Since the last decade, e government has assumed an important consideration in IS field research. This section explores the concept of e government using the available literature to give the present study a deeper understanding of e-government. The review of literature will, among other things, provide varied definitions of e government, illustrate e government categories, and provide insights into the different models of e government development. Finally, a conclusion of the section will be provided.
E government concept and definitions
|“e government is the continuous optimization of service delivery, constituency participation and governance by transforming internal and external relationships through technology, the Internet and new media”||Gartner (2000)|
|Electronic Government (e-Government) is the use of technology, especially Web-based applications, to enhance access to and efficiently deliver government information and services||Brown and Brudney (2001)|
|e government means services by the government and its authorities provided online, and which has the potential to improve the relationship between administration, citizens, and business and includes all administrative measures at all levels||Oberer (2002)|
|“e government refers to the use by government agencies of information technologies (such as Wide Area Networks, the Internet, and mobile computing) that have the ability to transform relations with citizens, businesses, and other arms of government”||The World Bank (2004)|
|“Means of delivering government information and service”||Moon and Norris (2005)|
|“The use of modern ICTs to deliver public services to citizens and businesses. It entails the transformation of public services to citizens using new organizational processes and new technologies”||Gunter (2006)|
|“The use of information technology to enable and improve the efficiency with which government services are provided to citizens, employees, businesses and agencies”||Bélanger and |
There are many definitions of e government that have emerged over the past decade based on different theoretical streams formulated and published by different academics. In table 1we illustrate these definitions in order of date of publication.
Table 1 : e government definitions
With these salient definitions we can abstract that the most e government elements are service, technology and transforming relations. Table 2 illustrates the existence of these elements in all used definitions.
|The World Bank (2004)||√||√||√|
|Brown and Brudney (2001)||√||√|
|Bélanger and |
|Moon and Norris (2005)||√|
Table 2 : e government definition’s elements
From the table above it can be seen that The World Bank (2004), Gartner (2000) and Gunter (2006), have the broadest definition of e government as they document the cardinal elements of Service, Technology and Transforming relations as conceivable constructs to e government. On the other hand, Moon and Norris (2005) have the most constrained definition of e government as the only document the element of Service.
However, to give e-government definition more clarity and deeper perspective, it is imperative to expound on the cardinal elements that have been used in e-government’s definitions, which are Service, Technology and Transforming relations.
Service has been defined as “any act or performance that one party can offer to another that is essentially intangible and does not result in the ownership of anything” (Kotler & Keller 2006, p. 402). In the context of e-government, the concept of e-service may be defined as “providing a superior experience to consumers with respect to the interactive flow of information” (Rust & Lemon 2001, p. 86).
Technology in the context of e-government refers to the use of ICT, particularly the Internet, in the provision of various information and public services over the Internet (Elsheikh 2011; Belanger & Carter 2009).
Transforming relations in the context of e-government refers to the transformational process of a government, involving the transformation of critical activities and processes of public administration using a variety of means to not only improve the interaction and communication with the public, but also to provide services tailored to their circumstances and needs (Liao et al 1999; Elsheikh 2011).
The present study relies on Gunter’s (2006) definition, which explicates e government as “the use of modern ICTs to deliver public services to citizens and businesses…It entails the transformation of public services to citizens using new organizational processes and new technologies” (p. 362).
E government categories
e government can be viewed as relationships among citizens, government entities, businesses and employees, and its functionality (when one physical system may include functionality from more than one category) can be classified into the four main categories as listed in Table 3.
|Government to Citizen||G2C|
|Government to Government||G2G|
|Government to Business||G2B|
|Government to Employee||G2E|
Table 3 : e government categories
Government to Citizen (G2C)
This category specifies the relationship that exists between the citizens and their government. The citizens, in this case, represent the stakeholders or voters from whom the government derives its legitimacy. The government uses this channel to communicate details regarding activities within the public sectors, to include the citizens’ input in decision making within the public sector, and to offer improved services in terms of cost, convenience and quality (Heeks 2002; Laukkenen et al 2007).
Government to Government (G2G)
This category specifies the relationship existing between organizations or agencies within the government or between organizations within different governments (Ndou 2004). The government relies on several agencies or organizations within it to effectively delegate duties and deliver quality services (Riley & Okot-Uma 2001). There is a great need to ensure that such agencies are able to communicate effectively and efficiently. This, in turn, ensures that such organizations have a single access point. Through online communication, such organizations can share resources, databases and pool capabilities and skills, hence ensuring that processes are carried out in an efficient and effective manner (Ndou 2004).
Government to Business (G2B)
This category specifies the relationship existing between private businesses and agencies of the government. Currently, businesses have adopted e-commerce to facilitate business interactions between themselves. E-government ensures that such businesses can carry out business transactions with the government in an environment where red tape is significantly reduced, hence not only simplifying business processes but also ensuring that business remains competitive (Ndou 2004).
Government to Employee (G2E)
This category specifies the government’s relationship with its employees. E-government is used in such a case to facilitate effective interaction between the government and its employees (Ndou 2004). Services included under this category of e-government include facilitating the transfer of information on government policies, rules and civil rights (Carbo & Williams 2004).
The categories mentioned above show interactions that take place between the government and other different parties. The different parties in this case are either individuals or organizations, and hence e government basically entails government’s interaction with individuals or organizations with the intent to simplify, streamline and control the costs of its operations (Singh & Das 2007). Interaction between the government and individuals is represented by either G2E or G2C, while that between the government and the organizations is represented by either G2G or G2B.
e government development models
There are different levels of transformational processes that are used in the implementation of e-government. In order to fully grasp the concept of the transformational factors, it is imperative for one to identify the varied phases of e-government. There exists literature on e-government that tries to explain the innovative approach by describing the phases of e-government in terms of their organizational complexity as well as their level of technology (Layne & Lee 2001). This has been done from the simple stance of developing web pages to the complex tasks of integrating government applications through the web interface, and depicts the different phases that a government evolves to. Academics demonstrate that these different phases are an indication of varied levels of citizen orientation, innovation in technology and administrative change (Lin et al 2007; Chen & Mort 2007).
