Submitted by llaverdure on

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

Samir Medrouk, doctorant du programme Ph.D. ESCPSamir MEDROUK, PhD candidate in the PhD program ESCP will publicly defend his PhD thesis in Management Sciences.
Thesis Title:
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.

Type (Don't capitalize)
PhD Thesis Defense
Join the event link
mailto:samir.medrouk@edu.escpeurope.eu?subject=Soutenance de Thèse Samir MEDROUK&cc=crocque@escpeurope.eu
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ESCP Europe Campus Paris

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ESCP - Campus Paris
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Paris
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Banner Phd Thesis Defense Samir Medrouk
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).
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Page title
Strategic Management and Machine Learning
In search of companies’ financial performance optimization in the digital age. PhD Thesis Defense of Samir Medrouk.
City
Paris
Country
France
Language
English