Science des données, transformation digitale, risques et systèmes complexes

@article{rai_3452,

title = {Uncorking the psychological factors behind habits and NoLo wine preferences},

author = {Krupa Rai and Antonino Galati and Sheshadri Chatterjee and Ranjan Chaudhuri and Demetris Vrontis and Giuseppina Migliore},

url = {http://dx.doi.org/10.1108/BFJ-10-2024-0998},

year  = {2025},

date = {2025-04-01},

journal = {British Food Journal},

volume = {127},

number = {4},

pages = {1420-1440},

abstract = {Purpose - The consumption of no-and low-alcohol (NoLo) wines has emerged as a growing trend among Italian

millennials, reflecting a shift towards healthier and more mindful drinking habits. This paper delves into the

social factors driving this trend, employing the rational of habit theory to provide a comprehensive

understanding of NoLo wines consumption as a social behaviour among Italian millennials.

Design/methodology/approach - The research design comprises symmetrical and asymmetrical approach.

The study employs Cluster and fsQCA to understand the granularities of NoLo wine consumption.

Findings - The present study reveals that young adults are willingness to pay (WTP) more for NoLo wine in

exchange of improved health benefits as a reward. The contrarian observation of relatively consumers with low

average income exhibiting the high willingness to pay more for NoLo wine.

Research limitations/implications - The sample islimitedto Italyand skewed in terms ofNoLowine consumption.

The participants were aware of NoLo wine but did not consume it in the past year. The study identified the

paradoxical stance of low average family income group exhibiting more willingness-to-pay for de-alcoholised wine.

Practical implications - Firstly, young adults are increasingly health-conscious,seeking alternativesto alcohol

that promote well-being and reduce health risks associated with excessive alcohol consumption. Secondly,

mindfulness practices have gained popularity among young adults for altering self-perception, leading to a

preference for beverages that align with mindful consumption and stress reduction. NoLo wine offers a suitable

alternative, providing a similar sensory experience without the intoxicating effects of alcohol.

Social implications - Habit theory, pioneered by James (1890), posits that habits are formed through a three-stage

process: cue,routine and reward.In the context of NoLo wine consumption, cues can include social gatherings, dining

occasions orstressrelieftriggers. The routine involvesthe act of consuming NoLo wine, while the reward stemsfrom

the perceived benefits of this wine, such as reduced alcohol intake, improved health and social acceptance. The

prevalence of NoLo wine consumption among Italian young adults can be attributed to a confluence ofsocialfactors.

Originality/value - The paper attempts to evaluate the contrarian case using fsQCA and the conceptual

configuration of necessary conditions, viz. self-perception, social norms and health-consciousness.},

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tppubtype = {article}

}

@article{chaudhuri_3665,

title = {Assessing the economic and social impacts of greenwashing: moderating impact of big data analytics adoption},

author = {Ranjan Chaudhuri and Bindu Singh and Barnali Nag and Shivam Singh Bhadauria and Demetris Vrontis and Sumana Chaudhuri and Sheshadri Chatterjee},

url = {https://doi.org/10.1108/IJBM-07-2024-0440},

year  = {2025},

date = {2025-04-01},

journal = {International Journal Of Bank Marketing},

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

number = {Vol. ahead},

abstract = {Purpose - This study empirically examines the impact of greenwashing practices on consumers' intention to

purchase green products. It also investigates whether greenwashing has any impact on economic and social

risks. Moreover, this research captures the moderating impact of big data analytics (BDA) on the relationships

between intention to purchase green products and its predictors.

Design/methodology/approach - With the support of literature in the field of greenwashing, economics,

consumer behavior, as well as emerging technologies and theories on consumer behavior, a conceptual model is

developed. The model was validated using partial least squares (PLS) structural equation modeling (SEM)

technique considering 356 respondents from European countries who are aware of greenwashing practices.

Findings - This study highlights that greenwashing practices negatively impact people both economically and

socially. But greenwashing practices also have a profound impact on consumers' intention to purchase

ecofriendly products. It also demonstrates a significant moderating impact of big data analytics adoption on the

relationship between intention to purchase green products with its predictors.