Two of the most important studies regarding stages of e government development include:
The four-stage model (Layne and Lee 2001)
This model represents an incorporated approach to E-government and illustrates the various developmental phases that the concept undergoes. When followed in the correct order, these phases result in an e-government initiative that is fully integrated. The four phases for development of e-government in their correct order include cataloguing, transaction, vertical integration and horizontal integration. Figure 1 below illustrates these phases in their correct order. The details of each of the phases are followed by the four stage model represented by figure 1.
- Cataloguing – this stage involves focusing all government efforts to set up an on-line presence. The stage also involves web development initiatives and all functionalities focused on presenting government information on-line. Extant literature demonstrates that the cataloguing phase is mostly pushed on by the demands of the citizens, resulting in pages or a portal through which the citizens can retrieve and download electronically organized government information (Layne & Lee 2001).
- Transaction – this phase facilitates direct interaction with the government through interfaces, and involves creating a connection between the government’s internal systems with on-line interfaces, thus providing live access to the government’s databases. The stage, according to available literature, supports online citizen’s services such as paying of fines, renewing licenses, etc (Layne & Lee 2001). However, with an increase of such services, it will be prudent for the government to integrate the different systems that are found within the different states to the on-line interfaces.
The demand for these services and facilities will continue to increase rapidly due to the benefits realized. In this case, the government will be required to integrate all underlying processes. The interaction within the different levels of government agencies and the different functions will ensure that citizens visualize the government as a “One Stop Shop” for information (Layne & Lee 2001). This, in turn, ensures that inconsistencies and redundancies are eliminated within the databases. Integration of information from the different government levels may be achieved in two ways; horizontal and vertical.
- Vertical integration – this involves creating a connection of services and functions on the following levels of government; federal, state and local (Layne & Lee 2001). For example, a state’s DMV system may be connected to the national database containing a list of all licensed truck drivers. Such seamless integration of the different government levels ensures that there is cross checking and referencing.
- Horizontal integration – this, on the other hand, involves integration of functions and services. Databases are maintained within the government facilitating communication and knowledge sharing between the different services and functions. An instance of this would be facilitating concurrent payment of unemployment insurance and business taxes to two different government agencies whose systems are able to communicate (Layne & Lee 2001).
The five-stage model (United Nations 2008)
The five-stage model, conceptualized by the United Nations, ranks the performance of countries through the use of an index. The index in this case is determined by the member state’s on-line presence and previous sophistication levels. The higher a country is according to the stages, the higher its index rank among the other member states.
The five-stage model dictates that member states are supposed to move up from emerging to connected stage. This movement through the stages involves various aspects that should be adhered to including: data management, business re-engineering, security, infrastructure development, customer management and content delivery. Obviously each of the states will undergo varied challenges in order to reach connected stage, but the rate of moving up the pyramid is intrinsically determined by individual state’s approach to the challenges (United Nations 2008).
The index measure is an indication of a state’s ability to distribute on-line services to its citizens (Davies 1996; United Nations 2008). The various stages are discussed below.
Stage 1 Emerging information services: In this stage, the government has established an on-line presence through an official website or several web pages. However, there are no links between the different government agencies such as departments of education, labor, health, etc. At this stage, the government has very little or no interaction with the public and the information stored is static (United Nations 2008).
Stage 2 Enhanced information services: It this stage, the government establishes some form of interaction with the public by availing information regarding governance and public policy (United Nations 2008). Links to archived information has been established providing the public with information such as laws, forms, regulations, documents, reports and newsletters (United Nations 2008).
Stage 3 Interactive services: It this stage, the government is able to support interaction with its citizenry. For example, through the e government platform, citizens are able to pay taxes through downloadable forms and can also renew licenses through on-line applications (United Nations 2008). Interactive portals or websites are established to ensure better delivery of services to the public (United Nations, 2008).
Stage 4 Transactional services: this involves a transformational process whereby the government initiates interactions between the government and its citizens. This is a two-way interaction that may include such services as license and passport renewals, application for passports, birth certificates and ID cards etc (United Nations 2008). At this stage, all transactions between the government and its citizens are carried out online (United Nations 2008). Also included in this stage, are government to citizens interactions and 24/7 access to on-line services.
Stage 5 Connected services: In this stage, the government has established itself as a “connected entity” that efficiently and effectively responds to citizen’s needs (United Nations 2008). This stage represents the highest level of a government’s initiative to establish an on-line presence (United Nations 2008). The following are the characteristics that determine whether a state has attained this level of sophistication in terms of on-line presence.
- Vertical integration – this is integration between the different levels of the government. For example, between the federal level and the local level.
- Horizontal integration –this is integration of services and functions within the government.
- Infrastructure integration – this involves resolving all interoperability issues that may arise as a result of integration.
- Stakeholder integration – this involves proving links between the private sector, NGOs, government, civil society, academic institutions, etc.
- Integration between the citizens and the government – in this stage, the government encourages and supports citizens’ inputs and participation to be involved in decision making.
Citizen definition and citizen in e government context
A citizen may be referred to as a part of a sovereign group (“Citizen”). This concept is used to refer to a group of people within a nation who are entitled to certain rights and privileges. It is common for a government of the said nation to support such rights and facilitate services for its citizens (Misra 2007).
In the context of e government, a citizen refers to the intended users or beneficiaries of the e government technology (Misra 2007). E government is used as a communicative tool that the government can use to communicate to its citizens (Misra 2007). Given that the term citizens refers to members of a sovereign state, this situation leads to a predicament whereby the government has to understand the needs of its citizens if it has to ensure effective delivery of services (Misra, 2007). This scenario is brought by the fact that there exist diverse people within a nation, with different characteristics, age-categories as well as ethnicities. These differences need to be understood and acted upon, especially when delivering a product to such people. As noted in the literature, all these citizens, who are of diverse nature, are the intended recipients of the e government tool (Misra 2007). Through this tool, the government will be able to pass on information to its citizens or receive suggestions etc.
