Publication

@article{thatte_4055,

title = {The PAH 3.4 micron feature as a tracer of shielding in the Orion Bar and NGC 6240},

author = {Niranjan Thatte and Dimitra Rigopoulou and Fergus R Donnan and Ismael Garcia-Bernete and Miguel Pereira-Santaella and Bruce Draine and Oscar Veenema and Bouthéïna Kerkeni and Almudena Alonso-Herrero and Hermosa Muñoz Laura and Gabriela Speranza},

url = {https://doi.org/10.1093/mnras/staf2047},

year  = {2026},

date = {2026-11-01},

journal = {Monthly Notices Of The Royal Astronomical Society},

volume = {545},

number = {1},

pages = {1-10},

abstract = {We have carried out a detailed analysis of the 3.4 ?m spectral feature arising from Polycyclic Aromatic Hydrocarbons (PAH),

using James Webb Space Telescope archival data. For the first time in an external galaxy (NGC 6240), we have identified two

distinct spectral components of the PAH 3.4 ?m feature: a shorter wavelength component at 3.395 ?m, which we attribute to

short aliphatic chains tightly attached to the aromatic rings of the PAH molecules; and a longer wavelength feature at 3.405 ?m

that arises from longer, more fragile, aliphatic chains that are weakly attached to the parent PAH molecule. These longer chains

are more easily destroyed by far-ultraviolet photons (>5 eV) and PAH thermal emission only occurs where PAH molecules

are shielded from more energetic photons by dense molecular gas. We see a very strong correlation in the morphology of the

PAH 3.395 ?m feature with the PAH 3.3 ?m emission, the latter arising from robust aromatic PAH molecules. We also see an

equally strong correlation between the PAH 3.405 ?m morphology and the warm molecular gas, as traced by H2 vibrational

lines. We show that the flux ratio PAH 3.395/PAH 3.405 < 0.3 corresponds strongly to regions where the PAH molecules are

shielded by dense molecular gas, so that only modestly energetic UV photons penetrate to excite the PAHs. Our work shows that

PAH 3.405 ?m and PAH 3.395 ?m emission features can provide robust diagnostics of the physical conditions of the interstellar

medium in external galaxies, and can be used to quantify the energies of the photon field penetrating molecular clouds.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{xiao_4539,

title = {Enhancing semi-supervised multi-view graph convolutional networks via supervised contrastive learning and self-training},

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

url = {https://doi.org/10.1016/j.knosys.2026.116500},

year  = {2026},

date = {2026-09-01},

journal = {Knowledge-Based Systems},

volume = {349},

pages = {116500},

abstract = {The advent of graph convolutional network (GCN)-based multi-view learning provides a powerful framework for integrating structural information from heterogeneous views, enabling effective modeling of complex multi-view data. However, existing methods often fail to fully exploit the complementary information across views, leading to suboptimal feature representations and limited performance. To address this, we propose MV-SupGCN, a semi-supervised GCN model that integrates several complementary components with clear motivations and mutual reinforcement. First, to better capture discriminative features and improve model generalization, we design a joint loss function that combines Cross-Entropy loss with Supervised Contrastive loss, encouraging the model to simultaneously minimize intra-class variance and maximize inter-class separability in the latent space. Second, recognizing the instability and incompleteness of single graph construction methods, we combine both KNN-based and semi-supervised graph construction approaches on each view, thereby enhancing the robustness of the data structure representation and reducing generalization error. Third, to effectively utilize abundant unlabeled data and enhance semantic alignment across multiple views, we propose a unified framework that integrates contrastive learning in order to enforce consistency among multi-view embeddings and capture meaningful inter-view relationships, together with pseudo-labeling, which provides additional supervision applied to both the cross-entropy and contrastive loss functions to enhance model generalization. Extensive experiments demonstrate that MV-SupGCN consistently surpasses state-of-the-art methods across multiple benchmarks, validating the effectiveness of our integrated approach.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{xiang_4433,

title = {An adaptive-weighted multi-level feature evidence and redundancy penalty method},

author = {Feng Xiang and Chunxiao Xing and Ye Ai and Zhiqiang Wang},

url = {https://doi.org/10.1016/j.engappai.2026.115245},

year  = {2026},

date = {2026-09-01},

journal = {Engineering Applications Of Artificial Intelligence},

volume = {180},

pages = {115245},

abstract = {Aiming to improve quality indicator prediction for the tobacco drying process in a cigarette factory, this study proposes an adaptive-weighted multi-level feature evidence and redundancy-penalty framework (F-XMF). To alleviate the limitations of isolated feature evaluation in complex industrial data, F-XMF jointly considers the direct contribution of individual features, the contribution of feature interactions, and the redundant dependency among candidate features. First, eXtreme Gradient Boosting (XGBoost) is used to estimate the importance of individual features and obtain an initial main-effect feature subset. Meanwhile, an Attentional Factorization Machine (AFM) is employed to identify high-contribution second-order interactions and derive interaction-related evidence. On this basis, conditional mutual information (CMI) is introduced to characterize redundant dependency among candidate features, and a Differential Redundancy Penalty Mechanism is further developed to impose differentiated penalties on highly overlapping features while preserving informative variables with meaningful interaction utility. Finally, a validation-based adaptive weight fusion strategy is used to integrate the main-effect subset and the interaction-related subset, yielding a compact and informative final feature subset. Experimental results on real tobacco-processing data show that F-XMF consistently reduces Mean Absolute Error (MAE) in ablation comparisons and achieves superior performance against multiple representative baseline methods. Mechanism validation further demonstrates that the proposed framework can effectively refine the candidate subset through interaction enhancement and redundancy suppression, showing good interpretability and practical value for outlet moisture content prediction in the tobacco drying process.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{vanaei_4463,

title = {Stereolithography-fabricated type IV hydrogen storage tank liners: Multi-scale characterization of photopolymer resin and structural validation under internal pressure},

author = {Hamidreza Vanaei and Albert Lucas and Mohammadali Rastak and Jérôme Fortineau and Abbas Tcharkhtchi},

