Abstract
Recently, the Tanzanian government has started making m-government initiatives. However, little is known about the factors and conditions surrounding m-government adoption in Tanzania. Consequently, some m-government services have been successfully adopted while others are still struggling (having a low level of adoption). This study investigates critical success factors (CSFs) that led m-government services belonging to the same family to have varying degrees of adoption level. The study employs a set of web analytics tools that monitored and analyzed the traffic data of the selected three m-government services. The results show that inspecting the web analytics data from multiple viewpoints and varying levels of detail gives insights on the CSFs towards the adoption of m-government services. The findings suggest that perceived usefulness, user needs, and usability favor the adoption of one m-government service over the other.
TopBackground
Web Analytics (WA) refers to the assessment, compilation, review, and reporting of web-based data with the aim of better understanding and improving web use (Sleeper, Consolvo, & Staddon, 2014). We can, for example, use WA to track the number of visitors, where they came from, how many times they visited, how far the visitors explored the site and where they went next. (Clifton, 2012). Web analytics’ strength lies in its ability to deliver unbiased results, overcoming the shortage of experts, being low cost, and evades inconsistent results from experts (Dingli and Misfud, 2011). Moreover, WA collects data from the user’s unobtrusiveness.
Key Terms in this Chapter
Number of Requests: The total number of requests needed to be executed to retrieve a complete web page.
Organic Search Results: The size (in bytes) of the web page that is rendered by the browser when it is requested.
Page Size: The size (in bytes) of the web page that is rendered by the browser when it is requested.
Accessibility: The ease with which an e-government medium may provide information and services.
Loading Time: The amount of time needed by the browser to load and display the web page.
Direct Traffic: Traffic generated from users familiar with the site name, and they go directly to the website by typing the site URL.