Week 5-Explore the Impact of Administrative Accountability and Week 6 - Assess the Oversight Functions of Administrative Rulemaking

Developing and Testing an Integrative Framework for Open Government

Adoption in Local Governments.

Authors:

Grimmelikhuijsen, Stephan G.1 [email protected]

Feeney, Mary K.2 [email protected]

Source:

Public Administration Review. Jul/Aug2017, Vol. 77 Issue 4, p579-590. 12p. 1 Diagram, 5 Charts.

Document Type:

Article

Subject Terms:

*RESEARCH

Local government -- United States

Transparency in government

Federal employees (U.S.)

Decision making in political science

Political participation -- United States

Public administration

Geographic Terms:

United States

NAICS/Industry Codes:

921190 Other General Government Support

Abstract:

Open government is an important innovation to foster trustworthy and inclusive governments. The

authors develop and test an integrative theoretical framework drawing from theories on policy diffusion

and innovation adoption. Based on this, they investigate how structural, cultural, and environmental

variables explain three dimensions of open government: accessibility, transparency, and participation.

The framework is tested by combining 2014 survey data and observational data from 500 local U.S.

government websites. Organizational structure, including technological and organizational capacity, is a

determinant shared by all dimensions of open government. Furthermore, accessibility is affected by a

mixture of an innovative and participative culture and external pressures. A flexible and innovative

culture positively relates to higher levels of transparency, whereas capacity is a strong predictor of

adopting participatory features. The main conclusion is that there is no one-size-fits-all solution to

fostering the three dimensions of open government, as each dimension is subject to a unique

combination of determinants. [ABSTRACT FROM AUTHOR]

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Author Affiliations:

1Utrecht University, The Netherlands

2Arizona State University

ISSN:

0033-3352

DOI:

10.1111/puar.12689

Accession Number:

123822099

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Developing and Testing an Integrative Framework for Open Government Adoption in Local

Governments.

Open government is an important innovation to foster trustworthy and inclusive governments. The

authors develop and test an integrative theoretical framework drawing from theories on policy diffusion

and innovation adoption. Based on this, they investigate how structural, cultural, and environmental

variables explain three dimensions of open government: accessibility, transparency, and participation.

The framework is tested by combining 2014 survey data and observational data from 500 local U.S.

government websites. Organizational structure, including technological and organizational capacity, is a

determinant shared by all dimensions of open government. Furthermore, accessibility is affected by a

mixture of an innovative and participative culture and external pressures. A flexible and innovative

culture positively relates to higher levels of transparency, whereas capacity is a strong predictor of

adopting participatory features. The main conclusion is that there is no one‐size‐fits‐all solution to

fostering the three dimensions of open government, as each dimension is subject to a unique

combination of determinants.

Practitioner Points

Open government adoption includes features such as accessibility, transparency, and participation.

There is no one‐size‐fits‐all solution to improving open government; each feature of open government is

subject to a unique set of determinants.

Adoption of open government features is more likely to succeed in less politicized environments, when

there is ample technological capacity, and when there is a rather flexible and innovative working

climate.

Open government brings the promise of more transparent and trustworthy government (Bertot, Jeager,

and Grimes 2010; Janssen, Charalabidis, and Zuiderwijk [ 22] ). The Barack Obama administration even

laid down principles in its Open Government Directive. Researchers have investigated various aspects of

open government, such as computer‐mediated transparency (Meijer [ 35] ), website information

provision (Grimmelikhuijsen and Welch [ 20] ), financial transparency (Pina, Torres, and Royo [ 48] ), and

online participation (Feeney and Welch [ 14] ; Ma [ 31] ; Oliveira and Welch [ 45] ). These studies provide

insights to individual theoretical explanations for the extent of government accessibility, transparency,

and participation.

More recently, scholars have suggested that open government is a multidimensional concept, including

accessibility, transparency, and participation (cf. Abu‐Shanab [ 1] ; Linders [ 30] ; Wirtz and Birkmeyer [

56] ), but because most research has separately investigated the dimensions of open government, our

understanding of open government as a whole is fragmented. An integrative analysis of open

government is important because connections between accessibility, transparency, and participation

facilitate active citizenship. For example, if citizens can access government information, they can actively

participate in decision‐making processes (Meijer [ 36] ; Meijer, Curtin, and Hillebrandt [ 37] ). While

there have been analyses of what dimensions make up open government (Abu‐Shanab [ 1] ; Linders [ 30]

; Meijer, Curtin, and Hillebrandt [ 37] ; Wirtz and Birkmeyer [ 56] ), to the best of our knowledge, there

have been no empirical studies on what factors determine open government as a whole.

The main contribution of this article is to develop and test an integrative approach to the potential

determinants of open government. We draw on theories of policy innovation diffusion (Berry and Berry [

5] ) and innovation adoption (Damanpour [ 10] ; Damanpour, Walker, and Avellaneda [ 11] ; Rogers [ 52]

) to better understand the determinants of open government. Our model incorporates the three main

categories of determinants from the policy innovation diffusion and innovation adoption literatures:

structural organizational variables, cultural organizational variables, and external environmental

variables. Scholars have investigated these determinants to an extent—structural organizational

determinants such as organizational resources (e.g., Bearfield and Bowman 2016; Grimmelikhuijsen and

Welch [ 20] ), organizational cultural variables (e.g., Oliveira and Welch [ 45] ), and the external

environment of an organization (e.g., Ma 2014). Our contribution is to theoretically integrate these

broad categories and provide an empirical test of that framework for all three dimensions of open

government. Our central research question is, to what extent do organizational structure, organizational

climate, and organizational environment affect the adoption of open government features by local

governments?

We test this framework for open government by combining two sources of data: a survey distributed to

a national sample of department heads in 500 U.S. cities (n = 790) and objective data from a content

analysis of the city websites. In general, analyzing websites on the presence of open government

features is thought to be a sound measure of open government adoption, as the emergence of open

government has been closely intertwined with the rapid development of information and

communications technologies (ICTs). ICTs enable governments to collect, store, and release information

on a large scale, which potentially fosters open government (e.g., Bertot, Jaeger, and Grimes; Meijer [

35] ). Indeed, new and old technologies are crucial to enabling open government (e.g., Abu‐Shanab [ 1] ;

Linders [ 30] ). Furthermore, many recent open government policy initiatives have a strong technical

focus. For instance, Obama's Open Government Directive prescribes that government agencies have

various data sets online (Obama [ 44] ). The Open Government Partnership—an international

collaboration of 69 countries devoted to improving open government policies—explicitly encourages

governments across the globe to “use innovations” and “new technologies” to “transform the culture of

government and to serve the public better” (OGP [ 46] , 9). So although it is true that open government

is broader than websites or other digital tools, the latter is regarded as a pillar in open government

policy and research.

