Download - Research Methods William G. Zikmund, Ch12
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Business Research Methods
William G. Zikmund
Chapter 12:
Experimental Research
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Experiment
• A research investigation in which conditions are controlled
• One independent variable is manipulated (sometimes more than one)
• Its effect on a dependent variable is measured• To test a hypothesis
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Basic Issues of Experimental Design
• Manipulation of the Independent Variable
• Selection of Dependent Variable
• Assignment of Subjects (or other Test Units)
• Control Over Extraneous Variables
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The experimenter has some degree of control over the independent variable. The variable is independent because its value can be manipulated by the experimenter to whatever he or she wishes it to be.
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Experiment Treatment
Alternative manipulations of the independent variable being
investigated
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Independent Variable
• The experimenter controls independent variable.
• The variable’s value can be manipulated by the experimenters to whatever they wish it to be.
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Manipulation of Independent Variable
• Classificatory Vs. continuous variables
• Experimental and control groups
• Treatment levels
• More than one independent variable
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Experimental Treatments
• The alternative manipulations of the independent variable being investigated
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Dependent Variable
• Its value is expected to be dependent on the experimenter’s manipulation
• Criterion or standard by which the results are judged
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Dependent Variable
• Selection– e.g... sales volume, awareness, recall,
• Measurement
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Test Units
• Subjects or entities whose response to the experimental treatment are measured or observed.
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Two Types of Experimental Error
• Constant errors• Random errors
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Field versus Laboratory Experiments
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Controlling Extraneous Variables
• Elimination of extraneous variables
• Constancy of conditions
• Order of presentation
• Blinding
• Random assignment
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How May an Experimenter control forExtraneous Variation?
• Eliminate Extraneous Variables
• Hold Conditions Constant
• Randomization
• Matching Subjects
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Establishing Control
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Demand Characteristics
• Experimental procedures that intentionally hint to subjects something about the experimenter’s hypothesis
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Demand Characteristics
• Guinea pig effect
• Hawthorne effect
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Field Vs. Laboratory Experiment
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Laboratory Experiment Field Experiment
Artificial-Low Realism
Few ExtraneousVariables
High control
Low Cost
Short Duration
Subjects Aware ofParticipation
Natural-High Realism
Many ExtraneousVariables
Low control
High Cost
Long Duration
Subjects Unaware ofParticipation
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Control Groups
Isolate extraneous variation
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When does an Experiment have Internal Validity?
Internal Validity - The ability of an experiment to answer the question whether the experimental treatment was the sole cause of changes in a dependent variable
Did the manipulation do what it was supposed to do?
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Factors Influencing Internal Validity
• History
• Maturation
• Testing
• Instrumentation
• Selection
• Mortality
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Isolating Extraneous Variationwith a Control Group
• History Effects
• Maturation Effects
• Mortality Effects
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Type of Extraneous Variable Example
History - Specific events in theenvironment between the Beforeand After measurement that are beyond the experimenter’s control
Maturation - Subjects changeduring the course of the experiment
Testing - The Before measure alertsor sensitizes subject to nature of experiment or second measure.
A major employercloses its plant intest market area
Subjects become tired
Questionnaireabout the traditionalrole of women triggers enhanced awareness of womenin an experiment.
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Instrument - Changes ininstrument result in response bias
Selection - Sample selectionerror because of differentialselection comparison groups
Mortality - Sample attrition; some subjects withdraw from experiment
New questions aboutwomen are interpreteddifferently from earlierquestions.
Control group and experimental group isself-selected groupbased on preference forsoft drinks
Subjects in one groupof a hair dying study marry rich widows and move to Florida
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How can Internal Validity Increase?
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Increasing Internal Validity
• Control group
• Random assignment
• Pretesting and posttesting
• Posttest only
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What are the Different Basic Experimental Designs?
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Quasi-Experimental Designs
• One Shot Design (After Only)
• One Group Pretest-Posttest
• Static Group Design
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One Shot Design (After Only)
X O1
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One Group Pretest-Posttest
O1 X O2
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Static Group Design
Experimental Group X O1 Control Group O2
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Three Good Experimental Designs
• Pretest - Posttest Control Group Design
• Posttest Only Control Group
• Solomon Four Group Design
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Pretest-Posttest Control Group Design
Experimental Group R O1 X O2
Control Group R O3 X O4
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Posttest Only Control Group
Experimental Group R X O1
Control Group R O2
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One-Shot DesignInternal Validity Problems
• History– weak
• Maturation– weak
• Testing– not relevant
• Instrumentation– not relevant
• Selection– weak
• Mortality– weak
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One-Group Pretest-PosttestInternal Validity Problems
• History– weak
• Maturation– weak
• Testing– weak
• Instrumentation– weak
• Selection– controlled
• Mortality– controlled
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Static-Group DesignInternal Validity Problems
• History– controlled
• Maturation– possible source of
concern
• Testing– controlled
• Instrumentation– controlled
• Selection– weak
• Mortality– weak
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Pretest-Posttest ControlInternal Validity Problems• History
– controlled
• Maturation– controlled
• Testing– controlled
• Instrumentation– controlled
• Selection– controlled
• Mortality– controlled
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Solomon Four-Group DesignInternal Validity Problems• History
– controlled
• Maturation– controlled
• Testing– controlled
• Instrumentation– controlled
• Selection– controlled
• Mortality– controlled
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Posttest-Only ControlInternal Validity Problems
• History– controlled
• Maturation– controlled
• Testing– controlled
• Instrumentation– controlled
• Selection– controlled
• Mortality– controlled
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Solomon Four Group Design
Experimental Group 1: R O1 X O2
Control Group 1: R O3 O4
Experimental Group 2: R X O5
Control Group 2: R X O6
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Advanced Experimental Designs are More Complex
• Completely randomized
• Randomized block design
• Latin square
• Factorial
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Completely Randomized Design
• An experimental design that uses a random process to assign subjects (test units) and treatments to investigate the effects of only one independent variable.
