On Independent Study - quasi-experiment
The basic idea underlying quasi-experiment, using an example, is as follows:
Choose 2 companies of very similar profile:
Step 1: Company A and Company B
Step 2: choose 5-6 years of financial data of both companies
Step 3: for one company, say Company A, a stimulus was introduced, e.g. implementation of ISO9000 by Company A in year 3; while Company B did not.
Step 4: Try to evaluate whether implementation of ISO9000 improved the financial performance of Company A
How:
Method 1: graphic approach, e.g. line graph, as the following diagram illustrates:
Method 2: store the panel data of Company A and B in one file and conduct a multiple regression analysis; use a flag to indicate whether ISO9000 has been implemented; 0 = not implemented while 1 = implemented.
E.g. of file fields can be: (1) financial year; (2) Return of Equity; (3) implementation of ISO 9000; (4) Sales Turnover; (5) Gearing ratios)... etc
You could improve your research design with a larger sample size (e.g. more companies) and/or with mixed research methods (e.g. to cross-validate findings [triangulation]).
Reference
Cook, T.D. (1983) "5: Quasi-Experimentation: Its ontology, epistemology and methodology" in Morgan, G. (editor) Beyond Method, pp. 74-94, Sage.
Choose 2 companies of very similar profile:
Step 1: Company A and Company B
Step 2: choose 5-6 years of financial data of both companies
Step 3: for one company, say Company A, a stimulus was introduced, e.g. implementation of ISO9000 by Company A in year 3; while Company B did not.
Step 4: Try to evaluate whether implementation of ISO9000 improved the financial performance of Company A
How:
Method 1: graphic approach, e.g. line graph, as the following diagram illustrates:
Method 2: store the panel data of Company A and B in one file and conduct a multiple regression analysis; use a flag to indicate whether ISO9000 has been implemented; 0 = not implemented while 1 = implemented.
E.g. of file fields can be: (1) financial year; (2) Return of Equity; (3) implementation of ISO 9000; (4) Sales Turnover; (5) Gearing ratios)... etc
You could improve your research design with a larger sample size (e.g. more companies) and/or with mixed research methods (e.g. to cross-validate findings [triangulation]).
Reference
Cook, T.D. (1983) "5: Quasi-Experimentation: Its ontology, epistemology and methodology" in Morgan, G. (editor) Beyond Method, pp. 74-94, Sage.
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