New service development: areas for exploitation and exploration
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
Abstract The management of new service development (NSD) has become an important competitive concern in many service industries. However, NSD remains among the least studied and understood topics in the service management literature. As a result, our current understanding of the critical resources and activities to develop new services is inadequate given NSD’s importance as a service competitiveness driver. Until recently, the generally accepted principle behind NSD was that “new services happen” rather than occurring through formal development processes. Recent efforts to address this debate have been inconclusive. Thus, additional research is needed to validate or discredit the belief that new services happen as a result of intuition, flair, and luck. Relying upon the general distinctions between research exploitation and exploration, this paper describes areas in NSD research that deserve further leveraging and refinement (i.e. exploitation) and identifies areas requiring discovery or new study (i.e. exploration). We discuss the critical substantive and research design issues facing NSD scholars such as defining new services, choice in focusing on the NSD process or performance (or both), and specification of unit of analysis. We also examine what can be exploited from the study of new product development to further understanding of NSD. Finally, we explore one important area for future NSD research exploration: the impact of the Internet on the design and development of services. We offer research opportunities and research challenges in the study of NSD throughout the paper.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it