models of e-government: are they correct? an empirical assessment

Models of E-Government: Are They Correct? An Empirical AssessmentAuthor(s): David Coursey and Donald F. NorrisSource: Public Administration Review, Vol. 68, No. 3 (May - Jun., 2008), pp. 523-536Published by: Wiley on behalf of the American Society for Public AdministrationStable URL: http://www.jstor.org/stable/25145630 .

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David Coursey

Arizona State University

Donald F. Norris

University of Maryland, Baltimore County

Models of E-Government: Are They Correct?

An Empirical Assessment

Research into e-government is relatively new. Neverthe

less, much contemporary thinking and writing about

e-government is driven by normative models that appeared

less than a decade ago. The authors present empirical

evidence from three surveys of local e-government in the

United States to test whether these models are accurate

or useful for understanding the actual development of

e-government. They find that local e-government is mainly

informational, with a few transactions but virtually no

indication of the high-level functions predicted in the

models. Thus, the models do not accurately describe or

predict the development of e-government, at least among

American local governments. These models, though

intellectually interesting, are

purely speculative, having

been developed without linkage to the literature about

information technology and government. The authors

offer grounded observations about e-government that

will useful to scholars and practitioners alike.

Research into the phenomenon of electronic

government (or e-government) is relatively

new.1 Research articles on this subject?that

is, articles based on more than intellectual speculation

and rumination and instead based on data from some

form of empirical exercise, such as surveys, case stud

ies, focus groups, or analysis of data from large data

sets?began to appear only in 1999 (Norris and

Lloyd 2006). This is not surprising, because the field

of e-government itself is not much more than a dozen

years old at this writing. Official governmental sites

delivering information and services first began appear

ing on the World Wide Web in the mid-1990s.

Not only is e-government research nascent, there is

sparse theory development and testing (Norris and

Lloyd 2006), with the arguable exception of models

predicting individual user adoption, such as the tech

nology acceptance model (Davis 1989), or those from

institutional and policy perspectives (e.g., Fountain

2001). Even so, theoretical explanations of why govern ment

organizations develop and adopt e-government are less mature, and few are

grounded either in actual

e-government research or in the prior literature on the

adoption of information technology in

governmental

organizations, which has developed over the past 30

years. Indeed, Fountain's (2001) work has been criti

cized as ignoring seminal works from that literature

(Grafton 2004; Danziger 2004).

The e-government literature contains five works that

offer explicit theories or models of e-government

relative to its growth and development. Four of these

works were published in 2001, and one was published in 2000, a mere handful of years into the e-government era. Two of these works were

published in scholarly

journals (Layne and Lee 2001; Wescott 2001), one

was part of a report by a well-known consulting group

(Baum and Di Maio 2000), one was part of an interna

tional e-government benchmarking effort undertaken

by the United Nations and the American Society for

Public Administration (Ronaghan 2001), and one was

part of a report written for the IBM Center for the

Business of Government (Hiller and Belanger 2001).

These models are partly descriptive, partly predictive,

and partly normative. It can even be asserted that

some, like that published by the Gartner Group (Baum and Di Maio 2000), may promote e-government

service sales ("more technology is better") rather than

unbiased theory building, with a bent toward prescrip tion over

description. Overall, all purport to describe

what might be considered the "normal" evolution of

e-government from its most basic element (a rudi

mentary governmental presence on the World Wide

Web) to fully developed e-government. Based on

empirical examination, it appears that, for the most

part, the descriptions in these models provide a rea

sonably accurate

portrait of e-government in its early

stages, from initial Web presence to information provi

sion to interactivity. Beyond this, however, the models

become both predictive and normative and their

empirical accuracy declines precipitously.

The models predict that e-government will move

beyond information provision and interactivity to

become fully transactional. They also predict that

New

Perspectives on E-Government

David Coursey is a visiting scholar at

Arizona State University's Decision Theater

(www.decisiontheater.org). He specializes in public management, information

technology, and research methods. Most

of his recent work is in public service

motivation, measurement models and

theory, and e-government. Email: [email protected]

Donald F. Norris is chair and professor in the Department of Public Policy and

director of the Maryland Institute for Policy

Analysis and Research at the University of

Maryland, Baltimore County. He is a special ist in public management, urban affairs, and

the application, uses, and impacts of

information technology (including electronic

government) in public organizations. His

works have been published in a number of

scholarly journals. E-mail: [email protected]

Models of E-Government 523



e-government will fundamentally transform the rela

tionship between governments and citizens. At this

point, nearly all of the models become quite norma

tive when describing a

fully developed e-government,

and they assert what e-government should become.

The models implicitly presume that fully transactional

systems are better and that more citizen interaction

equals improved service.

The models are similar in many respects. They all

predict the linear development or evolution of

e-government from a basic online presence to full

integration, seamlessness, and transformation. They

all suggest or explicitly

state that this development is

progressive (each successive stage of e-government is

better than the previous one) and stepwise (govern ments have to

proceed through each step in a series).

Four of the models are similar in the specific steps that

they predict, whereas the fifth (Layne and Lee 2001) is an outlier in terms of the precise steps, although

not in the direction of the development.

There has now been enough experience and study to

ask whether these models and their predictions and

normative expectations are accurate and, therefore,

useful to scholars and practitioners of e-government, or whether they need revision (or worse, rejection). In

this article, we ask whether the models are accurate;

we present empirical evidence from the actual develop ment of e-government among local governments in

the United States; and we test whether that develop ment is consistent with the predictions of the models.

Finally, we discuss the implications of our

empirical

findings for models of e-government and for the con

tinuing study of e-government.

E-Government Models

Figure 1 shows the steps that the five models predict

for the development or evolution of e-government.

What follows is a brief discussion of each model. As

readers will note, although the models differ somewhat

in their nomenclature, they are

highly similar in pre

dicting the progressive development of e-government

from a basic presence on the Web to results that can

only be considered quite extraordinary?seamlessness,

joined-up government, and transformation.

We begin with Baum and Di Maio's (2000) model

because it was the first one published. Baum and

Di Maio predict that e-government will move from

a Web presence in which governments provide basic

information to a second stage that produces interac

tivity or the ability of citizens to contact governmental

organizations and officials online. This is followed by a transactional stage in which citizens will be able to

conduct business online with governments. The final

stage in this model is called transformation.