Research limitations/implications - The study presentsinsights on greenwashing and itsimpact on society and

the economy. It also shows that technologies like BDA could help minimize the challenges of greenwashing

activities as well as the social and economic risks. Moreover, the study provides vital insights into the influence

of greenwashing practices on the intention to purchase green products. Finally, asthis is a cross-sectionalstudy,

there are some limitations.

Originality/value - This study takes a fresh look at greenwashing practices and BDA technology to overcome

some of the challenges. It provides a unique research model that is (1) unique in this research domain; (2)

International

Journal of Bank

Marketing

The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/0265-2323.htm

Received 30 July 2024

Revised 15 October 2024

2 January 2025

26 March 2025

Accepted 27 March 2025

International Journal of Bank Marketing

© Emerald Publishing Limited

e-ISSN: 1758-5937

p-ISSN: 0265-2323

DOI 10.1108/IJBM-07-2024-0440

provides a solid foundation for future researchersto further nurture; (3) extendsthe understanding of how using

technology can minimize the risks caused by greenwashing; and (4) contributes to the body of literature on

consumer behavior, economics, technology and social risks.},

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pubstate = {online},

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}

@article{zhang_3199,

title = {A survey of evidential clustering: Definitions, methods, and applications},

author = {Zuowei Zhang and Yiru Zhang and Hongpeng Tian and Arnaud Martin and Zhunga LIU and Weiping Ding},

url = {https://www.sciencedirect.com/science/article/pii/S1566253524005141},

year  = {2025},

date = {2025-03-01},

journal = {Information Fusion},

volume = {115},

pages = {102736},

abstract = {In the realm of information fusion, clustering stands out as a common subject and is extensively applied across various fields. Evidential clustering, an increasingly popular method in the soft clustering family, derives its strength from the theory of belief functions, which enables it to effectively characterize the uncertainty and imprecision of data distributions. This survey provides a comprehensive overview of evidential clustering, detailing its theoretical foundations, methodologies, and applications. Specifically, we start by briefly recalling the theory of belief functions with its transformations into other uncertainty reasoning theories. Then, we introduce the concepts of soft data, partitions, and methods with an emphasis on data and partitioning within the theory of belief functions. Subsequently, we summarize the advancements and quantitative evaluations of existing evidential clustering methods and provide a roadmap to help in selecting an appropriate method based on specific application needs. Finally, we identify the major challenges faced in the development and application of evidential clustering, pointing out promising avenues for future research, including theoretical limitations, applicable datasets, and application domains. The survey offers a structured understanding of existing evidential clustering methods, highlighting their theoretical underpinnings, practical implementations, and future research directions. It serves as a valuable resource for researchers seeking to deepen their understanding of evidential clustering.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{benjira_3275,

title = {Automated mapping between SDG indicators and open data: An LLM-augmented knowledge graph approach},

author = {Wissal Benjira and Faten Atigui and Benedicte Bucher and Malika Grim-Yefsah and Nicolas Travers},

url = {https://doi.org/10.1016/j.datak.2024.102405},

year  = {2025},

date = {2025-03-01},

journal = {Data & Knowledge Engineering},

volume = {156},

pages = {102405},

abstract = {Meeting the Sustainable Development Goals (SDGs) presents a large-scale challenge for all countries. SDGs established by the United Nations provide a comprehensive framework for addressing global issues. To monitor progress towards these goals, we need to develop key performance indicators and integrate and analyze heterogeneous datasets. The definition of these indicators requires the use of existing data and metadata. However, the diversity of data sources and formats raises major issues in terms of structuring and integration. Despite the abundance of open data and metadata, its exploitation remains limited, leaving untapped potential for guiding urban policies towards sustainability. Thus, this paper introduces a novel approach for SDG indicator computation, leveraging the capabilities of Large Language Models (LLMs) and Knowledge Graphs (KGs). We propose a method that combines rule-based filtering with LLM-powered schema mapping to establish semantic correspondences between diverse data sources and SDG indicators, including disaggregation. Our approach integrates these mappings into a KG, which enables indicator computation by querying graph's topology. We evaluate our method through a case study focusing on the SDG Indicator 11.7.1 about accessibility of public open spaces. Our experimental results show significant improvements in accuracy, precision, recall, and F1-score compared to traditional schema mapping techniques.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{obbadi_3392,

title = {A stable second-order splitting method for incompressible Navier-Stokes equations using the scalar auxiliary variable approach},

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

url = {https://www.sciencedirect.com/science/article/pii/S0045782525000738?dgcid=coauthor},

year  = {2025},

date = {2025-03-01},

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

volume = {437},

pages = {117801},

abstract = {We propose a novel second-order fractional-step method for the numerical solution of incompressible Navier-Stokes equations. This fractional-step method consists of two splitting steps and it employs the second-order implicit backward differentiation formula for the time integration.

