26 November 2018, AT 09:30 AM
ESCP - Campus République - room Europe

Thesis Title:
Strategic Management and Machine Learning: In search of companies’ financial performance optimization in the digital age
Strategic Management and Machine Learning: In search of companies’ financial performance optimization in the digital age
Jury
Thesis directors:
- Pr. TONDEUR Hubert,
University Professor, CNAM - Pr. LAROCHE Hervé ,
Professor, ESCP - Pr. EGLEM Jean Yves,
Professor Emeritus, ESCP
Referees:
- Pr. DREYFUS Gérard ,
Professeur Emeritus, ESPCI Paris - Pr. KALIKA Michel ,
University Professor, IAE de Lyon
Suffragants :
- Pr. BURLAUD Alain,
University Professor Emeritus, CNAM - Pr. DEJOUX Cécile,
University Professor, CNAM - M. SEKKAKI Nicolas,
CEO, IBM FRANCE
Abstract
A key goal for this dissertation has been to create a conceptual and numerical model based on machine learning that allows leaders and scholars to reimagine strategic management, and predict the evolution of organizational performance (e.g., profitability) based on the variation of the considered organizational factors (strategic alignment, strategic capabilities).This dissertation compares and integrates two conceptual (resource-based and contingency-based), and two analytical (linear and nonlinear) approaches.
The model developed called MSM (Model of Strategic Management) was validated using the data gathered from 239 senior executives, the results showed that MSM captures the organization nonlinearity (complexity) and offers a good prediction capability of firm performance based on the MSM variables.
Location
Organiser: ESCP - Campus Paris
Paris - France
MapDate
Start date: 28/11/2018
Start time: 9:30 AM
End time: 12:30 PM