Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

An Assessment Model for Sustainability City Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach

Version 1 : Received: 4 September 2023 / Approved: 5 September 2023 / Online: 6 September 2023 (09:26:08 CEST)

A peer-reviewed article of this Preprint also exists.

Ependi, U.; Rochim, A.F.; Wibowo, A. An Assessment Model for Sustainable Cities Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach. Smart Cities 2023, 6, 3032-3059. Ependi, U.; Rochim, A.F.; Wibowo, A. An Assessment Model for Sustainable Cities Using Crowdsourced Data Based on General System Theory: A Design Science Methodology Approach. Smart Cities 2023, 6, 3032-3059.

Abstract

Historically, the lack of comprehensive and real-time data is the main challenge in city sustainability assessments. However, with the increase in the availability of crowdsourced data over the last decade, a rich and real-time data source provides detailed images of urban systems. This has opened up new opportunities for practitioners, including geographers, social researchers, and data scientists, to gather and utilize social media data as a core source for studying cities and assessing their sustainability. This paper proposes an assessment model for the sustainability of cities based on crowdsourced data and the principles of General System Theory. The model aims to utilize crowdsourced data for the analysis and decision-making processes to enhance the sustainability and resilience of smart future cities.

Keywords

assessment model; sustainable city; crowdsourced data; design science; smart cities; general system theory

Subject

Social Sciences, Urban Studies and Planning

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