Unlike most of the projection methods for solving incompressible Navier-Stokes equations, the proposed method is free from any numerical inconsistencies generated by the treatment

of boundary conditions on the pressure solution. Two pressure-correction strategies including the scalar auxiliary variable approach are proposed to enhance the accuracy of the method.

A rigorous stability analysis is also carried out in this study for the considered strategies.

Numerical results are presented for three benchmark problems to validate the unconditional stability and to demonstrate the performance of the proposed fractional-step method for solving unsteady incompressible viscous flows. The obtained computational results support our

theoretical expectations for an unconditionally stable second-order fractional-step method for the incompressible Navier-Stokes equations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{singh_3397,

title = {Assessing the impact of digital transformation on green supply chain for achieving carbon neutrality and accelerating circular economy initiatives},

author = {Kuldeep Singh and Ranjan Chaudhuri and Sheshadri Chatterjee},

url = {https://www.sciencedirect.com/science/article/pii/S0360835225000890?via%3Dihub},

year  = {2025},

date = {2025-03-01},

journal = {Computers & Industrial Engineering},

volume = {201},

pages = {110943},

abstract = {The objective of this research is to analyse how digital transformation initiatives influence the effectiveness of green supply chain practices to achieve carbon neutrality as well as to accelerate circular economy practices. The study posits a theoretical model grounded in resource-based, data empowerment, and contingency theory to conduct the study. The main aspect of the research is to analyse the mediating role played by green supply chain integration on the association between digital transformation and green supply chain performance. Furthermore, the study also tried to uncover the moderating impact of absorptive capacity and economic policy uncertainty on above mentioned relationship. The moderating effect could deaccelerate carbon neutrality and could create hindrance towards circular economy. Hence, absorptive capacity is anticipated to influence how organizations assimilate and apply digital advancements, while economic policy uncertainty is expected to shape the overall landscape within which these transformations occur. The study followed a quantitative design and PLS-SEM analysis. The results show the importance of digital transformation in in order to derive environmental sustainability within supply chains. In this study absorptive capacity found as a significant moderator. The results offer valuable insights for businesses in order to to enhance environmental sustainability. Also, these efforts with digital transformation and effective SCM practices can help a firm to achieve carbon neutrality. This distinct approach promotes more sustainable and resilient green supply chain practices that enables businesses to stay agile and accelerate circular economy practices.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{appio_3661,

title = {The green premium: How environmental consciousness elevates crowdfunding success},

author = {Francesco Appio and Tarik Bazgour and Federico Platania and Celina Toscano Hernandez},

url = {http://dx.doi.org/10.1016/j.frl.2025.106743},

year  = {2025},

date = {2025-03-01},

journal = {Finance Research Letters},

volume = {74},

pages = {106743},

abstract = {This study investigates the impact of environmental orientation on the success of crowdfunding projects, using a comprehensive dataset from Kickstarter. By examining environmental keywords, geographic distribution of backers, and other project characteristics, we find that environmentally oriented projects achieve significantly higher success rates and funding levels. Notably, while sustainability plays a critical role in attracting backers, the combined effect of environmental orientation and a majority of US backers moderates this success. These findings underscore the importance of integrating environmental themes into crowdfunding campaigns and highlight the necessity for tailored strategies that account for geographic preferences.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kumar_3251,

title = {From insight to impact: Unravelling the dynamics of big data-backed growth hacking},

author = {Vinod Kumar and Sachin Kumar and Ranjan Chaudhuri and Sheshadri Chatterjee and Alkis Thrassou and Georgia Sakka},

url = {https://www.sciencedirect.com/science/article/pii/S0148296324005873?via%3Dihub},

