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Two Philosophical Paradigms* of Research Design Management Research:  An Introduction  (Esaterby-Smith et al., 1991/2001) ...
Figure 1.1 Main aspects of management research (P+p+t; 10) Political Philosophical Technical (Q+q data/analysis)
Two main traditions/ philosophies/paradigms (ch2: 22) <ul><li>Auguste Comte’s (1853) 8 implications of positivism*  </li><...
Figure 3.1 Different assumptions* about the nature of reality  (25: after Morgan and Smirich, 1980) <ul><li>Subjectivist* ...
Figure 3.2 Key features of positivist and phenomenological paradigms (P.27; Burrell and Morgan, 1979) Science is driven by...
Develop ideas through induction* from data Formulate hypotheses and then test them Look at the totality of each situation ...
Small samples investigated in depth or over time Taking large samples To establish different views of phenomena So that th...
Figure 3.3 Key choices  of research design  (P.33) Falsification  Verification Field work methods Experimental design Gene...
Figure 3.5 Questions of validity, reliability and generalisability  (P.41) How likely is it that ideas and theories genera...
Figure 5.4 Differences between content analysis and grounded theory  (p.106) Testing out themes, developing patterns Testi...
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Two Philosophical Paradigms

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Major Figures and Tables of Two Paradigms of research design by Easterby-Smith et al., 2001, London: Sage

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Two Philosophical Paradigms

  1. 1. Two Philosophical Paradigms* of Research Design Management Research: An Introduction (Esaterby-Smith et al., 1991/2001) Summarized by Yender McLEE 哲學典範 ;
  2. 2. Figure 1.1 Main aspects of management research (P+p+t; 10) Political Philosophical Technical (Q+q data/analysis)
  3. 3. Two main traditions/ philosophies/paradigms (ch2: 22) <ul><li>Auguste Comte’s (1853) 8 implications of positivism* </li></ul><ul><li>Independence: the observer </li></ul><ul><li>Value-freedom: objective value=beliefs and interests </li></ul><ul><li>Causality 因果關係 </li></ul><ul><li>Hypothectico-deductive 假設 </li></ul><ul><li>Operationalization </li></ul><ul><li>Reductionism </li></ul><ul><li>Generalization </li></ul><ul><li>Cross-section analysis </li></ul>
  4. 4. Figure 3.1 Different assumptions* about the nature of reality (25: after Morgan and Smirich, 1980) <ul><li>Subjectivist* Objectivist* </li></ul><ul><li>projection of human imagination </li></ul><ul><li>social construction* </li></ul><ul><li>symbolic discourse* </li></ul><ul><li>contextual field of information </li></ul><ul><li>concrete process* </li></ul><ul><li>concrete structure </li></ul><ul><li>6 ontological; phenomenologist; social constructionist; positivist; Dery and Toulouse (1996); 4d*=debates, discourse, dialog and discussion; SOP? </li></ul>
  5. 5. Figure 3.2 Key features of positivist and phenomenological paradigms (P.27; Burrell and Morgan, 1979) Science is driven by human interests Science is value-free Observer is part of what observed Observer is independent The world is social constructed and subjective The world is external and objective Basic beliefs: Phenomenological paradigm Positivist paradigms
  6. 6. Develop ideas through induction* from data Formulate hypotheses and then test them Look at the totality of each situation Reduce phenomenological simplest elements* (Descartes, method) Try to understand what is happening Look for causality and fundamental laws Focus on meanings* (make sense) Focus on facts Researcher should Phenomenological paradigm Positivist paradigm
  7. 7. Small samples investigated in depth or over time Taking large samples To establish different views of phenomena So that they can be measured Using multiple methods Operationalizing concepts Preferred methods include:
  8. 8. Figure 3.3 Key choices of research design (P.33) Falsification Verification Field work methods Experimental design Generating theories Testing theories Small sample Large sample Research is involved Researcher is independent
  9. 9. Figure 3.5 Questions of validity, reliability and generalisability (P.41) How likely is it that ideas and theories generated in one settings will also apply in other settings? What is the probability that patterns observed in a sample will also be presented in the wider population? generalizability Will similar observations be made by different researchers on different occasions? Will the measure yielded the same results on different occasions? reliability Has the researcher gained full access to the knowledge and meaning of informants? Does an instrument measure what is supposed to measure validity Phenomenologist viewpoint Positivist viewpoint
  10. 10. Figure 5.4 Differences between content analysis and grounded theory (p.106) Testing out themes, developing patterns Testing hypotheses Inductive Deductive Closer to the data, open much longer Objectivity Go by feel Go by frequency Holistic Bitty Grounded theory (data first?) Content Analysis
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Major Figures and Tables of Two Paradigms of research design by Easterby-Smith et al., 2001, London: Sage

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