Citizen Readiness on Usage Rate of E-Government Service

Introduction

Overview

As a direct result of advances in Information and Communication Technology (ICT) through the internet, citizens have developed a whole new set of expectations regarding the methods and processes used in interacting with their respective governments. Following in the footsteps of the revolution in consumer purchasing that was established by e-commerce, electronic government (e-government) has been stated in Dodd (2000) as the new wave of the future in public sector interaction between citizens and government offices for the next generation. E-government can be described as the implementation of digital processes and technologies in order to increase efficiency, reliability, and coverage of internal and external government services and information sharing to citizens while at the same time implementing a concept known as “lean governance” wherein wasteful spending processes and methods of operation are in effect eliminated as a direct result of utilizing e-government procedures and systems (Lam 2005). Based on these perceived benefits, many developed and developing countries around the world have begun to allocate resources towards the implementation of e-government programs and initiatives (Tassabehji 2005).

Benefits of a Government’s Online Strategy

In “Defining E-government: A Citizen-Centric Criteria Based Approach”, Misra (2007) talks of the benefits of e-government as occurring on three fronts: benefits to citizens, to businesses, and to the government. As noted by this author, there are several ways in which consumers or citizens in general benefit from e-government initiatives. For instance, these initiatives facilitate round-the-clock service, are economical since physical visits to the government offices are not necessary, are efficient and fast since the transactions are electronic, are convenient in that one can access the website wherever they are and are equitable since anyone can access the sites (Misra 2007). One study indicated that Australians are usually busy and often lack time. The private sector has already taken notice of this fact and has gone ahead to implement online services as a way of saving their clients’ effort and time in accessing information and carrying out transactions (E-government benefits study 2003).

The citizens of Australia can now also enjoy such services from their government. In terms of social benefits, the government is now able to deliver services efficiently to its citizens. The government website offers routine inquiries while other employees in government agencies are left to deal with complex issues (E-government benefits study 2003). Australian citizens are also able to access government services regardless of the time of day. In addition to this, citizens have also been allowed to access information at their own discretion. This implies that not only are they able to get accurate information in a timely manner, but they also get to make informed decisions. Through e-government initiatives, government agencies have been able to penetrate and spread information to many citizens within Australia. Indeed, with the broadband infrastructure in place, communities in remote and rural areas have also been able to access information and government services (E-government benefits study 2003). E-government services are also of great benefit to businesses. For instance, while setting up a new business has become faster than ever before, businesses can now transact their operations online, not to mention that transparency and convenience have been enhanced through e-procurement initiatives (Misra 2007).

Moving on, it is clear that the government is also a beneficiary of e-government initiatives. Through e-government, for instance, the government is able to develop and implement better policies and regulations since they are able to work with updated information. Not only have e-government initiatives enabled government officials to come up with better decisions since they are able to acquire, store and retrieve data in a fast manner, but they have also enhanced the government’s image and reputation, primarily because it is now perceived as progressive and modern in the eyes of investors and citizens (Misra 2007). According to the Australian study, most government-initiated online programs have led to a reduction in costs through lowering delivery costs, improving external and internal processes, and direct savings. The study further notes that government agencies are now able to make use of cheap communication channels to communicate with the citizens and other agencies. Efficiency in resource sharing has also been achieved through this strategy. The different agencies within the government have been able to communicate and exchange information electronically and with ease. This has ensured a reduction in expenses associated with paper-based communication systems (E-government benefits study 2003).

Research problem

A survey conducted in 2008 showed that 189 out of 192 UN member states were actually implementing substantial e-government initiatives, ostensibly because of the merits associated with the initiatives (United Nations 2008). But while the merits associated with utilizing online systems and digitized functions are not in doubt, it must be questioned whether there are drawbacks related to the implementation of e-government and whether these initiatives can truly result in a better functioning government. In many instances, citizens appear to be holding back from maximally utilizing e-government initiatives. For example, while it is known that the European Union (EU) has one of the highest rates of internet usage within the world with 71.5% of its population utilizing the internet on a daily basis (Internet World Stats 2012), one particular study established that only 28% of internet users within the EU actively accessed information on public authorities’ websites in 2009.

