How Artificial Intelligence (AI) and Data Science (DS) transform how firms do business?
In the digital era, data is the ultimate change-maker, and the leaders in the market are engaging with data through state-of-the-art innovations in business analytics.
The goal of this Area is to understand how to use data to engage with customers, improve business processes, design better products, manage various risks, and solve the innumerable wicked problems of society. Research in this Area proposes to advance research on various aspects of AI and DS that will significantly contribute to the well-being of individuals, organisations, and society.
For Indranil Bose, director of the Area, “The AI, Data Science and Business AE promotes collaborative research among colleagues interested in studying innovative uses of AI and DS in a variety of application areas related to business. Our focus is on understanding transformative technologies, evaluating their impact on businesses and consumers, and overcoming current and upcoming challenges through smart solutions. We perform impactful research using quantitative as well as qualitative techniques. We organize seminars, workshops, industry talks, and discussion groups to support our research endeavor.”
2025
Assefa, D. Z., Ishizaka, A., & La Torre, D. (2025). Exploring the ESG-finance relationship through PROMETHEE ranking. Annals of Operations Research.
https://doi.org/10.1007/s10479-025-06797-0
Bag, S., Gupta, S., Galera‐Zarco, C., & Laguir, I. (2025). Developing green hydrogen‐based regenerative supply chain strategies for a sustainable future : An empirical study. Business Strategy and the Environment, 34(6), 6968‑6990. https://doi.org/10.1002/bse.4334
Bag, S., Routray, S., Rahman, M. S., & Gupta, S. (2025). Digital innovation for circular supply chain sustainability and resilience for achieving carbon neutrality: An empirical study. Journal of Environmental Management, 386, 125665. https://doi.org/10.1016/j.jenvman.2025.125665
Bag, S., Rahman, M. S., Gupta, S., & Lopes De Sousa Jabbour, A. B. (2025). Artificial intelligence driven ethical procurement systems, circular economy and governance: A supplier performance analysis. Journal of Purchasing and Supply Management, 101075. https://doi.org/10.1016/j.pursup.2025.101075
Cantini, A., Coruzzolo, A. M., De Carlo, F., Lolli, F., & Peron, M. (2025). Additive or conventional manufacturing for the management of spare parts inventories? The impact of qualification testing. Production Planning & Control, 36(16), 2223‑2246. https://doi.org/10.1080/09537287.2025.2494096
Chakraborty, K., Adnan, Z. H., Bag, S., & Gupta, S. (2025). A study on pricing, emission reduction, and innovative digital investment strategies for competitive or cooperative EV supply chains. Journal of Cleaner Production, 512, 145239. https://doi.org/10.1016/j.jclepro.2025.145239
Chaudhuri, N., Gupta, G., & Popovič, A. (2025). Do you believe it? Examining user engagement with fake news on social media platforms. Technological Forecasting and Social Change, 212, 123950. https://doi.org/10.1016/j.techfore.2024.123950
Chaudhuri, N., Gupta, G., & Popovič, A. (2025). Do you believe it? Examining user engagement with fake news on social media platforms. Technological Forecasting and Social Change, 212, 123950. https://doi.org/10.1016/j.techfore.2024.123950
Chen, L., Han, S., Gupta, S., Sivarajah, U., & A. Yamoah, F. (2025). A novel untapped flight segment flow prediction framework based on graph deep learning and heuristic algorithm for sustainable transport development. Journal of the Operational Research Society, 76(7), 1338‑1354. https://doi.org/10.1080/01605682.2024.2433191
Deng, H., Huang, Z., Wu, J., Güneri, F., Shen, Z. Y., & Yu, C. (2025). Harnessing the power of industrial robots for green development: Evidence from China’s manufacturing industry. Technological Forecasting and Social Change, 215, 124099. https://doi.org/10.1016/j.techfore.2025.124099
Goldani, N., Ishizaka, A., Kazemi, M., & Khan, J. (2025). Enhancing pairwise comparisons for multi-criteria decision making : Application to healthcare waste management. IMA Journal of Management Mathematics, 36(4), 759‑793. https://doi.org/10.1093/imaman/dpaf020
Gupta, S., Modgil, S., Lopes De Sousa Jabbour, A. B., Laguir, I., & Stekelorum, R. (2025). Towards digital transformation and governance in the healthcare sector. Information Technology & People, 38(5), 2163‑2186. https://doi.org/10.1108/ITP-02-2023-0179
Gupta, S., Modgil, S., Tuunanen, T., Zhang, Z., & Ali, I. (2025). Blockchain‐based innovation in platforms for user‐centricity and transparency. R&D Management, 55(5), 1683‑1702. https://doi.org/10.1111/radm.12780
Gupta, S., Modgil, S., Tuunanen, T., & Kar, A. K. (2025). Transitioning to ai-enabled generative cyber-physical servicescape. Information Systems Frontiers. https://doi.org/10.1007/s10796-025-10616-z
Gupta, G., & Chaudhuri, N. (2025). Decoding GenAi assimilation in teams: A multi-method study of GenAi’s impact on collaborative performance in project-based work. Information Systems Frontiers. https://doi.org/10.1007/s10796-025-10646-7
Krishankumar, R., & Ishizaka, A. (2025). Solar panel prioritization with a combined multi-criteria approach including hyperbolic fuzzy set. Annals of Operations Research. https://doi.org/10.1007/s10479-025-06798-z
Krishna, P., Majumdar, A., & Bose, I. (2025). All that glitters is not code? Understanding the predictors of developer popularity and sponsorship on a social coding platform. Production and Operations Management, 10591478251405119.
