Visual Guidance Strategies for Low-Carbon Behaviour in Smart Scenic Spot Digital Wayfinding Systems: A Case Study of Qinhuangdao
スマート観光地デジタル案内システムにおける低炭素行動の視覚的誘導戦略：秦皇島の事例研究 (AI 翻訳)
L. N. Zhao
🤖 gxceed AI 要約
日本語
本研究は、スマート観光地のデジタル案内システムにおいて、視覚的説得理論を応用し、低炭素行動を促す3つの戦略（データ駆動、感情駆動、社会規範駆動）を比較した。ユーザーテストの結果、行動意図に有意差はなかったが、感情駆動戦略が選好で優位だった。層別適応型の視覚的誘導戦略システムを提案している。
English
This study applies visual persuasion theory to low-carbon behavior guidance in smart scenic spot digital wayfinding systems, comparing three strategies (data-driven, emotion-driven, social norm-driven). User testing found no significant difference in behavioral intention, but emotion-driven strategy was preferred. Proposes a stratified adaptation strategy system.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、観光地の脱炭素化やスマートシティ施策が進む中、行動変容を促すデザイン手法は、地域のGX推進に参考となる。ただし、日本の制度や政策との直接的な関連は薄く、一般的な行動科学の知見として捉えるのが適切。
In the global GX context
Globally, this contributes to the growing literature on behavioral interventions for climate action, particularly in tourism. It offers insights for designing digital interfaces that promote sustainable behaviors, relevant to sustainable tourism and smart city initiatives.
👥 読者別の含意
🔬研究者:行動科学とデザイン介入の統合に関する知見を提供。
🏢実務担当者:観光施設や自治体が低炭素行動を促すデジタルサイネージ設計に活用可能。
🏛政策担当者:観光分野の脱炭素政策における行動変容施策の参考になる。
📄 Abstract（原文）
Under the background of the “dual carbon” strategy and the integrated development of smart tourism, digital wayfinding systems in scenic spots, as the most frequent information touchpoints with tourists, possess significant potential for guiding public low-carbon behaviour. To the best of the author’s knowledge, this study is among the first to systematically apply visual persuasion theory to low-carbon behaviour guidance in scenic spot digital wayfinding systems. Taking Shanhaiguan Scenic Spot in Qinhuangdao as a case study, this paper integrates visual persuasion theory with persuasive design theory to construct a three-dimensional visual guidance framework of “information content – visual form – interaction mode” and designs three sets of digital wayfinding interface prototypes with different guidance strategies (data-driven, emotion-driven, and social norm-driven). Through user testing and questionnaire surveys (N = 32), the results showed that the main effect of strategy type on low-carbon behavioural intention was not significant, F(2, 62) = 0.02, p =.98, η2 =.001, with all three strategies yielding mean scores above the neutral point of 4 on a 7-point scale (data-driven M = 4.75, SD = 1.68; emotion-driven M = 4.80, SD = 1.49; social norm-driven M = 4.78, SD = 1.62). Notably, the emotion-driven strategy demonstrated a clear advantage in the preference ranking, accounting for 46.9% of all selections. This divergence between behavioural intention ratings and preference rankings suggests the possibility of different mechanisms underlying immediate decision-making and long-term preference formation. The study proposes a “stratified adaptation” low-carbon behaviour visual guidance strategy system, offering operable strategy references for the low-carbon design of smart scenic spot wayfinding systems and providing a new pathway for visual communication design to intervene in public energy-saving behaviour.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.7716/aem.v15i3.3665first seen 2026-08-16 04:58:12
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