AI-Driven Business

AI Strategy for Competitive Advantage

(Head: Dr André Nemeh)
This sub-area studies how AI impacts businesses and their strategies and policies. AI is considered as a special resource offering magnified data processing capabilities that advance the acquisition, understanding, and processing of knowledge, as well as resource allocations in companies. This helps shape the decision making and consequent performance of strategic actions. The rise of AI may fundamentally change how firms obtain and sustain their competitive advantages, not just for high-technology industries, but also for more traditional businesses. Researchers of this sub-area develop new theories supported by empirical evidence to explore this novel opportunity.

AI for Operations, Optimisation & Automation

(Head: Dr Oncü Hazir)
This sub-area involves investigating how AI and big data analytics can offer new opportunities to deal with challenges in operations and project management. A key challenge in the new era of AI, which researchers of this sub-area focus on, is the need to make rapid decisions which cope with the uncertainty and inherent complexity of a dynamic business environment. Computational intelligence approaches of AI and big data analytics tools help address this challenge by supporting decision making under uncertainty.

Human & Ethical AI

(Head: Dr Laura Noval)
This sub-area recognises that the development and exploitation of AI technologies in business raises anxiety and excitement surrounding its future implications for businesses, individual workers and societal fairness. For businesses, the developments in AI will clearly offer gains in productivity and reduction of human error by replacing certain non-routine and cognitive tasks currently requiring human intelligence. However, this development poses multiple social and environmental concerns relevant to business managers and policy makers. Researchers working for this sub-area investigate questions pertinent to these issues and business solutions to such problems.

The professors and PhD students in this research center are actively working around the three research clusters, with 19 publications in top-level international academic journals such as the International Journal of Production Economics, European Journal of Operational Research, Human Resource Management Journal, Technological Forecasting and Social Change and Tourism Management among others. They are also engaged in dissemination of their research through teaching on the AI summer school, the MSc in Big Data Analytics, the MSc in Strategic and Digital Marketing and on the PhD programme at Rennes SB.

Research Themes

Full Professors

• Dermot BRESLIN, Organisation Change-Creativity-Organisational Learning
• Helmi HAMMAMI, Accounting Information Systems
• Sarah HUDSON, CSR, Technology & employee well-being
• Ronan JOUAN de KERVENOAEL, Technologies, digital transformation, strategies and strategists
• Dr Balaji MAKAM, Sustainability communication and perceptions
• Rod McCOLL, Service management; Digital media and advertising
• Marco MICHELOTTI, Strategic HRM, Workplace and Industrial/Employee Relations
• Petya PUNCHEVA,  Sustainable development and AI-driven business
• Dirk SCHNECKENBERG, Perception and Adaptation of new Technologies
• Reza ZANJIRANI-FARAHANI, Operations Models and Artificial Intelligence to Manage Disasters

Associate Professors

• Claire-Lise ACKERMANN, Open Innovation
• Maher AGI,  eBusiness
• Christos ALEXAKIS, Sustainable finance, capital markets, SMEs
• Jbid ARSENYAN, Networks-Resilience
• Tuba BAKICI, Innovation Management
• Carole BONANNI, E-Business-Strategic Management
• Taoufik BOURAOUI, Financial Markets; Islamic Finance; Econometrics; Risk Management
• Ronald CLARKE, Social Networks-Intergroup Relations-Teams
• Irena DESCUBES, Sustainability-Cross Cultural Negotiations
• Pradeep DIVAKARAN, Data driven and digital marketing; Innovation & Marketing Management
• Mehdi FARAJALLAH, Knowledge Management
• Cilem Selin HAZIR, Knowledge Networks and Innovation; Sustainability Transition
• Oncu HAZIR, Project Management; Inventory Management; Machine scheduling
• Akanksha JALAN, Financial reporting and quality; corporate governance
• Sheila MATSON, Food, culture and Tourism
• Hamid MAZLOOMI, Innovation Management and Absorptive Capacity
• André NEMEH, Technological Innovation and Strategic Management
• Laura Noval, Behavioural Business Ethics
• Dr Antonio VEZZANI, Innovation and Technology Management

Assistant professors

• Malak EL HALABI
• Sohrab FARAMARZI OGHANI
• Clara KOETZ, Customer experience, social norms
• Ljupka NAUMOVSKA, Multigenerational Marketing
• Ozlem OZKOK, Customer service technologies, service innovation
• Gerald-Reparate RETALI, Information and communication technology in healthcare
• Hichem REZGUI, Quality of financial information
• Dima TAWIL, Performance and risk measurement; Behavioral finance

PhD Students

• Yara Atallah
• Keyvan Fardi
• Karen Rankin
• Mohammad Tarhini
• Lakshmi Vuddaraj

The professors and PhD students in this research center are actively working around the three research clusters, with 19 publications in top-level international academic journals such as the International Journal of Production Economics, European Journal of Operational Research, Human Resource Management Journal, Technological Forecasting and Social Change and Tourism Management among others.