Three Dimensions of Open Government

The literature on government transparency often equates transparency with openness (Bertot, Jaeger,

and Grimes [ 7] ), the while decision‐making literature specifies openness as access to decision‐making

arenas (Klijn et al. [ 25] ). Drawing on these two literatures, Meijer, Curtin, and Hillebrandt argue that

open government can refer to both types of openness in terms of information and participation, noting

that open government is “the extent to which citizens can monitor and influence government processes

through access to government information and access to decision‐making arenas” (2012, 13).

For our definition of open government, we propose one alteration: that the access provided by open

government includes a broader range of stakeholders, not just citizens, as specified in Meijer, Curtin,

and Hillebrandt's ([ 37] ) definition. This group of stakeholders who would access information and

decision‐making arenas might also include journalists and interest groups. We use the following

definition: open government is the extent to which external actors can monitor and influence

government processes through access to government information and decision‐making arenas.

Based on this definition, we distinguish three dimensions of open government: accessibility (“access”),

transparency (“government information”) and participation (“decision‐making arenas”). Meijer, Curtin,

and Hillebrandt ([ 37] ) analyze 103 articles on open government and find that it consists of two core

components: ( 1) transparency, which is the “traditional” way of thinking about open government, that

is, disclosure of information to the public; and ( 2) participation, or information disclosure that is

necessary to participate in a meaningful way. This conceptualization is at odds with some of the recent

literature, which notes an emerging consensus that collaboration is a separate dimension of open

government (Wirtz and Birkmeyer [ 56] ).

We do not include collaboration as a separate concept. Some participatory democracy scholars consider

various features of collaboration to be forms of participation (Michels and de Graaf [ 39] ). For instance,

scholars define collaboration as active solicitation for citizen feedback (McDermott [ 34] ) or active

engagement of citizens in government (Wirtz and Birkmeyer [ 56] ). However, there is little conceptual

difference between this definition of collaboration and the way democratic theory has viewed

participation. Participation not only encompasses political decision‐making processes but also the

workplace and local communities (Barber [ 2] ; Michels and de Graaf [ 39] ). Therefore, in line with the

extant literature on participation and the conceptual distinction proposed by Meijer, Curtin, and

Hillebrandt ([ 37] ), we focus primarily on participation, which includes features of collaboration,

including informal ways of soliciting for feedback.

In this study, we consider accessibility as an underlying dimension of open government. Without proper

access, transparency and participation are not possible. Meijer, Curtin, and Hillebrandt ([ 37] ) argue

that open government refers to openness in terms of information, participation, and accessibility.

Additionally, the interconnectedness between accessibility, transparency, and participation is noted in

many policy documents, such as the Open Government Directive issued by President Obama. Therefore,

it is crucial to take all three dimensions into account when investigating open government. We describe

each dimension in more detail next.

We consider accessibility as an underlying dimension of open government. Without proper access,

transparency and participation are not possible.

Accessibility refers to the ability of all stakeholders to utilize information or participation options, both

offline and online. However, we focus on online features of open government. Therefore, it is relevant

to also consider the specific accessibility challenges for online open government features. For example,

people with disabilities (e.g., hearing or visually impaired) or language barriers (e.g., translation of

websites) should have access to information and participation options on websites. The literature on

“digital divides” finds that online literacy, access, and tool use are influenced by socioeconomic status

(SES). Lower‐SES populations have lower online literacy, less secure access, less digital access at home,

and higher reliance on smartphones or public Internet access (Mossberger, Tolbert, and Hamilton [ 42] ).

Transparency refers to information provision to the public. Traditionally, transparency was related to

direct openness, that is, making official meetings of legislatures accessible to the public so that people

can assess government decision making. Transparency was practiced through the “old” information

carrier, ink on paper, with the proceedings of official meetings written in minutes. Today, government

organizations still provide information using leaflets or announcements in newspapers, but they

increasingly use websites and social media outlets to post information (Cucciniello and Nasi [ 9] ). We

focus on the extent to which governments disclose information to external stakeholders through

websites.

Participation refers to the extent to which governments allow external stakeholders to interact with

them and is considered an important democratic feature. A classic example of participation is the town

hall meeting. A different take on participation—which is more informal—is enabled by the use of

technology: governments can ask stakeholders to provide input using Twitter or other social media

channels (e.g., Grimmelikhuijsen and Meijer [ 18] ). Many scholars claim that participation is positively

related to the quality of democracy and improves the legitimacy of decisions (e.g., Porumbescu [ 50] ).

Thus, participation is embraced as one of the core dimensions of open government (Meijer, Curtin, and

Hillebrandt [ 37] ; Wirtz and Birkmeyer [ 56] ). Interestingly, empirical findings consistently show that

citizens have relatively little interest in participating and that active participants are not representative

of the broader population (Michels and de Graaf [ 39] ).

To overcome these problems of representativeness, accessibility, and interests, open government

movements emphasize the use of websites and other digital tools to encourage, enhance, and facilitate

participation in government dialogue and policy making. Particularly, the rise of social media use in the

public sector has increased scholarly attention on online participation (Magro [ 32] ; Mossberger, Wu,

and Crawford [ 43] ). The use of platforms such as Twitter and Facebook is thought to result in more

transparency and citizen participation in government (Feeney and Welch [ 14] ; Grimmelikhuijsen and

Meijer [ 18] ). Therefore, participation is an important dimension of open government.

An Integrative Framework for Open Government

Drawing from our discussion of the dimensions of open government (accessibility, transparency, and

participation), we outline a framework for the determinants of open government. We draw on theories

on policy innovation diffusion (Berry and Berry [ 5] ) and innovation adoption (Damanpour [ 10] ; Rogers

[ 52] ) to develop our propositions. Before outlining those theories and how they relate to our

propositions, we discuss our working definition of innovation and how this relates to open government.

