of hexadecane droplets (below and above 18 °C respectively). Various concentrations of 0 to 1 vol% of anionic bis (2-ethylhexyl) sulfosuccinate sodium (AOT) were used as anti-agglomerant agent and to ensure the continuous flow. Based on the capillary viscometer method associated with Rabinowitsch and Mooney's equation, the apparent viscosity of these emulsions (hexadecane in liquid state), dispersions (hexadecane in solid state) was determined by measuring the pressure drops of the flowing fluid as a function of the flow rate. We observed that the viscosity of those systems increased with the volume fraction of hexadecane, both in liquid and solid state. We also observed that the viscosity can be decreased by cycling the emulsions in the loop. This decrease of viscosity was accompanied by a decrease of the mean droplets size measured by granulometry analysis. We showed in this work the important role of AOT to avoid emulsion agglomeration during the cooling in the loop.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{servajean-hilst_3889,

title = {Any gender differences exist in the collaborative and innovative mindset of supply managers?},

author = {Romaric SERVAJEAN-HILST and Salomée Ruel},

url = {https://doi.org/10.1080/16258312.2025.2557787},

year  = {2025},

date = {2025-09-01},

journal = {Supply Chain Forum: An International Journal},

pages = {1-19},

abstract = {This study examines the influence of gender on collaborative and innovative mindsets in

upstream supply chain management (SCM), also considered as supply management. Given

the critical role of these mindsets in addressing today's supply challenges, this research

explores how gender impacts these attributes among supply managers. Using a quantitative

methodology, the study surveyed 250 junior supply managers in training and conducted

a narrow replication with 47 experienced supply managers in the same national context. The

results show significant gender differences in innovative mindset and differences in collaborative

mindset among junior managers only. Supported by replication, the study highlights

gender dimensions in upstream SCM mindsets. It extends discourse on gender in SCM by

linking it to collaboration and innovation. Findings encourage re-evaluating gender biases and

their impact on SCM practices. Practitioners and educators can apply these insights to design

training programmes that address and leverage gender differences, fostering innovative and

collaborative environments.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{dai_3878,

title = {Multiscale Risk Spillovers and External Driving Factors: Evidence From the Global Futures and Spot Markets of Staple Foods},

author = {Yun-Shi Dai and Peng-Fei Dai and Stéphane Goutte and Duc Khuong Nguyen and Wei-Xing Zhou},

url = {http://dx.doi.org/10.1111/risa.70094},

year  = {2025},

date = {2025-09-01},

journal = {Risk Analysis},

abstract = {Stable and efficient food markets are crucial for global food security. However, international staple food markets are increasingly exposed to complex risks, including intensified risk contagion and increasing external uncertainties. This paper systematically investigates risk spillovers in global staple food markets and explores the key determinants of these spillover effects, combining innovative decomposition-reconstruction techniques, risk connectedness analysis, and random forest models. The findings reveal that short-term components exhibit the highest volatility, with futures components generally more volatile than spot components. Further analysis identifies two main risk transmission patterns, namely, cross-grain and cross-timescale transmission, and clarifies the distinct roles of each component in various net risk spillover networks. Furthermore, price drivers, external uncertainties, and core supply-demand indicators significantly influence these spillover effects, with the heterogeneous importance of varying factors in explaining different risk spillovers. This study provides valuable information on the risk dynamics of staple food markets, offers evidence-based guidance to policymakers and market participants to improve risk warning and mitigation efforts, and supports the stabilization of international food markets and the protection of global food security.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{aweyaw_3863,

title = {Two decades of foreign direct investment in Africa: a systematic literature review, integrative framework, and agenda for future research},

author = {Abdul-Kadir Aweyaw and Andrei Panibratov},

url = {https://www.inderscience.com/offer.php?id=147963},

year  = {2025},

date = {2025-09-01},

journal = {European Journal Of International Management},

volume = {27},

number = {1},

pages = {1 - 47},

abstract = {Despite the increase in research efforts on Foreign Direct Investment (FDI) in International Business (IB), the literature on FDI in Africa suffers from disintegration, theoretical boundaries and empirical vagueness, leaving important countenances uninvestigated. The purpose of this article is to reveal how much work has been done, what knowledge has been obtained, and what directions need to be taken for future FDI in Africa research. We conduct a systematic literature review of pertinent theoretical and empirical studies encompassing 105 articles from reputable management and economics journals on FDI in Africa. Our study contributes to this body of scholarship by identifying and discussing prior research, agglomerating them into themes, providing a structured debate about what is already known, as well as offering an explanation of why and how Africa is a distinctive context different from other emerging markets. We further develop an integrative framework that provides extensive knowledge of contemporary and promising avenues for future research.},

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{el-amrani_3849,

title = {Mathematical modelling and simulation of reactive fluids with cross diffusion and Arrhenius activation energy},

