Social equity in the data era: A systematic literature review of data‐driven public service research

• Published date: 01 March 2023
• Author: Erna Ruijer,Gregory Porumbescu,Rebecca Porter,Suzanne Piotrowski
• Date: 01 March 2023
• DOI: http://doi.org/10.1111/puar.13585

RESEARCH ARTICLE

Social equity in the data era: A systematic literature review of

data-driven public service research

Erna Ruijer

1

| Gregory Porumbescu

2,3

| Rebecca Porter

2

| Suzanne Piotrowski

2

1

Utrecht University School of Governance,

Utrecht University, Utrecht, The Netherlands

2

Rutgers School of Public Affairs and

Administration, Rutgers University Newark,

Newark, New Jersey, USA

3

Department of Public Administration, Yonsei

University, Seoul, South Korea

Correspondence

Erna Ruijer, Utrecht University School of

Governance, Utrecht University, Bijlhouwerstraat

6, 3511 ZC The Netherlands.

Email: h.j.m.ruijer@uu.nl

Funding information

National Science Foundation, Grant/Award

Number: 1952096

Abstract

Governments increasingly rely on large amounts of data to deliver public services.

In response, there is a robust discussion about the implications of this trend for

efficiency and economy, but much less attention is paid to social equity. To

address this issue, our study synthesizes cross-disciplinary research on the relation-

ship between data-driven public services and social equity. Based on a systematic

literature review of 190 articles covering a decade of research, we demonstrate

how public sector data applications relate to social equity in terms of access to ser-

vices, treatment, service quality, and outcomes. Our review identifies key mecha-

nisms related to data collection, storage, analysis, and usage that need to be

addressed to ensure more equitable data-driven public services. This review con-

tributes to public administration research and practice by highlighting the com-

plexities of social equity in the data era.

Evidence for practice

•Choices about what data to collect on individuals and groups, on how to store,

analyze, and use data for specific purposes can lead to inequities in the manage-

ment of public services.

•Our review identifies underlying technical, socio-technical, and systemic mecha-

nisms in the data process and discusses their relationship to social equity.

•The identified mechanisms are transformed into key questions that govern-

ments can use for more equitable data-driven public services.

Governments increasingly rely on complex data sets and

sophisticated analyses to determine how to best deliver

public services. Examples of this trend include predictive

policing (Benbouzid, 2019;Brayne,2017), smart city projects

(Janssen & Kuk, 2016; Robinson & Franklin, 2020), and social

protection programs (Masiero & Das, 2019). While govern-

ments have always collected, stored, analyzed, and used

data, recent technological innovations have expanded the

production of data in terms of volume, velocity, variety,

openness, and interoperability (Kitchin, 2014a).

These data-led developments change the policy land-

scape by altering how decisions are made in government,

expanding the number of data sources, integrating cross-

agency data, and using predictive rather than reactive analyt-

ics (Nguyen & Boundy, 2017). These developments also cre-

ate new opportunities for governments to influence

democratic processes, the economy and efficiency of public

service provision, and innovation (Janssen et al., 2012;

Nguyen & Boundy, 2017; Safarov et al., 2017). However, while

data are often discussed with reference to their ability to

transform, there is growing attention to the choices the gov-

ernment makes regarding data that may reinforce or exacer-

bate social equity concerns in public services (Eubanks, 2017;

Nguyen & Boundy, 2017). For example, Eubanks (2017)dem-

onstrates how data-driven social services, meant to assist the

poor, are more likely to push them further into poverty.

Social equity is a foundational anchor of public admin-

istration (Blessett et al., 2019). Social equity refers to fair-

ness and justice in the provision of governmental policies

and services (Frederickson, 2015;Gooden,2015;Guy&

McCandless, 2012; Riccucci, 2009). A recent systematic

literature review on equity in public services revealed

Received: 11 December 2021 Revised: 29 November 2022 Accepted: 1 December 2022

DOI: 10.1111/puar.13585

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribu tion and reproduction in any medium, provided the

original work is properly cited.

© 2022 The Authors. Public Administration Review published by Wiley Periodicals LLC on behalf of American Society for Public Administration.