url = {https://doi.org/10.1016/j.est.2026.123019},

year  = {2026},

date = {2026-09-01},

journal = {Journal Of Energy Storage},

volume = {172},

pages = {123019},

abstract = {Improving the fabrication flexibility and performance of polymer liners for Type IV compressed hydrogen storage vessels is a critical challenge for the wider deployment of hydrogen fuel cell vehicles. This study establishes, for the first time, the technical feasibility of stereolithography (SLA) as an alternative to rotational molding for manufacturing Type IV liner components using a polyacrylic-based photopolymer resin (Resin Black V4). The effects of build orientation (0°, 30°, 45°, 60° and 90°) and post-processing conditions (UV curing at room temperature, 60°C and 80°C) on mechanical, thermal, viscoelastic and fatigue properties were systematically characterized. Significant orientation-dependent anisotropy was observed, with tensile strength decreasing 13% and compressive modulus decreasing 72% from 0° to 90°. UV+60°C post-curing achieved 74.5±1.2 MPa tensile strength with 7.7% ductility and fatigue endurance up to 10? cycles at 15 MPa. UV+80°C induced embrittlement despite higher static strength (79.9±1.6 MPa), significantly reducing fatigue life. Dynamic mechanical analysis showed glass transition temperature increases of up to 35°C after post-curing. Ultrasonic testing confirmed approximately 30% elastic constant enhancement and 30% attenuation reduction, establishing a non-destructive quality control pathway for SLA-fabricated components. Tsai-Hill and Tsai-Wu failure criteria predicted orientation-dependent strength with deviations below 6%. Finite element analysis validated against experimental air burst testing on scaled prototype tanks with 1, 3 and 6 mm wall thicknesses confirmed that predicted failure and survival outcomes agreed with experimental observations across all cases. UV+60°C post-processing emerges as optimal by balancing strength, toughness and fatigue resistance, establishing stereolithography as a viable fabrication route for Type IV hydrogen storage liners.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{wladdimiro_4216,

title = {A Multi-Model Predictive Framework for Adaptive Resource Management in Stream Processing Systems},

author = {Daniel Wladdimiro and Nicolás Hidalgo and Alessio Pagliari and Luciana Arantes and Pierre Sens and Erika Rosas and Victor Reyes},

url = {https://doi.org/10.1016/j.future.2026.108461},

year  = {2026},

date = {2026-09-01},

journal = {Future Generation Computer Systems-The International Journal Of Escience},

volume = {182},

pages = {108461},

abstract = {Stream Processing Systems (SPSs) are designed to process continuous streams of events, often under highly variable input rates. Although prior work has explored dynamic operator replication, many existing approaches lack generalizability and perform suboptimally across diverse scenarios. In this article, we present MMP-SPS, a predictive self-adaptive framework that extends extends our prior PA-SPS system by introducing a multi-window control loop, support for multiple prediction models, and online model selection via RMSE-based evaluation and multi-armed bandits. Targeting environments with high-volume and fluctuating data streams, such as social media analytics and network traffic monitoring, the framework dynamically selects the most suitable model based on real-time workload characteristics using a reinforcement learning (RL) strategy. To prove the validity of our system, we deployed an implementation of MMP-SPS based on Apache Storm, and we evaluated it on Google Cloud Platform against real-world datasets. Experimental results show substantial improvements in latency, throughput, and resource utilization compared to static and single-model baselines. These findings underscore the potential of multi-model predictive adaptation for scalable and robust stream processing under dynamic conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{el-amrani_4455,

title = {A consistent viscosity-splitting method for the Navier-Stokes equations with pressure boundary conditions},

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

url = {https://doi.org/10.1016/j.cma.2026.119063},

year  = {2026},

date = {2026-08-01},

journal = {Computer Methods In Applied Mechanics And Engineering},

volume = {458},

pages = {119063},

abstract = {The incompressible Navier-Stokes equations equipped with classical boundary conditions have been extensively studied from both theoretical and numerical perspectives, and a wide variety of fractional-step and splitting methods have been developed to reduce their computational complexity. However, in many realistic flow configurations, standard boundary conditions are inadequate to accurately represent the physical behavior at open or artificial boundaries, where mixed or pressure-based conditions are more appropriate. Despite their practical relevance, such unconventional boundary conditions have received comparatively little attention in the design and analysis of consistent splitting schemes. In the present work, we propose a class of viscosity-splitting schemes for the incompressible Navier-Stokes equations subject to non-standard boundary conditions. In particular, the velocity is prescribed in a Dirichlet sense on a portion of the boundary, while on the complementary part the tangential velocity together with the total pressure is imposed. The proposed schemes are constructed to ensure consistency with the continuous problem and to properly account for prescribed pressure on the boundary. To enhance mass conservation and improve numerical robustness, a grad-div stabilization term is incorporated into the formulation. The convergence and accuracy properties of the resulting methods are assessed using a series of numerical examples, which demonstrate their effectiveness in handling pressure boundary conditions and confirm the expected convergence behavior. These results indicate that the proposed viscosity-splitting approach provides a reliable and efficient method for the simulation of incompressible flows with physically relevant, non-standard boundary conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{barletti_4279,

title = {Trend to equilibrium of the Wigner function describing a quantum particle subject to decoherence},

author = {Luigi Barletti and Francesco Salvarani},

url = {https://doi.org/10.1016/j.aml.2026.109944},

year  = {2026},

date = {2026-08-01},

journal = {Applied Mathematics Letters},

volume = {179},

pages = {109944},

abstract = {This paper studies the long-time behavior of a spatially homogeneous Wigner equation describing a quantum particle subject to decoherence. The model extends the classical Wigner-Fokker-Planck equation by including a general decoherence term derived from microscopic collision mechanisms. An explicit representation of the equilibrium state is obtained, and a

necessary and sufficient condition ensuring that the equilibrium state belongs to ?2 is established, highlighting the balance between friction and decoherence. Under suitable assumptions on the initial data, exponential convergence in L2 toward equilibrium is rigorously proved.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{el-amrani_4082,

title = {Well-posedness of coupled Navier-Stokes and advection-diffusion equations for propagation of reaction fronts in viscous fluids},

