Value‐based management, EVA and stock price performance in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to determine the extent to which Canadian companies have embraced value‐based management (VBM) methods, identify the characteristics of these companies and of the executives responsible for the introduction of VBM in their organisations and assess the stock price performance of the companies that use VMB vs. those that do not. Design/methodology/approach The study is based on a survey of CEOs of a large sample of Canadian companies and examines the relation of a number of explanatory variables, including stock price performance, to the probability of using VBM versus not using VBM via a regression analysis of qualitative choice, namely logit analysis. Findings The study finds that value‐based management methods are widely used in Canada, with the likelihood of usage being higher for larger companies with younger and more educated executives with an accounting/finance background. The statistical analysis that follows the tabulation of survey results indicates companies that used EVA had a better stock price performance than those not using EVA. Moreover, our logit regression analysis shows that companies with better stock market performance exhibited higher likelihood of using EVA. Practical implications The study implies that the lower usage of EVA in Canada, especially at the corporate level, provides some explanation for the stock market under‐ performance of the Canada market vis‐à‐vis the USA in the 1990s. Originality/value To our knowledge, this study serves as the first widespread evaluation of VBM methods in Canada and their effect on company and stock price performance.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it