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

delete2022-05-01
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OA
AI
G
Germán-Lenin Dugarte-Peña *
M
Marı́a-Isabel Sánchez-Segura
F
Fuensanta Medina‐Domínguez
A
Antonio de Amescua Seco
C
Cleotilde González
DOI:10.1080/14778238.2022.2064348delete
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Abstract

Abstract

En 中文
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.
Keywords:
Digital business management
decision-making
knowledge assets management
decisions from experience
technology in the knowledge economy
digital business evolution

Journal

Knowledge Management Research and Practice cover
Knowledge Management Research and Practice
IF:
3.8
Papers:
909
Citations:
2.0K

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Carnegie Mellon University
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Universidad Carlos III de Madrid
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Universidad Francisco de Vitoria cover
Universidad Francisco de Vitoria
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Citations: 1.4K
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