Text highlighting as a new way of measuring consumers' attitudes: A case study on vertical farming

Abstract

Attitude measurement occupies a central position in consumer research. Concerns over the validity and reliability of traditional measures have motivated the development of alternative approaches. The present research introduces text highlighting as a method for measurement of explicit attitudes using a case study on vertical farming (VF) with 837 UK consumers. They participated in an online survey, where they read a text about VF and used highlighting functions to mark text as ‘like’ and ‘dislike.’ Consumers approached the task in a systematic and logical way and desirable aspects of VF were frequently highlighted as ‘like’, whereas undesirable aspects were more frequently highlighted as ‘dislike’. The text highlighting responses were summarised using word clouds, frequency tables and through sentiment scores to reveal an overall positive attitude to VF among participants. Sentiment scores enabled the identification of consumer segments with interpretable differences in their attitude towards VF. Two approaches to method validation – comparison with direct attitude questions and consumer profiling – further confirmed the potential of the text highlighting method. The sentiment of specific sentences in the text highlighting task matched results from self-reported attitudinal based on Likert scales. Consumer segments with different sentiment in the text highlighting task also differed in their food technology neophobia scores in the expected direction. Future research should investigate methodological aspects of text highlighting and explore its suitability to other applications.