Identification of Planning, Attitudinal, and Operational Differences among Types of Exporters

1977 ◽  
Vol 2 (2) ◽  
pp. 16-21 ◽  
Author(s):  
George Tesar

Multivariate discriminate analysis was used to identify differences among heavy exporters, light exporters, and nonexporters based on planning, attitudinal, and operational factors. A total of 423 small and medium-sized manufacturing firms were studied. The results clearly indicate that differences exist between the heavy exporters and the nonexporters. The discriminant function developed on the basis of these differences can be used to classify other firms into the appropriate category given the necessary information about them. Consequently, this study offers a step in the direction of developing a method for systematic identification of potential exporters.

1976 ◽  
Vol 11 (3) ◽  
pp. 175-179
Author(s):  
R. C. Walls ◽  
O. D. Murphree ◽  
C. Angel ◽  
J. E. O. Newton

2009 ◽  
Author(s):  
Clarence E. Rash ◽  
Keith L. Hiatt ◽  
Robert M. Wildzunas ◽  
J. Lynn Caldwell ◽  
John A. Caldwell ◽  
...  

2011 ◽  
Author(s):  
Andrew R. Hull ◽  
Kathryn L. Wolf ◽  
Reginald Adkisson

2016 ◽  
Vol 54 (08) ◽  
Author(s):  
T Zhan ◽  
LI Franke ◽  
M Arnold ◽  
M Breinig ◽  
F Heigwer ◽  
...  

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.


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