Models of E-Government: Are They Correct? An Empirical Assessment

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1 David Coursey Arizona State University Donald F. Norris University of Maryland, Baltimore County Models of E-Government: Are They Correct? An Empirical Assessment New Perspectives on E-Government Research into e-government is relatively new. Nevertheless, 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. R esearch 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 studies, 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 appearing 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 technology acceptance model ( Davis 1989 ), or those from institutional and policy perspectives (e.g., Fountain 2001 ). Even so, theoretical explanations of why government 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 criticized 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 international 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 Bélanger 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 prescription over description. Overall, all purport to describe what might be considered the normal evolution of e-government from its most basic element (a rudimentary 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 reasonably accurate portrait of e-government in its early stages, from initial Web presence to information provision 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. They also predict that 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. 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 specialist 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. Models of E-Government 523

2 e-government will fundamentally transform the relationship between governments and citizens. At this point, nearly all of the models become quite normative 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 (governments 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 development of e-government among local governments in the United States; and we test whether that development 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 continuing 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 predicting 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 interactivity 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 governments 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 Bélanger 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 communication (interactivity). Hiller and Bélanger predict that the third stage will be the integration of data and information within and among governments. Integration is followed by a transactional stage, and Hiller and Bélanger predict that at its end point, e-government Layne and Lee (2001) Baum and Di Maio (2000) Ronaghan (2001) Hiller and Bélanger (2001) Wescott (2001) Step 1 Step 2 Step 3 Step 4 Step 5 Step 6 Catalogue Transaction Vertical Horizontal integration integration Emerging presence and internal network Presence Interaction Transaction Transformation Enhanced presence Information dissemination Enable interorganizational and public access to information Interactive Two-way communication Two-way communication Transactional Seamless government Integration Transaction Participation Exchange of value Digital democracy Joined-up government Figure 1 The Models Steps 524 Public Administration Review May June 2008

3 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 establishment 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 governmental 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 information 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. Successive e-government steps, however, are not unlike those predicted by the other models information provision, 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 compared 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 predicts 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. Governments begin with a fairly basic, in some cases even primitive, Web presence. They pass through predictable 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 governments will overcome the numerous and significant barriers (e.g., financial, legal, organizational, technological, 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 Technology Incorporated and in 2004 by the ICMA. The ICMA samples are derived from the relative population 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 population 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 Models of E-Government 525

4 Table 1 Representativeness and Response Rates of ICMA Electronic Government Surveys ** Percent of responses Survey year 2002 Census * Population group More than 1,000, ,000 1,000, , , , , ,000 99, ,000 49, ,000 24, ,000-9, ,500-4, Geographic region Northeast North-central South West Metropolitan status Central Suburban Independent Form of government City Mayor-council Council-manager Other County Council-administrator Council-elected executive * From ICMA breakdown of U.S. Bureau of the Census 2002 data on local governments (ICMA 2005, xi), including counties regardless 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 population 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 councilelected 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 Yearbook organization of data sections ( ICMA 2001, 2003, 2005). Copies of the actual surveys are available from the ICMA. With a few exceptions, the respondents to all three surveys were reasonably representative 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 questions if they did not have Web sites. This instruction was not repeated in This led to the possibility, though in only a few cases, of respondents without Web sites answering questions in Ideally, responses 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 governments did not have Web sites for 2004, we chose to use the assumption that a survey with no identification 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 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 526 Public Administration Review May June 2008

5 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 address the extent to which U.S. local governments have established 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 address whether it can be reasonably 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 adoption 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, nonfinancial, and financial transactions. Transactional applications require some two-way exchange of data Table 2 Web Site Adoption... 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 Percent N Percent N Percent N Yes , , ,791 No 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 submissions are at least more technically complex to develop than a nontransactional 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 delivery of anything but basic information is not. The only services provided by at least a majority of local governments are nontransactional. Overall, nontransactional 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 pothole 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 governments 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 However, with the exception of recreational program registration, there was little meaningful change between 2002 and We also found scant differences in nonfinancial transactions between 2002 and 2004, with the possible exception of downloadable forms (72 percent versus 66 percent). Financial transactions showed the greatest relative change between 2002 and 2004, approximately doubling over the two years. However, their Models of E-Government 527