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

url = {https://doi.org/10.1016/j.cam.2025.117277},

year  = {2026},

date = {2026-08-01},

journal = {Journal Of Computational And Applied Mathematics},

volume = {481},

pages = {117277},

abstract = {In this paper, we investigate a steady system used for modelling propagation of reaction fronts in viscous fluids subject to a generalized Arrhenius law. The model consists of the incompressible Navier-Stokes equations for the fluid flow and a set of advection-diffusion equations for the temperature and degree of conversion. The resulting system is strongly coupled and presents many additional nonlinearities as the physical parameters such as the viscosity, diffusion and source terms are assumed to depend on the temperature and/or degree of conversion. Using a fixed-point method we prove the existence and uniqueness of the weak solution for the considered problem. To solve the associated fixed-point problem we consider an iterative scheme and its convergence is also studied in the present study. Here, the proposed scheme uncouples the computation of velocity, temperature and degree of conversion using the fixed-point iteration and we theoretically establish its convergence towards the unique solution of the considered model. Numerical results obtained for two test examples are presented to verify the theoretical analysis and to assess the performance of the proposed algorithm. The obtained computational results for both examples support the theoretical expectations for a good numerical convergence with the developed estimates.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{makhlouf_4535,

title = {The impact of TQM and GHRM practices on organizational agility: a dual-mediation pathway Available to Purchase},

author = {Hamdi Makhlouf and Lassaad Lakhal and Faten Lakhal},

url = {https://doi.org/10.1108/IJQRM-11-2025-0410},

year  = {2026},

date = {2026-07-01},

journal = {International Journal of Quality and Reliability Management},

pages = {1-32},

abstract = {Purpose - This study examines the relationships among total quality management (TQM) practices, green

human resource management (GHRM) practices, knowledge sharing (KS), and organizational agility (OA)

within the context of a developing country. It further investigates two underexplored mediation mechanisms: (1)

the mediating role of GHRM in the relationship between TQM and knowledge sharing, and (2) the mediating

role of knowledge sharing in linking both TQM and GHRM practices to OA.

Design/methodology/approach - This study is based on a structured survey questionnaire used to collect data

from 154 Tunisian manufacturing firms. We used a partial least squares structural equation modelling (PLS-

SEM) to test our hypotheses.

Findings - The results show that TQM practices positively impact both GHRM and OA. Furthermore, GHRM

practices positively influence knowledge sharing. However, there are no significant relationships between TQM

practices and knowledge sharing and between GHRM practices and OA. The results regarding the mediating

effects show that GHRM practices fully mediate the relationship between TQM and knowledge sharing.

Simultaneously, knowledge sharing serves as a partial mediator of the relationship between TQM and OA, and

as a full mediator between GHRM and OA.

Research limitations/implications - The results of this study are specific to manufacturing companies in

Tunisia and may not be generalizable to other sectors (e.g. services) or countries. Nevertheless, the findings

provide valuable insights for manufacturing managers in Tunisia.

Originality/value - Theoretically, the study extends the RBV by identifying GHRM as the micro-level

mechanism through which TQM generates green strategic capabilities, and advances KBV by demonstrating

that agility in emerging economies is socially activated through knowledge sharing rather than structurally

determined},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{nizar_4534,

title = {The Dark Cloud of Uncertainty: Strategic CSR Responses to Economic Policy Uncertainty},

author = {Hamza Nizar and Taher Hamza and Faten Lakhal and Hajer Jarrar},

url = {https://doi.org/10.1002/jsc.70103},

year  = {2026},

date = {2026-07-01},

journal = {Strategic Change},

pages = {1-18},

abstract = {This paper examines how firms adjust Corporate Social Responsibility (CSR) engagement as part of broader processes of strategic change under Economic Policy Uncertainty (EPU), using a large cross-country panel from 2010 to 2018. We frame this adjustment as a managerial trade-off between preserving strategic flexibility and maintaining stakeholder relationships in uncertain environments. Drawing on real options theory and strategic growth options theory, we develop competing predictions regarding firms' CSR responses to uncertainty. Our findings show that higher EPU leads to a strategic retrenchment in CSR engagement, supporting the real options perspective. However, this effect is not uniform across firms. It is significantly stronger among financially constrained firms, firms operating in highly competitive environments, and firms exposed to elevated climate risk, highlighting important boundary conditions of strategic change. Robustness tests, including alternative CSR measures and endogeneity checks, confirm the stability of the results. By conceptualizing CSR as a dynamic domain of strategic adjustment rather than a static attribute, this study contributes to the strategic change literature by explaining how firms recalibrate non-market strategies and long-term commitments in response to macroeconomic uncertainty.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{ghorbel_4371,

title = {Mechanical behavior of apatite-alumina coatings deposited by high-velocity oxy-fuel spray (SHVOF): Prosthesis application},

author = {Halima Ghorbel and Radouane Akrache and Jinan Charafeddine and Awatef Guidara},

url = {https://doi.org/10.1016/j.nxmate.2026.102076},

year  = {2026},

date = {2026-07-01},

journal = {Next Materials},

volume = {12},

pages = {102076},

abstract = {Alumina-fluorapatite (Al?O?-Fap) composite coatings deposited on 316?L stainless steel by Suspension High-Velocity Oxy-Fuel (SHVOF) spraying were investigated as candidate surfaces for prosthetic applications. Compared with conventional atmospheric plasma spraying (APS), SHVOF processing is known to produce denser coatings with improved adhesion, which is of interest for load-bearing biomedical interfaces. In this study, low fluorapatite contents (0-1?wt%) were incorporated into an alumina matrix to explore their influence on coating mechanical behavior. The coatings were characterized in terms of surface roughness, adhesion strength, and elastic properties. The results indicate that the addition of fluorapatite modifies the coating morphology and leads to an increase in surface roughness (Ra from ?1.7 to ?3.1 ?m), while maintaining adhesion values within the range reported for thermally sprayed bioceramic coatings. An increase in elastic modulus was also observed, from 59.7?GPa for pure alumina to 98.3?GPa for Al?O?-Fap (1?wt%), corresponding to an increase of approximately 64%, indicating a marked modification of the coating mechanical response. In parallel, a three-dimensional finite element (FE) model of a cylindrical 316?L implant inserted into cortical bone was developed using Abaqus/CAE to simulate the early stage of implantation. The model was used to evaluate von Mises stresses and contact pressures at the bone-implant interface. The simulations predict von Mises stresses of approximately 48?MPa and contact pressures ranging from 25 to 55?MPa during insertion, values consistent with those reported for cortical bone under similar conditions. However, these results depend on simplifying assumptions, including linear elastic and isotropic bone behavior and the absence of an explicit coating layer. Overall, this combined experimental-numerical approach provides quantitative insight into the effect of low fluorapatite additions on the mechanical performance of SHVOF-deposited alumina coatings. The results suggest that such coatings may contribute to improved mechanical compatibility at the implant interface, although further biological and in vivo investigations are required to confirm their clinical relevance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{shahab_4308,

title = {Do green firms select and terminate supply chain partners based on sustainability criteria? International evidence},

