MEMBANGUN KINERJA PEMASARAN MELALUI ORIENTASI PASAR: PERANAN PEMBELAJARAN ORGANISASIONAL DAN INOVASI (Studi Empiris pada UKM Makanan dan Minuman di Eks-Karesidenan Banyumas)
Bibliographic record
Abstract
The objectives of the research was to explain the contradictory results of some research on the relationship between market orientation and marketing performance; It was also aimed at investigating and to analyzing the development process of market orientation. To test the empirical models, Structural Equation Modelling (SEM) was used. Among software used to assist the analysis in this study were AMOS 16.0, SPSS 16.0 and Microsoft Excel 2007. Sample size of this research was 200 owners and/or managers of Small and Medium Enterprises (SMEs) running food and beverage sector in Karesidenan Banyumas area. The findings of this research had successfully explained: (1) the research gap on the causal relationship between market orientation and marketing performance, (2) the research gap on the causal relationship between market orientation and innovation, (3) ) the research gap on the causal relationship between innovation and marketing performance (4) the indistinct roles of learning organizational in converting market orientation to marketing performance. (5) this study had enriched similar literatures on the field that examined the antecedent of market orientation, and (6) contributed to the limited numbers of literatures on market orientation and innovation in developing countries particularly in Small and Medium Enterprises (SMEs). The managerial findings of the research was the marketing performance development model for the Small and Medium Enterprises (SMEs) that is called the pyramid of marketing performance development (PMPD). The limitations of this research and the implications for future research were also presented in this study.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".