• de Kervenoael, R., Schwob, A., Manson, I.T. et al. (2022) Business-to-business and self-governance practice in the digital knowledge economy: learning from pharmaceutical e-detailing in Thailand. Asian Business and Management, 21, 598–622
• Bakici, T., Nemeh, A., Hazir, Ö.(2023) Big Data Adoption in Project Management: Insights from French Organizations IEEE Transactions on Engineering Management, vol. 70, no. 10, pp. 3358-3372, Oct. 2023
• Baek, C.H., Kim, S.-Y., Lim, S.U. and Xiong, J. (2023) Quality evaluation model of artificial intelligence service for startups. International Journal of Entrepreneurial Behavior & Research,  Vol. 29 No. 4, pp. 913-940.
• Shamima Ahmed, Muneer M. Alshater, Anis El Ammari, Helmi Hammami (2022) Artificial intelligence and machine learning in finance: A bibliometric review. Research in International Business and Finance, Volume 61, 2022, 101646
• “Schwob, A., de Kervenoael, R., Kirova, V. and Vo-Thanh, T. (2023), Casual selling practice: a qualitative study of non-professional sellers’ involvement on C2C social commerce platforms. Information Technology & People, Vol. 36 No. 2, 2023, pp. 940-965 “
• Truong, Y., Schneckenberg, D., & M. Battisti & R. Jabbouri (2023). Artificial Intelligence as an Enabler for Entrepreneurs: An Integrative Perspective and Future Research Directions. International Journal of Entrepreneurial Behaviour & Research, 29(4), 801-815
• Reza Zanjirani Farahani, Rubén Ruiz, Luk N. Van Wassenhove (2023) Introduction to the special issue on the role of operational research in future epidemics/ pandemics, European Journal of Operational Research, Volume 304, Issue 1, 2023, Pages 1-8
• Hammami, H, Rezgui, H. (2022) Intelligence artificielle : quel impact sur le monde du chiffre. Revue Française de Comptabilité, volume 567, Septembre 2022
• Pavan Kumar Nagula, Christos Alexakis (2022) A new hybrid machine learning model for predicting the bitcoin (BTC-USD) price. Journal of Behavioral and Experimental Finance, Volume 36, 2022, 100741
• Alexandre Schwob, Ronan de Kervenoael, Valentina Kirova & Yan San Sim (2022) Understanding and harnessing the potential of front-line employees’ self-governance in technologised museums and theme parks: insights from a qualitative study, Museum Management and Curatorship, DOI: 10.1080/09647775.2022.2111334
• Timur Narbaev, Oncu Hazir, Maher Agi (2022) A Review of the Use of Game Theory in Project Management. Journal of Management in Engineering, Volume 38 Issue 6 – November 2022, 03122002
• Nagula, P.K., Alexakis, C. (2022) A Novel Machine Learning Approach for Predicting the NIFTY50 Index in India. International Advances in Economic Research . Volume 28, issue 3-4, pp 155–170
• Tekin, K., Bakici, T. , Hazir, O. (2022). Completing Projects on Time and Budget: A Study on the Analysis of Project Monitoring Practices Using Real Data. IEEE Transactions on Engineering Management. DOI: 10.1109/TEM.2022.3227428
• J. Arsenyan and A. Piepenbrink (2023) Artificial Intelligence Research in Management: A Computational Literature Review. IEEE Transactions on Engineering Management, doi: 10.1109/TEM.2022.3229821.
• “Helena V. González-Gómez, Sarah Hudson (2023) Employee frustration with information systems: appraisals and resources, European Management Journal, https://doi.org/10.1016/j.emj.2023.03.004”
• Ronan de Kervenoael, Alexandre Schwob, Rajibul Hasan & Sara Kemari (2023) Food choice and the epistemic value of the consumption of recommender systems: the case of Yuka’s perceived value in France, Behaviour and Information Technology https://doi.org/10.1080/0144929X.2023.2212088
• Jbid Arsenyan, Agata Mirowska, Anke Piepenbrink (2023) Close encounters with the virtual kind: Defining a human-virtual agent coexistence framework. Technological Forecasting and Social Change, Volume 193, 2023, 122644
• Nishant, R., Schneckenberg, D., & Ravishankar, M. (2023). The formal rationality of artificial intelligence-based algorithms and the problem of bias. Journal of Information Technology, 0(0). https://doi.org/10.1177/02683962231176842
• Sandro Montresor & Antonio Vezzani (2023) Digital technologies and eco-innovation. Evidence of the twin transition from Italian firms, Industry and Innovation, DOI: 10.1080/13662716.2023.2213179
• Agi, M. A., & Jha, A. K. (2022). Blockchain technology for supply chain management: An integrated theoretical perspective of organizational adoption. International Journal of Production Economics, 108458.
• Ahmed, S., Alshater, M. M., El Ammari, A., & Hammami, H. (2022). Artificial intelligence and machine learning in finance: A bibliometric review. Research in International Business and Finance, 61, 101646.