author = {Yasir Shahab and Ammar Ali Gull and Muzhar Javed and Tanveer Ahsan},

url = {https://doi.org/10.1016/j.ijpe.2026.110000},

year  = {2026},

date = {2026-07-01},

journal = {International Journal Of Production Economics},

volume = {297},

pages = {110000},

abstract = {The ?United Nations Global Compact? reiterates how important supply chain processes are for reaching sustainable growth targets. It points out that only eight supply chains contribute more than half of the world's greenhouse gas emissions. Thus, management of suppliers becomes crucial to meeting these goals. However, how green firms select and terminate their suppliers in response to mounting pressure of sustainability remains an area yet to be explored in operations management. To address these concerns, we investigate the data of listed firms from 38 countries over the 2002 to 2019 time-period. The results show that eco-friendly firms are more sensitive to sustainability practices of their suppliers while offering or terminating their contracts. Surprisingly, the stringency of environmental policy negatively moderates this relationship due to the substitution effect. Finally, we document that eco-innovative firms experience an increase in their market value when they select or terminate their supply chain partners based on sustainability criteria. The results offer vital theoretical and policy insinuations for the discipline of sustainable operations and supply chain management.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{naouar_4250,

title = {Empowering Women on Boards: Gender Quotas and Waste Generation},

author = {Hind Naouar and Faten Lakhal},

url = {https://doi.org/10.1111/gwao.70112},

year  = {2026},

date = {2026-07-01},

journal = {Gender Work And Organization},

volume = {33},

number = {4},

pages = {1210-1226},

abstract = {With the growing emphasis on sustainability in corporate governance, implementing quotas to increase gender diversity on boards has attracted attention because of its potential to promote more responsible environmental practices, including waste management. The purpose of this paper is to explore the role of gender quotas in the boardroom on waste generation for a sample of European listed companies from 2011 to 2021. Based on critical mass and institutional theory perspectives, the results show that gender quotas on boards have a significant negative effect on waste generation. This negative effect increases in countries with binding quotas, suggesting that firms operating in countries with binding gender quotas capitalize on the potential for improved environmental outcomes. Further results show that the negative relationship between gender quotas and waste generation is more prevalent following the Paris Agreement on climate change and the adoption of the Sustainable Development Goals (SDGs) in 2015, in firms with corporate social responsibility (CSR) committees and in firms operating in manufacturing industries.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{benmoussa_4110,

title = {On the well-posedness of the unsteady velocity-vorticity-helicity formulation of the Navier-Stokes equations},

author = {K. Benmoussa and Jean Deteix and Driss Yakoubi},

url = {https://doi.org/10.1016/j.jmaa.2026.130421},

year  = {2026},

date = {2026-07-01},

journal = {Journal Of Mathematical Analysis And Applications},

volume = {559},

number = {1},

pages = {130421},

abstract = {In this paper, we study the three-dimensional velocity-vorticity helicity (VVH) formulation modeling the flow of incompressible Newtonian fluids. We present an analysis of the formulation that encompasses the existence and regularity of solutions, providing a rigorous functional framework in which the VVH formulation is shown to be equivalent to the more traditional velocity-pressure formulation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{subhra_chatterjee_4543,

title = {The Impact of Generative AI Servitization on Reward Mix Evaluation: The Equivocal Role of Job Demand and Job Resource},

author = {Rajat Subhra Chatterjee and Pavol Durana and Roman Blazek and Md Asadul Islam and Ranjan Chaudhuri and Sheshadri Chatterjee},

url = {https://doi.org/10.1002/jsc.70081},

year  = {2026},

date = {2026-06-01},

journal = {Strategic Change},

pages = {1-17},

abstract = {The advent of generative AI has permeated industries, with its direct impact on employees' jobs and work performance widely 

anticipated. Although studies have examined the cognitive and psychological impact of AI- embedded servitization, the evalu

ation of employees' rewards in relation to their organizational job- oriented perceptivity has received very little attention. This 

is critical, especially for small and medium- sized enterprises, where rewards significantly impact employee performance. The 

current study addresses this issue through a modular design that measures the direct and indirect effects of job- oriented positive 

and negative factors on employees' evaluation of their reward mix. The study draws on a combined theoretical background in 

digital servitization theory and the job demands-resources (JD-R) theory to examine the direct impact of generative AI imple

mentation on reward evaluation and the effect of job demand-  and job resource- oriented factors on this relationship. The survey 

method was used, and responses were collected from 329 manufacturing- based SMEs. The data analysis was conducted using 

structural equation modeling. The results showed a significant impact of the direct and moderate hypotheses on employees' eval

uation of perceived complexity in the reward mix. However, it also shows that perceptivity towards acquired job independence 

does not significantly affect the relationship between the serviceization and reward mix evaluation. The study provides several 

new contributions from conceptual, theoretical, and managerial perspectives. It extends the conceptualization of job demand- 

resources theory through the pioneer model design, which integrates digital servitization to examine the impact of generative 

AI implementation. It equips the SME managerial fraternity with a practical understanding of reward mix evaluation. The study 

provides new managerial implications for servitization and job design to enable a more effective reward orientation for organi

zational staff.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{lebon_4518,

title = {A computer-aided manufacturing tool for analyzing the tool-workpiece contact during the micro grinding of dental prostheses},

author = {Nicolas Lebon and Laurent Tapie},

url = {https://doi.org/10.21203/rs.3.rs-9860168/v1},

year  = {2026},

date = {2026-06-01},

journal = {International Journal Of Advanced Manufacturing Technology},

abstract = {Dental CAD/CAM manufacturing predominantly relies on three-axis milling strategies, which impose geometric and kinematic constraints that influence machining conditions and prosthesis quality. This study investigates tool-workpiece contact configurations and effective grinding speed variations during the micro-grinding of dental prostheses. Two abrasive burs were geometrically characterized and modeled using an APT-based analytical formalism. The resulting models enabled the determination of local contact conditions and effective grinding speeds on freeform crown geometries.

The methodology was implemented on a clinical dental crown model to evaluate the spatial distribution of tool engagement, grinding speed, and machining accessibility. Results showed that, regardless of tool geometry, machining is performed almost exclusively by the hemispherical tip of the bur, while conical and cylindrical sections contribute marginally. Consequently, effective grinding speed exhibits strong spatial variability driven mainly by local surface orientation. The lowest speeds occur at cusp tips, whereas higher values are observed along peripheral regions, suggesting significant variations in surface integrity, roughness, and tool wear across the prosthesis.

A curvature-based accessibility analysis revealed that 40,1% of the crown surface is inaccessible under three-axis machining constraints, particularly within anatomically important grooves and fossae. Because these regions contribute to food guidance, fragmentation, and occlusal contact distribution during mastication, their incomplete reproduction may compromise the functional anatomy of the restoration and reduce masticatory efficiency.

