From service quality to service theory and practice
Bibliographic record
Abstract
Purpose – The purpose of this editorial paper is to set out the vision for theJournal of Service Theory and Practice(JSTP). Design/methodology/approach – Together with personal reflections of the authors, it is based on a review of literature on the past, the present and the future of service research, an analysis of a broad range of global environmental trends, as well as interviews, communications and feedback from eminent scholars in the field of service research. Findings – The paper sets out the expanded aims and scope for theJSTP. It also explains the rationale for the change in title and elaborates upon expectations for manuscripts submitted to the journal. Research limitations/implications – It identifies a set of research priorities for the journal and the field. Practical implications – It highlights the importance of translating theory into practice by making meaningful recommendations and action plans for firms and managers. Originality/value – This paper is written at a time when the journal has been undergoing considerable change, including retitling as well as the complete restructuring of the editorial team. It is also written at a time when the field of service management is being transformed by new approaches and research perspectives. As such, it is both necessary and timely.
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.
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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.006 | 0.048 |
| Scholarly communication | 0.023 | 0.016 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".