Formalizing Experiential Knowledge For Analysis And Diagnosis Of Sme.

LUCAS BOULLOSA; CECILIA ZANNI-MERK; NATHALIE GARTISER; ANA CASALI

Buenos Aires

Workshop; The International Workshop on Applied Modeling and Simulation; 2013

IEEE

<!-- @page { margin: 2cm } P { margin-bottom: 0.21cm; direction: ltr; color: #000000; text-align: justify; widows: 2; orphans: 2 } P.western { font-family: "Times New Roman", serif; font-size: 10pt; so-language: en-GB } P.cjk { font-family: "Times New Roman", serif; font-size: 10pt; so-language: zh-CN } P.ctl { font-family: "Times New Roman", serif; font-size: 10pt; so-language: ar-SA } A:link { color: #0000ff } --> This article describes the research project MAEOS, whose purpose is to model the organizational and strategic development of SMEs. The main objective of this project is to improve the efficiency and performance of business advice given to this enterprises by establishing a set of methods and software tools for its analysis and diagnosis. In order to achieve this, a multi-disciplinary team was created in which two main research areas are represented: artificial intelligence and management science. In this work several key questions of the knowledge engineering field are addressed by the team: how to extract theoretical knowledge (e.g. from scientific works in management science) and practical one (e.g. from consultants); how to formalize it and use it to assist consultants in their daily work.