Incorporating Affective Customer Needs for Luxuriousness into Product Design Attributes

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1 , Vol. 19 (2) (2009) C 2009 Wiley Periodicals, Inc. Published online in Wiley InterScience ( Incorporating Affective Customer Needs for Luxuriousness into Product Design Attributes Sangwoo Bahn and Cheol Lee Department of Industrial Engineering, Seoul National University, Seoul , Korea Chang S. Nam Department of Industrial Engineering, University of Arkansas, Fayetteville, AR 72701, USA Myung Hwan Yun Department of Industrial Engineering, Seoul National University, Seoul , Korea ABSTRACT In a highly competitive market, customers product affection is a critical factor to product success. However, understanding customers affective needs is difficult to grasp; product design practitioners often misunderstand what customers really want. In this study we report our experience in developing and using an affective design framework that identified critical affective features customers have on products and are systematically incorporated into product design attributes. To identify key affective features such as luxuriousness, we utilized the Kansei engineering methodology. This approach consists of three steps: (1) selecting related affective features and product design attributes through a comprehensive literature survey, expert panel opinion, and focus group interviews; (2) conducting evaluation experiments; and (3) developing Kansei models using multivariate statistical analysis and analyzing critical product design attributes. To demonstrate applicability of the proposed affective design framework, 30 customers and 30 product design practitioners participated in an evaluation experiment for car crash pads, and 44 customers and 20 designers participated in an evaluation experiment for two interior room products (wallpapers and flooring materials). The evaluation experiments were conducted via systematically developed questionnaires consisting of a 7-point semantic differential scale and a 100-point magnitude estimation scale. The results of the experiments were analyzed using principal component regression and quantification theory type I method. Using the analyzed survey data, the relationship between luxuriousness and related affective features and product design attributes were identified. This relationship indicated that there was a significant difference in the perception of luxuriousness between customers and designers. Consequently, it is expected that the results of this study could provide a foundation for developing affective products. C 2009 Wiley Periodicals, Inc. 1. INTRODUCTION In today s competitive market environment, almost every company is concerned with satisfying customers needs (Cross, 2000). Likewise, the mass customization and personalization Correspondence to: Cheol Lee, 56-1, Silim 9-Dong, Kwanak-Gu, Seoul South Korea. iehis@snu.ac.kr or Dr.Lee412@gmail.com 105

