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. Th e 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. Th ey fi nd that local e-government is mainly informational, with a few transactions but virtually no indication of the high-level functions predicted in the models. Th us, the models do not accurately describe or predict the development of e-government, at least among American local governments. Th ese models, though intellectually interesting, are purely speculative, having been developed without linkage to the literature about

information technology and government. Th e authors

off er grounded observations about e-government that will useful to scholars and practitioners alike.

R

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 ). Th is is not surprising, because the fi eld of e-government itself is not much more than a dozen years old at this writing. Offi cial governmental sites delivering information and services fi rst 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-governgovern-ment 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 ).

Th e e-government literature contains fi ve works that off er 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 eff ort 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 Bélanger 2001 ). Th ese 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 descripprescrip-tion. 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. Th e models predict that e-government will move beyond information provision and interactivity to become fully transactional. Th ey also predict that

David Coursey

Arizona State University

Donald F. Norris

University of Maryland, Baltimore County

Models of E-Government: Are Th

ey Correct?

An Empirical Assessment

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]

New

Perspectives on

E-Government

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. Th e models implicitly presume that fully transactional systems are better and that more citizen interaction equals improved service.

Th e models are similar in many respects. Th ey all predict the linear development or evolution of e-government from a basic online presence to full integration, seamlessness, and transformation. Th ey 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 specifi c steps that they predict, whereas the fi fth ( Layne and Lee 2001 ) is an outlier in terms of the precise steps, although not in the direction of the development.

Th ere 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-governdevelop-ment among local governdevelop-ments 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 fi ndings for models of e-government and for the con-tinuing study of e-government.

E-Government Models

Figure 1 shows the steps that the fi ve 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 diff er 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 fi rst 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 offi cials online. Th is is followed by a transactional stage in which citizens will be able to conduct business online with governments. Th e fi nal 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 specifi cs 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 Bélanger’s (2001) model suggests a slightly diff erent progression than the other models and also predicts a somewhat diff erent 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 Bélanger 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 Bélanger predict that at its end point, e-government

Step 1 Step 2 Step 3 Step 4 Step 5 Step 6

Layne and Lee (2001)

Catalogue Transaction Vertical integration

Horizontal integration

Baum and Di Maio (2000)

Presence Interaction Transaction Transformation

Ronaghan (2001)

Emerging presence

Enhanced presence

Interactive Transactional government

Seamless

Hiller and Bélanger (2001)

Information dissemination

Two-way communication

Integration Transaction Participation

Wescott (2001)

E-mail and internal network

Enable

interorganizational and public access to information

Two-way communication

Exchange of value

Digital democracy

Joined-up government

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 offi cials, and transacting business with government. At this stage, citizens participate electronically in the very activities of governance.

Th e models off ered 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 offi cial Web site 24/7. Th e 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. Th e fi nal stage in Ronaghan’s model is seamlessness. Th is 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 Bélanger’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. Th ey 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. Th e fi nal step in Layne and Lee’s model is horizontal integration, which means the sharing of data and information online across departments within governments.

Th ese 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. Th ey pass through predict-able stages of e-government, such as interactivity, transactions, and integration, and then arrive at an e-government nirvana. Th is fi nal 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. Th e 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 signifi cant barriers (e.g., fi nancial, 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 Th e 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. Th e ICMA samples are derived from the relative popula-tion distribupopula-tions of key demographic variables or stratifi ed on such variables as form of government and region. Table 1 provides descriptives by various classifi cations.

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 diff erence 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

relative breakdowns are still quite similar to the popu-lation data (see ICMA 2005 , xii – xiii). Overall, the samples do not display signifi cant variation in key demographics, which might alter the interpretation of change. However, there is some imbalance in the form of government.

Th e 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. Th e response rate was 50.2 percent. Th e 2002 and 2004 surveys were mailed to all municipalities with populations of 2,500 or more and all counties with manager or council-elected executive forms of government. Th e 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 diff erences

are relevant to this study. First, in 2000 and 2002, respondents were specifi cally told not to answer ques-tions if they did not have Web sites. Th is instruction was not repeated in 2004. Th is 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 identifi ca-tion of any Web-provided informaca-tion 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 Moon’s (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

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

Survey year 2002 Census *

Percent of responses

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.

