1. Associate Prof Dr Ng Siew Imm (Serene) Associate Prof Dr Ho Jo Ann
Research Methodology
Associate Prof Dr Ng Siew Imm (Serene)
Associate Prof Dr Ho Jo Ann

2. WHAT IS Research?
Research is about acquiring knowledge and developing understanding, collecting facts and interpreting them to build up a picture of the world around us (Walliman, 2011).

3. WHAT IS Research Methodology?
Research methodology refers to a systematic way to solve the research problem or to answer the research questions.
Looks at the various steps that are generally adopted by a researcher in studying the research problem.

4. Agenda Qualitative versus Quantitative Method Selection Criteria
Research Paradigm for Quantitative Method
Quantitative Method using Questionnaires
Sampling Technique for Quantitative Method
Sample Size for Quantitative Method

5. Qualitative versus Quantitative Method Selection Criteria

6. Which Research Approach to Take?
Selection Criteria
Which Research Approach to Take?
Quantitative? Qualitative? A combination of both?

7. Qualitative or Quantitative or combination?
Selection Criteria
Qualitative or Quantitative or combination?
Depends on:
your research questions
your skills and abilities
your supervisor’s preferences
accessibility to the data
the feasibility within the available resources of time (and money)
your research paradigm (positivist or constructionist)

8. Research Paradigm for Quantitative Method (our world view)
Selection Criteria
Research Paradigm for Quantitative Method (our world view)
Positivism (Quantitative)
Interpretivism (Qualitative)
Ontology:
What is reality?
Reality is objective and
Singular; independent from the researcher
Reality is subjective
and multiple as seen
by the participants
Epistemology:
What is our relationship
with the knowledge that we are discovering? Are we part of the knowledge?
Researcher is independent
from that being researched. Knowledge is objective and governed by laws/theories.
Researcher interacts
with that being researched. Knowledge is something that is interpreted by the individuals
Axiology:
Role of values
Value-free
Value-laden

9. The Link between Research paradigm and the Methodology
Selection Criteria
The Link between Research paradigm and the Methodology

10. Quantitative Research Method
USING QUESTIONNAIRES

11. Quantitative Research
Refers to a deductive, theory-testing, objective and positivist process where scientific methods are applied to the study of people/organization/country.
Best suited to questions which seek differences within and across categories or discovering social trends.
Data collection methods are experimental studies and surveys.

12. Examples of Research Questions
Quantitative
Examples of Research Questions
Is there a relationship between uncertainty- avoidance and intention to visit New Zealand?
Do Malays, Chinese and Indians have different ethical perceptions?
What is the relationship between job insecurity and role overload on the surviving employees’ turnover intention?

13. Quantitative
Questionnaires
Questionnaires are a series of questions that the respondent answers on their own.
Most common quantitative method for postgraduate students.
Suitable for collecting data on relatively simple topics, and for gaining a general overview of an issue.
Questionnaires need to have clear questions, an easy to follow design and not be too long.

14. Quantitative method using questionnaireS
Step 1: Identify measurement scales Step 2: Create a measurement Table Step 3: Develop the questionnaire Step 4: Prepare a cover letter Step 5: Pre-test the questionnaire Step 6: Distribute the questionnaire Step 7: Analyze the Data Step 8: Report Findings

15. Step 1: identify measurement scales
Quantitative
Step 1: identify measurement scales
Identify variables from your hypothesis (developed from literature)
Find relevant measurement scales for each variable
Example:
H1: Uncertainty-avoidant people will have a less positive intention of visiting New Zealand
requires finding appropriate measurement scales for two variables:
uncertainty avoidance
intention to visit New Zealand.

16. Step 2: Create a measurement Table
Quantitative
Step 2: Create a measurement Table
A measurement table is a checklist to ensure measurement items of all variables are included in the questionnaire

17. Step 3: Develop the questionnaire
Quantitative
Step 3: Develop the questionnaire
Convert all items in measurement table into questionnaire format

18. Step 3: Develop the questionnaire (con’t)
Quantitative
Step 3: Develop the questionnaire (con’t)
Identify demographic variables to classify respondents

19. Step 4: Prepare a cover letter
Quantitative
Step 4: Prepare a cover letter
To explain objectives of study
To solicit and encourage participation
To address the issue of confidentiality

20. Step 5: Pre-test the questionnaire
Quantitative
Step 5: Pre-test the questionnaire
• To determine the time taken to complete the questionnaire. • To check whether respondents understand the instructions • To check whether there are unclear or ambiguous questions • To check response categories are exhaustive and mutually-exclusive • To provide an idea of the reliability and validity of the measurement questions

21. Step 6: Distribute the questionnaire
Quantitative
Postal Online Delivery and collection Collective administration

22. Step 7: analyZE the Data Software for Quantitative Data Analysis:

23. Step 8: report findings
Quantitative
Descriptive
Inferential

24. Analysis – Descriptive Statistics
Quantitative
Analysis – Descriptive Statistics

25. Analysis - Inferential Statistic
Quantitative
Analysis - Inferential Statistic

26. Analysis - Inferential Statistic
Quantitative
Analysis - Inferential Statistic

27. Quantitative
Results

28. Quantitative
Conclusion

29. Quantitative method using questionnaire
Step 1: Identify measurement scales Step 2: Create a measurement Table Step 3: Develop the questionnaire Step 4: Prepare a cover letter Step 5: Pre-test the questionnaire Step 6: Distribute the questionnaire Step 7: Analyze the Data Step 8: Report Findings

30. Sampling for Quantitative Method

31. EXHIBIT 16.1 Stages in the Selection of a Sample

32. EXHIBIT 16.2 Mailing List Directory Page

33. Probability versus Nonprobability Sampling
A sampling technique in which every member of the population has a known, nonzero probability of selection.
Use when need to answer research questions that require statistical estimation on the characteristics of the population from the sample, generalized results to population.
Can be used when sampling frame is available
Often associated with Survey or Experimental research strategies