Studies of the adoption of innovation at the organizational level often define innovation as something

new to the adopting organization (Walker [ 54] ). Furthermore, a new idea can pertain to products,

services, and administrative structures and processes (Damanpour, Walker, and Avellaneda [ 11] ). Jun

and Weare ([ 23] ) argue that innovation adoption is something that requires up‐front expenditure of

resources and a major departure from established routines. Open government qualifies as a type of

innovation because it requires a departure from a more traditional logic. Open government requires

governments to proactively disclose information in an accessible way, ultimately enabling participation.

It requires “up‐front expenditure” to develop, monitor, and update websites and social media platforms.

Finally, an element of risk is also involved, as openness comes with potential negative outcomes such as

decreased trust (Grimmelikhuijsen et al. [ 19] ) or disrupted policy processes (Feeney and Welch [ 14] ;

Welch and Feeney [ 55] ). Hence, because open government introduces new technology, new

relationships with stakeholders, and potential risks, we can consider it a form of public sector

innovation.

But why do organizations innovate? One explanation is that organizations respond to pressures from the

external environment, such as competition, resource scarcity, or citizen demands. A second reason is

deliberate organizational decision making, for instance, to acquire new resources or distinctive

competencies. The adoption of innovation is a way to adapt in order to maintain or improve

organizational performance (Damanpour, Walker and Avellaneda [ 11] ; Walker 2006). Likewise, local

governments may respond to pressures from the environment to become more open, as there is a

broad movement to pressure governments to become more accessible, transparent, and participatory

(e.g., OGP [ 46] ). In addition, adopting open government policies may help create better services. Our

proposed framework incorporates three main categories of determinants that relate to the external

environment and internal decision making: structural organizational variables, softer cultural

organizational variables, and external environmental variables.

Structural Organizational Determinants

The first structural determinant of innovation adoption is organizational capacity (Damanpour [ 10] ).

Organizations with higher capacity can more easily afford innovations and have more freedom to

experiment with innovations. Furthermore, prior research recognizes the importance of capacity for the

development, maintenance, and smooth functioning of e‐government initiatives, which may not be

equal to but are related to open government. For instance, research has found that organizational

capacity is positively related to e‐government implementation and progress (Moon [ 40] ; Moon and

Norris [ 41] ). Ma (2014) uses municipal wealth and size to gauge organizational capacity and finds that

these are positively and significantly correlated with the number of government microblogs in China—

furthering evidence that capacity is critical to open government initiatives. Given these findings, we

expect that open government adoption will be positively related to organizational capacity.

Proposition 1: Organizational capacity will be positively related to open government.

Organizations with higher capacity can more easily afford innovations and have more freedom to

experiment with innovations.

Second, we investigate technological capacity. The technological expertise and capabilities available in

an organization might be crucial to furthering open government (Meijer [ 35] ; Wirtz and Birkmeyer [ 56]

). A core concept in government use of technology is the stages models for e‐government (Gil‐Garcia [

15] ; Layne and Lee [ 27] ), which argue that in order to attain full openness and participation,

governments must progress from basic to more advanced technologies.

The presence of e‐services is one of the early or middle stages of e‐government adoption and thus is

important. E‐services include the provision of services and transactions such as allowing residents to

register to vote or complete financial transactions such as paying tickets or fines. Governments that

have well‐developed e‐services demonstrate a basic level of technological capacity and effort. Thus,

technological capacity, measured as e‐services, is expected to be positively related to open government

because the use of technology to inform and involve citizens is a pillar of various open government

initiatives (Wirtz and Birkmeyer [ 56] ).

Proposition 2: Higher levels of technological capacity (presence of e‐services) will be positively related to

the adoption of open government.

Third, we consider centralization, a concept that describes centralized decision making in organizations

(Hall [ 21] ). Centralized organizations are characterized by centralized reporting, processes, decision

making, and control and are expected to limit the contribution that individual employees can make

through their work, as individuals are expected to follow centralized processes. According to a widely

cited meta‐analysis by Damanpour ([ 10] ), centralization has a negative effect on innovation adoption.

Similarly, Mergel and Bretschneider ([ 38] ) hypothesize that decentralized decision making fosters social

media adoption because this allows individuals to experiment with innovations. When decision making

is highly centralized, it is likely that there is less room for experimentation with new technologies that

facilitate participation, making it less likely for centralized organizations to be accessible and

transparent. Thus, we hypothesize the following:

Proposition 3: Higher levels of organizational centralization will be negatively related to the adoption of

open government.

Cultural Organizational Determinants

A category of determinants of adoption of open government that is often overlooked in the literature is

the “softer” organizational determinants (Greenhalgh et al. [ 16] ; Korteland and Bekkers [ 26] ). In a

comprehensive literature review on organizational innovation, Greenhalgh et al. ([ 16] ) find that

dimensions such as the prevailing culture in an organization and attitudes toward risk taking can

influence innovation adoption. We take these findings into account by including work routineness,

innovation‐oriented climate, and citizen participation climate in our study. These three determinants all

relate to the extent to which an organizational culture is flexible and open to unexpected events.

Work routineness is characterized by low task variety and sameness in work activities on a day‐to‐day

basis (Lee, Rainey, and Chun [ 29] ). Work routineness is often related to jobs with lower levels of

professional education and organizational structures that require less analyzability and problem solving.

Because open government facilitates interactions with government constituents, it may conflict with

other organizational routines. Furthermore, work routineness is often related to risk aversion; a civil

servant in an organization with strong work routineness will experience a stable work environment and

may be less used to risk taking. Indeed, Wirtz et al. ([ 57] ) find that the perceived risk‐based attitude of

civil servants can be a barrier to adopting open government data policies. Thus, we expect the following:

Proposition 4: Work routineness will be negatively related to the adoption of open government.

Innovation‐minded organizational climates are more likely to accept innovations (Feeney and Welch [

14] ; Moon and Norris [ 41] ; Oliveira and Welch [ 45] ). Innovation‐oriented cultures are typically

defined by their receptiveness to new ideas (Wynen, Ongaro, and Van Thiel [ 58] ). While Kim and

Bretschneider ([ 24] ) link innovation orientations and climates to e‐government adoption, the literature

on this link is scarce. Moon and Norris ([ 41] ) argue that innovation‐oriented governments tend to

adopt new managerial and technological approaches faster. Specifically, governments that implement

such innovations fervently have a prevailing innovation‐minded culture. Overall, this makes these

governments more likely to see the value of innovations such as open government initiatives and enable

them to adopt these with less resistance. Recently, Oliveira and Welch ([ 45] ) found that innovation‐

minded cultures are more likely to use social media to disseminate information and to enable

participation. Therefore, we postulate the following:

Proposition 5: A climate that is more conducive to innovation will be positively related to adoption of

open government.

