Understanding consumer satisfaction with railway transportation service: An application of 7Ps marketing mix
Bibliographic record
Abstract
Railway transportation (RT) plays a crucial role and it is an inseparable part of one country's main traffic network. However, due to the advantages of aviation industry and other modes of transportation, the share of RT of total traffic volume gradually decreases and RT enterprises are facing various difficulties. Customer satisfaction is one of the essential factors for the survival of any business organization. In order to accordingly offer products and services, RT companies must understand their customers and find out to what extent the consumer is satisfied with their offered services and products. The objective of this study is to evaluate the effect of each factor on the passengers' satisfaction and freight owners for RT service in Vietnam's context. The study utilizes 7Ps marketing mix (Product, Price, Place, Promotion, People, Process and Physical evidence) to analyze the customer satisfaction level. The collected data are analyzed through the multiple regression method by the use of SPSS software to understand the relationship of marketing mix elements and consumers' satisfaction. The study finding helps us guide the RT operators on their marketing strategy formulation. Customers will benefit through enhanced knowledge regarding both core and augmented products associated with RT services. It is also expected that this work can be used as a reference material for RT managers to enhance competitiveness.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".