For Baum and Di Maio and for other writers,

transformation means that e-government will cause

or permit the relationship between citizens and gov

ernments to fundamentally change

in positive ways,

generally producing much more citizen-centric and

responsive government and thereby increasing citizen

trust in government dramatically. Baum and Di Maio,

however, like nearly all writers on e-government, provide

specifics about the before-and-after conditions of the

transformation and the mechanisms at work to produce

the transformation?that is, the relationship between

citizens and governments today, what it will be like at

the end of e-government, and why.

Hiller and Belanger's (2001) model suggests a slightly different progression than the other models and also

predicts a somewhat different end point. Stages

one

and two in this model are similar to those in most

models: information followed by two-way communi

cation (interactivity). Hiller and Belanger predict that the third stage will be the integration of data and infor

mation within and among governments. Integration is followed by

a transactional stage, and Hiller and

Belanger predict that at its end point, e-government

1 Stepl I Step 2 I Step 3 I Step 4 I Step 5 I Step 6

Layne Catalogue Transaction Vertical Horizontal

and Lee integration integration

(2001)_ Baum Presence Interaction Transaction Transformation

and Di

Maio

(2000)_

Ronaghan Emerging Enhanced Interactive Transactional Seamless

(2001)_presence presence_government_ Hillerand Information Two-way Integration Transaction Participation

Belanger dissemination communication

(2001)_ Wescott E-mail Enable Two-way Exchange of Digital Joined-up

(2001) and interorganizational communication value democracy government internal and public access

network to information

Figure 1 The Models' Steps

524 Public Administration Review May | June 2008



will enable or produce e-participation. In this model,

e-government is clearly expected to evolve to a

higher

plane at which citizens have moved beyond accessing

information and services, interacting with governmental

officials, and transacting business with government. At

this stage, citizens participate electronically in the very

activities of governance.

The models offered by Ronaghan (2001) and Wescott

(2001) argue that the initial presence on the Web of at

least some governments (mainly, third-world nations)

is very primitive and not quite informational. Rather,

this emerging presence represents simply the establish

ment of a Web site with not much substance to it. In

Ronaghan's model, governments at this stage morph to a second stage, which is an enhanced presence in

which governmental information is made available

on an official Web site 24/7. The next two stages in

Ronaghan's model, interactivity and transactional

government, are

quite similar to the stages found

in three of the four other models. The final stage in

Ronaghan's model is seamlessness. This involves both

the horizontal and vertical integration of governmen

tal information and services, and it is a condition that

permits citizens to access such services regardless of

the type or level of government in which the informa

tion or services are located.

Like Ronaghan, Wescott suggests that for some

governments, the initial step in e-government is not

much more than a mere presence on the Web. Succes

sive e-government steps, however, are not unlike those

predicted by the other models?information provi

sion, interactivity, transactions (what Wescott calls

exchange of value), digital democracy (similar to

Hiller and Belanger's participation), and joined-up

government (similar to Ronaghan's seamlessness).

We have chosen to discuss Layne and Lee's (2001) model last because it is somewhat of an outlier com

pared to the other models. Layne and Lee argue that

e-government begins with what they call cataloguing, or the basic provision of mostly static information

online. They predict that e-government will then

move to a transactional stage. Up to this point, their

model is substantially similar to the other models

reviewed here. From this point, however, Layne and

Lee's model diverges from the other models. It pre

dicts that the third stage of e-government will be

vertical integration, which involves upper and lower

levels of government sharing data and information

online. The final step in Layne and Lee's model is

horizontal integration, which means the sharing

of data and information online across departments

within governments.

These models all predict the linear, stepwise, and

progressive development of e-government. Govern

ments begin with a

fairly basic, in some cases even

primitive, Web presence. They pass through predict

able stages of e-government, such as interactivity,

transactions, and integration, and then arrive at an

e-government nirvana. This final step is described

variously as either the seamless delivery of governmental

information and services, e-participation, e-democracy,

governmental transformation, or some combination

of the above. The models do not, however, tell us how

this progression or evolution will occur or how long

it will take to fully unfold. In particular?and this

should be quite troublesome for students of public

organizations?the models do not tell us how govern

ments will overcome the numerous and significant

barriers (e.g., financial, legal, organizational, techno

logical, political), for example, to the integration of

governmental information and services.

Normatively, these models also tell us that more

e-government is better. E-government that is interactive,

transactional, and integrated is better. E-government

should (and will) be used by governments to provide for

interactivity, transactions, and integration. And

e-government should (and will) produce e-participation or

e-democracy and a fundamental transformation in

the relationship between governments and citizens.

As we have previously indicated, we believe that it is

time to examine these models with empirical data to

see whether their predictions have come to pass. We

describe our data and methods for doing so in the

next section of this paper.

Data, Methods, and Research Questions The data for this article come from three nationwide

surveys of local e-government that were conducted

in 2000 and 2002 by the International City/County

Management Association (ICMA) and Public Tech

nology Incorporated and in 2004 by the ICMA. The

ICMA samples are derived from the relative popula

tion distributions of key demographic variables or

stratified on such variables as form of government

and region. Table 1 provides descriptives by various

classifications.

Sample variation is always an issue in multiyear

surveys. Table 1 demonstrates that the samples are

remarkably consistent on key demographics. Another

question is how well the surveys represent the true popu

lation of U.S. local governments. Council-manager

governments are overrepresented and mayor-council

governments are underrepresented by

a few percentages.