• Aziz, S., Dowling, M., Hammami, H., & Piepenbrink, A. (2022). Machine learning in finance: A topic modeling approach. European Financial Management, 28(3), 744-770.
• Baek, C. H., Kim, S. Y., Lim, S. U., & Xiong, J. (Forthcoming). Quality evaluation model of artificial intelligence service for startups. International Journal of Entrepreneurial Behavior & Research. https://doi.org/10.1108/IJEBR-03-2021-0223
• Bakici, T., Nemeh, A., & Hazir, Ö. (Forthcoming). Big data adoption in project management: Insights from French organizations. IEEE Transactions on Engineering Management. 10.1109/TEM.2021.3091661
• Farahani, R. Z., Ruiz, R., & Van Wassenhove, L. N. (Forthcoming). Introduction to the Special Issue on the role of Operational Research in future epidemics/pandemics. European Journal of Operational Research, 304(1).
• Jalan, A., Matkovskyy, R., & Potì, V. (2022). Shall the winning last? A study of recent bubbles and persistence. Finance Research Letters, 45, 102162.
• Michelotti, M., McColl, R., Puncheva‐Michelotti, P., Clarke, R., & McNamara, T. (Forthcoming). The effects of medium and sequence on personality trait assessments in face‐to‐face and videoconference selection interviews: Implications for HR analytics. Human Resource Management Journal. https://doi.org/10.1111/1748-8583.12425
• Nagula, P. K., & Alexakis, C. (2022). A new hybrid machine learning model for predicting the bitcoin (BTC-USD) price. Journal of Behavioral and Experimental Finance, 36, 100741.
• Schwob, A., de Kervenoael, R., Kirova, V. and Vo-Thanh, T. (Forthcoming), “Casual selling practice: a qualitative study of non-professional sellers’ involvement on C2C social commerce platforms”, Information Technology & People, https://doi.org/10.1108/ITP-09-2020-0635
• Atwal, G., & Bryson, D. (2021). Antecedents of intention to adopt artificial intelligence services by consumers in personal financial investing. Strategic Change, 30(3), 293-298.
• Jalan, A., Matkovskyy, R., & Urquhart, A. (2021). What effect did the introduction of Bitcoin futures have on the Bitcoin spot market?. The European Journal of Finance, 27(13), 1251-1281.
• Matkovskyy, R., Jalan, A., Dowling, M., & Bouraoui, T. (2021). From bottom ten to top ten: the role of cryptocurrencies in enhancing portfolio return of poorly performing stocks. Finance Research Letters, 38, 101405.
• Yarovaya, L., Matkovskyy, R., & Jalan, A. (2021). The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets. Journal of International Financial Markets, Institutions and Money, 75, 101321.
• Aslam, F., Aziz, S., Nguyen, D. K., Mughal, K. S., & Khan, M. (2020). On the efficiency of foreign exchange markets in times of the COVID-19 pandemic. Technological forecasting and social change, 161, 120261.
• Bouraoui, T. (2020). The drivers of Bitcoin trading volume in selected emerging countries. The Quarterly Review of Economics and Finance, 76, 218-229.
• de Kervenoael, R., Hasan, R., Schwob, A., & Goh, E. (2020). Leveraging human-robot interaction in hospitality services: Incorporating the role of perceived value, empathy, and information sharing into visitors’ intentions to use social robots. Tourism Management, 78, 104042.
• Hammami, H., Hammami, M., Coulibaly, S., & Marzouk, M. (2020). Determinants of FDI attractiveness: A MCI model approach. Economics Bulletin, 40(2), 1033-1048.
• Hasan, R., Lowe, B., & Petrovici, D. (2020). Consumer adoption of pro-poor service innovations in subsistence marketplaces. Journal of Business Research, 121, 461-475.
• Hasan, M. R., Shams, S. R., Rahman, M., & Haque, S. E. (2020). Analysing pro-poor innovation acceptance by income segments. Management Decision, 58(8), 1663-1674.
• Hazır, Ö., & Ulusoy, G. (2020). A classification and review of approaches and methods for modeling uncertainty in projects. International Journal of Production Economics, 223, 107522.
• Jha, A. K., Agi, M. A., & Ngai, E. W. (2020). A note on big data analytics capability development in supply chain. Decision Support Systems, 138, 113382.
• Matkovskyy, R., & Jalan, A. (2020). Can Bitcoin Be an Inflation Hedge? Evidence from a Quantile-on-Quantile Model. Revue économique, 7, 1021-1041.
• Matkovskyy, R., Jalan, A., & Dowling, M. (2020). Effects of economic policy uncertainty shocks on the interdependence between Bitcoin and traditional financial markets. The Quarterly Review of Economics and Finance, 77, 150-155.
• Tóth, Z., Nieroda, M. E., & Koles, B. (2020). Becoming a more attractive supplier by managing references–The case of small and medium-sized enterprises in a digitally enhanced business environment. Industrial Marketing Management, 84, 312-327.

