Kansei Engineering-Based Mapping of Gender Differences in Robusta Coffee Perception
DOI:
https://doi.org/10.25186/.v21i.2452Abstract
Robusta coffee is as less preferred than Arabica because of its bitterness and simple sensory profile. Nevertheless, its value is determined by consumer preferences and perceptions, which may vary according to gender. This study employed Kansei Engineering to systematically extract, quantify, and delineate gender-based perceptions of Robusta coffee into structured insights. From 160 respondents, 26 Kansei words were identified and subsequently assessed by 42 participants (21 male and 21 female) using semantic differential scales. Word cloud visualization highlighted gender-specific emphases: females focused on ‘aromatic’ and ‘fragrant’, whereas males emphasized ‘comfort’ and ‘spirit’. These Kansei descriptors were grouped into five categories: flavor and aroma, texture and appearance, emotion and feeling, physiological effects, and additional qualities. Descriptive statistics revealed that ‘aroma’
and ‘pleasure’ achieved the highest mean scores, while ‘bitter’ obtained the lowest. ‘Freshness’ showed strong positive skewness, suggesting potential for innovation. Reliability testing confirmed high internal consistency (Cronbach’s alpha > 0.80). The Mann–Whitney U test demonstrated a significant gender difference for ‘aromatic’. Principal Component Analysis (KMO = 0.602; Bartlett’s test, p < 0.001) with Varimax rotation explained 52.2% of the variance, yielding two main conceptual dimensions: affective-hedonic (44.6%), predominantly associated with females, and flavor-complexity (7.6%), more strongly associated with males, based on 18 Kansei words. MANOVA and repeated-measures ANOVA indicated no significant overall gender effect, whereas cluster analysis identified emotion-driven and flavor-oriented consumer groups. Thus, Kansei Engineering integrates sensory and emotional responses into cognitive maps, facilitating gender-based segmentation and providing practical insights for the development of Robusta coffee products.
Key words: Semantic differential; affective perception; principal component analysis; cluster analysis; consumer segmentation.
References
Barrea, L. et al. (2023). Coffee consumption, health benefits and side effects: a narrative review and update for dietitians and nutritionists. Critical Reviews in Food Science and Nutrition, 63(9):1238-1261.
Bressani, A. P. P. et al. (2021). Into the minds of coffee consumers: perception, preference, and impact of information in the sensory analysis of specialty coffee. Food Science and Technology, 41:667-675.
Chen, Y. L., & Chen, Y. C. (2025). Impact of brand and testing method on coffee taste perception between genders: A comparative study of two leading coffee brands in Taiwan. SAGE Open, 15(1):1-12.
De Winter, J. C. F., Dodou, D., & Wieringa, P. A. (2009). Exploratory factor analysis with small sample sizes. Multivariate Behavioral Research, 44(2):147-181.
Demura, S. et al. (2013). Gender differences in coffee consumption and its effects in young people. Food and Nutrition Sciences, 4(7):748-757.
Dolgun, L. R., & Köksal, G. (2007). Effective use of quality function deployment and Kansei engineering for productplanning with sensory customer requirements. Quality Engineering, 30(4):569-582.
Dong, Y et al. (2021). A fuzzy mapping method for Kansei needs interpretation considering the individual Kansei variance. Research in Engineering Design, 32(2):175-187.
Fatchurrohman, N. et al. (2022). Product development using kansei engineering to re-design new food packaging. Jurnal Teknologi, 12:8-13.
Gad Mohsen, M., & Dacko, S. (2013). An extension of the benefit segmentation base for the consumption of organic foods: A time perspective. Journal of Marketing Management, 29(15-16):1701-1728.
Gadilkar, J. (2024). Impact of sensory marketing on consumer behaviour: Gender differences in aroma, music, and visual aesthetic preferences in coffee shops. International Journal for Multidisciplinary Research, 6(5):1-9.
González, A. G. et al. (2024). Semantic kansei engineering approach for game controllers and design improvement. Applied Sciences, 14:15.