The third cultural element we consider is the organization's likeliness to be open to external

stakeholders. For organizations to adopt open government, they need to use various enabling

technologies such as social media and websites. However, such tools are not a silver bullet to engaging

the public (Grimmelikhuijsen and Meijer [ 18] ); engagement requires an organizational culture that

supports openness of citizen participation. A culture of openness toward external stakeholders also

enables learning and better adaption to the environment (Mahler [ 33] ), thus increasing the likeliness of

open government adoption. Furthermore, a culture of transparency and openness is necessary to have a

real impact on government (Bertot, Jaeger, and Grimes [ 7] ). To our knowledge, the specific effect of a

“culture of openness” on open government adoption has not been investigated in the literature thus far.

Therefore, we postulate the following:

Proposition 6: An organizational climate that is more conducive to openness will be positively related to

the adoption of open government.

Determinants in the Organizational Environment

Much of the research investigating the adoption and diffusion of policy innovations draws from

institutional theory: organizations sometimes adopt innovations as a way to adapt to their environment

and legitimize their existence (e.g., Damanpour, Walker and Avellaneda [ 11] ; DiMaggio and Powell [ 13]

). Based on institutional theory, Berry and Berry ([ 5] ) develop a theory on how policy innovations

“diffuse” across states. According to this theory, competition, normative pressure, coercion, and

learning are mechanisms that cause states to adopt policies developed in other jurisdictions. These

processes have found further external validation in later studies (e.g., Lee, Chang, and Berry [ 28] ;

Shipan and Volden [ 53] ). Next we explain how each part of the Berry and Berry model might apply to

the adoption of open government.

Competition

Implementing innovations such as open government lends public support and indicates that a

government organization is “modern” and “makes sense” (DiMaggio and Powell [ 13] ; Korteland and

Bekkers [ 26] ). Conversely, governments that do not remain competitive and adopt innovations at the

same rate will lag their peers. Ma (2014) demonstrates that horizontal competition was positively

associated with the adoption of government microblogging in China. This resonates in recent empirical

findings by Bearfield and Bowman (2016), who find that large cities are driven by competition to

become more transparent. In line with the literature, we expect that governments will be driven by

open government competition and will be more likely to adopt social media technologies when peer

cities are doing the same.

Proposition 7: Competitive pressures from peer cities will be positively related to the adoption of open

government.

Coercive Pressures

A second determinant of innovation adoption is coercive pressures. Coercive regulations and vertical

political mandates exert pressure on governments to adopt particular innovations (Berry and Berry [ 6] ;

DiMaggio and Powell [ 13] ; Shipan and Volden [ 53] ). In this case, U.S. municipal governments often fall

under policies, rules, and regulations from higher levels of government such as states and the federal

government, which serve as coercive pressures. Additionally, some local government agencies such as

police and transportation departments may fall under professional and national standards and

regulations with regard to policing and road building, respectively. Bryson et al. ([ 8] ) highlight that in

order to fit participatory policies to the environment, it is important to clarify legal requirements and

observe freedom of information laws for the public. We capture coercive pressures by looking at

whether an organization is required to adhere to a law or regulation about engaging the public in

decision making.

Proposition 8: Coercive pressures for public participation will be positively related to the adoption of

open government.

Normative Pressures

Normative pressures—the culmination of common practices, values, and norms—can be external or

internal to the organization and are typically exerted by relevant government constituents (Berry and

Berry [ 6] ; Lee, Chang, and Berry [ 28] ). In the case of open government, individuals and organizations

that are using online technologies and want to use the tools to interact with government most

prominently exert external normative pressure for government adoption (Ma 2014). However, there are

other relevant constituents that use open government, most notably, individuals, community

organizations, business, or media who might seek transparency or participatory tools to track, monitor,

and report government actions. For instance, research shows that stakeholder pressure can influence

website transparency (Bearfield and Bowman 2016; Grimmelikhuijsen and Welch [ 20] ). Thus, we

postulate the following:

Proposition 9: Increased influence from external stakeholders will be positively related to the adoption

of open government.

There are also internal normative pressures for open government. The decision to adopt open

government, and especially the participation dimension, might derive from personal use of social

networking services (SNS). As of 2015, use of SNS is quite high. The Pew Research Center reports that 65

percent of American adults use SNS and that this use affects politics, work, communication patterns,

civic life, health, access to information, parenting, dating, and other outcomes (Perrin [ 47] ). Individuals

who are already using the technologies associated with open government in their personal lives might

be more likely to advocate for these technologies in the workplace. We argue that individuals who are

avid users of social media platforms will be more likely to push for technological adoption in the

organization, or at the very least, they will have less resistance to new technologies in their

departments.

Proposition 10: Personal social media use will be positively related to the adoption of online open

government.

Learning

Learning can be described as governments adopting innovations by observing the experiences of nearby

jurisdictions (Shipan and Volden [ 53] ). The line between learning and competition is not always clear.

According to Shipan and Volden ([ 53] ), learning focuses on the policy itself, how is it effective, and how

can it be effectively implemented. In comparison, competition is more strongly focused on imitation of a

peer government, identifying what a certain competitor does and trying to do the same. In comparison,

learning occurs across organizations that are not necessarily at the same level (Lee, Chang, and Berry [

28] ; Ma 2014) but can learn with relative ease in geographic or cultural terms.

Proposition 11: Governments that are able to learn from other organizations will be positively related to

the adoption of online open government.

Political Environment

Our final proposition regards the political environment. Political competition is a core construct that

may influence the adoption of open government (cf. Grimmelikhuijsen and Welch [ 20] ). Political

competition could foster stronger open government because when incumbents face uncertainty over

future political power—which is the case in a competitive environment—they seek to ensure future

access by increasing access to govern-ment information (Berliner and Erlich [ 4] ). On the other hand, a

more politicized environment could also hamper openness. For instance, in the U.S. mayor‐council type,

governments are highly politicized and have elected mayors with strong executive powers, such as

controlling budgets and appointing key officials including judges, police chiefs, and so on. Manager‐

council governments, in comparison, have elected councils that hire a professional city manager to steer

the city (Zhang and Feiock [ 59] ). Recent findings suggest that administrative professionalism influences

transparency of local governments, particularly in smaller cities (Bearfield and Bowman 2016).

