Kansei

HCI

User

M e n t a l m o d e l

Matching Mental Model

Customer Satisfaction

PRODUCT

Ethnographer Researcher

Developer Tester Designer

M e n t a l m o d e l

Kansei Engineering

• Japanese term used to describe people’s impression towards object, surrounding, situation

• Similar to Affective Engineering

• Found by Mitsuo Nagamachi

Kansei Gateway

Kansei Gateway

• Use 5 senses to deduce feelings, emotions and intuition – vision

– hearing

– smell

– taste

– touch

Kansei Words

• When a person’s senses are triggered, psychological cognition that involves perception, judgment and memory will become apparent to a person.

Stimulus and Response

What Words ?

Stimulus and Response

Stimulus and Response

What Words ?

Fun Colors

Stimulus and Response

Stimulus and Response

What Words ?

Star Bouncy

Stimulus and Response

Stimulus and Response

What Words ?

Circular Google

Kansei Words

• How to evaluate the impact the object, situation or surrounding has on someone ?

• Ask the person to express their Kansei in words for the object, situation or surrounding they would like to encounter in the future.

Kansei Overview

Kansei for e-Commerce

Past Research

• Gather Kansei Words from – Magazines – Common keywords – Interviewing Subject Matter Expert

• Proposal – Usability testing on e-Commerce websites – Feedback Capture After Task (FCAT) – Retrospective Think Aloud (RTA) – Retrospective Think Aloud with Eye Tracking

(RTE)

FCAT e-Commerce

• FCAT is useful in determining issues – defects – requirements

Method & Instrument

• Six users

• Male age range from 18-22

• Tobii T60 Eye Tracker, Tobii Studio and URANUS

• Moderator

• Duration of one hour

• 5 tasks

3 methods

1. Feedback Capture after Task (FCAT)

– type their thoughts in URANUS

– does not involve playback of video

2. Retrospective Think Aloud (RTA)

– video playback of task performed by user

– users are prompted by the moderator to talk about what was done to complete the tasks

– Hofstede’s model

3 methods

3. Retrospective Think Aloud with Eye Movements (RTE)

– similar to RTA but additionally during playback, eye tracking features such as gaze overlay, gaze plot and heat map are analyzed

Tasks

Tasks Description

1 Next Friday is your partner’s birthday; you wish to buy him/her a small gift. You have a budget of RM30 to buy a gift for your partner. What are the 2 gifts that you think is most suitable for your partner?

2 Read the description of each product.

3 Find the product comparison tool and compare the price of ‘Love Letter Keychain’ and ‘3D Character Keychain’.

4 You are a new user to this website. Create a new account for this website.

5 You do not wish to buy anything today. You want to log off the account.

FCAT Output

Synthesizing Kansei Word

• 4 Categories

– Aesthetic

– Physical

– Sensational

– Operational

Kansei Checklist - Aesthetic

Kansei Checklist - Physical

Kansei Checklist - Sensational

Kansei Checklist - Operational

Case Study: Sunglasses

e-Commerce UX

o Optomet ry

Kansei Words

KE Type 1

1. Collection of Kansei words

2. Collection of specimens

3. Classification of item/ category:

4. Evaluation experiment

5. Statistical analysis

6. Interpretation of the analysed data

7. Identification of influential design elements

Specimen

4. Evaluation experiment

Statistical Analysis

1. Factor Analysis

F1 F2 F3 F4 F5

Eigenvalue 14.508 7.141 2.368 1.091 0.821

Variability (%) 48.361 22.802 7.892 3.638 2.736

Cumulative % 48.361 80.054 80.054 83.692 86.428

Statistical Analysis

2. Factor Loading Table

F1 F2

Trendy 0.921 Sporty 0.959

Beautiful 0.920 Cool 0.885

Gorgeous 0.917 Safety 0.784

Stylish 0.891 Practical 0.770

Designer 0.884 Modern 0.572

Glamorous 0.882 Intellectual 0.448

Premium 0.869 Premium 0.384

Hot 0.863 Hot 0.337

Bold 0.848 Youthful 0.323

Sophisticated 0.830 Sleek 0.310

Principal Component Analysis

Interpretation

Partial Least Square Analysis

Item - Category Modern Intellectual Premium Youthful

Intercept 2.5624 3.1067 2.5627 2.7351

Color Intensity-Dark 0.0185 0.0597 0.0339 -0.0037

Color Intensity-Light 0.0848 0.0589 0.0965 0.0550

Color count-One -0.0149 -0.0351 0.0232 0.0619

Color count -Two 0.0245 0.0376 0.0441 -0.0197

Color count –Three or more -0.0146 -0.0142 -0.0596 -0.0215

Frame Color-Blue 0.4826 0.2931 0.4630 0.1604

Frame Color-Orange 0.2361 0.1819 0.2947 0.1325

Frame Color-Yellow 0.1541 0.0843 0.1432 0.0169

Frame design-Half frame 0.1001 0.0686 0.1029 0.0228

Frame design-Round frame 0.0550 0.0366 0.0602 0.0354

Frame design-Thin frame 0.1259 0.0275 0.0971 0.0547

Overall color: Two. Frame: Blue, orange, or yellow. Half or thin frame. Light colors.

Recommendation

Conclusion

• KE Type have been implemented.

• Recommendations are sunglasses with overall color of two; half or thin frame; and light colors.

• KE could be used for other e-commerce products as well.

Our Team

o Ashok S iva j i o ashok.s iva j i@mimos.my o +60122119154

References

1. Anitawati, M.L.: Design & Emotion: The Kansei Engineering

Methodology.

2. Nagamachi, M.: The story of Kansei Engineering.

3. Ishihara, I., Nishino, et al, Kansei And Product Development.

4. Lokman, A.M., Nagamachi, M.: Validation of Kansei

Engineering Adoption in E-Commerce Web Design

5. Sivaji, A., Mazlan, M. F., Soo, S. T., Abdullah, A., Downe, A.

G.: Importance of Incorporating Fundamental Usability with

Social, Trust & Persuasive Elements for E-Commerce

Website.

References

6. Goh, K.N., Chen, Y.Y., Lai, F.W., Daud,S.C., Sivaji A., Soo

S.T.: A Comparison of Usability Testing Methods for an E-

Commerce Website: A Case Study on a Malaysian Online

Gift Shop.

7. Sivaji, A., Soo, S. T.: Website User Experience (UX) Testing

Tool Development using Open Source Software (OSS).

8. Ngip-Khean Chuan, Ashok Sivaji, Mizhanim Mohamad

Shahimin, Nursyakinah Saad “Kansei Engineering for E-

Commerce Sunglasses Selection in Malaysia”

9. Sivaji, A., Soo, S. T.: Website User Experience (UX) Testing

Tool Development using Open Source Software (OSS).

10. Zhu X, Huang J, Zhou Q. Apparel image matting and

applications in e-commerce.