A system dynamic approach for the smart mobility of people: Implications in the age of big data

Pasquale Del Vecchio, Giustina Secundo, Ylenia Maruccia and Giuseppina Passiante

Technological Forecasting and Social Change, 2019, vol. 149, issue C

Abstract: Mobility of people can be configured as an information intensive process resulting from a complex set of factors. Its effective implementation requires the adoption of methods able to leverage on a set of complex and dynamic variables, and mainly on a huge amount of data available. Moving from this assumption, this paper aims to demonstrate that system dynamics could present a useful approach for optimising decision making for people's mobility. The conceptual model is built by using the principles of system dynamics methodology and is based on causal feedback relationships among the various factors related to the different needs of people's mobility. The causal feedback loops and interrelationship among various parameters illustrate the dynamicity and the influence of parameters on one another. The simulation analysis was conducted to dynamically evaluate six scenarios corresponding to the different solutions available for particular segments of demand. Findings highlight that the modelling approaches could guide the city planners to evolve responsive policy interventions for further developing smart mobility of people. Implications for policy makers regard the developing sustainable mobility scenarios based on the analysis of big data from the adoption of digital platforms grounded on the simulation model.

Keywords: Big data; Smart mobility; Data science; System dynamics; Simulation Model; Decision Making (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162519306419
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:149:y:2019:i:c:s0040162519306419

DOI: 10.1016/j.techfore.2019.119771

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().