It is further reported that “…only 13% of European citizens sent information electronically within 3 months prior to the survey in 2009” (European Commission 2010, para. 8). These trends are indicative of an incredibly low citizen usage rate despite the number of services and capacity the EU e-government initiatives have at the present. However, these trends are not unique to the EU alone; rather they are actually evident in most governments around the world that have implemented e-governments initiatives. Based on the apparently low uptake rate of e-government platforms and services, therefore, it is only proper that the functionality and practicality of the e-government concept be questioned given the fact that so much has been spent on it with so few people actually using it.

A study conducted by Sharma and Pant (2009) demonstrated that IT usage in the Indian state of Uttarakhand is significantly low. Awareness of computers and IT-related facilities was high among urban dwellers as opposed to rural dwellers; however, usage of computers among the urban population was mainly limited to word processing. Few of those in the rural areas were aware of the government website or its online services. The study also revealed that nobody in the rural population made use of these services. A high number of respondents revealed that they had not used e-government services. Indeed, very few participants reported ever making use of the Indian Railway website or the Uttara Portal (Sharma & Pant 2009). This analysis on Uttarakhand citizens serves to reinforce the fact that there is extremely low usage of IT services, e-government initiatives, and computers in general.

In the same study, student respondents from various institutions revealed that they either had access to computers or had computers. This finding revealed that usage of computers and the internet among this group of the population was considerably high (Sharma & Pant 2009). However, despite the high internet usage, there is still low uptake and adoption of online government services among students. Indeed, internet usage among students is often limited to reading or posting emails and surfing popular youth-oriented web content using Google or Orkut. This group, however, made constant use of the university’s website to check their results. Overall, the study demonstrated that a significantly low number of students do not use any IT facilities or services (Sharma & Pant 2009).

This study went ahead to analyze data collected from employees in the private and public sectors. The results depicted that some employees made use of internet services in their daily operations, which included browsing, emailing, paying bills, carrying out bank transactions, etc. However, very few of these respondents had used e-government services such as income tax filing. Consequently, it was concluded that usage of e-government services among this group of the population is significantly low (Sharma & Pant 2009). Finally, the study collected data from the business class to identify the uptake rate of IT facilities within the state of Uttarakhand. An analysis on this group demonstrated that most respondents had not used online services for booking railway tickets and had instead opted for the manual system. Only a few had used government-oriented websites to access government services (Sharma & Pant 2009).

The study focusing on the state of Uttarakhand is a clear indication of the low usage rate of IT infrastructure that has already been put in place. IT awareness among the various groups covered in the study has been demonstrated as exceedingly low. This study shows that low awareness is directly proportionate to the low usage of IT infrastructure. The study, more than anything else, illustrates that usage levels of IT facilities among various sampled groups is directly influenced by low IT awareness within the state of Uttarakhand.

On the other hand, most citizen centric e-government studies that have been conducted over the years focus on the subsequent adoption and acceptance of digital/internet based platforms and services. Such studies have tried to predict users’ reception of technology by measuring how they rate statements on a questionnaire. Table 1 shows a random selection of the citizen centric e-government publications illustrating how adoption and acceptance dominates the topic.

Table 1: Analysis if Citizen-Centric E-Government Publications.

Author Model
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
Adopted from: (Please include an in-text citation here of where you got the table from. Remember to include the reference for the same in the reference list)

It must be noted, though, that recent criticisms have started to emerge about the perceived constraints in adoption and acceptance studies and the research approach they utilize in general. For instance, Lee, Kozar and Larsen (2003) point out that many studies base their measurements on the user’s self-reported numbers of use and short usage with the technology in question, and as such represents a distinct lack of sufficient breadth and depth in terms of sufficient data observing other facets regarding the use of the technology. Benbasat and Barki (2007), on their part, mention the inherent lack of longitudinal studies which take into account multiple measurement points. In addition, acceptance models have been criticized for their insensitivity to different use contexts. More importantly, the models do not take into account the fact that a technology may be initially accepted in the beginning but later abandoned, or vice versa (Salovaara & Tamminen 2009).