Furthermore, an experimental study by de Fine Licht ([ 12] ) finds that transparency in more politicized

policy arenas is more likely to result in less public support. Overall, the empirical evidence indicates that

less political environments are more likely to adopt of open government features.

Proposition 12: Governments in less politicized environments will have increased adoption of online

open government.

Methodology

Data Collection and Analysis

We use three data sources: a 2014 national survey of U.S. city government managers, observational

data collected from 500 local government websites, and U.S. Census data. The survey was conducted by

the Center for Science, Technology, and Environmental Policy Studies at Arizona State University. The

sampling frame draws from managers working in 500 U.S. cities with populations ranging from 25,000 to

250,000. The frame includes all cities with populations of 100,000 to 250,000 and a random sample of

cities with populations of 25,000 to 100,000. The survey was administered to individuals holding five

positions in each city—city manager/city administrator, director of community and/or economic

development, finance director, director of parks and recreation, deputy police chief—using Sawtooth

Software from April 7, 2014, to June 6, 2014. The survey was administered to an adjusted sample of

2,442 individuals,1 with 790 completed responses. The American Association for Public Opinion

Research–calculated response rate is 33.29 percent: 790 responses from 2,373 known eligible cases.

Weights for the data were calculated based on respondent city size (the sampling procedure).

The observational data come from the websites of the 500 cities in the sample. Two coders used an

identical protocol to identify 19 key functionalities on each website. The coding was conducted from

April 2014 through June 2014. An intercoder reliability test resulted in the retention of 17 of the coded

items. A third coder, the principal investigator, verified the remaining 17 items with a spot check of

consistent codes and broke ties between inconsistent codes.

The unit of analysis is the survey respondent, who was asked to respond to a series of questions about

his or her work environment (e.g., the department). The individual responses were then paired with

census data for the city, region, and state and the codes from the website content analysis. We

calculated four linear regression models—one for each dimension of open government and one for all

dimensions simultaneously—in which we included variables to measure 11 of the 12 propositions. We

also included variables to control for population and department.

Variables and Measures

Dependent Variables

We measure the adoption of open government using content analysis of 500 city government websites.

The protocol instructed three coders to look only at content that was no more than three links away

from the homepage, ensuring that only easily accessible content was measured. All codes were based

on a three‐clicks search. Coders were allowed to use the search bar, but only if the end content was still

within three clicks of the home page. The researchers coded the same 500 websites in two stages. First,

two researchers worked independently to code all 500 websites. After conducting an intercoder

reliability analysis, the principal investigator eliminated two of the items (federal government link and

press release) from the data set (because of inconsistent coding and low kappa scores) and then

reconciled the remaining codes.

It is important to note that one limitation of the content analysis is that the codes indicate the presence

of a service and not the quality of that service or how often it is used. We do not know whether the

service is mediocre or advanced or how citizens feel about accessibility, usability, and functionality.

Table [NaN] shows which items we used to calculate sum scores for the three dimensions of open

government: accessibility, transparency, and participation.

Intercoder Reliability for Dependent Variables

Variable Description Kappa

Accessibility

NonEnglish Provides access for non‐English speakers .893

RSS There is an RSS feed .838

Searchbar There is a searchable database/search bar .937

SearchProvider Search bar by outside provider (e.g., Google or Bing) .899

Transparency

DeptDescription Provides description of activities of municipal departments/agencies/units;

description should be on a central site/directory rather than having to go to departments .791

Directory Central directory with all employees listed with contact information; not just directors

but also an employee directory that enables citizens to find a particular person .786

Districtmaps Provides maps of council districts .813

FOIA Freedom of Information Act/FOIA is mentioned or there is a link to or text of public information

law; this includes records requests .838

LawIndex Provides a searchable index or list for archived laws, regulations, and requirements;

includes municipal code .657

MajorSpeech Text or video of major speeches of mayor or chief executive or city council chair (or

president or head) .837

Meetingvideo Online video, audio podcast, video webcast, or live feed of council meetings .791

SiteContract Statement or advertisement declaring that the site is development or maintained by an

outside contractor .927

VotingInfo Provides information on voting and/or elections .880

Participation

Blog There is a blog, discussion board, or forum .697

ContactMayor Provides contact information for mayor: e‐mail, phone, address .671

CouncilAgenda Council meeting agendas are posted .772

Facebook There is a “Follow us on Facebook” link .914

Twitter There is a “Follow us on Twitter” link .893

VotingRegister Provides forms for voter registration (direct link to county or state also counts) .842

Youtube There is a YouTube link .883

Independent Variables

We use a number of independent variables to capture the concepts outlined in the propositions. Scales

constructed of multiple survey items are detailed in table [NaN] and briefly described in this section.

Organizational capacity (proposition 1) is measured using a natural log of the city population. We

acknowledge that city size is not a perfect measure for organizational capacity, although it is often

argued in the literature on technology adoption that larger govern-ments have the advantage of having

a greater administration, more slack, and more resources than smaller cities (e.g., Moon [ 40] ). In a

similar vein, we use city population as a proxy for organizational capacity (see, e.g., Damanpour [ 10] ;

Ma 2014).

Scale Measures

Scale Cronbach's Alpha Questionnaire Items

Centralization 0.79 1. There can be little action taken here until a supervisor approves a decision.

2. In general, a person who wants to make his own decisions would be quickly discouraged in this

agency.

3. Even small matters have to be referred to someone higher up for a final answer.

Competition n/a Does your organization use social media for any purpose?

1. Facebook (no/yes)

2. Twitter (no/yes)

3. YouTube (no/yes)

4. LinkedIn (no/yes)

Sum scores of these for items were used to calculate means for nine population size categories.

Routineness 0.63 1. People here do the same job in the same way every day.

2. One thing people like around here is the variety of work. (R)

3. Most jobs have something new happening every day. (R)

Innovativeness 0.83 1. This organization has a strong commitment to innovation. People who

develop innovative solutions to problems are rewarded.

2. This organization is a very dynamic and entrepreneurial place. People are willing to stick their necks

out and take risks.