These findings demonstrate the strong coupling between prosthesis geometry, tool design, and machining kinematics, highlighting the need for advanced manufacturing strategies, such as multi-axis machining, to improve accessibility, preserve functional morphology, and enhance prosthesis performance.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{boukhari_4538,

title = {H-ARN: A holo-attentive relational network for holistic facial beauty prediction via distribution learning},

author = {Djamel Boukhari and Fadi Dornaika and Jinan Charafeddine},

url = {https://doi.org/10.1007/s13735-026-00401-2},

year  = {2026},

date = {2026-06-01},

journal = {International Journal Of Multimedia Information Retrieval},

volume = {15},

number = {3},

pages = {20},

abstract = {Facial Beauty Prediction (FBP) remains a significant challenge in computer vision, primarily due to the inherent subjectivity

of human perception and the difficulty in modeling the holistic harmony of facial features. Existing deep learning models,

typically based on Convolutional Neural Networks (CNNs), often regress a deterministic score and struggle to surpass

a performance plateau. In this work, we propose the Holo-Attentive Relational Network (H-ARN), a novel architecture

designed to overcome these fundamental limitations. H-ARN makes two primary contributions: (1) It pioneers the use of

distribution learning by predicting the mean and variance of beauty scores, employing a Gaussian Negative Log-Likelihood

loss to robustly model the subjectivity and ambiguity in training data. (2) It introduces a relational self-attention module

atop a powerful Vision Transformer (ViT) backbone, explicitly learning the complex, long-range relationships between facial

components that define aesthetic harmony. Evaluated on the challenging SCUT-FBP5500 benchmark, our proposed H-ARN

achieves a new state-of-the-art Pearson Correlation of 0.9333, significantly outperforming previous methods. The code will

be made publicly available upon publication https://github.com/DjameleddineBoukhari/H-ARN.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{maroun_4537,

title = {A Global-Context Vision Transformer for Facial Age Estimation},

author = {Ghaby Maroun and Salah Eddine Bekhouche and Jinan Charafeddine and Fadi Dornaika},

url = {https://doi.org/10.1007/s12559-026-10605-7},

year  = {2026},

date = {2026-06-01},

journal = {Cognitive Computation},

volume = {18},

number = {1},

pages = {72},

abstract = {Estimating a person's age from a single facial image remains challenging because ageing cues are subtle, non-linear, and

easily confounded by identity, pose, illumination, and demographic factors. In this work, we investigate the suitability of

the Global Context Vision Transformer (GC-ViT), originally introduced for general vision tasks, as a pure transformer

backbone for facial age estimation. We extend GC-ViT to scalar age regression through a lightweight MLP head and

a task-specific training strategy, with the emphasis placed on a targeted reformulation of the architecture for facial age

estimation and on its comprehensive empirical validation in this setting. GC-ViT is well suited to age estimation because

it combines short-range window self-attention with long-range global attention, enabling a single hierarchical transformer

to capture both fine texture cues (e.g., wrinkles) and global facial proportions. To improve robustness under limited data,

we introduce an age-aware region replacement augmentation that replaces semantically defined facial regions with age-

proximal donor content, or with self-flipped target content, and blends them using a feathered mask together with area-

proportional soft label interpolation in donor mode. Training uses an ablation-validated composite regression loss (MAE

with a secondary stabilising term, MSE or SmoothL1 depending on the dataset). We evaluate on MORPH II, IMDB-Clean,

AFAD, and UTKFace, reporting MAE together with Pearson correlation and cumulative scores (CS@5/CS@10). Our GC-

ViT achieves an MAE of 2.41 on MORPH II, 3.11 on AFAD, and 4.26 on UTKFace (the latter two obtained by fine-tuning

from IMDB-Clean pretraining), while also being assessed under zero-shot cross-dataset transfer to quantify domain shift

and out-of-domain generalization. Overall, the results show that an adapted local-global attention transformer, trained

with targeted augmentation and a stable regression objective, can serve as a strong transformer-based baseline for facial

age estimation without auxiliary CNN branches or test-time post-processing.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{khafaga_4498,

title = {An Integrated NB-IoT/5G Architecture Leveraging Fabry-Perot Optical Sensors for Enhanced Energy Efficiency and Coverage},

author = {Ali Salah Mahdi Khafaga and Dhurgham Ali Saeed ALRasheed and Wafaa M. R. Shakir and Jinan Charafeddine},

url = {https://doi.org/10.48084/etasr.18034},

year  = {2026},

date = {2026-06-01},

journal = {Engineering, Technology & Applied Science Research},

volume = {16},

number = {3},

pages = {35129-35135},

abstract = {In the current era of rapid development in communications technology, fifth-generation (5G) networks, next-generation networks, and the Internet of Things (IoT), many challenges have appeared, the most important being energy consumption and coverage. Although 5G networks offer high data speeds and low latency, the use of millimeter waves limits their range. However, the Narrowband Internet of Things  (NB-IoT) is characterized by wide coverage and low energy consumption, but does not have the bandwidth to accommodate all applications that require high data transfer speeds. This study presents an integrated communication model that uses Fabry-Perot optical sensors and combines NB-IoT and 5G network technologies. Fabry-Perot sensors are integrated into a network infrastructure to feed the Software-Defined Network / Network Function Virtualization (SDN/NFV) controller, which dynamically manages resources, leading to a quantitative improvement in key simulation results (38.67% energy savings and improved spectrum efficiency). This model improves both energy efficiency and coverage and is scalable and effective for next-generation networks, especially in IoT networks. The model was simulated using MATLAB, demonstrating the scalable performance and effective integration of optical sensing with network control.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{chatterjee_4497,

title = {AI insurance chatbots and phygital service engagement: the triadic impact of trust-anxiety-complexity- on aging consumers},

author = {Subhra Chatterjee and Bindu Singh and Ranjan Chaudhuri and Sheshadri Chatterjee and Demetris Vrontis and Pantea Foroudi},

