Methodical Snark critical reflections on how we measure and assess civic tech

Why do governments do civic tech and open government? (a mini lit review)


The civic tech and open government community spends a fair amount of energy persuading government counterparts to get in the game, measuring how well they do, and encouraging them to do more and better. There seems to be based on a general assumption that doing so works best when appealing to government incentives, either to make their work easier, to increase their legitimacy or to get on the right side of national and international norms. But what does the literature say?

Well, as usual, it’s complicated. Scholarly work looking at why governments pursue civic tech, open government, open data, e-participation and other such programming is as diverse as one might expect. It’s spread across a number of disciplines and uses a variety of methods, and lots of careful distinctions should be made between studies on the incentives, motivations, boosters, enabling factors and predictors of government engagement. I’ll refer casually to “incentives” for “civic tech” in order to keep this brief, but the distinctions do matter.

As per usual, the literature seems to be dominated by case studies, and there’s a lack of comparative empirical or synthetic work. This likely because the field of study is relatively new, but serves as a general point of caution when drawing conclusions. As usual, I’ve pasted formatted references with links below the fold. A lot of the links bump into paywalls, but I’m happy to facilitate access to the articles if you drop me an email.

Frameworks, complicated influences and rhetorical frames

Several scholars offer broad frameworks or diverse taxonomies for understanding government incentives. Yang and Wu (2016) conduct a comprehensive literature review on incentives to open government data, and use their findings to propose a framework in which eight exogenous socio-technical constructs (“perceived usefulness, perceived effort, external influence, facilitating conditions, organizational culture, perceived benefits, perceived risks, and organizational capability”) influence official’s intentions to open government data (2). They then test the framework in a survey with Taiwanese government officials, finding that both organizational culture and external influence are motivating constructs, and that “the expectation of higher-level authority” had a particularly compelling effect (10-11). Davies and Fumega (2014) adopt a more conceptual approach to understanding incentives for governments to adopt ICT innovations for transparency, accountability, and anti-corruption, and note five (often overlapping) factors: efficiency, innovation/value, internal, accountability, international standing, manage bottom up demands (v), but don’t suggest mechanisms for operationalizing or comparing them. .

Other scholars note distinct types of incentives, and find that they interact in complicated ways. Yavuz and Welch’s (2014) survey of government managers in 500 US cities proposes a conceptual model in which organizational constraints, technical capacity and external influence determine the degree of openness and interactivity in US government websites (575), while Martin and Begany (2016) find that “efficient operations, improved data, improved external access, improved healthcare and literacy, increased access, new applications (mob) and increased transparency and fairness” (3) constitute “anticipated benefits of posting government health data to open data platforms” in their study of two US institutions.

Several scholars propose rhetorical frames as the best way to understand why civic tech gets pursued. At the regional level, De Blasio et al (2016) review open government policies in four European countries, and identify three frames within which arguments for pursuing open government are pursued and contested. They argue that motivations and arguments get clustered around “economic constraints or opportunities, innovation, and enhancement of democracy” (8). Gonzalez-Zapata and Heeks (2014) propose a similar approach on the basis of their open government data  study in Chile, which reveals four distinct stakeholder perspectives, including a bureaucratic perspective in which is motivated by efficiency and the quality of public service delivery, and a political perspective, in which open data is motivated by norms and perceptions of government action (447-448).


Most research on government incentives is based on discrete case studies, and produces evidence for why one type of incentive or another is the dominant force incentivizing civic tech for governments. They’re clustered below by types of incentive.

Inherent characteristics

The majority of research appears to attribute civic tech uptake to internal characteristics and enabling factors. Hofmann et al’s (2012) literature review on factors of e-government acceptance identifies five characteristics of governance (demographic, administrative structure, managerial style, and government capacities), and a single variable (sigh) relating to “environmental characteristics,” including relationships to other governmental organizations and “social expectations” (11-13). This emphasis is supported by Conradie and Choenni (2012), who find procedural and institutional aspects related to technology to be most important in their survey of Dutch public officials, which “found that important indicators for data release are the way data is stored in an organization (distributed/decentralized versus centralized), whether data is internally produced or externally gathered, the use of data, and the availability of guidelines to determine whether data is suitable for release” (2).

Political culture is king for Zheng et al (2014), who studied municipal governments in the US state of New Jersey, to conclude that “the willingness of government to provide access for citizens to participate, rather than its technical capacity, becomes the key factor in determining the level of e- participation” through websites (657), and that “political will trumps technology as a source for developing opportunities for e-participation” (658).