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

url = {http://dx.doi.org/10.1007/s40314-025-03353-1},

year  = {2025},

date = {2025-08-01},

journal = {Computational & Applied Mathematics},

volume = {44},

number = {8},

pages = {393},

abstract = {A wide spectrum of natural phenomena and industrial processes involve the propagation of reaction fronts in a viscous fluid medium. Consistent models of this class of problems should account for the competition between the flow dynamics and the reaction properties related to temperature and degree of conversion. In the present study, to resolve these features in reactive flows, we consider the incompressible Navier-Stokes equations with temperature-dependent viscosity for the velocity and pressure coupled with a double system of reaction-advection-diffusion equations for the temperature and the degree of conversion. The reactions in this coupled system are assumed to be generated using the Arrhenius activation energy and cross diffusion coefficients are influenced by both the temperature and degree of conversion. We analyze the solvability of the proposed model and prove existence of the weak solution using a Galerkin approach combined with appropriate compactness arguments. The uniqueness of the solution is also achieved under additional assumptions on the problem data. In the current work, we also introduce a time-marching scheme for the numerical approximation of the continuous problem and prove the unconditional stability with respect to the time step. Numerical results are presented for a problem with exact solutions to verify the theoretical analysis and to assess the performance of the numerical method. The coupled system is also employed to solve a two-dimensional flame-like propagation problem in viscous fluids. The computational results obtained for both examples support the theoretical expectations for a stable and accurate numerical solver for reactive fluids with cross diffusion and Arrhenius activation energy.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nasir_3862,

title = {A study on the dynamics of government-university-industry knowledge transfer in emerging knowledge-based economies},

author = {Nayab Nasir and Sarwar M. Azhar and Muhammad Ishtiaq ISHAQ and Iqra Shafqat},

url = {http://dx.doi.org/10.1093/scipol/scaf038},

year  = {2025},

date = {2025-08-01},

journal = {Science And Public Policy},

volume = {00},

pages = {1-11},

abstract = {This article is drawn from a more extensive study on the dynamics of government-university-industry knowledge transfer in an emerging

knowledge-based economy (KBE). Pragmatism was used as the fundamental philosophical tenet for this research, as the grounded theory

approach was applied to identify the barriers and challenges that hinder the progress of universities consequently offering pragmatic solutions.

Participants were selected using theoretical sampling technique who responded to questions addressing the performance of key entities in

the triple helix framework of Pakistan. The dominant themes that emerged after data saturation included (1) perception of a KBE, (2) building

knowledge-transfer channels, (3) efficiency of knowledge-transfer activities, and (4) knowledge co-creation spaces. These domains aided in

developing a model for building sustainable knowledge co-creation spaces, with implications for policymakers to facilitate higher education

institutions in improving their performance in the triple helix framework of developing countries.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{ul-ain_3865,

title = {Measuring the success of business intelligence and analytics systems: A literature review},

author = {Noor Ul-Ain and William H. DeLone and Giovanni Vaia},

url = {http://dx.doi.org/10.1016/j.technovation.2025.103277},

year  = {2025},

date = {2025-08-01},

journal = {Technovation},

volume = {146},

pages = {103277},

abstract = {Technology-based solutions such as business intelligence and analytics (BI&A) systems have become indispensable for organizations due to their ability to support decision-making. Recent developments in big data availability and more powerful analytical tools have increased the potential value of BI&A systems. However, academic and practitioner-oriented research suggests that the potential success of BI&A systems has not yet been fully realized by most organizations. Existing studies have attempted to evaluate the effectiveness and success of BI&A systems by proposing various success measures. However, these studies have generated inconsistent results, limiting the ability to compare and generalize the findings. Therefore, this study takes a step forward by proposing an updated, comprehensive, and consolidated set of success measures for this unique class of information systems. Using a systematic literature review approach, this study examined and synthesized BI&A systems success measures across 173 past studies using the DeLone & McLean IS success framework. Findings revealed success measures such as ease of use, information accuracy, and financial performance that are consistently applied to the measurement of BI&A systems, and importantly, other recommended measures such as system features, presentation format, and decision-making performance that are uniquely important to BI&A systems but infrequently applied. Finally, a comprehensive set of BI&A success measures is proposed for future empirical research studies and practitioner use.},

note = {demande du PDF le 05/09/2025},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pairolero_3853,

title = {Closing the Gender Gap in Patenting: Evidence from a Randomized Control Trial at the USPTO},

author = {Nicholas Pairolero and Andrew Toole and Peter-Anthony Pappas and Charles de Grazia and Mike Teodorescu},

url = {http://dx.doi.org/10.1257/pol.20230253},

year  = {2025},

date = {2025-08-01},

journal = {American Economic Journal-Economic Policy},

volume = {17},

number = {3},

pages = {281-310},

abstract = {Analyzing a randomized control trial at the United States Patent and Trademark Office that was designed to provide additional help to applicants who do not have legal representation, we find heterogeneous causal impacts across inventor gender, driven primarily by an increase in successful negotiations by women inventor teams via the use of examiner's amendments. While both men and women applicants benefited, the probability of obtaining a patent was over 12 percentage points greater for women. Our results suggest that a portion of the gender gap in patenting could be eliminated through additional assistance during patent examination.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{antonin_3851,