year  = {2025},

date = {2025-02-01},

journal = {Journal Of Business Research},

volume = {188},

pages = {115083},

abstract = {The rise of growth hacking, fuelled by big data analytics, poses a challenge for scholars and executives alike, with

limited research at their intersection. This article aims to fill the knowledge gap by focusing on the integration of

big data analytics and growth hacking. Extant theory suggests that incorporating big data cultivates marketing

ambidexterity, especially when moderated by environmental dynamism. The synergistic interplay between big

data analytics and marketing ambidexterity is postulated to enhance firm marketing capabilities, manifesting

itself as growth hacking. The present study develops a corresponding scale on growth hacking and empirically

validates the proposed theoretical framework. Data have been collected from businesses that have used growth

hacking tactics, regardless of their timeframe or resource investment, in two phases and adhering to requisite

sampling size and techniques. The relationships between all variables were found to be significant except the

impact of firm marketing capabilities on customer regain and maintenance. Environmental dynamism was found

to moderate significantly big data analytics and marketing ambidexterity. This study enriches the growth

hacking literature by shedding light on the intricate relationship between big data analytics and strategic

business growth. The findings are also significant to industry, as they arm executives with new and practicable

knowledge towards harnessing growth hacking strategies and securing a competitive edge.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kumar_3311,

title = {Innovation capability and R&D performance of organizations: moderating role of industry-academic knowledge transfer},

author = {Vinod Kumar and Sachim KUMAR and Ranjan Chaudhuri and Sheshadri Chatterjee and Demetris Vrontis and Saeedeh Rezaee Vessal},

url = {https://www.emerald.com/insight/content/doi/10.1108/jkm-02-2024-0175/full/html},

year  = {2025},

date = {2025-02-01},

journal = {Journal Of Knowledge Management},

volume = {29},

number = {3},

pages = {891-914},

abstract = {Purpose



This study aims to examine how an organization's innovation capability could influence research and development (R&D) performance. It also investigates if industry-academic knowledge transfer has a moderating relationship between organizational innovation capability and exploration and exploitative innovation in improving the R&D performance of the organizations.

Design/methodology/approach



Based on the literature and dynamic capability view, a conceptual model was developed and then validated using the partial least squares-structural equation modeling technique considering 387 responses from academicians and industry personnel.

Findings



The study found that industry-academic knowledge transfer has a significant moderating impact toward improving innovation capability, organizations' R&D performance and exploration innovation. However, it has an insignificant moderating impact on improving innovation capability and exploitative innovation.

Practical implications



Organizational innovation capability is characterized by both exploratory and exploitative innovation. Both types of innovation support the R&D performance of an organization. Also, organizations that closely work with academic institutions could gain significant R&D knowledge from academic expertise. This study provides food for thought for the academic community as well as industry policymakers.

Originality/value



There are significant opportunities for academic institutions to gain practical knowledge from industry which can help them to accelerate their R&D activities. However, transferring knowledge between industry and academia has challenges related to intellectual property, patents and so on. Not much research has been conducted in this area. Thus, the proposed research model is unique and adds to the existing literature.

Keywords},

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pubstate = {published},

tppubtype = {article}

}

@article{korger_3326,

title = {Modulational instability of geodesic-acoustic-mode packets},

author = {David Korger and Emanuele Poli and Alessandro Biancalani and Alberto Bottino and Omar Maj and Juvert Njeck Sama},

url = {https://doi.org/10.1017/S0022377824001284},

year  = {2025},

date = {2025-02-01},

journal = {Plasma Physics And Controlled Fusion},

volume = {91},

number = {1},

pages = {E17},

abstract = {Isolated, undamped geodesic-acoustic-mode (GAM) packets have been demonstrated to

obey a (focusing) nonlinear Schrödinger equation (NLSE) (E. Poli, Phys. Plasmas, 2021).

This equation predicts susceptibility of GAM packets to the modulational instability (MI).

The necessary conditions for this instability are analysed analytically and numerically

using the NLSE model. The predictions of the NLSE are compared with gyrokinetic

simulations performed with the global particle-in-cell code ORB5, where GAM packets

are created from initial perturbations of the axisymmetric radial electric field E r . An

instability of the GAM packets with respect to modulations is observed both in cases in

which an initial perturbation is imposed and when the instability develops spontaneously.