2 106 BAHN ET AL. of products aid companies in gaining the competitive edge (Tseng & Piller, 2003). Considering the plethora of products available today, customers may find it difficult to distinguish and choose among them as many similar products are functionally equivalent due to the development of global markets and advances in modern technology (Huffman & Kahn, 1998). Understanding what buyers value, creating a value for each of them, and then managing it over time have long been recognized as essential elements of every market-oriented company s core business strategy (Drucker, 1985; Porter, 1998; Slater & Narve, 1998). Perceived images/impressions and related human emotions are key factors in the design of a physical product. It is imperative to design products by engaging customers emotions or attention so as to differentiate among products (Jordan, 2000; Yun, Han, Hong, & Kim, 2003). Affection is defined as a customer s psychological response to the perceptual design details (e.g., styling) of the product (Demirbilek & Sener, 2003). Affection is the basis for the formation of human values and judgment (Khalid & Helander, 2006). For this reason, product design models that do not consider customers affection may essentially be weakened (Helander & Tham, 2003). The main challenge for affective design is to accurately grasp the customer s affective needs and subsequently to design products to meet those needs. Many research issues are implied, for example, (a) how to measure and analyze human reactions toward affective design; and (b) how to assess the corresponding affective design features. First, the semantic deferential method (SD; Osgood, Suci, & Tannenbaum, 1967) was used most frequently to investigate customers perception on products. By studying product semantics, customers subjective feelings about a product can be discerned and quantized on a Likert-type scale. Many researchers have used this method to study specific aspects of different product aspects, including styles and colors (Alcantara, Artacho, Gonzalez, & Garcia, 2005; Chuang & Ma, 2001; Houser & Tiller, 2003; Hsu, Chuang, & Chang, 2000; Llinares & Page, 2007; Mondraqon, Company, & Vergara, 2005; Petiot & Yannou, 2004). As a qualitative approach, focus groups are utilized to provide a clear insight on the usefulness of a new product s design (LaChance-Porter, 1993). Similar techniques include one-on-one interviews and similarity dissimilarity attribute rankings (Griffin & Hauser, 1992). Although these types of methods are helpful for discerning customer needs, it can be difficult to obtain a product s design requirement information due to the fact that customers and marketers are not typically thinking in a design practitioner s paradigm. Furthermore, designing a customer-oriented conceptual model for a perceived product that encompasses numerous individuals perceptions, as well as verification methods for such a model, has not been fully explored. Quality function deployment (QFD; Clausing, 1994) has also been used to aid a designer in defining product specifications geared toward customers. Although QFD excels in converting customer information into design requirements, it is limited as a means of actually discovering the voice of customers (Hauge & Stauffer, 1993). Finally, Kansei engineering has been well recognized as a technique of translating consumers psychological feelings about a product into perceptual design attributes (Nagamachi, 2002). Nagamachi (1996) proposed six technical styles of Kansei engineering methods with applications to the automobile industry, cosmetics, house design, and sketch diagnosis. Other product design practitioners in a variety of areas have utilized such computational approaches (Jindo & Hirasago, 1997; Nakada, 1997; Ou, Luo, Woodcock, & Wright, 2004; Schütte & Eklund, 2005; You, Ryu, Oh, Yun, & Kim, 2006; Yun et al., 2003; Yun, Han, Ryu, & Yoo, 2001). These studies quantified people s perceptions about the product in order to translate a consumer s perceptions into design elements. Nevertheless, defining a conceptual model of users product perception has not been fully explored.

3 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 107 A number of studies have demonstrated that these approaches are applicable in many areas, but most of the previous studies focused on either analyzing affective reactions or partially assessing product design attributes. In reality, subjective impressions are difficult to translate into verbal descriptions, and affective needs are relatively short-lasting emotional states and tend to be imprecise and ambiguous (Helander & Khalid, 2005). Regarding the conceptual model of the product, Krippendorff (1995) argued that the designers objectified meaning is built into the product and is not presumed to be the same as the product s meaning in the user s eyes. Such contrariety would cause a high-tone design to fail. Moreover, general users may not appreciate a product s aesthetics. It is, therefore, necessary to study how designers and users affective conceptual models are related in terms of a product s affective features. For this matter, target emotions should be more clearly defined before relating them to design attributes. In addition, assessing the relationship of target emotions with just a few design variables could result in inaccurate design guidelines due to the variety of methods available for expressing targeted emotions. Hence, defining complex emotions through relative variables and design variables, all with distinct and clear meaning, would result in more efficient product design. Finally, more comprehensive studies, which cover both the affective characteristics of a target emotion and the optimal combination of related product design attributes, are still required. Luxuriousness is an important impression of many products and there are steady demands for luxurious products (Jang, 2004). However, luxuriousness is a very abstract and ambiguous emotion. Moreover, the definition of its meaning differs from person to person. There are few studies that have investigated the meanings of the luxuriousness of products or the relationship between luxuriousness and physical design elements (Yun et al., 2001, 2003). In this study we report our experience of identifying quantitative relationships between target emotions and related affective features of (a) an automobile interior product and (b) two interior room products (wallpaper and flooring materials), which present a complex and conceptual emotion (luxuriousness) as a simpler affective variable coupled with an optimal combination of physical design attributes. First, we collected related affective feature and design attributes in detail and developed comprehensive Kansei models of luxuriousness that covered related affective features and design attributes. We also investigated designers misunderstandings on luxuriousness by comparing the results from Kansei models of customers to product design practitioners. 2. A FRAMEWORK FOR AFFECTIVE DESIGN The overall procedure of an affective design framework, which is demonstrated in this study s case studies, is shown in Figure 1. First, a target product s related affective features and design attributes are collected through literature review, a focus group interview (FGI) of customers and designers, and expert panel opinions. Second, to identify the relationship between luxuriousness as well as affective product features and design attributes, evaluation experiments were conducted using a questionnaire. Finally, based on the survey results, the relationship between affective features and product design attributes were identified and the key factor of luxuriousness was identified quantitatively by using a multivariate statistical methodology Development of Hierarchical Structure of Affective Features Through the extensive literature review, customer FGIs, and the gathering of expert opinions about a target product from salespersons and designers, each product s affective

