Understanding consumer face mask consumption: a MaxDiff-based cluster analysis

AbstractThis study aims to develop a consumer typology based on the importance of product attributes in consumer face mask consumption during the COVID-19 pandemic. An online survey with a MaxDiff experiment was employed to measure the importance of eight face mask attributes. Data were collected from 563 U.S. consumers during April 2022. Hierarchical Bayes analysis, K-means clustering, Chi-square tests, and ANOVA were used for data analysis. Results suggested that protection and comfort were the most important attributes, while appearance and brand were the least important. Based on the tradeoffs made in their purchase decision-making process, three distinct groups of face mask consumers were identified, named protection-focused, utilitarian-driven, and eco-conscious consumers. A consumer profile was established for each group, reflecting their mask-wearing behaviors, mask type preferences, and demographics. This study provides implications for face mask manufacturers and retailers to develop effective production and target marketing strategies for future respiratory pandemics.Keywords: Face maskattribute importanceMaxDiffcluster analysismarket segmentation Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe data that support the findings of this study are available from the corresponding author upon reasonable request.Permission to reproduce material from other sourcesThere are no excerpts from copyrighted works owned by third parties included in this study.Additional informationFundingThis work was supported by a grant from the NSRP program at North Carolina State University.