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Procedia Manufacturing 3 (2015) 6228 - 6236
6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the
Affiliated Conferences, AHFE 2015
Affective perception of disposable razors: A Kansei Engineering
approach
Bruno Razzaa*, Luis Carlos Paschoarellib
"Maringa State University (UEM), R. Dom Pedro II, 598, Cianorte-PR 87200-055, Brazil bUniv. EstadualPaulista (UNESP), Av. Eng. Luis Ed. Carrijo Coube, 14-01, Bauru-SP, 17013-360, Brazil
Abstract
In recent decades, the market of consumer products has changed from the production-oriented point of view to a more market-focused, i.e. aiming to attend consumers' expectations. Today, consumers turn their attention not only to the logical and rational aspects of the product, but increasingly symbolic and emotional factors have gained an important role in buying decision. Some methods have already been used to design emotional meaning in the products, such as the Kansei Engineering with reported results in literature. This study had as a goal to investigate affective aspects of disposable razors perceived by the users and how they relate to product features using Kansei Engineering. Thus, 40 disposable razors commonly found in the international market were evaluated in a virtual system through a variety of pictures (photographic representation) of the products. In order to identify the most relevant product features Morphological Analysis was performed. To evaluate the disposable razors, 321 male adults volunteered in this study. Semantic differential with 17 pairs of bipolar adjectives were employed to construct the semantic space in Kansei Engineering. The results showed no high correlation in the sample. Moderate correlations, however were found in 12 pairs of bipolar adjectives with 13 product features. Thus, it can be assumed that affective responses can be mildly related to product feature, considering limitation of statistic treatment.
© 2015PublishedbyElsevier B.V. This is anopenaccess article under the CC BY-NC-ND license
(http://creativecommons.Org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of AHFE Conference
Keywords:Kansei Engineering; Emotional Design; Semantic Differential; Factor Analysis; Disposable Razor.
* Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 . E-mail address:author@institute.xxx
2351-9789 © 2015 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.Org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of AHFE Conference
doi: 10.1016/j.promfg.2015.07.750
1. Introduction
In recent decades, the market of consumer products has changed from the production-oriented point of view to a more market-focused, i.e. aiming to attend consumers' expectations. Today, consumers turn their attention not only to logical and rational aspects of the product, but increasingly symbolic and emotional factors have gained an important role in buying decision [1]. All this aspects constitute the user experience with a product.
The User Experience was defined by Hekkert [2] as the entire set of effects that is elicited by the interaction between a user and a product, including the degree to which all our senses are gratified (aesthetic experience), the meanings we attach to the product (experience of meaning), and the feelings and emotions that are provoked (emotional experience). Although great advances in last decades were made by ergonomic design, little attention was given to semantic and emotional aspects of the product [3, 4].
Some methods have already been used to design emotional meaning in the products, such as the Kansei Engineering. This tool aims to convert expectations, desires and emotions of users into product attributes. Kansei Engineering can be defined as the translating technology of a consumer's feeling and image for a product into design elements [5]. It is originated from Japan in 1970s and remained almost unaware by the product design community until the journal papers published by Mitsuo Nagamachi and his colleagues [5]. According to Yang [6], the basic assumption of Kansei engineering studies is that there is a cause-effect relationship between affective perception and product's attributes. Kansei is a Japanese word referred as the emotional affection in contrast to chisei, related to the reason aspects [7].
There are many related papers in the literature showing how affective aspects of products can be converted into product features, and with many reported methodological implications; however none investigating disposable razors. This product is a very task oriented device but can also be associated with other more subtle aspects such as manliness and status.
This study had as a goal to investigate affective aspects of disposable razors perceived by the users and how they can relate to product features using Kansei Engineering.
2. Material and methods
2.1. Building Kansei Engineering
Kansei Engineering consists on the relationship of two structures: the product features and the semantic space. The semantic spaceis build based on the subjective perception of the user about the product; the most used method is the Semantic Differential [6, 7, 8,9, 10, 11], a method created by Osgood [12] which consists of two pair of bipolar adjectives (opposite meaning) anchoring both sides of a Likert scale. These words were obtained from product packages, advertisings, specialized magazines, scientific journals andmanufactures websites, because those sources constitute the semantic universe of disposable razors; this procedure was described in the Kansei Engineering literature [13, 14, 15].The meaning of each word used in the study as also provided to avoid misinterpretation.
