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Technology-task coupling: Exploring social media use and managerial perceptions of e-government

Mary K. Feeney Associate Professor School of Public Affairs Arizona State University 411 Central Ave Phoenix, AZ. 85004 mkfeeney@asu.edu

Eric W. Welch Professor School of Public Affairs Arizona State University 411 Central Ave Phoenix, AZ. 85004 ewwelch@asu.edu

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Technology-task coupling: Exploring social media use and managerial perceptions of e-government Abstract: Social media comprises a set of new technologies that enable richer data exchange in

highly decentralized, dynamic, and loosely structured, versatile virtual environments. Social

media technology is expected to enhance participation, learning, and knowledge production in

government settings, aligning traditional structural and authority boundaries while also

challenging them. We examine the extent to which local governments in the U.S. are coupling

social media technology with two types of participative tasks: collaborative work inside the

organization and participative interaction with external stakeholders. We also explore how these

two technology-task couples are associated with perceptions of the positive and negative

outcomes of technology use. We use survey data from five departments – community

development, finance, police, mayor’s office and parks and recreation – in 500 U.S. cities.

Respondents were asked to identify the social media technologies that they use and the kinds of

activities for which each identified technology is used, resulting in a set of technology-task

couples. Findings show that social media and their use for specific tasks have limited impact on

either positive or negative perceived outcomes. These non-findings may demonstrate that the

implementation cost of the technologies outweighs the benefits they realize; that the technology-

task application substitutes for traditional approaches to the same task, but no effect is incurred;

or that these technologies are relatively new to local governments and efforts to effectively

utilize them for internal work tasks and external engagement are in their infancy.

Keywords: Social Media, local government, technology, management

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Technology-task coupling: Exploring social media use and managerial perceptions of e-government

Introduction

Social media tools, online tools that are designed for interaction between two or more

parties, are pervasive in modern society, from the driver on a cell phone to the student texting in

class, from the Facebook updates at a political event to the Twitter messages that follow a

terrorist attack. Rich and poor, young and old, and everyone in between use social media tools.

Some people jump at the opportunity to utilize these technologies, with their promise of speed,

efficiency, clarity, and the ability to connect more of us across space and time. Others are more

hesitant to adopt social media tools, worried about the Whale and the Reactor (Winner, 1989),

the dangers of technology, the threat that technology will further divide people and eliminate

face-to-face interactions, and electronic activity is a surrender of privacy. Some adopters use

these new tools for purposes of communicating with their friends, others are integrating social

media into the work place, private companies like Amazon and Google are using it to track and

anticipate consumer needs, and still others are seeking to engage stakeholders or clients to

disseminate information, integrate feedback into decision making, and invigorate democratic

processes.

We are facing a new age of technology with the promise of Web 2.0 technologies, and

many of the fears associated with the use of technology in governments are similar to the fears

articulated when we shifted from pen and paper to computer, from filing cabinet to digital

databases, from stopping in to talk to a government official to calling on the phone to eventually

sending an email. Governments adopting technological changes can enable residents to submit

service claims via 311 (a non-emergency hot-line or online service now available in many major

US cities), pay parking tickets online, reserve park facilities online, renew a driver’s license

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online, and more. While there are some uniform changes that are occurring with technology

adoption, technology adopters are embedded in different social and work contexts in which

technology use is explored and adapted. And while there are always challenges when shifting to

new technologies, Web 2.0 is somewhat different in that it enables a significant change in the

potential interactivity schemas with which people work.

The promises of new technologies including social media are well-recognized -

increasing cost effectiveness of services, improving service delivery, and increasing participation

of external groups (Mergel 2010). Nevertheless there are potential limitations of new media, for

example distracting researchers from work, threatening privacy, raising expectations beyond

what is possible, or increasing management complexity (Author Cite). Social media comes with

additional challenges including managing interactions, privacy, security, data management,

accessibility and inclusion, and general governance issues (Bertot, Jaeger, & Hansen 2012). The

interactive nature of social media, and that it often takes place on third party platforms, increases

the challenges facing the appropriate use and management of these technologies. Social media

comprises a set of new technologies—including Twitter and Facebook, but others as well — that

enable richer data exchange in highly decentralized, dynamic, and loosely structured, versatile

virtual environments (Parameswaran & Whinston, 2007). Social media technology is expected to

generate ‘‘cultures of participation’’ marked by collaborative production in ways that enhance

participation, learning, and knowledge production (Fischer, 2009; Fischer & Ostwald, 2002;

Hagel, Seely Brown, & Davison, 2009). In some cases the use of social media technologies may

align with traditional structural and authority boundaries, in other cases they may challenge

them.

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A good deal of current research in the e-government and information and

communications technology (ICT) literatures has focused on how many technologies

governments are using, the adoption of website and intranets, the prevalence of Facebook and

Twitter accounts and how those accounts are being used, and the prevalence of e-services and if

those services are reducing costs and improving service delivery. While the prevalence of ICTs

is an important component of understanding their use, it tells us little about how these

technologies are changing the ways in which local government officials are working and how

local government managers perceive the outcomes of these technologies. This research is

interested in understanding what social media and interactive technologies local governments are

using, how governments and managers are using those technologies, and how managers perceive

the outcomes of those technology-task couplings. Specifically, are managers using ICTs and

social media to improve internal work efficiencies? Are they using these technologies to enhance

participation and communication with external actors? We examine the extent to which local

U.S. governments are coupling social media technology with two types of participative tasks:

collaborative work inside the organization and participative interaction with external

stakeholders. We also explore how these different types of technology-task couples are

associated with manager perceptions of the positive and negative outcomes of ICTs.

