Using Crowd-Sourced Data to Study Public Services: Lessons from Urban India

Abstract

Forthcoming, Studies in Comparative International DevelopmentAs cities throughout the developing world grow, they often expand more quickly than the infrastructure and service delivery networks that provide residents with basic necessities such as water and public safety. Why do some cities deliver more effective infrastructure and services in the face of rapid growth than others? Why do some households and communities secure better services than others? Answering these questions requires studying the large, politicized bureaucracies charged with providing urban services, and especially the relationships between frontline workers, agency managers, and citizens in informal settlements. Researchers investigating public service delivery in cities of the Global South, however, have faced acute data scarcity when addressing these themes. The recent emergence of crowd-sourced data offers researchers new means of addressing such questions. In this paper, we draw on our own research on the politics of urban water delivery in India to highlight new types of analysis that are possible using crowd-sourced data, and propose solutions to common pitfalls associated with analyzing it. These insights should be of use for researchers working on a broad range of topics in comparative politics where crowd-sourced data could provide leverage, such as protest politics, conflict processes, public opinion, and law and order.

A bibliometric and scientometric review of research on crowdsourcing in smart cities

“…Crowdsourcing originated in the USA, and researchers in the USA have applied it in many areas, including software development [31], gaming [32], data and information collection [33], and other areas; as a result, there are more related research studies from the USA on the use of crowdsourcing in smart‐city applications. Research topics in the USA focus on the technical aspects in terms of crowdsourcing technology, for example, task effectiveness [34] and MCS [35].…”

Determinants of Smart Digital Infrastructure Diffusion for Urban Public Services

“…Vijai and Sivakumar (2016) felt usage of smart technologies like IoT and Analytics leads to successful implementation of various SmartCity applications. Post et al (2018), Rao et al (2020) studied social Media influence on citizen engagement in crisis and disaster management (e.g., Covid19), public priorities, law and order situation, whereas Verma et al (2017) found limited Social Media usage in governance in India due to lack of indigenous platform and lack of inclusivity. Study of several Indian urban public services like municipalities, police and traffic, utilities like water and electricity supplies, single-window citizen service (eDistrict), social media shows newer establishments offered participative and transactional citizen services, but older establishments are stuck in static information dissipation portal.…”

Why Political Scientists Should Study Smaller Cities

“…Examples include public complaint systems about water and air quality (Sachdev 2017), problems with service delivery (Iliffe et al 2014), and the collection of bribes (Ang 2014;Ryvkin, Serra and Tremewan 2017). Researchers should, however, be aware of inferential problems posed by crowdsourced data, such as those related to selection and data continuity, and develop strategies to address them (Post, Agnihotri and Hyun 2018).…”

“…Second, researchers can also use the crowdsourced initiatives upon which cities increasingly rely to collect and provide information about service delivery and other government functions (Ashton, Weber and Zook 2017; Bannister and O’Sullivan 2021; Post, Agnihotri and Hyun 2018). These data can be used to estimate outcomes relevant for political behavior.…”