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POPOVIC Ales

  • briefcase Système d’Information, Supply Chain Management & aide à la Décision
  • quality PhD, Sciences Economiques, Sociales et de Gestion, Systèmes d'information
Domaines de spécialisation
  • Business value of IT
  • Digitalization
  • Behavioral and organizational issues in IS
  • IT in inter-organizational relationships

Ales Popovic est Professeur de Systèmes d'Information à NEOMA Business School.

Ses domaines de Recherche pertinents et utiles à la fois aux universitaires et aux praticiens sont axés sur l'étude des SI, notamment  la valeur qu'elles apportent aux personnes, aux organisations et aux marchés. Ales Popovic étudie la valeur du SI dans les organisations, la réussite du SI, les problématiques comportementales et organisationnelles en SI et l'informatique dans les relations inter-organisationnelles.

Ales a publié ses recherches dans diverses revues académiques, telles que Journal of the Association for Information Systems, Journal of Strategic Information Systems, Decision Support Systems, Expert Systems with Applications, Information Systems Frontiers, Government Information Quarterly et Journal of Business Research. 

M. Popovic est membre du comité de rédaction de l'International Journal of Information Management, Industrial Management & Data Systems, and Information Systems Management.

 

Dernières publications

  • An artificial intelligence system for predicting customer default in e-commerce
  • The impact of big data analytics on firms’ high value business performance
  • Unlocking the drivers of big data analytics value in firms
  • The role of compatibility in predicting business intelligence and analytics use intentions
  • Understanding SaaS adoption: The moderating impact of the environment context
  • Justifying business intelligence systems adoption in SMEs
  • Understanding the determinants of business intelligence system adoption stages
  • Business Intelligence Capability: The Effect of Top Management and the Mediating Roles of User Participation and Analytical Decision Making Orientation
  • Analysis of the proficiency of fully connected neural networks in the process of classifying digital images. Benchmark of different classification algorithms on high-level image features from convolutional layers
  • An expert system for extracting knowledge from customers’ reviews: The case of Amazon.com, Inc.
  • Business Intelligence Effectiveness and Corporate Performance Management: An Empirical Analysis
  • Online consumer reviews and sales: Examining the chicken-egg relationships
  • If we implement it, will they come? User resistance in post-acceptance usage behaviour within a business intelligence systems context