4 108 BAHN ET AL. Literature Survey Focus Group Interview Opinion of Expert Panel Hierarchy of Affective Features Selection of Product Design Attributes Evaluation Experiment Design of Experiment Statistical Analysis & Kansei Modeling Recommendation for Design Guidelines Questionnaire Formulation Figure 1 A framework for affective design. features were determined. Then, the affective features were classified according to their characteristics focused on the target emotion (i.e., luxuriousness) into visual characteristic features (look and feel) and tactile characteristic features (touch and feel). An example of affective features, particularly luxuriousness, is shown in Table Selection of Product Design Attributes Based on the target product s design, product design attributes can be systematically represented as a hierarchical structure of various functional aspects of the product. Customer TABLE 1. Category An Example of the Hierarchical Structure of Selected Affective Features Affective Features Tactile Material Degree of softness Degree of smoothness Degree of regularity Degree of solidness Degree of elasticity Harmony Degree of tactile oneness Visual Shape Degree of hardness Degree of delicate Degree of vividness of pattern Degree of size of unit pattern Degree of complexity of pattern Color Degree of warmness of color Degree of brightness of color Degree of gloss

5 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 109 needs or requirements depend directly upon product design attributes. For example, if a customer wants an impression of luxuriousness, then it is necessary to investigate which product design attributes make the customer sense such an impression. To answer this question, the relationship between affective features and product design attributes should be analyzed. In a practical manner, product design attributes should be selected based on the design practitioners expert knowledge and design guidelines. In addition, design attributes, such as experimental variables, should be selected independently from one another since the variables will be analyzed by statistical methodology. For the reliability of case studies, the target product s manufacturing and ergonomic design specifications were collected and utilized in this study Evaluation Experiment The purpose of the evaluation experiment is to identify the relationship between affective features based on a target emotion (i.e., luxuriousness) and product design attributes. Purpose-built questionnaires were developed based on the experimental objectives. The metrics of each question were carefully selected based on customers perceptual capabilities. We utilized a 7-point semantic differential scale for the affective features and a 100-point magnitude estimation scale for the overall evaluation of target emotion. To compare the differences between customers and designers in terms of perception of the target emotion, two types of subject groups customers (who had experience with a target product over 1 year) and designers (who had experience in the design of a target product over 1 year) were recruited for the evaluation experiments. In addition, before the evaluation experiment, realistic sample materials of a target product were prepared according to the design theory of the experiment Statistical Analysis and Kansei Modeling The Kansei modeling of a target emotion consists of two parts. The first part is about the perception of a target emotion. By modeling with sensation variables (e.g., visual characteristics, tactile characteristics, etc.), the sensational characteristics of the target emotion can be identified. The second part aims to find the optimal combination of design specifications of the related product s design attributes. To this end, we identified the relationship between the target emotion and the product design attributes (which were selected from section 2.2) quantifiably using multivariate analysis (e.g., quantification theory, regression, conjoint analysis, etc.). The metrics may include continuous and discrete variables. Thus, appropriate statistical analysis techniques should be employed based on the characteristics of the variables. In this study, principal component regression and quantification theory type I were adopted. 3. CASE STUDY To demonstrate applicability of the proposed affective design framework, we conducted three case studies on automobile and interior room products (e.g., car crash pad, wallpaper, flooring material). It should be noted that affective responses could vary from customer to customer.