Some criticism has been directed at the nature of technology acceptance models and how different models have been improved over the years. There have been numerous suggestions raised to extend the models backwards through the roots features of technology depending on which users assess the usefulness and ease of use of the technology itself (Benbasat & Barki, 2007). Moreover, all adoption models do not take into account the readiness of citizens as an important base to adopt the government web services; rather they focus on how citizens utilize the web service and measure their perceptions about such services (Salovaara & Tamminen 2009). With these inherent limitations witnessed in acceptance and adoption models, it is indeed correct to state that the government’s web designers and practitioners are far away from understanding citizens’ attitudes and needs for government web services. Consequently, these designers need to not only build a strong and tangible model made particularly for government web services infusion, but also to understand the manner in which citizens perceive the use of e-government services while they design the government’s web services.

Another aspect that has been of great interest in the implementation of e-government is e-readiness. This refers to the capacity, both individual and collective, to benefit from and participate in the digital globalization of the economy. In this research, we will focus on the conditions that have been established before the implementation of e-government. Therefore, e-readiness also refers to the level of commitment of a community to engage in and interact with relevant government agencies through a network. There has been a lot of literature that focuses on e-readiness, but most of it is limited to the readiness of either the government or the citizen. For instance, the Economist Intelligence Unit (2008, p. 2) defines e-readiness as “…the measure of a country’s ability to leverage digital channels for communication, commerce and government in order to further economic and social development”. According to this definition, e-readiness refers to the conditions that have been set by the government to ensure that e-government implementation is successful. Such conditions may include setting up the available infrastructure, presenting the data to the public and so on. Hence, it would be correct to say, in such instance, that a country is ready but its citizens are not. This definition does not, however, look into the citizens’ readiness and particularly the readiness of an individual.

According to Osorio and Sachs (2002, p.), e-readiness refers to “…the degree to which a community is prepared and has the potential to participate in the networked world”. There have been numerous assessment measures and models of e-readiness that have been developed over the years. A comparison carried out by Bridges.org (2001) cited in Vaezi and Bimar (2009) discovered that each of the models had their own definition of e-readiness. Harvard University’s Center for International Development cited in Tah (2012, P. 370) defines an e-ready society as:

one that has the necessary physical infrastructure (high bandwidth, reliability, and affordable prices), has integrated current ICTs throughout businesses (ecommerce, local ICT sector), communities (local content, organizations online, ICTs used in everyday life, ICTs taught in schools), has government (e-government), has strong telecommunications competition, has independent regulation with a commitment to universal access and has no limits on trade or foreign investment.

E-readiness has also been defined by Bui et al (2003) cited in Davidrajuh (2004, p. 95) as “…the aptitude of an economy to use the internet to migrate traditional businesses into the new digital economy, when the economy is able to create new businesses that could not be done otherwise.” On his part, Krull (2003, p. 10) defines e-readiness as the “…degree to which a society is prepared to participate in the digital economy with the underlying concept that the digital economy can help to build a better society.”

The literature presented above demonstrates a clear indication that the focus of scholarly content on e-readiness has been one sided. This is primarily because the individual or the end user is not considered as part of being ready for e-governance. Indeed, extant literature only focuses on the ability of the government to provide the necessary infrastructure to implement e-governance. The numerous assessment tools and models that have been developed over the years are undeniably focused on assessing an economy’s or country’s e-readiness factor. It has been argued in the academic circles that the present models focus on extrinsic factors that make up an individual’s environment. Such models bear an indirect impact on an individual’s level of e-readiness.

An assessment model developed by Asia Pacific Economic Cooperation (2000) has been used by different economies and communities to measure their level of e-readiness. The indicators used in this model are as follows:

  • Essential technology and infrastructure – this refers to the ease of access to the necessary facilities, the speed, price and reliability of the infrastructure and market conditions.
  • Facilitation and promotion facilities
  • The present use and level of internet
  • Human resources and skills
  • Access to the required services such as internet services, etc.

