case-based design aid for sustainable behavior and lifestyle

8/11/2019 Case-based Design Aid for Sustainable Behavior and Lifestyle

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Case-based Design Aid for Sustainable Behavior and Lifestyle

Li-Hsing Shih1and Yi-Hsien Chang

1

1Dept. of Resources Engineering, National Cheng Kung University, Tainan, Taiwan

Abstract

This study proposes two approaches to facilitate design for sustainable behavior and lifestyle based on acase library containing existing product designs that lead to behavior change. For each case, expected

behavior change, design patterns and technologies used are analyzed and recorded in the cases library.

In the first approach, relationship between target behavior, design pattern and technology used is

constructed based on the cases. With tables presenting the relationship, designers can find suggestions

of design patterns and technologies for a given target sustainable behavior. In the second approach,

sustainable Kansei descriptors are chosen to describe customer feelings for each case so that

relationship between Kansei description and design patterns and technologies used can be established.

After sampling measures of multiple Kansei description via a questionnaire survey, statistical

correlations between Kansei description and design patterns and technologies used are obtained.

Designers can find useful design patterns and technologies for intended feelings with Kansei

descriptors.

Keywords:Case based reasoning, design with intent, Kansei, sustainable behavior.

1. INTRODUCTION

In the past decades, design for lower environmental

impact in manufacturing stage has caught more attention

than in use stage. Recently, focus may have turn to

environmental impact occurring in use stage. Bhamra et al

[1] stated that a great potential of lowering environmental

impact exists in household energy use. Herring and Roy [2]

suggested that a rebound effect appeared when energy

saving produced by energy efficient products is taken back

in the form of higher consumption. Many consumers,knowing that products (e.g. light bulbs) now costs less, are

less concerned about turning them off, or even leave them

on all night. Thus these behaviors take back some of the

energy savings by the green products. Because of these

phenomenon, design for sustainable behavior (DfSB) was

discussed most anxiously recently. Eco-design has to not

only adopt green materials or energy efficient technology

but also change consumers behavior in the use stage.

Consumers decision and behavior should be incorporated

in design stage so that eco-design could lead consumer to

a sustainable way of living.

There are many literatures working on design that

can lead to behavior change, although they could be

presented in different terms. For instance, Lilley [3], Elias

et al [4], Lockton et al [5], Wever et al [6] and Pettersenand Boks [7] worked on design intervention

emphasizing that designers should take responsibility of

user behavior. If applied to DfSB, design and technology

should persuade or guide users to sustainable way of using

products. Design intervention was categorized into three

types: educational intervention, technological interventionand product-led intervention. In product-led intervention,

designers can adopt concepts of behavior steering,

eco-feedback and intelligent product or systems to guideconsumers. Jelsma [8] worked more on the design

philosophy behavior steering. Wever et al [6] suggested

to involve users in the design stage and used the

term user-centered design where designers should

collect information, identify needs of users and invite

users to involve, evaluate and test the product design.Lockton et al have had a series of studies and developed

methodology called design with intent (DWI)

([5][9][10][11]). They presented three ways to influenceuser behavior: enabling, motivating, and constraining

behavior. Wever et al [6] integrated the concepts

mentioned above and suggested more work could be donein design for sustainable behavior area. To summarize,

there are several ways to influence user behavior including

(a) Eco-feedback

(b) Educational intervention

(c) Scripting, enabling behavior

(d) Forced functionality, intelligence system

Locton et al presented useful DWI method with 11target behaviors and more than 101 design patterns and 8

lenses that can be adopted to achieve target behaviors.

They [9] mentioned that DWI method can also be used in

design for sustainable behavior. In this study, targetbehavior and design pattern are included as major

elements of domain model of case based reasoning.