We take advantage of survey data examining the use of technology in five departments –

community development, finance, police, mayor’s office and parks and recreation – in municipal

governments that range in population from 25,000 to 250,000. The survey asked a set of

questions where respondents identified the types of social media technologies that they use and

then how they use each technology. We then match these responses on technology type and

technology use to crease “technology-task couples”. We then investigate how these technology-

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task couples are related to perceived outcomes, while controlling for organizational context and

environment. Findings show that social media and their use for specific tasks have very limited

impact on either positive or negative perceived outcomes. These non-findings may demonstrate

that the implementation cost of the technologies outweighs the benefits they realize; that the

technology-task application substitutes for traditional approaches to the same task, but is

unrelated to perceptions of the effectiveness of those technologies; or that these technologies are

relatively new to local governments and efforts to effectively utilize them are in their infancy.

Literature and Hypotheses

Socio-technical systems theory recognizes that the development, adoption, adaptation of

technology by organizations happens within a social context. The theory notes that it is

impossible to consider technology without considering the human dimension; that the technical

system and the social system are fundamentally intertwined (Kling & Scacchi 1982; Trist &

Bamforth 1951; Bostrom & Heinen 1977). The social system is concerned with the attributes of

people including skills, values, and attitudes, while the technical system considers the tasks,

technologies, and processes that manipulate inputs to form outputs (Bostrom & Heinen 1977).

Although this prior work is well-known, most studies have either primarily considered the

technical dimensions of social media or they have considered the use of the technology to be a

discrete phenomenon, divorced from the various ways in which organizations may use

technology (Kaplan and Haenlein 2010; Kietzmann et al. 2011; Kietzmann et al. 2012). But we

contend that social media technology is malleable and government managers and employees

make decisions about how they prefer to employ it for work purposes. There is a human-

technology interface that needs to be better integrated into our understanding of e-government.

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Social media technologies are primarily defined by their interactive nature (Bertot et al.

2012). Whether we are considering web-based interactive technologies such as blogs and wikis,

tools for sharing information and files like YouTube and Flickr, interactive communication tools

such as text messaging, Googletalk, or WhatsApp, or social networking tools like Facebook,

these tools are interactive (Hansen et al 2011) and share the characteristic of being designed to

enable users to communicate with one another or the broader community (Porter 2008). They are

“social” in that they occur in a social environment and everyday users interact with one another

to develop content (Porter 2008). Unlike previous technologies adopted by governments, social

media bring the added challenge of managing, responding to, and working with the interactive

and user-generated nature of the tools (Bertot et al 2012).

Government agencies have been consistently challenged by the fact that they are

designed as institutions to effectively address categorically defined issues, but are not well

designed to address cross-cutting, complex problems that require multiple sources of expertise

and input (Provan & Kenis 2008). Bureaus are often siloed in ways that constrain collaboration

across offices. Additionally, observers have often lamented that the bureaucracy is insufficiently

democratic; citizens and stakeholder organizations that make up civil society are perceived to

have inadequate access to decision making and are ineffectively informed about the inner

workings, decisions, and decision outcomes of government (Dunleavy et al., 2006; Evans & Yen

2006). This general nature of government makes it ill-equipped to respond to the changing nature

of communication and interaction that social media tools bring.

On the other hand, social media and other interactive technologies are often viewed as

means by which actors can span institutional boundaries and engage people with different

experiences, perspectives, and professions in ways that address modern problems. With social

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media technologies at their disposal, public managers and employees have the opportunity to

interact with citizens and external stakeholders or work collaboratively on internal government

projects, in new ways. Research indicates that there are a number of opportunities for social

media to be used in government including creating records and disseminating information and

communicating with the public and increasingly governments are acknowledging the ways that

social media technologies can enable them to reach more individuals, disseminate information,

engage the public, and increase participatory decision-making (Hanson 2008; Jaeger et al 2010;

Snyder 2009; Wyld 2008). Of course, there are challenges with using social medial technologies

to engage the public, including a lack of access for people with limited technological means

(Bertot et al 2010l Jaeger et al 2009).

There is a push for governments to adopt more social media tools, with the promise of

increasing efficiency, participation, and transparency. In some cases, this push is from private

actors (e.g. Google America), in other cases from citizens who want more data about what

government is doing and a more interactive experience with their government. There are

increasing calls for the use of social media to address national and local priorities (Pirolli et al.

2010). Bertot and colleagues (2010) contend that social media tools can enable increased

democratic participation and engagement, co-production (governments and public working

together to improve service delivery and quality), and crowdsourcing solutions to public

problems. But there is less discussion of the real or potential negative outcomes of these

technologies. Additionally, while the use of social media is increasing at the federal level (Bertot

et al 2010; Bertot et al. 2012), there has been little investigation of social media tools at the

municipal level, both what social media tools managers are using and how they are using them.

Thus, our first research question is what social media technologies are being used by municipal

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departments/managers? Second, how are managers/departments coupling technologies with

tasks? Specifically, are municipal managers/departments using social media technologies for

internal work collaborations, to facilitate participation with external stakeholders, or both?

Our second research interest is how using these social media technologies for particular

tasks (technology-task couplings) are or are not related to perceived outcomes of the

technologies. While there is a great deal of rhetoric about the ways in which social media can

help to improve government efficiencies, effectiveness, and communication (Hoover 2012; Finn

2014), we know little about variation among social media tools, or how some tools might be

better suited for some work activities and not others. Moreover, we do not know how the use of

social media tools shapes municipal managers perceptions of technology outcomes. As

previously noted, it is not clear that public managers perceive new technologies as improving

government outcomes (AUTHOR CITE). Simply employing a new technology does not

necessarily lead to a ‘good’ outcome. In fact, technology use could result in negative outcomes.

