Hybrid strategic thinking in deregulated retail energy markets
Bibliographic record
Abstract
Purpose The purpose of this paper is to present the results of research undertaken to test the use of traditional strategic approaches in developing competitive advantage through the assessment of the importance to small‐ and medium‐sized firms of cost and services available in a competitive retail market. Design/methodology/approach A survey involving 181 small‐ and medium‐enterprises provided responses to a questionnaire that measured the importance of key success factors to the customer when making a decision regarding their choice of natural gas supplier. Findings The findings suggest that, the use of a low‐cost strategy alone may not be sufficient to create a competitive advantage for suppliers and that a hybrid strategy of cost, service quality, enhanced communication and unbundled services will. Research limitations/implications The sample was limited to natural gas customers in Ontario, Canada at a specific period of time in the deregulation process reducing the ability to generalize results across other regions and other energy types. This limitation is defended by the recognition that the importance of variables measured is consistent between regions and energy types. Practical implications Energy suppliers can create a competitive advantage over their competition if they can differentiate themselves through the application of enhanced service quality and communications. Originality/value Little, if any, empirical research exists that addresses the response of customers to strategic approaches of suppliers in deregulating energy markets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".