3. Employees in this organization are rewarded for developing innovative solutions to problems.

4. Most employees in this organization are not afraid to take risks.

Openness 0.80 1. People in this organization believe that citizen participation is necessary even

if it dramatically slows down government decisions.

2. People in this organization believe that citizen participation actually increases government

effectiveness.

3. People in this organization believe it is the government's responsibility to fully integrate citizens in its

deliberation and decision processes.

1 Response categories: Five‐point Likert scale of agreement, 1 = strongly agree, 5 = strongly disagree.

Technological capacity (proposition 2) is measured using a sum score of five items from the website

content analysis: ( 1) online completion and submission of job applications, ( 2) online employment

information (e.g., openings and application procedures), ( 3) ability to file police reports online (includes

graffiti reporting), ( 4) ability to register and pay for classes online, and ( 5) direct link or access to

transactional opportunities such as paying bills or parking tickets. In each case, the items were coded 1 if

the feature was present on the website, 0 if not.

Centralization (proposition 3) is measured using the average of responses to three questionnaire items

(Hall [ 21] ). The Cronbach's alpha for the centralization scale is 0.79.Routineness (proposition 4) is

measured by averaging responses to three items asking respondents about work routineness (Hall [ 21]

). The routineness scale has a Cronbach's alpha of 0.63, which is sufficient because the scale consists of

three items. Innovative climate (proposition 5) is measured using an average of responses on four items

and has a Cronbach's alpha of 0.83. Openness to participation (proposition 6) is measured as the

averaged responses to the three questionnaire items and has a Cronbach's alpha of 0.80.

Competition (proposition 7) is measured by calculating the average open government score for peer

cities, defined as being the same size. We coded the 500 cities into nine groups based on population:

lowest through 49,999; 50,000–74,999; 75,000–99,999; 100,000–124,999; 125,000–174,999; 175,000–

199,999; 200,000–224,999; and 225,000–250,000. For each set of cities, we calculated a perceived open

government score based on the survey data. Questions can be found in table [NaN] . The mean open

government score was then coded as a separate variable for each respondent. So, for instance, a

respondent from a city with 70,000 inhabitants would be coded with the open government mean of the

cities with a population of 50,000 to 74,999. Thus, peer open government scores are an indicator of

competition from similarly sized cities. A higher average in a “peer category” is an indicator of higher

competition to have more advanced and open websites.

Coercive pressures (proposition 8), pressure that forces or obligates behaviors, is measured using

responses to the following question: “Is your organization legally required to include citizen input in

policy‐making activities?” (1 = yes, 0 = no). External public pressures (proposition 9) is calculated as the

average of responses to four questionnaire items that asked respondents how often the following four

groups participated in decision making: individual citizens, neighborhood associations, news media, and

interest groups (Cronbach's alpha = 0.80). Response categories used a five‐point scale ranging from

1 = very often to 5 = never.

To assess a respondent's internal norms (proposition 10) toward innovation and participation, we asked

how often the respondent uses social media to ( 1) communicate with work colleagues and ( 2)

communicate with friends or family. The measure is the average response from a five‐point scale

(1 = several times an hour; 2 = several times a day; 3 = about once a day; 4 = every few days; 5 = less

often or never) and has Cronbach's alpha of 0.72.

We had no fitting measure for learning (proposition 11) in our data. Various studies have shown that a

link between learning and policy adoption exists (Shipan and Volden [ 53] ), and subsequent research

could aim to develop concrete measures to test this proposition in the context of open government.

To measure the political environment (proposition 12), we use data from the International City/County

Management Association and website searches to code the type of government for each city: council‐

manager (0) and mayor‐council ( 1).

We controlled for department type using a set of dummy variables: mayor's office, parks and recreation,

police, community development, finance, and police.

Results

Table [NaN] shows the descriptive statistics for all the variables in the regression equation. Table [NaN]

indicates that there are missing data for the coercive pressure variable; 694 out of 790 respondents

completed this question. This question asked whether the participant's organization was legally required

to include citizen input in policy‐making activities. Seventy‐nine participants (10 percent) indicated they

did not know whether this was the case. We used pairwise deletion of cases in the regression analyses

so as not to lose all of these cases and thus statistical power.

Descriptive Statistics

Min. Max. Mean SD N

Organizational capacity 10.13 12.39 10.90 0.55 790

Technological capacity 1 5 3.39 1.19 790

Centralization 1 5 2.41 0.74 724

Innovativeness 1 5 3.16 0.80 732

Routineness 1 5 3.46 0.65 724

Openness to participation 1 5 3.55 0.79 771

Competition 2.81 3.63 2.91 0.13 790

External pressure 1 5 3.25 0.87 768

Internal norms 1 5 1.42 0.74 769

Coercive pressure 0 1 0.44 0.50 694

Political environment: Mayor‐council 0 1 0.27 0.45 790

Mayor's office 0 1 0.17 0.38 790

Community development 0 1 0.25 0.43 790

Finance 0 1 0.17 0.38 790

Parks and recreation 0 1 0.20 0.40 790

Police 0 1 0.21 0.41 790

Accessibility 0 4 2.08 1.00 790

Transparency 1 9 4.47 1.64 790

Participation 0 7 4.44 1.32 790

Online open government (all) 1 15 9.47 2.54 790

Table [NaN] shows that the correlations between the independent variables are in the expected

directions: see, for instance, the negative correlation between centralization and innovativeness

(R = −.414), the positive correlation between centralization and work routineness (R = .448), and the

strong relationship between some of the environmental pressures (e.g., coercive and external pressures,

R = .344). None of the correlations in table [NaN] indicates multicollinearity; however, the correlation

between competition and organizational capacity is relatively high (R = .806). This can be explained by

the fact that we used city size as a proxy for organizational capacity: larger cities are more likely to have

larger government agencies and capacity for servicing larger populations but also because they are likely

to feel more pressure from competition as they are more visible to the public (Bearfield and Bowman

2016). Furthermore, although a coefficient of.806 is high, the ordinary least squares regression analysis

results presented in table [NaN] indicate there is no multicollinearity in our models.

