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From the previous chapter, we had reviewed the literature of OCB and developed the proposed hypotheses. Now, we are going to determine the types of research design and data collection method, clarify the sampling design, develop the questionnaire, conduct pilot test and lastly carry out fieldwork.
3.1 Research Design
In this study, descriptive studies were carried out in order to describe and explain the phenomenon of OCB in PHEIs in Malaysia. It can provide us a detail about the phenomenon of interest from PHEIs in Malaysia towards OCB. Thus, it can help us to determine whether the concept or practices of OCB in profit organization can be applied into education industry. In descriptive studies, quantitative data in terms of frequencies or mean and standard deviations is necessary (Sekaran & Bougie, 2010). Therefore, we have done a quantitative research by distributing the questionnaires to the respondents in order to collect primary data. The result of the research was numerical measurable because the hypotheses are tested with Statistical Package for Social Sciences (SPSS).
3.2 Data Collection Methods
In this research, primary and secondary data had been used to answer the research questions. The adoption of primary and secondary data is necessary and practical in ensuring the data collected is consistent and accurate. Besides, the combination of these two methods allowed "check and balance" among the data collected from different sources in a way that low possibility to getting biased information (Sekaran & Bougie, 2010).
3.2.1 Primary Data
During the data collection process, we were using questionnaire as a mean to collect data from the target respondents.Â There are many intermediaries available to distribute the questionnaire to respondents. Among these, we had adopted electronic device and make used of internet technology to reach the questionnaire to our respondents. According to Zikmund, Babin, Carr and Griffin (2010), advantages of mail questionnaire can be geographic flexibility, save cost, save time and provide conveniences to the respondents. An invitation email will be sent to the respondents which required the respondents to fill up the questionnaires through internet by clicking on the link provided. To provide greater flexibility for respondents, self-administered practice was being used in managing over the data collection process; the respondents have to take responsibility in understanding and answering all the questions.
3.2.2 Secondary Data
Secondary data was also playing an important role in providing useful input in developing thisÂ research paper. The secondary data were from academic journal, research papers, reality case studies in different regions and other publication such as review papers and local newspapers. Academic journals and research papers were the main source of our secondary data because it has higher preciseness than others. Most of the academic journals and research papers were getting from online journal database including EBSCOhost, ProQuest, Emerald, ScienceDirect, SAGE Journals Online, etc.
3.3 Sampling Design
In this section, we had decided our population and sample. Besides, we had also determined which method to be used in collecting data as well as the sampling location.
3.3.1 Target Population
In this paper, we were doing a comparative study between UTAR and MMU. Hence, academic staffs from UTAR Perak Campus, and MMU Cyberjaya Campus were selected as our target population. There were 505 academic staffs from UTAR Perak Campus and 494 academic staffs from MMU Cyberjaya Campus. So, total up to 999 respondents were selected as target population.
3.3.2 Sampling Frame and Sampling Location
Sampling frame which includes the name, position, email address, educations background of the respondents can be derived from UTAR website (www.utar.edu.my) and MMU website (www.mmu.edu.my). Thus, we are able to obtain the details of respondents easily.
The sampling locations were online survey questionnaires portal (www.my3q.com) and UTAR Perak Campus.
3.3.3 Sampling Elements
The sampling elements of this study were academic staffs from UTAR Perak Campus and MMU Cyberjaya Campus since they were our target population. The data obtained from UTAR and MMU academic staffs were expected to be precise and significant.
3.3.4 Sampling Size
We need to determine the sample size from 999 target population. Therefore we had referred to a table of sample size for a given population size which developed by Sekaran (2003). Based on Table 3.0, 278 subjects are needed to be selected as sample size from the population of 999 elements. Thus, we had selected 278 elements from 999 populations. This is because 278 subjects are able to represent the entire population and provide reliable results. Besides, it helps us to save cost and money because we don't have to collect data from the entire population which consists of large numbers of elements. Therefore, fatigue and errors also can be reduced when collecting data (Sekaran & Bougie, 2010).
3.3.5 Sampling Technique
Probability sampling was used in determining sample subjects because the elements in the population (UTAR and MMU academic staffs) have some known, non-zero chance or probability of being selected as sample subjects (Sekaran & Bougie, 2010). In this sense, we have selected simple random sampling in selecting the sample subjects. This is because every element in the population has an equal and known chance of being selected as a subject. Besides, simple random sampling has the least bias and offers the most generalizability (Sekaran & Bougie, 2010).
