In spite of attempting to implement e-government innovations to enhance efficiency in public organizations for several decades, e-government innovation has often not met the expectations of citizens, legislatures, or the organizations. Although a wide range of causes from poor planning to improper implementation have been suggested for explanation of failures, it is still challenging to theoretically construct an explanation of what the overarching dynamic is behind those causes. To further develop the understanding of the conditions of unrealized benefits of e-government innovation, we propose a conceptual framework of a knowledge vacuum, which is an organizational condition in which excessive exploration and organizational inertia interact to create a vicious cycle of low performance. We first review the history of e-government and factors that affect the success and failure of e-government innovation. Next, we develop the conceptual framework, and apply the concept to review an e-government innovation failure case for an illustrative purpose. We conclude by discussing theoretical and practical implications of the conceptual framework and its limitations in understanding the current state of e-government innovations.
The public sector has been attempting for several decades to implement e-government innovations in order to improve the effectiveness, efficiency, responsiveness and creativity in public organizations (Chen & Perry, 2003; Coursey & Norris, 2008; Moon, 2002; Wood, Bernt, & Ting, 2009). However, there are many cases of low performance and failures, and many examples of e-government implementation that have not met the expectations of citizens, legislatures, or the organizations (Anthopoulos, Reddick, Giannakidou, & Mavridis, 2016; Askim, Christensen, Fimreite, & Laegreid, 2010; Holmes, 2005; Morgeson III & Mithas, 2009; Moynihan & Lavertu, 2012). When looking at the history of e-government innovations, scholars find that they have not been a well-planned, coherent movement; instead, they are rather fragmented attempts (Dawes, 2008) driven by different factors such as technological innovations, political pressure, or even precedent failures. New technologies as well as innovative information, management and communication approaches seem to provide optimism, but until recently scholars still remain cautious. Causes of these broken promises have been investigated by scholars, from the planning to the implementation stage across the domains of technology, management, regulation, and environment (Gil-Garcia & Pardo, 2005). Although the literature suggests which factors may help explain e-government success and failure, it is still necessary to design a comprehensive theoretical framework through which we can more systematically understand the relationship among causes of e-government success and failure. One venue to develop a theoretical framework is to elucidate the dynamic nature of e-government innovations through the learning perspective. Innovation research has been closely related to the organizational learning literature (Borins, 2001; Brown & Brudney, 2003; Cohen & Levinthal, 1990; Moynihan & Lavertu, 2012; Salge, 2010). Recent policy implementation research has also paid increasing attention to the role of organizational and social policy learning to better understand the dynamic of policy decisions, implementation and evaluation (Bennett & Howlett, 1992; Dunlop, 2017; Hall, 1993; Howlett, Ramesh, & Perl, 2009; May, 1992; Moyson, Scholten, & Weible, 2017). Both literatures emphasize that learning lies at the center of the dynamic aspect of the causes of innovation success and failure.