6 110 BAHN ET AL. Figure 2 Examples of car crash pad Automobile Interior Product: Crash Pad The first case study is about the passenger car crash pad placed in front of the driver s seat. The crash pad was designed to elicit strong customer feelings on the overall interior of the automobile (see Figure 2) Related Affective Features of Luxuriousness for Crash Pad. Twenty initial affective crash pad features were collected through extensive literature review and FGIs employing designers, salespeople, and customers. After integrating the initial affective features, 10 variables were selected based on expert opinions. In addition, a hierarchical structure of important affective features of luxuriousness for crash pads was developed according to a previous study (Postech, 1997) and FGIs that consisted of ergonomic experts and crash pad design practitioners, as shown in Table 2. TABLE 2. Category A Hierarchical Structure of Selected affective Features of Car Crash Pad Affective Features Tactile Material Degree of softness Degree of smoothness Elasticity Degree of solidness Degree of elasticity Harmony Degree of tactile oneness Visual Shape Degree of hardness Degree of delicate Color Degree of warmness of color Degree of brightness of color Degree of gloss

7 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 111 TABLE 3. Number and Characteristics of Car Crash Pad Samples Design Attributes Number Material type Hard IP 10 PU Spray 7 TPO 4 PVC PSM 11 PVC ABS 4 TPU PSM 5 Embossing type Cell type 14 Wave type 16 Technical type 6 Geometric type 5 Color Black 12 Dark brown 7 Brown 7 Dark blue 9 Grey 6 Note: IP (instrument panel), PU (polyurethane), TPO (thermal plastic olefin), PVC (poly vinyl chloride), PSM (powder slush molding), ABS (acrylonitrile butadiene styrene), TPU (thermoplastic polyurethane) Evaluation Experiment on Luxuriousness of Crash Pad. Table 3 displays the number and characteristics of crash pad samples used in the evaluation experiment. Based on their design specifications, crash pads were characterized by their material type, embossing type, and color. A questionnaire utilized in the evaluation experiment was formulated based on the hierarchical structure of affective features, where the 7-point Likert scale and 100-point magnitude estimation scale were used (see Figure 3). Thirty participants from the customer group, who had more than 1 year of driving experience, and 30 designers from the designer group, who had more than 1 year experience in product design practice, participated in the evaluation experiment. The quantification theory type I method was utilized to analyze the relationships of luxuriousness and related variables. Rating scores of the 100-point scale were normalized to avoid the effect of individual variation in subjective evaluation shown as Equation 1. For Figure 3 Example of 7 point SD scale - When you are touching the sample, how soft is the sample? worst in softness not soft normal soft very soft Example of 100 point continuous scale - Evaluate the overall luxuriousness score of the sample from 0 to 100 Score : An example of the questionnaire used in evaluation experiment.

8 112 BAHN ET AL. TABLE 4. Results of Principal Component Regression of Crash Pad Group Variable Principal Component Coefficient p Value Customer Tactile luxuriousness 0.30 <0.001 Visual luxuriousness 0.62 <0.001 Designer Tactile luxuriousness 0.26 <0.001 Visual luxuriousness 0.66 <0.001 the statistical analysis, SPSS (version 12.0) and SAS (version 9.1) software packages were utilized. Q Q new ij min(q ij ij = ) max(q ij ) min(q ij ) (1) where = normalized subjective evaluation score of ith participant about jth sample Q ij = subjective evaluation score of ith participant about jth sample Q new ij min(q ij ) = min (Q ij j, j = 1, 2,..., 41) and max(q ij ) = max (Q ij j, j = 1,2,...,41) Analysis and Modeling Results. A series of principal component regressions was conducted to analyze the relationship of overall luxuriousness with tactile and visual luxuriousness scores. Due to a significant multicollinearity, principal component regressions were conducted rather than multiple linear regressions (Liu, Kuang, Gong, & Hou, 2003). The results are presented in Table 4. According to Table 4, results indicated that both the customer and designer group were influenced more by visual characteristics rather than tactile characteristics. To identify the relationships between affective features and luxuriousness, quantification theory type I analysis was conducted. Table 5 shows the ranges of partial regression coefficients of each variable and the relative importance of each variable. According to the results, customers are mainly affected by the softness of a crash pad, whereas designers mainly focus on the tactile oneness and hardness. Table 6 and Table 7 are integrated from the result of a quantification theory type I analysis presenting regression coefficients of each affective feature. From these results, designers can better grasp users understanding of luxuriousness from combining the effects of each variable and each level shown in Table Identification of Relationship between Luxuriousness and Design Attributes of Car Crash Pad. With respect to the luxuriousness of a car crash pad, related design attributes were collected based on expert opinions. Table 8 shows the collected product design attributes and Figure 4 illustrates the dimension of the product design attributes. In addition, the relative importance of each variables and the effect of each of the levels were identified using quantification theory type I analysis. Before the analysis,

