Towards a Conceptual Framework for Customer Intelligence in the Era of Big Data
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
The dominance of services and service-based products in today's economy highlights the significance of customer intelligence for service offerings. Furthermore, the revolution of big data has generated a vast amount of customer data and reshaped the dimensions of organization, management, and technology within enterprises. The big data era also acknowledges the role of customers for value co-creation. Therefore, the objective of this paper is to propose a service-based framework for customer intelligence in the age of big data, hereafter called the SBCI framework, from the design science and service science approach. It laid the groundwork upon design science; the SBCI framework is proposed with the detailed artefacts, including construct, model, method, and instantiation. The framework also reflects service science through the three levels: 1) the network of service systems level for service proposal, 2) the service system level for service creation, and 3) the service level for service operation.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.003 | 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