This section has explored the concept of e-government using the available literature. The section has dug into extant literature to define the e government concept before illustrating e government categories and then analyzing the different models of e-government development. From the e-government literature review done in this section, we can reliably conclude that the concept of e-government focuses on the elements of Service, Technology and Transforming relations. In addition, we can demonstrate that there are four categories of e-government, which are government to government, government to business, government to citizen and government to employee. Finally, we are able to find out that the stages of e-government reflect their degree of technological and organizational sophistication, from the development of Web pages to the integration of internal government systems through a web interface.
In the academic domain, extant literature demonstrates that the concept of technology readiness was initially formulated to measure people’s general beliefs about technology (Chen & Mort 2007). This section aims to, among other things, provide varied definitions of the technology readiness concept, illuminate some technology readiness models, as well as analyze literature on user readiness factors.
Technology readiness concept and definitions
|Parasuraman 2000; Parasuraman and Colby 2001||Individual||“People’s propensity to embrace and use new technology for accomplishing goals in home life and at work”|
|Department of Defense; NASA; Lee et al 2011||System||“It is the measure used to apprehend the evolution or maturity of technology”|
|The Economic Intelligence Unit||Government||“It refers to the ICT infrastructure, socio-economic, culture, and legal policies. Likewise, the business environment and the user adoption of the technology are also given ample consideration”|
|Del Aguila – Obra and Padilla- Meléndez 2006; Laukkanen et al 2007; Mallat et al 2006; Richey and Auntry 2009; Yu and Tao 2008||Organization||“The strategic cooperation among the management, employees, business environment, and consumers are the integral factors determinative of the technological readiness of the organization”|
Table 4 : Technology readiness definitions
Table 4 shows the various definitions of technological readiness. However, by looking at the various definitions, it can be gleaned that technological readiness is approached from several viewpoints. Figure 3 shows the different perspectives of technological readiness.
The figure above shows that the current definitions of technological readiness are definitive when it comes to how technological readiness can be measured or apprehended from different perspectives. In the opinion of Lin, Shih and Sher (2007, p. 643), technology readiness concept “…can be viewed as an overall state of mind resulting from a gestalt of mental enablers and inhibitors that collectively determine a person’s predisposition to use new technologies.” These authors further observe that technology readiness basically conceptualizes the people’s general beliefs about emergent technology, and is intrinsically associated with their use of technology-based products and services.
As reported by Chen and Mort (2007), a mass of evidence, from anecdotes to recent studies, demonstrates that the construct of technology readiness has four sub-dimensions, namely optimism, innovativeness, discomfort and insecurity. While optimism relates to a positive perception of technology and a sustained belief that technology provides people with heightened control, flexibility and efficiency, innovativeness in the technology readiness context denotes a tendency to be a technology pioneer and thought-leader (Lin et al 2007). Similarly, discomfort in the technology readiness context is described as a perception of lack of control over technology and a disjointed feeling of being overwhelmed by it, and insecurity is viewed as a distrust of technology and cynicism about its capability to function properly. In yet another published article, Lin and Shi (2007) argue that in the context of technology readiness, optimism and innovativeness are perceived as motivating factors, while discomfort and insecurity are seen as inhibitors. The bottom-line of this argument, as acknowledged by Chen & Mort (2007), is that people may hold both positive and negative perceptions about technology; that is, they can be arrayed along a technology beliefs continuum, anchored by strongly positive perceptions at one side and strongly negative perceptions at the other.
Technological readiness model
Among the increasing research highlighting technology readiness, the technology acceptance model (TAM) developed by Davis in 1989 for utilization in the organization context is still favored by academics and practitioners, in large part because of its robustness as well as simplicity (Chen & Mort 2007). Rooted in the Theory of Reasoned Action (TRA), “…TAM is a specific and parsimonious framework for predicting and explaining people’s adoption of information technology in work settings” (Lin et al 2007, p. 643). In IS context, TAM hypothesizes that user acceptance of new technology is to a large extent determined by the user’s intention to utilize the technology, which, in turn, is not only influenced by the user’s set beliefs about the technology’s perceived usefulness, but also by its perceived ease of use. Perceived usefulness has been defined by Lin et al (2007, p. 643) as the “…extent to which a person believes that using a particular system will enhance his or her performance, and perceived ease of use refers to the extent to which a person believes that using a particular system will be free from effort.” A study conducted by Lin et al (2005) cited in Chen & Mort (2007) found that the two constructs (perceived usefulness and perceived ease of use) function as key mediators between technology readiness and use intention, and were vital in influencing consumer’s intentions to use e-services.
User’s readiness factors
As postulated by Kottemann and Boyer-Wright (2010), readying users to transition to the intensive mechanisms of new technology necessitates progress along a multiplicity of socioeconomic as well as behavioral dimensions. A close scrutiny of extant literature on technology readiness reveals several user readiness factors. In their study, Chen & Mort (2007) view usefulness and convenience as two of the most important factors that come into play in readying user to transition to technology use. Lin et al (2007, p. 643) mentions several user readiness factors, including “…training, support, perceived accessibility, social influence processes, and cognitive instrumental processes.”
This section has analyzed literature on technology readiness, from providing varied definitions to the concept to analyzing its different perspectives, presenting a technology readiness model, and explicating some of the user readiness factors mentioned in the literature. From the exposition of the literature, we can conclude that the concept of technology readiness focuses on the people’s propensity to not only embrace but also use new technologies, with the aim to accomplish objectives in home life and at work. We can also demonstrate that technology readiness can be approached from a number of viewpoints, namely government, individuals, organization and system. Furthermore, we have produced evidence to demonstrate how TAM can be used as a model for technology readiness. Finally, we have illuminated some user readiness factors that cover socioeconomic as well as behavioral dimensions.
