Context sensitive transit oriented development assessment: AHP weighted TOD standards for regional railway hubs in Thailand
Bibliographic record
Abstract
This study develops a context-specific Transit-Oriented Development (TOD) evaluation framework for Thailand's regional railway hubs by integrating the Analytic Hierarchy Process (AHP) with established TOD Standards. Through expert-based pairwise comparisons, we determined that transit accessibility (19.1%), connectivity (15.0%), and walkability (14.1%) represent priority criteria for the Thai context, contrasting with the uniform weighting system of international standards. We applied this AHP-weighted framework to assess six regional railway stations: Chiang Mai, Phitsanulok, Nakhon Ratchasima, Khon Kaen, Pattaya, and Hat Yai Junction. Comparative analysis revealed that Hat Yai Junction achieved the highest TOD potential ranking under both standard (74/100) and AHP-weighted (79.7/100) methods, followed by Chiang Mai (72/100 standard; 78.8/100 weighted). The most notable scoring differential appeared in Nakhon Ratchasima (69/100 vs. 78.4/100), demonstrating the significant impact of context-sensitive weighting. All stations showed common weaknesses in cycling infrastructure (average 3.2/5) and car use reduction metrics while achieving the highest scores in transit accessibility criteria. Station-specific evaluation identified targeted improvement priorities: enhancing cycling networks in Chiang Mai, improving pedestrian infrastructure in Phitsanulok, and increasing block connectivity in Pattaya. This contextualized framework gives planners a practical tool for prioritizing TOD investments in Thailand's regional centers.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".