On the other hand, technology should also be

developed for changing people behavior instead of simply

Proceedings of EcoDesign 2011 International Symposium

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OI 10.1007/978-94-007-3010-6_65, Springer Science+Business Media Dordrecht 2012D

,Design for Innovative Value Towards a Sustainable SocietyM. Matsumoto et al. (eds.),


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fulfilling their needs (Verbeek et al [12]). Fogg [13]

started research on persuasive technology that focuses

on how technology could persuade or influence people.

Jager et al [14] used persuasive technology to raise

awareness of energy consumption of household devices.

Midden et al [15] suggested using persuasive technology

to encourage sustainable behavior. Midden et al [16]

summarized four ways in which human and technologyinteract with respect to sustainability. The four roles

technology can play are (1) as intermediary, (2) as

amplifier, (3) as determinant, and (4) as promoter of

environmentally significant behavior.

This study aims at helping designers find useful

design patterns and technologies for DfSB. Existing cases

of DfSB were collected to form a case library so that

experience can be extracted. Concepts of case based

reasoning (CBR) such as setting domain model, retrieve,

and reuse of cases are adopted to facilitate DfSB.

2. DESIGN FOR SUSTAINABLE BEHAVIOR

WITH CBR

This section discusses how to extract information of

past cases and find useful suggestions for designers. Inlight of the above literatures, design patterns and

technology used are found essential for leading to

behavior change. For example, DWI provides 11 target

behaviors and 101 related design patterns. Using the idea

of DWI, existing cases are analyzed and coded with a

domain model that consists of target behavior and designpatterns.

In addition to design patterns and target behavior,

authors suggest that domain model should include: (1)

technology used in DfSB products and (2) emotional or

Kansei descriptors that are used to describe the feelings

and affective influence of users (see Figure 1). The second

idea is from Kansei engineering approach that builds

relationship between design parameters and Kansei

descriptors so that design parameters can be properly

controlled to have a design reaching users emotional

expectation (Nagamachi [17]).

Target behaviors and users feelings represented byKansei descriptors could be seen as expected results of

DfSB while design patterns and technologies are means to

behavior change. Hence, a domain model is proposed to

describe past cases containing:

(1) target behavior that are adopted from DWI method,

(2) design patterns that are adopted for DWI method,

(3) Kansei descriptors to describe the feelings of users for

each case product, and

(4) technologies used in the cases.

Fig. 1: Scheme of case based design aid for DfSB

With the domain model, cases of products with DfSB

were written into a case library. To demonstrate the

approach, fifty household products with DfSB were

collected, analyzed and coded based on the domain model.The cases are collected from websites of large companies

(like Philips), platforms of green products, anddescriptions of intelligent house, and meet three

conditions: (1) leading to sustainable behavior, (2)

household use excluding personal mobile devices, and (3)

applying information and communication technologies

(ICT). Since there are only fifty cases, limited number of

design patterns and target behaviors out of DWI are found.

Table 1shows six target behaviors while Table2contains

fifty design patterns. Numbers of target behavior and

design patterns should increase as the number of collected

cases increases.

Table 3 shows examples of 20 Kansei descriptorsthat are collected from literature describing sustainable

lifestyle. Table 4 shows some examples of 23 ICTs found

in the cases. Two approaches that start from target

behavior and intended feelings to facilitate DfSB using the

case library are presented in the following two sections.

Table 1: Target behaviors for DfSB for household ICT

products

User-system interaction

S1User follows a process or path, doing things in a

sequence chosen by the designer

S2 User follows a process or path thats optimized forthose particular circumstances