Technology usage refers to the use of a new or existing technology. Extant literature demonstrates that information systems research must incorporate an extensive understanding of the factors that affect or influence an individual to accept or use a certain technology (Venkatesh, Thong & Xu 2012). This, in the view of Bavec (2006), entails looking into an individual, in this case, a citizen and understanding forces or motivators that drive them towards technology. In this section, we illuminate the most popular acceptance models that have been applied in IS research. Afterwards, we illustrate how far they have been used in e government context before summarizing the analysis in the conclusion.
Technology Usage Models
There are many models that have been formulated to predict the use of an information system by the destined users. However, of all these models, the Technology Acceptance Models (TAM) and the unified theory of acceptance and use of technology (UTAUT) have generated huge interest and are still favored by many in academics and IS practice (Chen & Mort 2007; Venkatesh et al 2012).
Technology Acceptance Model (TAM)
During the 1970’s it was observed that the adoption of many systems faced various barriers and resulted in their failure. This led to concerted research aimed at identifying the various factors that influenced an individual to accept or reject a system. The research crystallized into the proposal of the TAM by Davis in 1985 (Davis 1986). The TAM model was derived from the discipline of psychology and was initially grounded on the Theory of Reasoned Action, which attempts to explain and understand human behavior. Davis adopted this theory and structured it to fit and explain the acceptance of technology among the intended users. The researcher argued that an individual’s desire to accept or reject a system was reliant on three critical characteristics, namely the expected ease of use, an individual’s mind-set towards the system, and the intended use of the system (Chuttur 2009). Figure 4 shows the dynamics of the Technology Acceptance Model.
Previously some studies had proposed the relation between ease of use and usefulness of a technology with the behavior of an individual. According to Robey (1979), in his works replicated from Schultz and Slevin (1975), there exists a link between observable usefulness and the usage of the system. Bandura (1982) further reinforced this view by demonstrating that an individual’s behavior is best envisaged through one’s efficacy as well as the final outcome. One’s efficacy is equated to the ease of use of a technology in question, whereby a judgment of how one is able to handle a set course of actions is carried out. On the other hand, the final outcome refers to the expected usefulness of the technology.
In yet another influential research, Swanson (1982) concluded that both perceived usefulness and ease of use were the main determinants of human behavior. According to this particular researcher, individuals are likely to choose and use data reports on the basis of the data quality and its cost of access. In this scenario, the quality of the data report refers to the observable usefulness of the report in regard to its data while the cost of access can be equated to the ease of use. In conclusion, Davis (1986) discovered that an individual’s use of or lack of use of a system was based on the belief of such a system benefitting them or helping them carry out their work easily.
Unified Theory of Acceptance and Use of Technology (UTAUT)
According to Venkatesh et al (2003), the UTAUT was developed as a synthesis that was comprehensive enough before the technology acceptance research came into being. The UTAUT has four key constructs, namely: performance expectancy, its effort expectancy, the conditions that facilitate it and its social influence. These are the four constructs that have an influence on technology use and the UTAUT’s behavioral constructs. Venkatesh et al (2012) adopted these constructs from the user’s use and how they accept technology. Extant literature demonstrates that while performance expectancy refers to the level in which benefits are retrieved when technology is used to perform specific activities, effort expectancy refers to the level in which users can use technology with ease and how they can access it easily (Venkatesh et al 2012). The construct of facilitating conditions refers to (1) the support that can be awarded to the users from the support, (2) the perceptions in regard to technology which users may have developed. Lastly, there is the social influence construct, which refers to the level in which a user may perceive technology to be critical to other users, including friends and relatives (Venkatesh et al 2012). Figure 5 shows the model of Unified Theory of Acceptance and Use of Technology.
According to UTAUT, the four constructs are based on the different theories of technology acceptance so as to give an account of how technology is used and the behavioral intention of technology. The conditions that are facilitated usually determine how technology may be used (Venkatesh et al 2012). Additionally, variables and personal differences in users also contribute to the relationships in which UTAUT is moderately theorized. The variables may include the user’s experience with technology, age and gender (Venkatesh et al 2012).
In addition to describing technology usage and acceptance, this section has also analyzed two models that are mostly used in IS research to provide insights into the processes that come into play to affect or influence an individual to accept or use a certain technology. The two models, namely TAM and UTAUT, helps us understand the motivators and inhibitors that either drive people to, or inhibit them from, using technology. In TAM, we have acknowledged the fact that an individual’s desire to accept or reject a system is essentially reliant on three critical characteristics, namely the expected ease of use, an individual’s mind-set towards the system, and the intended use of the system. In UTAUT, we have underlined that an individual’s desire to accept or reject technology is presumably influenced by four dimensions, namely: performance expectancy, its effort expectancy, the conditions that facilitate it and its social influence.
Technology Usage and Citizen’s Readiness in E Government
To date, there exists a huge research gap in technology acceptance and readiness, especially in e government context. Most of the models used to demonstrate technology usage and citizen’s readiness in e government, including TAM and UTAUT, are deeply rooted in organizational life, yet researchers have been slow in developing newer models to coincide with the mounting technology usage across governments (Chien-Hung & Mort 2007; Singh & Das 2007). This section reviews some of the limitations in acceptance and readiness studies, in addition to analyzing the limitations posed by the TAM and UTAUT models in explaining technology usage and citizen’s readiness in e government context.