It is possible that social media technologies make it easier for government to communicate with

citizens and residents, enable agencies to share information and deliver services more effectively

than ever before, and provide services that are accessible to all citizens. Some argue that social

media will enable the public to better communicate and interact with government, others hope

that it will make government transparent, while others envision a more open, efficient

government system (Bertot et al. 2010; Bertot et al. 2012; Mergel 2010, 2011).

While there is much promise from technology, there remain challenges and threats,

including citizens’ concerns about privacy and security and government managers’ concerns

about increasing workloads. Social media use in government requires management. And while

communicating with the public can be faster through social media, when all government

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employees are using social media, an organization might have trouble managing communications

or ensuring that all communications are truthful, consistent, and accurate. For example, one

manager in our study notes “The anonymous blogs and forums have a detrimental effect on local

government and generally discourage local governments from getting into social networking and

other forms of web based communication. There really is no incentive to make more [social

media] available.” Another respondent writes that, “Utilizing social media to increase and

improve our city's meaningful interaction with the public is challenging when also needing to

comply with state laws regarding public access and records.” And still others note that adopting

social media can be costly, requiring technical and financial resources, and that these are new

tasks for many organizations. For example, one manager reports, “Social media networks are

becoming an increasingly important tool to communicate with and market to our users. This is

uncharted territory for a public agency.”

While there is research investigating public demands for social media and public

perceptions of technology use in government, there is little research focusing on the managerial

perspective. This research is primarily concerned with social media use from the perspective of

municipal government managers. How do government managers perceive technology adoption?

How do they use social media in their workplaces? What are the positive and negative outcomes

of these uses? We expect that using social media tools, and using social media for particular

tasks (technology-task coupling) will be significantly related to managers’ perceptions of

technology outcomes.

Hypothesis 1: Social media use will be significantly related to perceptions of e-government outcomes. Specifically, we expect that when social media tools are used for work

collaborations, managers will report increased positive perceptions of the outcomes of

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social media tools. The logic here being that these technologies will increase work

efficiencies and communications to improve productivity.

Hypotheses 1.a: Technology-task coupling for work coordination activities will be positively related to perceptions of e-government outcomes.

In contrast, we expect that when social media tools are used for interacting with

the public, there will be increased negative perceptions of technology outcomes.

Hypothesis 1.b: Technology-task coupling to facilitate participation with the public will be negatively related to perceptions e-government outcomes.

Data and Models

We use data from a 2012 national survey of local government managers. The survey was

administered to 2500 managers in 500 randomly selected local governments with citizen

populations ranging from 25,000 to 250,000. The breakdown of cities by population is highly

skewed to smaller cities (50%), with only 16% of cities having a population of 100,000-250,000.

The sample included a census of the larger communities (100,000-250,000) and a proportional

sample for smaller cities (25,000-100,000).1 The benefit of this design is that it captures both

small and medium sized cities in the US, whereas much of the research on technology in

government focuses on large municipalities alone (one exception is Brudney and Seldon 1995).

The final dataset is weighted to account for the proportional sample.

For each city, we surveyed five lead managers from the following departments: general

city management, community development, finance, police, and parks and recreation. After

removing bad addresses and individuals who were no longer working in the position the sample

was reduced to 2,428. The final response rate was 34.8%, or 845 respondents, as calculated by

the American Association for Public Opinion Research response rate calculator2. Those 845

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respondents came from 429 cities from around the U.S.3 Thus the unit of analysis is the

individual.

Dependent variables. Two dependent variables capture perceptions of positive and

negative outcomes of information and communication technologies. We asked respondents to

indicate the extent to which electronic information and communication technologies lead to 15

possible outcomes (see Table 1).

[Insert Table 1 about here]

Positive Outcomes is the average of responses from 10 items that indicated positive

outcomes. The Cronbach’s alpha for Positive Outcomes is .874. Negative Outcomes is the

average of the following five items that specified negative outcomes: Increase uncertainty for my

organization; Distort political information and facts; Undermine democratic practices; Reduce

clarity about what citizens want; and Increase conflict with citizens. The Cronbach’s alpha for

Negative Outcomes is .766. While Positive and Negative Outcomes are not exact opposites, they

are slightly correlated at the 0.01 level (2-tailed) = -.178.

Independent variables. We are interested in how local U.S. governments are coupling

social media technology with two types of participative tasks: collaborative work inside the

organization and participative interaction with external stakeholders. We explore these

relationships with three primary independent variables: Social Media, which indicates if the

respondent uses social media, and two technology-task couples: SocialMedia-

InternalCollaboration, and SocialMedia-ExternalParticipation. These items draw from a set

of survey questions that were designed as follows. Respondents were told “For the purposes of

this survey, social media is defined as having the characteristic of being social and interactive in

nature – allowing, but not requiring, two-way information exchange between individuals or

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groups, such as between individual public employees and citizen. Examples of commonly used

social media tools include: blogs, Facebook, Twitter, YouTube, etc.” They were then asked: To

the best of your knowledge: does your organization use social media for any purpose? [Response

categories: Yes, no, don’t know]. This item is the basis for the binary variable, Social Media, to

which 684 individuals indicated “yes” (84.9%) and 122 indicated “no” (14.4%). We also include

dummy variables for each of the social media tools.

