Explaining Government Crowdsourcing Decisions: A Theoretical Model

Introduction

With the ever-growing advancements in ICTs, there emerge many opportunities for governments to innovate public service delivery, to improve democratic outcomes, and to undertake administrative reforms. One of the digitally enabled government innovations that have been gaining more attention recently is government crowdsourcing. Crowdsourcing can be defined as “the act of an organization taking a function once performed by an organization’s own employees and outsourcing it to people outside the organization (crowd) through an open call online” (Liu, 2017, p. 656; Howe, 2006a). In public context, main examples of crowdsourcing include involving citizens in the production of public services, inviting the public to solve public problems, and incorporating public participation into policy making (Nam, 2012; Liu, 2017). It is argued that crowdsourcing has the potential to provide solutions to persistent or emergent issues and problems that may not be met by traditional bureaucratic efforts (Bommert, 2010). Crowdsourcing platforms “can empower citizens, create legitimacy for the government with the people, and enhance the effectiveness of public services and goods” (Liu, 2017, p. 656). In addition, crowdsourcing can be very functional to employ the public at large for searching for new ways and methods to conduct the business, particularly at lower costs when compared to paying traditional employees (Howe, 2006b). Since crowdsourcing can be operationalized using online networks and communities through the intra- and internet, it eliminates time and space as the limiting elements together with the associated costs that public institutions are assumed to bear when aiming to address societal issues.

Nonetheless, the initial experience of governments with these online platforms has been a trial-and-error process (Brabham, 2009). While the potential benefits and challenges mentioned earlier -to some extent- explain governments’ decisions to crowdsource online, there is a need to adopt a more holistic approach in understanding governmental adoption of crowdsourcing, and consider a variety of factors in explaining this process, including the decision to use information and communication technologies.

In a study that conducts a systematic review of crowdsourcing decisions in the business sector, Thuan, Antunes and Johnstone (2016, p.48) assert that “there is lack of a commonly accepted list of factors that affect the decision to crowdsource” and “the overall picture on the crowdsourcing decision is still unveiled”. Existing research on government crowdsourcing has largely focused on dispersed case studies or the citizens’ perspective. However, factors that affect governments to engage in online crowdsourcing are not comprehensively explored in the literature.

In the light of this gap, the objective of this study is to identify factors related to government online crowdsourcing decisions. By conducting a review of the case studies on government online crowdsourcing, the chapter proposes an integrated theoretical model of factors affecting government crowdsourcing decisions, including individual perceptions, organizational factors, and environmental factors. According to this framework, some policy recommendations for government crowdsourcing decisions are made.

The paper is organized as follows. The first section discusses crowdsourcing concept and presents a theoretical framework for the study. In the next section, methodology for the study is explained, and findings from the review of the case studies on governmental online crowdsourcing are presented. Based on this review, a theoretical model is developed for government online crowdsourcing adoption. Finally, conclusions discuss research and policy implications of the model.