6 Table 3 Online Service Adoption Percent N Percent N Percent N Financial transactions Tax payments Utility payments Fee and fine payments Nonfinancial transactions Permit applications Business licenses and renewals Government record requests Recreational program registration Service requests Voter registration Property registration Nontransactional/informational Government record delivery Download forms for manual , ,203 completion Communicate with government officials , ,215 GIS, interactive maps Council agendas and minutes ,489 Codes and ordinances ,307 ed newsletter to residents Streaming video Employment information, applications ,305 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 Th e 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 business process reengineering is clearly part of the rhetoric 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 Percent N Percent N Percent N Cost impacts Reduced number of staff Increased non-tax revenues Reduced administrative costs Noncost impacts Reduced time demands on staff Increased demands on staff Reengineered business processes Business process more efficient Increased citizen contact with elected and appointed officials Improved communication to public ,068 Improved customer service Public Administration Review May June 2008

7 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 substantially different from previous years. Only three changes were indicated by more than a third of local governments: 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 percent) rather than reduced demands (25 percent) on staff. Direct cost impacts are all quite low, especially reducing the number of staff (3 percent) and increasing 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 savings 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 governments 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 With this exception, the greatest amount of change appeared to occur between 2000 and 2002 and leveled off between 2002 and 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 encountered a number of possible barriers. We report these 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. 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 financial resources (57 percent) and lack of technology or Web staff (53 percent). Staffing and financial problems within government information 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 compete with the private sector for skilled information technology staff. Additionally, the reported lack of financial resources as an e-government barrier is understandable given recent pressure on local government budgets and e-government s dependence on general revenue financing ( Coursey 2005 ). No other barrier was cited by a majority of governments, although six barriers were reported by between a quarter and a third of respondents. These were security 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 perceived 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 ). Th e lack of resident or business demand (23 percent) is also interesting. 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. 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 government of the United Kingdom) or by the professional Models of E-Government 529

8 Table 5 Barriers to E-Government Percent N Percent N Percent N Technical capabilities Lack of technology/web staff Lack of technology/web expertise Lack of information on e-government applications Web site does not accept credit cards Bandwidth issues Need to upgrade PCs, networks Political and organizational Lack of support from elected officials Lack of collaboration among departments Staff resistance to change Resident resistance to change Lack of business/resident interest or demand Legal Issues related to convenience fees for online transactions Privacy issues Security issues Financial Difficulty justifying return on investment Lack of financial resources norms of information technology departments and management officials of local governments (e.g., see Coleman and Norris 2005 ). Legal issues, collectively, are quite prominent. Convenience 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 responses of the local governments whether increasing or decreasing about barriers than between 2002 and 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 nonfinancial 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 financial, nonfinancial, or nontransactional/informational. We categorized the change items as either cost or noncost. Tables 6 and 7 present our correlations between services and changes. The increased demands on staff item was considered a negative Table 6 Service Adoption by Changes, (Kendall s tau-b correlations) All Changes Cost Noncost All services Financial transactions Nonfinancial transactions Note: All correlations significant at p <.001. Table 7 Service Adoption by Changes, (Kendall s tau-b correlations) All Changes Cost Noncost All services Financial transactions Nonfinancial transactions Nontransactional Note: All correlations significant at p < Public Administration Review May June 2008