But the population sample frequencies are very

similar to the entire United States. Hence, the form

of government difference does not appear to be related

to population response variation. As the e-government

samples do not include county commissions or cities

with populations under 10,000 for two years, the

ICMA data (see table 1 notes) for other full-population values cannot be accurately derived. However, the




Table 1 Representativeness and Response Rates of ICMA Electronic Government Surveys**

Percent of responses

Survey year 2002 Census* 2000 2002 2004

Population group More than 1,000,000 0.8 0.8 0.6 0.7

500,000-1,000,000 1.0 1.1 0.9 1.6

250,000-499,999 3.0 2.7 2.7 2.9

100,000-249,999 8.2 9.6 9.3 10.8

50,000-99,999 13.7 14.3 14.3 15.6

25,000-49,999 22.9 23.7 23.3 23.0

10,000-24,999 48.9 46.0 47.7 44.0

5,000-9,999 1.2 1.4 1.2 1.1

2,500-4,999 0.1 0.5 0.1 0.2

Geographic region Northeast 16.3 18.3 16.6

North-central 27.6 28.8 28.1

South 32.9 31.9 33.2

West 23.3 21.0 22.2

Metropolitan status

Central 19.5 21.0 22.8

Suburban 53.9 54.7 52.5

Independent 26.6 24.4 24.6

Form of government City

Mayor-council 28.4 18.5 21.7 19.2

Council-manager 45.3 56.3 54.2 55.3

Other 5.6 3.7 4.0 3.9

County Council-administrator 9.0 10.6 8.9 9.9

Council-elected executive 11.6 11.1 10.8 11.6

*From ICMA breakdown of U.S. Bureau of the Census 2002 data on local governments (ICMA 2005, xi), including counties regard

less of population and municipal areas with populations of more than 10,000.

**Response rates by year: 2000, 50.2%; 2002, 52.6%; 2004, 42.9%.

relative breakdowns are still quite similar to the popu

lation data (see ICMA 2005, xii-xiii). Overall, the

samples do not display significant variation in key

demographics, which might alter the interpretation of

change. However, there is some imbalance in the form

of government.

The 2000 survey was mailed to all municipalities with

populations greater than 10,000 and all counties with

council-administrator (manager) or council-elected

executive forms of government. The response rate was

50.2 percent. The 2002 and 2004 surveys were mailed

to all municipalities with populations of 2,500 or more

and all counties with council-manager or council

elected executive forms of government. The response

rates to the surveys were 52.6 percent and 42.4 percent

in 2002 and 2004, respectively. In order to provide for

direct comparisons between the surveys, we used data

from all responding counties but only data from

municipalities with populations greater than 10,000 from the 2002 and 2004 surveys. For more details on

the sampling, see the various ICMA Municipal Year

book "organization of data" sections (ICMA 2001,

2003, 2005). Copies of the actual surveys are available

from the ICMA. With a few exceptions, the respon

dents to all three surveys were reasonably representa

tive of U.S. local governments as a whole.

As might be expected, the surveys varied somewhat

in the question sets and instructions. Two differences

are relevant to this study. First, in 2000 and 2002,

respondents were

specifically told not to answer ques

tions if they did not have Web sites. This instruction

was not repeated in 2004. This led to the possibility,

though in only

a few cases, of respondents without

Web sites answering questions in 2004. Ideally, re

sponses from governments without Web sites should

be included, especially regarding barriers to adoption. However, it is not possible to do so given the 2000

and 2002 survey designs. To determine which govern ments did not have Web sites for 2004, we chose to

use the assumption that a survey with no identifica

tion of any Web-provided information or service

meant that the government did not have a Web site.

A second issue is that the 2000 survey asked about

internal versus contracted-out services separately.

Outsourced services were not included in Norris and

Moons (2005) review of the 2000 and 2004 results.

Here, we chose to include the outsourced services

from the 2000 survey to provide

a better comparison

of the 2002 and 2004 results.

All change and barrier items were checkbox responses.

Hence, failure to check a box does not necessarily

indicate "no" but could be missing data. We chose

to presume an unmarked box was missing data if the

respondent did not indicate any items. Certainly, it

is possible that a local government could indicate no

changes or barriers at all, but this is a better assumption




than presuming all unmarked boxes are "no." Hence,

we counted items without a marked checkbox as no

only if the respondent did indicate at least one change or barrier. The effect of this coding schema is to inflate

the previously reported percentages (Norris and

Moon 2005).

Evidence

In the following pages, we ad

dress the extent to which U.S.

local governments have estab

lished official sites on the World

Wide Web through which they deliver information and services,

their adoption of online services,

changes that they report as a result

of e-government, and barriers to

the adoption of e-government

that they report. Next, we ad

dress whether it can be reason

ably inferred from the data that the adoption of e-government is related to the changes reported

and whether, in any event, the changes reported are

consistent with the models of e-government.

Adoption of Web Sites

To begin with, we are interested in knowing how

many local governments have any form of Web

presence (table 2) and whether this figure has changed over time. Clearly, the vast majority (96.2 percent in

2004) have Web sites, up from 83.6 percent in 2000

(almost a 13 percent gain) and 87.7 percent in 2002

(an 8.5 percent increase). Today, a 96.2 percent adop

tion rate means that nearly all local governments of

any size (populations of more than 10,000) are

engaged in some level of e-government.

Online Services

There is a major difference between a simple Web

presence and actually providing real-time transactions

and applications. Here, we can begin

to understand

both Web site sophistication and the extent to which

local e-government is consistent with the predictions

of the e-government models.

All three surveys asked local governments with Web sites to report the information and services that they

provided through their Web sites (table 3). Not all

services were included in every survey. The services

can be roughly divided into nontransactional, nonfi

nancial, and financial transactions. Transactional

applications require some two-way exchange of data

Table 2 Web Site Adoption

2000 2002 2004

Percent N Percent N Percent N

Yes 83^6 V571 877 1,866 962 1,791 No 16.4 308 12.3 262 3.8 71

and storage, at least on the host side. For example, users

complete online job applications, which are

stored in a host database. Under the e-government

models, transactional services would be presumed to

be more advanced or sophisticated. Such online sub

missions are at least more technically

complex to

develop than a nontransac

tional system in which users can only

download a copy of the job application to

complete offline.

For 2004, it is apparent that although Web sites are

commonplace, the deliv

ery of anything but basic information is not. The only services provided by

at

least a majority of local governments are

nontransactional. Overall, nontransac

tional services are the most common,

followed by nonfinancial, and financial

transactions. Few local governments

offer financial transactions (all between 11 percent and 14 percent). There is, however, variation among

other service categories. For example, 35 percent

reported providing requests for services, such as pot

hole repair, but only 3 percent reported providing for voter

registration and 8 percent for business licensing

within nonfinancial transactions.

