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Title:

Assessment of Public-Private Partnership in Smart Ningbo Tong App Based on Effectiveness of Smartphone Traffic Information

Accession Number:

01626175

Record Type:

Component

Abstract:

Alongside the advent of smartphones, the development of traffic information applications (TIAs) has revolutionized the way drivers obtain the latest traffic information and guidance. TIAs show added advantage and have positive effects on changing travel behavior. The shrinking public funding has made the public–private partnership (PPP) an attractive instrument for promoting TIAs. The use of PPP to fund public projects in developing countries, however, is in its infancy, and the related issues do not receive adequate attention in the literature. In this study, PPP opportunities in TIAs were assessed in the case of a city in a developing country, Ningbo, China. Factors contributing to TIAs’ effectiveness were studied by analyzing commuters’ behavioral changes in response to current traffic information provided by Smart Ningbo Tong Apps. Analysis was conducted with multinomial logit and nested logit models. From this analysis, commuter characteristics, trip purpose, and content of App traffic information were identified as factors contributing to drivers’ willingness to divert. These findings directed the research to some potential markets and strategies for investment in TIAs. The literature was reviewed to identify some challenges and opportunities of PPP in past experience and special regional constraints. On the basis of the modeling results and literature review, business models for PPP in TIAs were outlined. Key findings are that (a) data integration and customization are essential; (b) with respect to purchasing behavior, the market has to be stratified into commuter and corporate markets; and (c) the financial subsidy is necessary.

Supplemental Notes:

This paper was sponsored by TRB committee AND20 Standing Committee on User Information Systems.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-00169

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Ye, Xiaofei
Chen, Jun
Yan, Xingchen
Wang, Tao

ORCID 0000-0001-9619-8717

Pagination:

20p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Geographic Terms:

Subject Areas:

Administration and Management; Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-00169

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 9:58AM