title = {Researchers of a Feather Flock Together: Endogamy Recruitment Tracks for Industrial Researchers},

author = {Céline Antonin and Pierre COURTIOUX},

url = {https://onlinelibrary.wiley.com/doi/10.1111/labr.70003},

year  = {2025},

date = {2025-08-01},

journal = {Labour: Review of Labour Economics and Industrial Relations},

abstract = {Based on French company data, we assess the hiring of different education profiles of industrial researchers in corporate R&D

departments. First, our results show engineers are more likely to be recruited in corporate R&D that develops a patent-oriented

strategy; PhD-holders

are more likely to be recruited in firms that compete at the technological frontier and in companies that

maintain close links with academia and public research. Second, new results reveal the endogamy of industrial researchers'

recruitment based on the specifics of their scientific human capital and highlight the mitigating role of hybrid scientific human

capital.},

note = {Revue ABS 1 2018, 2021 et 2024},

keywords = {},

pubstate = {online},

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{benjelloun_3848,

title = {Homogenization of two-dimentional materials in the Thomas-Fermi-von Weizsäcker theory},

author = {SAAD BENJELLOUN and Salma Lahbabi and Abdelqoddous Moussa},

url = {http://dx.doi.org/10.1063/5.0191472},

year  = {2025},

date = {2025-07-01},

journal = {Journal Of Mathematical Physics},

volume = {66},

number = {7},

pages = {072106},

abstract = {We study the homogenization of the Thomas-Fermi-von Weizsäcker (TFW) model for two-dimentional (2D) materials introduced in [Blanc and Le Bris, Adv. Differ. Equations 5, 977-1032 (2000)]. It consists in considering 2D-periodic nuclear densities with periods going to zero. We study the behavior of the corresponding ground state electronic densities and ground state energies. The main result is that these three-dimensional problems converge to a limit model that is one dimensional, similar to the one proposed in [Gontier et al., Commun. Math. Phys. 388, 1475-1505 (2021)]. We also illustrate this convergence with numerical simulations and estimate the converging rate for the ground state electronic densities and the ground state energies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{platania_3857,

title = {Harnessing the Power of AI in RD&E Management: The Innovation Index},

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

url = {https://ieeexplore.ieee.org/abstract/document/11072517},

year  = {2025},

date = {2025-07-01},

journal = {Ieee Transactions On Engineering Management},

volume = {72},

pages = {3055 - 3064},

abstract = {This article investigates the complex relationship between artificial intelligence (AI)-related technological innovation and its impact on the market returns of leading technology companies. We introduce the ?Innovation Index,? a latent variable based on the number of AI-related patents, and incorporate it into the traditional Fama-French model to better capture the influence of AI advancements on financial performance. Using a state-space representation, our empirical analysis suggests that AI-related innovation significantly contributes to the market returns of prominent and leading technology firms. The findings highlight the strategic importance of AI investments in sustaining long-term growth and competitiveness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{khan_3827,

title = {Climate Change Initiatives, Environmental Management Training, and Firm Performance: The Trickle?Down Effect of Board?Level Gender Diversity on Gender Diversity in the top Management Team},

author = {Mushtaq Hussain Khan and Inam Ul Haq and Muhammad Umer Azeem and Abdul Ghafoor},

url = {http://dx.doi.org/10.1002/bse.70061},

year  = {2025},

date = {2025-07-01},

journal = {Business Strategy And The Environment},

abstract = {We examine the interrelationships among climate change initiatives, environmental management training, and firm performance while considering the trickle-down effect of board-level gender diversity on gender diversity in the top management

team (TMT). Using an unbalanced panel dataset of 117,410 firm-year observations from five regions, representing 11 industries

and operating in 71 countries from 2013 to 2022, our findings reveal that climate change initiatives significantly enhance firm

performance. Our results further exhibit that the interaction effects of gender diversity at the board and TMT levels (the trickledown effect) support climate change initiatives by encouraging environmental management training (EMT), thereby improving

firm performance. To address the potential endogeneity issues, we employed a two-step system generalized method of moments

(GMM) approach. Our empirical results are robust to endogeneity and alternative measures. Overall, our evidence supports the

Resource-Based View Theory and Upper Echelon Theory to demonstrate how a diverse TMT and board members can contribute

to more robust climate change strategies by using EMT as a resource to achieve performance objectives. Hence, we make important contributions to the corporate governance and environmentalism strands of the literature by highlighting the role of gender

in shaping climate change initiatives and influencing firm performance.},

keywords = {},

pubstate = {online},

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}

}