34. Probability versus Nonprobability Sampling
Use when sampling frame is not available
A sampling technique in which units of the sample are selected on the basis of personal subjective judgment or convenience.
The probability of any particular member of the population being chosen is unknown.
Often associated with Case Study research strategies, where in-depth study on only a few cases are involved to gain theoretical insights.
Result not generalizable to population
Able to sample purposively and reach difficult to identify members of population

35. Choice of sampling Technique is determined by
Research questions/objectives: if need to estimate statistically the characteristics of the population from a sample (generalize result to population) require probability techniques; if do not require generalizations, can make use of non-probability sampling technique.
Availability of sampling frame: probability techniques requires some form of sampling frame, when sampling frame is not available, need to use non-probability sampling techniques.
Availability of resources e.g. financial and time
For many research projects, you will need to use a combination of different sampling techniques

36. Quantitative versus Qualitative study
Sample size requirement for quantitative study and qualitative study is different.
Quantitative study aims to generalize the results to the population, thus bigger sample size is required.
Qualitative research, seeks to gain “in-depth understanding”, thus tend to choose sample who has rich experience relating to the phenomenon of interest. Generalizability is not the priority.

37. Determining sample size
1. use sample size calculator that is available on line. It was calculated following Krejcie and Morgan (1970) Table as follow:
Key in population size, confidence interval 5% and confidence level of 95%, sample size required will be generated for you.
For instance, for a population size of 30,000, sample size generated is 379.
Determine Sample Size
Confidence Level:
95% 99%
Confidence Interval:
Population:
    
Sample size needed:

38. follow statistical rule
the desired ratio of sample size to construct numbers should be 20:1 (Hair, Anderson, Tatham and Black 1998).
When this ratio is observed, the result should be generaliazble if the sample is representative.

39. 3. a minimum sample size of 30 is required for statistical analysis of each category within the overall sample.
This is because only sample size of 30 or more produce a sampling distribution that is very close to a normal distribution that allows statistical analysis to be performed (Stutely, 2003).
Thus, in the case of a sub-category in the population that has less than 30 units, all units should be included as sample.

40. 4. Effect Size G*Power 3 software by Faul et al. (2007)
The effect size use is 0.15, margin error of 5%, power of (1-β) = 80%,
E.g. 30 number of predictors (30 items of a formative measure) and the results indicated that the minimum sample size that should taken into consideration is 187 respondents with the power of 0.80 (Hager, 2006).

41. Simple Random Sampling
Probability Sampling
Simple Random Sampling
Assures each element in the population of an equal chance of being included in the sample.
Use random number to select sample without bias, can be said to be representative of the whole population
Inappropriate to use if population covers a large geographical area and require face to face contact, random selection means selected cases are likely to disperse throughout the area and results in high travel costs.
However, if alternative data collection techniques like internet-based, postal or telephone interview, simple random would still be suitable

42. Probability Sampling Systematic Sampling
A starting point is selected by a random process and then every nth number on the list (sampling frame) is selected.
In some instances, it is not necessary to actually construct a sampling frame, e.g. online pop-up questionnaires
Every tenth visitor to the site over a specific period of time are invited in the survey to participate

43. Probability Sampling Stratified Sampling
Simple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of the population.
The sampling frame is divided into a number of subsets (e.g. managers versus non-managers) and samples are selected from each subset/strata randomly.
The extra step needed to identify distinguishable strata within a population means it is likely to take longer, more expensive, and more difficult to explain than simple random or systematic random sampling

44. Cluster Sampling
Allows focusing on a few (e.g. four) geographical clusters from the high number of geographical areas in the country (population), selecting clusters randomly makes cluster sampling a probability sampling technique.
Travelling and interviewing elements in a few geographical clusters, reduces time and cost.
Restricting sample to a few geographical clusters maximizes the amount of data you can collect using face-to-face methods within the resources available
However, you need to maximize the number of clusters covered to increase the amount of variation in the population

45. Nonprobability Sampling
Convenience Sampling
Obtaining those people or units that are most conveniently available.
E.g. person interviewed in a shopping centre
While this may not be problematic if there is little variation in the population, where the population is more varied, it can result in participants that are of limited representation of population
E.g. taking part-time MBA students as surrogate for managers, bias in educational background, thus interpretations should be treated with caution

46. Nonprobability Sampling
Judgment (Purposive) Sampling
An experienced individual selects the sample based on personal judgment about some appropriate characteristic of the sample member.
E.g. using case study strategies, intend to select small samples and wish to select cases that are most informative
E.g. only select those who travelled overseas in the last two years

47. Nonprobability Sampling (cont’d)
Snowball Sampling
A sampling procedure in which initial respondents are selected by probability methods and additional respondents are obtained from information provided by the initial respondents.
Used when difficult to identify members of the desired populations
e.g. people who are working while claiming unemployment benefits.
E.g. breast cancer patient survivors

48. Nonprobability Sampling (cont’d)
Quota Sampling
Quota sampling is a type of stratified sample except that selection of cases within a strata is entirely non-random.
Quota sampling has similar sample size requirements as probabilistic sampling techniques.
Cheaper, faster and sampling frame not required.
Quota used include age, gender and social class.
Interviewer decide who to interview until they have completed quota given to them for each strata

49. Talk summary
Qualitative versus Quantitative Method Selection Criteria
Research Paradigm for Quantitative Method
Quantitative Method using Questionnaire
Sampling Technique for Quantitative Method
Sample Size for Quantitative Method
Take workshops /courses that will help build your methodology competencies