9 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 113 TABLE 5. Relative Importance of Each Affective Features of Car Crash Pad Customers (R 2 = 0.53) Designers (R 2 = 0.67) Affective features Range Relative Importance (%) Range Relative Importance (%) Tactile Softness Smoothness Solidness Elasticity Tactile oneness Visual Delicateness Hardness Warmness Brightness Gloss continuous variables were categorized into a range of levels from 10 to 17 with respect to the values of luxuriousness as exemplified in Figure 5. A quantification theory type I method was utilized for the analysis of the categorized data. The results of the analysis are shown in Table 9 and Table 10. According to Table 9, surface luxuriousness was mainly affected by the coefficient of static friction. Table 10 shows the effects of each level of the variables. With these results, we can see the effects of each variable level and identify the optimal combination of design attributes. Table 11 shows the optimal combination of each design attribute that was drawn from the results of the quantification theory type I analysis between luxuriousness and design attributes. TABLE 6. Partial Regression Coefficient of Each Level of Tactile Affective Features of Crash Pad Features Tactile Affective Softness Smoothness Solidness Elasticity Oneness Group C D C D C D C D C D 1 Solow Low A little low 4 Normal A little high 6 High So high Group C: Customers, Group D: Designers.

10 114 BAHN ET AL. TABLE 7. Partial Regression Coefficient of Each Level of Visual Affective Features of Crash Pad Affective Features Delicacy Hardness Warmness Brightness Gloss Group C D C D C D C D C D 1 So low Low A little low Normal A little high High So high Group C: Customers, Group D: Designers. TABLE 8. Collected Design Attributes Related with Luxuriousness of Car Crash Pad Design Attributes Dimension Type of Variable The type of embossment Dimensionless Categorical The hardness of surface HS Continuous The length of embossment mm Continuous The height of embossment mm Continuous Thesizeofembossment mm 2 Continuous The depth of embossment μm Continuous The coefficient of static friction Dimensionless Continuous The coefficient of dynamic friction Dimensionless Continuous TABLE 9. Result of Quantification Theory Type I Analysis of Car Crash Pad Customers (R 2 = 0.42) Designers (R 2 = 0.61) Relative Relative Design Attributes Range Importance (%) Range Importance (%) The type of material The type of embossment The hardness of surface The length of embossment The height of embossment The size of embossment The depth of embossment The coefficient of static friction The coefficient of dynamic friction

11 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 115 TABLE 10. Partial Regression Coefficient of Each Level of Design Attributes (Customers) Design Attributes Levels and Their Partial Regression Coefficients The width of unit embossment (mm) Coefficient The height of unit embossment (mm) Coefficient Thesizeofunit embossment (mm 2 ) Coefficient The depth of unit embossment (μm) Coefficient The coefficient of static friction Coefficient The coefficient of dynamic friction Coefficient The hardness of 65 surface (HS) Coefficient The type of material Hard IP PU spray TPO PVC PSM PVC ABS Coefficient The type of Geo Cell Wave Tech embossment Coefficient TPU PSM HS: Unit of shore hardness.