However, significant differences in the dynamics of the small scales are discerned between

the NLSE and gyrokinetic simulations. These discrepancies are mainly due to the radial

dependence of the strength of the nonlinear term, which we do not retain in the solution

of the NLSE, and to the damping of higher radial spectral components k r . The damping

of the high- k r components, which develop as a consequence of the nonlinearity, can be

understood in terms of Landau damping. The influence of the ion Larmor radius ? i as well

as the perturbation wavevector k pert on this effect is studied. For the parameters considered

here the aforementioned damping mechanism hinders the MI process significantly from

developing to its full extent and is strong enough to stabilize some of the (according to the

undamped NLSE model) unstable wavevectors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{singh_3406,

title = {Knowledge Management and Organizational Resilience in MSMEs: The Intervening Role of Innovation Orientation},

author = {Kuldeep Singh and Sheshadri Chatterjee and Ranjan Chaudhuri and Demetris Vrontis and Helene Yildiz},

url = {https://doi.org/10.1002/jsc.2640},

year  = {2025},

date = {2025-02-01},

journal = {Strategic Change},

volume = {0},

pages = {1-13},

abstract = {The relationship between knowledge management (KM) and organization performance has been thoroughly studied. However,

there is still a research gap to determine other factors that could influence this relationship. One significant component is innovation,

and we need to consider the size and age of the organization to determine how innovation influences organizational resilience

(OR). A few studies discussed innovation and knowledge management; however, they usually focus on large firms. This

study is based on MSMEs in India. In this study, we analyzed how innovation can link between KM and OR. We examined three

components of KM in our research: knowledge generation (KG), knowledge transfer (KT), and knowledge acquisition (KA). We

obtained responses from 336 respondents who took part in this study. We used PLS-SEM

to analyze the data. The findings indicate

that innovation plays an essential role in establishing a relationship between KM and OR. Firm age is found as a significant

moderating factor of this relationship. It implies that, to be robust, older enterprises in MSMEs should prioritize both KM and

innovation. This study can serve as a useful resource for MSMEs that wish to learn more about the role of innovation in utilizing

KM and OR.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{el-amrani_3162,

title = {A fractional time-stepping method for unsteady thermal convection in non-Newtonian fluids},

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

url = {https://www.sciencedirect.com/science/article/pii/S1007570424005355},

year  = {2025},

date = {2025-01-01},

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

volume = {140},

number = {Part 1},

pages = {108350},

abstract = {We propose a fractional-step method for the numerical solution of unsteady thermal convection in non-Newtonian fluids with temperature-dependent physical parameters. The proposed method is based on a viscosity-splitting approach, and it consists of four uncoupled steps where

the convection and diffusion terms of both velocity and temperature solutions are uncoupled while a viscosity term is kept in the correction step at all times. 

This fractional-step method maintains the same boundary conditions imposed in the original problem for the corrected velocity solution, and it eliminates all inconsistencies related to boundary conditions for the

treatment of the pressure solution. In addition, the method is unconditionally stable, and it allows the temperature to be transported by a non-divergence-free velocity field. In this case, we introduce a methodology to handle the subtle temperature convection term in the error analysis

and establish full first-order error estimates for the velocity and the temperature solutions and 1?2-order estimates for the pressure solution in their appropriate norms. Three numerical examples are presented to demonstrate the theoretical results and examine the performance of the proposed method for solving unsteady thermal convection in non-Newtonian fluids. The computational results obtained for the considered examples confirm the convergence, accuracy, and applicability of the proposed time fractional-step method for unsteady thermal convection in non-Newtonian fluids.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{paty_3212,

title = {IoT-Enabled Methane Monitoring and LSTM-Based Forecasting System for Enhanced Safety in Underground Coal Mining},

author = {Soumyadeep PATY and Arindam BISWAS and Sonia Djebali and Guillaume Guérard and Supreeti KAMILYA},

url = {https://dl.acm.org/doi/pdf/10.1145/3703460},

year  = {2025},

date = {2025-01-01},

journal = {ACM Transactions on Internet of Things},

volume = {6},

number = {1},

abstract = {Ensuring safety in the mining industry is a critical concern for a nation's industrial advancement. Industry 4.0, characterized by the integration of advanced technologies, is at the forefront of efforts to enhance mining practices. Coal seams contain a range of