There are two likely explanations for these variations.

One is that the study did not control for local govern ments for which such services are not germane. For

example, many local governments may not conduct

voter or business registration (e.g., a city defers to a

county, local government defers to the state). Also,

arguably, less common services are more technically

or

managerially complex to develop. Simple requests for

pothole repair or

registering for a Softball league are

relatively uncomplicated compared with business

licensing and voter registration.

In addition to current service levels, there is the issue

of how quickly Web services have spread among local

governments. It should be noted that the differences

reported here between 2000 and 2002 are less than

those provided by Norris and Moon (2005). They do not include outsourced services for 2000, which,

unlike the 2002 and 2004 surveys, were separated

from internal offerings.

For nonfinancial transactions, most services showed

fair gains between 2000 and 2002. However, with the

exception of recreational program registration, there

was little meaningful change between 2002 and 2004.

We also found scant differences in nonfinancial trans

actions between 2002 and 2004, with the possible

exception of downloadable forms (72 percent versus

66 percent). Financial transactions showed the great est relative change between 2002 and 2004, approxi

mately doubling over the two years. However, their

... it is apparent that

although Web sites are

commonplace, the delivery of anything but basic

information is not. The

only services provided by at least a majority of local

governments were

nontransactional.




Table 3 Online Service Adoption

2000 2002 2004


Financial transactions

Tax payments 4.9 57 6.6 115 13.4 220

Utility payments 3.7 43 6.1 105 13.7 224

Fee and fine payments 5.1 59 5.6 98 11.1 183

Nonfinancial transactions

Permit applications 7.0 81 11.4 202 13.1 218

Business licenses and renewals 4.9 56 5.8 101 8.1 133

Government record requests 20.6 237 32.3 577 31.4 524

Recreational program registration 10.4 120 15.8 274 22.6 370

Service requests 24.8 286 33.3 589 35.1 588

Voter registration 4.1 47 2.4 41 3.3 51

Property registration 1.7 20 3.3 45 3.9 61

Nontransactional/informational

Government record delivery ? ? 21.3 372 22.1 363

Download forms for manual ? ? 65.7 1,067 71.8 1,203

completion Communicate with government officials ? ? 76.0 1,276 74.1 1,215

GIS, interactive maps 16.0 184 ? ? 39.2 639

Council agendas and minutes ? ? ? ? 87.4 1,489

Codes and ordinances ? ? ? ? 78.1 1,307

Emailed newsletter to residents ? ? ? ? 32.9 531

Streaming video ? ? ? ? 13.9 221

Employment information, ? ? ? ? 77.7 1,305

applications

absolute percentages remained low showing an overall

low rate of adoption.

Overall, the results indicate that most Web services,

with the exception of some nontransactional and

informational services, have not been adopted by

many American local governments. Perhaps more

disconcerting, there is little evidence of substantially

increased adoption of Web services except among

financial transactions, which are still uncommon. This

suggests that among governments that have embraced

e-government, the use of the Web for real business

purposes is far from a reality. It also suggests that the

development of e-government is not progressing

as

predicted by the principal normative models in the

field. However, as would be expected by the models,

more basic e-government offerings (information and

nontransactional services) have been fairly widely

adopted. Thus, even after 10 years of adoption,

e-government remains mainly informational; it is not

highly interactive or transactional as the models

predict; and it is not moving with any speed toward

an interactive and transactional state.

Changes Resulting from E-Government

The surveys asked local governments about the

changes that they attributed to their e-government

efforts (table 4). We present them in table 4 as cost

and noncost impacts. Nearly all of the impacts, as

written in the ICMA questionnaire, are

positive. Only

"increased demands on staff can be seen as a negative

impact. Arguably, "reengineered business processes"

could be viewed as a neutral impact, except that busi

ness process reengineering is clearly part of the rheto

ric around e-government (i.e., e-government will

result in business process reengineering, which, in

turn, will produce greater governmental efficiencies).

Hence, we view business process reengineering as a

Table 4 Changes Attributed to E-Government

2000 2002 2004


Cost impacts Reduced number of staff 0.7 11 1.3 24 2.6 46 Increased non-tax revenues 0.6 10 0.9 16 1.3 24

Reduced administrative costs 5.0 78 7.9 148 10.9 195

Noncost impacts Reduced time demands on staff 8.2 129 17.1 320 25.0 447 Increased demands on staff 21.1 332 33.0 620 27.6 494

Reengineered business processes 17.5 275 24.1 453 25.3 453

Business process more efficient 13.3 209 19.6 368 23.5 420

Increased citizen contact with elected ? ? 38.0 712 35.8 641

and appointed officials

Improved communication to public ? ? ? ? 59.6 1,068

Improved customer service ? ? ? ? 52.8 945




positive impact. The results for 2000 and 2002 are a

bit higher (generally one to 3 percent) than those

reported by Norris and Moon (2005) because of

coding differences.

Overall, for 2004, the number of

governments reporting positive

changes, especially changes with

clear cost impacts, was not substan

tially different from previous years.

Only three changes were indicated

by more than a third of local govern

ments: increased citizen contact with

officials (36 percent), improved

public communication (60 percent), and customer service (53 percent).

It is very important to realize that

these are changes that should not be judged solely from the perspective of the local government?

citizens may have a differing evaluation?but clearly,

local governments tend most commonly

to cite these

related citizen interaction benefits. Not all changes are

positive. More governments noted increased (28 per

cent) rather than reduced demands (25 percent) on

staff. Direct cost impacts

are all quite low, especially

reducing the number of staff (3 percent) and increas

ing nontax revenues such as from Web site

advertising

(1 percent). This suggests that local governments are

not reaping the often touted financial gains from

e-government. This finding, that direct financial sav

ings are difficult to obtain, is well known from the

information technology and government literature.

Results for positive effects that have indirect costs or

effectiveness implications, such as staff time demands,

are decidedly mixed. Business process reengineering

that results in more efficient processes may also save

money, at least in cost avoidance to support growth in

service demands, but only about one-fourth of gov ernments

reported any business process reengineering.

