The study is thoroughly checked for internal validity with a proper balance in the structure of design and adoption of appropriate research instruments. The adoption of case study evaluation is highly suitable to find out to identify the implications of supply chain implications in global sourcing strategy of Zara. “Findings can be said to be internally invalid because they may have been affected by factors other than those thought to have caused them, or because the interpretation of the data by the researcher is not clearly supportable” (Seliger & Shohamy 1989, 95).
The internal validity of the data is checked, with the following factors:
Subject variability: The study has taken care to avoid subject variability, by keeping concentration on the hypothesis through out the structure of the paper Historical evidence: While considering the Case study selection the study observed the historical background of the company chosen. Maturation: the study also observed the maturity of the case taken and Industry before commenting and summarizing the issue
the study is purely valid in terms of instrumentation, as it intends to observe sourcing strategy The study is also checked for the external validity by generalizing the findings to a larger group of companies that are not involved in the study and to the other sectors of Industry other than apparel, to observe the general implications of global sourcing. The study has checked for the external validity with the following factors:
Population characteristics (subjects)
Interaction of subject selection and research Descriptive explicitness of the independent variable The effect of the research environment Researcher or experimenter effects Data collection methodology The effect of time Quantitative methods allow for a broader study, involving a greater number of subjects, and enhancing the generalization of the results. Quantitative research is generally defined as the collection of numerical and statistical data. Read also about Zara corporate social responsibility issues
It is perceived as the scientific approach of research employing ‘experimental’ and ‘quasi-experimental’ strategies. Harvey (2002) as cited in Roboneill describes quantitative data as data which can be sorted, classified, measured in a strictly “objective” way – they are capable of being accurately described by a set of rules or formulae or strict procedures which then make their definition (if not always their interpretation) unambiguous and independent of individual judgments.
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