The limitations in acceptance and readiness studies
An important proportion of citizen-centric e government studies that have been conducted over the years primarily focus on the subsequent acceptance of e government services. Such studies have attempted to predict users’ reception of technology as an indicator that could be used to understand human behavior with technology, with the view to analyzing how such technology could be increased. Table 5 shows a random selection of the citizen-centric e-government publications illustrating how acceptance informs the focal consideration of these studies.
|Author||Theory or Model used in the study|
|Al-Adawi et al (2005)||Extended technology acceptance model|
|Alsaghier et al (2009)||Extended technology acceptance model|
|Rokhman (2011)||Diffusion of Innovation|
|Kumar et al (2007)||Extended technology acceptance model|
|Susanto and Goodwin (2010)||Technology acceptance model and the unified theory of acceptance and use of technology|
|Chan et al (2010)||Extended unified theory of acceptance and use of technology|
|Dimitrova and Chen (2006)||Diffusion of innovation and technology acceptance model|
|Lai and Pires (2010)||Technology acceptance model and end user satisfaction theories|
|Carter and Belanger (2004)||Diffusion of innovation|
|Mahadeo (2009)||Diffusion of innovation|
|Wangpipatwong et al (2008)||Extended technology acceptance model|
|Mofleh and Wanous (2008)||Technology acceptance model and diffusion of innovation|
|Chee-Wee et al (2010)||Service quality model|
|Suki and Ramayah (2010)||Extended technology acceptance model|
Table 5 : Analysis of Citizen-Centric e Government studies
Despite the domination of studies primarily interested in using acceptance models in e-government research, it must be noted that acceptance models continue to attract criticism for their insensitivity to different use contexts (Salovaara & Tamminen, 2009). For example, it is easy to notice that within e government context, the adoption and acceptance of technology has been studied without giving due attention to individual’s readiness.
To explain the importance of citizen’s readiness within e government context, it should be noted that studies of acceptance models in organizations have implicitly discussed the factors of readiness already provided by organizations, including equipment, network, and awareness, but fail to account how users are willing to use the technology. The predisposition generated by these models, hence, leads to an implicit assumption that the user is always ready to use technology, but nevertheless fails to provide an account on the user’s willingness to use technology. But within e government context, it must be explained how the user is willing to use the technology and how interested parties bring the citizen into the acceptance step, primarily because the technology provided is to be consumed by citizens only.
To support this idea, the technology acceptance model (TAM) has been developed by Davis (1986, 1989) within organizational context. Additionally, the unified theory of acceptance and use of technology (UTAUT) has also been developed by Venkatesh et al (2003) within organizational context. However, nearly all researchers who apply these models to e government contexts do not take into account the fundamental importance of citizen’s readiness in the usage process. But this should not be the case as postulated by Ismail (2008), who in his thesis finds that readiness factors have a significant impact on increasing citizens’ usage of e-government services.
In their contribution to extant literature on user acceptance, Venkatesh et al (2012) state that the employment of any theory in new context not only results in changes in the direction of relationships, but also alters the magnitude of the relationships and generate new ones. These authors add that the unified theory of acceptance and use of technology (UTAUT) has been developed to understand the “employee” acceptance and use of technology, thus the importance of examining it in a different context to accommodate citizens rather than employees. In addition, they emphasize about taking into account the differences between “organizational use sitting” and other use sitting (Venkatesh et al 2012).
Further analysis of existing literature demonstrates that few studies have emerged as a direct consequence of insensitivity of acceptance models. These studies deal with individual’s readiness to use technology outside the organization, hence try to develop models to understand this important aspect. However, the studies do not take into account the step of acceptance in usage process, in addition to presuming that the user is already an acceptor of technology. Additionally, the studies underline the fundamental impact of readiness factors, but to a large extent fail to provide an explanation on how these factors lead to successful usage process. The Figure below demonstrates the research gap in acceptance and readiness studies.
Figure 6 : Research gap in acceptance and readiness studies
This section has, among other things, summarized published articles on citizen-centric e government to demonstrate the limitation in theoretical orientation in studies essentially interested in using acceptance models in e government research. From the analysis, we can conclude that most acceptance models not only continue to attract criticism for their insensitivity to different use contexts, but also fail to account how users are willing to use the technology. To be precise, these models generate an implicit assumption that the user is always ready to use technology, but nevertheless fails to provide an account on the user’s willingness to use technology. The main argument in this section is hinged on the understanding that models used in e government context must at least explain how the user is willing to use the technology and how interested parties bring the citizen into the acceptance step, primarily because the technology provided is to be consumed by citizens only
This section seeks to analyze the process theory and illuminate its advantages when used in IS research. As will be seen during the analysis, many studies of technology usage use variance theoretical perspective irrespective of its shortcomings in explaining fundamental processes that lead to the adoption of the technology or, in a much explicit way, to the intention to use the technology (Singh & Das 2007; Tiamiyo & Ogunsola 2008). Additionally, the section will illuminate the rationale towards the choice of the process theory as the research model, before theorizing the model. Finally, the section will analyze some dimensions related to the intention to use e government.
Variance theory Vs process theory
Theory can be considered from two different perspectives, namely the variance theoretical perspective and the process theoretical perspective. Process theory has been introduced to IS field by Markus and Robey (1988), and extant literature reveals that it continues to be used in a range of studies though in a far much less context than variance theory (Burton-Jones et al 2011).
To provide a critical analysis of the differences between variance theory and process theory, it is important to note that variance theory is based on a factor model that not only seeks to causally link variables with each other, but also to assess the extent of these links between variables, with the view to explain variation in dependent variables as caused by the variations of one or more independent variables (Radeke 2010).On the other hand, process theory seeks “…to explain by identifying sequences of actions that lead to outcomes if specific antecedent conditions are fulfilled” (Radeke 2010, p.3). In other words, process theory is primarily concerned with understanding how phenomena evolve over the course of time, and also why they evolve in this way (Langle 1999).
Extant literature characterizes the process theory using three main components, namely: (1) the process itself, (2) the causal factors, such as contextual or antecedent conditions that shape the evolution of the process, and (3) the consequential factors, such as impacts or outcomes that are caused by the process (Radeke 2010).