What about changes over time? Most reported

changes increased slightly over the

three surveys, with the possible

exception of increased demands on

staff, which increased from 2000 to

2002 and then decreased between 2002 and 2004. With this excep tion, the greatest amount of change

appeared to occur between 2000

and 2002 and leveled off between

2002 and 2004.

Barriers to E-Government

Not unlike other technological innovations,

e-government faces numerous potential barriers to

adoption and development. The surveys asked local

governments to indicate whether they had encoun

tered a number of possible barriers. We report these

barriers across four domains: technical, political and

organizational, legal, and financial (table 5). Not all

questions were asked in each survey. The percentages

for 2000 and 2002 are higher _ than those reported by Norris and

Moon (2005) because of coding differences.

For 2004, the two most commonly

cited problems were lack of finan

cial resources (57 percent) and

lack of technology or Web staff

(53 percent). Staffing and financial

problems within government infor

mation technology

are not new to

e-government but are likely

exacerbated by it. The lack of

e-government staffing is related to the lack of financial

resources, as local governments find it hard to com

pete with the private sector for skilled information

technology staff. Additionally, the reported lack of

financial resources as an e-government barrier is un

derstandable given recent pressure on local govern

ment budgets and e-government s

dependence on

general revenue financing (Coursey 2005).

No other barrier was cited by a

majority of govern

ments, although six barriers were reported by between

a quarter and a third of respondents. These were secu

rity issues (37 percent), difficulty justifying return on

investment (33 percent), issues related to convenience

fees (32 percent), lack of technology/Web expertise (31 percent), privacy issues (29 percent), and lack of

demand (23 percent). Thus, only eight of 16 per ceived barriers were cited by

more than one in four of

these governments.

It is interesting that the lack of support from elected officials (11 percent), staff resistance (17 percent), and resident resistance (5 percent)

are all among least cited

barriers. The staff resistance result reflects previous research finding that government personnel

are not

technophobes and do value new

technology (Bretschneider and Wittmer 1993).

The lack of resident or business demand (23 percent) is also inter

esting. Too often, governments

develop Web applications without

any consideration of real citizen

demand. A "field of dreams" per

spective exists?if we build it, they will come. Yet local officials and

even e-government enthusiasts will admit that

there is a lack of demand for e-government, and

e-government is being driven primarily from the top

down by governments themselves (i.e., the govern ment of the United Kingdom) or by the professional

The lack of e-government

staffing is related to the

lack of financial resources,

as local governments find

it hard to compete with

the private sector for

skilled information

technology staff.

Too often, governments

develop Web applications without any consideration

of real citizen demand. A

"field of dreams"

perspective exists?if we

build it, they will come.




Table 5 Barriers to E-Government

2000 2002 2004


Technical capabilities Lack of technology/Web staff 58.1 913 56.9 1067 53.0 950

Lack of technology/Web expertise 40.0 629 36.4 682 31.4 563 Lack of information on e-government 24.9 391 16.2 304 12.7 228

applications Web site does not accept credit cards ? ? ? ? 27.9 499

Bandwidth issues ? ? ? ? 8.2 146

Need to upgrade PCs, networks 29.5 463 26.0 487 20.5 367

Political and organizational Lack of support from elected officials 10.6 167 10.9 205 10.7 192

Lack of collaboration among departments ? ? 17.4 327 16.9 302

Staff resistance to change ? ? 15.1 284 17.0 304

Resident resistance to change ? ? ? ? 4.6 82

Lack of business/resident interest or ? ? ? ? 22.8 408

demand

Legal Issues related to convenience fees for 25.0 393 30.9 580 31.8 570

online transactions

Privacy issues 25.1 395 33.5 628 28.6 513 Security issues 38.3 602 42.4 795 37.4 669

Financial

Difficulty justifying return on investment ? ? 33.4 627 32.5 582

Lack of financial resources_482_757_533_1000_5^4_1028

norms of information technology departments and

management officials of local governments (e.g., see

Coleman and Norris 2005).

Legal issues, collectively, are

quite prominent. Conve

nience fees (32 percent), privacy issues (29 percent), and security (37 percent) all relate to complex, varying

legal concerns

requiring extensive coordination among

various officials and departments to resolve and cross

over into volatile political issues.

It would be reasonable to assume that as governments

collectively gain more

experience with e-government,

there should be a reduction in perceived barriers.

Somewhat fewer governments reported technical

barriers across the three surveys, particularly a

"lack of information on e-government applications"

(25 percent, 16 percent, and 13 percent, respectively) and a "lack of technology Web expertise" (40 percent, 36 percent, and 31 percent, respectively).

The only other discernable trend is that there was

greater change between 2000 and 2002 in the re

sponses of the local governments?whether increasing

or decreasing?about barriers than between 2002 and

2004.

Table 6 Service Adoption by Changes, 2000-04 (Kendall's tau-b

correlations)

All Changes Cost Noncost

All services .175 .170 .162

Financial transactions .168 .142 .158

Nonfinancial transactions .157 .158 .145

Note: All correlations significant at p < .001.

Adoption and Change

E-government adoption is predicted to be related to

various changes, mostly presumed positive, in local

governments. Hence, we would expect that local

governments adopting more services would report

greater change. Furthermore, we would expect the

level and type of change to vary with adopted services.

For example, if the e-government models are correct,

financial services should have a stronger relationship to

change, both cost and noncost related, than nonfi

nancial or non transactional.

In tables 3 and 4, we present summated measures of

the various online service adoption and change items.

In the survey, these were checkbox items indicating

whether a change had been noted (e.g., "has reduced

the number of staff") or a particular service adopted

(e.g., "online payment of taxes"). We summed each of

these to create overall measures of the number of

changes or

adoptions. We categorized services as fi

nancial, nonfinancial, or nontransactional/informa

tional. We categorized the change items as either cost

or noncost. Tables 6 and 7 present our correlations

between services and changes. The "increased de

mands on staff" item was considered a negative

Table 7 Service Adoption by Changes, 2002-04 (Kendall's tau-b

correlations)

All Changes Cost Noncost

All services .294 .188 .288

Financial transactions .189 .154 .181

Nonfinancial transactions .241 .169 .235

Nontransactional .267 .154 .264

Note: All correlations significant at p < .001.




impact and subtracted from the index for changes. Table 6 presents data for 2000-04, while table 7 pre sents data for 2002-04, only where additional mea

sures were available for both years (cf. tables 3 and 4).