For the technology-task couple items, respondents were asked, “Please indicate which of

the following 10 social media tools your organization uses for any purpose: Facebook; Twitter;

YouTube; LinkedIn; GovLoop; Skype; Flickr; Google Talk, Blackberry Messenger, MSN, or

other instant messaging tools; MySpace; and Google Docs”. For each technology identified the

respondent was asked: “For what purposes does your organization use the types of tools that you

named? (1) To enable internal collaboration on work tasks and (2) To enable or facilitate

participation by citizens or external stakeholders”. SocialMedia-InternalCollaboration

indicates if the respondent uses any of the 10 technologies “To enable internal collaboration on

work tasks.” SocialMedia-ExternalParticipation is coded one if the respondent uses any of the

10 social media technologies “To enable or facilitate participation by citizens or external

stakeholders”. Among the 684 who use social media, 258 (37.8%) use it to facilitate participation

with external stakeholders, 57 (8.4%) use social media for internal collaboration, and 193

(28.3%) use social media for both purposes. SocialMedia-InternalCollaboration and

SocialMedia-ExternalParticipation are not mutually exclusive and are positively correlated

(Pearson Correlation .309**, Sig. (2-tailed .000)).

We include control variables for organizational culture and technology capacity and

individual, department, and city characteristics. Four variables capture the organizational culture

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and the respondent’s perceptions of the organization. Participation is a measure of the

frequency with which external actors participate in organization’s decision-making and policy

making. Respondents were asked: Over the last year, how often did the following citizens and

stakeholder groups participate in your organization's decision and policy making? (1=don’t

know, 2=never, 3=rarely, 4=sometimes, 5=often, 6=very often): Individual citizens,

Neighborhood associations, Federal government agencies/employees/officials, News media,

Interest groups, Urban civic groups, Religious groups, Consultants or paid experts, Professional

associations, Internal department staff, Other city departments, Mayor’s office, Governor’s

office, and State legislators. Participation is the average of responses to the 14 items.

Job Satisfaction indicates the respondent’s satisfaction with the job and is the average of

two questionnaire items: (1) All in all I am satisfied with my job and (2) I sometimes feel my job

is meaningless (R). The Cronbach’s alpha is .724. Routineness is a scale that captures the level

of routines in the work environment. It is the average of responses to two items: (1) One thing

people like around here is the variety of work (Reversed coded) and (2) Most jobs have

something new happening every day (Reversed coded) (Response categories 5-point Likert scale

of agreement). The Cronbach’s alpha for Routineness is .607. Centralization is an average of

responses to the following three questionnaire items: (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; and (3) Even small matters have to be

referred to someone higher up for a final answer. The Cronbach's alpha for Centralization is

.750.

We include five variables as measures of the organization’s technology capacity. Percent

Use Computer indicates responses to the question: Approximately what proportion of the

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employees in your department use a computer for their work? Percent Use Internet is responses

to the questionnaire item: Approximately what proportion of the employees in your department

use the Internet for their work? Intranet is a binary variable coded “1” if the respondent

responded yes to the following question: Does your local government or department have an

Intranet (a web server accessible only to local government employees)? E-Services is a count

variable ranging from 0 to 4 which indicates if the department offers the following e-services: (1)

Online payment for services including fees and fines; (2) Online delivery of local government

records or department information to citizens who request information; (3) Online requests for

services that your department is responsible for delivering; and (4) Online completion and

submission of job applications. Good Website is a scale that captures the respondent’s

perceptions about the quality of the city’s website. Good Website is the average of responses

from the following five questionnaire items: (1) The city’s website is easy to navigate; (2) The

information on the city’s website is up-to-date; (3) The city website is poorly managed (Reverse

coded); (4) Residents and citizens tell me our website is very useful; and (5) Citizens and

residents complain about our website (Reverse coded). Response categories are 1=strongly

disagree, 2=disagree, 3=neither agree nor disagree, 4=agree, and 5=strongly agree. The

Cronbach’s Alpha is .833.

We control for the following individual characteristics: age, job tenure, gender, and

previous work experience. AgeTenure is an interaction variable created from a continuous

variable indicating age (range 23 to 77) and tenure in the current position (range 1 to 45).

Female is coded 2 if female and 1 if male. Previous work experience is captured by two binary

variables, Private work experience and NPO work experience, which are coded 1 if the

respondent had previous work experience in the private sector and 0 if not, and 1 if the

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respondent had previous work experience in the nonprofit sector and 0 if not, respectively.

Labor union is a binary variable coded 1 if the respondent is the member of a labor union.

We also control for department and city characteristics, since previous research indicates

that technology adoption in municipal governments is related to city size and other

characteristics (Moon 2002). OrgSize is a continuous variable indicating the about how many

full-time employees work in the respondent’s department. Populationln is the natural log of the

city’s population. Five binary variables indicate the respondent’s department of employment:

Mayor’s Office, Community Development, Finance, Parks & Recreation, and Police. The

descriptive statistics for all study variables and variable scales are listed in Appendix A and B,

respectively.

Analysis and Results

In this study, 84.9% of respondents report using social media in the workplace, indicating

widespread overall use of these technologies in municipal governments. There is significant

variation of social media use by department of employment (Pearson Chi-Square, 18.197,

Asymp. Sig. 2-sided .001). The least frequent use of social media is among respondents working

in departments of community development (78%) as compared to 79.7% of those working in

finance departments, 85.3% of respondents in police departments, 88.5% of those working

departments of parks and recreation, and 93% of those working in mayor’s offices.