Correlation Matrix

1 2 3 4 5 6 7 8 9 10 11 12 13

14

1. Organizational capacity (city size) 1

2. Technological capacity .275 1

3. Centralization .006 –.128 1

4. Innovativeness .078 .124 –.414 1

5. Work routineness –.038 –.181 .448 –.394 1

6. Openness to participation .006 .070 –.121 .246 –.191 1

7. Competition .806 .216 –.006 .042 –.040 –.011 1

8. External pressure .108 .148 .003 .090 –.126 .407 .0990 1

9. Internal norms .017 –.030 –.015 .099 –.094 –.011 .012 .023 1

10. Coercive pressure .048 .060 .058 .009 –.006 .283 .045 .344 –.035 1

11. Political environment (mayor‐council = 1) .016 –.340 .127 –.035 .080 .040 .016

.082 .073 .037 1

12. Accessibility .215 .342 –.076 .139 –.071 .127 .142 .165 .033 –.001 –.138

1

13. Transparency .150 .250 –.026 .104 .017 .018 .148 .082 –.064 .091

–.143 .277 1

14. Participation .320 .419 –.046 .068 –.077 .095 .252 .137 –.010 .030

–.192 .369 .356 1

2 Pearson correlation coefficients.

3 p < .05;

4 p < .01.

Regression Models for Accessibility, Transparency, Participation, and Combined Construct

Accessibility Transparency Participation Open Government (all)

Organizational capacity (size) 0.191 0.019 0.238 0.207

Technological capacity 0.264 0.188 0.312 0.376

Centralization −0.007 0.007 0.010 −0.024

Routineness −0.072 −0.106 −0.007 −0.081

Innovativeness 0.072 0.126 −0.011 0.073

Participation 0.094 −0.039 0.068 0.055

Competition −0.081 0.084 −0.008 −0.011

Coercive pressure −0.044 0.084 −0.030 0.001

External pressure 0.123 0.049 0.064 0.093

Internal norms 0.029 −0.061 0.000 −0.012

Mayor‐council −0.068 −0.087 −0.099 −0.108

Control variables

Mayor's office −0.061 −0.004 0.014 −0.018

Community development −0.105 −0.038 −0.030 −0.078

Finance −0.071 −0.003 0.013 −0.021

Parks and Recreation −0.042 0.016 0.002 −0.012

F = 8.72 F = 4.92 F = 13.11 F = 17.97

R2 = .172 R2 = .105 R2 = .238 R2 = .299

Adj. R2 = .152 Adj. R2 = .083 Adj. R2 = .220 Adj. R2 = .283

5 p < .1;

6 p < .05;

7 p < .01;

8 p < .001.

9 Standardized beta coefficients are displayed.

10 All variables have variance inflation factors of 3.0 or lower, which indicates there is no or very little

multicollinearity.

11 Pairwise deletion of missing values.

12 Reference category for departments: Police department

First we review the findings for the separate models predicting accessibility, transparency, and

participation. A combination of the three factors (organizational structure, culture, and environment)

influences accessibility. For example, accessibility is higher in governments with more organizational

(β = .191) and technological capacity (β = .264). Furthermore, accessibility is higher with organizational

climates that are conducive to participation (β = .094). External pressures from citizens, interest groups,

and news media are also positively related to online accessibility (β = .123).

A combination of factors influence website transparency, including technological capacity and

organizational culture. An organizational climate conducive to innovation is positively related to website

transparency (β = .126) and negatively related to work routineness (β = −.106). This aligns with our

expectation that organizations with daily routines are less likely to be innovative. Furthermore, the

political environment is a significant predictor of the adoption of open government. As we expected,

mayor‐council governments tend to be less transparent than council‐manager governments (β = −.087).

Technological capacity is a strong predictor of participation (β = .312). In addition, organizational

capacity is significantly associated with participation (β = .238). Surprisingly, none of the cultural

variables is associated with the adoption of participation practices. From the environmental variables,

only mayor‐council governments tend to be less developed in terms of online participation

opportunities (β = −.099).

The fourth regression model, presented in table [NaN] , shows the results for the combined open

government adoption. The model indicates that e‐services are strongly and positively related to

adoption of open government (β = .366). External public pressures (β = .091) make open government

adoption more likely. Council‐manager systems tend to have stronger open government presence

(β = −.107). We also observe that organizational climates affect open government adoption, either

positively by an innovative climate (β = .072) or negatively by high routineness (β = −.081).

The variance explained by our model is reasonable for participation (23.8 percent), moderate for

accessibility (17.2 percent), and low for transparency (10.5 percent). The fourth model, which takes the

means of all three dimensions together, has an explained variance of 29.9 percent.

Figure [NaN] presents the overall empirical findings as they relate to our framework for investigating the

ways in which organizational structure, culture, and environment are related to open government. We

find that technological capacity is positively related to open government. This is in line with the idea that

if a strong online infrastructure is present, it is easier to facilitate open government through digital

channels. Furthermore, organizational capacity is related to open government, while centralization is

not significant in the empirical model.

Second, the organizational cultural variables have a heterogeneous effect on open government as the

effect varies across dimensions. We find a marginally negative significant relationship between work

routineness and accessibility and a slightly stronger relationship with transparency, whereas

participation is unrelated. The figures for innovativeness are opposite that for work routineness, that is,

a marginal but positive association with accessibility and bit stronger relationship with transparency.

Openness to participation is not related to transparency, but it is positively related to accessibility and

online participation.

Third, organizational environment is related to open government. The political environment shows the

clearest relation: small cities in a mayor‐council system tend to have less open websites than cities with

a council‐manager system. Furthermore, external pressures are weakly significantly related to

accessibility and marginally related to participation. Other variables—competition, internal norms, and

coercive pressures—are not significantly related to open government.

Discussion

This research is one of the first empirical tests of the determinants of open government, a concept that

comprises previously disconnected literatures on government accessibility, transparency, and

participation. We find that a mixture of structural, cultural, and environmental forces shape open

government. This mixture of factors shows that an integrative framework for open government has

value. We cannot get a full picture of open government determinants using only structural, cultural, or

environmental factors. From the structural organizational perspective, technological and organizational

capacity are more strongly related to open government. From a cultural point of view, organizations

with high work routineness are less likely to adopt open government practices. Furthermore, the

political environment and the extent to which individual citizens, neighborhood associations, news

media, and interest groups are involved in decision making (reflecting external pressures) are positively

associated with open government.

We cannot get a full picture of open government determinants using only structural, cultural, or

environmental factors.

Furthermore, we find that there are distinct drivers for each dimension of open government. First,

accessibility is fostered in climates that value openness and are under pressure by external stakeholders.

