Measuring and Understanding Brand Value in a Dynamic Model of Brand Management
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
We develop a structural model of brand management to estimate the value of a brand to a firm. In our framework, a brand’s value is the expected net present value of future cash flows accruing to a firm due to its brand. Our brand value measure recognizes that a firm can change its brand equity by investing in advertising. We estimate quarterly brand values in the stacked chips category for the period 2001–2006 and explore how those values change over time. Comparing our brand value measure to its static counterpart, we find that a static measure, which ignores advertising and its ability to affect brand equity dynamics, yields brand values that are artificially high and that fluctuate too much over time. We also explore how changing the ability to build and sustain brand equity affects brand value. At our estimated parameterization, if brand equity were to depreciate more slowly, or if advertising were more effective at building brand equity, then brand value would increase. However, counterintuitively, we find that when the effectiveness of advertising is sufficiently high, increasing the rate at which brand equity depreciates can increase the value of a firm’s brand, even as it reduces the value of the firm overall. Data and the online appendix are available at https://doi.org/10.1287/mksc.2016.1020 .
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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