Smart mobility: Crowdsourcing solutions for smart transport system in smart cities context

The increasing population, traffic growth and congestion have created a huge pressure on transport authorities to maintain and control traffic conditions in better way in most of the cities worldwide. Such issues have generated a huge demand for smart mobility to facilitate the organized commuting process and transport services. The article focuses on identifying the various components which can make transport system advanced and smart. For this, the crowdsourcing technique has been applied to get the innovative ideas related to transport systems. The content analysis has been performed to classify the received ideas into seven designed categories. The findings suggest the significant improvements that can be incorporated in current transport system especially in Indian cities to develop a sustainable and efficient transport system which can fulfil the population mobility demand. Some worldwide initiatives of smart transport system also have been presented in the study to drive lessons outcomes for developing countries like India.

[1]  J L Western,et al.  INFORMATION TECHNOLOGY IN TRANSPORTATION: KEY ISSUES AND A LOOK FORWARD , 2000 .

[2]  Lai Choo Malone-Lee,et al.  Integrating land use and transport planning to reduce work-related travel: , 2001 .

[3]  Juhwan Oh,et al.  Transit-oriented development in a high-density city: Identifying its association with transit ridership in Seoul, Korea , 2011 .

[4]  A. Bullinger,et al.  Community-Based Innovation Contests: Where Competition Meets Cooperation , 2010 .

[5]  Hyejung Lee,et al.  Developing and validating a citizen-centric typology for smart city services , 2014, Gov. Inf. Q..

[6]  Corrine Cash.  Good governance and strong political will: Are they enough for transformation? , 2016 .

[7]  Lorraine Cairnes,et al.  The Compact City: A Sustainable Urban Form , 1996 .

[8]  Hans Schaffers,et al.  Smart Cities and the Future Internet: Towards Cooperation Frameworks for Open Innovation , 2011, Future Internet Assembly.

[9]  Maria Berrittella,et al.  Transport policy and climate change: How to decide when experts disagree , 2008 .

[10]  Manish Gupta,et al.  Smart neighbourhood: A TISM approach to reduce urban polarization for the sustainable development of smart cities , 2017 .

[11]  M. Ibrahim,et al.  Improvements and integration of a public transport system: the case of Singapore , 2003 .

[12]  Shunsuke Managi,et al.  Efficiency and emissions from urban transport: Application to world city-level public transportation , 2016, Economic Analysis and Policy.

[13]  J. Rak,et al.  Smart Cities , 2018, Computer Communications and Networks.

[14]  M. Ignaccolo,et al.  Influence of Accessibility, Land Use and Transport Policies on the Transport Energy Dependence of a City , 2017 .

[15]  Jörg Firnkorn,et al.  Free-floating electric carsharing-fleets in smart cities: The dawning of a post-private car era in urban environments? , 2015 .

[16]  Ang Liu,et al.  A crowdsourcing design framework for concept generation , 2016 .

[17]  R. Cervero.  Land-Use Mixing and Suburban Mobility , 1988 .

[18]  Klaus Krippendorff,et al.  Content Analysis: An Introduction to Its Methodology , 1980 .

[19]  Ashim Kumar Debnath,et al.  Sustainable, safe, smart—three key elements of Singapore’s evolving transport policies , 2013 .

[20]  F. Kohlbacher.  The Use of Qualitative Content Analysis in Case Study Research , 2006 .

[21]  Sun Sheng Han,et al.  Managing motorization in sustainable transport planning: the Singapore experience , 2010 .

[22]  D. Bonilla,et al.  Building sustainable transport futures for the Mexico City Metropolitan Area , 2016 .

[23]  P. Van den Bossche,et al.  CITELEC — electric vehicles on the move in Europe's cities , 1992 .

[24]  Nikolaus Franke,et al.  Integrating Problem Solvers from Analogous Markets in New Product Ideation , 2014, Manag. Sci..

[25]  Pierre Berthon,et al.  Crowded identity: Managing crowdsourcing initiatives to maximize value for participants through identity creation , 2017 .

[26]  Michael Meyer,et al.  Methods of text and discourse analysis , 2000 .

[27]  John S. Miller,et al.  The “smart growth” debate: best practices for urban transportation planning , 2002 .

[28]  Foo Tuan Seik.  An advanced demand management instrument in urban transport , 2000 .

[29]  L. Møller-Jensen,et al.  Access to the city: Mobility patterns, transport and accessibility in peripheral settlements of Dar es Salaam , 2017 .

[30]  R. Weber.  Basic Content Analysis , 1986 .

[31]  Giuseppe Piro,et al.  Information centric services in Smart Cities , 2014, J. Syst. Softw..

[32]  Danny Samson,et al.  Using real time information for transport effectiveness in cities , 2011 .

[33]  Geetam Tiwari,et al.  Impact of public transport and non-motorized transport infrastructure on travel mode shares, energy, emissions and safety: Case of Indian cities , 2016 .

[34]  Michel Bierlaire,et al.  Network design of a transport system based on accelerating moving walkways , 2017 .

[35]  Karim R. Lakhani,et al.  Marginality and Problem-Solving Effectiveness in Broadcast Search , 2010, Organ. Sci..

[36]  Hyungon Sung,et al.  Policy Implications of Compact-City Measures for Sustainable Development: A Case Study in Korea , 2010 .

[37]  Fábio Duarte,et al.  Policy tools for sustainable transport in three cities of the Americas: Seattle, Montreal and Curitiba , 2016 .