Table 2 reports the types of technologies used by respondent organizations. The most

common technology used in municipal governments is Facebook (91%). Nearly three-quarters of

respondents report using Twitter. The least commonly used technologies are GovLoop (5%) and

MySpace (8%). While many of the respondents report using social media, these data tell us little

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about how managers use those technologies, or if they use them for internal work coordination or

interactions with citizens and external stakeholders.

The right side columns of Table 2 show the technology-task coupling for each type of

social media technology. For example, the columns labeled “used to enable internal collaboration

on work tasks” show the number of individuals who report using each technology for work

collaboration and that count as a percentage of total users of the specific technology. Three-

quarters of respondents who use email report using it for internal collaboration on work tasks.

More than half of users report that they use instant messaging tools such as Google Talk,

Blackberry Messenger, or MSN (54%) and Google Docs (56%) to enable internal collaboration

on work tasks. Interestingly, although GovLoop is not widely used in the full sample (5%),

among those who do use GovLoop, 37% report using it for collaboration on work tasks. And

while a large percentage of respondents report using Twitter (71%) and YouTube (50%), only

10% of those users report using those tools for collaboration on work tasks.

The far right columns of Table 2 show the percent of technology users that use each

technology to enable or facilitate participation by citizens or external stakeholders. Not

surprisingly, Facebook (67%) and Twitter (58%) are the most frequently used technologies to

enable or facilitate participation by citizens or external stakeholders. Around one third of users of

Linked In, MySpace, and Flickr report using those technologies to enable or facilitate

participation by citizens or external stakeholders. Thus we see that while 84.9% of respondents

report using social media in the workplace, they are using different technologies for particular

purposes.

[Insert Table 2 about here]

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Having noted the distribution of technology use among respondents, and that technology

use is coupled with internal collaboration on work tasks and participation by citizens or external

stakeholders, we now look at how these technology-task couples are related to perceptions of the

positive and negative outcomes of e-government activities. We assess these perceptions in

models that separately predict perceptions of positive outcomes and perceptions of negative

outcomes, since it is possible for respondents to hold both perceptions simultaneously. Just as job

dissatisfaction is not the opposite of job satisfaction (Herzberg 1987), we contend that negative

and positive outcomes of government technology use are mutually exclusive but not necessarily

opposites. The opposite of positive outcomes is no outcomes; the opposite of negative outcomes

is no outcomes. One might believe that there are positive and negative outcomes from social

media use, or simply perceive positive or negative outcomes alone. Similarly, we expect that the

predictors of positive outcomes and negative outcomes may not be the same. Thus, we ran a

series of OLS regression models to test the relationships between social media technology use,

technology-task couplings, and the perceptions of positive outcomes and negative e-government

outcomes. First we ran a models investigating whether the use of social media is related to

perceived positive and negative outcomes (table 3). Second, we ran models that focus on each of

the two technology-task coupling independent variables of interest: Social Media-Internal

Collaboration, and Social Media-External Participation (table 4). The technology-task coupling

models presented in table 4 are limited to respondents who indicated that they use social media

(n=684).

[Insert Table 3 about here]

In our initial models investigating social media use and positive and negative perceptions

of e-government outcomes, we operationalized social media use as a dummy variable indicating

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social media use (=1), or not (=0) (see Table 3). The results in Table 3 indicate that overall social

media use is not significantly related to perceptions of e-government outcomes. We then reran

the models with each of the social media technologies specified (Table 4).

[Insert Table 4 about here]

Table 4 indicates that use of certain types of social media is significantly related to

reporting positive perceptions of the outcomes of ICTs and e-government initiatives in local

government. Specifically, respondents who report using Skype and GovLoop report increased

positive perceptions of e-government outcomes. Skype enables two-way interactions via phone

calls, instant messaging, and video conferencing. GovLoop is an online community, developed

by and for the government community, where over 100,000 public sector professionals can

connect to collaborate, solve problems, learn from one another, and share knowledge. GovLoop

users also report a significant decrease in negative perceptions. GovLoop use, though not wide

spread, is significantly related to both increased positive perceptions and decreased negative

perceptions. The results also show that respondents who report using YouTube and MySpace at

work report increased negative outcomes.

The results in Table 4 also indicate that organizational factors, including culture and

technology capacity, also differently predict perceptions of positive outcomes and negative

outcomes. Job satisfaction is positively related to reporting positive e-government outcomes. Job

satisfaction is also related to decreases in negative outcomes. Respondents who report more

frequent interactions with the public also report more positive perceptions, as do those who

report having a good department website. Specifically, respondents working in organizations that

have good websites report more positive perceptions of e-government. Thus, positive perceptions

of e-government are related to the use of some social media, job satisfaction, interacting with the

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public, and reporting positive perceptions of the department website (which may be an indicator

of department technology capacity).

In comparison, perceptions that e-government results in negative outcomes are related to

organization centralization, private sector work experience, and population. Respondents

working in more centralized organizations report more negative outcomes from e-government,

possibly because centralized organizations make decisions about e-government initiatives

without engaging individual managers in technology adoption. Respondents who have private

sector work experience report lower negative views of e-government outcomes, as do

respondents working in larger cities.

Table 5 shows the results from the two models predicting the relationship between

technology-task coupling and e-government outcomes. Among those who use social media, we

find that the purpose of the technology use is not related to positive perceptions about e-

government. In fact, among social media users, we see that job satisfaction, frequency of

participation with the public, and e-services are positive predictors of perceiving e-government

outcomes as being good for the community and for government. But technology-task coupling,

the purpose for which local government managements use social media is not related to positive

perceptions of e-government.