9 impact and subtracted from the index for changes. Table 6 presents data for , while table 7 presents data for , only where additional measures were available for both years (cf. tables 3 and 4 ). The data in table 6 for the period show a very modest relationship between the number of noted online services and changes. All correlations were significant at the p <.001 level. However, as indicated by the Kendall s tau-b statistics, none of the strengths exceeded.175. The associations are somewhat stronger for ( 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 transactions, should have a stronger relationship to change. The data for are mixed, but the results for 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 demonstrate 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 attributable 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 connections 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 example, political and legal issues should be more germane to transactional versus informational services. Tables 8 and 9 present correlations between barriers and services. Table 8 presents data for , while Table 8 Barriers by Service Adoption, (Kendall s tau-b correlations) All services Financial Nonfinancial All barriers Technical capabilities Political and *.050 organizational Legal.039** *** Financial ***.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 and.094 for ). 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 established 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 services. 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, encompassing applications (e.g., those involving interactivity and transactions). It may be that these barriers become 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. Additionally, technical barriers inhibit all service levels, so regardless of the stage of e-government development, technical problems may be consistently reported as a primary problem. There is no evidence of a stronger relationship between political and legal barriers to more complex services as might be expected 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, (Kendall s tau-b correlations) All services Financial Nonfinancial Nontransactional All barriers ** Technical capabilities Political and.017 ***.033***.025 ***.000 organizational Legal ***.076 Financial * *** Note: All correlations significant at p <.001 except where noted. * p <.01 : ** p <.05 ; *** p >.05. Models of E-Government 531

10 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 nontransactional 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 information 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 important questions about the principal normative models 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 predictions that governments will move stepwise toward the adoption of more sophisticated e-government offerings, 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 involving cost impacts. And not all the reported changes were positive, even though positive change is an important 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 between 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 problems. 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 adopters versus laggards), and with respect to different types of applications (low-hanging fruit versus high-end applications). This would be a reasonable interpretation 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 barriers 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 transformational 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 sophistication. These theories had virtually no recognition of existing information technology adoption literature, partly because many of these models came from engineering, not business or public administration (i.e., Coursey and Shangraw 1989 ). Expert systems advocates believed that such applications would become increasingly technically sophisticated, 532 Public Administration Review May June 2008

11 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 experienced employees, and expert resistance, among other political and organizational issues. Thus, expert systems, all the rage in the late 1980s, are today an afterthought 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 technology and government that is now 30 years old, or to what little empirical literature about e-government that was available in 2000 and 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 transformation in the relations between citizens and governments 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 innovations. The models were certainly not connected to the research into information technology and government that might have more effectively informed and underpinned their guesses. Empirical findings from this research allow us to make some statements about e-government that provide a better understanding of this phenomenon than is possible from reading the models. Among these statements are at least the following: E-government is mainly an addon 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 reinventing 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 importantly 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 application development, performance, and adoption. Th ese findings should have special meaning for governmental managers. To begin with, managers should be appropriately skeptical of the claims made about e-government. Often, such claims come from a decidedly technologically 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-Government 533

12 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-government 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 delivery and technological advancement approaches dominating 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 information technology theory of reinforcement politics: that information technology is developed and managed 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 underlying decision tasks of organizations? Such an approach has been used for expert systems (e.g., Coursey and Shangraw 1989 ). This would be particularly helpful to developers, as decision complexity, including 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) distribution, regulation, and redistribution typology can anchor e-government in a more purposive cost benefit orientation as a guide to prospective stakeholder 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 results 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 demographics 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 respondents 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 presenting a misleading overestimate of change). Of course, standard statistical analysis presumes sample 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-government experience is significant and not clearly addressed. Unfortunately, this is not directly measured in all three surveys. The ICMA should strongly consider 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. Th ird, we did find that the samples tended to slightly overrepresent council-manager compared to mayorcouncil governments. The exact effect on assessed barriers, changes, and provided services is difficult to ascertain. Presuming that the difference is not attributable to population and potentially larger governments with greater resources, it could simply be that council-manager governments with more professional 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 governments. Clearly, international efforts should be considered in future research development and testing. Finally, the question concerning changes and adoption are simple nominal items that do not consider the maturity and extensiveness of a service delivery 534 Public Administration Review May June 2008