Chadwick’s (2011) fantastic study of the failure of a local e-participation initiative in the US emphasizes the importance of exploring “insider studies” in addition to the study of external factors when attempting to understand e-participation initiatives, and notes that  “attitudes, shared meanings, resources, inter- actions, and decisions of insider actors matter a great deal in determining outcomes” of governmental strategies for digital engagement (23).

Notably, however, the literature emphasizing internal government attributes does not look closely at purely internal uses of technology. Hofmann et al’s (2012) literature review on factors of e-government acceptance identified only two articles exploring the adoption of internal e-Government services by government employees (13).

External pressure

Let’s face it, being told what to do matters, though I found this to be surprisingly under-emphasised in the literature. Nurdin et al (2012) pursue a hard-end understanding of external pressure and adopt the concept of coercive force from institutional theory to assess a case of local e-government implementation in Indonesia. They find that the external pressures of central government, regulation and citizen groups all motivate e-government implementation to some (imprecise) degree. More surprisingly, they find that financial limitations also encourage e-government, lending credence to rhetorical frames that emphasize efficiency and cost saving described above.

Jun and Weare (2011) survey on innovatoin in US municipalities found that “externally oriented motivations appear more influential than internal factors such as bureaucratic politics” or “efficiency concerns” (495-abstract). They also note that a “more systematic focus on institutional motivations can advance theory and inform policies to promote innovation.“ (496) Duh.


Arguably a variant of external pressures, several scholars emphasize how much government actors care about they they are perceived. Often, evidence supports commonsensical conclusions. Governments want to look good, as shown by Rodríguez Bolívar’s (2016) survey of how Spanish municipalities are using “Web 2.0” technologies in service provision, which concludes that “the main goal pursued by governments is the representation of the agency function through all available online channels” (614). But reputation is also shaped by deep contextual factors, as shown by Ahn and Berardino (2014), who reviewed US state webportals to conclude that the government adoption of “web 2.0” tools is viewed as risky by state governors, and more likely to be pursued by governors that are newly elected or have little political support.

Other studies suggest that peer performance matters, such as ben-Aaron et al’s (2016) field survey of US country governments, which concluded that the speed and frequency with which county governments fulfil freedom of information requests is positively correlated with knowledge that neighboring municipalities have done the same.  

And lastly, what governments think is going to happen appears to be more important than what actually will. Wang and Lo (2016) survey Taiwanese government agencies to conclude that perceived benefit is a more significant driver of OGD initiatives than organizational readiness or external pressures. So keep making those strong arguments, civil society.

The Question of Norms

Research on the influence of norms is notably absent here. The million dollar elephant in the room, as far as I can see, is whether powerful normative frameworks like open government or initiatives like the OGP actually encourage government uptake of civic take. I haven’t seen any research directly addressing this and would love to hear if I’ve missed it.

Notably, there is some research on this dynamic from other fields. Human rights research has suggested that committing to international norms through treaties does not improve human rights observance (Landman, 2005; see also this research placed in context). Literature on the diffusion of policy innovation (why countries choose to adopt new policies) suggests that international frameworks and norms don’t matter (at least for economic policy) (Simmons & Elkins, 2004; Brooks, 2005), but that peer behavior can be tremendously important (Brooks, 2007; Brooks, 2005; Brinks & Coppedge, 2006). This recalls the findings of ben-Aaron et al (2016), who also cite multiple studies supporting this dynamic (68). I’ll have more on this in a full paper in the next weeks.

Grab bag

A number of other studies are interesting and worth mention, though they enjoy little support from other research. Yavuz and Welch (2014) note a dark side of government civic tech adoption, citing arguments that tech gets used by governments “to maintain agencies’ own mission and reinforce existing social and political patterns” rather than “enhance responsiveness or increase citizen participation” (citing Davis, 1999, 146-48; Margolis & Resnick, 2000; Chadwick & May, 2001in Yavuz & Welch, 2014: 575).

For non-democracies, exposure to economic globalization is a demonstrable predictor of e-participation according to a review of global data sets on governance systems and economic contextual variables by Åström et al (2012), which concludes that while “domestic factors are still the best predictors of e-participation efforts among democracies, economic globalization emerges as the strongest driver behind e-participation initiatives within the group of non-democratic regimes“ (148). In other news, Delphi studies by Wagner et al (2016) find that German politicians are super optimistic about technology legitimizing politics (6-7), and early adopters tend to be best performers according to Chatfield and Reddick’s (2016) review of Australian open data portals (161).


