Bayesian analysis of color preferences: An application for product and product line design

Abstract

When choosing which colors to offer in their product lines, firms often rely upon consumer preference models that do not account for the heterogeneity of their target market and do not consider the trade‐offs consumers are willing to make for different color options. For this research we used visual conjoint analysis to assess preference for backpack color and then modeled respondent utilities with a Bayesian hierarchal multinomial logit model. This provided counter intuitive results in which product line color options are not additive but each color changes depending on the number of options the firm is willing to offer and that colors which seem to dominate secondary preferences within a target market may not be the best colors to choose for product line expansion. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 445–456, 2016

Predictive modeling of consumer color preference: Using retail data and merchandise images

“…These approaches commonly describe the color attributes by using dummy variables (Deliza, Macfie, & Hedderley, 2003;Silayoi & Speece, 2007), which are not capable of capturing the color features of real merchandise. P. Choi et al (2016) utilized CIELAB color space to accurately represent color features of a single-color backpack. They estimated a choice model to obtain the color preference and heterogeneity of the target market, which could assist firms in deciding which color to offer.…”

“…L. Yu et al () used online surveys and laboratory experiments to show the correlation between personal color preferences and product color choices. P. Choi, Orsborn, and Boatwright () designed a visual conjoint analysis and applied a Bayesian hierarchical multinomial logit model to capture the consumer preferences of single‐color products.…”

Constructing a Mathematical Model of Product Color Design Based on Data Mining: Case Study of a Thermos Cup

“…Manufacturers often design multiple colors when creating color schemes to meet consumers' personalized needs while achieving product diversification and serialization at a lower cost [1,2]. Understanding consumer color preferences accurately and promoting product sales has long been a concern for researchers.…”

Attention affordances: Applying attention theory to the design of complex visual interfaces.

“…To this end, user studies represent a useful tool, which improve design through increased knowledge of the potential user (Crilly et al, 2009), and thus better knowledge of how to manage affordances. For example, previous research has provided guidelines that help practitioners improve performance of products by changing their visual characteristics, such as their general aesthetic appeal (Blijlevens et al, 2013; Choi et al, 2016; Crilly et al, 2004; Orsborn et al, 2009), investigation of specific product tests, and user evaluation studies (Braseth & Øritsland, 2013; Karlsson, 2007; Lau et al, 2008; Na & Suk, 2014; Ranscombe et al, 2012; Weyer et al, 2010). However, such studies seldom relate or base their findings to the underlying cognitive mechanisms or to testing established theories of the cognitive mechanisms behind the interactions, making it harder to generalize across design cases.…”