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Driving Sustainable Choices: The Impact of Warning Messages in Car Advertisements on Consumer Attention and Emotional Responses

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Zenodo2026-07-20 更新2026-08-01 收录
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Supporting data for the article "Driving Sustainable Choices: The Impact of Warning Messages in Car Advertisements on Consumer Attention and Emotional Responses". This repository contains the two datasets supporting the article "Driving Sustainable Choices: The Impact of Warning Messages in Car Advertisements on Consumer Attention and Emotional Responses", which examines how the framing (gain vs. loss) and the format (text vs. image) of environmental warnings embedded in static car advertisements affect consumers' visual attention, emotional responses and perceived message effectiveness, and whether environmental concern moderates these effects. Two independent studies were conducted with Spanish participants who were regular users of a private car. Study 1 (Study_1.sav, N = 41; 18 men, 23 women). A between-subjects eye-tracking experiment conducted at a laboratory of the University of Granada between January and November 2024. Participants were randomly assigned to view a single static car advertisement containing an environmental warning framed either positively (gain) or negatively (loss); each warning combined a short text and a congruent image. Stimuli (2560 × 1440 px) differed only in the warning. Two areas of interest (AOIs) were defined: image (412 × 266 px) and text (1301 × 213 px). Eye movements were recorded with a Tobii Pro Nano eye-tracker (60 Hz; accuracy 0.3° of visual angle) and processed in Tobii Pro Lab using an I-VT filter with a 60 ms minimum fixation threshold, over a 10 s free-viewing presentation. The dataset contains, for each participant, the experimental condition, the environmental concern score obtained at recruitment (Environmental Concern Scale, Díaz, Beerli & Martín, 2004; Cronbach's α = .88), and four attention metrics: fixation duration and fixation count on the image AOI and on the text AOI. Data from all 41 participants were retained after quality checks. These data support the MANCOVA reported in the article (Tables 1–4 and Appendices 5–10). Study 2 (Study_2.sav, N = 91 participants; 182 observations). A within-subjects self-report study. Participants viewed both advertisements (order counterbalanced) projected in a classroom setting and, after each one, completed a paper questionnaire assessing perceived effectiveness in reducing private car use (10-point scale) and three affective dimensions from the Self-Assessment Manikin (Bradley & Lang, 1994) — valence, arousal and dominance — plus a subjective attention dimension (external vigilance vs. internal introspection) based on Joffily, Jandre & Volchan (2005), each on a 9-point scale. Environmental concern was measured with the same scale as in Study 1. The file is organised in long format: one row per participant × advertisement, which is the structure required by the linear mixed models (random intercept for participant) reported in the article (Tables 5–6 and Appendices 11–14). Both files are provided in SPSS (.sav) format and are accompanied by plain-text codebooks (Codebook_Study_1.txt, Codebook_Study_2.txt) documenting every variable, its measurement level, coding, range and interpretation. The full questionnaire (original Spanish wording), the Environmental Concern Scale items, the stimulus material and the AOI diagram are reproduced in the Appendices and Supplementary Materials of the article. Ethics. The study followed the ethical principles of the Declaration of Helsinki. All participants provided written informed consent. Study 1 participants received €15 as compensation. The datasets contain no direct or indirect personal identifiers: participants are identified only by a sequential code, and no demographic variable in the files allows re-identification. Repository contents Study_1.sav Eye-tracking experiment data (N = 41; 41 rows × 6 variables) Study_2.sav Self-report data in long format (N = 91; 182 rows × 9 variables) Codebook_Study_1.txt Study 1 data dictionary Codebook_Study_2.txt Study 2 data dictionary

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2026-07-20
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