Indonesia Ministry of Agriculture. (2022). Outlook for plantation commodities-coffee. Jakarta, Indonesia. Available in <https://satudata.pertanian.go.id/assets/docs/publikasi/Buku_Outlook_Kopi_2022_compressed.pdf>.
Jane, J. C. et al. (2020). Assessment of Arabusta coffee hybrids [Coffea arabica L. X Tetraploid Robusta (Coffea canephora )] for green bean physical properties and cup quality. African Journal of Food Science, 14(5):119-127.
Kath, J. et al. (2020). Not so robust: Robusta coffee production is highly sensitive to temperature. Global Change Biology, 26(6):3677-3688.
Li, X. et al. (2024). Multi-dimensional data analysis platform (MuDAP): A cognitive science data toolbox. Symmetry, 16(4):1-17.
Liu, C. et al. (2019). Enhancing Robusta coffee aroma by modifying flavour precursors in the green coffee bean. Food Chemistry, 281:8-17.
Mahmud, M. M. C., Shellie, R. A., & Keast, R. (2020). Unravelling the relationship between aroma compounds and consumer acceptance: Coffee as an example. Comprehensive Reviews in Food Science and Food Safety, 19(5):2380-2420.
Mud’is, M. H. et al. (2019). Implementation of kansei engineering on academic information system interface design based on android. Journal of Physics: Conference Series, 1402:066066.
Nawrot, P. et al. (2003). Effects of caffeine on human health. Food Additives and Contaminants, 20(1):1-30.
Nehlig, A., Daval, J. L., & Debry, G. (1992). Caffeine and the central nervous system: mechanisms of action. Brain Research Reviews, 17(2):139-170.
Okamoto, S et al. (2021). Layered-Modeling of affective and sensory experiences using structural equation modeling: Touch experiences of plastic surfaces as an example. IEEE Transactions on Affective Computing, 12(2):429-438.
Peterson, R. A. (1994). A meta-analysis of cronbach’s coefficient alpha. Journal of Consumer Research, 21(9):381-391.
Pinsuwan, A. et al. (2022). Sensory drivers of consumer acceptance, purchase intent and emotions toward brewed black coffee. Foods, 11(2):180.
Reiko, U. et al. (2008). Modified food kansei model to integrate differences in personal attributes between in-house expert sensory assessors and consumer panels. Food Science and Technology Research, 14(5):445-456.
Sari, K. N. et al. (2023). Application of kansei engineering to capture consumer demand for cooking oil product packaging. International Journal of Eco-Innovation in Science and Engineering, 4(1):12-17.
Sari, N. P. et al. (2025). Implementation of kansei engineering in the design of packaging design elements: Study case for Food MSME. Operations Excellence: Journal of Applied Industrial Engineering, 1(1):105-118.
Sollai, G., Solari, P., & Crnjar, R. (2024). Qualitative and quantitative sex-related differences in the perception of single molecules from coffee headspace. Foods, 13:3239.
Souza, C. M. de., Rodrigues, D. da C., & Sousa, P. H. M. de. (2022). Development of the coffee Taster’s emotion wheel for the coffee drinking experience. International Journal of Gastronomy and Food Science, 27:100451.
Tifferet, S., Shani, N., & Cohen, Haim. (2013). Gender Differences in the Status Consumption of Coffee. Human Ethology, 28(3):5-9.
Ushada, M. et al. (2023). Multiple affective attributes for the customization of post-pandemic food services. Journal of Quality Assurance in Hospitality and Tourism, 26(1):1-24.
Vaswani, N., Chi, Y., & Bouwmans, T. (2018). Rethinking PCA for modern data sets: Theory, algorithms, and applications. Proceedings of the IEEE, 106(8):1274-1276.
Viencz, T. et al. (2024). Sensory characterization and acceptance of amazonian robustas coffee brews by consumers using a Home-Use Test. Beverages, 10(3):57.
Wahyuddin, M., Setyawan, A. A., & Nugroho, S. P. (2017). Shopping Behavior Among Urban Women. Mediterranean Journal of Social Sciences, 8(1):306-311.
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