The data in table 6 for the 2000-04 period show a

very modest relationship between the number of

noted online services and changes. All correlations

were significant

at thep

< .001 level. However, as

indicated by the Kendalls tau-b statistics, none of the

strengths exceeded .175. The associations are some

what stronger for 2002-04 (table 7), which suggests that experience with e-government, both within and

among local governments, may strengthen the linkage

between adoption and change.

The e-government models, however, suggest that more

"sophisticated" adoptions, such as financial transac

tions, should have a stronger relationship to

change.

The data for 2000-04 are mixed, but the results for

2002?04 strongly suggest otherwise. Nontransactional

services (.267), followed by nonfinancial transactions

(.241), have a stronger relationship to overall change

than financial transactions. Even specifically for cost

impacts, financial transactions (. 154) do not demon

strate a stronger relationship. Thus, nontransactional

(less sophisticated) services have a

greater relationship

to reported changes than financial transactions (more

sophisticated services). Possibly, this could be attribut

able to experience with the form of service as local

governments have adopted more nontransactional

services (cf. table 3). However, the models tell us that

financial transactions should have far clearer connec

tions to change than nonfinancial services?

something that is not shown by these data.

Barriers and Services

Local governments that report more barriers to e

government should also report the adoption of fewer

services. Additionally, those that have adopted more

sophisticated services (such as financial transactions) should report a different pattern of barriers. For ex

ample, political and legal issues should be more ger

mane to transactional versus informational services.

Tables 8 and 9 present correlations between barriers

and services. Table 8 presents data for 2000-04, while

Table 8 Barriers by Service Adoption, 2000-04 (Kendall's tau-b

correlations)

All services Financial Nonfinancial

All barriers -.090 -.045 -.090

Technical capabilities -.155 -.104 -.141

Political and -.052 -.032* -.050

organizational

Legal .039** .045 .026***

Financial -.059 -.014*** -.064

Note: All correlations significant at p < .001 except where

noted. *p < .01; **p < .05; ***p > .05.

table 9 reports additional items included only in the

2002 and 2004 surveys (cf. table 4).

Overall, there is a very weak negative association

between all reported barriers and services (correlations

of-.090 for 2000-04 and -.094 for 2002-04). Only for technical barriers, such as lack of technology Web

staff and expertise, do the correlations exceed .100.

Does this suggest that barriers have no relationship

to

service adoption? Not necessarily. First, the results are

only for local governments that have already estab

lished Web site operations. It may be that these often

touted barriers are more important in

launching e

government efforts. Also, the barrier items did not,

unfortunately, ask local governments to assess how

great a hindrance each barrier was to their efforts.

Instead, it simply asked whether each barrier existed.

Even so, the results do not support the view that a

strong relationship exists between barriers and ser

vices. Technical barriers appear the most important,

a

finding mirrored by the way in which many local

governments reported it as a barrier (see table 5). But

even here, the correlations are weak. Much of the e

government literature stresses bridging organizational

boundaries and related political and legal problems as

significant hurdles to e-government. Yet these barriers

are far more germane to more complicated,

encom

passing applications (e.g., those involving interactivity

and transactions). It may be that these barriers be

come more important

as local governments expand

into such services. However, as previously discussed,

the survey results show that few local governments

actually offer sophisticated services via the Web. Ad

ditionally, technical barriers inhibit all service levels, so

regardless of the stage of e-government develop

ment, technical problems may be consistently re

ported as a

primary problem. There is no evidence of

a stronger relationship between political and legal

barriers to more complex services as

might be ex

pected from the e-government literature.

Another interesting finding is that the correlations

between legal barriers and services, though very small,

are all positive, implying that more legal barriers are

Table 9 Barriers by Service Adoption, 2002-04 (Kendall's tau-b

correlations)

All services Financial Nonfinancial Nontran

sactional

All barriers -.094 -.036** -.098 -.055

Technical -.200 -.107 -.166 -.168

capabilities Political and -.017*** .033*** -.025*** .000

organizational

Legal .062 .055 .027*** .076

Financial -.054 -.044* -.069 -.020***

Note: All correlations significant at p < .001 except where

noted. *p< .01: **p< .05; ***p> .05.




related to greater service adoption. This may be

because such legal issues as privacy, security, and

convenience fees occur more often with complex

e-government operations. Hence, governments with

more services and operating transactional applications encounter these as barriers, whereas those with non

transactional sites do not. This does suggest some

weak support for the predictions of the e-government

models. However, it is critical to remember these

correlations are extremely small and, as such, they

probably are not

substantively meaningful.

Conclusions and Implications Local e-government in the United States is only

about a dozen years old. Yet more than nine in 10

(96.2 percent) local governments with populations

greater than 10,000 have established official sites on

the World Wide Web through which they offer infor

mation and services. However, the e-government

offerings reported by these governments are limited,

relatively unsophisticated, and primarily involve

information and nontransactional services. Few local

governments provide nonfinancial transactions, and

fewer still provide financial transactions via their Web

sites. Moreover, in recent years, the adoption of

e-government services has slowed considerably and,

in some areas, seems to have halted.

These findings offer some support but also raise im

portant questions about the principal normative mod

els of e-government. The findings support the models

in that most local governments have adopted

e-government, at least at the basic level predicted by

models, and have done so in a very short period of

time. The findings raise questions about the models in

that they are

clearly at odds with the models' predic

tions that governments will move stepwise toward the

adoption of more sophisticated e-government offer

ings, moving from information to transactions to

integration and ultimately to transformation. This

predicted movement is not

happening, or if it is, the

movement is glacial in its speed.

