Faculty & Research
Areas of Excellence: a 360° expertise for an impactful Research
AI, Data Science & Business
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.”
Specific sub-areas of research
ALLAL-CHERIF, O., " Intelligent cathedrals: using augmented reality, virtual reality, and artificial intelligence to provide an intense cultural, historical, and religious visitor experience", Technological Forecasting and Social Change, May 2022, vol. 178.
Dhar, S., I. Bose, “Walking on air or hopping mad? Understanding the impact of emotions, sentiments and reactions on ratings in online customer reviews of mobile apps,” Decision Support Systems, March 2022.
BOSE I., AGUIR, I., S. MODGIL, S. GUPTA, R. STEKELORUM, "Performance effects of analytics capability, disruption orientation, and resilience in the supply chain under environmental uncertainty" in Annals of Operations Research, January 2022 (Rank 2)
ARSENYAN, J., A. MIROWSKA, “Almost human? A comparative case study on the social media presence of virtual influencers,” International Journal of Human-Computer Studies, November 2021, vol. 155, pp. 102-694
GUPTA S., S. MODGIL, R. MEISSONIER, Y. K. DWIVEDI, "Artificial Intelligence and Information System Resilience to Cope With Supply Chain Disruption" in IEEE Transactions on Engineering Management, October 2021 (Rank 2).
CHAUDHURI, N., G. GUPTA, V. VAMSI, I. BOSE, "On the platform but will they buy? Predicting customers' purchase behavior using deep learning", Decision Support Systems, October 2021, vol. 149
MIROWSKA, A., L. MESNET, “Preferring the devil you know: Potential applicant reactions to artificial intelligence evaluation of interviews,” Human Resource Management Journal, September 2021, online
ALLAL-CHERIF, O., A. YELA ARANEGA, R. CASTAÑO SANCHEZ, "Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence", Technological Forecasting and Social Change, August 2021, vol. 169
JAMMELI, H., R. KSANTINI, F. BEN ABDELAZIZ, H. MASRI, "Sequential Artificial Intelligence Models to Forecast Urban Solid Waste in the City of Sousse, Tunisia", IEEE Transactions on Engineering Management, June 2021
ISHIZAKA, A., V. PEREIRA, S. SIRAJ, "AHPSort-GAIA: a visualisation tool for the sorting of alternative in AHP portrayed through a case in the food and drink industry", Annals of Operations Research, May 2021
FOSSO WAMBA, S., M. QUEIROZ, L. TRINCHERA, "Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation", International Journal of Production Economics, November 2020, vol. 229
SBRANA, G., A.SILVESTRINI, "Forecasting with the damped trend model using the structural approach", International Journal of Production Economics, August 2020, vol. 226
CHAUDHURI, N., I. BOSE, "Exploring the Role of Deep Neural Networks for Post-disaster Decision Support", Decision Support Systems, March 2020, vol. 130
LANGE, A.-C., M.LENGLET, R.SEYFERT, "On studying algorithms ethnographically: Making sense of objects of ignorance", Organization, July 2019, vol. 26, no. 4
CÔRTE-REAL, N., P.RUIVO, T.OLIVEIRA, A.POPOVIC, "Unlocking the drivers of big data analytics value in firms", Journal of Business Research, April 2019, vol. 97
ACHARYA, A., S.SINGH, V.PEREIRA, P.SINGH, "Big Data, Knowledge Co-creation and Decision Making in Fashion Industry", International Journal of Information Management, October 2018, vol. 42
GOUDEY, A., G.BONNIN, "Must smart objects look human? Study of the impact of anthropomorphism on the acceptance of companion robots", Recherche et Applications en Marketing, April 2016, vol. 31, no. 2
Research Talk Thursday, March 31th, 2022 - Online -Massimo Aria, Full Professor in Statistics for Social Sciences in Department of Economics and Statistics, University of Naples Federico II “Introduction to “Bibliometrix”, an R-tool for Comprehensive Science Mapping Analysis”.
Research seminar – February 24, 2022 -Online- Patrick Mikalef, Associate Professor in Data Science and Information Systems, Department of Computer Science, Norwegian University of Science and Technology In the past, he has been a Marie Skłodowska-Curie post-doctoral research fellow working on the research project "Competitive Advantage for the Data-driven Enterprise" (CADENT). He received his B.Sc. in Informatics from the Ionian University, his M.Sc. in Business Informatics for Utrecht University, and his Ph.D. in IT Strategy from the Ionian University. His research interests focus on the strategic use of information systems and IT-business value in turbulent environments. He has published work in international conferences and peer-reviewed journals including the Journal of Business Research, British Journal of Management, Information and Management, Industrial Management & Data Systems, and Information Systems and e-Business Management. He presented The business value of responsible AI. This talk explores the notion of responsible AI from a governance point of view.
Academic research seminar – January 20, 2022 - Online - Guest speaker: Prof. Christian Janiesch is Professor for Enterprise Computing at the TU Dortmund University. His research focusses on intelligent systems at the intersection of business process management and artificial intelligence with frequent applications in the Industrial Internet of Things. He is editor for BISE, IJMR, and JBA. He has authored over 150 scholarly publications. This has appeared in journals such as the Journal of the Association for Information Systems, Communications of the Association for Information Systems, Information & Management, Business & Information Systems Engineering, Information Systems, Decision Support Systems, Future Generation Computer Systems as well as in various major international conferences including ICIS, ECIS, BPM, and HICSS and has been registered as U.S. patents.
Project review workshop – December 2, 2021 - Online - The goal of this meeting is to know about the progress of the research projects that were granted funds under the respective sub-areas. Several grant holding faculty members will be presenting the progress of their research project and sharing their experiences.
Academic research seminar – November 18, 2021 - Prof. Cheng Zhang, professor and chair at Department of Information Management & Information Systems, Fudan University, China. His research interests include IT business value and innovation. He has more than 40 papers published by prestigious journals including MIS Quarterly, Journal of Management Information Systems, Journal on Computing, Production and Operations Management, Marketing Science, and Journal of Marketing.
Academic research seminar - October 21, 2021 – Online - Use of AR Technology to Promote Innovative Products, by Prof. Chee Wei (David) Phang, Head of Department for EMM, Professor in Marketing and Information Systems, University of Nottingham Ningbo China
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