Research themes in big data analytics for policymaking

The use of big data and data analytics are slowly emerging in public policy-making, and there are calls for systematic reviews and research agendas focusing on the impacts that big data and analytics have on policy processes. This paper examines the nascent field of big data and data analytics in public policy by reviewing the literature with bibliometric and qualitative analyses. The study encompassed scientific publications gathered from SCOPUS (N = 538). Nine bibliographically coupled clusters were identified, with the three largest clusters being big data's impact on the policy cycle, data-based decision-making, and productivity. Through the qualitative coding of the literature, our study highlights the core of the discussions and proposes a research agenda for further studies. 大数据和数据分析的使用已逐渐出现在公共决策中,对此需要展开系统性综述和研究议程,聚焦大数据和数据分析对政策过程产生的影响。本文通过文献计量分析和定性分析,分析了公共政策中大数据和数据分析这一新兴领域。本研究包括了从SCOPUS中选取的科学刊物(N=538)。识别了9个文献耦合簇,其中最大的三个簇分别为:大数据对政策周期的影响、基于数据的决策、生产率。通过对文献进行定性编码,我们的研究强调了探讨的核心,并提出了进一步的研究议程。 El uso de macrodatos y análisis de datos está emergiendo lentamente en la formulación de políticas públicas, y hay pedidos de revisiones sistemáticas y agendas de investigación que se centren en los impactos que los macrodatos y el análisis tienen en los procesos de políticas. Este artículo examina el campo naciente del big data y el análisis de datos en las políticas públicas mediante la revisión de la literatura con análisis bibliométricos y cualitativos. El estudio abarcó publicaciones científicas recopiladas de SCOPUS (N = 538). Se identificaron nueve grupos acoplados bibliográficamente, siendo los tres grupos más grandes el impacto de los macrodatos en el ciclo de políticas, la toma de decisiones basada en datos y la productividad. A través de la codificación cualitativa de la literatura, nuestro estudio destaca el núcleo de las discusiones y propone una agenda de investigación para estudios posteriores. Big data and data analytics have been seen as augmenting knowledge, ultimately leading to better decision-making. Arguments such as that the broad-based use of big data and data analytics will lead to the end-of-theory speak volumes about our expectations of big data and data analytics technologies' transformative power. While industry has been leading the way to test big data and analytics, public actors have been slower to engage (Poel et al., 2018), despite an equal opportunity for big data and data analytics to augment the public policy process. Utilizing big data and data analytics has become a near necessity due to our increasing capability for creating and collecting data at an extraordinary rate. The terms “big data” and “data analytics” have been among the buzzwords of recent years, leading to an upsurge in research, industry, and government applications (Zhou et al., 2014). The increased interest in big data in public policy can be seen in the scientific literature Figure 1, highlighting the increase in big data and analytics related literature. We also see public organizations increasingly engaging with big data analytics to solve challenges like the sustainability crisis and pandemics.1 Scholarly discourse has highlighted case studies and narratives on implementing big data and data analytics in the policy process. However, the literature lacks a systematic view of the current state of big data and data analytics in public policy, and there are identifiable research gaps (Desouza & Jacob, 2017). RQ1. What are the thematic communities of big data and data analytics literature concerning public policy-making? RQ2. What are the research questions emerging under each of the thematic research communities? Our study adopted a mixed-method systematic literature review approach based on a robust empirical bibliometric analysis followed by a qualitative analysis of the core documents to answer these questions. Using a well-established bibliometric method, bibliographic coupling, we identified thematic differences within the literature, and here, we highlight points of departure from the extant literature. The bibliometric analysis was, in turn, used as a basis for the qualitative analysis of the core literature, which is used to propose a research agenda. We find nine contemporary research communities addressing different aspects of big data and data analytics in public policy. While these communities have significant overlap, our analysis identifies them drawing from different theoretical foundations. Moreover, we demonstrate three larger research strands taking different vantage points, namely building strategic capability, data-based decision-making and productivity increases. Finally, our work proposes a research agenda focusing on the role of strategic capability, data-based decision-making, how to address expectations for better services while simultaneously increasing productivity and how to leverage policy analytics and empiricism. Our results offer scholars in public policy a vantage point to the theoretical foundations of research in big data and data analytics in public policy-making. We also draw from the identified communities to highlight emerging research themes that can guide research forward. For policymakers, our results highlight the on-going scholarly debate that focuses on addressing critical issues in the adoption of big data in public policy-making, namely capability building and the extent of data-based decision-making. This article will proceed as follows: next, we review the central elements of big data in policy-making. This is followed by a description of the data and our mixed-method approach. Finally, the empirical results are described and followed by a discussion to make sense of the research themes emerging from the analysis. “Big data” is a general term used for the process of gathering massive amounts of data from different sources. Sources can include human-input data but also includes data from sensors or different types of monitoring systems that create process data while running. It is clear that we are accumulating data at a never before seen rate. Already, in 2014, the pace was staggering, with 90% of the world's data being collected during the prior 2 years and 2.5 quintillion bytes of data added each day (Kim et al., 2014). Having access to massive amounts of data has enabled significant innovation in both the public and private domains. Looking at companies like Google and Amazon, with their innovation of new services for consumers, or at the recent ability for doctors to detect cancer cells more precisely thanks to massive training data about what a cancerous cell is, we can see that we are very much on the cusp of creating a broad utility of big data and analytics. This has been seen as a shift in the Industrial Revolution's magnitude (Richards & King, 2014) and has been widely hyped in business (Margetts & Sutcliffe, 2013). That said, public policy is not at the forefront of the use of big data and data analytics in decision making (Kaski et al., 2019; Poel et al., 2018). This nonadoption is due to multiple factors limiting these technologies' utility (Malomo & Sena, 2017). The ever-increasing amount of data offers possibilities for discovering new relationships and inferencing a multitude of problems. However, this comes with new challenges involving reproducibility, complexity, security, and risks to privacy and a need for new technology and human skills. This is very much the case in public policy, where we need to clearly identify where big data can add value in an ethical and trustworthy manner. In a review, Giest (2017) highlighted three underlying factors to consider. First, institutional capacities have a significant role in the use of big data in public policy, producing solutions that can to with data while also taking the data in the public However, we from research that are an limiting for public policy of big data (Malomo & Sena, 2017). with big data comes the of public for to with big data but also the of new is, that the and public and new from both big data will have an impact on the policy have that there has been in taking of big data and analytics (Poel et al., a significant in the policy et al., Giest (2017) highlights the role and the role of big data in policy on such as while to collecting data for for policy and the role of big data in the and policy are core to and policy In is to that are not a and policy the of analytics the policy et al., or not we approach the policy as & and has been that big data analytics, used more in policy in government policy and agenda (Poel et al., 2018). 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