https://doi.org/10.1177/10591478251405119
Kucukkoc, I., Finco, S., Peron, M., & Aydin Keskin, G. (2025). Including mechanical requirements in a bi-objective nesting and scheduling model for additive manufacturing. European Journal of Operational Research, 325(3), 416‑432. https://doi.org/10.1016/j.ejor.2025.03.022
Larsen, K. R., Mueller, R. M., Bonaretti, D., Fischer-Preßler, D., Burleson, J. (Jim), Singh, N., Parsons, J., Pillet, J.-C., Sang, L., & Zhang, Z. (Drew). (2025). The item ontology: A tool to elucidate the anatomy of psychometric indicators. Information Systems Research, isre.2023.0257. https://doi.org/10.1287/isre.2023.0257
Leoni, L., Peron, M., & De Carlo, F. (2025). Machine learning-based predictive maintenance: Empirical insights of challenges and countermeasures. Production Planning & Control, 1‑30.
https://doi.org/10.1080/09537287.2025.2555924
Liang, Y., Qin, J., & Ishizaka, A. (2025). Assessment of digital economy development with the new multicriteria sorting method: DCMSort. Omega, 132, 103224. https://doi.org/10.1016/j.omega.2024.103224
Lin, W., Wang, Y., Zhang, Q., Peron, M., & Lu, J. (2025). Emerging opportunities or paradoxes : Assessing the effect of digital technology adoption on corporate carbon performance. Journal of Environmental Management, 391, 126399. https://doi.org/10.1016/j.jenvman.2025.126399
Lolli, F., Coruzzolo, A. M., Forgione, C., Peron, M., & Sgarbossa, F. (2025). Auto-AzKNIOSH : An automatic NIOSH evaluation with Azure Kinect coupled with task recognition. Ergonomics, 68(10), 1718‑1734. https://doi.org/10.1080/00140139.2024.2433027
Lolli, F., Coruzzolo, A. M., Peron, M., & Sgarbossa, F. (2025). Insourcing additive manufacturing for spare parts production : Is it profitable? An extensive analysis and the proposal of a Decision Support System. International Journal of Production Research, 63(11), 3961‑3981. https://doi.org/10.1080/00207543.2024.2432470
Lopes De Sousa Jabbour, A. B., Laguir, I., Stekelorum, R., & Gupta, S. (2025). The nexus of artificial intelligence and sustainability performance : Unveiling the impact of supply chain transparency and customer pressure on ethical conduct. Journal of Environmental Management, 379, 124847. https://doi.org/10.1016/j.jenvman.2025.124847
Markovic, S., Iglesias, O., Torres, A., Rivera‐Torres, P., & Koporcic, N. (2025). Unpacking the relationship between co‐creation and brand equity: A multi‐study approach. European Management Review, emre.70030. https://doi.org/10.1111/emre.70030
Modgil, S., Gupta, S., Kar, A. K., & Tuunanen, T. (2025). How could Generative AI support and add value to non-technology companies – A qualitative study. Technovation, 139, 103124. https://doi.org/10.1016/j.technovation.2024.103124
Müller, S. D., Zaggl, M., Svangaard, R., & Jakobsen, A. M. (2025). Digital Transformation Toward Data-Driven Decision-Making: Theorizing Action Strategies in Response to Transformation Challenges. Communications of the Association for Information Systems, 56, 961-999. https://doi.org/10.17705/1CAIS.05637
Pattanaik, P. K., Gupta, S., Pani, A. K., Himanshu, U., & Pappas, I. O. (2025). Impact of inter and intra organizational factors in healthcare digitalization: A conditional mediation analysis. Information Systems Frontiers, 27(3), 1275‑1302. https://doi.org/10.1007/s10796-024-10522-w
Sahoo, S., Kumar, A., Mangla, S. K., & Ishizaka, A. (2025). Examining the effects of industry 4. 0 adoption, information acquisition capability, and organizational ambidexterity on innovation and circular economy performance. Business Strategy and the Environment, 34(2), 1590‑1606. https://doi.org/10.1002/bse.4067
Sbrana, G., & Silvestrini, A. (2025). The structural Theta method and its predictive performance in the M4-Competition. International Journal of Forecasting, 41(3), 940‑952. https://doi.org/10.1016/j.ijforecast.2024.08.003
Sbrana, G. (2025). Markov Walk and Walmart sales prediction. Journal of the Operational Research Society, 1‑12. https://doi.org/10.1080/01605682.2025.2569661
Sedighi‐Maman, Z., Gupta, A., Wilkerson, G. B., & Popovič, A. (2025). Machine learning approaches for improved understanding of factors associated with history of sport‐related concussion. Risk Analysis, risa.70061. https://doi.org/10.1111/risa.70061
Sègbotangni, E. A., Laguir, I., & Gupta, S. (2025). Exploring the effect of supply chain integration and supply chain transparency on SME environmental performance under conditions of environmental unpredictability. Journal of Environmental Management, 375, 124225. https://doi.org/10.1016/j.jenvman.2025.124225