In this study, 17 pairs of bipolar adjectives were applied to evaluate the semantic space of the razors and Semantic Differential was used with a 7 points Likert Scale, ranging from -3 to +3.The position of the pair of bipolar adjectives in the scale was randomized to avoid bias due to association of negative expression, such as 'ugly' or 'bad design' to negative values and vice versa.
The sample of products consisted of 40 disposable razors commonly found in the international market. The criteria of selection aimed to obtain the most distinctive products in order to cover a wider variety of features. Morphological Analysis was performed to select the product features and a group of five industrial designers were recruited to develop the criteria and perform the product evaluation. The analysis of the 40 razors resulted in 16 main features, as described in Table 1. For comprehension purpose, we call 'head' the superior part of the razor, which has the blade, and 'cable' the lower part.
2.2. Subjects
To evaluate the disposable razors, 321 male adults volunteered in this study; their mean age was 30.5 years [± 10.81], ranging from 18 to 66. All subjects were regular users of disposable razors, and most shave twice a week or less (62.1%). Personal data was also collected in order to establish the users profile. Their scholarship status varied from middle school to post graduation. The vast majority of subjects (99.4%) are middle class and 44.7% of the sample work in areas related to art and design, such as fashion design, industrial design, architecture, etc.
Table 1. Categories of the Morphological Analysis.
Categories Feature
General Total length mm
features Type of razor System; disposable
Quantity of colours 1; 2; 3; 4; 5; 6.
Finishing Matte; Glossy; Both,
Special feature None; Flexible blade; Hair cleaner; Precision blade; Vibratory system; Precision trimmer.
Head features Width mm
Height mm
Material Plastic; metallic and plastic
Number of blades 1; 2; 3; 4; 5; 6.
Joint with the cable Fixed; articulated.
Type of hair lifter Rigid and incorporated; Rubber flexible.
Format of hair lifter Parallel lines; Texturized; Hybrid.
Length of hair lifter mm
Type of lube stripe None; Smooth and without linear mark; Smooth with linear mark; Texturized.
Size of lube stripe mm
Cable features Cable length mm
Material Chrome; Metallic; Plastic with rubber application; simple plastic.
Cable format (frontal view) Strait; Cylindrical; Tapered; Hourglass shaped; Hourglass shaped with longer bottom part.
Cable format (lateral view) Strait; Thicker in the top part; Thicker in the middle; Thicker in the bottom; Curved; Cylindrical; Slightly S shaped; Markedly S shaped.
Design of the joint with the head Strait and small; Strait and big; Rounded; Fork shaped; Open in V; Large; Large fork shaped.
Main Textures Deep grooves; Parallel lines; Curved lines; Dots; Roughness; Multiple
2.3. Procedure
The evaluation of the products was performed in a virtual system through a variety of pictures (photographic representation) of the products. Detailed pictures of the product features were also provided in order to prevent from misjudgement. To avoid fatigue due to the high number of variables, each subject evaluated 3 to 5 products only. Written consent to participate in the study was obtained previously.
2.4. Data analysis
Factor Analysis was conduct in order to show the consistency of the semantic space and found the main factors. This procedure also aims to reduce the number of variables to further analysis. To relate product features to affective response and build the Kansei Engineering, Multiple Linear Regression was conducted in the StatSoft Statistic R7. The Factor Analysis conducted was to obtain the Principal Components, with Eingenvalues of 1.0 and Varymax Rotation was applied. This procedure is in accordance with the literature [6, 10,11, 13, 16].
Table 2. Evaluation of affective dimensions. The higher values are associated with the adjectives in bold and the lower values are associated with the adjectives underlined.