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Completely Randomized Designs
Average minutesshopper spendsin store
Control:no music
Experimentaltreatment:slow music
Experimentaltreatment:fast music
16 18 12
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Independent Variable A
Group A Group B Group C
Level 1 Level 2 Level 3
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Completely Randomized Design
With a pretest posttest
Group A R O1 X1 O2
Group A R O3 X2 O4
Group A R O5 X3 O6
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With a posttest
Group A R X1 O1
Group B R X2 O2
Group C R X3 O3
Completely Randomized Design
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Randomized Block Design
• An extension of the completely randomized design in which a single extraneous variable that might affect test units’ response to the treatment has been identified and the effects of this variable are isolated by blocking out its effects.
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Independent Variables
Control:no music
Experimentaltreatment
slow music
Experimentaltreatment: fast music
Mornings andafternoons
Evening hours
Blo
ckin
g v
aria
ble
Randomized Block Design
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Factorial Design
• An experiment that investigates the interaction of two or more variables on a single dependent variable.
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Independent Variable 1
No Musiccart signs
Slow Music Fast MusicNo Music
Grocerycart signs
Ind
epen
den
t V
aria
ble
2
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Price Red Gold
$25 Cell 1 Cell 4$30 Cell 2 Cell 5$35 Cell 3 Cell 6
Package Design
Factorial Design -- Roller Skates
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Effects
• Main effect• The influence of a
single independent variable on a dependent variable.
• Interaction effect• The influence on a
dependent variable by combinations of two or more independent variables.
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Men
Women
Ad A Ad B
65
65
70 60
Main Effectsof Gender
Main Effects of Ad
>
>
2 x 2 Factorial Design
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100
90
80
70
60
50
40
30
20
10
Ad A Ad B
Women
Men
Bel
ieva
bilit
yInteraction Between Gender and
Advertising Copy
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Level 1 Level 2
Level 1
Level 2
Group A
Group DGroup C
Group B
Ind
epen
den
t V
aria
ble
2Independent Variable 1
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Group A R O1 X11 O2
Group B R O3 X21 O4
Group C R O5 X12 O6
Group D R O7 X22 O8
2 x 2 Factorial with a Pretest Posttest
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Group A R X11 O1
Group B R X21 O2
Group C R X12 O3
Group D R X22 O4
2 x 2 Factorial Design with a Posttest Measure
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A Test Market Experiment on Pricing
Sales in Units (thousands)
Regular Price$.99
1301188784
X1=104.75X=119.58
Reduced Price$.89
145143120131
X2=134.75
Cents-Off CouponRegular Price
1531299699
X1=119.25
Test Market A, B, or CTest Market D, E, or FTest Market G, H, or ITest Market J, K, or L
MeanGrand Mean
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Latin Square Design
• A balanced, two-way classification scheme that attempts to control or block out the effect of two or more extraneous factors by restricting randomization with respect to the row and column effects.
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1 2 3
1 A B C2 B C A3 C A B
Order of UsageS
UB
JEC
T
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TEST MARKETING
Controlled experimentationControlled experimentation
Not just tryingNot just tryingsomethingsomethingoutout
But scientificBut scientifictestingtesting
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Controlled experimentationControlled experimentation
Not just tryingNot just tryingsomethingsomethingoutout
But scientificBut scientifictestingtesting
Test Marketing
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Test Marketing
• An experimental procedure that provides an opportunity to test a new product or a new marketing plan under realistic market conditions to measure sales or profit potential.
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ESTIMATEESTIMATEOUTCOMESOUTCOMES
IDENTIFY ANDIDENTIFY ANDCORRECTCORRECT
WEAKNESSESWEAKNESSESIN PLANSIN PLANS
Functions of Test Marketing
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A Lengthy and Costly Procedure
$$$$$$$$$$
Loss of Loss of SecrecySecrecy
When notWhen notto Test?to Test?
How LongHow LongShould aShould a
Test Last?Test Last?
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Popular Test Markets
• Pittsfield, Massachusetts
• Charlotte, North Carolina
• Columbus, Ohio• Little Rock, Arkansas• Evansville, Indiana • Cedar Rapids, Iowa
• Eau Claire,Wisconsin• Wichita, Kansas• Tulsa, Oklahoma • Omaha, Nebraska• Grand Junction.
Colorado• Wichita Falls, Texas• Odessa-Midland, Texas
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Selecting a Test Market
• Population size
• Demographic composition
• Lifestyle considerations
• Competitive situation
• Media
• Self-contained trading area
• Overused markets - secrecy
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Control Method of Test Marketing
• Small city
• Low chance of being detected
• Distribution is forced (guaranteed)
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The Advantages of Using the Control Method of Test Marketing
• Reduced costs
• Shorter time period needed for reading test market results
• Increased secrecy from competitors
• No distraction of company salespeople from regular product lines
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Some Problems Estimating Sales Volume
• Over-attention
• Unrealistic store conditions
• Reading competitive environment incorrectly
• Incorrect volume forecasts– Adjusted data
– Penetration and repeat purchase rate
• Time lapse
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High Tech Test Markets
ElectricElectricTestTest
MarketsMarketsSimulatedSimulated
TestTestMarketsMarkets Virtual-realityVirtual-reality
SimulatedSimulatedTest MarketsTest Markets