TY - CHAP
T1 - Key Technology Adoption Indicators for Smart Universities
AU - Rico-Bautista, Dewar
AU - Guerrero, César D.
AU - Collazos, César A.
AU - Maestre-Gongora, Gina
AU - Sánchez-Velásquez, María Camila
AU - Medina-Cárdenas, Yurley
AU - Parra-Sánchez, Diana Teresa
AU - Barreto, Antón Garcia
AU - Swaminathan, Jose
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - Technology management in universities impacts the quality of their administrative and academic processes. Smart technologies, such as big data, artificial intelligence, the Internet of Things, and cloud computing, continue to be disruptive and highly relevant. The factors for adopting smart technology and the key indicators will contribute to the knowledge of the transformation processes of current universities in Smart Universities. An evolutionary approach for a traditional university to progress by levels toward a smart university can be seen in a maturity model that integrates such factors and indicators. Although maturity models are numerous and widely applicable, there is little documentation on how to develop them. So far, there is a lack of useful tools to support the practical adoption of the developed models in universities. This article presents 52 key indicators associated with the proposed smart technology adoption factors that are the basis for the maturity model.
AB - Technology management in universities impacts the quality of their administrative and academic processes. Smart technologies, such as big data, artificial intelligence, the Internet of Things, and cloud computing, continue to be disruptive and highly relevant. The factors for adopting smart technology and the key indicators will contribute to the knowledge of the transformation processes of current universities in Smart Universities. An evolutionary approach for a traditional university to progress by levels toward a smart university can be seen in a maturity model that integrates such factors and indicators. Although maturity models are numerous and widely applicable, there is little documentation on how to develop them. So far, there is a lack of useful tools to support the practical adoption of the developed models in universities. This article presents 52 key indicators associated with the proposed smart technology adoption factors that are the basis for the maturity model.
KW - ICT adoption
KW - ICT indicators
KW - Maturity model
KW - Smart technologies
KW - Smart university
KW - Technology adoption
UR - http://www.scopus.com/inward/record.url?scp=85123280653&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-6309-3_61
DO - 10.1007/978-981-16-6309-3_61
M3 - Capítulos en libro
AN - SCOPUS:85123280653
SN - 9789811663086
T3 - Lecture Notes in Networks and Systems
SP - 651
EP - 663
BT - Lecture Notes in Networks and Systems
A2 - Nagar, Atulya K.
A2 - Jat, Dharm Singh
A2 - Marín-Raventós, Gabriela
A2 - Mishra, Durgesh Kumar
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 29 July 2021 through 30 July 2021
ER -