Text highlighting for attitude measurement in cross‐cultural consumer research: A methodological study
Gastón Ares, Sara R. Jaeger
Abstract
Abstract Text highlighting was explored as a new method for direct attitude measurement in cross‐cultural research. Participants in an online survey read a text about vertical farming. They used highlighter functions to mark parts of the text they “liked” and “disliked”. Four countries were included in the research—United Kingdom, United States, Singapore, and China (637–683 adults per country). The percentage of participants who highlighted words as “like” and “dislike” was calculated for each of the sentences and countries. Analysis of the highlighting responses did not point to response style or systematic differences in responding. This supported the use of text highlighting in cross‐cultural research. Groups of consumers with different sentiment towards specific sentences in the text highlighting task (Positive, Neutral/Ambivalent, or Negative) showed predictable differences in their average scores for attitudinal statements. Practical Implications Likert scales are ubiquitous in attitude measurement but subject to response styles which is a hindrance in cross‐cultural research. This suggests the need to develop scale‐free methods. Results from the present research confirmed the ability of text highlighting to capture specific attitudes towards vertical farming across countries and languages, as well as its ability to overcome response style differences.