Research Designs
Facilitator:
Assoc. Prof. Dr. Abdul Hamid b. Hj. Mar Iman
Former Director,
Centre for Real Estate Studies
Faculty of Engineering and Geoinformation Science
Universiti Teknologi Malaysia
Skudai, Johor
Research Design
“What it is”
 Researcher’s overall strategy for answering
research questions.
 How the study will be performed
 Different strengths and weakness
 Classified in a number of ways:
* Descriptive
* Analytic, observational
Quasi-experimental
* Interventional
* Experimental
Research Design - Descriptive Studies”
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Describes general characteristics of
phenomena. E.g.
* distribution of industrial sites, squatter
areas, trend in property values, etc.
Further classified into:
* correlational studies
* case studies
* cross-sectional survey
Descriptive studies
“Correlational studies”

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Uses population data to compare between different groups. E.g.
* Mean per house price could be compared to per capita income
levels for several geographic areas.
Have a number of limitations:
* Multi-characteristic nature of population → which correlate to
which?
- beliefs of the investigators (e.g. income and house price are
somehow linked)
- researcher’s bias, lack of knowledge (factors other than
income!!)
* Tend to be bi-directional → underestimate underlying reality. E.g.
Deposit
Loan margin
Loan period
?
?
Price
Price
?
?
xx
Income
Income
Interest rate
Locality
* Correlation does not basically measure cause-and-effect → Misses
the opportunity to explain “what causes what, how much, and how”
Descriptive studies
“Case Studies”



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Describe individual or a group of cases showing certain
characteristics, in certain situations, under certain conditions.
Describe a relatively “new”, “unusual”, or “peculiar” issues/things
worth researching. E.g.
* Why the shopping complex fails?
* What makes the place very popular?
* How did SARS, Avien flu affect Johor Bahru property market?
Limited to some “localised”, “personalised” problem/issue and
suggesting potential hypotheses to be tested in future studies.
May not be generalisable due to some “unusualness”,
“peculiarity”
attached to a particular case
To a certain extent may suggest potential hypotheses to be
tested in future studies.
Descriptive studies
“Cross-Sectional Survey”

Presence or absence of some characteristics
are determined at the same time point. E.g.
whether subjects were current smokers
(exposure) and whether they had evidence of
emphysema (disease). Because both
exposure and disease are determined at the
same time, it is impossible to determine, in
most cases, which came first. Therefore,
cross-sectional studies can suggest
associations between an exposure and a
disease but cannot prove causality.
Elements of Design
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Observations or Measures
* Symbolized by an 'O'
* Can refer to a single measure (e.g., sale price), a single instrument with multiple
items (e.g. Likert scale), a complex multi-part instrument (e.g., a survey), or a whole
battery of tests or measures given out on one occasion.
* To distinguish among specific measures, use subscripts: O1, O2, and so on.
Treatments or Programs
* Symbolized with an 'X‘
* Can refer to a simple (e.g., a technique) or complex (e.g., an industrial training
program) intervention.
* No symbol for no-treatment control or comparison group
* Can use X+ and X- to indicate treatment and control respectively.
* Can use subscripts to distinguish different programs or program variations.
Groups
* Each group is shown on one line in the design structure. So, if the design notation has
three groups, there are three lines in the design.
Assignment to Group
* Designated by a letter at the beginning of each line (i.e., group)
* Describes how the group is assigned.
* Major types of assignment: R = random assignment; N = non-equivalent groups; C =
assignment by cutoff; Time
Elements of Design
“Generic examples”
Type of design
General structure
Example of issue
Effects of crime on
housing demand in the
Johor Bahru inner city &
city-outskirt areas
Effects of KLIA project
on land-travel convenience
among the residents in the
neighbouring areas
Relationship between
investor’s risk attitude and
choices of type of investment
in shares
R = random assignment; X = treatment; O = observation; N = non-random
Research design
“An example”
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Research question/issue:
“Effects of KLIA project on land-travel convenience among the residents
in the neighbouring areas”
Design elements:
* Convenience
- saved travel-time, T
- reduction in petrol consumption, P
- evasion from traffic congestion, C
- increased frequency of public transport service, F
* Residents
- Group 1: own transport
- Group 2: public transport
* Hypothesis 1: Average time-travel saved is 20 minutes “after” project
2: Average reduction in petrol consumption is 15%/trip
3: Average time of traffic congestion drops to 15 minutes
4: Frequency of public transport increases by 20% after
“project”
Research design - “Pre-test post-test
equivalent-group quasi-experimental”
N
N
O1
X
O1
T1
T1’
P1
C1
F1
P1’
C1’
F1’
O2
X
T2
P2
C2
F2
O1 = Own transport
O2
T2’
P2’
C2’
F2’
O2= Public transport
X = KLIA project
Cause-and-effect investigated using instrument – structured q’naire
Research design
“An example”
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Research question/issue:
“Does decision to choose a particular type of shares investment have any
relationship with risk attitude of the investor?”
Design elements:
* Type of investment (post-test observation, O”)
- share
High-risk share
corporate, C
- property trust, P
Low-risk share
- bon, B
government, G
* Risk attitude (post-test observation, O’)
- Taker, T
- Averser, A
- Neutral, N
* Hypothesis 1: If one is a risk-taker, then invest in high-risk shares
2: If one is risk-averser, then invest in low-risk shares
3: If one is risk-neutral, then invest in low-risk and/or high-risk shares
Research design
“Post-test non-experimental”
Post-test
observation
Post-test
treatment
N
O
X
T
C, P
A
G
C
B
G
P
B
High-risk
shares
Low-risk
shares
N
X
O
Risk attitude groups
Shares’ risk categories
Cause-and-effect investigated using various interview
instruments
Thank you!