[Insert Table 5 about here]

We do find that the technology-task coupling of, SocialMedia-ExternalParticipation, is

significantly related to reporting negative e-government outcomes. Municipal managers who

report using social media to enable or facilitate participation by citizens or external stakeholders

report fewer negative outcomes from e-government. In contrast, those who are not using social

media for participatory purposes report increased negative outcomes from e-government. This

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finding indicates that social media use, especially when used to connect with the public, might

help to reduce negative perceptions of the threats associated with these technologies. Though it

may also be true that those who have negative perceptions of e-government initiatives choose not

to adopt these technologies, while those who adopt social media technologies to engage the

public are simply more inclined to perceive positive outcomes of these technologies. On the

other hand, it might be that managers using social media to interact with the public are simply

less aware of the threats of social media use. Of course, we may see changes in these views over

time, as government managers develop mechanisms for using social media while addressing the

possible threats and negative outcomes of their use, and of course, as more managers become

familiar with social media technologies which are increasingly pervasive in the U.S.

Having a good website is a consistent predictor of both positive and negative perceptions

of e-government outcomes. Respondents who report that their department has a good website,

e.g. technology capacity, report increased positive perceptions and decreased negative

perceptions of e-government outcomes.

Respondents who work in finance departments report significantly lower negative

perceptions of e-government as compared to those working in police departments. This might be

explained by the fact that significantly more respondents in police departments (85.3%) use

social media as compared to those in finance departments (79.7%) (Pearson Chi-Square 18.197,

Asymp sig. (2-sided) .001). It is possible that because police departments use these technologies

more frequently they are more aware of the potential negative outcomes of their use – or have

experienced those negative outcomes first hand. Additionally, the report of negative outcomes

might be because of the type of information and communications that social media can enable

for police departments as compared to finance departments. One can certainly imagine a plethora

22    

of possible uses of interactive technologies for police departments, from text message public

safety warnings, to interactive community discussions online, or two-way communications about

crime. In comparison, the use of two-way communications and social media for finance

departments are more likely to include input on budget decisions or question and answer sessions

with regards to public data. The threats associated with the former might exceed those of the

latter.

Before turning to a discussion of our findings, it is important to note the limitations of

this research. First, we are limited by the data, which are drawn from a single cross-sectional

study. Second, the survey was administered to high-level managers, so we cannot say that these

results reflect the perceptions and experiences of others in the organizations. Additionally, it is

possible that these managers do not have an accurate understanding of technology use in their

organizations. While this might be a weakness of the study, it is also important to note that if

high-level managers are unaware of the technology use in the organization, it is hard to know the

effectiveness (or widespread use) of such technology. In our view, effective technology will be

used seamlessly in an organization and not by a single Chief Information Officer or information

technology specialist. And finally, the measures in this study are limited in that they capture

respondent perceptions and in some cases are crude approximations for technology use. Despite

these data limitations, we believe this research remains important to our understanding of social

media use in local governments.

Discussion

Our findings point to some important issues. First, we see that social media is being used

in local governments in a variety of ways and for a variety of purposes (Hypotheses 1). As noted

23    

in Table 1, the most widely used tools, Facebook and Twitter, are most commonly used for

facilitating participation by citizens and external stakeholders. Meanwhile social tools such as

instant messaging programs, GovLoop, and GoogleDocs are more widely used for internal

collaboration on work tasks. These findings reinforce the importance of understanding that social

media are not just used for “social” purposes or necessarily in citizen-oriented ways (e.g. for

participatory purposes). In fact, they may play important roles in internal government work

coordination and task completion – combatting the presumption that social media is not really

used by government and is just a Facebook or Twitter icon posted on a webpage. It will be

important that e-government researchers begin to differentiate between social media technologies

that serve different purposes for managers, other government agencies and workers, clients,

citizens, and other stakeholders. Additionally, we find that there remains ample opportunity to

increase the use of social media technologies for internal work collaborations. For example,

around half of respondents using instant messaging tools and GoogleDocs use them for internal

collaboration on work tasks, how might the remainder of these users better utilize these tools in

the work place? And what about the hundred or more respondents who do not use social media

tools at work?

Second, our results indicate that, as of 2012, social media use in municipal governments

is excessively hyped. A great deal of energy has gone into touting the promise of these tools, but

our research finds little effect on perceived outcomes for managers at the local level (although

there are limitations with our measures and analysis). While we find that the use of social media

for internal work and external participation is not significantly related to reporting positive

outcomes from e-government technologies, we note that it is too early to say that social media

cannot have these types of effects. Social media remains relatively new in the public sector work

24    

place, and efforts to use social media to its full advantage on internal work tasks and external

engagement are in their infancy. We can easily imagine public sector workers in the near future

having high-speed intranet systems that better enable instant messaging to coordinate activities

or electronic bulletin boards for coordinating meetings or collaborating on policy documents and

initiatives. There needs to be much better research in this area to understand how technologies

are being employed, by whom and to what advantage…and disadvantage.

Finally, our findings could indicate hidden costs and benefits from social media

technologies. For example, positive and negative outcomes can occur at the same time, social

media could make it easier to communicate with the public, but at the same time make it more

complicated to manage the communications or weigh and align the interests of multiple

stakeholders. Positive and negative outcomes might also be trade-offs. With increased speed and

efficiency (a positive), there is less face-to-face interaction (a negative). Where there is less

travel time, there might be more work time. Social media use may be employed in a manner that

washes out the promised advantages – resulting in more time-consuming work, instead of

efficiencies. At the same time, social media may be costly and time consuming to adopt, but

once the start-up costs are complete, there may be exponential benefits reaped. With social media

technology use is just beginning in municipal governments, it seems many are still in the high

cost stage – wondering if the high cost will result in efficiencies and working to balance the

demands of adopting new technologies while still providing face-to-face services. Future

research should look at the complex relationships of positive and negative outcomes from social

media technologies and their effects on managerial work life, service delivery, and interactions

with the public. We expect that just as these technologies move quickly, so too will managers’

perceptions of their costs and benefits.