url = {https://doi.org/10.1080/0965254X.2026.2662669},

year  = {2026},

date = {2026-06-01},

journal = {Journal of Strategic Marketing},

pages = {1-28},

abstract = {This study examines elderly consumers' perceptions of the design of AI insurance chatbot services in a phygital context. Drawing on the extended reality technology (ERT) framework and the stimulus - organism - response (SOR) model, it explores the cognitive - affective dynamics shaping chatbot adoption in a sensitive service setting. Data were collected from 396 elderly consumers of major insurance companies in Malaysia and analysed using structural equation modelling to assess mediating and moderating effects. Findings show that perceived trust critically mediates the relationship between cognitive factors and chatbot adoption. Technology anxiety and perceived complexity strongly moderate the trust - usage relationship, confirming a triadic interaction. The study advances theory by integrating the ERT - SOR framework to explain the physical - digital service dichotomy and the continuous use of chatbots. It also highlights the unique affective and psychosocial aspects of aging consumers and offers practical guidance for insurers to design trust-enhancing, user-friendly chatbot services for older users.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{kefi_4391,

title = {Impact of Stress on Workplace E-Learning Satisfaction:  Gender and Generational Effects},

author = {Hajer Kefi and Peter Saba and Ekaterina Besson and Karina Sokolova},

url = {https://doi.org/10.1007/s10796-026-10771-x},

year  = {2026},

date = {2026-06-01},

journal = {Information Systems Frontiers},

abstract = {This study investigates the determinants of learner satisfaction in workplace e-learning, emphasizing Perceived Stress, Instructor Support, Learner-Learner Interaction, and Self-Motivation. It offers a novel perspective by integrating psychological factors into the Virtual Learning Environment (VLE) framework, with a particular focus on gender and generational differences in LifeLong Learning (LLL) within the tourism sector. Using data from 318 French tourism employees, Partial Least Squares (PLS) analysis shows that Perceived Stress negatively affects E-Learning Satisfaction. Subgroup analyses further indicate patterned variation across gender and generation, with stress appearing more salient in the female subgroup and Learner-Learner Interaction simultaneously fostering satisfaction while being associated with higher stress among Generations Y and Z. In addition, Self-Motivation appears especially important under higher stress. These insights advance Information Systems (IS) research by refining VLE frameworks to account for demographic diversity in technology-mediated learning. The study offers practical guidance for designing inclusive e-learning strategies, advocating for stress mitigation, adaptive instructor support, and structured peer engagement to enhance learning effectiveness in corporate environments.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{cheng_4501,

title = {Dynamic demand forecasting in bike-sharing systems: a multidimensional spatiotemporal network},

author = {Quan Cheng and Xin Li and Xiaoli SU and Zhe Yuan},

url = {https://doi.org/10.1080/00207543.2026.2683107},

year  = {2026},

date = {2026-06-01},

journal = {International Journal Of Production Research},

pages = {1-31},

abstract = {Accurate demand forecasting is critical for optimising resource allocation and operational efficiency in bike-sharing systems (BSS). However, this remains challenging owing to the complex nonlinear characteristics of large-scale data, irregular spatiotemporal patterns, and external environmental uncertainties. To address these issues, this study proposes a multidimensional spatiotemporal fusion framework that combines Domain-Adaptive Density Clustering (DADC) and an Attention Temporal Graph Convolutional Network (A3T-GCN). First, the DADC algorithm addresses data sparsity by adaptively clustering stations based on spatial density variations, thereby effectively capturing dynamic distribution patterns. Second, a weighted directed graph is constructed incorporating station utility and full-load-rate functions to eliminate low-performance nodes. A dynamic graph sequence model is then developed to characterise the temporal evolution of spatial dependencies and enhance peak-period responsiveness. The A3T-GCN architecture integrates station-specific attributes with environmental factors through attention mechanisms, enabling the focused analysis of critical demand influencers while processing multidimensional spatiotemporal dependencies. Experimental validation using Citi Bike datasets demonstrates superior performance over benchmark models, reducing prediction errors by 11.54% (15?min) and 12.33% (60?min) through improved short-term accuracy and long-term stability. The framework effectively addresses the uncertainty in demand forecasting, providing methodological support for sustainable BSS operations through enhanced spatiotemporal pattern recognition and environmental adaptability.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{lebon_4378,

title = {Machinability of complex concentrated alloys for bio-implants: Roughness analysis after machining},

author = {Nicolas Lebon and Bernardin Mawussi},

url = {https://www.sciencedirect.com/science/article/pii/S2352492826010238?via%3Dihub},

year  = {2026},

date = {2026-06-01},

journal = {Materials Today Communications},

volume = {54},

number = {115634},

pages = {1-15},

abstract = {TiNbZrMoTa-based HEAs produced by laser powder bed fusion (L-PBF) are promising candidates for biomedical implants, but their post-processing machinability remains insufficiently understood. This study investigates the influence of additive manufacturing conditions and machining strategies on the cutting forces and surface integrity of 3 TiNbZrMoTa-based HEAs manufactured under different volumetric energy densities. Five machining configurations were evaluated at different feedrates.

Cutting force measurements revealed a significant influence of both alloy grade and machining strategy. Under carbide cutting conditions, mean cutting forces increased from 28.8±1.2 N for VED550 to 57.3±1.4 N for VED350 and 61.1±2.7 N for VED88. Abrasive machining reduced machining loads up to 68% compared with cutting tools. Feedrate increased cutting forces but had little influence on surface roughness.

Cutting tool consistently produced the smoothest surfaces, with Ra/Sa values below 0.30 µm. The VED88 alloy machined with a cutting tool exhibited the best overall performance, achieving Ra = 0.118±0.018 µm, Rz = 0.765±0.144 µm, Sa = 0.143±0.010 µm, and Sz = 2.365±0.533 µm. One-way ANOVA demonstrated a highly significant effect of machining configuration on roughness parameters (p < 0.001), whereas ultrasonic assistance mainly improved process stability by reducing Sz variability from 7.31 to 2.45 µm. The results identify VED88 machined with a carbide cutting tool as the optimal compromise between machinability, surface integrity, and process repeatability for biomedical implant applications. These results provide guidance for the post processing of additive manufactured HEAs and support their integration into machined biomedical implant where surface integrity is critical for functional performance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{gregory_4507,

title = {The role of venture?financed startups in innovation for US agriculture},