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. Th e eff ect of this coding schema is to infl ate 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 offi cial 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 fi gure 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

Th ere is a major diff erence 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. Th e services can be roughly divided into nontransactional, nonfi -nancial, and fi nancial transactions. Transactional applications require some two-way exchange of data

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 offl ine.

For 2004, it is apparent that although Web sites are commonplace, the deliv-ery of anything but basic information is not. Th e only services provided by at least a majority of local governments are nontransactional. Overall, nontransac-tional services are the most common, followed by nonfi nancial, and fi nancial transactions. Few local governments off er fi nancial transactions (all between 11 percent and 14 percent). Th ere 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 nonfi nancial transactions.

Th ere 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 diff erences reported here between 2000 and 2002 are less than those provided by Norris and Moon (2005). Th ey do not include outsourced services for 2000, which, unlike the 2002 and 2004 surveys, were separated from internal off erings.

For nonfi nancial 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 diff erences in nonfi nancial 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

Table 2 Web Site Adoption

2000 2002 2004

Percent N Percent N Percent N

Yes 83.6 1,571 87.7 1,866 96.2 1,791

No 16.4 308 12.3 262 3.8 71

. . . it is apparent that

although Web sites are

commonplace, the delivery

of anything but basic

information is not. Th

e

only services provided by

at least a majority of local

governments were

nontransactional.

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 fi nancial transactions, which are still uncommon. Th is 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 fi eld. However, as would be expected by the models, more basic e-government off erings (information and nontransactional services) have been fairly widely adopted. Th us, 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

Th e surveys asked local governments about the changes that they attributed to their e-government eff orts ( 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 effi ciencies). Hence, we view business process reengineering as a

Table 4 Changes Attributed to E-Government

2000 2002 2004

Percent N Percent N Percent N

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 effi cient 13.3 209 19.6 368 23.5 420

Increased citizen contact with elected and appointed offi cials

— — 38.0 712 35.8 641

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

Improved customer service — — — — 52.8 945

Table 3 Online Service Adoption

2000 2002 2004

Percent N Percent N Percent N

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 fi ne payments 5.1 59 5.6 98 11.1 183

Nonfi nancial 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 completion

— — 65.7 1,067 71.8 1,203

Communicate with government offi cials — — 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, applications

positive impact. Th e 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 diff erences.

Overall, for 2004, the number of governments reporting positive changes, especially changes with clear cost impacts, was not substan-tially diff erent from previous years. Only three changes were indicated by more than a third of local govern-ments: increased citizen contact with offi cials (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 diff ering evaluation — but clearly, local governments tend most commonly to cite these related citizen interaction benefi ts. Not all changes are positive. More governments noted increased (28 per-cent) rather than reduced demands (25 perper-cent) 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 advertisincreas-ing (1 percent). Th is suggests that local governments are not reaping the often touted fi nancial gains from e-government. Th is fi nding, that direct fi nancial sav-ings are diffi cult to obtain, is well known from the information technology and government literature. Results for positive eff ects that have indirect costs or eff ectiveness implications, such as staff time demands, are decidedly mixed. Business process reengineering that results in more effi cient 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. Th e 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 fi nancial ( table 5 ). Not all questions were asked in each survey. Th e percentages

for 2000 and 2002 are higher than those reported by Norris and Moon (2005) because of coding diff erences.