Second, transparency seems best fostered in a culture without strong work routineness, as it has more

flexibility. Civil servants in such an environment may be better equipped to deal with transparency

because disclosing information can cause unpredictable responses among the public (e.g.,

Grimmelikhuijsen and Kasymova [ 17] ; Wirtz et al. [ 57] ). Third, participation is prevalent when there is

ample organizational and technological capacity in combination with a less political environment.

Technological capacity is particularly important for participation because the resources to continuously

and actively involve external stakeholders are high. Governments require resources to start and

maintain conversation with citizens and stakeholders.

Overall, technological capacity is an important determinant across all three dimensions. Our study may

somewhat overestimate the effect of technological capacity on open government and is limited by the

method by which we measure and operationalize technological capacity. That said, this finding aligns

with earlier findings that technological capacity is a determinant of open government (e.g., Ma 2014;

Moon [ 40] ), and we do not find empirical evidence that the relationship is endogenous.

Organizational climate has a heterogeneous effect, which is an important finding because research on

open government and innovation thus far has not paid much attention to the influence of these “softer”

organizational determinants (Greenhalgh et al. [ 16] ; Korteland and Bekkers [ 26] ). Furthermore, the

organizational environment influences open government adoption. This resonates with the literature on

government transparency, which has found that external pressures matter (Grimmelikhuijsen and

Welch [ 20] ; Relly and Sabharwal [ 51] ) and that the council‐manager structure—the less political form

of local government—tends to be more transparent (Bearfield and Bowman 2016).

We propose five modifications for future research. First, we find no relation between centralization and

open government adoption. We suspect that the relationship between centralization and adoption is

not as straightforward for open government as it is for the adoption of other innovations (Damanpour [

10] ). The adoption of open government is a highly complex organizational and political process and may

benefit from a centralized structure. For instance, centralized decision‐making power could help make

bolder decisions to adopt and advance open government.

Second, although recent research finds a relationship between competition and social media (Ma 2014)

and e‐government adoption (Lee, Chang, and Berry [ 28] ), we do not find a relationship between our

measure of competition with peer cities and open government adoption. One substantive explanation

for this is that open government may not be an item for competition; it is not a simple innovative

“gadget” that can easily be emulated. According to Shipan and Volden ([ 53] ), competition is focused on

imitating a peer government, identifying what a certain competitor does, and trying to do the same,

which may not fit the complexity of open government adoption. An alternative explanation is that our

measure of competition is too limited. Because this variable is based on population categories, this

measure is partly collinear with the population control variable. This measure could be improved to

better gauge the influence of organizational environment, for instance, by assessing mayoral or

employee participation in state, regional, or national conferences open government.

Third, an important limitation of our empirical analysis is that we do not have measures for learning, a

component of our framework for open government. Future studies may consider focusing on how (local)

governments learn from each other in implementation, accessibility, transparency, and participation

practices.

Fourth, coercive pressures apparently have no influence. However, we acknowledge that we used a

limited measure. The coercive pressure measure consisted of one question asking whether the

respondent's organization was subject to some kind of law that required citizen input in decision

making. However, this measure did not specify whether this obligation only applied to offline

participation or also online participation. A more precise measure could improve the model.

A final improvement is to further explore how the political environment affects open government. We

have one measure of the political environment (type of government). Future research would benefit

from additional political measures that might affect open government such as political competition,

government ideology, and past government's experience with open government. Political competition

(e.g., Berliner and Erlich [ 4] ) and ideology (e.g., Grimmelikhuijsen and Welch [ 20] ) have already been

found to affect government transparency and may affect other dimensions of open government too.

Future research might consider these iterations to improve our understanding of open government

adoption.

Conclusion

The main contribution of this article is to develop and test an integrative framework for the

determinants of open—accessible, transparent, and participative—government. To our knowledge, this

is the first study to empirically test such an integrative model for open government. Much more is to be

done to further assess our framework. Five specific suggestions to improve the construct validity are

already mentioned in the Discussion section. In addition, we need more research to assess the external

validity of our findings. Most importantly, our framework was tested in the U.S. context. and it is unclear

whether our findings hold across different institutional and cultural contexts. Following prior research

on transparency, it is likely that shared determinants such as organizational and technological capacity

also matter in very different cultural contexts (e.g., Piotrowski et al. [ 49] ), yet it is less certain that

findings also hold for the “softer” cultural and environmental determinants.

Our main conclusion is that there is no one‐size‐fits‐all solution to fostering the three dimensions of

open government, as each dimension is subject to a unique combination of determinants. For instance,

transparency is best fostered in innovative and less bureaucratic organizational cultures, participation is

most likely to be present in local governments with a great deal of organizational and technological

resources, and external pressures are important for accessibility. Organizational capacity, technological

capacity, and a depoliticized environment are shared determinants.

Finally, this article shows the added value of integrating the potential determinants of open government

innovation in a framework integrating structural, cultural, and environmental perspectives. We cannot

get a full picture of open government determinants by looking only at organizational structure, culture,

or the environment. As governments are under increasing pressure to be more open, both online and

offline, it will be critical to recognize the role that strong technological and organizational capacity,

innovative cultures, low work routineness, external pressures, and depoliticized environments play to

become more open.

Acknowledgments

This article was presented at a workshop during the Global Conference on Transparency Research, 2015,

held in Lugano. We thank the participants, particularly Albert Meijer, for their feedback.

Note

A total of 69 surveys were returned undelivered and categorized as “unknown eligibility.” The sample

was adjusted for 58 cases that were not eligible: 2 e‐mail addresses were unavailable, 37 individuals in

the sample were no longer working in the position or had retired, and 19 individuals were serving in

more than one position in the city.

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Graph: Framework for Explaining Open Online Government

~~~~~~~~

By Stephan G. Grimmelikhuijsen and Mary K. Feeney

Stephan G. Grimmelikhuijsen is assistant professor in the Utrecht University School of Governance in

The Netherlands. His research interests include public sector transparency, citizen attitudes, e‐

government, and experimental and behavioral public administration. E‐mail:

Mary K. Feeney is associate professor and Lincoln Professor of Ethics in Public Affairs at Arizona State

University and associate director for the Center for Science, Technology and Environmental Policy

Studies. Her research focuses on public and nonprofit management and science and technology policy.

Her most recent book is Nonprofit Organizations and Civil Society in the United States (Routledge, 2014).

E‐mail: