3.1 Research Design 3.1.1 Sample
To answer the research questions, a quantitative approach was applied. The proposed model was tested via a survey with a sample size of 186. The subjects were drawn from a complete agency list published by Taiwan government at its portal website (http://www.gov.tw/). In general, it is those top-level senior IT managers that have the power to make decisions for their subsidiary divisions. For this reason, we chose the major IT decision makers at division chief level or higher from the list.
To prevent our subjects from confusion, we design one short but all needed information inclusive introduction page right before the questionnaire to make sure that all our subjects know the following information: The background, definition, benefits (advantages), drawbacks
(disadvantages), and classification of IaaS.
To focus more on our main research question, we would like to introduce a research assumption here: these decision makers rationally make their decisions and without the imperative intervention of their supervisors. The reason why we make this assumption is that some of the decisions in the government agency are affected solely by the top-level policy makers, and their subordinates may just follow the policy in reality. Indeed, some researchers also stated that adoption of IT may be encouraged by management (Leonard-Barton & Deschamps, 1988) or even mandated (Moore &
Benbasat, 1991). Unfortunately, the policy makers in some cases are not those who really
understand all the facets of certain technology, and thus the decisions are poorly made. Based on the track record, the government agency sometimes made wrong adoption decisions to invest a lot in some under-used, never-implemented, or used in a short term then scraped technology. From the working experience as a public servant, we know that the upper middle-class IT managers in the IT division in the government agency are the ones most familiar with the technological details. As a result, in order to answer one of our research questions “Is it the right time to adopt IaaS
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technology?” we must know what the actual implementers are really thinking about to obtain an impartial, objective, and true answer. This notion also affects how we choose the subjects in this research.
3.1.2 Operational Variable Definition and Measurement
To operationalize the constructs in our research framework, we adapt the items from the instruments used in other studies or popular IT periodicals with similarity of context. These items for each construct had been under strict development and used widely and frequently in many related researches. The content validity of the constructs is deemed acceptable by many experts and each of the items presents high reliability or internal consistency. Therefore, we believed that the usability of these items is out of question. For example, the items from one of the source of our questionnaire, “Organizational adoption of open systems: a ‘technology-push, need-pull’
perspective,” have a reported reliability of at least 0.7 in its original study. As a result, we think that it is appropriate to use these items in our research.
The operational definitions and the sources of definitions of each variable are given in Table 3-1. Please refer to the appendix A of the thesis for the detailed questionnaire.
Dimension Concept Operational Definition Source of Definition
Technological
Perceived Efficiency Improvement
1. More choices for hardware and software.
2. Better utilization of IT resources.
3. Promoting flexibility and integration.
4. Increased IT infrastructure service quality.
6. Reduced maintenance cost.
7. Reduced maintenance effort.
This Research
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Dimension Concept Operational Definition Source of Definition
Organizational
Satisfaction with Existing IT Infrastructure
1. Serve the needs.
2. Good price/performance ratio. Organizational Adoption of Open Systems: A
“Technology-Push,
Need-Pull” Perspective (Chau
& Tam, 1999) 3. Level of satisfaction as a whole.
4. Joyful using experience.
5. Considering functions useful.
6. Considering convenient.
7. Willingness to use.
The Impact of Knowledge Management System on User’s Satisfaction in a Governmental Organization (Yung-Feng Hsu, 2006)
IT Knowledge
1. We have very little knowledge how Internet and electronic commerce (Change to IaaS) can help to improve my business and increase our sales.
2. We do not have the technical knowledge and skills to start using Internet and electronic commerce (Change to IaaS).
3. We have very good understanding about how Internet and e-commerce (Change to IaaS) can be used to help to improve my business profit.
Dimension Concept Operational Definition Source of Definition
Environmental
Agency Trust
1. Based on experience, I think vendors are trust worthy.
2. Based on experience, I think vendors can provide service with decent quality.
3. Based on experience, I think vendors can meet users’
demands.
4. Based on experience, I think vendors can reliably comply with the agreement.
An Empirical Study of Information Outsourcing from User Perspective (Jung-Ya Hung, 2008)
Vendors’ Promotion
1. Vendors’ marketing activities.
2. Vendors’ planning proposal.
3. Vendors’ offering of a preferential price.
A Study on the Factors that Influence Enterprises’
Decision to Adopt New Information
Technology─Based on ADSL (Uen-Yu Chuang, 2002)
Dimension Concept Operational Definition Source of Definition
Dependent Variable Intention to adopt
1. How likely is it that your company intends to have an Internet website within the next 6 months?
2. How likely is it that your company intends to have an Internet website within the next 12 months?
3. How likely is it that your company intends to have an Internet website within the next 18 months?
Executive Decisions About Website Adoption in Small and Medium-Sized Enterprise (Gemino, Mackay & Reich, 2006)
Table 3-1: Operational Definition of Variables
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As to the measurement, we measured all these factors and the adoption level of IaaS using 5-point Likert scale (strongly disagree=1, strongly agree=5). In order to discover the intention of the decision makers in the government agency to adopt IaaS, we measure it by using a combination of three items introduced by Tan and Teo (2000) in their research. They used three items on a
five-point Likert-type scale. The items look like this: “How likely is it that your company intends to….1) within the next 6 months; 2) within the next 12 months; 3) within the next 18 months.” The responses are weighted by 3/6, 2/6, 1/6 respectively. As to the details of the questionnaire, please refer to the end of the thesis to view the actual questionnaire items used in this research.
3.1.3 Data Collection Method and Result
A survey instrument was created to test the model of IaaS adoption for this study. The data were collected by a questionnaire mailed to the IT section managers of 186 agencies. The questionnaire that we used was divided into five parts. The first three parts are the technological dimension, the organization dimension, and the environmental dimension, respectively. The fourth part is the dependent variable ─ the intention to adopt. The last part is the personal information of the respondent.
In addition to preparing the stamped addressed envelopes for our questionnaire respondents to reply, we provide the questionnaire website address in the cover letter, which is served as a
complement approach to completing to questionnaires and might be helpful to improve the response rate.
In two weeks, 65 responses (40 from mail, 25 from Internet) are returned. However, the response rate was far lower than we expected. Therefore, we started a second round questionnaire collection by carrying out a reminder call or paying a visit directly to those who had not responded.
Additional 46 (25 from mail, 21 from Internet) questionnaires were collected in the second round.
To sum up, we received 111 responses in the end and the final response rate was 59.677%.
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