For 2004, the two most commonly cited problems were lack of fi nan-cial resources (57 percent) and lack of technology or Web staff (53 percent). Staffi ng and fi nancial problems within government infor-mation technology are not new to e-government but are likely exacerbated by it. Th e lack of e-government staffi ng is related to the lack of fi nancial resources, as local governments fi nd it hard to com-pete with the private sector for skilled information technology staff . Additionally, the reported lack of fi nancial resources as an e-government barrier is un-derstandable given recent pressure on local govern-ment budgets and e-governgovern-ment’s dependence on general revenue fi nancing ( 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. Th ese were secu-rity issues (37 percent), diffi culty 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). Th us, 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 offi cials (11 percent), staff resistance (17 percent), and resident resistance (5 percent) are all among least cited barriers. Th e staff resistance result refl ects previous research fi nding that government personnel are not

technophobes and do value new technology ( Bretschneider and Wittmer 1993 ).

Th e 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 “fi eld of dreams” per-spective exists — if we build it, they will come. Yet local offi cials 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

Th

e lack of e-government

staffi

ng is related to the

lack of fi nancial resources,

as local governments fi nd

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

“fi eld of dreams”

perspective exists—if we

build it, they will come.

norms of information technology departments and management offi cials 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 offi cials 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). Th e 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.

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, fi nancial services should have a stronger relationship to change, both cost and noncost related, than nonfi -nancial or nontransactional.

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, nonfi -nancial, 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. Th e “increased de-mands on staff ” item was considered a negative

Table 5 Barriers to E-Government

2000 2002 2004

Percent N Percent N Percent N

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 applications

24.9 391 16.2 304 12.7 228

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 offi cials 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 demand

— — — — 22.8 408

Legal

Issues related to convenience fees for online transactions

25.0 393 30.9 580 31.8 570

Privacy issues 25.1 395 33.5 628 28.6 513

Security issues 38.3 602 42.4 795 37.4 669

Financial

Diffi culty justifying return on investment — — 33.4 627 32.5 582

Lack of fi nancial resources 48.2 757 53.3 1000 57.4 1028

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

Nonfi nancial transactions .157 .158 .145

Note: All correlations signifi cant at p < .001.

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

Nonfi nancial transactions .241 .169 .235

Nontransactional .267 .154 .264

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 ). Th e 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 signifi cant at the p < .001 level. However, as indicated by the Kendall’s tau-b statistics, none of the strengths exceeded .175. Th e 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.

Th e e-government models, however, suggest that more “sophisticated” adoptions, such as fi nancial transac-tions, should have a stronger relationship to change. Th e data for 2000 – 04 are mixed, but the results for 2002 – 04 strongly suggest otherwise. Nontransactional services (.267), followed by nonfi nancial transactions (.241), have a stronger relationship to overall change than fi nancial transactions. Even specifi cally for cost impacts, fi nancial transactions (.154) do not demon-strate a stronger relationship. Th us, nontransactional (less sophisticated) services have a greater relationship to reported changes than fi nancial 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 fi nancial transactions should have far clearer connec-tions to change than nonfi nancial 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 fi nancial transactions) should report a diff erent 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 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 eff orts. Also, the barrier items did not, unfortunately, ask local governments to assess how great a hindrance each barrier was to their eff orts. 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 fi nding 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 signifi cant 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 off er 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. Th ere 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 fi nding is that the correlations between legal barriers and services, though very small, are all positive, implying that more legal barriers are

Table 8 Barriers by Service Adoption, 2000 – 04 (Kendall’s tau-b correlations)

All services Financial Nonfi nancial

All barriers −.090 −.045 −.090

Technical capabilities −.155 −.104 −.141

Political and organizational

−.052 −.032 * −.050

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

Financial −.059 −.014 *** −.064

Note: All correlations signifi cant at p < .001 except where noted. * p < .01 ; ** p < .05 ; *** p > .05.

Table 9 Barriers by Service Adoption, 2002 – 04 (Kendall’s tau-b correlations)

All services Financial Nonfi nancial

Nontran-sactional

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

Technical capabilities

−.200 −.107 −.166 −.168

Political and organizational

−.017 *** .033 *** −.025 *** .000

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

Financial −.054 −.044 * −.069 −.020 ***

Note: All correlations signifi cant at p < .001 except where noted. * p < .01 : ** p < .05 ; *** p > .05.

related to greater service adoption. Th is 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. Th is 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 offi cial sites on the World Wide Web through which they off er infor-mation and services. However, the e-government off erings reported by these governments are limited, relatively unsophisticated, and primarily involve information and nontransactional services. Few local governments provide nonfi nancial transactions, and fewer still provide fi nancial 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.

