Most recent issue published online in the International Journal of Technology Intelligence and Planning.
International Journal of Technology Intelligence and Planning
http://www.inderscience.com/browse/index.php?journalID=105&year=2022&vol=13&issue=2
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International Journal of Technology Intelligence and Planning
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International Journal of Technology Intelligence and Planning
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http://www.inderscience.com/browse/index.php?journalID=105&year=2022&vol=13&issue=2
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All for one, or one out of many? An analysis of cryptocurrency returns and technological differentiation
http://www.inderscience.com/link.php?id=126819
Analysing the 60 largest cryptocurrencies, we evaluate whether cryptocurrency movement can be differentiated by their underlying technological differences. We found that while substantial correlation in movement exists between the largest cryptocurrencies, investors are only beginning to understand and evaluate cryptocurrencies based on their technological characteristics. Studying both daily and monthly cryptocurrency returns, cryptocurrencies utilising <i>decentralised application</i> (DApp) reported higher returns, while currencies classified as coins reported lower returns. While not highly correlated to the US stock market performance, cryptocurrency returns are positively correlated with both technology and materials sectors within the US stock market. The results present a case for valuing cryptocurrencies as both a financial asset and a technological advancement.
All for one, or one out of many? An analysis of cryptocurrency returns and technological differentiation
Sarina Baldoni; Reilly S. White
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 103 - 126
Analysing the 60 largest cryptocurrencies, we evaluate whether cryptocurrency movement can be differentiated by their underlying technological differences. We found that while substantial correlation in movement exists between the largest cryptocurrencies, investors are only beginning to understand and evaluate cryptocurrencies based on their technological characteristics. Studying both daily and monthly cryptocurrency returns, cryptocurrencies utilising <i>decentralised application</i> (DApp) reported higher returns, while currencies classified as coins reported lower returns. While not highly correlated to the US stock market performance, cryptocurrency returns are positively correlated with both technology and materials sectors within the US stock market. The results present a case for valuing cryptocurrencies as both a financial asset and a technological advancement.]]>
10.1504/IJTIP.2022.126819
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 103 - 126
Sarina Baldoni
Reilly S. White
Anderson School of Management, University of New Mexico, Albuquerque, New Mexico 87131, Mexico ' Anderson School of Management, University of New Mexico, Albuquerque, New Mexico 87131, Mexico
cryptocurrency
investments
blockchain
consumer value proposition
new product development
smart contracts
2022-11-08T23:20:50-05:00
Copyright © 2022 Inderscience Enterprises Ltd.
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126
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An introduction to the new challenges and promise of I-4.0 based commercialisation in the COVID-19-induced 'low-touch economy' ecosystem
http://www.inderscience.com/link.php?id=126823
The Fourth Industrial Revolution – Industry 4.0 (I-4.0) provides innovators new commercial promise and challenges. For the first time, service-based disruptive technologies are included as harbingers of the Schumpeterian economic industrial waves. The strategic, tactical, and operational importance of disruptive technologies and their resultant discontinuous innovations that underpin a new industrial wave are game-changing for state, regional, national, and global economies. However, there are always barriers, both technical and social, to new technology product adoption. The COVID-19-induced industry forcing function has created a 'low-touch economy', changing business action and creating a new normal. We focus on the challenges to the realisation of I-4.0. We use the internet of things (IoT) as our exemplar. IoT is the first service-based technology to support an industrial revolution. It challenges the traditional view of how firms compete. It is creating wealth and jobs and is an agent of societal transformation.
An introduction to the new challenges and promise of I-4.0 based commercialisation in the COVID-19-induced 'low-touch economy' ecosystem
Robert F. Gary; Steven T. Walsh
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 127 - 142
The Fourth Industrial Revolution – Industry 4.0 (I-4.0) provides innovators new commercial promise and challenges. For the first time, service-based disruptive technologies are included as harbingers of the Schumpeterian economic industrial waves. The strategic, tactical, and operational importance of disruptive technologies and their resultant discontinuous innovations that underpin a new industrial wave are game-changing for state, regional, national, and global economies. However, there are always barriers, both technical and social, to new technology product adoption. The COVID-19-induced industry forcing function has created a 'low-touch economy', changing business action and creating a new normal. We focus on the challenges to the realisation of I-4.0. We use the internet of things (IoT) as our exemplar. IoT is the first service-based technology to support an industrial revolution. It challenges the traditional view of how firms compete. It is creating wealth and jobs and is an agent of societal transformation.]]>
10.1504/IJTIP.2022.126823
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 127 - 142
Robert F. Gary
Steven T. Walsh
Anderson School of Management, University of New Mexico, Albuquerque, NM 87131-0001, USA Fax: +(505)-277-7108 ' Anderson School of Management, University of New Mexico, Albuquerque, NM 87131-0001, USA Fax: +(505)-277-7108
technology entrepreneurship
low-touch economy
IoT
disruptive technology
learning curves
2022-11-08T23:20:50-05:00
Copyright © 2022 Inderscience Enterprises Ltd.