12 116 BAHN ET AL. TABLE 11. Partial Regression Coefficient of Each Level of Design Attributes (Customers) The The The Width The Height The Size The Depth Coefficient Coefficient The of Unit of Unit of Unit of Unit of Static of Dynamic Hardness The Type The Type of Design Embossment Embossment Embossment Embossment Friction Friction of Surface of Material Embossment Attributes (mm) (mm) (mm 2 ) (mm) Coefficient Coefficient (HS) Coefficient Coefficient Optimal level PVC PSM Cell

13 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 117 Figure 4 An example of measurement of embossment size of car crash pad Interior Room Products: Wallpaper and Flooring Material The wallpaper and flooring material are important parts in interior design of a room, and luxuriousness is a major target emotion that designers try to provide to customers. The samples used in this case study are shown in Figure Related Affective Features of Luxuriousness for Wallpaper and Flooring Material. Similar to the car crash pad method, hierarchical structures were developed for the major affective features of luxuriousness of wallpaper as well as flooring materials, as shown in Table 12 and Table Evaluation Experiment on Luxuriousness of Wallpaper and Flooring Material. Table 14 and Table 15 present design attributes and the number of samples used in the evaluation experiment for wallpaper and flooring material, respectively. The combinations of each design attribute and the number of each sample were constructed according to the experiment s design theory. To analyze the main effect of each independent variable as well as probable interactions between the variables fractional factorial design (wall paper) and full factorial design (flooring material) were applied (Montgomery, Runger, & Hubele, 2001). Forty-four housewives, aged 37 to 58, were recruited as a customer group and 20 design practitioners, who have more than 1 year interior design practice in field, participated as a designer group in the evaluation experiment. As in the car crash pads case, the principal component regression and the quantification theory type I method were utilized to analyze the relationship between luxuriousness and related variables Analysis and Modeling Results. A series of principal component regressions were conducted to analyze the relationship between overall luxuriousness and tactile and visual luxuriousness scores. The results are presented in Table 16 and Table 17. The results

14 118 BAHN ET AL Luxuriousness Coefficient of Horizontal Static Friction Figure 5 An example of categorizing continuous design attributes of car crash pad. Figure 6 Examples of wallpaper (left) and flooring material (right). show that both the customer group and the designer group were influenced more by visual characteristics than tactile characteristics. The results of the quantification theory type I analysis, which are shown in Table 18 (wallpaper) and Table 19 (flooring material), show the ranges of the partial regression

15 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 119 TABLE 12. Category Hierarchical Structure of Affective Features for Wallpaper Affective Features Tactile Material Degree of softness Degree of smoothness Degree of elasticity Shape Degree of embossment, density Degree of embossment, depth Degree of embossment, size Degree of embossment, regularity Visual Shape Degree of vividness of pattern Degree of size of unit pattern Degree of complexity of pattern Degree of regularity of pattern Color Degree of warmness of color Degree of clearness of color Degree of gloss coefficients and the relative importance of each variable. Similar to the results of the car crash pad case, there were significant differences between customers and designers in perception of luxuriousness of wallpaper and flooring materials. Tables 20, 21, 22, and 23 show the results of the quantification theory type I analysis presenting regression coefficients of each affective feature. From these results, as with the crash pad results, designers can better grasp users understanding of luxuriousness by combining the effects of each variable and each level Identification of Relationship between Luxuriousness and Design Attributes of Wallpaper and Flooring Materials. With respect to the luxuriousness of wallpapers and flooring materials, related design attributes were collected based on expert opinion. In a similar manner to the car crash pad case, the relative importance of each TABLE 13. Category Hierarchical Structure of Affective Features for Flooring Material Affective Features Visual Material Degree of wood similarity Degree of vividness of pattern Degree of visual naturalness Color Degree of warmth of color Degree of visual hardness Shape Degree of gloss Degree of spaciousness Degree of visual comfort Degree of harmoniousness Tactile Material Degree of roughness Degree of wood similarity Degree of tactile naturalness