Another important finding from these data is that

few governments reported any changes that are

attributable to e-government, especially changes in

volving cost impacts. And not all the reported changes

were positive,

even though positive change

is an im

portant part of the mantra surrounding e-government

and is clearly expected by the models. Additionally, local governments reported fewer changes attributable

to e-government between 2002 and 2004 than be

tween 2000 and 2002, suggesting that the movement

through the stages of e-government (if there are

stages) is neither as accelerated nor as

simple as the

models posit. If e-government were "evolving"

as the

models predict, greater numbers of governments

would have reported changes, and they would have

reported more positive changes.

We found a modest association between adoption

and reported changes. But the changes were more

associated with nonfinancial services. This finding is also at odds with the models that predict the

ever-increasing adoption of more sophisticated

applications which, in turn, will produce more

and greater positive changes.

Local governments reported a number of barriers to

the adoption of e-government. But only two barriers

were reported by

more than half of the governments

and only four were reported by one-third or more of

the governments. Fewer barriers were reported in

2004 than in 2002, suggesting that as governments

gain more

experience with e-government, they are less

plagued by barriers.

However, the models miss or ignore the possibility

that barriers to e-government adoption exist. Indeed,

this is a serious limitation of the models that, until

now, has not been identified in the literature. The

models assume, quite uncritically, that governments

will increasingly adopt more and better e-government.

We know of no theories of innovation adoption that

suggest that innovations are adopted without prob

lems. For example, it is possible that certain barriers

(money, staff, infrastructure, others) may be more or

less important to different governments (large versus

small governments, wealthy versus poor governments),

at different times in the adoption process (early adopt ers versus

laggards), and with respect to different types

of applications (low-hanging fruit versus high-end

applications). This would be a reasonable interpreta

tion of the empirical data on barriers to the adoption

of e-government. However, the models provide no

guidance here and instead simply assume a

progressive

adoption of e-government, sans barriers.

We found a weak negative association between barri

ers and adoption. But U.S. local governments are still

offering fairly basic e-government menus. Surely, after

10 years of e-government, we should expect some

empirical validation of the models' predictions of the

road to transactional, interactive, and transforma

tional e-government. We found no such evidence.

Why are there such great inconsistencies between the

models and these empirical findings? First, the models were created in a vacuum.

They were based on neither

extant theory

nor empirical data. This is not dissimilar

to the expert systems theories developed in the 1980s,

which predicted growth along a level of technical so

phistication. These theories had virtually no

recogni

tion of existing information technology adoption

literature, partly because many of these models came

from engineering, not business or

public administra

tion (i.e., Coursey and Shangraw 1989). Expert sys

tems advocates believed that such applications would

become increasingly technically sophisticated,




handling more

complex tasks and replacing human

expertise. Yet the models did not account for the real

barriers of legal limitations, lack of human contact in

transferring knowledge to younger and less experi

enced employees, and expert resistance, among other

political and organizational issues. Thus, expert sys

tems, all the rage in the late 1980s, are today

an after

thought among information technologies in

government decision making. Like expert systems,

e-government models were also developed without any

linkage to the rich literature about information tech

nology and government that is now 30 years old, or to

what little empirical literature about e-government

that was available in 2000 and 2001.

Thus, while intellectually interesting, the models are

almost purely speculative. They were not models per se

but guesses about what e-government might be and how

it might develop. As it turns out, this guesswork was

only

partly correct. But why should such an outcome be

unexpected? On what basis could or should one guess that there would be stages of e-government, especially

a

specific number of stages? That governments would have

to move stepwise through these stages? That the final

stages of e-government would produce a literal transfor

mation in the relations between citizens and govern

ments in which both citizen participation and trust in

government would dramatically increase? That nearly all

of the consequences of e-government would be positive?

What foundation is there for any of these guesses?

Upon reflection, they appear consistent with what

Pippa Norris (2001) calls "cyber-optimism" and what

others might consider technological determinism,

problems that have plagued our understanding of the

adoption of previous information technology innova

tions. The models were certainly not connected to the

research into information technology and government

that might have more effectively informed and under

pinned their guesses.

Empirical findings from this research allow us to make

some statements about e-government that provide a

better understanding of this phenom enon than is possible from reading the

models. Among these statements are at

least the following:

E-government is mainly an add

on to traditional ways of delivering governmental information and

services, not a substitute for them.

Thus, the onus is on e-government

researchers to refrain from reinvent

ing the wheel of previous research.

The burden of proof that somehow

e-government should be presumed so different from preceding

innovation as to require

totally new, unconnected scholarship is on them.

There do not appear to be discernable steps or

stages in e-government. Rather, after an initial

e-government presence, governments adopt

e-government slowly and incrementally.

E-government is not linear. Late adopters of

e-government need not start at the most basic level

of e-government. They can and do learn from the

experiences of other governments and the private sector and begin with more

sophisticated offerings.

E-government is not necessarily continually

progressive in its technical development,

nor is it

without problems?more is not necessarily always

better, and some consequences are not positive.

E-government probably has great potential to

do or be many things, and some of those things cannot be anticipated?this is true of technological innovation in

general. But some of the potentials

of e-government suggested by the models (e.g.,

seamlessness and e-transformation) seem not to

have been based on a careful reading or a realistic

understanding of the prior literature that impor

tantly informs this field (see, e.g., Danziger and

Andersen 2002; Kraemer and King 2006).

E-government, like information technology in

government before it, will probably not produce

governmental reform or transformation but instead

can be expected to support the interests of the

dominant political-administrative coalitions within

governmental organizations (Kraemer and King

2006).

Tougher applications, more

costly applications,

and applications for which there is little demand, if

added at all, probably will be added later and more

slowly.

Technology is not likely a primary barrier to

e-government, especially as governments gain

experience. Organizational and political factors are

likely to

significantly affect e-government applica

tion development, performance, and adoption.

These findings should have special meaning for gov ernmental managers. To begin with, managers should

be appropriately skeptical of the claims made about

e-government. Often, such claims

come from a decidedly technologi

cally deterministic perspective?

"If we build it, they will

come!"?and are not based on

empirical assessment. Based on

the prior history of information

technology in government

(see especially Danziger and

Andersen 2002; Kraemer and

King 2006), we do not expect that e-government will produce

many, if any, immediate and

dramatic results. Rather, we

expect that e-government will advance slowly and

incrementally. Initially, at least, it will require substantial

At the end of the day, e-government is what it is,

not what it was predicted to be, and empirical

findings provide a more

accurate, if also decidedly more prosaic portrait of

e-government than the

principal models.

