Does Technology Readiness and Acceptance Induce more Adoption of E-Government? Applying the UTAUT and TRI on an Indonesian Complaint-Based Application

Most researches relating to the success of information and technology system application focus on two separate matters, namely technology readiness and technology acceptance. Both perspectives are used to observe how technology is adopted by users. However, very few studies test them both concurrently in a single research. This research, therefore, aims to conduct testing on the two concurrently without separating them. This article attempts to put two differing theories to the test, which are the Uni ied Theory of Acceptance and Use of Technology (UTAUT) and the Technology Readiness Index (TRI), in the context of e-government that is carried out via the Jakarta Smart City Program. To be more speci ic, the aJakarta Smart City Program analyzed in this study is the Qlue and CRM (Citizen Management Relationship) applications. The research method employed in this article is the quantitative method, wherein 225 respondents participated in this research to assess the level of technology readiness, the gathered data were subsequently processed by using the descriptive statistics analysis technique. Furthermore, 185 respondents also participated in observing how behavior in luences the intention to use technology. These data were processed by using multiple linear regression analysis. Research results indicate that Jakarta SCR citizens’ technology readiness level can still be categorized as low and is identi ied as belonging to the Low Technology Readiness group, with a total TRI value of 2.7. Additionally, this research also shows that performance expectancy (PE), effort expectancy (EE), social in luence (SI), and facilitating conditions (FC) have positive and signi icant in luence on the dependent variable, namely the behavioral intention to use the system (BIUS).

was born in Dumai, Indonesia 2th July 1994. Graduated from Faculty of Social and Political Sciences, Universitas Gadjah Mada in Major of Management and Public Policy (2018). She is currently a public policy analyst in Foundation of Biotechnology and Bioscience (YPBB), Bandung. She is also a founder of Beri Kembali which is a social enterprise concerned on problem of excess resources and inequality issues. In short, Beri Kembali attempt to rescue and redistribute excess resources (such as food, clothes and books) to people in need in Bandung. Furthermore, Dhia together with her partner are currently working to build a sustainable clothing line business which will be launched on April 2020.

Introduction
Most governments the world over have realized the potential opportunities offered by the application of information and communication technology within an organization (Mohammed & Ibrahim, 2013). Such a rather dramatic increase in the use of information and communication technology has de initely in luenced public sector organizations to shift their past traditional or conventional organizational activities and culture into technology-innovation based organizational activities (Dukic, 2016). One of the instances in the implementation of technology based system by public sector organizations or governments as an instrument to meet principles of good governance is something called Electronic Government (E-Government). According to the OECD, E-Government refers to the use of information and communication technology (ICT), and particularly the internet, as a means to achieve better government (OECD, 2003).
Additionally, the application of information and communication technology has been introduced in the public sector for the past 28 years as an effort to achieve greater level of effectiveness and ef iciency (O'Neill, 2009).
The successful implementation of an information and technology system is in luenced by both internal and external factors (Handayani & Sudiana, 2015). Lam, Chiang, and Parasuraman (2008) state in their article that in order to understand the success of information and technology system implementation, it is imperative that we understand matters relating to technological adoption (Lam, Chiang, & Parasuraman, 2008). There are two perspectives that can be utilized to understand the adoption level of a technology, which are: 1) personality and 2) technology traits (Harry, Gombachika, & Gift, 2012). Edmunds argues that the perspective about personality is closely associated with technology readiness, which holds a signi icant role in the adoption level of technology users (Edmunds, Thorpe, & Conole, 2010). Whereas the perspective of certain technology traits may in luence the attitude of technology users, which thus far has been known as technology acceptance (Chiu, & Tseng, 2010). (Element 2) Therefore, it is crucial for both central and regional governments to know and understand these personality traits, which in this case is observed from technology readiness and technology traits, which is seen from technology readiness, because these are the two things that drive the adoption and use of e-government in a region by its users. If the level of information and communication technology adoption and usage is high, the implementation of e-government will consequently produce good outcome in that region.

The elaboration above is in line with
Hartono's argument in his study asserting that one of the internal factors that may in luence the success of technology usage is acceptance and usage by those applying that technology (Hartono, 2007). In another study, Dukic mentions that for a government to achieve success in e-government implementation, all the factors are of utmost importance, however, the human resource factor is of particular importance, of which in this case are the public servants who provide the services through e-government application (Dukic, 2016 (Anthopoulos et al., 2015).
In the discussion about the acceptance of new information and technology system,  (Jaafar et al., 2007), in service provision (Lai, 2007), and in education (Lai, 2008;Lai & Chong, 2007).
Furthermore, other studies have also been carried out on the relationship between readiness and behavior toward technology (Parasuraman & Colby, 2001), relationship between technology readiness and technology adoption (Chang & Kannan, 2006;Lin & Hsieh, 2006;Sophonthummapharn & Tesar, 2007), and the relationship between technology readiness and quality of service (Lai, 2007 This article comprises of seven sections.
First, this paper will conduct a literature review on technology readiness and technology acceptance.
Next, the article's research methodology is elaborated, then followed by data analysis and further discussion of the results. After that, the discussion relating to the research indings will be summarized and discussed more extensively. This paper will then be concluded by presenting the research limitations and managerial implications that may be used by relevant stakeholders.