author = {Graff Gregory and Charles de Grazia and E. Rada Nicholas},

url = {https://doi.org/10.1002/ajae.70083},

year  = {2026},

date = {2026-06-01},

journal = {American Journal Of Agricultural Economics},

abstract = {Technology diffusion and spillovers are key drivers of both innovation and economic growth. This paper examines the effects of obtaining initial intellectual property rights on international knowledge flows through new technological entrants, an important yet understudied function of the IP system. We propose a simple theoretical framework which examines exclusivity and proximity effects as countervailing forces acting on the broader diffusion of foreign-developed technology within a host country. Our study provides causal evidence that a foreign technological entrant's initial patent grant in the host country (the United States) increases the likelihood of international knowledge flows to local U.S. firms and other patenting entities (7.1 percentage points and 29.4 percent, respectively), demonstrating the importance of patent rights in facilitating international knowledge flows beyond the disclosure mechanism. These effects are at least partly driven by sustained presence, cross-country differences in search costs, and voluntary technology sales, but the evidence on inventor mobility is mixed. Overall, initial intellectual property rights appear to mitigate impediments to cross-border knowledge flows in this setting, and the benefits of doing so outweigh the frictions arising from the exclusionary nature of patents.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{wang_4532,

title = {Optimizing parallel machine location and scheduling with sequence-dependent setup times via logic-based benders decomposition},

author = {Yun Wang and Peng Wu and Zhe Yuan and Yeming Gong and Ajay Kumar},

url = {https://doi.org/10.1016/j.ejor.2026.06.027},

year  = {2026},

date = {2026-06-01},

journal = {European Journal Of Operational Research},

abstract = {ow that (i) The proposed FLBBD algorithm can solve a significantly greater number of instances to optimality compared with the off-the-shelf MILP solver CPLEX and BD incorporated within CPLEX; (ii) The FLBBD algorithm finds feasible solutions for 100% instances whereas CPLEX and BD solve only 81.17% and 57.65% instances; (iii) The FLBBD algorithm attains a smaller average optimality gap of 4.89%, in contrast to the 59.10% and 26.09% average optimality gap observed for CPLEX and BD; and (iv) The derived valid inequalities reduces 6.67% computational time and 62.37% optimality gap compared with CPLEX.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{khalifeh_4519,

title = {Mathematical analysis and numerical validation of an extended KdV model for shallow water waves},

author = {Youssef Khalifeh and Samer Israwi and Ralph Lteif and Raafat Talhouk},

url = {https://doi.org/10.3934/dcdss.2026175},

year  = {2026},

date = {2026-06-01},

journal = {Discrete And Continuous Dynamical Systems-Series S},

abstract = {The KdV is one of the most widespread nonlinear models, commonly used by coastal engineers, to describe wave propagation in weakly nonlinear and weakly dispersive shallow water problems. In this paper, we investigate the solutions of the extended KdV equation, previously formally derived for both the velocity and the free-surface elevation, by analyzing its consistency with the extended Boussinesq equations. Combined with a stability result, this leads to a convergence result. This analysis enables us to derive new linear asymptotic models based on this equation. We then explicitly solve these new linear models and illustrate the residual behavior of the resulting approximate solutions through numerical computations for representative initial data. Finally, we analyze solitary-wave solutions of the extended KdV model and quantify its improved accuracy.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{kumar_4513,

title = {Decoding Deepfake Perceptions: Trustworthiness, Importance and Behavioral Intention},

author = {Vinod Kumar and Sachin Kumar and Sheshadri Chatterjee and Ranjan Chaudhuri and Shivam Gupta},

url = {https://doi.org/10.1007/s10796-026-10765-9},

year  = {2026},

date = {2026-06-01},

journal = {Information Systems Frontiers},

abstract = {The present study examines association between deepfake content trustworthiness, perceived importance of content, attitude towards content, and behavioral intentions. Furthermore, the mediating role of perceived importance of content and moderating role of attitude is also observed. The data is collected from 393 customers approached in shopping malls in Delhi-NCR through mall-intercept survey methodology and proposed theoretical model is tested using PLS-SEM. The results indicate that the trustworthiness of deepfake content significantly influence individual's attitude and behavioral intention. The perceived importance of content also plays significant roles as driving factor and mediator, sharping the way users engage with deepfake media. This study will offer insights to practitioners, media platforms and digital content creators in addressing misinformation and enhancing audience trust. This study also provides valuable perspective on elaboration likelihood model that how content evaluation is carried out by users in the age of AI-generated media.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{wang_4512,

title = {Going global through regional digitalization: The case of BRI},

author = {Da Wang and Zhensen Yang and Xiuqun Ye and Marina Latukha and Alexey Kalinin and Miraj Ahmed Bhuiyan and Andrei Panibratov},

url = {https://doi.org/10.1108/cpoib-09-2025-0193},

year  = {2026},

date = {2026-06-01},

journal = {Critical Perspectives on International Business},

volume = {Vol. ahead-of-print},

number = {No. ahead-},

pages = {1-18},

abstract = {Purpose



This study aims to investigate whether and how corporate digitalization promotes multinational enterprises' (MNEs') outward foreign direct investment (OFDI), particularly in developing countries along the Belt and Road Initiative (BRI). It further seeks to uncover the internal and external boundary conditions under which digitalization translates into greater international investment activity by integrating firm-level strategy and host-country digital environment into a unified analytical framework.

Design/methodology/approach



Grounded in the resource-based view (RBV), this study empirically examines the impact of corporate digitalization on OFDI. Using an unbalanced panel data set of 2,780 Chinese listed MNEs from 2013 to 2022, overseas subsidiaries serve as the unit of analysis. Firm-level digitalization is measured through objective digital input-output indicators using an entropy-weight method, while moderating variables include corporate digital strategic orientation and host-country digital infrastructure.

Findings



The corporate digitalization significantly promotes OFDI: more digitally advanced MNEs engage more actively in overseas investment. This positive relationship is strengthened when firms exhibit a stronger digital strategic orientation, indicating the critical role of strategy alignment. Moreover, higher levels of host-country digital infrastructure amplify the effect of firm digitalization on OFDI, especially in developing economies. These findings remain robust across alternative measures, subsamples and instrumental-variable estimations.