Trinh, T. (2025). The effect of modern information technology on corporate payout policy. Evidence from EDGAR implementation. Journal of Economic Studies, 52(5), 872‑886. https://doi.org/10.1108/JES-05-2024-0366
Tsirozidis, G., Kirk, U. B., & Zaggl, M. A. (2025). Benefits for thee, not for me? mHealth engagement through the lens of privacy calculus theory and trust. Behaviour & Information Technology, 44(19), 4663‑4683. https://doi.org/10.1080/0144929X.2025.2485395
Yang, F., Qian, Y., & Xie, H. (2025). Addressing endogeneity using a two-stage copula generated regressor approach. Journal of Marketing Research, 62(4), 601‑623. https://doi.org/10.1177/00222437241296453
Zaggl, M. A., Block, J., & Wissel, J. (2025). Certification of open source software compliance: Insights from a conjoint experiment. Information Systems Journal, isj.70014. https://doi.org/10.1111/isj.70014
Zhang, S., Chen, R., Wu, J., & Zhu, N. (2025). Scale measurement and economic effect evaluation of smart agriculture in China. Socio-Economic Planning Sciences, 99, 102195. https://doi.org/10.1016/j.seps.2025.102195
2023-24
- Research Talk – Thursday, 12 October, 2023: Ning Zhong (assistant professor of marketing at Smeal College of Business, Pennsylvania State University). Using Text Analytics Models to Examine Consumer Mobility Patterns.
The AI, Data Science & Business, Insights & Value Creation sub-area
- Research Talk – Monday, 18 December, 2023, Paris campus: “Exploring the Power of Advanced Social Network Analysis in Understanding Business and Social Dynamics”, Giuseppe Giordano (University of Salerno).
- Research Talk – Wednesday, 15 May and Thursday 16 May, Reims Campus: Prof. Fan Yang Wallentin, Uppsala University. Prof. Wallentin’s research interests focus on the theory and applications of structural equation modelling and other types of multivariate statistical analysis, particularly their applications in the social and behavioural sciences.
- Eye-Tracking Workshop – Thursday, 23 May, Rouen Campus: by Prof. Michel Wedel, Distinguished University Professor (PepsiCo Chair in Consumer Science), Robert H. Smith School of Business, University of Maryland. The eye-tracking workshop is open to all NEOMA Faculty and PhD students, as well as research collaborators from other business schools.
- Research Talk – Friday, 24 May, Rouen Campus and hybrid: Research Talk: “Strategic Merchant Competitions and Growth Opportunities for Small Deal Platforms” by Prof. Jie Zhang, Dean’s Professor of Marketing, Harvey Sanders Fellow of Retail Management, Robert H. Smith School of Business, University of Maryland.
- Research Talk – Thursday, 6 June 2024, Reims Campus: Professor Riccardo Vecchio from the University of Naples Federico II. Professor Vecchio is renowned for his expertise in Wine and Food Marketing, Consumer Behavior, and Experimental Economics, making his research focus highly relevant to the themes of the Chair.
Pedagogy
Examples of courses linked to this sub-Area include: "Data Analytics for Strategic Decisions", "Financial Data & Analytics", "Blockchain and Fintech", "Data Science for Finance", "Big Data for Finance", "Machine Learning and Artificial Intelligence in Finance",” "Digital Markets and Society", "Search Engine Marketing and Community Management", "UX Design", "Unstructured Data Analysis", "Data Analysis and Business Intelligence", "Machine Learning and Artificial Intelligence for Business", "Product, Design and Innovation", "Ethics, Consumption and Technology"
Pint of Science Festival 2021. Gaël Bonnin talked about the impact of virtual reality on the attractiveness of tourist attractions at the Pint of Science Festival, a national event aimed at demystifying and making scientific research accessible to the general public. View the replay (at 39:40)
Chairs, partners, and funded projects
The AE includes two externally funded research projects:
- AdoptBlockChain (Grand Est Region) , whose goal is to study the adoption of blockchain technology and its impact in the supply chain context.
- AI adoption in Reims Firms (Grand Reims), whose goal is to evaluate the use of AI technologies by local industry and farmers, to understand the resistance to use and assess the business impact of AI adoption
The AE also integrates the SPOC Institute. Created in 2015 with an applied research orientation, the goal of SPOC Institute is to better the adoption as well as the societal and business consequences of the development of robotics.
FNEGE Medias: Giacomo Sbrana discusses making forecasts with damped model tendency using a structural approach. Watch video

Key Facts
- 50+ research projects
- 20+ internal and external grants
- 30+ professors working on projects
- 104 courses
- SPOC Institute
Chairs, partners and financed projects








