Service system transformation through service design: Linking analytical dimensions and service design approaches
Bibliographic record
Abstract
The increasingly interconnected world is leading to continuous and profound transformations within and among service systems (e.g., firms, industries, societies). While service research studying such transformations is growing, the literature is missing a conceptualization of service system transformation (SST) that accounts for the richness and diversity of the phenomenon. This hinders the development of approaches to intentionally influence SST toward desired paths. Providing an integrated, multidimensional understanding of SST, this paper explores how service design can intentionally influence SST. To do so, the paper contributes by advancing conceptual clarity of SST and delineating three analytical dimensions—scope, endurance, and paradigmatic radicalness—that, in combination, provide a framework for understanding the diversity of the transformations unfolding within and across service systems. Building upon this conceptualization, the paper systematizes how service design approaches can foster SST along these dimensions, setting the ground for service design to further strengthen its transformative potential.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.005 | 0.035 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".