It is imperative to note that this model highlights human resources and skills as one of the indicators used to measure e-readiness.

Intrinsic factors have been identified as those that influence an individual while making decisions. Extrinsic factors have been identified to have some bearing on the intrinsic factors. The intrinsic factors, on the other hand, have been identified to have a direct bearing on the level of e-readiness of an individual. In this light, the theory of planned behavior (Azjen 1991) and theory of reasoned action (Fishbein & Azjen, 1973) can best be used to study an individual’s level of e-readiness. Ratnananthan (2011) explores these two theories in his dissertation on e-readiness. According to him, the adoption of these theories has ensured that researchers and theorists within the Information Systems field are able to grasp an individual’s psychological impact on adoption of information systems (Ratnananthan 2011). He has also identified motivation as one of the factors affecting an individual’s level of e-readiness. He explores various motivation-based theories to illustrate this as a factor influencing an individual’s level of e-readiness. This particular study represents one of the few works that presently address e-readiness on an individual level.

Research objective

According to the research problem the objective of the proposed study will focus on exploring citizen readiness factors and their impact on the usage rate of e-government web services, with the view to provide practitioners and researchers with a better understanding of citizens’ readiness in e-government context.

Key Research Questions

The proposed study will be guided by the following research questions:

  1. What are the aggregated factors that guarantee citizen readiness in e-government web services?
  2. Does citizen readiness influence the usage rate of e-government web services?
  3. What are some of the limitations that influence the level of e-readiness of the citizen in regard to e-governance initiatives?

References

Arzen, I 1991, ‘The theory of planned behavior’, Organizational Behavior and Human Decision Processes’, vol. 50 no. 2, pp. 179-211.

Asia Pacific Economic Cooperation 2000, APEC readiness initiative: E-commerce readiness assessment guide, Web.

Benbasat, I & Barki, H 2007, ‘Quo Vadis, TAM?, Journal of the Association for Information Systems, vol. 8 no. 4, pp. 211-218.

Davidrajuh, R 2004, ‘Planning e-government start-up: A case study on e-Sri Lanka, Electronic Government, vol. 1 no. 1, pp. 92-106, Web.

Dodd, J 2000, Delivering on the e government promise, A Government Technology Industry Profile: NIC, Web.

Economic Intelligence Unit 2008, E-readiness rankings 2008: Maintaining momentum, Web.

E-government benefits study 2007, Web.

European Commission 2010, E-government statistics, Web.

Fishbein, M & Ajzen, I 1975, Belief, attitude, intention, and behavior: An introduction to theory and research, Addison-Wesley, Reading, MA.

Internet World Stats 2012, Usage and population statistics: European Union, Web.

Krull, A 2003, ICT infrastructure and e-readiness: Assessment report: Estonia, Praxis Center for Policy Studies, Tallinn.

Lam, W 2005, ‘Barriers to e-government integration’, Journal of Enterprise Information Management, vol. 18 no. 5, pp. 511-530.

Lee, Y, Kozar, KA & Larsen, KRT 2003, ‘The technology acceptance model: Past, present, and future’, Communications of the Association for Information Systems, vol. 12 no. 1, pp. 752-780.

Misra, DC 2007, Defining e-government: A citizen-centric criteria-based approach, Web.

Ratnananthan, A 2011, E-readiness of consumers for e-commerce adoption: A case study in Sri Lanka’, Research dissertation, The University of Sheffield, Web.

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.

Tah, JHM 2012, “Virtue planning and knowledge-based decision support”, In A. Akintoye, J. Gouding & G. Zawdie (eds), Construction innovation and process improvement, John Wiley & Sons Ltd, West Sussex, pp. 347-390.

Tassabehji, R 2005, ‘Inclusion in e-government: A security perspective’, paper presented to the E Government Workshop 05 (eGov05), Brunel University, UK, Web.

United Nations 2008, UN e-government survey 2008: From e-government to connected governance, Web.

Vaezi, SK & Bimar, HIS 2009, ‘Comparison of e-readiness assessment models’, Scientific Research & Essay, vol. 4 no. 5, pp. 501-512, Web.

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