Models of E-Govemment 533



investment by governments, with little overall

impact by way of cost reduction or productivity

improvement.

At the end of the day, e-government is what it is, not

what it was predicted to be, and empirical findings

provide a more accurate, if also decidedly

more prosaic,

portrait of e-government than the principal models. It

is on these findings, not on the speculations of e-gov

ernment models or the hype surrounding the field, that

our understanding of e-government ought

to be based.

If these models of e-government are as "challenged"

as

we have shown them to be, what theoretical directions

appear useful? Any theory needs plausible, grounded,

and testable predictions to guide the development and maintenance of e-government services. We need to

escape the simplistic documentation of service deliv

ery and technological advancement approaches domi

nating the literature. It is far beyond the scope of this

paper to explicate alternative theory, but readers

should perhaps consider three useful directions.

One course is to deploy the traditional public infor mation

technology theory of reinforcement politics:

that information technology is developed and man

aged in such a way as to

simply reinforce existing

power arrangements (Kraemer, Dutton, and Northrup

1981). Such a theory is very skeptical of e-democracy promises and increased citizen involvement. Some

case study work examining the nascent

development

of e-government in Florida supports reinforcement

theory (e.g., Coursey and Killingsworth 2001). A

second is to ground understanding of e-government

in decision making: How do services affect the under

lying decision tasks of organizations? Such an ap

proach has been used for expert systems (e.g., Coursey

and Shangraw 1989). This would be particularly

helpful to

developers, as decision complexity, includ

ing stakeholders, varying outcomes and benefits,

among many other attributes, are critical development factors. Finally,

a policy-making and institutional

focus (e.g., Fountain 2001) can help discover and

explain complex interactions across policy factors.

Such traditional frameworks as Lowi's (1969) distribu

tion, regulation, and redistribution typology can

anchor e-government in a more purposive cost

benefit orientation as a guide

to prospective stake

holder development issues.

To those who would aver that it is too early

to assess

the impacts of e-government, we respectfully disagree.

At this writing, e-government has been around for at

least a dozen years. Certainly, it is time to begin

to

examine its early impacts. We would agree, however,

that the unfolding of e-government is likely to be a

slow and incremental process, and therefore, the re

sults shown here should be considered preliminary.

Indeed, for these reasons, we believe that scholars

should continue to conduct systematic research into e

government and its impacts.

Like all research, our findings should be couched within their limitations. First, these are cross-sectional

surveys, and there is some variation in the pool of

responding governments. Hence, some variation is

attributable to the pool, not

just differences in activity,

although there are scant differences in key demo

graphics between the samples and population

(table 1). Currently, we are

conducting research

segmenting only governments responding to each

survey, but even so, there is no guarantee that respon

dents were constant and that participation did not

change as a result of e-government related reasons

(e.g., those more involved in e-government may be

more likely

to respond

to all the surveys, hence pre

senting a

misleading overestimate of change). Of course, standard statistical analysis presumes sam

ple variation?hence the use of dependent sample tests with more statistical power in such panel

cases.

Second, even with a panel design, the issue of e-gov

ernment experience is significant and not

clearly ad

dressed. Unfortunately, this is not directly measured

in all three surveys. The ICMA should strongly con

sider asking about year of first activity by area, such as

transactional, citizen participation, and so forth. No

doubt, experience is probably

a critical factor. We plan on

attempting to track this information directly in

future research by contacting the local governments

responding to each survey. Also, a test for response

mortality across the three surveys will be conducted

on a variety of e-government items and government

characteristics.

Third, we did find that the samples tended to slightly overrepresent council-manager compared

to mayor

council governments. The exact effect on assessed

barriers, changes, and provided services is difficult to

ascertain. Presuming that the difference is not attrib

utable to population and potentially larger govern

ments with greater resources, it could simply be that

council-manager governments with more "profes

sional" administration are more likely

to complete

such surveys for professional associations such as the

ICMA. Still, the samples are

remarkably stable in their

key demographics, including form of government,

such that variation over the three periods can be more

readily attributed to real change and not variation in

the sample makeup.

Fourth, this study focuses on American local govern

ments. Clearly, international efforts should be consid

ered in future research development and testing.

Finally, the question concerning changes and adop tion are

simple nominal items that do not consider

the maturity and extensiveness of a service delivery




or how much change has actually occurred. For

example, two governments may both indicate some

cost savings, but they may be dramatically different

in magnitude. The same goes for adoption. One city

may have just begun online fee collection for one

service, whereas another has such payments for a

number of its units. Obviously, these are critical

considerations and future ICMA surveys should

strongly consider items that tap not only the exis

tence of service and changes, but also their diffusion

and intensity.

Future research into local e-government should move

beyond the examination of local governments that

have adopted e-government. It would be valuable to

examine local governments that have not adopted

to

learn what has kept them from adopting. The data for

this analysis came from the responses of governmental

officials. It would also be valuable in future research to

examine citizen uptake and use of e-government. Now

that e-government has been built, do citizens come?

Once they arrive, what do they find, and what do they

think of what is there? More importantly, and usually an

afterthought, what about those who are not using

e-government? Why do people not use the Web sites?

Finally, future research should endeavor to get at

issues of the maturity and sophistication of e-govern

ment offerings (not all services are

equal), intensity of

use (versus simply whether a service exists), and mea

sures of impacts beyond the opinions of local govern

mental officials. Each of these added research

dimensions will further our understanding of

e-government in important ways.

Note 1. We define e-government as the electronic delivery

of governmental information and services, 24

hours per day, seven days per week (Holden,

Norris, and Fletcher 2003). E-government is

provided principally, although not exclusively, via

the Internet. E-government is also distinct from

prior generations of information technology

applications in government because it is mainly

outward facing?that is, government to citizen

(G2C), government to business (G2B), and gov

ernment to government (G2G)?rather than

inwardly facing (i.e., the automation of routine

governmental functions such as finance and ac

counting and record keeping).

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