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E-Government, or e-gov, is the use of information and communication technology to disseminate information and services by governments. For nearly two decades, e-government has been hyped as a game changing web-based solution to many of the challenges of public administration and a means to greater political participation and knowledge for American citizens (Layne & Lee, 2001; Tat-Kei Ho, 2002; Carter & Bélanger, 2005). Many studies have focused on the supply of various services offered by local and national governments (Moon, 2002; Tat-Kei Ho, 2002; Chadwick & May, 2003). Several studies find inconsistent adoption of services by governments (Layne & Lee, 2001), and limited utility and usage rates among citizens (Gilbert & Balestrini, 2004; Welch et al., 2005). While these studies have explored the adoption and use of new digital tools by local, state, or federal governments, and the utility of these services for citizens, they have generally focused on snapshots based on data collected at one particular moment and do not take into account changes over time. This study expands the time line in which e-government adoption is considered, exploring the level of diffusion of e-government by cities across time.
This study evaluates changes in e-government since 2001 by analyzing the diffusion rates of various types of e-government services by cities across the United States. Analysis of numerous E-Government surveys conducted by the International City/County Management Association (ICMA) from 2001-2011 provide an early trendline of e-government services offered during a ten-year period which witnessed massive growth in high-speed internet access, interactive apps, social media, and greater mobility. Original content analysis of local government websites and mobile apps in 2014 and 2019 offer both an extension of these e-government diffusion timelines beyond 2011, and a clarification of which types of e-gov tools are being used extensively (i.e. information dissemination, city codes, and documents), and which are used more sporadically (i.e. financial tools, social media, and interactive tools). The 2014 sample includes 83 cities randomly selected from all cities with populations over 50,000, representing over 10 percent of medium and large size cities in the U.S. The 2019 data set included a similar sample size including a subset of 50 cities that were the same as those sampled in 2014. This offers the ability to compare how individual cities changed their e-gov adoption from 2014-2019 and also how the diffusion of e-gov adoption changed overall during that 5-year period. The findings of this study provide a clear picture of the diffusion of e-government services over a nearly 20-year period, offering important context regarding the reality of e-gov adoption over time, and a different perspective than studies which have evaluated any single point during that period. Adoption and diffusion of e-government services have been neither steady nor uniform. The findings offer insights into the characteristics of cities that have adopted e-government innovations earlier than others (i.e. population size, per capita income, and government type) and what services are more or less likely to be widely adopted. These findings contribute to a broader conversation about how the adoption of new communication technology is affecting the relationship between citizens and their governments throughout the majority of the internet era.