Disseration Chapter 3 - The Economic Implications of Information Technology in E-Governance: A System Thinking/System Dynamics Approach
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Systems thinking/dynamic approach was implemented in this study. Systems thinking was founded in the field of system dynamics by MIT professor Jay Forrester in 1959 (Aronson n.d.). Systems dynamic has the exceptional ability to stand for the real world – it can recognize the complexity, nonlinearity as well as feedback loop structures that are innate in social and physical systems (Forrester 1992). Professor Forrester distinguished the need for a better way of testing new ideas regarding the social systems, in the same way in testing ideas in engineering. Thus, systems thinking enable people to make their understanding of the social systems overt and develop them in the same way that people can use engineering principles to make clear and advance their understanding of mechanical systems (Forrester 1992). This is different from the traditional form of analysis – while the traditional analysis pertains on the separating individual pieces of what is being studied, systems thinking pertains on how the things being studied interacts with other constituents of the systems – a set of elements which interact and connect in order to produce behavior – of which it is a part (Forrester 1992). Therefore, in systems thinking analysis, instead of separating each smaller and smaller parts of the system being studied, systems thinking focuses by developing and increasing its view in order to take into account larger and larger numbers of connections as an issue is being studied (Forrester 1992).
Quantitative method was used in this study which helps in order the author to conduct the study in specifically. Furthermore, it had helped in order to follow the original set of goals, focusing on more objective conclusions, affecting issues that are related with causality and prevent the subjectivity of judgment (Creswell 2003).
In order to evaluate the past research and literatures about the past researches and studies about the impact of IT towards e-governance, secondary resources were evaluated and analyzed. The next stage focused on gathering data and information by using qualitative methods from the government employees and citizens of Southwark. This enables the researchers to distinguish and reduce the key factors as well as related elements which encompass the factors that are expected to clarify factors that are related with IT and e-governance. With all these information, survey questionnaire or data gathering method can be designed and pretested. The final survey questionnaire was disseminated by using random sampling (Urden 2001). The pre-testing was done to assess the strengths and weaknesses of questionnaire as a data gathering tool, at the same time, it help in order to make sure that all of the important items that are all included in the questionnaire and remove some of those that are not needed.
The data used in this researcher were gathered from two groups of users and benefactors of e-governance in Southwark, the people or the citizens and the government employees. A total of 25 questionnaires were disseminated to the government employees and 75 for the citizens. A total of 25 and 70 questionnaires were returned with valid and complete answers or responses. These shows a high return rate, thus, it can be said that the data gathering processes implemented were successful. The respondents were selected via random sampling. This was used in order to ensure that bias will be prevented and ensure that the population will be equally represented. The name of the employees and the citizens respondents were selected via lottery method.
The survey questionnaire is consists of 2 parts. The first part pertains on the demographic factor or those details that are connected to the background of the respondents. The second part pertains on the different political, economic, social and technological factors and advantages that are related with the relationship of technology and e-governance. Thus, it enables to show the connections or relationships of these advantages in order to create the overall importance of IT in e-governance. Likert scale was used in order to get the level of agreement of the respondents to the different questions.
4.50 – 5.00 Strongly Agree
3.50 – 4.49 Agree
2.50 – 3.49 Not Sure
1.50 – 2.49 Disagree
0.00 – 1.49 Strongly Disagree
All of the gathered data was analyzed using the latest SPSS software including the weighted mean, percentage and frequency. The following statistical formulas were used:
1. Percentage – to determine the magnitude of the responses to the questionnaire.
% = -------- x 100 ; n – number of responses
N N – total number of respondents
2. Weighted Mean
f1x1 + f2x2 + f3x3 + f4x4 + f5x5
x = --------------------------------------------- ;
where: f – weight given to each response
x – number of responses
xt – total number of responses