Adjectives on the positive
side of the scale (+3) able n ysar e v al ic 'M n M
Product Cheap beautiful io hi s a H u sportive ss e c e un simple light constant practical at v o n in serious lo ol n h c te doubtful lasting rigid modest si e d d a B
Schick Ultrabarba 2.25 -0.80 0.50 -0.65 -0.80 2.30 2.65 1.00 2.05 -2.30 0.20 -2.05 -0.15 -2.05 1.15 2.50 0.20
Gillette Fusion Power -2.39 0.61 0.11 1.89 0.00 -1.28 -1.11 -1.17 -0.06 1.94 -1.28 2.17 -0.44 0.89 -1.44 -1.67 -1.17
Bozzano* Speed 3 133 010 Hl 010 -0.72 194 206 014 217 -1.17 Ö39 -128 -0.72 -083 012 210 -0.44
Bozzano M5 [System] -161 i"44 -133 2.22 -0.89 -0.33 -0.28 -0.44 014 133 -1.72 1*39 -1.00 019 -1.17 -128 -1.61
Schick Xtreme 3 -0"28 -1.39 1.17 1.22 0 2 8 014 1.67 -0.72 018 -0.06 -0.50 017 0~39 -1.00 -0.72 0~56 0H
Bic Sensitive 2.71 -1.67 133 -0.86 1H 2.62 2.90 1.62 2.33 -2*43 012 -2.24 0~81 -2.76 200 215 T"43"
GillettePrestobarbaExcel -0.44 167 -128 2Ü6 -128 014 iH -0.89 il7 022 -1.44 0.89 -1.50 -0.39 -0.39 022 -1.61
KS Azor 5 -2.00 011 -0.39 044 -0.67 -0.83 019 -0.94 0T1 2.22 -1.17 210 -0.50 015 -061 -1.44 -0.83
Dorco Pace 4 -183 2.22 -1.94 178 -1.56 010 -0.39 -1.33 122 1.44 -1.72 1.83 -178 -078 -1.56 -2.33
Schick Slim Triple 013 -0.89 106 012 0Ü6 133 2T H! 133 0.00 -083 0.22 012 -0.67 -0.17 014 017
Schick Hydro -1.00 1.05 -075 110 -0.65 -0.20 015 -0.65 i!5 -0.50 -0.75 0.45 115 010 -0.30 -0.65 -0.50
Bozzano Smart 2 2.83 -2.33 1.89 -2.56 -0.67 212 2 78 156 183 -2.72 128 -2.56 H7 -2.17 2.61 2*67 128"
Gillette Mach 3 -1.67 2.44 -2.22 172 -1.56 -0.28 022 -1.33 11 128 -0.56 014 -2.11 2.22 -2.11 -11 -2.00
BicCode H0 -0.80 015 -0.50 -0.50 21Ö 210 015 21Ö -215 010 -2.10 115 -2.10 125 2.40 011
Bozzano Matrix 3 -161 014 0.00 2"17 -0.39 -0.67 0"06 -0.44 01Ö 1.06 H5 H4 -1.06 050 -1.50 -0.56 -0.94
Equate 3 -HI 128 1.83 HI 014 128 H! 1.00 117 -1.72 1.00 -0.06 -0.39 -083 017 010"
Bic Comfort 3 075 -041 050 182 -0.77 1T8 218 015 180 -168 -1.16 -0.20 010 -155 0 55 110 -0.11
Equate 3 Eco -1.30 012 -0.20 -0.80 -0.64 01Ö -0.02 027 018 -0.02 134 0.23 -1.00 0H 1.02 1H -0.41
Schick Quattro -1.89 0.20 H5 136 -0.32 -0.57 -0.41 -0.14 015 077 -0.16 T! 118 010 0T -11 -0.61
Bic comfort H5 -1.70 iH -075 015 210 215 H 195 -2.3 0 0 25 -2.00 0.35 -1.80 145 210 105
Dorco Pace 6 -2.22 0*50 044 il7 0T -1.50 -0.67 -0.33 -011 11 -078 Ü-^ 010 HI -1.06 -1.39 -0.44
Bozzano Ultraspeed 3 0.56 IH 0~56 028 -0.39 014 144 014 il0 -0.50 115 010 HI -0.39 -0.22 015 010"
