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The role of information sharing-centered IT infrastructure factor by using advanced Metcalfe's law: Case study of Incheon International Airport

Authors
Ha, HyodongNa, HyunjongLee, Ook
Issue Date
Oct-2020
Publisher
International Research Publication House
Keywords
EAI; Information Integration System; Information Sharing; IT Interaction Model; Metcalfe's Law
Citation
International Journal of Engineering Research and Technology, v.13, no.10, pp 2752 - 2760
Pages
9
Indexed
SCOPUS
Journal Title
International Journal of Engineering Research and Technology
Volume
13
Number
10
Start Page
2752
End Page
2760
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/32735
DOI
10.37624/IJERT/13.10.2020.2752-2760
ISSN
0974-3154
Abstract
Many airports are continuously implementing Information Systems (IS) and Information Technology (IT) services in order to achieve their organizational objectives. Such IS, known as nodes in distributional environment, are systematically interconnected to share information and thereby increase task performance efficiency. As importance of information sharing arise, strategic management of nodes that surround Information Integration System (IIS) has become essential. This paper suggests application plan of Enterprise Application Integration (EAI) installed IIS based on case study of which previously has been implemented in Incheon International Airport, and further estimates effects on the organizational output. We have calculated and analyzed advanced Metcalfe's law applied EAI network power of interconnected nodes of IIS between year 2014 and 2018. Moreover, we performed multiple regression analysis in order to derive statistical impact of EAI network power on the organizational output as an IT infrastructure. The result indicates exponential increase in EAI network power for increased number of nodes. And the number of flights, which is organizational output of the airport, is affected by 3 factors in decreasing order - firm strategy, IT infrastructure, and firm culture. Therefore, we conclude that quantification of internal system via managing number of nodes can be used as evidence for Key Performance Indicator (KPI) to aid organizational decision making.
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