In IS research, a dynamic phenomenon such as technology usage, which is known to be dominated by variance theories, has been explained by focusing on the static aspects in the form of variances in independent and dependent variables for purposes of determining the degree or extent of relationships between variables. Consequently, these models widely omit any sequential or temporal details that may form a critical component of this relationship (Ramiller & Pentland 2009). However, the process theory overcomes these limitations by emphasizing the dynamic view of the phenomena because it “…seeks to explain how independent variables (e.g., the context) shape the evolution of the process and, in turn, how the process influences dependent variables (e.g., outcomes)” (Radeke 2010, p.2). To simplify the discussion on variance and process theories, table 6 illustrates the three important components of these theories.
|Concept||Focuses on properties of entities, often called variables or factors||Focuses on entities participation within the events |
The ability to act by entities is considered important in deciding if they are major actors or not
|Relationship||Focuses on variation among the values of properties.||Focuses on outcomes that result from the sequence of events involving the major actors.|
|causal logic||It is said to assume necessary, sufficient, and efficient causality.||It is said to use necessary, final, formal, and efficient causality.|
Table 6 : The three components of variance and process theories (Burton-Jones et al 2011)
Burton-Jones et al (2011) give an example of DeLone and McLean’s IS Success Model (ISM) from the two different perspectives. Figure 7 shows the model from the variance approach perspective.
The process approach perspective gives a different model’s shape, with underlying theory in it as demonstrated in figure 8.
A rationale for using process theory
In the present study, the need to explicate the dynamic view of the usage process of e government services by explaining how independent variables shape the evolution of the process, lead us to apply the process theory approach. In IS research, as is the case in management research, process theory is always preferred over the variance theoretical perspective when it comes to explaining ‘how’ a particular phenomenon happens (Teo, Srivastava & Jiang 2008). The present study attempts to explain how independent variables shape the e government usage process, thus the justification to use the process model. Additionally, unlike variance theory which attempts to explicate the variation in a dependent variable as a direct consequence of the variation in an independent variable(s), process theory attempts “…to address the complex dynamics of a variety of fundamental organizational processes including adaptation, co-evolution, improvisation, selection, and self-organization, illustrating how a favored paradigm holds powerful sway over what we can and cannot see (Chiles 2003, p. 288)” This provides the basis for the second justification.
Theorizing the research model
Awareness has different meanings in many contexts, but in the present study it is taken to imply the citizen’s knowledge of e government services existence and the benefits of using e government services. The proposed model of e government services usage assumes that awareness is the first event in the readiness step of usage process. Ismail (2008) not only agues that awareness is a significant factor in e government’s citizen readiness, but also proposes that government should engage in an advertisement campaign to increase the citizens’ knowledge about the existence of e government services by explaining the benefits of receiving services, with the view to encourage them to adopt the technology.
Governments across the world have a strong interest and commitment to maintain citizens’ trust on their e services. However, the citizens are unlikely to use e government services unless they have the confidence that government will guarantee two important factors in its service transactions (Law 2004), discussed as follows:
Privacy is a serious concern in any electronic transaction. Culnan (2000, p. 20) defines privacy as the “…people’s ability to control the terms under which their personal information is acquired and used”. A user’s privacy, as such, is always in an inherent situation of tension and must demonstrate the capacity to relate with capabilities of others to transact services, and even to control their own privacy (Culnan 2000).
While extant literature mentions four categories of privacy (information privacy, bodily privacy, communications privacy, and territorial privacy), it has been noted that most individuals using e government services are concerned with information privacy (Davis 1996). This category of privacy, according to this particular author, denotes the ability of the citizen to control one’s self as privacy becomes non-existent when the citizen loses the capacity to maintain a substantial degree of control over their personal information and its use.
Security is “…the combination of processes, procedures, and systems used to ensure confidentiality, authentication, and integrity of data” (Akhlaq et al 2006, p 29). In e government context, citizens are concerned about the security sent via the platform, and usually employ several security properties to make a decision about the security of the services. These security properties include “…confidentiality, authentication, integrity and non-repudiation” (Akhlaq et al 2006, p 29). The confidentiality property implies that the government must have the capacity to keep the information sent unreadable to unauthorized users, while the authentication property means the government must demonstrate the capacity to decipher the identity of the citizen to avoid identity fraud, which often leads to loss of critical data to unauthorized users. The integrity component denotes the government’s capacity to ensure information sent is not illegally altered or destroyed during transmission, while non-repudiation entails putting in place mechanisms that will ensure the infrastructure will acknowledge that it indeed sent information or data to the citizen (Akhlaq et al 2006).
Ability to use e government services
There are different elements that lead to citizen’s ability to use e government services, analyzed as follows:
One of the most critical elements of e government’s usage process is access channels. Access channels consist of online and offline channels and include web sites, PCs, laptops, kiosks and mobile phones, among others. Extant literature demonstrates the fundamental importance for the government to provide a common mechanism for citizens to not only find all government information and services, but to also use such information with much ease (Ebrahim & Irani 2005).
Authentication to access
Another critical element of e government usage process is authentication to access. One of the simplest approaches of authentication mechanisms in internet applications and kiosk channels is password authentication, with extant literature demonstrating that this approach allows citizens’ to use e government services from remote locations (Liao 2006).
The traditional conception of literacy, according to Lankshear and Knobel (2008), is the ability to read and write. However, in the context of using technology, digital literacy and other similar ‘literacies’, including information literacy and technology literacy, are concepts that are to a large extent associated with knowledge, skills and attitudes in dealing with information not only in diverse formats but also in different contexts and scope. Going by this description, therefore, a citizen can be considered as literate in the digital context when he has ability to acquire and use information appropriately for any given situation (Bawden & Robinson 2002).