16 120 BAHN ET AL. TABLE 14. Samples Used in Evaluation Experiment for Wallpaper Design Attributes Levels Number of Samples Color White 9 Ivory 9 Beige 10 Texture Rectangular 5 Horizontal 6 Directionless 5 Vertical 6 Deformation 6 Gloss Matte 14 Glossy 14 Embossment depth Deep 15 Shallow 13 design attribute and the effect of each level were identified using the quantification theory type I analysis. The analysis results are shown in Table 24 and Table 25. According to Table 24, wallpaper luxuriousness is mainly affected by the surface gloss. In addition, Table 26 and Table 27 show the optimal combination of each design attribute that was drawn from the results of quantification theory type I analysis between luxuriousness and design attributes. TABLE 15. Samples Used in Evaluation Experiment for Flooring Material Design Attributes Levels Number of Samples Size Width (cm) Length (cm) V-cut Yes 32 No 32 Gloss Surface Closed pore 32 Open pore 32 TABLE 16. Results of Principal Component Regression for Wallpaper Group Variable Principal Component Coefficient p Value Customer Tactile luxuriousness 0.31 <0.001 Visual luxuriousness 0.64 <0.001 Designer Tactile luxuriousness 0.25 <0.001 Visual luxuriousness 0.74 <0.001

17 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 121 TABLE 17. Results of Principal Component Regression for Flooring Material Group Variable Principal Component Coefficient p Value Customer Tactile luxuriousness 0.34 <0.001 Visual luxuriousness 0.65 <0.001 Designer Tactile luxuriousness 0.29 <0.001 Visual luxuriousness 0.70 <0.001 TABLE 18. Relative Importance of Affective Features of Wallpaper Customers (R 2 = 0.33) Designers (R 2 = 0.46) Relative Relative Affective Features Range Importance (%) Range Importance (%) Tactile Softness Resilience Embossment density Embossment depth Embossment size Embossment regularity Visual Vividness of pattern Size of pattern Complexity of pattern Regularity of pattern Warmness of color Clearness of color Gloss TABLE 19. Partial Regression Coefficient of Each Level of Tactile Affective Features of Wallpaper Affective Embossment Embossment Embossment Embossment Features Softness Resilience Density Depth Size Regularity Group C D C D C D C D C D C D 1 Solow Low A little low Normal A little high High So high Group C: Customers, Group D: Designers.

18 122 BAHN ET AL. TABLE 20. Partial Regression Coefficient of Each Level of Visual Affective Features of Wallpaper Affective Vividness Size of Complexity Regularity Warmness Clearness Features of Pattern Pattern of Pattern of Pattern of Color of Color Gloss Group C D C D C D C D C D C D C D 1 Solow Low A little low 4 Normal A little high 6 High So high Group C: Customers, Group D: Designers. 4. DISCUSSION AND CONCLUSIONS Designing an affective product is creative work. The main challenge for affective design is to accurately grasp customers affective needs and to subsequently design products that satisfy those needs (Tseng & Piller, 2003). In most cases, it is very hard to capture customers affective needs due to their linguistic origins. Luxuriousness is also an ambiguous and complex emotion. In an attempt to simplify the complexity and ambiguity of the target emotion, we applied statistical modeling techniques to relate affective features whose meanings are concrete, which identified each level s effect on affective features. These results can provide guidance and insight to product design practitioners in the early TABLE 21. Relative Importance of Affective Features of Flooring Material Customers (R 2 = 0.51) Designers (R 2 = 0.64) Relative Relative Affective features Range Importance (%) Range Importance (%) Visual variables Wood similarity Vividness of pattern Visual naturalness Looking cold or warm Looking hard Gloss Spaciousness Looking comfort Tactile variables Roughness Wooden texture Tactile naturalness

