Factors affecting consumers' cognition of food photos using Kansei engineering

Mei-Yi Wu,Ying-Hsuan Chen

doi:10.1590/fst.38921

Abstract

The charm of food photos plays a decisive role in advertising because people search and buy food on the Internet more frequently than ever. Photos with appealing food design elements can immediately attract people's attention. The same food with different design features will attract different consumer groups through photos on the web. They greatly affected consumers' feel, and purchase decisions. This study uses Taiwanese mango ice as an example to explore the perceptual reasons why consumers are attracted to existing mango ice products, their attractive design features, and the relationship between the two. Miryoku engineering was used to explore the relationship between consumers and the appeal of food design revealed by photos, the Evaluation Grid Method (EGM) was used to extract the attractive factors of food design, and the Quantification Theory Type 1 (QTT1) is used to analyze the weight of each design feature that affects the charm of food. Three Kansei factors and 16 concrete design elements were obtained through EGM, and the weights of food design elements that influence the charm were found using QTT1. The results show that the obtained regression models can explain the relationship between the design elements of food photos and the perception of customers. The application have important reference value for evaluating food design elements and market segmentation of consumer groups. This research proves the feasibility of using Kansei engineering to explore the charm of food design, and has reference value for future related research.

Highlights

Providing products with emotional value and attractiveness has long been a critical topic (Ho & Hou, 2015)
The coefficients of multiple determination (R2) for each model are 0.827, 0.705, and 0.808, respectively. These results show that the overall fits of these Quantification Theory Type 1 (QTT1) function models are good
Because CEI with a higher partial correlation coefficients (PCC) value has a higher correlation with the dependent variable, it contributes to the prediction model

Summary

Introduction

Providing products with emotional value and attractiveness has long been a critical topic (Ho & Hou, 2015). Due to the increasing popularity of the Internet, combined with services such as electronic maps and delivery platforms, people are searching and buying food on the Internet more frequently than ever. The convenience of searching for food on the Internet has brought more opportunities for the catering industry, and at the same time, it has brought more fierce competition. For the catering industry, it is essential to find the food charm that attracts customers and present it in pictures on the Internet for food marketing through the Internet. To segment the market, the food providers should consider the food design and the resulting visual appeal. Vision plays a vital role in the human experience of the five senses

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