The effects of information technology and operation performance on service supply chain management practices with moderating effect of capital owners
Bibliographic record
Abstract
The objective of this study is to analyze and review the influence of government regulations and information technology on the operational performance of local television stations in East Java with service supply chain management practices as the mediator variable and capital owner’s intervention as the moderator variable. The data of exploratory research was collected through questionnaires distributed to twenty-nine local televisions stations, selected through saturated sampling method from a population of local television stations in East Java, and was analyzed using structural equation modeling. The finding of this study reveals that government regulations and information technology significantly influence the operational performance of local television stations with service supply chain management (SCM) practices as the mediator variable, which means that better government regulations and better information technology are analogous with the importance for the improvement of local television stations operational performance. Capital owner intervention weakens service SCM practices on operating performance and has a direct and immediate effect on reducing the operational performance of local television stations. The practical implications of this study signify the understanding that service SCM practices is an important concept in enhancing the operational performance. Capital owner’s intervention weakens service SCM practices on operating performance of local television stations.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".