19 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 123 TABLE 22. Partial Regression Coefficient of Each Level of Visual Affective Features of Flooring Material Affective Features Roughness Wooden Texture Tactile Naturalness Group C D C D C D 1 Solow Low A little low Normal A little high High So high Group C: Customers, Group D: Designers. stage of product development. In addition, the effects of each level of design attributes were identified through systematic evaluation of the experiment, which designers can use to determine design specifications. The results showed that some significant differences exist between designers and users regarding product perception. The reduction of this discrepancy is a challenge for designers (Khalid & Helander, 2006). One way to narrow the gap between designers and customers is to adopt a user-centered approach (Helander & Khalid, 2005). Designers need to identify and study the needs and affection of users as well as the latest design trends (Hsu et al., 2000). As an effective solution to these issues, this study provides quantitative results of some important affective features and the effective methodology to be adopted. In this study, principal component regression and quantification theory type I were adopted to analyze the effect of each factors. Principal component regression is an effective method to analyze the effect of correlated Kansei variables. A number of Kansei engineering studies (Jindo & Hirasago, 1997; Nakada, 1997; Tanoue et al., 1997; You et al., 2006) have used the quantification I method to analyze the effects of categorical and continuous design variables on customer image and impression since the quantification I method can estimate the relative importance of continuous and categorical variables at once. Furthermore, the quantification I method does not assume the distribution of error, whereas the GLM (General Linear Model) method assumes the normality of error (Heo, 1998) so that it might be suitable to analyze fuzzy Kansei data set. The results of the case study successfully demonstrated the practical effectiveness of the proposed framework. In addition to identifying a quantitative relationship between design variables and the target emotion, this study s framework also facilitated the identification of relationships between related affective features and the target emotion. The results of affective features can be used to understand the target emotion in order to determine optimal product concepts and attribute levels, as obtained from the results, which can serve as the basis for product design. In this way, users affective needs can be transmitted into design specifications that will meet the requirements of the end users. This study specifically explored the quantitative relationship between luxuriousness and related attributes such as affective feature and design attributes. By modeling the luxuriousness using affective

20 124 BAHN ET AL. TABLE 23. Partial Regression Coefficient of Each Level of Tactile Affective Features of Flooring Material Affective Wood Vividness Visual Looking Cold Looking Looking Features Similarity of Pattern Naturalness or Warm Hard Gloss Spaciousness Comfort Group C D C D C D C D C D C D C D C D 1 So low Low A little low Normal A little high High So high Group C: Customers, Group D: Designers.

21 CUSTOMER NEEDS FOR LUXURIOUSNESS INTO PRODUCT DESIGN ATTRIBUTES 125 TABLE 24. Results of Quantification Theory Type I Analysis, Wallpaper Customers (R 2 = 0.26) Designers (R 2 = 0.34) Design Attributes Range Relative Importance (%) Range Relative Importance (%) Color Texture Gloss Embossment depth TABLE 25. Results of Quantification Theory Type I Analysis, Flooring Material Customers (R 2 = 0.28) Designers (R 2 = 0.42) Design Attributes Range Relative Importance (%) Range Relative Importance (%) Size Width Length V-cut Gloss Surface type TABLE 26. Optimal Combinations of Each Design Attribute of Wallpaper Design Attributes Color Texture Gloss Embossment Depth Optimal level Ivory Rectangular Glossy Deep TABLE 27. Optimal Combinations of Each Design attribute of Flooring Material Design Attributes Length (cm) Width (cm) V-Cut Gloss Surface Optimal level N N Closed pore features whose meanings were clear and easy to grasp, the luxuriousness could be decomposed into more concrete dimensions. Based on these results, it is expected that product design practitioners can conceptualize the luxuriousness more clearly. The procedure proposed in this study was verified through automobile and interior room products case studies. However, due to the difficulty of collecting appropriate samples, the number of design attributes is limited. To investigate more precise relationships between design attributes and target emotions, more design attributes and evaluation samples should be utilized. In addition, to investigate the relationship between each affective features level and quantitative physical dimensions, further research that relates affective characteristics to physical characteristics of products is required.

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