25    

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28    

Tables Table 1: Questionnaire items for outcomes of Information and Communication Technologies

In your opinion, to what extent do electronic information and communication technologies

lead to the following outcomes? Positive Outcomes

Improve governmental decision-making Lead to better policies Revitalize public debate Improve information dissemination to external stakeholders and citizens Increase opportunity to interact and collaborate with other government officials Increase access to government services Enable feedback on service quality Increase certainty about the importance of the work I do Enhance citizen trust of government Improve efficiency and lower costs of the department

Negative Outcomes Increased uncertainty for my organization Distort political information and facts Undermine democratic practices Reduced clarity about what citizens want Increase conflict with citizens

Response categories were 1=To a very small extent, 2=To a small extent, 3=Somewhat, 4=To a great extent, and 5=To a very great extent

29    

Table 2: Types of technologies used by organizations and purposes of technology use

Use by the organization

Used to enable internal

collaboration on work tasks

Used to enable or facilitate

participation by citizens or

external stakeholders

Count

Valid % Count

% of

users Count

% of

users

Facebook 616 91% 75 12% 410 67% Twitter 466 71% 45 10% 270 58% YouTube 308 50% 32 10% 118 38% LinkedIn 255 41% 46 18% 77 30% Gov Loop 31 5% 11 37% 6 18% Skype 131 22% 39 30% 35 26% Flickr 63 11% 5 8% 23 37% Google Talk, Blackberry Messenger, MSN, or other instant messaging tools 268 44% 145 54% 69 26% MySpace 49 8% 9 18% 15 31% Google Docs 98 17% 54 56% 21 22% Note: Among all respondents to study (n=845)

30    

Table 3. Social Media Use and Positive and Negative Perceptions of ICT Outcomes, full sample

Positive Negative

B Std.

Error Sig B Std.

Error Sig (Constant) 1.110 .631

3.548 .731

Social Media -.073 .080

.093 .092 Participation .210 .046 *** .085 .054 Job Satisfaction .165 .040 *** -.084 .046 Routineness -.056 .045

-.034 .052

Centralization -.037 .043

.120 .049 * Percent Use Computer .001 .002

.001 .002

Percent Use Internet .000 .001

-.001 .001 Intranet .000 .000

.000 .000

E-Services .048 .022 * .026 .026 Good Website .129 .042 ** -.076 .048 Female .122 .073

-.014 .084

AgeTenure .000 .000

.000 .000 * Private work experience .076 .062

-.140 .072

NPO work experience .011 .063

-.083 .073 Labor union member .150 .109

-.040 .127

OrgSize .000 .000

.000 .000 Populationln .032 .051

-.108 .059

Mayor's Office -.030 .097

-.059 .112 Community Development -.138 .087

-.070 .101

Finance Department -.115 .103

-.279 .119 * Parks & Recreation -.050 .098

-.086 .114

R .422

.277 R Square .178

.076

Adjusted R Square .148

.042 *p < .05, **p < .01, ***p < .001

31    

Table 4. Social media use and positive and negative perceptions of e-government

outcomes

Positive Negative

B SE Sig. B SE Sig. Constant 1.315 0.634 3.578 0.733

Facebook 0.039 0.077

0.025 0.089

Twitter 0.080 0.065

-0.062 0.075

YouTube 0.023 0.063

0.232 0.073 ***

LinkedIn -0.093 0.061

-0.032 0.071

GovLoop 0.280 0.138 *

-0.344 0.160 *

Skype 0.194 0.079 * -

0.032 0.091

Flikr 0.014 0.106

-0.041 0.122

GoogleTalk -0.105 0.063

0.043 0.072 MySpace -0.166 0.118

0.309 0.136 *

GoogleDocs 0.076 0.088

-0.084 0.101

Participation 0.189 0.047 *** 0.097 0.054

Job Satisfaction 0.168 0.040 *** -

0.090 0.046 *

Routineness -0.048 0.045

-0.016 0.052

Centralization -0.029 0.043

0.119 0.049 * Percent Use Computer 0.000 0.002

0.001 0.002

Percent Use Internet 0.000 0.001

-0.002 0.001

Intranet 0.000 0.000

0.000 0.000 E-Services 0.043 0.023

0.024 0.026

Good Website 0.138 0.041 ***

-0.062 0.048

Female 0.129 0.073

-0.028 0.084

AgeTenure 0.000 0.000

0.000 0.000

Private work exp. 0.068 0.062

-0.142 0.072 *

NPO work experience -0.002 0.063

-0.075 0.072

Labor union member 0.159 0.110

0.028 0.127 OrgSize 0.000 0.000

0.000 0.000

Populationln 0.012 0.052

-0.123 0.060 *

32    

Mayor's Office -0.110 0.099

-0.007 0.115

Community Dvlp -0.148 0.088

0.004 0.102

Finance Department -0.160 0.105

-0.220 0.121

Parks & Recreation -0.106 0.099

-0.029 0.115

R 0.454

0.332 R Square 0.206

0.110

Adjusted R Square 0.164

0.062 *p < .05, **p < .01, ***p < .001

33    

Table 5. Technology-Task Coupling predicting Positive and Negative Perceptions e-government outcomes, social media users (n=684)

Positive Negative

B Std.

Error Sig B Std.

