Chapter 4 Experimental Research Designs

1. Chapter 4 • Experimental Research Designs

2. AIMS • To outline deductive logic; • To illustrate (laboratory) experimental research design; • To give a management example of experimental design; • To indicate why experimental logic is taken out of the laboratory; • To illustrate quasi-experimental design.

3. Deductive Logic Entails: • 1. Reduction of theoretical statements to causal/predictive hypotheses that are testable. This entails: • 2. Identification of: • Independent Dependent • Variable Variable • 3. Neutralize Extraneous • Effects of: Variables

4. The Problems for Research Design in Deductive Research • Methods for observing, Methods for observing • manipulating and and measuring changes • measuring the variation in the Dependent Variable • of the Independent Variable • (Problem D) (Problem E) • Independent Dependent • Variable Variable • (Problem A) (Problem B) • Methods of controlling for, or ruling out, • the influence of the Extraneous Variables • (Problem F) • Extraneous • Variables • (Problem C)

5. ‘Classical’ or ‘True’ Experimental Research Design • Two important requirements: • 1. Control • 2. Measurement • Testing Hypotheses in Experimental Research • Need to vary independent variable(s) and to investigate effects upon the dependent variable. • In this need to have: • 1. An experimental group • 2. A control group

6. Experimental Protocol and Procedure • Application of Experimental Treatment • by Experimenter • PRE TREATMENT POST TREATMENT • Experimental Group E1 Experimental Group E2 • matched • Control Group C1 Control Group C2 • no experimental treatment • E1 and E2 Measure the incidence of the dependent variable, in the experimental group, prior to and after the experimental treatment. • C1 and C2 Measure the incidence of the dependent variable, in the control group, prior to and after the occurrence of the experimental treatment in the experimental group. • (Cont’d)

7. Therefore E2 - E1 = De (the difference between the post and pre-treatment measures of the dependent variable in the experimental group). • Similarly C2 - C1 = Dc (the difference between the post and pre-treatment measures of the dependent variable in the control group). • If there is a difference between De and Dc it follows that this must have been caused by the experimental treatment.

8. Two main methods for overcoming and controlling confounded extraneous variables in experiments: • 1. The use of systematic controls • 2. The use of randomization • Both (1) and (2) are used so as to rule out, or control for, rival explanations, to the one being tested. (1) and (2) are physical controls as opposed to statistical controls.

9. Hawthorne Studies - Western Electric Company, Chicago • 1. Studies relationship between • Physical working and Employee • conditions productivity • therefore • Independent Dependent • Variable Variable • Lighting Output • 2. Pre-treatment Post-treatment • illumination varied • Experimental Experimental • Group E1 Group E2 • Matched Productivity Productivity • Isolation Measured Measured • Control Control • Group C1 Group C2 • No experimental treatments • E2 - E1 = De C2 - C1= Dc • Any difference between De and Dc must be due to the manipulation of the independent variable.

10. Findings • 1. Output in experimental group regardless of how illumination was varied. • Simultaneously • 2. Output in control group. • These results and the results of similar experiments caused researchers to conclude that they were not simply looking at the effects of physical working conditions • also • Effects of employee norms and attitudes etc. • ‘Hawthorne effect’ • or • ‘Experimental artefacts’ • related to • 1. Indexicality • 2. Experimenter effects • 3. Subjects’ mediation via interpretation.

11. Why take research out of the laboratory? • Five possible reasons: • 1. Indexicality • 2. Experimenter effects • 3. Interpretation by subjects • 4. Ethics • 5. The nature of the research problem.

12. Quasi Experiments • Involve data from naturally occurring events. Therefore: • 1. Researcher cannot manipulate independent variables • 2. Control problematic • Speeding • Deaths on Roads Crack-down • Time • The Connecticut Crack-down on Speeding

13. An Example of a Quasi Experiment: Wall et al., 1986.

14. From this research design - if the hypotheses regarding the impact of autonomous groups upon intrinsic and extrinsic job satisfaction, intrinsic job motivation, organizational commitment and mental health were to survive the test then: • Employees in situations A1, A2, A3, B2 and B3 should record higher scores on these 5 variables than employees in situations B1, C1, C2 and D1 e.g. : • B1< B2, B3 • A1> B1, C1, D1 • A2, B2 > C2 • ‘the results show that autonomous group working is a viable proposition ...[which]...may have economic benefits. This is not as the theory predicts, because groups enhance operators’ motivation and effort; economic benefits stem instead from the logic of the groups themselves...indirect labour costs decrease and productivity benefits can accrue’ (Wall et al., 1986: 299-300).

15. Conclusions: • Deductive logic is expressed in a number of different research designs including laboratory experiments, quasi-experiments and (analytical) surveys/questionnaires; • All attempt to test theory by deducing hypotheses and gathering data; • All include in their design • 1. manipulating/varying the causal or independent variable(s); • 2. trying to control extraneous variables; • 3. measuring variance in the dependent variable(s) - i.e. the effects. • Different ways of doing 1-3 result in different deductive research designs.