There are 999 elements in the population and we need 278 as sample. In order to select the sample subjects or respondents by using simple random sampling, we have run through a selecting process. Firstly, we wrote down each element's number (each element has a representative number) in a piece of paper. Then, the papers were being folded. After that, we picked the paper. At the end, 278 pieces of papers were picked. Therefore, the elements who with the numbers in the picked paper were selected as sample subjects. In other words, 278 respondents were selected as sample.
3.4 Questionnaire design
We used fixed-alternative question in designing the questionnaires. The respondents will be given specific, limited alternative responses and asked to choose the one that closest to their own viewpoint. By using fixed-alternative question, comparability of respondent's answers is more systematic and easier to conduct that compared to interviews and observation techniques. It also allows respondents to take lesser time to comprehend and answer the questionnaire.
The questionnaire was designed in a simple and clear manner. Thus, it motivates the respondents in answering the questions. The respondents were only required to select one answer that best fit their preferences and interest from a fixed range of given answers for each of the questions. Individual opinions and comments are not demanded from the respondents.
3.4.1 Questionnaire design for Section A
The questionnaire comprises Section A and Section B.
Section A consists of 50 questions; it was used to collect the responses from the respondents towards the independent and dependent variables. Under Section A, there were nine statement categories which were conscientiousness, agreeableness, openness, organizational justice, transformational leadership, job satisfaction, empowerment, commitment and organizational citizenship behavior. Each statement category includes some dimensions of variables which had been explained in the previous chapter.
All the questions under Section A were measured by Likert scale. In Likert scale, respondents specify their attitude by selecting how strongly they agree or disagree with the statement on a five-point scale in the questionnaire (Sekaran & Bougie, 2010). Below is an example of Section A:
Section B consists of 5 questions; it was used to collect the classification data or personal information of the respondents such as demographic data (age group, gender), educational qualifications, years in organization and institution.
Under Section B, gender and institution were measured by nominal scale. Nominal scale is the most basic level of measurement; it assigns a value to an object for identification or categorization purposes only (Zikmund, Babin, Carr & Griffin, 2010). For example:
E.g. Please indicate your gender:
( Â ) male Â ( Â ) female
Age group, educational qualification and years of working within organization were measured by ordinal scale. Ordinal Scale is a ranking scale that allows things to be arranged based on how much of some concept they possess (Zikmund, Babin, Carr & Griffin, 2010). For example:
E.g. You have been in this organization for:
( ) Less than 2 years
( ) More than 2 years but less than 5 years
( ) More than 5 years
3.4.3 Sources of questions in questionnaires
Basically, a 50-question of questionnaire was developed to measure the respondent's response towards OCB and independent variables. The questionnaire covered all the dimensions of the variables except those inappropriate for this study. In order to ensure the dimensions were fairly measured and expressed, we had adopted few sets of related questionnaires from previous studies.
In the section A of the questionnaire, question 1 until question 12 was used to measure the dimensions of personality of target respondents. Question 1 to 4 represented the conscientiousness; question 5 to 8 represented agreeableness; while openness was measured by question 9 to 12. These questions were adopted from Handbook of Personality (Pervin, & John, Eds.).
Question 13 to 17 was selected from Kivimaki, Elovainio, Vahtera, and Ferrie, (2003) and Moorman (1991); it was used to measure the respondents' responses on organizational justice. Question 13, 14, 15 measured the dimension of distributive justice while question 16 and 17 indicated the distributive justice dimension.
Seven questions (question 18 to 24) were used to indicate the extent of transformational leadership. The transformational leadership questionnaire was developed by House (1977) and Podsakoff et al. (1990). The model of Multifactor Leadership Questionnaire (MLQ) had also been taken into consideration in the development of leadership questionnaire.
Question 18 to 24 was adopted from several researchers who are Richard (2004), Vey and Campbell (2009) and Wood (1986). It was used to measure the extent of job satisfaction.
In the design of empowerment questionnaire, we adopted the study from Short and Rinehart (1992). In this measurement, we had chosen 3 dimensions to represent the whole picture of empowerment. This was because some of the questions do not consistent based on reliability test. Therefore, some of the questions had been removed from the original questionnaire set. Empowerment was measured by question 32 to 36.
In the measurement of commitment, 5 questions (question 37 to 41) were used to evaluate the extent commitment. We adopted few questions from the original set of questionnaire which previously developed by Celep (n.d.), Demiray and Curabay (2008), Hayday (n.d.) and LaMastro (n.d.).
