Customer Co-creation through the Lens of Service-dominant Logic: A literature Review.
Bibliographic record
Abstract
The proliferation of the service sector in the age of big data highlights the role of customers as co-creators for business value. Customer interactions on digital platforms make a significant contribution to the vast amount of big data. Considering the lack of systematic and comprehensive studies on this research stream, the objective of the paper is to conduct a concept-centric literature review on customer co-creation from the lens of the service-dominant logic and guide future research. The paper systematically synthesizes and categorizes 50 articles by the concept matrix to reveal the interrelationships among them. The result of the paper provides a holistic overview of value, resources, and mechanisms relevant to customer co-creation. Concrete ideas for future research directions are also proposed for enriching the academic literature and promoting practical implications. The paper holds important implications for accelerating customer co-creation for service providers to achieve big-data-driven competitive advantages.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".