Computational business management and marketing models
In the real world there are many examples of complex systems such as the social ones (people have a natural tendency to form groups: families, circles of friends, professional or religious groups, cities, nations, etc.), the business/economic ones (companies, clients, etc.) and the biological ones (e.g. metabolic networks). Given the important role that complex systems play in our environment, their understanding, quantification, prediction and eventually control have acquired a capital importance, becoming one of the main intellectual scientific challenges of the 21st century.
In the field of Economics, these complex phenomena can be modeled through different types of simulation models: classical econometric models, system dynamics models and models based on artificial intelligence (AI) techniques such as social simulation carried out with agent-based models (ABM), among others. These models allow to extract knowledge that helps to understand how the relationships between customers, brands and media drive all market dynamics. Instead of thinking about big ideas and testing them in the market, we can test them by running experiments in a virtual marketplace and learn from those simulations by continuously asking “what-if” scenarios at a negligible cost. In addition, marketers can study how “word-of-mouth” and social influences travel in a network of consumers, thus being able to test the effects of advertising campaigns and marketing strategies on the diffusion of innovation at the macro level.
In this way, the use of ABMs and other AI technologies can improve marketing and business management processes by providing new knowledge to decision makers and supporting decision making on an unprecedented scale. Our main objective in this line of research is to exploit the use of AI/computational intelligence techniques (in particular ABM, social network analysis, interpretable and non-interpretable machine learning algorithms, advanced search and optimization algorithms, and probabilistic and enabling knowledge representation and reasoning frameworks) to design realistic models of marketing/business management problems, develop knowledge extraction tasks from data in these domains, and assist the associated decision maker. In particular, several of our research developments are being applied in the market through a technological alliance with the marketing consulting firm R0D Brand Consultants in the commercial product Zio Analytics, which incorporates our AI solutions for strategic branding and consumer behavior modeling in virtual markets.
Contact: Óscar Cordón García
|Bermejo Nievas, Enrique||enrique.bermejo@decsEyIKoJLai.ugr.es||DaSCI Technology Applications Area, Computational Intelligence Area||PhD|
|Casillas Barranquero, Jorge||casillas@dekh9P0tAXPRzcsai.ugr.es||Data Science and Big Data Area||PhD|
|Chica Serrano, Manuelemail@example.comPdBq0BSgr.es||DaSCI Technology Applications Area||PhD - Ramón y Cajal|
|Cordón García, Óscarfirstname.lastname@example.orgRSNYvUxnugr.es||DaSCI Technology Applications Area||PhD|
|Damas Arroyo, Sergio||sdamas@ugr1cBuJ0P.es||DaSCI Technology Applications Area||PhD|
|Giráldez Crú, Jesús||jgiraldez@r@@LLRJT31R.ugr.es||DaSCI Technology Applications Area||PhD - Juan de la Cierva|
|Melero Rus, Francisco Javier||fjmelero@ugr.RIvShBGyes||DaSCI Technology Applications Area, Data Science and Big Data Area, Computational Intelligence Area||PhD|