The AI-driven Business area of excellence has different types of collaborations:

• Collaborations with other higher education institutions and organisations to enhance cooperation and create new synergies,
• Collaborations with businesses through consultancy, research and innovation development, data analysis etc.,
• Cross-disciplinary collaborations with other areas of excellence within Rennes School of Business to make each area stronger.

Information on our current key research collaborations are detailed below. We are always interested in new research collaboration opportunities. Please contact either the AI Business Director, Andre Nemeh, or any Principal Investigator to discuss the possibility of working together.

UNCTAD

AI in Research Global Survey in collaboration with UNCTAD: We gathered opinions among researchers on how the scientific community perceives the role of artificial intelligence in research.

B<>com
We partner with B-Com, the leading digital technology innovation hub in Brittany, on number of research projects on envisaging the long-term impact of AI.

• ANR-registered research project (Pollen – 2022-2025) on the social acceptability of each stage of an NLP-driven decision-making process (in collaboration with RTO)
• Metaverse and employee well-being project (2022-2023) to explore creativity and social interactions at work in the metaverse.
• ANR-registered research project (AI powered, 2018-2021) on prospecting on the future impact and development of fintech

DotLAB

We are a research partner institute with the Irish Institute of Digital Business (dotLAB), one of the largest digital business research groups in Europe. In this partnership we, as dotLAB France, specialise in textual analysis for AI business as part of a global network of research institutes

Zayed University (~100K€)
A funded research project on the application of Latent Dirichlet Allocation topic modelling to predict agricultural commodity pricing (In collaboration with Agribusiness center).

Britanny Innovation and Development agency
Regional Observatory for AI and Data Science for a project to examine: The state of AI adoption by the key sectors in Brittany and the future development of AI; Needs, main obstacles, and constraints in adopting AI; Sectoral disparities/ developments among firms: measuring the impact of AI on firms’ functions; The links between AI users and solution providers. https://tools.bdi.fr/Etudes/IA/accueil.htm

INSOFE
We collaborate with INSOFE on a number of pedagogic and research projects. INSOFE is one of the largest data science training institutes in India well-known for the excellence of their education. Our projects centre on developing case studies of AI application in business, and research into effective AI business education.

CCI Paris (~20K€)
A funded project with the CCI Paris, Paris School of Business and Università Cattolica del Sacro Cuore, to apply machine learning and deep learning to understand growth patterns of small-to-medium-sized enterprises.

Other Project funding
The AI-driven Business Research Center has received funding for various research projects:
– Banque de France : Fraud detection by using AI
– Région Bretagne (cryptomonnaie, the Economic and Financial Perspectives on Non-Fungible Tokens (NFTs) and Blockchain-Based Investment Strategies conference (May 2022).

