Bibliographic record
Abstract
Purpose Why are some libraries more market‐oriented than others? The purpose of this paper is to answer this question by examining the pertinent issues underlying the inter‐relationship between market‐orientation and superior service performance. Design/methodology/approach An integrated methodological approach of qualitative as well as quantitative methods was used to gain knowledge behind the market‐orientation – service performance relationship. The directors and consumers of 33 academic and special libraries participated as respondents in this study. Findings In total, three kinds of libraries were found: the strong; the medium; and the weak. The findings show that the higher market‐orientation is positively connected with the libraries’ superior service performance. Research limitations/implications The implication of this research does suggest that thegapbetween the service provider and receiver can be closed by increasing the marketing competence of service provider. Practical implications The practical implication for libraries is that it pays to be market‐oriented, the ultimate result being higher customer satisfaction. Originality/value The relationship between market‐orientation and service performance has yet to be explored and established in the library world. This is one of the first such studies which attempted to investigate this inter‐relationship.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".