hydrocarbon gases, predominantly methane, which is released in significant quantities during mining operations. Effectively

mitigating methane emissions is imperative. The inclusion of methane forecasting allows for the early identification of potential methane emissions, hence results in significance enhancement in mine safety. The research work is focused on real-time remote monitoring and cloud-based forecasting of methane levels in underground coal mines. An Industrial Internet of Things (IIoT) device is developed for data acquisition in underground coal mines, capturing essential parameters such as methane concentration,

temperature, and humidity. The collected data are utilized to train LSTM based multivariate forecasting model. The trained model is

subsequently deployed in the cloud. The experiment is performed in a mine of Eastern Coalfields Limited, India. After the deployment

of the proposed model, the developed IIoT device transmits real-time data, obtained from the mine, to the cloud. Based on the real

time data, our model conducts methane forecasting and communicates results back to the IIoT device. The device issues immediate

alerts when methane levels surpass predefined thresholds. This ensures enhanced safety in mining operations by providing warnings

for both current and forecasted methane concentrations. The forecasted methane concentrations, along with real-time data, are

accessible through mobile applications and a web-based dashboard. The accuracy of the proposed model is measured by mean

absolute error, mean absolute percentage error and root mean square error, which demonstrate values of 156.95 ppm, 4.23% and

191.53 ppm respectively. A comparative study is performed where our model is evaluated against the multivariate Multilayer

Perceptron (MLP), Vector autoregression (VAR) and Auto-Regressive Integrated Moving Average (ARIMA) models. The comparative

study demonstrates that our developed model outperforms the others, showing superior results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{garcin_3272,

title = {Credit scoring using neural networks and SURE posterior probability calibration},

author = {Matthieu Garcin and Samuel Stéphan},

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

year  = {2025},

date = {2025-01-01},

journal = {International Journal of Applied Decision Sciences},

volume = {In press},

abstract = {In this article we compare the performances of a logistic regression and a feed forward neural network for credit scoring purposes. Our results show that the logistic regression gives quite good results on the dataset and the neural network can improve a little the performance. We also consider different sets of features in order to assess their importance in terms of prediction accuracy. We found that temporal features can be an important source of information resulting in an increase in the overall model accuracy. Finally, we introduce a new technique for the calibration of predicted probabilities based on Stein's unbiased risk estimate (SURE). This

calibration technique can be applied to very general calibration functions such as the sigmoid function and the Kumaraswamy function, which includes the identity as a particular case. We show that stacking the SURE calibration technique with the classical Platt method can

improve the calibration results.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{ghizzo_3325,

title = {Internal transport barrier triggered by phase synchronization of zonal flow with energetic particle modes},

author = {Alain Ghizzo and Daniele Del Sarto and Juvert Njeck Sama and Alessandro Biancalani},

url = {https://doi.org/10.1088/1361-6587/ad9be6},

year  = {2025},

date = {2025-01-01},

journal = {Plasma Physics And Controlled Fusion},

volume = {67},

number = {1},

pages = {015016},

abstract = {The suppression of the microturbulence associated to the emergence of a spontaneous internal transport barrier has been recently demonstrated in a system showing a possible amplification of the zonal flow component in the low-frequency regime (Ghizzo and Del Sarto 2023 Nucl. Fusion 63 104002). We use here numerical experiments performed with a 'particles modes' model based on a double average over the fast cyclotron phase and over the bounce (or transit) phase to show the major role played by energetic particles and shear flows in this scenario. 'Particle modes' are meant here as classes of particles, identified by some adiabatic invariant after a gyro-average procedure, which are associated to the description of some specific linear modes of the plasma. The introduction of energetic circulating ions or shear flows into the system makes a larger number of particle modes being involved in the synchronization process. A global synchronization of the Fourier modes of the turbulent spectrum can be this way achieved. This process allows for a bifurcation towards self-organization, which is associated to the emergence of a staircase-like structure. This is known to be an essential element in the modification of the zonal flow pattern in phase space during the suppression of microturbulence in tokamaks.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{recuero_virto_3615,

title = {Digital Sustainability Trade-Offs: Public Perceptions of Mobile Radiation and Green Roofs},