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127
142
2022-11-08T23:20:50-05:00
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Artificial intelligence in project management: systematic literature review
http://www.inderscience.com/link.php?id=126841
Project management is a common field in many industries, and it is not immune to the innovations that artificial intelligence is bringing to the world. Even so, the application of artificial intelligence is not that widespread in companies and especially not in all of project management areas. The reasons are not clear but seem to be related to the uncertainty of the application of artificial intelligence in project management. The purpose of this paper was to acknowledge the potentialities and limitations of artificial intelligence in the specific area of project management by doing a systematic literature review with which it was possible to analyse and correlate the selected articles and reach some patterns and tendencies. In the end, it was clear that there is an increased interest in the scientific community in this field, although with some areas to explore.
Artificial intelligence in project management: systematic literature review
Sofia Bento; Leandro Pereira; Rui Gonçalves; Ãlvaro Dias; Renato Lopes da Costa
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 143 - 163
Project management is a common field in many industries, and it is not immune to the innovations that artificial intelligence is bringing to the world. Even so, the application of artificial intelligence is not that widespread in companies and especially not in all of project management areas. The reasons are not clear but seem to be related to the uncertainty of the application of artificial intelligence in project management. The purpose of this paper was to acknowledge the potentialities and limitations of artificial intelligence in the specific area of project management by doing a systematic literature review with which it was possible to analyse and correlate the selected articles and reach some patterns and tendencies. In the end, it was clear that there is an increased interest in the scientific community in this field, although with some areas to explore.]]>
10.1504/IJTIP.2022.126841
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 143 - 163
Sofia Bento
Leandro Pereira
Rui Gonçalves
Ãlvaro Dias
Renato Lopes da Costa
ISCTE †Instituto Universitário de Lisboa, Lisbon, Portugal ' BRU †Business Research Unit, ISCTE †Instituto Universitário de Lisboa, Lisbon, Portugal ' PIAGET Almada, Almada, Portugal ' Universidade Lusófona de Humanidades e Tecnologias, ISCTE †Instituto Universitário de Lisboa, Lisbon, Portugal ' BRU-IUL †Business Research Unit, ISCTE †Instituto Universitário de Lisboa, Lisbon, Portugal
artificial intelligence
project management
data mining
decision support system
human resources management
2022-11-08T23:20:50-05:00
Copyright © 2022 Inderscience Enterprises Ltd.
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143
163
2022-11-08T23:20:50-05:00
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Innovation research knowledge accumulation in leading actors: a bibliometric analysis approach
http://www.inderscience.com/link.php?id=126845
Studies analysing relevant actors in the innovation research (IR) field have often relied on aggregated productivity and impact measures such as the total number of publications or citations. Owing to the high diversity inherent in innovation, such approaches have provided biased estimates of the role of actors in the development of IR knowledge. This study examines leading innovation actors based on their strength and directional patterns of IR knowledge accumulation. First, I collected IR-relevant publications to approximate the knowledge base supporting this field. Next, I extracted co-authors' affiliations from publications, as a proxy for identifying leading actors, and examined them through dimensions, such as publication and citation numbers and growth rates, cognitive foci, and collaboration schemes. These findings provide innovation researchers and practitioners with a better understanding of the IR field by presenting relevant actors, an actor classification based on their IR knowledge accumulation patterns, and factors influencing collaboration schemes.
Innovation research knowledge accumulation in leading actors: a bibliometric analysis approach
Alfonso Ãvila-Robinson
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 164 - 190
Studies analysing relevant actors in the innovation research (IR) field have often relied on aggregated productivity and impact measures such as the total number of publications or citations. Owing to the high diversity inherent in innovation, such approaches have provided biased estimates of the role of actors in the development of IR knowledge. This study examines leading innovation actors based on their strength and directional patterns of IR knowledge accumulation. First, I collected IR-relevant publications to approximate the knowledge base supporting this field. Next, I extracted co-authors' affiliations from publications, as a proxy for identifying leading actors, and examined them through dimensions, such as publication and citation numbers and growth rates, cognitive foci, and collaboration schemes. These findings provide innovation researchers and practitioners with a better understanding of the IR field by presenting relevant actors, an actor classification based on their IR knowledge accumulation patterns, and factors influencing collaboration schemes.]]>
10.1504/IJTIP.2022.126845
International Journal of Technology Intelligence and Planning, Vol. 13, No. 2 (2022) pp. 164 - 190
Sofia Bento
Leandro Pereira
Rui Gonçalves
Ãlvaro Dias
Renato Lopes da Costa
Tecnologico de Monterrey, EGADE Business School, Ãlvaro Obregón, Mexico City, Mexico
innovation research
actors/stakeholders
bibliometrics
knowledge accumulation
collaboration
research organisations
knowledge base
research productivity
research impact
cross-country analysis
2022-11-08T23:20:50-05:00
Copyright © 2022 Inderscience Enterprises Ltd.
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190
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