A Study on the Complementary Direction of Guidelines for Developing Green Conventions in Korea: Using Comparative Analysis among Domestic and Overseas Cases
Bibliographic record
Abstract
As interests in sustainability have been increasing and discussions of environmental issues are ongoing globally, the MICE industry (Meeting, Incentive Travel, Convention, and Exhibition), which is attracting attention as a high value-added industry, also became an important part of the sustainability domain. Consequently, there has been a rise in hosting ‘green conventions’, or ‘green MICE’ which are designed to minimize all the negative impacts on the environment such as energy and water consumption. At some point, a large number of studies had been conducted for the development of green conventions, but most of them mainly used empirical methods. Although the Ministry of Environment has presented guidelines and some domestic exhibition convention centers have implemented strategies, they are not enough compared to overseas countries. This study aims to examine the latest guidelines to supplement the guidelines of Korea’s green convention. In this regard, the study will use a comparative analysis method among the current guidelines of convention centers in Australia (Sydney), Canada (Vancouver), and the U.S.A (Detroit and San Francisco) and draw up complementary directions. As a result, we could draw out common items in the facility management and event planning and operation section. Some items were similar in all convention centers, but others were included in the guidelines of few centers only. This research is sure to be the academic background for developing related practices and standards for the future green convention in Korea. In addition, this study will have value in terms of investigating sustainable management in the convention industry as the importance of sustainability in the tourism industry emerges.
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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 | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".