Th ese fi ndings off er some support but also raise im-portant questions about the principal normative mod-els of e-government. Th e fi ndings 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. Th e fi ndings 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 off er-ings, moving from information to transactions to integration and ultimately to transformation. Th is predicted movement is not happening, or if it is, the movement is glacial in its speed.

Another important fi nding 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 nonfi nancial services. Th is fi nding 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 identifi ed in the literature. Th e 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 diff erent governments (large versus small governments, wealthy versus poor governments), at diff erent times in the adoption process (early adopt-ers vadopt-ersus laggards), and with respect to diff erent types of applications (low-hanging fruit versus high-end applications). Th is would be a reasonable interpreta-tion of the empirical data on barriers to the adopinterpreta-tion 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 off ering 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 fi ndings? First, the models were created in a vacuum. Th ey were based on neither extant theory nor empirical data. Th is is not dissimilar to the expert systems theories developed in the 1980s, which predicted growth along a level of technical so-phistication. Th ese theories had virtually no recogni-tion of existing informarecogni-tion technology adoprecogni-tion 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. Th us, 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.

Th us, while intellectually interesting, the models are almost purely speculative. Th ey 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 specifi c number of stages? Th at governments would have to move stepwise through these stages? Th at the fi nal 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? Th at nearly all of the consequences of e-government would be positive? What foundation is there for any of these guesses? Upon refl ection, 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. Th e models were certainly not connected to the research into information technology and government that might have more eff ectively informed and under-pinned their guesses.

Empirical fi ndings 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 traditiadd-onal ways of delivering governmental information and services, not a substitute for them. Th us, the onus is on e-government researchers to refrain from reinvent-ing the wheel of previous research. Th e burden of proof that somehow e-government should be presumed

so diff erent from preceding innovation as to require totally new, unconnected scholarship is on them.

• Th ere 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. Th ey can and do learn from the experiences of other governments and the private sector and begin with more sophisticated off erings. • 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 fi eld (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 signifi cantly aff ect e-government applica-tion development, performance, and adopapplica-tion. Th ese fi ndings 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

fi ndings provide a more

accurate, if also decidedly

more prosaic portrait of

e-government than the

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 fi ndings provide a more accurate, if also decidedly more prosaic, portrait of e-government than the principal models. It is on these fi ndings, not on the speculations of e-gov-ernment models or the hype surrounding the fi eld, 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 aff ect the under-lying decision tasks of organizations? Such an ap-proach has been used for expert systems (e.g., Coursey and Shangraw 1989 ). Th is would be particularly helpful to developers, as decision complexity, includ-ing stakeholders, varyinclud-ing outcomes and benefi ts, 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, reguladistribu-tion, and redistribution typology can anchor e-government in a more purposive cost – benefi t 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 fi ndings 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 diff erences in activity, although there are scant diff erences 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 samsam-ple tests with more statistical power in such panel cases. Second, even with a panel design, the issue of e-gov-ernment experience is signifi cant and not clearly ad-dressed. Unfortunately, this is not directly measured in all three surveys. Th e ICMA should strongly con-sider asking about year of fi rst 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.

Th ird, we did fi nd that the samples tended to slightly overrepresent council-manager compared to mayor-council governments. Th e exact eff ect on assessed barriers, changes, and provided services is diffi cult to ascertain. Presuming that the diff erence 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 eff orts 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 diff erent in magnitude. Th e 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 diff usion 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. Th e data for this analysis came from the responses of governmental offi cials. 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 fi nd, 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 off erings (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 offi cials. Each of these added research dimensions will further our understanding of e-government in important ways.

Note

1. We defi ne 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 govgov-ernment (G2G) — rather than inwardly facing (i.e., the automation of routine governmental functions such as fi nance and ac-counting and record keeping).

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