Gillette Probak 1 213 -1.66 1l6 -1.14 -0.20 214 2~59 i!5 i!8 -2.39 014 -2.19 0.39 118 170 216 0H
Bozzano Action 3 H3 011 -0.50 178 -1.06 -0.89 -0.39 -0.56 018 01Ö -1.22 HI -1.44 0.56 -1.44 -013 -1.06
Schick Exacta 2 010 -0.60 010 010 -0.80 110 210 010 110 -0.20 -0.80 -0.60 010 -1.20 -0.80 110 010"
Gillette Prestob. Ultragrip 1~20 -0.90 010 015 -045 210 215 010 215 -2.10 -0.10 -1.20 115 -1.70 010 210 011
Bozzano Smart 1 2.06 -1.44 iH -0.89 017 213 212 133 189 -2I1 139 -1.72 156 -2.06 194 218 ill
Schick Exacta 3 -0.20 H0 -1.00 110 -0.80 010 210 -0.20 160 110 -1.40 010 -0.80 -0.80 -1.00 010 -0.40
GMetteFusion -0.89 0.89 -0.50 143 -121 016 1.07 -0.68 136 -021 IH 079 IH -0.07 -1.04 010 -1.25
GMettePrestobarba 182 Hi 179 -2.04 -0.07 275 2H ill 189 -2-71 2.11 -271 012 IH 2.61 218 ill
Bozzano Smart 2 sensitive 17 -2.07 182 -1.79 018 213 217 1.04 185 -2.39 16 -213 012 1H 215 213 2.11
Bozzano Comfort 2 sensit. H0 H5 150 -175 115 215 210 180 21Ö -2.70 110 -215 H5 -2.00 215 215 m
Gillette Mach 3 Power -2.44 2.44 -161 2.61 -0.94 -0.17 -0.39 -0.83 018 115 -1.72 2.28 -178 117 -133 -2.00 -2.33
Bozzano M5 [disposable] -1.00 -1.00 il0 010 -0.80 010 110 -0.20 110 010 -0.40 010 -1.20 010 -1.20 010 010"
Gillette Prestobarba 3 ice H5 015 010 130 -105 120 190 -0.05 1.75 -0.60 -1.00 010 -1.50 H5 -015 015 -0.55
Bozzano ultracomfort 2 189 -1.22 0I9 -1.67 -0.67 212 212 139 150 -2.67 Hci lH 0^ -m 214 213 010"
Schick Exacta 2 -0.20 0^ 010 010 -1.60 210 110 110 0"10 -0.80 -0.60 010 -0.80 -1.20 140 140 -0.20
Bic Comfort 2 2^ -1.72 1I0 -1.52 -0.40 218 212 124 210 -2.56 110 -2.56 -0.32 118 214 210 ill
Gillette Prestobarba 3 bs -018 216 -1.04 014 il2 -1.24 m 1.44 -2.36 176 -148 016 -1.84 -0.92 -1.52
Bic comfort Twin sensit. -1.00 012 -0.92 018 21^ 212 01^ il6 -118 014 -1.52 0^ -1.00 188 H 01?
Adjectives on the u S x ^^^ <a o » -o e
negative side of the scale ^ | ^ ^^ £ '> $ ^ I
xp es c v d co ad r e f u
e tr h l
*Bozzano products are produced by Personna Co.
3. Results and discussion
Results of the perception of affective dimensions of razors are shown in Table 2. This table show the results using the scale from -3 to +3. The adjectives in the top are associated to the positive side of the scale and the adjectives in the bottom are related to the negative side of the scale. It is important to address that a negative score do not necessary mean a negative evaluation. The higher and lower scores are highlighted in bold.
