Research activities in the field of business analytics (BA) and supply chain management (SCM) are focused on analyzing data collected from a variety of sources and decision making informed by data analysis and supported by optimization techniques, with the aim of enabling enterprises and organizations to improve their service levels and operational efficiency, in particular in the context of supply chain and logistics management.
The main areas of expertise are therefore analytical methods of uncovering business insights and predicting future situations with use of data (statistical and data mining methods: nonparametric regression models, censored data analysis, discrete choice models, machine learning, natural language processing, pattern recognition, simulation and digital twins…), and also of recommending decisions (operations research methods: mathematical modelling, stochastic programming, combinatorial optimization, exact and heuristic solution approaches, discrete mathematics,…).
SCM is a major field of application of such analytical methods, and these areas are frequently associated in the so-called “industrial engineering” departments of many foreign universities.
Research in BA & SCM includes: Design and coordination of supply chains and intermodal transport networks; production, distribution, and transport planning; vehicle routing and loading; pricing and revenue management in transport; reduction of energy consumption and pollutant emissions; health care operations management; portfolio optimization and stock market forecasting; clustering and question-answering systems; methodological developments in the fields of expertise.
At HEC Liège, the Business Engineering curriculum is strongly associated to our research field through core courses, mainly in analytics, and the two fields of specialization “SCM and BA” and “Digital Business”. The Master in Management Science also benefits of the BA & SCM research field through some core courses in quantitative methods and the specialization in “Global Supply Chain Management”.
We aim at transferring our competencies and internationally recognized research and expertise to our local community and our international partners. The researchers in BA & SCM perform fundamental and applied research. They have numerous collaborations with the public and private sectors. It’s at the same time a need, for data and knowledge, and a goal. In the same spirit, we favor partnerships with companies through chairs and PhD funding; e.g. based on the Digital Lab platform.
Research activities in the fields of BA & SCM are mostly conducted by the research team QuantOM (Quantitative methods and Operations Management). QuantOM is the association of several researchers under a common label to stimulate and promote research conducted at HEC Liège (or more broadly, within the ULg) in the fields of quantitative methods and of their applications in SCM and other areas of management and economics.
MEMBERS OF THE FIELD
ARDA DE SILVEIRA Yasemin, Full Professor, PhD
CRAMA Yves, Full Professor, PhD
HENG Samedi, Assistant Professor, PhD
HEUCHENNE Cédric, Full Professor, PhD
ITTOO RAVI Ashwin, Associate Professor, PhD
LIMBOURG Sabine, Full Professor, PhD
PAQUAY Célia, Assistant Professor, PhD
PIRONET Thierry, Associate Professor, PhD
SCHYNS Michael, Full Professor, PhD
FRANÇOIS Véronique, Researcher, PhD
BARATTO Marie, Teaching & Research Assistant, PhD Candidate
BEBRONNE Elodie, Teaching & Research Assistant, PhD Candidate
CASTILLO LENZ Sergio, Researcher, PhD Candidate
CHUOR Porchourng, Researcher, PhD Candidate
ETIENNE Elodie, Teaching & Research Assistant, PhD Candidate
EVERS Justine, Researcher, PhD Candidate
GILLAIN Cédric, Researcher, PhD Candidate
JAMAR Julie, Teaching & Research Assistant, PhD Candidate
LELOUP Emeline, Teaching & Research Assistant, PhD Candidate
MAHARANI Anisha, Teaching & Research Assistant, PhD Candidate
NGUYEN Thi Thuy Van, Teaching & Research Assistant, PhD Candidate
POUMAY Judicaël, Researcher, PhD Candidate
TRAN PHUONG Hanh, PhD Candidate
TONKA Jenny, Researcher, PhD Candidate