Citizen Adoption of Mobile and Customizable E-Government Services: A Literature Review and Conceptual Framework

Introduction

With the widespread use of information technology (IT), governments around the world have realized its significance to enhance public service provision to their citizens and businesses, cooperate flexibly with their departments, and communicate efficiently within their very own public administration and organizations in a new interaction form called e-government (Idoughi and Abdelhakim, 2018). Nowadays, e-government services cover most if not all transactions among government departments, organizations, and private sector. E-government promised to provide many benefits to its patrons, including the reduction of corruption, the provision of more transparent, accountable, and easily accessible public services, the promotion of e-democracy and e-participation, cost reduction, predominant over the social and digital divide, and fast customization to meet citizens' requests (Rana et al, 2016). With the increased use of e-services, and due to the high penetration rate of mobile and smart devices among citizens, governments of both (developed and developing) countries interested in making their services more fit and accessible started providing mobile e-services compatible with mobile and smart handled devices to gain more citizens’ acceptances (Althunibat and Sahari, 2011). Many e-government projects gained high successes, but even more disappointedly failed especially in developing countries (Carter et al, 2016) where governments are still struggling with the low citizens' participation and immature adoption of e-government (Al-Hujran et al, 2015). A study from (Saif et al, 2017) reported that 96% of survey respondents have smartphones, yet among them 65% never used the available mobile services. This high failure rate that was not explained or justified dispute the rich research and the countless number of evaluation methods and validated models clearly indicates that there are some unknown factors in the new e-services forms that were not studied nor evaluated by existing e-assessment models. Therefore, this paper aims to:

• 1.

  Uncover and understand the specific factors that influence mobile e-government services adoption in developing countries where Algeria is selected as a study field.

• 2.

  Help to provide a new assessment model, which will help, boost the success of mobile and customizable e-services in the context of developing countries.

This study is structured as follows. Section 2 reviews widely known technology adoption models and theories. The next section reviews studies on e-government. Section 4 presents the new assessment model and hypotheses development. In Section 5, the research method is described. The results are presented in the next section. Section 7 provides the discussion of the results, and finally, section 8 provides the implications and future perspectives of this research.

Review Of Models Used For Studying E-Government Adoption

In light of concerns about why users are not using available IT solutions, various technology acceptances models (TAMs) are presented as theoretical approaches to describe factors that affect their acceptance of technologies (Ajzen and Fishbein, 1972; Davis, 1985; Davis et al, 1989). These models are the cornerstone upon which built most recent assessment approaches. Later, developments and adjustments were made to these models where newly discovered important factors as trustworthiness were added to improve testing results.

This section performs an analysis of the current literature for TAMs and provides a narrative review of the identified key models with a chronological positioning (Figure 1). It will discuss five models, which are précised in (Figure 1) and listed below. The constructs identified in these models are defined in (Table 1) and the models are discussed in the following sections:

• 1.

  Diffusion of innovation (Rogers and Shoemaker, 1971).

• 2.

  Theory of Reasoned Action (Ajzen and Fishbein, 1972).

• 3.

  Technology acceptance model (Davis, 1985).

• 4.

  Technology acceptance model 2 (Venkatesh and Davis, 2000).

• 5.

  Unified theory of acceptance and use of technology 2 (Venkatesh et al, 2003).

Figure 1.

Chronological positioning of technology acceptance models