The model of system in disposable razors (discard only the head with the blades) was better evaluated than the razors that are discardedentirely. This behaviour is possible to be noticed by observing the scores of, e.g., Gillette Mach 3, Dorco Pace 4 and KS Azor 5. Another pattern identified is that the razors with less blades (one or two) were rated as worse for many variables (e.g. Bozzano Smart 1, Bozzano Smart 2, Bic Sensitive and Gillette Prestobarba) and consequently the razors with more blades were considered better (e.g. Gillette Fusion Power, Dorco Pace 6). However, Gillette Mach 3 has received high positive evaluation for many semantic axes, indicating a good image of quality and performance by the user besides having only three blades. It can be assumed that a positive influence of marketing and a strong brand image might have influenced the users evaluation [17].
Table 3 shows the results of Factor Analysis performed for the affective dimensions. Strong factors (above 0.7) are highlighted in bold and moderate factors (above 0.4) are underlined. Only three semantic axis were found for the 17 bipolar adjectives, representing 11,31% of the total variance.
Table 3. Results for Factor Analysis.
[+] [-] Factor 1 Factor 2 Factor 3
Cheap expensive 0.669299 0.338687 0.337485
beautiful ugly -0.236168 -0.755448 -0.304083
unfashionable elegant 0.182344 0.781562 0.209264
sportive classic -0.262567 -0.204669 -0.751351
unnecessary essential -0.210031 0.676417 0.019197
simple complex 0.769853 0.084852 0.290010
light heavy 0.837421 0.141522 0.066439
constant versatile 0,101859 0.163579 0.692857
practical complicated 0,782556 -0.226445 0.010999
innovative common -0.568360 -0.400604 -0.478887
serious jovial 0.106175 0.137006 0.791634
technological traditional -0.553898 -0.365692 -0.566843
doubtful reliable 0.046646 0.757863 0.131875
lasting ephemerous -0.490946 -0.577233 -0.084571
rigid flexible 0.244302 0.239601 0.697341
modest luxurious 0.689870 0.455782 0.382122
Bad design Good design 0.201411 0.771335 0.288799
Percentage (%) of explained variation 4.027239 3.981585 3.301320
Total Variation 11.310143%
Factor 1 includes the following pair of bipolar adjectives: cheap/expensive; simple/complex; light/heavy; practical/complicated; innovative/common; and modest/luxurious. Factor 2 includes: beautiful/ugly; unfashionable/elegant; unnecessary/essential; doubtful/reliable; lasting/ephemerous; bad design/good design. And Factor 3 groups the following pairs: sportive/classic; constant/versatile; serious/jovial; technological/traditional; rigid/flexible.
The Factor Analysis results indicate the patter of the semantic space for this sample of razors, showing, e.g. that the products considered expensive are also perceived as innovative, heavy and luxurious. This similarity in perception allows the adjectives to be grouped and treated as a single semantic axis [6; 18]. For razors, the aesthetic perception is dissociated from the perception of monetary value; the latter concept may be more related to the material of which the product is made, as can be seen by the variable light/heavy. According to Spence and Gallace [19], since the visual channel could not perceive the weight of the product, the user tends to make associations with other attributes to complete the lack of sensory channels.
It is important to consider, however, that five pair of adjectives are related to more than just one Factor, as follows: innovative/common; technological/traditional; doubtful/reliable; lasting/ephemerous; and modest/luxurious. This intricate relationship is natural in the human perception, as individuals tend to notice the objects in a whole and not by its parts isolated.
Table 4 shows the results of Multiple Linear Regression for the main factor found in Factor Analysis and the product features identified in the Morphological Analysis.
Table 4. Results of the Multiple Linear Regression for Factor Analysis main semantic axes.
