Products' Shared Visual Features Do Not Cancel in Consumer Decisions

Abstract

Consumers' product purchase decisions typically involve comparing competing products' visual features and functional attributes. Companies strive for “product differentiation” (Liu et al., 2013, “Product Family Design Through Ontology-Based Faceted Component Analysis, Selection, and Optimization,” ASME J. Mech. Des., 135(8), p. 081007; Thevenot and Simpson, 2009, “A Product Dissection-Based Methodology to Benchmark Product Family Design Alternatives,” ASME J. Mech. Des., 131(4), p. 041002; Kota et al., 2000, “A Metric for Evaluating Design Commonality in Product Families,” ASME J. Mech. Des., 122(4), pp. 403–410; Orfi et al. 2011, “Harnessing Product Complexity: Step 1—Establishing Product Complexity Dimensions and Indicators,” Eng. Econ., 56(1), pp. 59–79; and Shooter et al. 2005, “Toward a Multi-Agent Information Management Infrastructure for Product Family Planning and Mass Customisation,” Int. J. Mass Customisation, 1(1), pp. 134–155), which makes consumers' product comparisons fruitful but also sometimes challenging. Psychologists who study decision-making have created models of choice such as the cancellation-and-focus (C&F) model. C&F explains and predicts how people decide between choice alternatives with both shared and unique attributes: The shared attributes are “canceled” (ignored) while the unique ones have greater weight in decisions. However, this behavior has only been tested with text descriptions of choice alternatives. To be useful to designers, C&F must be tested with product visuals. This study tests C&F under six conditions defined by: The representation mode (text-only, image-only, and image-with-text) and presentation (sequentially or side-by-side) of choice alternatives. For the products tested, C&F holds for only limited situations. Survey and eye-tracking data suggest different cognitive responses to shared text attributes versus shared image features: In text-only, an attribute's repetition cancels its importance in decisions, while in images, repetition of a feature reinforces its importance. Generally, product differences prove to attract more attention than commonalities, demonstrating product differentiation's importance in forming consumer preferences.

Value Perception of Green Products: An Exploratory Study Combining Conscious Answers and Unconscious Behavioral Aspects

“…Previous research has found correlations between the provision of sustainability-related information and engendered emotions, e.g., [21,25]. The diverging outcomes arisen from the present study, where this information is less explicit, seem to confirm the differences caused by diverse information fashions as discussed by Du and MacDonald [66]. To investigate the ease of individuating features ascribable to eco-design, the authors plan to exploit the experiment's outputs further and analyze participants' observation of specific Areas of Interest in the pictures, which is enabled by ET results.…”

“…This introduces a fundamental bias with respect to a real-word purchasing decision scenario, apart from certain circumstances potentially applying to e-commerce. Besides, Du and MacDonald [66] found different cognitive responses between shared text attributes and shared image features based on data collected through a survey and the monitoring of gaze behavior during the comparison of products' pictures. As aforementioned, survey-based studies might have failed to include unconscious aspects by either neglecting the chance to use biometric instruments for monitoring spontaneous reactions or overlooking the attitude-behavior gap.…”

“…Many studies link the fixations to the object's capability of attracting the participant's attention [34,66,76,77]. Antes [78] found that when subjects look at a picture, their eye gaze position concentrates on informative areas.…”

A Test of the Rapid Formation of Design Cues for Product Body Shapes and Features

“…The data provided a different dimension of information when used with other forms of data (for example, survey data). References [4], [20], [27], and [28] summarize uses of eye movement data in product design research. This paper uses fixations, or "eye movements that stabilize the retina over a stationary object of interest" [29], to study areas of interest (AOIs), which refer to "areas of a given stimulus related to the research hypothesis" [27].…”

“…In the past, cue building has been used in industrial design as an art, without understanding how cues are formed or which cues are the most effective. Past research indicates that product visuals do not always behave as one might predict; for example, shared visual features between products are not ignored but rather magnified in judgments [4]. Thus, designers should approach the design of new visual cues carefully.…”