Intention to use e government services
As acknowledged by Srivastava and Teo (2009), “…for adopting and using e-government processes, citizens must have intention to engage in e government, which encompasses the intentions to receive and provide information through online channels.” Extant literature demonstrate that although e government is a growing phenomenon that is increasingly affecting all aspects of our lives (Chalhoub 2010), it would be plausible to expect that its successful introduction as well as internalization would depend on many factors, including social and attitudinal factors (Alomari, Woods & Sandhu 2012). These factors, which will definitely influence how citizens intend to use e government services, include: ease of use (effort expectancy), usefulness (performance expectancy), and price value (Chalhoub 2010), as discussed below.
Ease of use “Effort expectancy”
Ease of use or effort expectancy is one of the factors, along with trust in e government and perceived usefulness, which are thought to intrinsically affect citizens’ intention to use e government services (Teo et al 2008). It is hypothesized that citizens’ intentions to use e government services will obviously be heightened if citizens perceive the service to be easy to use (Srivastava & Teo 2009), and will be diminished if they perceive the service to be complicated (Singh & Das 2007). Consequently, not only should online government services be intuitive, ensuring that citizens are able to navigate through the web pages with much ease, but information should be organized and presented based on citizens’ needs to allow them to quickly, effortlessly and seamlessly find the information or services they seek (Carter & Belanger 2005).
Usefulness “performance expectancy”
Davis (1989) cited in Carter & Belanger (2005, p. 8) defines perceived usefulness as “…the degree to which a person believes that using a particular system would enhance his or her job performance.” Perceived usefulness, according to these authors, “…influences one’s attitude towards system usage, which influences one’s behavioral intention to use a system, which, in turn, determines actual system usage.” It is reported in the literature that e government acceptance will obviously suffer if citizens fail to perceive the phenomenon as useful and easy to use (Tiamiyo & Ogunsola 2008).
Venkatesh et al (2012, p. 161) defines price value in terms of “…consumers’ cognitive tradeoff between the perceived benefits of the application and the monetary cost for using them.” These authors further argue that the price value is positive in any given situation when the benefits of using a technology are viewed to be greater than the monetary cost, not mentioning that such price value bears a positive impact on intention. Citizens may intend to use online birth registration service, for example, if its benefits are perceived to be greater than the monetary cost involved in travelling to the government offices, and time lost in queuing up to wait for services to be served (Srivastava & Teo 2009).
The research’s model
Figure 9 : Research’s model
Apart from analyzing the differences between variance theory and process theory, this section has also provided the rationale for using the process model in the present study, and theorized the research model. In justification, we can conclude that the process theory will not only assist in explaining ‘how’ independent variables shape the e government usage process, but will also illustrate how a favored paradigm in e government context holds powerful sway over what we can and cannot see. Additionally, the section has analyzed several dimensions related to ability to use e government services as well as intention to use e government services.
Akhlaq M, Jafri, MN, Khan, MA & Aslam, B 2006, ‘Addressing security concerns of data exchange in AODV’, Transactions on Engineering, Computing and Technology, vol. 16 no. 3, pp. 29-33.
Alomari, M, Woods, P & Sandhu, K 2012, ‘Predictors for e-government adoption in Jordan: Deployment of an empirical evaluation based on a citizen-centric approach’, Information Technology & People, vol. 25 no. 2, pp. 207-234.
Bavec, C 2006, ‘On the current environments for e-government development in the enlarged European Union’, Information Polity: The International Journal of Government & Democracy in the Information Age, vol. 11 no. 3/4, pp. 197-206.
Bawden, D & Robinson, L 2002, ‘Promoting literacy in a digital age: approaches to training for information literacy’, Learned Publishing, vol. 15 no. 4, pp. 297-301. Web.
Belanger, F & Carter, L 2009, ‘The impact of the digital divide on e-government usage’, Communications of the ACM, vol. 52 no. 4, pp. 132-135.
Burton-Jones, A, McLean, E & Monod, E 2011, On approaches to building theories: Process, variance and systems, MISQ working paper, pp.1–42. Web.
Carbo, T & Williams, J 2004, ‘Models and metrics for evaluating local electronic government systems and services’, Electronic Journal of e-Government, vol. 2 no. 2, pp 95-104.
Carter, L & Belenger, F 2005, ‘The utilization of e-government services: Citizen trust, innovation and acceptance factors’, Information Systems Journal, vol. 15 no. 1, pp. 5-25.
Chalhoub, MS 2010, ‘Public attitude towards government restructuring of IT public services: Application to e-government in the Middle East’, International Journal of Management, vol. 27 no. 3, pp. 541-561.
Chien-Hung, C & Mort, GS 2007, ‘Consumers’ technology adoption behavior: An alternative model’, The Marketing Review, vol. 7 no. 4, pp. 355-368.
Chiles, TH 2003, ‘Process theorizing: Too important to ignore in a kaleidic world’, Academy of Management Learning & Education, vol. 2 no. 3, pp. 288-291. Web.
Chuttur, MY 2009, Overview of the technology acceptance model: Origins, developments and future directions, Indiana University. Web.
Culnan, MJ 2000, ‘Protecting privacy online: Is self-regulation working?,’ Journal of Public Policy and Marketing, vol. 19 no.1, pp. 20-26.
Davis, FD 1986, A technology acceptance model for empirically testing new end-user information systems: Theory and results, Massachusetts Institute of Technology. Web.
Davis, FD 1989, ‘Perceived usefulness, perceived ease of use, and user acceptance of information technology’, MIS quarterly, vol. 13 no. 3, pp. 319-340. Web.
Davies, S 1996, Big Brother: Britain’s web of surveillance and the new technological order, Pan Books, London.
Ebrahim, Z & Irani, Z 2005, ‘E-government adoption: architecture and barriers’, Business Process Management Journal, vol. 11 no. 5, pp. 589-611. Web.
Elsheikh, Y 2011, A model for the adoption and implementation of web-based government services and applications, A PHD Thesis, School of Computing, Informatics and Media, University of Bradford.
Gunter, B 2006, ‘Advances in E-Democracy: Overview’, Aslib Proceedings, vol. 58 no. 5, pp. 361-370.
