An Evaluation of the Organizational Learning Survey
Bibliographic Data
| ID | 13655831 |
|---|---|
| Authors | Subhra Chakrabarty (Mississippi State University, corresponding author), Joseph N Rogé (Department of Computer Information Systems & Quantitative Methods, College of Business Administration, The University of Texas Pan American) |
| Year | 2002 |
| Volume | 91 |
| Issue | 3_suppl |
| Pages | 1255-1267 |
| Publication date | 2002-12-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Psychological Reports (JOURNAL) |
| Journal identifiers | ISSN: 0033-2941 • E-ISSN: 1558-691X |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.2466/pr0.2002.91.3f.1255 |
| PMID | 12585547 |
| OpenAlex | W2135209984 |
| Language | EN |
| References cited | 17 |
A mail survey of a national random sample of 2,000 marketing managers was conducted. The data provided by 221 respondents were analyzed to assess the unidimensionaliry of the 21-item 1997 Organizational Learning Survey developed by Goh and Richards. A confirmatory factor analysis using LISREL 8.30 did not support the unidimensionality of the 21-item survey; however, unidimensionality was established for most of the dimensions. Managerial implications and directions for research were suggested
Confirmatory factor analysis · LISREL · Sample (material · Statistics · Structural equation modeling · Survey methodology · Survey research · Applied Psychology · Customer Service Quality and Loyalty · Management and Marketing Education · Mathematics · Psychology · Social Psychology · Technology Adoption and User Behaviour
A Paradigm for Developing Better Measures of Marketing Constructs
Methodology Review
An Updated Paradigm for Scale Development Incorporating Unidimensionality and Its Assessment
The use of lisrel in validating marketing constructs
A Paradigm for Developing Better Measures of Marketing Constructs
Structural equation modeling in practice
The Analysis of Covariance Structures
Disciplines of Organizational Learning
On the Meaning of within-Factor Correlated Measurement Errors
| Highly cited | No |
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