Big Data and Urban Transportation in India: A Bengaluru Bus Corporation Case Study

S, Rakesh V; Heeks, Richard; Chattapadhyay, Sumandro; Foster, Christopher

doi:10.2139/ssrn.3427274

Cited by 3 publications

(3 citation statements)

References 3 publications

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“… A study of big data in the Bengaluru Metropolitan Transport Corporation (BMTC), which runs the city's 6,000-plus buses. The study was led by Vanya Rakesh and is available as Rakesh et al (2017). The Corporation has financed development of a new big data system, called the Intelligent Transport System (ITS).…”

Section: B Field Study Evidencementioning

confidence: 99%

A Structural Model and Manifesto for Data Justice for International Development

Heeks

2017

SSRN Journal

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Section: B Field Study Evidencementioning

confidence: 99%

A Structural Model and Manifesto for Data Justice for International Development

Heeks

2017

SSRN Journal

Self Cite

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“…In India, the Smart Cities Mission was launched in 2015 to support sustainable development through the application of information and communication technologies (Dwevedi, Krishna, & Kumar, 2018). The Smart Cities Mission is focused on cities with a population between 1 and 4 million (“second tier” cities) and particular opportunities are thought to exist in the transport sector and from new sources of Big Data, including Google Maps (Jindal, Kumar, & Singh, 2020; Rakesh, Heeks, Chattapadhyay, & Foster, 2018; Rizwan, Suresh, & Rajasekhara Babu, 2016). Hubballi‐Dharwad, the case study analysis focuses on among the 100 cities in the “Smart Cities Mission”, and “Smart Mobility” is recognised as a key area for intervention (Hubballi‐Dharwad, 2013).…”

Section: Introductionmentioning

confidence: 99%

Fair weather forecasting? The shortcomings of big data for sustainable development, a case study from Hubballi‐Dharwad, India

Sudmant

Viguié

Lepetit

et al. 2021

Sustainable Development

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Sustainable urban mobility is an essential component of sustainable development but requires careful planning in rapidly growing urban areas. This paper investigates the value and limitations of Big Data for evaluating transport policies, plans, and projects in Hubballi-Dharwad, India. Results show how Big Data can enable the outcomes of transport interventions to be evaluated more readily than conventional transport analysis.However, the analysis also found that this data may be less able to detect the impacts of travel behaviours in informal settlements, and the impact of extreme weather events. These potential shortcomings, as well as a lack of transparency around the methodology and data sources used by sources of Big Data, could generate unintended consequences and biases in transport planning. Reflecting on these challenges, and the wider implications for urban governance, we conclude that there is an urgent need for Big Data and other technical advances in urban modelling to be seen as compliments to, rather than substitutes for, wider methods of knowledge generation in urban areas.

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“…Findings integrate material from two working papers that describe each case study in greater detail:Sengupta et al (2017) andRakesh et al (2018).3 The requirement for anonymity in the case of Stelcorp means it is not possible to cite some of these documents since to do so would enable case identification.…”

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confidence: 99%

Datafication, value and power in developing countries: Big data in two Indian public service organizations

Heeks

S²,

Sengupta

et al. 2020

Development Policy Review

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Motivation: Datafication-the growing presence, use and impact of data in social processes-is spreading to all sectors in developing countries. But, to date, there are few analyses of real-world experiences of datafication in developing country organizations. Purpose: We address this knowledge gap by analysing evidence of big data in practice in relation to three key issues: implementation, value and power. Approach and methods: Using interview, observation and documentary sources, we analyse the implementation and impact of big data systems in Indian electricity and transport public sector organizations. Findings: Big data systems have been much slower to implement than anticipated, and the article exposes the nature and scale of the implementation challenge facing such systems. These are already delivering value for some managers within public service organizations but are, as yet, more operational than strategic and incremental not transformative. Big data systems are facilitating a shift in power from the public sector to the private sector, and from labour and middle management to panopticon-type control by central managers. Big data intersects with politics especially around the imaginaries of wider stakeholders, changing their view of the financial and political issues that technology can address. Policy implications: Policy-makers and practitioners can better understand and plan for big data in development using three frameworks presented in the article: information value chain, decision pyramid, and big data-power model. These expose key issues of implementation, organizational value and power that must be incorporated into big data policy and projects. Benefits of datafication have been largely restricted to senior managers, private contractors and some politicians. To spread these to other stakeholders, including workers and citizens, action must be taken to address both practical and political issues arising in the datafication of development.

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Big Data and Urban Transportation in India: A Bengaluru Bus Corporation Case Study

Cited by 3 publications

References 3 publications

A Structural Model and Manifesto for Data Justice for International Development

A Structural Model and Manifesto for Data Justice for International Development

Fair weather forecasting? The shortcomings of big data for sustainable development, a case study from Hubballi‐Dharwad, India

Datafication, value and power in developing countries: Big data in two Indian public service organizations

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