Technology Readiness Index
Technology Readiness Index is a model developed by Parasuraman (2000). In his research, Parasuraman observes the signi icance of consumers' readiness in the process of technology adoption or use. The consumers' technology readiness can develop their proclivity to embrace and use new technology in their daily activities or their activities at the work place (Parasuraman, 2000). Parasuraman states in his research that a person's readiness in adopting technology is determined by four factors, namely:

Optimism
A conviction of someone who believes that technology can offer far better control, increased lexibility, and ef iciency in their daily lives or in their activities at work.

Innovativeness
A tendency to be a pioneer in every aspect and form of their life. Parasuraman explains that the pioneer's tendency is more lenient toward the use of new technology, and they tend to easily adopt to technology that is constantly renewed from time to time.

Discomfort
A perception that one lacks control over technology. In other words, this dimension shows low technological mastery resulting in a feeling of dif idence in using technology.
Such dif idence will eventually drive a feeling of discomfort in the consumer's use of technology, thereby rendering them to continue using traditional means in dealing with their daily activities.

Insecurity
A distrust of technology-based transactions and pessimism toward the performance of technology. In other words, a feeling of disbelief or doubt that a technology can properly complete a task.
In his writing, Pasuraman also elaborates that the variables of optimism and innovativeness are called contributors, capable of enhancing one's readiness in adopting and using technology.
Additionally, the variables of discomfort and insecurity are called inhibitors, capable of lowering one's readiness level in technology use and adoption.
The four variables above can produce certain user proclivities at the time they adopt or use technology.

Technology (UTAUT)
The Uni ied Theory of Acceptance and Use of Technology is a model derived from psychology and sociology (Venkatesh, 2012). The degree to which a person believes that the use of technology can enhance their performance.

b. Effort Expectancy
The degree to which a person believes that a technology can be used with ease.

c. Social In luence
The degree to which a person believes that others around them believe they should use a particular technology.

d. Facilitating Conditions
The degree to which a person believes that organizational support is provided to facilitate the use of technology.
In the UTAUT model, the user's intention to use a technology system is also in luenced by moderating variables, these moderating variables are: gender, age, experience, voluntariness of use.

Hypothesis
To answer the second research question, a hypothesis is required to understand the correlations between the independent constructs, consisting of performance expectancy/PE, effort expectancy/EE, social in luence/SI, and facilitating conditions/FC, and the dependent construct, which is the the behavioral intention to use the system (BIUS).

Ha1
There is positive correlation between performance expectancy/PE and behavioral intention to use the system (BIUS) in the Jakarta Smart City Program.

Ha2
There is positive correlation between effort expectancy/EE and behavioral intention to use the system (BIUS) in the Jakarta Smart City Program.

Data Analysis Technique
The descriptive statistical analysis is used to answer the irst research question.
According to Sugiyono, descriptive statistical analysis is aimed at analyzing data by way of describing or illustrating the collected data as dictated by the acquired results (Sugiyono, 2017). The Technology Readiness Index value was calculated by multiplying the means value of each questionnaire with the weight of every question (Lazuardi, 2013). Each variable has a weight relating to the total variables by 25%.
The weights of each variable were then divided by the total statement indicators of each variable (Lazuardi, 2013). Next, the means value of the statement were multiplied by the weights of each statement to calculate the total score for each statement (Lazuardi, 2013). At the end of the analysis, the total TRI score was acquired from the accumulative score of total scores from each statement. The total TRI score acquired was subsequently used to determine the category level of Jakarta SCR residents' technology readiness.
According to Parasuraman, there are 3 levels of technology readiness, namely (Parasuraman, 2000): a. Low Technology Readiness.
Technology readiness level is considered low if the total TRI value is equivalent to or less than 2.89 (TRI ≤ 2.89). If total TRI is more than 3.51 (TRI > 3.51) In addition, multiple linear regression analysis was used to answer the second research question. This is an analysis model aimed at understanding the in luence independent variables (X) has over the dependent variable (Y) (Cooper & Schindler, 2014). Moreover, a hypothesis is accepted if the level of signi icance is t count ≤ 5% and it is rejected if the signi icance level is t count > 5%. Furthermore, a regression model can also be used for predictions given that it has met a number of assumptions. These are called "classical assumptions". There are several tests that must be carried out to ful ill these classical assumptions, namely: 1) data normality test; 2) heteroscedasticity test; and 3) multicollinearity test.

Validity
The Pearson Correlation Coef icient was used to conduct validity test. Furthermore, an Moreover, the three invalid statement indicators were deleted from the questionnaire. As a result, only 5 statement indicators relating to behavioral intention to use the system remain.