13 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 existence 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-government offerings (not all services are equal), intensity of use (versus simply whether a service exists), and measures of impacts beyond the opinions of local governmental 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 government to government (G2G) rather than inwardly facing (i.e., the automation of routine governmental functions such as finance and accounting and record keeping). References Baum, Christopher H., and Andrea Di Maio Gartner s Four Phases of E-government Model. [accessed January 28, 2008]. Bretschneider, Stuart, and D. Wittmer Organizational Adoption of Microcomputer Technology: The Role of Sector. Information Systems Research 4 (1): Coleman, Stephen, and Donald F. Norris A New Agenda for E-Democracy. International Journal of Electronic Government Research 1 (3): [See the full Oxford Internet Institute Forum Discussion Paper no. 4 at mipar and ] Coursey, David E-Government: Trends, Benefits, and Challenges. In The Municipal Yearbook 2005, Washington, DC : International City/County Management Association. Coursey, David, and Jennifer Killingsworth Managing Web Services: Lessons from Florida. In Handbook of Public Information Systems, 2nd ed., edited by G. David Garson, New York : Marcel Dekker/CRC. Coursey, David, and R. Shangraw Expert System Technology for Managerial Applications: A Typology. Public Productivity and Management Review 12 (3): Danziger, James N Innovation in Innovation: The Technology Enactment Framework. Social Science Computer Review 22 (1): Danziger, James N., and Kim Viborg Andersen The Impacts of Information Technology on Public Administration: An Analysis of Empirical Research from the Golden Age of Transformation. International Journal of Public Administration 25 (5): Davis, Fred D Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly 13 (3): Fountain, Jane Building the Virtual State: Information Technology and Institutional Change. Washington, DC : Brookings Institution Press. Grafton, Carl Shadow Theories in Fountain s Theory of Technology Enactment. Social Science Computer Review 21 (4): Hiller, Janine S., and France Bélanger Privacy Strategies for Electronic Government. Washington, DC : IBM Center for the Business of Government. HillerReport.pdf [accessed January 28, 2008]. Holden, Stephen H., Donald F. Norris, and Patricia D. Fletcher Electronic Government at the Local Level: Progress to Date and Future Issues. Public Productivity and Management Review 26 (3): International City/County Management Association (ICMA) Municipal Yearbook. Washington, DC : International City/County Management Association. Kraemer, Kenneth L., and John L. King Information Technology and Administrative Reform: Will E-Government Be Different? International Journal of Electronic Government Research 2 (1): Models of E-Government 535

14 Kraemer, Kenneth L., William H. Dutton, and Alana Northrup The Management of Information Systems. New York : Columbia University Press. Layne, Karen, and Jungwoo Lee Developing Fully Functional E-Government: A Four Stage Model. Government Information Quarterly 18 (2): Lowi, Theodore J The End of Liberalism: Ideology, Policy, and the Crisis of Public Authority. New York : W. W. Norton. Norris, Donald F., and Benjamin A. Lloyd The Scholarly Literature on E-Government: Characterizing a Nascent Field. International Journal of Electronic Government Research 2 (4). Norris, Donald F., and M. Jae Moon Advancing E-Government at the Grass Roots: Tortoise or Hare? Public Administration Review 65 (1): Norris, Pippa Digital Divide: Civic Engagement, Information Poverty, and the Internet Worldwide. Cambridge : Cambridge University Press. Ronaghan, Stephen A Benchmarking E-Government: A Global Perspective. New York : United Nations Division for Public Economics and Public Administration and American Society for Public Administration. documents/un/unpan pdf [accessed January 28, 2008]. Wescott, Clay E-Government in the Asia- Pacific Region. Asian Journal of Political Science 9 ( 2 ): Did you know Any university that has a current, paid subscription to PAR may make copies for course-pack use provided the copies are not being made/distributed for commercial gain. That means it s easier than ever to use PAR in the classroom! Check with your university library for more information. 536 Public Administration Review May June 2008

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