Abstract
Over the past ten years, Digital Twin (DT) technology has developed from a specialised academic idea to a
widely utilised operational tool across a wide range of sectors. Since its initial introduction in 2003, the idea has
garnered increasing attention from academics and business due to developments in cloud computing, artificial
intelligence, and the Internet of Things. The purpose of the study is to review the literature in order to present an
organised picture of the state of technology today. Conceptual fundamentals and typologies are analyzed, including the
widely cited distinction between Digital Model, Digital Shadow, and Digital Twin. Moreover, the main supporting
technologies (IoT, cloud computing, artificial intelligence, extended reality), five major application areas
(manufacturing, healthcare, construction, agriculture, services and product-service systems) and the key
implementation challenges, are also examined. The analysis highlights that the success of DT adoption does not depend
exclusively on solving technical difficulties, but equally on the organizational and human capacities of the companies
implementing it. The paper highlights that non-technical implementation challenges are consistently underestimated in
the specialised literature and simultaneously integrates the technical and organisational perspectives, covering five
application areas through a unified analytical framework in contrast to previous syntheses.
widely utilised operational tool across a wide range of sectors. Since its initial introduction in 2003, the idea has
garnered increasing attention from academics and business due to developments in cloud computing, artificial
intelligence, and the Internet of Things. The purpose of the study is to review the literature in order to present an
organised picture of the state of technology today. Conceptual fundamentals and typologies are analyzed, including the
widely cited distinction between Digital Model, Digital Shadow, and Digital Twin. Moreover, the main supporting
technologies (IoT, cloud computing, artificial intelligence, extended reality), five major application areas
(manufacturing, healthcare, construction, agriculture, services and product-service systems) and the key
implementation challenges, are also examined. The analysis highlights that the success of DT adoption does not depend
exclusively on solving technical difficulties, but equally on the organizational and human capacities of the companies
implementing it. The paper highlights that non-technical implementation challenges are consistently underestimated in
the specialised literature and simultaneously integrates the technical and organisational perspectives, covering five
application areas through a unified analytical framework in contrast to previous syntheses.
Cuvinte cheie
Digital Twin
Industry 4.0
Internet of Things
artificial intelligence
industrial applications
implementation challenges
Istoric articol
Publicat
26.06.2026
Informații autori
Citare recomandată
ANCA POPESCU, ADRIANA TULBURE (2026). DIGITAL TWIN TECHNOLOGY: CONCEPTUAL FOUNDATIONS, APPLICATIONS AND IMPLEMENTATION CHALLENGES. Constantin Brâncuși University of Târgu Jiu Economics Series, 1(3), 169–179. https://doi.org/10.65631/jes.3.2026.14
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