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A Practice Based Exploration on Electric Mobility as a Service in Smart Cities

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Information Systems (EMCIS 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 381))

Abstract

With increase in urban residents and CO2 emission from vehicles, there is need to deploy smart electric mobility services termed as Electric Mobility as a Service (eMaaS) facilitated by innovations in Information Communication Technology (ICT) to mitigate environmental issues, improve social inclusion, and enhance economic growth. However, citizens and stakeholders are faced with issues related to acquiring appropriate information needed to make decisions which impacts their wellbeing and natural environment due to heterogenous data being generated from various sources. Therefore, this study adopts Enterprise Architecture (EA) and integrates Application Programming Interfaces (APIs) to improve interoperability for acquisition, processing, retaining, and dissemination of mobility relevant data. Secondary data from the literature and ArchiMate modeling tool was utilized to model eMaaS case to verify the feasibility of EA to improve city transport services. Findings from ArchiMate reveal that EA provides a theoretical and practical approach that supports mobility services in smart cities.

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Acknowledgements

This publication is a part of the +CityxChange smart city project under the Smart Cities and Communities topic that is funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 824260. The authors gratefully acknowledge the support of the project partners; Trondheim Municipality, Powel AS, TrønderEnergi AS, FourC AS, IOTA, and the participants of work packages 1 and 2 as well as the whole project team.

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Correspondence to Bokolo Anthony Jr. .

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Anthony, B., Petersen, S.A. (2020). A Practice Based Exploration on Electric Mobility as a Service in Smart Cities. In: Themistocleous, M., Papadaki, M. (eds) Information Systems. EMCIS 2019. Lecture Notes in Business Information Processing, vol 381. Springer, Cham. https://doi.org/10.1007/978-3-030-44322-1_1

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  • DOI: https://doi.org/10.1007/978-3-030-44322-1_1

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