Categories Factor 1 Factor 2 Factor 3
Total length 0.30 0.35 0.34
at <a Type of razor 0.19 0.16 0.26
eral Quantity of colours 0.25 0.35 0.25
en Finishing 0.18 0.19 0.18
Special feature 0.13 0.20 0.15
Length 0.08 0.16 0.12
Height 0.08 0.07 0.08
Material 0.20 0.22 0.16
Number of blades 0.25 0.30 0.24
Articulation 0.33 0.38 0.33
res Type of hair lifter 0.30 0.27 0.26
tur at Format of hair lifter 0.21 0.22 0.17
e f Length of hair lifter 0.15 0.17 0.05
« e Type of lube stripe 0.20 0.28 0.17
X Size of lube stripe 0.15 0.09 0.13
Cable length 0.14 0.23 0.18
es r Material 0.25 0.23 0.24
tu at Cable format (F.V.) 0.28 0.44 0.35
fe le Cable format (L.V.) 0.27 0.42 0.34
abl Joint with the head 0.30 0.36 0.27
u Main Textures 0.16 0.26 0.21
The results of the Multiple Linear Regression presented in Table 4 have no practical results for the Kansei Engineering since no correlation were found. Part of the problem is the low percentage of explained variation found the Factor Analysis. According to Comrey and Lee [18], the percentage of explained variation is an indicative of the consistency of the sample to perform the analysis, and values below 0.32 are considered weak. Additionally, some semantic axes are related to more than just one factor, creating a different pattern in subjects' perception.
The main problem with Semantic Space is that the data is full of noise and is difficult to isolate and to control. This is due to the nature of human perception, which is influenced by many variables such as individual expectation, previous experience, context, humour, preferences, etc. [20; 21].
Hence, another Multiple Linear Regression was conducted comparing all bipolar adjectives to the product features in the Morphological Analysis. This practice has also been reported in the literature [14, 22, 23]. The results for this latters analysis can be seen in the Table 5.
The results showed no high correlation in the sample. Moderate correlations, however were found in 12 pairs of bipolar adjectives with 13 product features. Thus, it can be assumed that affective responses can be mildly related to product feature, in this study. For example, bigger razors are perceived as more expensive, more innovative, more luxurious and more complex. The same happens with the increasing number of blades, which are perceived as more technological, expensive and luxurious.
4. Conclusion
Due to statistical limitation, it cannot be affirmed by the results of this study how the manipulation of product features will lead to determined affective sensation. It is know that the perception of the majority of the product variables do not vary in linear standard [10, 24, 25]. Other statistical treatments such as fuzzy logic, genetic
algorithms and neural network [10, 26, 27] should be more suitable to analyse the behaviour of human perception with product interaction. However, an attempt to analyse the results using neural network techniques described in literature was performed [28, 29, 30]; however, the amount of data was too complex to apply this treatment. It was necessary a larger sample and much less variables, leading to a context far more distant from the reality. Due to this data processing restriction, the majority of Kansei Engineering studies use few semantic axes [6, 20, 24, 28, 31, 32, 33, 34, 35, 36]. This is the main reason why Factor Analysis is applied in this context. However, in this study and other reported in literature [11, 13] the reduction performed by Factor Analysis put different aspects in the same semantic axes leading to difficulties to use Kansei Engineering in the actual design practice.
