1 / 15

Quote from Literature Review

Using Qualitative Comparative Analysis in Strategic Management Research T.Greckhamer, V.F.Misangyi, H.Elms, R.Lacey 2008, Organizational Research Methods 11(4) Presented by Kevin Burr, to TTMG 5004 June 25, 2009. Quote from Literature Review.

patty
Download Presentation

Quote from Literature Review

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Using Qualitative Comparative Analysis in Strategic Management ResearchT.Greckhamer, V.F.Misangyi, H.Elms, R.Lacey2008, Organizational Research Methods 11(4)Presented byKevin Burr, to TTMG 5004June 25, 2009

  2. Quote from Literature Review “Perhaps the only enduring point of consensus during the last three decades of research in [strategic management] literature has been that industry, corporate, and business-unit effects are not independent, and that this condition presents a seriouschallenge for general linear methodologies given their assumption that effects are independently generated.” Kevin Burrburr@sce.carleton.ca

  3. Introduction • Purpose of the paper is to demonstrate that Qualitative Comparative Analysis (QCA) is a valid technique for management research • The paper gives a step by step description of how the authors used QCA to analyze 2,841 cases of business-unit performance, as well as discussing the advantages and disadvantages of the technique. Kevin Burrburr@sce.carleton.ca

  4. Qualitative Comparative Analysis “…is a technique, developed by Charles Ragin in 1987, for solving the problems that are caused by making causal inferences on the basis of only a small number of cases. The method is used in social science and is based on the binary logic of Boolean algebra, and attempts to maximize the number of comparisons that can be made across the cases under investigation.” (Wikipedia) Kevin Burrburr@sce.carleton.ca

  5. QCA approach: • Construct a property space out of a set of theoretically relevant causal attributes of interest • In this study: industry, corporate, and business-unit attributes • Analyze the diversity and causal complexity underlying the outcome of interest • In this study, superior and inferior business-unit performance • Done using a Truth Table and Boolean Algebra • Evaluate and interpret the results of the study. Kevin Burrburr@sce.carleton.ca

  6. 1. Construct the Property Space • The integrity of cases must be maintained in the analysis: • a configuration is defined as ‘‘any multidimensional constellation of conceptually distinct characteristics that commonly occur together’’ • A single difference among cases may constitute a difference in kind • the character of any particular case may change qualitatively if a single key attribute is changed • ‘‘property space approach’’ to typology • Any given set of theoretically relevant attributes constitute a property space such that each combination of attributes represents a specific location within the space. • Select both cases and the attributes that theoretically may cause the outcome of interest, and use these to construct the property space. Kevin Burrburr@sce.carleton.ca

  7. 2. Analyzing the Property Space • Type 1: Descriptive analysis of the property space. • examine the distribution of cases across the property space: The identification of those locations in the property space that are inhabited by cases and those that are not, and the diversity of this distribution. • Type 2: Examining the sufficiency of causal conditions. • Uses Boolean methods to assess whether attributes of cases are necessary and/or sufficient for the outcome of interest to occur. Kevin Burrburr@sce.carleton.ca

  8. Truth Table (a subset) Please see paper for explanation of fields Kevin Burrburr@sce.carleton.ca

  9. For example: Panel B shows the results for the Service Sector. Three out of the four conditions usually sufficient for superior performance are combinations of industry, corporate, and business-unit attributes (Conditions 1ss, 3ss, and 4ss; left side of Panel B), The remaining one is a combination of corporate and business-unit attributes (2ss). Two of the three combinations sufficient for inferior performance contain all three types of attributes (Conditions 2si and 3si; see right side of Panel B, Table 4), The other consists of a single corporate attribute (1si). 3. Evaluation and Interpretation of Results Kevin Burrburr@sce.carleton.ca

  10. Boolean Results Please see paper for explanation of fields Kevin Burrburr@sce.carleton.ca

  11. Since probabilistic criteria are used to capture complex combinations of attributes, it is possible that the configurations may to some degree result from random chance Paper uses subsets of the data to ‘‘cross-validate’’ the findings and show their interpretations are robust. This validation of results is important. Different sets of attributes can create different property spaces and therefore potentially different configurations of causal attributes. The more attributes the more likely chance will come into play “Crisp” data sets (i.e. 1 or 0) are not very realistic There are newer approaches which use Fuzzy or Multi-value (MVQCA) for modeling Limitations Kevin Burrburr@sce.carleton.ca

  12. Considerations for using QCA • Well suited to small-N analyses when the number of cases is too small for conventional linear statistical methods but at the same time too large for the in-depth qualitative analysis generally utilized for very small numbers of cases • Whether the researcher is interested in isolating independent effects or in studying combinations of effects. Kevin Burrburr@sce.carleton.ca

  13. References fuzzy set/Qualitative Comparative Analysis Website: http://www.u.arizona.edu/~cragin/fsQCA Greckhamer, T., Misangyi, V., Elms, H. and Lacey, R. (2008), “Using qualitative comparative analysis in strategic management research - An examination of combinations of industry, corporate, and business unit effects”, Organizational Research Methods 11(4), pp. 695-726 Ragin, C. “What is Qualitative Comparative Analysis?” NCRM Research Methods Festival 2008. (Unpublished), Accessed June 24, 2009 http://eprints.ncrm.ac.uk/250/1/What_is_QCA.pdf, Rihoux, B., “Qualitative Comparative Analysis (QCA) and Related Systematic Comparative Methods - Recent Advances and Remaining Challenges for Social Science Research”, International Sociology 21(5), pp. 679–706 "Qualitative comparative analysis" Wikipedia, The Free Encyclopedia. 28 Oct 2008, Accessed June 24, 2009 http://en.wikipedia.org/w/index.php?title=Qualitative_comparative_analysis&oldid=248240525 Kevin Burrburr@sce.carleton.ca

  14. Thank-you

  15. Overview of results Kevin Burrburr@sce.carleton.ca

More Related