Originality/value



This study advances international business and digitalization research by integrating micro-level strategic orientation and macro-level digital infrastructure within the RBV to explain OFDI. It offers a dynamic interpretation of digital resources as sources of international competitive advantage providing actionable insights for managers and policymakers seeking to leverage digital transformation to foster sustainable OFDI.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{platania_4456,

title = {The price of going green: Multi-objective optimization in the energy equity space},

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

url = {https://doi.org/10.1016/j.eneco.2026.109302},

year  = {2026},

date = {2026-06-01},

journal = {Energy Economics},

volume = {158},

pages = {109302},

abstract = {This paper develops a three-objective portfolio optimization framework for the energy sector that simultaneously maximizes expected return, minimizes volatility, and improves environmental performance, measured by the Environmental Pillar Score. Using NSGA-III and rolling 60-month windows from 2010 to 2024, we analyze the U.S. and European equity markets and extract four representative strategies: Max-Return, Min-Volatility, Max-Environmental, and Balanced. Our findings show that trade-offs between financial performance and environmental impact are systematic and regionally specific. U.S. portfolios generally achieve higher returns with greater risk and lower environmental scores, while European portfolios offer stronger sustainability outcomes and lower volatility. The Balanced strategy proves to be a robust compromise among environmental scores, reduced risk, and moderate returns, offering a viable path for investors seeking alignment between financial and sustainability objectives. These results emphasize the value of multi-objective optimization in designing portfolios that align with both financial and sustainability goals.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zalan_4453,

title = {Metaverse Alchemy: Connecting NFTs, Crypto-Tokens, and Social Media in Web3 Platform Multinationals' Success},

author = {Tatiana ZALAN and Efstathios Polyzos and Elissar Toufaily},

url = {https://doi.org/10.1016/j.lrp.2026.102647},

year  = {2026},

date = {2026-06-01},

journal = {Long Range Planning},

pages = {102647},

abstract = {This paper focuses on the emerging internet phenomenon of Web3 platforms which are a new generation of multinationals. Using two popular metaverse platforms, Decentraland and The Sandbox, we examine the nexus between the platform NFTs (non-fungible tokens), the cryptocurrency (i.e., the native token) and the social media discussions around the platforms. We combine token price data with information from OpenSea and X (Twitter) and implement wavelet coherence analysis to examine the time-varying relationship between these three pillars of performance. Our analysis suggests that it is the NFT market (and not the cryptocurrency market) that drives the performance of the decentralized metaverse platforms. Social media discussions generate buzz and sentiment, acting as a catalyst of success. We contribute to shedding light on ?the big question? in international business (IB) research (Peng, 2004) and on the issue of user adoption in the novel context of Web3 PMNCs (platform multinational corporations). The practical implication of our research is that Web3 PMNC builders should design business models that provide utility to NFTs.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{rong_4435,

title = {Strategic climate risk management and innovation outcomes: Insights from China's industrial and policy landscape},

author = {Bao Rong and Sultan Sikandar Mirza and Lotfi Karoui and Asif Saeed},

url = {https://doi.org/10.1016/j.jeconbus.2026.106316},

year  = {2026},

date = {2026-06-01},

journal = {Journal of Economics and Business},

volume = {140},

pages = {106316},

abstract = {This study investigates the influence of climate risk perception (CRP) on environmental innovation among 1511 Chinese A-share-listed firms during 2010-2021. Empirical findings reveal a significant positive relationship between CRP and environmental innovation, which is conditioned by Economic Policy Uncertainty (EPU). Mechanism analysis shows that environmental innovation exploitation, innovation based on existing or historical patents, is more encouraged with higher CRP, while channelling analysis identifies transition risk, stemming from climate-induced supply chain disruptions, resource scarcity, and market volatility, as the central channel. Heterogeneity analysis reveals stronger effects in less competitive markets, manufacturing/heavy-polluting industries, non-state-owned enterprises (non-SOEs), and those characterized by stringent internal controls. A nonlinear inverted U-shaped relationship emerges: moderate CRP boosts innovation, while excessive risk perception hinders it. Nonetheless, the inflection point of this inverted U-shaped relationship lies within the sample range of CRP. This study contributes by distinguishing CRP from objective climate risk (CR) as a strategic cognitive antecedent, integrating macro boundary conditions (EPU) into a coherent theoretical framework, and highlighting innovation exploitation as a significant mechanism and transition risk as a critical channel, addressing gaps in prior literature on firm-level adaptive responses to climate change.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{latan_4000,

title = {Disincentives to reporting sexual harassment in government agencies: A large-scale survey},

author = {Hengky Latan and Charbel Jose Chiappetta Jabbour and Ana Beatriz Lopes de Sousa Jabbour and Tan Vo-Thanh and Murad Ali},

url = {https://doi.org/10.1177/00910260251369131},

year  = {2026},

date = {2026-06-01},

journal = {Public Personnel Management},

volume = {55},

number = {2},

pages = {201-223},

abstract = {This article investigates the factors that discourage employees from engaging in formal complaining behavior within government agencies, particularly in response to workplace misconduct such as sexual harassment. The data used in this study were obtained from the Merit Principles Survey (MPS) 2021, and covariance structure analysis (CSA) was applied to examine the relationships between variables. Guided by social identity theory (SIT), the study tests hypotheses related to perceived disincentives that may inhibit employees from submitting formal complaints. A key contribution of this research lies in its integrated analysis of three critical deterrents?non-disclosure agreements, non-disclosure policies, and the perceived seriousness of threats?which have not previously been examined collectively in the context of complaint behavior. The results offer valuable insights for public sector administrators aiming to foster transparent and responsive organizational cultures.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zighan_4038,

title = {Managing Social Sustainability Paradoxes in the Digitalized Supply Chains for Circular Economy},

author = {Saad ZIGHAN and Salomée Ruel},

url = {https://doi.org/10.1016/j.pursup.2025.101090},

year  = {2026},

date = {2026-06-01},

journal = {Journal Of Purchasing And Supply Management},

volume = {32},

number = {3},

pages = {101090},

abstract = {This study explores how social sustainability is enabled and constrained within Circular Digitalized Supply Chains (CDSCs), mobilizing paradox theory as a theoretical lens. Through a qualitative analysis of interviews with 22 supply chain (SC), operations, logistics, and procurement managers, the research identifies key paradoxes that emerge when pursuing social goals alongside circular and digital transformations. The study finds that pursuing CDSCs' goals alongside social sustainability objectives creates paradoxical tensions, such as conflicts between efficiency and fair labor practices, data privacy concerns, and the potential for power concentration within digital platforms. These tensions highlight the complexities of balancing competing objectives within CDSC operations. Moreover, the different managerial perspectives, such as SC, operational, logistics, and procurement, may prioritize different aspects of sustainability, leading to potential tensions. These tensions were categorized into four paradoxes: the paradox of progress, the paradox of efficiency, the paradox of control, and the paradox of governance. To manage these paradoxes, the findings highlight the importance of dynamic management, stakeholder engagement, transparency, innovation, and continuous learning. This should also be supported by holistic integration, which involves a unified, comprehensive approach to managing paradoxes in CDSCs, transitioning from separate functional strategies to a cohesive solution. This study contributes to understanding the complexities of social sustainability in CDSCs. It offers insights for practitioners and policymakers seeking to promote more responsible and sustainable SC practices.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}