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An Ecological Business Model for Intelligent Operation and Maintenance of Urban Infrastructure

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 357))

Abstract

With the increasing number of urban infrastructure construction projects under the PPP (Public-Private-Partnership) investment, the traditional operation and maintenance model presents a number of problems, such as low efficiency and high cost of operation & maintenance, fragmentation of stakeholders, difficulty in estimating the value of facility assets and utilizing the isolated multi-source data. In view of this, this research proposes a new model for Intelligent Operation and Maintenance of Urban Infrastructure (IOMUI), which is based on the exploration of the claims from various stakeholders under the PPP model, and combined with emerging ICT technologies. Through the analysis of the current facility industry chain, our research proposes a shared ecosystem, which extends the vertical industrial chain, and ultimately forms the model of IOMUI. The proposed ecological business model provides a reference for the reform and upgrading of the OMUI industry, and also contributes to the sustainable development of the industry.

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Acknowledgment

This work is supported in part by the National Natural Science Foundation of China under Grant 71701121, and the Chinese Ministry of Education of Humanities and Social Science Project under Grant 17YJC630021.

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Correspondence to Juan Du .

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Du, J., Wang, X., Sugumaran, V. (2019). An Ecological Business Model for Intelligent Operation and Maintenance of Urban Infrastructure. In: Xu, J., Zhu, B., Liu, X., Shaw, M., Zhang, H., Fan, M. (eds) The Ecosystem of e-Business: Technologies, Stakeholders, and Connections. WEB 2018. Lecture Notes in Business Information Processing, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-030-22784-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-22784-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22783-8

  • Online ISBN: 978-3-030-22784-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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