Seminars and Workshops

Research seminars

2023

• Professor Stefano Tasselli-Rotterdam School of Management, Erasmus University : Doing more harm than good? A practice-based study on AI’s large-scale deployment and the propagation of social injustice
• Professor Dmitry Ivanov GoutAI/CUTIS joint seminar -Department of Business and Economics at Berlin School of Economics and Law (HWR Berlin), : “the use of AI and digital technology in supply chain management
• CUT – Knowledge in Society & AI Driven Business: CUT CAID – Strategic autonomy, innovation, digitalization, and Artificial Intelligence:
  • Stefano Bianchini is Associate Professor at the University Strasbourg and member of expert groups for European Commission (DG-JRC-Modelling, Indicators and Impact Evaluation; DG-RTD-Research and Innovation) and OECD (Structural Policy Analysis Division, Economics Department).
  • Pietro Moncada-Paternò-Castello is Senior Adviser in Economics and Policy of Industrial Research & Innovation at the European Commission (EC), Joint Research Centre (JRC), Directorate for Fair and Sustainable Economy (ESP). Currently Pietro leads the activities on “Innovation for Green Deal Strategy and Coordination”.
  • Zoltán Cséfalvay is Professor at Mathias Corvinus Collegium and Head of the Centre for Next Technological Futures. Previously, he worked as senior researcher at the Joint Research Centre of European Commission in Seville (2019-2020), he served as ambassador of Hungary to the OECD and UNESCO in Paris (2014-2018) and as Minister of State for Economic Strategy in Hungary (2010-2014).
  • Hélène Dernis is a statistician and analyst in the Directorate for Science, Technology and Innovation at the OECD. She is responsible for the STI Micro-data Lab, a data infrastructure that collects and links large-scale administrative, of which IP filings, and commercial micro-level datasets. She notably contributed to the development of IP-related indicators, particularly on patents.

2022

• Professor Periklis Gogas-Democritus University of Thrace, Greece: “AI & Machine Learning in Finance and Economics”
• Professor Damien Dupré-Dublin City University: “Urban and socio-economic correlates of property prices in Dublin’s area”
• Professor Miguel Minutti Meza-Miami Business School: “Regression and Machine Learning Methods to Predict Discrete Outcomes in Accounting Research”
• Professor Rohit Nishant-Laval University (Canada)- “AI and Sustainability – what does empirical evidence inform us?”
• Paavo Ritala – Professor of Strategy and Innovation at LUT School of Business and Management (Finland)- “Building and scaling industrial AI capabilities through explorative and exploitative learning: A multiple-case study”
• Professor Dmitry Ivanov-Department of Business and Economics-Berlin School of Economics and Law (HWR Berlin)- “Industry 4.0 in Supply Chain Networks and Digital Technology for Resilience Management” (Guest Speaker)
• Volodymyr Babich-McDonough School of Business, Georgetown University. (USA)- “Playing with DISASTER: Behavioral Simulations of Supply Shortages, Competition for Supplier Capacity, Blockchain-enabled Strategic Information Sharing, and Markets for Capacity-Token Trading” (Guest Speaker)

Conferences

• Economic and Financial Perspectives on Non-Fungible Tokens (NFTs) and Blockchain-Based Investment Strategies conference (https://www.ffea.eu/future-conferences/rennes-april-2022) hosted at Rennes School of Business, April 8th & 9th, 2022 (Dr. André NEMEH & Dr. Roman MATKOVSKYY)
• The centre is engaged in dissemination of their research through teaching on the AI summer school, the MSc in Big Data Analytics, the MSc in Strategic and Digital Marketing and on the PhD programme at Rennes SB.

Summer School

The AI Business Summer School is a four-week (from 15th May to 9th June) summer school programme providing the students with advanced knowledge in a wide range of aspects of data science applied to business. This includes developing knowledge of Python programming from scratch, network analysis, data visualisation, textual analysis, and application of machine learning and deep learning.

Four courses are available:

• Data Science for Business
• AI Business Intelligence
• Business Textual Learning
• Business Network Intelligence

The completion of all four courses leads to a Certificate in AI Business and each course is equivalent to 3 ECTS (1.5 US credits).

The AI Business Summer School offers a wide range of benefits:

• Having the opportunity to learn from a team of experts in AI applied to business
• Meeting with multicultural and cross-disciplinary professors who are experts in their field
• Encounter students from all over the world
• Obtaining ECTS/US credits for students’ curriculum

In the Press

• Virtual influencers by Jbid Arsenyan
• Cryptocurrencies and youth by Akanksha Jalan & Roman Matkovskyy

Dr André Nemeh
aibusiness@rennes-sb.com