Three value-focused strategic questions for continuously updating your business model
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 article describes how a well-functioning, competent system of self-evaluation of customer value creation and delivery can be an essential part of a corporate initiative to reach or sustain the winner state.” Design/methodology/approach The true value the firm’s customers are obtaining from interactions with the firm can be assessed by obtaining candid answers to the following three strategic value-focused business model questions: 10;(1)9;How do you make sure you are offering the benefits your customers really appreciate most? 10;(2)9;What group of customers is the primary focus of your efforts? 10;(3)9;How do you help your customers fully appreciate the delivery of the benefits offered? 10;These three questions were derived from an in-depth investigation of the business models of real-world firms that succeeded in moving to and remaining in the winner state, an ongoing longitudinal study undertaken by the authors’ team in North America, Southeast Asia and Europe. Findings Based on the authors’ research, companies with sustainable winning business models institutionalize the processes of systematic, ongoing collection of the information about customer value, integrating it into the strategic decision making processes. Practical implications To be effective, according to our research, the analysis needs to consider value proposition (what is promised), value targeting (who is the primary recipient) and value delivery (how the promise is fulfilled) separately, which most companies don’t do. Originality/value The article offers top executives, marketing executives and board members process for updating and adjusting the business model so that it continues to produce superior revenue, operating profit and ongoing customer and shareholder satisfaction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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