Lastly the dependent variable (OCB) was represented by 9 questions (question 42 to 50). These questions were adopted from Meredith and John (2004) and Nerina, Rachel and Gibllian (2010).
All the questions in the questionnaire were expected able to measure all the variables precisely and completely.
3.5 Pilot Test
A pilot test was conducted to check the reliability and consistency of each of the questions (Sekaran, 2003). With this effort, waste of resources could be avoided as problems can be detected in the earlier progress.
On 1st December 2010, 30 sets of questionnaire were printed out and subsequently distributed to 30 respondents from UTAR Perak Campus. During the distribution, we only invited those academic staffs that were available in their office. The 30 respondents were well informed the objectives of our study and what we will do with their information. After two hours, 30 completed questionnaires were collected.
A brief scanning was performed on the 30 completed questionnaires. After that, all the responses were keyed in accordingly into SSPS software. Initially, the reliability test result was undesirable and questionnaire. In this sense, some modification had been made to solve this issue. Through Inter-Item Correlation Matrix from SSPS software, we can easily know that which question(s) are highly inconsistent among the questions. Thus, we took out those questions that significantly pulled down the Cronbach's Alpha and run the reliability test again. The results of the new reliability test were shown in Table 3.1 as below:
Based on the results shown in Table 3.1, the Cronbach's Alpha of each variable fell between 0.70 and 0.80. Based on the Table 3.2 which is reliability test table from Gliem and Gliem (2003), the questionnaire was considered acceptable. Thus, we will retain the questionnaires for data collection.
Source: Gliem, J.A., & Gliem, R.R. (2003). Calculating, interpreting, and reporting Cronbach's alpha reliability coefficient for likert- type scales. Paper presented at the Midwest Research-to-Practice Conference in Adult, Continuing, and Community Education, Columbus, OH.
Since the questionnaire was reliable and acceptable based on the reliability test results, we started to conduct fieldwork in order to collect data from the respondents.
At first, we developed an online questionnaire survey at www.my3q.com which is an online questionnaire survey portal. Then, we collected the email address of the sampling elements from UTAR website (www.utar.edu.my) and MMU website (www.mmu.edu.my). After that, survey invitations were e-mailed to 278 respondents. The email content included the survey intent and purpose, what we will do with the data, the privacy of the respondent's information, our contact information, estimated duration and due date of the survey. Survey data were collected over a two-week period from 24 December 2010 to 6 January 2011. Besides, a gentle reminder was sent to the respondents prior to and during the survey collection period.
On 6 January 2011, we were only able to collect 113 completed questionnaires. In the other words, there were only 113 out of 278 respondents fill up the online questionnaire survey. The online survey generated a response rate of 40.65% (N=278). According to Hamilton (2003), online surveys for industry had an average response rate of 32.5%, with most surveys receiving at least a 26% response rate. Hamilton (2003) also indicated that response rate of online surveys are variable due to the survey process. But, he experienced in most online surveys received 26% in average or better. Thus, our response rate (40.65%) is higher than average (26%).
However, we need to get 278 completed questionnaires in order to make precise data analysis. Now, we were still lack of 165 set of completed questionnaires. Thus, we had moved our survey from internet to on-the-ground by approaching the respondents physically to distribute questionnaires to them. In this sense, our sampling locations are UTAR Perak Campus. During 2 days of data collection (13 and 14 January 2010), we are able to collect 100 sets of completed questionnaires from the respondents who did not response to the online survey.
Now, we got 213 completed responses from the respondents and 30 completed questionnaires from previous pilot test. So, we had total up to 243 completed questionnaires on hand which were still lower than 278 sample size. However, Roscoe (1975) indicated that sample size larger than 30 and less than 500 are appropriate for most research.
Besides, Table 3.3 from Institute of Food and Agricultural Sciences, University of Florida (2009) indicates the sample size for Â±3%, Â±5%, Â±7% and Â±10% Precision Levels Where Confidence Level is 95% and P=5. In this study, we able to collect 243 completed response which was fall between Â±5% to Â±7% precision level where confidence level is 95% and P=5. Therefore, 243 completed response was considered acceptable with the precision level between Â±5% to Â±7% where confidence level is 95% and P=0.5.
Source: This document is PEOD6, one of a series of the Agricultural Education and Communication Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Original publication date November 1992. Reviewed April 2009. http://edis.ifas.ufl.edu/pd006
In this chapter, we had essentially carried out the planning of our research methodology, pilot test and fieldwork. The output of the fieldwork will be processed and discussed in Chapter 4. Then, a series of analyses and testing will be conducted in the next chapter as well.