Business Research Methods William G Zikmund Chapter 12

Business Research Methods William G. Zikmund Chapter 12: Experimental Research

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

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

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.

Experiment Treatment Alternative manipulations of the independent variable being investigated

Independent Variable • The experimenter controls independent variable. • The variable’s value can be manipulated by the experimenters to whatever they wish it to be.

Manipulation of Independent Variable • • Classificatory Vs. continuous variables Experimental and control groups Treatment levels More than one independent variable

Experimental Treatments • The alternative manipulations of the independent variable being investigated

Dependent Variable • Its value is expected to be dependent on the experimenter’s manipulation • Criterion or standard by which the results are judged

Dependent Variable • Selection – e. g. . . sales volume, awareness, recall, • Measurement

Test Units • Subjects or entities whose response to the experimental treatment are measured or observed.

Two Types of Experimental Error • Constant errors • Random errors

Field versus Laboratory Experiments

Controlling Extraneous Variables • • • Elimination of extraneous variables Constancy of conditions Order of presentation Blinding Random assignment

How May an Experimenter control for Extraneous Variation? • • Eliminate Extraneous Variables Hold Conditions Constant Randomization Matching Subjects

Establishing Control

Demand Characteristics • Experimental procedures that intentionally hint to subjects something about the experimenter’s hypothesis

Demand Characteristics • Guinea pig effect • Hawthorne effect

Field Vs. Laboratory Experiment

Laboratory Experiment Field Experiment Artificial-Low Realism Natural-High Realism Few Extraneous Variables Many Extraneous Variables High control Low Cost High Cost Short Duration Long Duration Subjects Aware of Participation Subjects Unaware of Participation

Control Groups Isolate extraneous variation

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?

Factors Influencing Internal Validity • • • History Maturation Testing Instrumentation Selection Mortality

Isolating Extraneous Variation with a Control Group • History Effects • Maturation Effects • Mortality Effects

Type of Extraneous Variable Example History - Specific events in the environment between the Before and After measurement that are beyond the experimenter’s control A major employer closes its plant in test market area Maturation - Subjects change during the course of the experiment Subjects become tired Testing - The Before measure alerts or sensitizes subject to nature of experiment or second measure. Questionnaire about the traditional role of women triggers enhanced awareness of women in an experiment.

Instrument - Changes in instrument result in response bias New questions about women are interpreted differently from earlier questions. Selection - Sample selection error because of differential selection comparison groups Control group and experimental group is self-selected group based on preference for soft drinks Mortality - Sample attrition; some subjects withdraw from experiment Subjects in one group of a hair dying study marry rich widows and move to Florida

How can Internal Validity Increase?

Increasing Internal Validity • Control group • Random assignment • Pretesting and posttesting • Posttest only

What are the Different Basic Experimental Designs?

Quasi-Experimental Designs • One Shot Design (After Only) • One Group Pretest-Posttest • Static Group Design

One Shot Design (After Only) X O 1

One Group Pretest-Posttest O 1 X O 2

Static Group Design Experimental Group Control Group X O 1 O 2

Three Good Experimental Designs • Pretest - Posttest Control Group Design • Posttest Only Control Group • Solomon Four Group Design

Pretest-Posttest Control Group Design Experimental Group R O 1 X O 2 Control Group R O 3 X O 4

Posttest Only Control Group Experimental Group R Control Group R X O 1 O 2

One-Shot Design Internal Validity Problems • History – weak • Instrumentation – not relevant • Maturation • Selection – weak • Testing – not relevant • Mortality – weak

One-Group Pretest-Posttest Internal Validity Problems • History • Instrumentation – weak • Maturation • Selection – weak • Testing – weak – controlled • Mortality – controlled

Static-Group Design Internal Validity Problems • History – controlled • Maturation – possible source of concern • Testing – controlled • Instrumentation – controlled • Selection – weak • Mortality – weak

