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Volume 5 Issue 1 July 2007
Is Research that is both Causally Adequate and Adequate on the Level of Meaning Possible or Necessary in Business Research? A Critical Analysis of Some Methodological Alternatives.
D.A.L. Coldwell
School of Management, University of KwaZulu-Natal, Durban, South Africa
Open University, Milton Keynes, UK
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There has been a recent resurgence of interest in both statistical methods aimed at generating causally adequate explanations in business research and criticisms of these. Running parallel with this resurgence of statistical interest has been critical discussion of the adequacy of such explanations at the level of meaning and specific attempts to address this issue with techniques such as those used in grounded theory have emerged in response. However, the core issue remains unresolved. Is causally adequate explanation possible with statistical -type analyses? And, are idiographic techniques such as grounded theory, able to capture explanations that are valid at the level of meaning?
The paper critiques some past and recent methods aimed at implementing statistical analyses for generating causally adequate explanations and qualitative techniques aimed at providing explanations that are adequate at the level of meaning.
The paper reviews an empirical study aimed at providing such a complete explanation and questions, building on the perspectives of evidence-based management and critical realism, whether such fully adequate explanations are practically possible or, indeed, fundamentally necessary in generating knowledge that is useful for solving specific managerial problems.
The paper suggests that to generate effective evidence-based data in business research which is capable also of taking account of the ongoing dynamics of the business situation, a triangulated dialectical methodology be adopted.
Keywords:
Causal adequacy, adequacy at the level of meaning, phenomenology, grounded research, imponderable evidence, dialectical triangulation, methodological triangulation, critical realism, evidence-based research, dualism, piecemeal social engineer
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