Crowdsourcing information for knowledge-based design of routes for unscheduled public transport trips

Abstract

Purpose – The purpose of this paper is to devise a crowdsourcing methodology for acquiring and exploiting knowledge to profile unscheduled transport networks for design of efficient routes for public transport trips. Design/methodology/approach – This paper analyzes daily travel itineraries within Mexico City provided by 610 public transport users. In addition, a statistical analysis of quality-of-service parameters of the public transport systems of Mexico City was also conducted. From the statistical analysis, a knowledge base was consolidated to characterize the unscheduled public transport network of Mexico City. Then, by using a heuristic search algorithm for finding routes, public transport users are provided with efficient routes for their trips. Findings – The findings of the paper are as follows. A crowdsourcing methodology can be used to characterize complex and unscheduled transport networks. In addition, the knowledge of the crowds can be used to devise efficient routes for trips (using public transport) within a city. Moreover, the design of routes for trips can be automated by SmartPaths, a mobile application for public transport navigation. Research limitations/implications – The data collected from the public transport users of Mexico City may vary through the year. Originality/value – The significance and novelty is that the present work is the earliest effort in making use of a crowdsourcing approach for profiling unscheduled public transport networks to design efficient routes for public transport trips.

Pro-socially motivated interaction for knowledge integration in crowd-based open innovation

“…Open innovation is an expected business strategy for firms today (Afuah and Tucci, 2012; Chesbrough, 2003), used for everything from the creation of user-adapted products (von Hippel, 2005) to open strategy formulation (Whittington, 2015), from solving heuristic-based problems (Boudreau et al , 2011) to solving ill-structured problems (Cairo et al , 2015; Majchrzak and Malhotra, 2020); Malhotra and Majchrzak, 2019; Natalicchio et al , 2017). Advanced communication and collaboration technologies are used to make this possible.…”

A gestão do conhecimento em serviços transportes, um estudo bibliométrico

“…O presente estudo bibliométrico procurou esquadrinhar no contexto científico a produção relacionada à GC no contexto dos Serviços de Transportes sob a luz de diversos aspectos. Na evolução do tema, nota-se um pico produtivo de estudos em 2015 com três artigos, sendo dois com ênfase na área pública e que abordam melhorias nos serviços de transportes públicos (Cairo et al 2015 O estudo também contribui com a emersão de termos pouco conhecidos na área de ciências sociais aplicadas como é o caso dos vocábulos crowdsourcing (Cairo et al, 2015), aldeias de fretes (Wu & Haasis, 2013), taxonomia (Gkoumas & Tsakalidis, 2019) e e-gov Research, Society and Development, v. 9, n. 10, e5449108344, 2020(CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i10.8344 (Fachini et al, 2016.…”

“…Cairo et al (2015);Sindakis et. al (2015), Kassens-Noor(2013)e Fachini et al (2016) os quais lançaram uma ênfase pública aos estudos enquanto que Pulkkinen et al(2019), Wu & Haasis (2013), Evangelista & Durst (2015) e Škerlič et al (2016) sugerem um olhar privado á relação.…”

“…Cairo et al (2015) sugerem pesquisas focadas no design de um flocksourcing para levantar o perfil das rotas de ônibus do sistema público na Cidade do México além da criação de um mecanismo automático para utilização dos usuários.Sindakis et al (2015) abordam numa primeira perspectiva, a necessidade de pesquisas com o cunho de examinar de forma empírica aspectos voltados ao conhecimento de cunho intangível e capital intelectual para a inovação nos serviços de transportes. Como segunda perspectiva, sugerem ainda pesquisas acerca dos fluxos de conhecimento atreladas a demanda e oferta do mercado e as contribuições da GC nessa relação.…”

Mapping with Stakeholders: An Overview of Public Participatory GIS and VGI in Transport Decision-Making

“…More than the half of the studies (55%) deal with the identification of project types and the present situation analysis, due to the spatial GIS component providing an essential aid in definition of physical constraints. Research focused on: the building of comprehensive urban networks through VGI data [32,51]; road and traffic condition analysis through crowdsourcing [70][71][72][73]; analysis of vehicle behavior [74] and investigation of travel patterns [52,[75][76][77], with an extensive use of SoftGIS, an internet-based approach which relies on collecting, analyzing and delivering soft knowledge produced by the residents and other local actors in a certain area through interactive maps [29,41,[78][79][80][81]; urban connectivity assessment [82] and general analysis of urban public transport and sustainable mobility aspects through smartphones [37,[83][84][85][86][87][88]. Crowdsourcing techniques have been extensively used in studies related to non-motorized mobility, such as cyclist spatial patterns identification [39,53,54,56,58,71], their socio-economic analysis [89] and environmental related problems [55,90] or the identification of peculiar elements of the pedestrian network to improve the walking experience of vulnerable people [29,55,57].…”