author = {Laura Recuero Virto and Peter Saba and Arno Thielens and Marek Czerwinski and Paul Noumba Um},

url = {https://aisel.aisnet.org/cais/vol56/iss1/27/},

year  = {2025},

date = {2025-01-01},

journal = {Communications of the AIS},

volume = {56},

pages = {720-762},

abstract = {This paper explores how public perceptions influence the interplay between Digital Sustainability (DS), public health, and environmental policy, particularly regarding the effects of mobile radiation on green roofs. While green roofs are recognized for their ecological advantages, the impact of mobile radiation exposure, especially from 5G technology, has not been thoroughly examined in Information Systems (IS) research. Through a Discrete Choice Experiment (DCE) involving an urban sample from the French population, our findings indicate a significant preference for funding research focused on human health compared to plant health, with willingness to pay (WTP) estimates for human health nearly twice as high. Nonetheless, the considerable support for plant health research underscores the importance of addressing both human and environmental aspects in policy formulation. This study contributes to the growing DS dialogue by demonstrating how cognitive, emotional, and moral perceptions shape public backing for research on mobile radiation. These findings enhance our understanding of how public attitudes influence the adoption and regulation of green technologies in urban environments. Our research provides insights for IS researchers and policymakers, advocating for balanced funding approaches and the integration of cognitive, emotional, and ethical factors into policy frameworks to foster effective public engagement and regulatory policies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{rodrigues_3621,

title = {REDIRE: Extreme REduction DImension for extRactivE Summarization},

author = {Christophe Rodrigues and Marius Ortega and Aurélien Bossard and Nédra Mellouli},

url = {http://dx.doi.org/10.1016/j.datak.2025.102407},

year  = {2025},

date = {2025-01-01},

journal = {Data & Knowledge Engineering},

volume = {157},

pages = {102407},

abstract = {This paper presents an automatic unsupervised summarization model capable of extracting the most important sentences from a corpus. The unsupervised aspect makes it possible to do away

with large corpora, made up of documents and their reference summaries, and to directly process documents potentially made up of several thousand words. To extract sentences in a summary, we use pre-entrained word embeddings to represent the documents. From this thick cloud of word vectors, we apply an extreme dimension reduction to identify important words, which we group by proximity. Sentences are extracted using linear constraint solving

to maximize the information present in the summary. We evaluate the approach on large documents and present very encouraging initial results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ha_3625,

title = {Financial inclusion and fintech: a state-of-the-art systematic literature review},

author = {Dao Ha and Phuong Le and Duc Khuong Nguyen},

url = {https://jfin-swufe.springeropen.com/articles/10.1186/s40854-024-00741-0},

year  = {2025},

date = {2025-01-01},

journal = {Financial Innovation},

volume = {11, 69},

abstract = {This study presents an all-inclusive analysis of the literature on the augmentation

of financial inclusion through fintech. Ninety-six papers were selected from the 2951

articles in the Web of Science, Scopus, and EBSCO databases. This study uses bibliometric

and content analysis techniques to illuminate the underexplored aspects of fintech's

impact on financial inclusion. Unlike previous studies, this study consolidates a significant

amount of the literature on financial inclusion by systematically contextualizing

theories and viewpoints from the fintech sector. The key findings include the identification

of three main research clusters: (1) the advent of novel services, (2) the transformation

of the market landscape, and (3) the roles of stakeholders in the fintech

ecosystem. The analysis reveals gaps in the existing research, such as the need for more

studies on the tangible impact of fintech on financial inclusion and regulation. This

study concludes by highlighting potential directions for future research and emphasizing

the importance of policymakers paying greater attention to fintech's implications

for financial inclusion.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ngo_3627,

title = {Revisit the First 60 Days of COVID-19: Assessment of the Global Healthcare Systems using Data Envelopment Analysis},

author = {Thanh Ngo and Duc Khuong Nguyen and Dinh-Tri Vo},

url = {https://doi.org/10.1177/09720634241312029},

year  = {2025},

date = {2025-01-01},

journal = {Journal of Health Management},

volume = {0},

number = {0},

abstract = {The ongoing pandemic of the novel coronavirus (COVID-19) has exploded and raised important questions on the efficiency