Heeks, R 2002, ‘E government in Africa: Promise and Practice’, Information polity, vol.7 no. 2/3, pp. 97-114.
Kotler, P & Keller, K 2006, Marketing management, Prentice-Hall, New Jersey.
Kottemann, JE & Boyer-Wright, KM 2010, ‘Socioeconomic foundations enabling e-business and e-government’, Information Technology for Development, vol. 16 no. 1, pp. 4-15.
Lankshear, C & Knobel, M 2008, Introduction: digital literacies: concepts, policies and practices, 1st edn, P. Lang, New York. Web.
Laukkenen, T, Sinkkonen, S, Kivijärvi, M & Laukkenen, P 2007,’Innovation resistance among mature consumers’, Journal of Consumer Marketing, vol. 24 no 7, pp. 419–427.
Law, E 2004, Strategic implementation of e-government in OECD countries: Major challenges, The12th NISPAcee Annual Conference, Vilnius. Web.
Layne, K & Lee, J 2001, ‘Developing fully functional e-government: A four stage Model’, Government Information Quarterly, vol. 18 no. 2, pp. 122-136.
Lee, MC, Chang T & Chang-Chien, WT 2011, ‘An approach for developing concept of innovation readiness levels,’ International Journal of Managing Information Technology, vol. 3 no. 2, pp. 18-38.
Liao, S, Shao, YP, Wang, H & Chen, A 1999, ‘The adoption of virtual banking: an empirical study’, International Journal of Information Management, vol. 19 no. 2, pp. 63-74. Web.
Liao, IE, Lee, CC & Hwang, MS 2006, ‘A password authentication scheme over insecure networks’, Journal of Computer and System Sciences, vol. 72 no. 4, pp. 727-740. Web.
Lin, CH, Shi, HY & Sher, PJ 2007, ‘Integrating technology readiness into technology acceptance: The TRAM model’, Psychology & Marketing, vol. 24 no. 7, pp. 641-657.
Markus, ML & Robey, D 1988, ‘Information Technology and Organizational Change: Causal Structure in Theory and Research’, Management Science, vol. 34 no. 5, pp. 583-598.
Misra, D 2007, Defining e-government: a citizen-centric criteria-based approach, Paper presented to Proceedings of the 10th National Conference on e-Governance, Bhopal, Madhya Pradesh, India, 2-3 February 2007.
Ndou, V 2004, ‘E government for Developing Countries: Opportunities and Challenges’, The Electronic Journal on Information Systems in Developing Countries, vol.18 no. 1, pp. 95-104.
Parasuraman, A 2000, ‘Technology readiness index (TRI): a multiple-item scale to measure readiness to embrace new technologies’, Journal of Service Research, vol. 2 no. 4, pp. 307-320.
Parasuraman, A & Colby, CL 2001, Techno-ready marketing: How and why your customers adopt technology, The Free Press, New York, NY.
Radeke, F 2010, How to Rigorously Develop Process Theory Using Case Research, 18thEuropean Conference on Information Systems – Pretoria, South Africa.
Ramiller, NC & Pentland, BT 2009, ‘Management implications in information systems research: The untold story’, Journal of the Association for Information Systems, vol. 10 no. 6, pp. 474-494.
Richey, GR & Autry, CW 2009, ‘Assessing inter-firm collaboration/technology investment tradeoffs: The effects of technological readiness and organizational learning,’ The International Journal of Logistics Management, vol. 20 no. 1, pp. 30-56.
Riley, TB & Okot-Uma, RW 2001, Electronic governance and electronic democracy: Living and working in the wired world, Stylus Pub. Llc, Commonwealth Secretariat.
Robey, D 1979, ‘User attitudes and management information system use’, Academy of Management Journal, vol. 22 no. 3, pp. 527-538.
Rust, R & Lemon, K 2001, ‘E-Service and the Consumer’, International Journal of Electronic Commerce, vol. 5 no. 3, pp. 83-99.
Salovaara, A & Tamminen, S 2009, “Acceptance or appropriation? A design-oriented critique of technology acceptance models”, In P. Saariluoma & H. Isomaki (eds), Future interaction design II, Springer, London, pp. 157-173.
Schultz, RL. & Slevin, DP 1975, “Implementation and organization validity: An empirical investigation”, In RL Schultz & DP Slevin (eds), implementing operations research management science, American Elselvier, New York, NY, pp. 153-182.
Singh, H & Das, A 2007, ‘Country-level determinants of e-government maturity’, Communications of the AIS, vol. 2007 no. 20, pp. 632-648.
Srivastava, S & Teo, TSH 2009, ‘Citizen trust development for e-government adoption and usage: Insights from young adults in Singapore’, Communications of the AIS, vol. 2009 no. 25, pp. 359-378.
Swanson, EB 1982, ‘Measuring user attitudes in MIS research: A review’, Omega International Journal of Management Science, vol. 10 no. 2, pp. 157-165.
Teo, TSH, Srivastava, SC & Jiang, L 2008, ‘Trust and electronic government success: An empirical study’, Journal of Management Information Systems, vol. 25 no. 2, pp. 99-131.
Tiamiyo, MA & Ogunsola, K 2008, ‘Preparing for e-government: Some findings and lessons from government agencies in Oyo State, Nigeria’, South African Journal of Libraries & Information Science, vol. 74 no. 1, pp. 58-72.
United Nations 2008, Government to Connected Governance, Department of Economic and Social Affairs, Division for Public Administration and Development Management, New York, NY.
Venkatesh, V, Morris, MG, Davis, GB & Davis, FD 2003, ‘User Acceptance of Information Technology: Toward a Unified View’, MIS Quarterly, vol. 27 no. 3, pp. 425-478.
Venkatesh, V, Thong, J &Xu, X 2012, ‘Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology’, MIS Quarterly, vol. 36 no. 1, pp 157- 178.