Error Sig (Constant) .953 .669

3.736 .761

SocialMedia-InternalCollaboration .050 .062

.100 .071

SocialMedia-ExternalParticipation .112 .065

-.186 .074 *

Participation .219 .052 *** .111 .059 Job Satisfaction .143 .043 *** -.069 .049 Routineness -.060 .050

-.023 .056

Centralization -.062 .046

.094 .052 Percent Use Computer .003 .002

-.002 .003

Percent Use Internet .000 .001

-.001 .001 Intranet .000 .000

.000 .000

E-Services .040 .025

.009 .029 Good Website .151 .045 *** -.113 .051 *

Female .128 .078

.055 .088 AgeTenure .000 .000

.000 .000

Private work experience .107 .067

-.137 .076 NPO work experience -.021 .069

-.112 .079

Labor union member .284 .128 * -.226 .146 OrgSize .000 .000

.000 .000

Populationln .014 .054

-.094 .062 Mayor's Office .003 .104

-.024 .118

Community Development -.142 .098

-.137 .111 Finance Department -.080 .112

-.252 .127 *

Parks & Recreation .058 .106

-.078 .122 R .463 .306

R Square .214

.093 Adjusted R Square .178

.052

*p < .05, **p < .01, ***p < .001

34    

Appendix A: Descriptive Statistics for Study Variables Mean Std Dev Min Max Valid Missing Positive Outcomes of E-government 3.44 0.69 1 5 733 112 Negative Outcomes of E-government 2.11 0.74 1 5 731 114 Social Media 0.87 0.34 0 1 803 42 SocialMedia-InternalCollaboration 0.31 0.46 0 1 845 0 SocialMedia-ExternalParticipation 0.55 0.50 0 1 845 0 Participation 3.95 0.67 1 6 808 37 Job Satisfaction 4.23 0.70 1 5 817 28 Routineness 2.39 0.68 1 5 696 149 Centralization 2.38 0.72 1 5 697 148 Percent Use Computer 90.67 18.57 5 100 694 151 Percent Use Internet 73.69 30.40 0 100 686 159 Intranet 39.01 191.45 0 999 733 112 E-Services 2.48 1.31 0 4 709 136 Good Website 3.56 0.70 1 5 718 127

AgeTenure 369.6

0 380.96 0 3015 608 237 Female 1.19 0.40 1 2 832 13 Private work experience 0.72 0.45 0 1 694 151 NPO work experience 0.26 0.44 0 1 694 151 Labor union member 0.09 0.28 0 1 695 150

OrgSize 172.1

0 1001.64 0 18400 689 156 Populationln 11.14 0.65 10 12 845 0 Police Department 0.24 0.43 0 1 845 0 Mayor's Office 0.17 0.38 0 1 845 0 Community Development 0.22 0.42 0 1 845 0 Finance Department 0.16 0.36 0 1 845 0 Parks & Recreation 0.21 0.41 0 1 845 0

35    

Appendix B: Variable scales Variable Name

Description

Participation

Scale - mean of responses Over the last year, how often did the following citizens and stakeholder groups participate in your organization's decision and policy making? (1=DK, 2=never, 3=rarely, 4=sometimes, 5=often, 6=very often)

Individual citizens Neighborhood associations Federal government agencies/employees/officials News media Interest groups Urban civic groups Religious groups

Consultants or paid experts Professional associations Internal department staff Other city departments Mayor’s office Governor’s office State legislators

Job satisfaction

Scale - mean of responses All in all I am satisfied with my job I sometimes feel my job is meaningless (Reversed coded)

(Response categories: 1=strongly disagree, 2=disagree, 3=neither agree nor disagree, 4=agree, and 5=strongly agree)

Cronbach’s alpha=.724

Routineness

Scale - mean of responses One thing people like around here is the variety of work. (Reversed coded) Most jobs have something new happening every day. (Reversed coded) (Response categories: 5-point Likert scale of agreement)

Cronbach's alpha=.607

Centralization

Scale - mean of responses There can be little action taken here until a supervisor approves a decision. In general, a person who wants to make his own decisions would be quickly discouraged in this organization. Even small matters have to be referred to someone higher up for a final answer. (Response categories 5-point Likert scale of agreement).

Cronbach's alpha=.750

E-Services

Count of responses Online payment for services including fees and fines. Online delivery of local government records or department information to citizens who request information. Online requests for services that your department is responsible for delivering. Online completion and submission of job applications. (Response categories: 1=yes, 0=no)

Good Website

Scale - mean of responses The city’s website is easy to navigate. The information on the city’s website is up-to-date. The city website is poorly managed. (Reverse coded)

36    

Residents and citizens tell me our website is very useful. Citizens and residents complain about our website. (Reverse coded) (Response categories: 5-point Likert scale of agreement.)

The Cronbach’s alpha=.833

37    

Footnotes

                                                                                                               1 The census of cities with a population 100K-250K resulted in 184 cities. For the remaining 316 cities, a

proportional sample with 59% of the sample was drawn from 25K-50K, 28% from 50-75K, and 13% from

cities 75K-100K. Among all respondents, 37.8% are from smaller towns with a population less than 49,999

and 19% are in cities with a population from 50,000 to 74,999.

2  American Association for Public Opinion Research. AAPOR Outcome Rate Calculator. Version 3.1

November, 2010. Accessed Jan 26, 2014 at

http://www.aapor.org/Response_Rates_An_Overview1.htm#.UuXWRRZ6jw4  

3  One respondent from 167 cities, two from 146 cities, three respondents from 83 cities, four respondents from 28 cities, and all five individuals from five cities responded.