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- 검색키워드
- 저자 : M Ronald Buckley (검색결과 2 건)
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MULTITRAIT-MULTIMETHOD INFORMATION MANAGEMENT: GLOBAL STRATEGIC ANALYSIS ISSUES
Shawn M Carraher,M Ronald Buckley,Joseph A Cote 사람과세계경영학회 1999 Global Business and Finance Review Vol.4 No.2
International researchers commonly encounter fitting problems when analyzing Multitrait-Multimethod data with confirmatory factor analysis (CFA) in both domestic and cross-cultural research (Scherpenzeel and Saris 1997). In 1992, Kenny and Kashy examined a special case of one of the most frequently used CFA models using one data set and found that it was not statistically identified and, therefore, not estimable. They then argued that most MTMM data were likely to conform closely to this special case, and because of this, alternative CFA models should be utilized in most data analysis. In this study nine data sets are analyzed using five different additive factor analytic models (CFA with inequality constraints, CFA with error variances fixed to uniqueness estimates from exploratory factor analysis, Rindskopf parameterization, correlated errors model, and a combination of the Rindskopf correlated errors model) and one multiplicative factor analytic (MUTMUM) model. As with previous attempts, myriad fitting problems were encountered with all six alternative specifications. Closer inspection indicates fitting problems may be due to imperfections in the data rather than fundamental flaws with the model specifications- indicating possible problems with the robustness of the techniques utilized. Several suggestions for improving international research to possibly avoid these problems are provided as are alternative methods of estimating construct validity.
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STRATEGIC ENTREPRENEURIALISM IN ANALYSIS: GLOBAL PROBLEMS IN RESEARCH
Shawn M Carraher,M Ronald Buckley,Joseph A Cote People&Global Business Association 2000 Global Business and Finance Review Vol.5 No.2
A decade ago, a series of published articles debated the amount of method variance in organizational measures from all over' the world (Bagozzi and Yi, 1990; Spector, 1987; Williams, Cote, and Buckley, 1989). Interestingly, while all three studies analyzed the same data sets, they reached different conclusions concerning the presence of method variance. Spector (1987) reported that method effects were relatively minor, Bagozzi and Yi (1990) found them to be of moderate importance, and Williams et al. (1989) found method effects to be quite pervasive. Up to this time, no one has offered reasonable explanations as to why these results were found. While some of the differences in results may be due to the use of different analytic methods; even the use of the same technique (Confirmatory Factor Analysis - CFA) resulted in different conclusions. The differences found by these researchers (Bagozzi and Yi, 1990; Williams et al., 1989) are likely due to the multiple solutions problem caused by factor indeterminacy which is common with factor analytic techniques which is likely to exist with domestic and international data (Cattell and Gorsuch, 1963; Gorsuch, 1974; 1983; Rozeboom, 1992). A series of simulations were performed which indicate that there are, in fact, many reasonable solutions which can be fit to MTMM data using CFA and that therefore it appears that the multiple solutions problem is also significant for CFA as it is for other factor analytic methods. Some possible remedies for the problem of fitting MTMM models are proposed. We suggest that researchers need to be adaptable in the analytic methods which they employ and the topics that they explore (entrepreneurial researchers) and to carefully examine their data so that the research questions match the capabilities of the techniques utilized.
KCI
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