Correlation
Cronbach's Alpha was employed in this study to show the degree of reliability a measuring tool has (Singarimbun & Effendi, 1995). Furthermore, a research instrument in a questionnaire is valid if the Cronbanch's coef icient alpha is > than 0.6. Based on the reliability test, it is known that the research instrument relating to the irst research question is reliable. This is indicated by the Cronbach's coef icient alpha measuring in at 0.882, which is more than 0.6, therefore allowing it to be considered reliable. All the research instruments can, thus, be utilized in the study.
Moreover, the research instrument relating to the second research question which consisted of 34 statement indicators, after 3 statements proven to be invalid had been deleted, also indicates reliable data. This can be substantiated by the Cronbach alpha value indicating 0.810, which is more than 0.6, or in other words it proves that it is reliable to use in this study.

Regression Assumptions
In this study, regression assumptions tests were conducted on the respondents who  The above igure indicates that the points are randomly scattered and do not speci ically or clearly form a particular pattern. In addition, the points are scattered randomly both above and below 0 on the Y axis. It can, thus, be concluded that the tested regression model does not experience heteroscedasticity, allowing it to be used as a prediction in the following research.

c) Multicollinearity Test Result
It is known that the tolerance value of each independent variable, namely: performance

Value of Technology Readiness Index (TRI)
This subsection describes the data acquired from the TRI analysis that have been done previously to answer the second research question, which relates to the Jakarta SCR residents' technology readiness in applying the e-government system through the Jakarta Smart City program.
Based on the TRI value calculation results, the total technology readiness index is known to be at 2.7.

Analysis
Based on table 1.5, we can understand that the index value of the optimism variable has the highest score that contributes to the total value of technology readiness index at 0.82.
Given such high optimism variable value, we can, thus, understand that the people of Jakarta SCR have a positive perspective on technology. This is in line with Parasuraman's statement that the optimism variable can be viewed from the positive belief a person has in technology. Furthermore, they believe that technology can provide them certain bene its, such as lexibility, and ef iciency in their daily activities or in their activities at work. This is the kind of positive perspective the Jakarta SCR public has concerning technology.
Aside from believing that technology can be bene icial to support their daily life, the people of Jakarta also believe that, as individuals, they can properly control and operate technology.
Such kind of perspective is surely much required by the people of Jakarta SCR if they want to lend their support to the success of the Jakarta Smart for the people of Jakarta SCR to feel discomfort and insecurity in adopting and using technology cannot yet be known and identi ied by merely examining the statistical igures above. As it is known, the second research question merely aims to understand the people of Jakarta SCR's degree of readiness in adopting and using technology by observing the technology readiness index values, without conducting further qualitative studies to understand the underlying cause behind such high or low technology readiness index values. This is actually one of the limitations of this study.
Thus, ample space is provided for conducting follow-up studies and exploring further the underlying factors or causes that lead to high or low technology readiness index values by using the qualitative research method, so that there will subsequently be information and data available to support the results of the readiness index value statistical analysis.
Speci ically, the total technology readiness index value is at 2.7. It can, thus, be concluded that the people of Jakarta SCR still have a low level of readiness in technology adoption and use.
Parasuraman states that technology readiness is considered low or included in the low technology readiness category when the total TRI value is equivalent to or less than 2.89. At the time, Lazuardi had conducted research on the Panin Bank staff who applied a system called Business Intelligence (Oracle), which is useful in facilitating the process of gathering a bank's inancial data (Lazuardi, 2013). When the system was implemented, the acquired results did not meet the managers' expectations. The Panin Bank staff, who were expected to be able to use the Oracle system to facilitate their work in obtaining accurate data, were unable to operate the system properly in their respective computer instead (Lazuardi, 2013). Furthermore, Lazuardi even states that there were still many Panin Bank personnel who requested data manually and

Multiple Linear Regression Analysis
There are several matters of importance found based on the acquired data and indings, namely: First, the performance expectancy variable has a positive and signi icant in luence on the behavioral intention to use technology (BIUS) variable. Furthermore, in this study the performance expectancy's in luence has been assessed to identify the in luence of a person's belief and perspective that adopting and using the Jakarta Smart City program can increase their performance, and the quality of their daily life. Once such assumption exists in a person's mind, then that will boost their intention to adopt and use the Jakarta Smart city program in matters relating to their job or even just for their daily activities. According to Vankatesh, once an individual assumes that an information technology based program or activity can provide positive impact to their work or daily life, they will then have a signi icant inclination to adopt and utilize that information technology based program in a certain period of time. Such inding is similar to those obtained by Dasgupta, 2007;Davis, 1989;Handayani, 2005;Sedana & Wijaya, 2009;Taylor & Todd, 1995;Venketesh & Davis, 2000).

Limitations of Study
In this study, the researcher has afforded maximum efforts to design, obtain, and produce