and effectiveness of healthcare systems around the world to provide guidance for appropriate policy responses. While it is

important to look at the current (and future) situation, it is also needed to look back into the past, especially at the first few

months of the pandemic. This study re-examines the efficiency of healthcare systems around the world against the outbreak

of COVID-19 in its first 62 days (23 January 2020-25 March 2020) to see if the examined countries were well prepared

and well reacted to the pandemic. Results from a data envelopment analysis evaluation indicated that the global healthcare

systems experienced a very low efficiency on average. Besides the absence of a coronavirus vaccine at that time, this low efficiency

is typically linked to the operational scale of the healthcare systems, suggesting that countries could tightly rationalise

their healthcare resources/inputs to improve the technical efficiency of their healthcare systems.},

keywords = {},

pubstate = {online},

tppubtype = {article}

}

@article{beaulieu_3954,

title = {Comment implanter les mesures de résilience d'une chaîne logistique ? Une étude de cas du secteur québécois de la santé},

author = {Martin BEAULIEU and Salomée Ruel},

url = {https://doi.org/10.1080/12507970.2024.2407087},

year  = {2025},

date = {2025-01-01},

journal = {Logistique & Management},

volume = {33},

number = {1},

pages = {38-61},

abstract = {La pandémie de la Covid-19 a propulsé le concept de résilience de la chaîne logistique alors

que plusieurs d'entre elles subissaient les contrecoups de cet événement planétaire. Pour le

secteur de la santé, des études ont justement formulé de nombreuses recommandations afin

d'assurer la résilience de cette chaîne logistique. Cependant, ces mêmes études demeurent

peu explicites sur la façon dont un acteur ou des acteurs s'imposeront à l'intérieur de la

chaîne et dans le cas de la résilience, qui pourra articuler et assurer la mise en oeuvre des

recommandations. Cette observation renvoie à des constats soulevés dans la littérature sur

les défis de l'opérationnalisation de la résilience de la chaîne logistique. Ainsi, cet article pose

la question suivante : comment une organisation-pivot de la chaîne logistique de la santé

peut-elle émerger afin de mettre en oeuvre ces mesures de résilience ? Pour y répondre, cette

recherche mobilise la méthode des cas et revient sur les événements du secteur public de la

santé de la province de Québec. Les résultats questionnent l'intérêt d'une organisation-pivot

comme orchestre des décisions en faveur de la résilience de la chaîne logistique.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{zouari_3955,

title = {The nexus of stewardship and sustainability in supply chains: revealing the impact of purchasing social responsibility on innovativeness and operation performance},

author = {Dorsaf ZOUARI and Laurence VIALE and Salomée Ruel and Klaas STEK},

url = {https://doi.org/10.1108/EBR-01-2024-0014},

year  = {2025},

date = {2025-01-01},

journal = {European Business Review},

volume = {37},

number = {2},

pages = {193-229},

abstract = {Purpose - The authors mobilise stewardship theory, which delves into trust and collaboration dynamics,

advocating for long-term gains through actions beneficial to the broader community. Used as a fundamental

framework to conceptualise the model, stewardship theory enhances the understanding of the effect of purchasing

social responsibility (PSR) practices to foster innovativeness and performance through the supply chain (SC). This

study aims to examine the relationship between PSR, SC innovativeness (SC-INNO) and SC operational

performance (SCOP). In addition, themoderating effect of sustainability labels on these relationshipswill be studied.

Design/methodology/approach - Based on survey data from 177 organisations analysed through partial

least square structural equation modelling, the results suggest that PSR has a positive and significant effect on

SC-INNO and SCOP. In addition, SC-INNO plays a partial mediation role since the direct effect between PSR

and SCOP is validated. Furthermore, the moderating effects of holding a sustainability label and industry type

about PSR and SCOP are supported.

Findings - The results indicate a significant positive influence of PSR on both SC-INNO and operational

performance. SC-INNO is found to partially mediate the PSR-SCOP relationship. Moreover, sustainability

labels and industry type significantly moderate the effects of PSR on SCOP.

Originality/value - The findings extend stewardship theory into the sustainable purchasing and supply

management field by providing empirical support for PSR as a reflection of stewardship behaviours by

fostering innovation and performance throughout the SC.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}