Characteristics of Analysis Methods for the Impression Evaluation Method by Space

Characteristics of Analysis Methods for the Impression Evaluation Method by Space

Shunsuke Akai (Kyoto Institute of Technology, Kyoto, Japan & Kanden System Solutions Co., Inc., Osaka, Japan), Teruhisa Hochin (Graduate School of Information Science, Kyoto Institute of Technology, Kyoto, Japan) and Hiroki Nomiya (Graduate School of Information Science, Kyoto Institute of Technology, Kyoto, Japan)
Copyright: © 2016 |Pages: 13
DOI: 10.4018/IJSI.2016070105
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Abstract

This paper clarifies the characteristics of analysis methods of the evaluation results obtained through the Impression Evaluation Method by Space (IEMS). The IEMS uses a plane containing impression words as the Kansei space. The impression of an object is specified by circling the areas matching the impression. The degree of matching the impression is expressed by painting color. Three analysis methods have been proposed for the IEMS. These use the baseline Kansei space, the impression words, and the peaks of darkness of the evaluation results, respectively. These methods are compared from the viewpoints of spatial evaluation, relationships among impression words, darkness of evaluated areas, impression words added, and impression words moved. Moreover, it is clarified the information obtained through the three analysis methods. Each of them is suitable in obtaining specific information. They should be used according to the information required to be obtained.
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1. Introduction

In recent years, in addition to functions and convenience, Kansei topics such as design have become important. Kansei is a word that means how people feel. Because Kansei is vague, it is difficult to precisely capture and quantify it. Moreover, because Kansei differs for each person, it is difficult to evaluate.

The Semantic Differential (SD) method (Osgood, Suci & Tannenbaum, 1957) is often used as an evaluation method of such Kansei. As the SD method digitizes impressions, it enables statistical processing and makes it possible to perform various analyses. However, to enable statistical processing, the evaluation is required to be performed in a predefined range. As a result, it is difficult to evaluate vague aspects of Kansei. A method enabling the evaluation of the vagueness of Kansei is required. Although various research efforts concerning the expression of Kansei have been conducted (Choi & Okazaki, 2011; Tazaki & Okazaki, 2008; Kashiwazaki, 2004), such an evaluation method has not yet been established. An impression evaluation method considering the vagueness of Kansei has been proposed in order to overcome this issue (Akai, Hochin & Nomiya, 2012; Akai, Hochin & Nomiya, 2015b). This method uses a plane containing impression words. The impression of an object is specified by circling the areas matching the impression. The degree of matching of the impression is expressed by the painting color. This method is called the Impression Evaluation Method by Space (IEMS). The IEMS provides to users a commonly used baseline Kansei space. Users can modify this baseline Kansei space as needed.

Three analysis methods for the evaluation results of the IEMS have also been proposed (Akai, Hochin & Nomiya, 2013a; Akai, Hochin & Nomiya, 2013b; Akai, Hochin & Nomiya, 2014a; Akai, Hochin & Nomiya, 2014b; Akai, Hochin & Nomiya, 2015a). One focuses on the baseline Kansei space (Akai, Hochin & Nomiya, 2013a; Akai, Hochin & Nomiya, 2013b). It spatially shows average values and coefficients of variation of scores of the evaluation results. By using this method, the characteristics of the impression of objects and the dispersion among subjects could easily be obtained. This method is called the analysis method focusing on the baseline Kansei space (abbr., AM_BKS).

Another method focuses on the impression words (Akai, Hochin & Nomiya, 2014a). The numbers of the impression words circled are spatially displayed. This method enables us to visually capture the tendency of impression of objects because impression words having similar impression are placed nearer than those having different impression in the Kansei space. This method is called the analysis method focusing on the impression words (abbr., AM_IW).

The other method focuses on the peaks of darkness of the evaluation result (Akai, Hochin & Nomiya, 2014b; Akai, Hochin & Nomiya, 2015a). By mapping the peaks of the darkness in each evaluation result to the same Kansei space, this method can analyze characteristic impressions. This method can be used even when the impression words in the Kansei space are moved. This method is called the analysis method focusing on peaks of darkness (abbr., AM_PD).

These three analysis methods have merits and demerits. These are, however, not clarified yet. We can neither decide which method should be used in the evaluation, nor know what information can be obtained.

This paper clarifies the characteristics of these analysis methods and the information obtained through them. They are evaluated from the viewpoints of spatial evaluation, relationships among impression words, darkness of evaluated areas, impression words added, and impression words moved. The AM_PD can analyze evaluation results in any case. When the darkness is mainly required to be analyzed, the AM_BKS is suitable. The AM_IW is suitable in obtaining the relationships of impression words. It is also clarified the information obtained through the three analysis methods. Each of them is suitable in obtaining specific information. These should be used according to the information required to be obtained.

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