Table 5. Results of the Multiple Linear Regression for all 17 pair of bipolar adjectives.
Categories
*!3 O 13 <D ia us <D us o ir u T3 o o M
T3 <D > > o M o o r xi e x ¡3 e M
a o "o a r at > o n G O S S o o us o ir e &0 o n JS o e T n a rt £ JD u o ß Lasting/ epheme c rs S es T3 o s Bad des design
Total length -0.65 0.44 -0.34 0.49 -0.12 -0.53 -0.53 -0.34 -0.31 0.57 -0.35 0.61 -0.31 0.50 -0.45 -0.67 -0.43
Type of razor -0.49 0.36 -0.28 0.35 -0.08 -0.39 -0.47 -0.21 -0.23 0.33 -0.16 0.41 -0.21 0.38 -0.27 -0.49 -0.32
Quantity of colours -0.47 0.38 -0.28 0.42 -0.08 -0.40 -0.38 -0.28 -0.23 0.46 -0.35 0.49 -0.23 0.32 -0.40 -0.51 -0.34
Finishing -0.44 0.30 -0.25 0.28 -0.06 -0.39 -0.43 -0.22 -0.28 0.38 -0.19 0.38 -0.17 0.34 -0.27 -0.49 -0.29
Special feature -0.25 0.20 -0.14 0.22 -0.05 -0.20 -0.21 -0.16 -0.13 0.25 -0.20 0.26 -0.15 0.18 -0.23 -0.29 -0.21
Length -0.23 0.16 -0.10 0.23 -0.01 -0.23 -0.24 -0.11 -0.14 0.21 -0.16 0.23 -0.06 0.15 -0.16 -0.25 -0.13
Height -0.25 0.13 -0.07 0.13 -0.03 -0.24 -0.27 -0.10 -0.19 0.17 -0.07 0.18 -0.05 0.16 -0.11 -0.27 -0.11
Material -0.39 0.33 -0.26 0.26 -0.08 -0.32 -0.35 -0.24 -0.19 0.36 -0.22 0.36 -0.19 0.31 -0.29 -0.45 -0.30
Number of blades -0.57 0.36 -0.26 0.42 -0.06 -0.50 -0.50 -0.30 -0.32 0.50 -0.30 0.53 -0.20 0.41 -0.39 -0.60 -0.32
Articulation -0.62 0.45 -0.35 0.55 -0.14 -0.51 -0.49 -0.36 -0.28 0.55 -0.38 0.63 -0.30 0.47 -0.49 -0.64 -0.42
Type of hair lifter -0.61 0.39 -0.29 0.42 -0.07 -0.51 -0.54 -0.32 -0.32 0.56 -0.27 0.56 -0.24 0.50 -0.44 -0.64 -0.34
Format of hair lifter -0.46 0.27 -0.21 0.30 -0.06 -0.41 -0.41 -0.23 -0.26 0.46 -0.22 0.44 -0.16 0.37 -0.30 -0.50 -0.24
Length of hair lifter -0.31 0.19 -0.12 0.15 -0.06 -0.27 -0.25 -0.15 -0.18 0.30 -0.17 0.28 -0.12 0.19 -0.19 -0.34 -0.18
Type of lube stripe -0.45 0.36 -0.30 0.39 -0.10 -0.38 -0.35 -0.27 -0.21 0.38 -0.28 0.44 -0.22 0.34 -0.33 -0.47 -0.31
Size of lube stripe -0.35 0.21 -0.15 0.25 -0.01 -0.26 -0.28 -0.16 -0.14 0.24 -0.09 0.30 -0.18 0.25 -0.21 -0.33 -0.15
Cable length -0.37 0.21 -0.13 0.35 0.01 -0.35 -0.33 -0.16 -0.21 0.31 -0.23 0.36 -0.09 0.25 -0.24 -0.36 -0.19
Material -0.58 0.38 -0.30 0.34 -0.06 -0.49 -0.55 -0.26 -0.34 0.52 -0.23 0.53 -0.22 0.47 -0.35 -0.62 -0.34
Cable format (F.V.) -0.51 0.39 -0.29 0.58 -0.13 -0.44 -0.35 -0.34 -0.19 0.47 -0.44 0.56 -0.26 0.33 -0.48 -0.52 -0.38
Cable format (L.V.) -0.48 0.37 -0.28 0.56 -0.13 -0.41 -0.33 -0.33 -0.17 0.44 -0.42 0.54 -0.25 0.33 -0.46 -0.48 -0.36
Joint with the head -0.60 0.38 -0.28 0.46 -0.10 -0.48 -0.44 -0.34 -0.27 0.55 -0.36 0.58 -0.27 0.41 -0.46 -0.62 -0.36
^ Main Textures
-0.23 0.23 -0.19 0.33 -0.14 -0.17 -0.13 -0.20 -0.04 0.21 -0.26 0.27 -0.19 0.17 -0.28 -0.23 -0.22
Future research conducted with more powerful and precise statistical treatments can bring some light into the correlation between affective response and product features in disposable razors. Additionally, the advances in mathematical treatments may contribute to Kansei Engineering to rely less on subjective perception of the designers and their experience and judgements, becoming a powerful and, more importantly, more practical tool to assist designing emotional attributes in consumer products.
Acknowledgements
The authors gratefully acknowledge CAPES (Coordination for the Improvement of Higher Education Personnel -Brazil) and CNPq (National Council for Scientific and Technological Development - Brazil, Proc. 309290/2013-9) for the financial support.
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