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An instance-based-learning simulation model to predict knowledge assets evolution involved in potential digital transformation projects

Author

Listed:
  • German-Lenin Dugarte-Peña
  • María-Isabel Sánchez-Segura
  • Fuensanta Medina-Domínguez
  • Antonio de Amescua
  • Cleotilde González

Abstract

Software engineering professionals must consider the appropriate technological solutions to meet their client’s needs and the organisational impact. The decision to implement a solution is not explicitly based on how it empowers the knowledge assets. Organisational knowledge assets are the foundation of the knowledge economy and a key element in evaluating the health of an organisation. This paper provides software engineers with a simulation model which illustrates the decision-making process for the implementation of technological solutions based on an evaluation of their client’s knowledge assets and how such assets impact and are impacted by the deployment of a solution. We use an agent-based approach and implement an instance-based learning model (a cognitive approach) to represent scenarios for experience-based decisions. 11 case studies were used to train the prediction engine and validate the usefulness of the model in generating scenarios and nurturing decision-making and user experiences.

Suggested Citation

  • German-Lenin Dugarte-Peña & María-Isabel Sánchez-Segura & Fuensanta Medina-Domínguez & Antonio de Amescua & Cleotilde González, 2022. "An instance-based-learning simulation model to predict knowledge assets evolution involved in potential digital transformation projects," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 20(6), pages 843-864, November.
  • Handle: RePEc:taf:tkmrxx:v:20:y:2022:i:6:p:843-864
    DOI: 10.1080/14778238.2022.2064348
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