Ahn, M. J., & Berardino, M. (2014). The Adoption of Web 2.0 by the State Government: International Journal of Public Administration in the Digital Age, 1(1), 56–73.

Ben-Aaron, J., Denny, M., Desmarais, B., & Wallach, H. (2016). Transparency by Conformity: A Field Experiment Evaluating Openness in Local Governments. Public Administration Review, (February).

Brinks, D., & Coppedge, M. (2006). Diffusion Is No Illusion. Comparative Political Studies, 39(4), 463–489.

Brooks, S. M. (2007). When Does DiffusionMatter? Explaining the Spread of Structural Pension Reforms Across Nation. The Journal of Politics, 69(3), 701–715.

Brooks, S. M. (2005). Interdependent and domestic foundations of policy change: The diffusion of pension privatization around the world. International Studies Quarterly, 49(2), 273–294.

Chadwick, A. (2011). Explaining the Failure of an Online Citizen Engagement Initiative: The Role of Internal Institutional Variables. Journal of Information Technology & Politics, 8(1), 21–40.

Chatfield, A. T., & Reddick, C. G. (2016). Open Data Policy Innovation Diffusion : An Analysis of Australian Federal and State Governments. In Proceedings of the 17th International Digital Government Research Conference on Digital Government Research (pp. 155–163).

Conradie, P., & Choenni, S. (2012). Exploring process barriers to release public sector information in local government. In Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance – ICEGOV ’12 (p. 5).

Davies, T., & Fumega, S. (2014). Mixed incentives : Adopting ICT innovations for transparency, accountability and anti-corruption (U4 Issue Paper). Retrieved from

De Blasio, E., Selva, D., Blasio, E. De, & Selva, D. (2016). Why Choose Open Government? Motivations for the Adoption of Open Government Policies in Four European Countries. Policy & Internet, 1944–2866.

Gonzalez-Zapata, F., & Heeks, R. (2014). The multiple meanings of open government data: Understanding different stakeholders and their perspectives. Government Information Quarterly, 32(4), 441–452.

Hofmann, S., Räckers, M., & Becker, J. (2012). Identifying Factors of E-Government Acceptance – A Literature Review. Proceedings of the Thirty-Third International Conference on Information Systems, 1–19. Retrieved from

Jun, K. N., & Weare, C. (2011). Institutional motivations in the adoption of innovations: The case of e-government. Journal of Public Administration Research and Theory, 21(3), 495–519.

Landman, T. (2005). Protecting Human Rights: A Comparative Study. Georgetown University Press.

Martin, E. G., & Begany, G. M. (2016). Opening government health data to the public: benefits, challenges, and lessons learned from early innovators. Journal of the American Medical Informatics Association, (518), ocw076.

Nurdin, N., Stockdale, R., & Scheepers, H. (2012). The influence of external institutional pressures on local e-government adoption and implementation: A coercive perspective within an indonesian local e-government context. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7443 LNCS, 13–26.

Rodríguez Bolívar, P. M. (2016). Political Factors for the Adoption of Different Governance Models in the Provision of Public Services Under Web 2.0 Technologies. In K. Y. Dwivedi, M. Mäntymäki, M. N. Ravishankar, M. Janssen, M. Clement, L. E. Slade, … C. A. Simintiras (Eds.), Social Media: The Good, the Bad, and the Ugly (Vol. 9844, pp. 607–618). Cham: Springer International Publishing.

Simmons, B., & Elkins, Z. (2004). The Globalization of Liberalization : Policy Diffusion in the International Political Economy. American Political Science Review, 98(1), 171–189.

Wang, H.-J., & Lo, J. (2016). Adoption of open government data among government agencies. Government Information Quarterly, 33(1), 80–88.

Yang, T.-M., & Wu, Y.-J. (2016). Examining the socio-technical determinants influencing government agencies’ open data publication: A study in Taiwan. Government Information Quarterly.

Yavuz, N., & Welch, E. W. (2014). Factors affecting openness of local government websites: Examining the differences across planning, finance and police departments. Government Information Quarterly, 31(4), 574–583.

Zheng, Y., Schachter, H. L., & Holzer, M. (2014). The impact of government form on e-participation: A study of New Jersey municipalities. Government Information Quarterly, 31(4), 653–659.

Åström, J., Karlsson, M., Linde, J., & Pirannejad, A. (2012). Understanding the rise of e-participation in non-democracies: Domestic and international factors. Government Information Quarterly, 29(2), 142–150. 

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Methodical Snark critical reflections on how we measure and assess civic tech