Pretest-Posttest Control Internal Validity Problems • History – controlled • Maturation – controlled • Testing – controlled • Instrumentation – controlled • Selection – controlled • Mortality – controlled

Solomon Four-Group Design Internal Validity Problems • History – controlled • Maturation – controlled • Testing – controlled • Instrumentation – controlled • Selection – controlled • Mortality – controlled

Posttest-Only Control Internal Validity Problems • History – controlled • Maturation – controlled • Testing – controlled • Instrumentation – controlled • Selection – controlled • Mortality – controlled

Solomon Four Group Design Experimental Group 1: Control Group 1: Experimental Group 2: Control Group 2: R O 1 X R O 3 R X O 2 O 4 O 5 O 6

Advanced Experimental Designs are More Complex • • Completely randomized Randomized block design Latin square Factorial

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.

Completely Randomized Designs Control: no music Average minutes shopper spends in store 16 Experimental treatment: slow music 18 Experimental treatment: fast music 12

Independent Variable A Level 1 Group A Level 2 Level 3 Group B Group C

Completely Randomized Design With a pretest posttest Group A R O 1 X 1 O 2 Group A R O 3 X 2 O 4 Group A R O 5 X 3 O 6

Completely Randomized Design With a posttest Group A R X 1 O 1 Group B R X 2 O 2 Group C R X 3 O 3

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.

Randomized Block Design Independent Variables Blocking variable Control: no music Mornings and afternoons Evening hours Experimental treatment slow music Experimental treatment: fast music

Factorial Design • An experiment that investigates the interaction of two or more variables on a single dependent variable.

Independent Variable 1 Independent Variable 2 No Music cart signs Grocery cart signs Slow Music Fast Music

Factorial Design -- Roller Skates Package Design Price Red Gold $25 $30 $35 Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 Cell 6

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.

2 x 2 Factorial Design Ad A Ad B Men 65 Main Effects > of Gender Women 65 70 60 > Main Effects of Ad

Interaction Between Gender and Advertising Copy 100 90 Wo 80 me n Believability 70 Men 60 50 40 30 20 10 Ad A Ad B

Independent Variable 2 Independent Variable 1 Level 2 Level 1 Group A Group B Level 2 Group C Group D

2 x 2 Factorial with a Pretest Posttest Group A R O 1 X 11 O 2 Group B R O 3 X 21 O 4 Group C R O 5 X 12 O 6 Group D R O 7 X 22 O 8

2 x 2 Factorial Design with a Posttest Measure Group A R X 11 O 1 Group B R X 21 O 2 Group C R X 12 O 3 Group D R X 22 O 4

A Test Market Experiment on Pricing Sales in Units (thousands) Regular Price $. 99 Test Market A, B, or C Test Market D, E, or F Test Market G, H, or I Test Market J, K, or L Mean Grand Mean Reduced Price $. 89 Cents-Off Coupon Regular Price 130 118 87 84 145 143 120 131 153 129 96 99 X 1=104. 75 X=119. 58 X 2=134. 75 X 1=119. 25

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.

Order of Usage SUBJECT 1 1 2 3 A B C A C A B

TEST MARKETING Not just trying something out Controlled experimentation But scientific testing

Test Marketing Not just trying something out Controlled experimentation But scientific testing

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.

Functions of Test Marketing ESTIMATE OUTCOMES IDENTIFY AND CORRECT WEAKNESSES IN PLANS

A Lengthy and Costly Procedure When not to Test? $$$$$ Loss of Secrecy How Long Should a Test Last?

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

Selecting a Test Market • • Population size Demographic composition Lifestyle considerations Competitive situation Media Self-contained trading area Overused markets - secrecy

Control Method of Test Marketing • Small city • Low chance of being detected • Distribution is forced (guaranteed)

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

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

High Tech Test Markets Electric Test Markets Simulated Test Markets Virtual-reality Simulated Test Markets