316 Public Admin Rev. 2023;83:316–332.

wileyonlinelibrary.com/journal/puar

well-established streams of social equity research, which

include representative bureaucracy, performance manage-

ment, administrative burden, and administrative reforms

(Cepiku and Mastradascio 2021). Data-driven public service

delivery, however, was not found to be a separate stream,

even though social equity scholars do, in fact, increasingly

examine the role of data-informed decision-making. To

illustrate, Gooden (2017) demonstrates the importance of

data to capture the magnitude of inequities and to track

theprogressofequityovertime.

Thus, one important conclusion is that, while scholars

are now interrogating the implications of data-driven public

services for social equity, our understanding of this relation-

ship is fragmented and ambiguous (Eubanks, 2017;

Kleinberg et al., 2020; Staines et al., 2020). This lack of clarity

is problematic because an awareness of social equity in

public administration is critical to the way we think about

and evaluate government (Cepiku & Mastrodascio, 2021;

Fredrickson 2015; Gooden, 2015;Guy&McCandless,2012;

Riccucci, 2009). This study seeks to resolve some of this

uncertainty by providing a structured and systematic

understanding of the relationship between data-driven

public services and social equity. With this objective in

mind, our study bridges the rapidly growing bodies of

research on the ‘datafication’of the public sector

(Kitchin, 2014a;Redden,2018)andsocialequity(Cepiku&

Mastrodascio, 2021;Fredrickson2015;Guy&

McCandless, 2012; Gooden, 2015; Riccucci, 2009), to answer

the following research questions:

1. What are the implications of data-driven public ser-

vices for social equity?

2. How are governmental choices and activities regarding

data-driven public services related to social equity?

To address these questions, we conduct a systematic liter-

ature review. As noted earlier, there is ambiguity in

understanding how data-driven public services affect social

equity. To this end, a systematic literature review is well

suited to address this ambiguity, because it offers a compre-

hensive overview of important themes and patterns across

the published body of research on this topic. Our systematic

literature review cast a wide net but, in the end, yielded only

190 articles published between 2010 and 2020.

Our review contributes to public administration schol-

arship and practice in a number of ways. First, we

advance the concept of social equity in the data era by

assessing the state of the art on data-driven service provi-

sion along the four different dimensions of social equity

(Johnson & Svara, 2011): distributional equity (access),

procedural fairness (equal rights and treatment), process

equity (quality), and equity in outcomes. Second, we iden-

tify key mechanisms related to data collection, storage,

analysis, and usage (Löfgren and Webster 2020), which

explain the relationship between data-driven public ser-

vices and social equity. Third, we contribute to public

administration research and theory by outlining a

research agenda that promises to advance our under-

standing of the implications of this prominent reform

trend for social equity. Finally, our review results in key

actions for practice that can facilitate more equitable

data-driven public services.

THEORETICAL BACKGROUND

Information and communication technologies (ICTs) have

transformed how data are produced, stored, analyzed,

and utilized, triggering what some refer to as a data revo-

lution (Kitchin, 2014a). Governments worldwide are

attempting to leverage these data-centric developments

to improve different aspects of public services in hopes

that better information will help them improve the effi-

ciency and effectiveness with which public services are

delivered (Redden, 2018). Four prominent illustrations of

TABLE 1 Overview of data developments included in this study

Data developments Definition Example

Open Government

Data

Government data that are freely available to the general

public without any limitations (Attard et al., 2015)

Government data portals e.g., Data.gov;

data.europa.eu that contain, for

example, health data, energy data,

climate data, and transport data

Big Data “High-volume data that frequently combines highly

structured administrative data actively collected by

public sector organizations with continuously and

automatically collected structured and unstructured

real-time data that are often passively created by public

and private entities (…)”(Mergel et al., 2016)

Census data, social media data, and scan

data

Algorithm “Any set of rules, whether computational or other,

implemented in a sequence to reach a particular

outcome (…)”(Busuioc 2021 p. 4)

Predictive policing; criminal risk

assessments for bail algorithms

Smart City “The increasing extent to which urban spaces are

composed of and monitored by pervasive and

ubiquitous computing and digitally instrumented

devices (…) that produce ‘big data’(Kitchin, 2014b p. 1)

Data generated by air quality monitors or

smart traffic lights to manage traffic

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