S3Decision among alternatives: a users choice isguided

S4 Only certain users/groups of users can use something

S7Users only get functionality when environmental

criteria are satisfied

User-user interaction

U2Users (and groups of users) do interact with, and

affect each other while using a system

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Table 2: Examples of the fifty design patterns adopted

from DWI

index Design patterns

A3 Conveyor belts

A4 Feature deletion

A6 Material properties

A8 Pave the cowpaths

I8 Summary feedback

I9 Tailoring

I10 Tunneling & wizards

Table 3: Examples of Kansei descriptors

SustainableKansei descriptors

energy-saving

environmental-friendly

good looking

plain

simple

safe

harmonious

tranquil/peaceful

Table 4: Examples of ICT used in DfSB

index Technology application

a display

blighting/ to guide bylighting

c camera/ monitord audio

e voice record

falarm

clock/stopwatch/timer

u automation

v remote control

wsensor that detects

circumstance

3. DfSB STARTING WITH TARGET

BEHAVIOR

After the case library of products with DfSB is built,

cases with intended target behaviors could be retrieved. To

use this approach, premise is that designers know what

behavior DfSB intends to lead to. Once designer has anidea of intended behavior, cases with the specified target

behavior could be retrieved and therefore design patterns

and technologies adopted in the cases can be found. Since

multiple cases that have the same target behavior may beretrieved, number of times that design patterns and

technologies appear is used to reflect strength of

suggestion. Design patterns and technologies with more

times of appearance are considered highly related to the

target behavior.

Table 5 shows design patterns recommended forvarious target behaviors where design patterns on the left

are highly recommended because they appear more times

than others in the retrieved cases. Indices representingdesign patterns are shown in last section. In other words,

the number of appearance of the design patterns in

retrieved cases decreases from left to right. Similarly,

Table 6 shows technologies recommended for various

target behaviors where technologies on the left are

strongly recommended.

Designs could refer to these recommended design

patterns and technologies for conceptual design of DfSB.Combination of multiple design patterns and technologies

could be acquired from these tables. Since these

recommendations are based on past cases, users may be

more convinced as the number of cases increases.

Table 5: Recommended design patterns for various targetbehaviors

Target

behavior

(Strongly (weakly

Recomm) Recomm)

S1 A12, I6, M7, P8, ..C10, M14, S3

S2 I6, I9, A12, E3,. P10, M11, M14, S2, S5

S3 I6, I8, I9, A3, .., C6, C10, M1, S6

S4 A3, M14

S7 A12, I6, L1, ., P14, C6, C10

U2 I6, I8, A12, L1,... M3, M11, S2, S3

Table 6: Recommended technologies for various targetbehaviors

Target

behavior

(Strongly (weakly

Recomm) Recomm)

S1 a, b, o, p, f,j, ., s, w, g, k, v

S2 o, a, o, j, u, b, . k, c, e, l

S3 a, o, b, h, j, p, c.., m, q, w

S4 a, c, g

S7 U, v, t, b, f, j

U2 a, o, d, b, .... l, r, u, v

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4. DfSB STARTING WITH INTENDED FEELINGS

OF USERS

Designers conducting DfSB may start with intended

feelings that a new design would bring to users. Kansei

(emotional) descriptors were selected to describe feelings

of potential users with respect to each case. In aquestionnaire survey, consent/dissent of using Kansei

descriptors to describe feeling for each case is collected

from each respondent. More than 30 respondents were

asked whether they would use each of the twenty Kanseidescriptors for each case. For each case, we can collect 20

normalized scores (ranging from 0 to 1.0) with respect to

20 Kansei descriptors. If the score is 1.0, it means that all

respondents used the descriptor to describe the case.

With the survey results, correlation coefficients

between scores of Kansei descriptors and appearances ofdesign patterns and technologies are hence calculated.

Tables 7 shows design patterns with positive correlation

with Kansei descriptors. Table8 shows technologies withpositive correlation with Kansei descriptors. To achieve

intended Kansei descriptors in DfSB, design patterns and

technologies with highly positive correlations are

recommended. Contrarily, those negatively correlated

design patterns and technologies are not recommended.

Designers could certainly start with multiple Kansei

descriptors and thus find more suggestions using the

information in Tables7 and8.

Table 7: Examples of design patterns with

positive correlation with Kansei descriptors

Kansei

descriptors

Design patterns

Highly

positive corr

Design

patterns

Positive

corr

Energy saving I8, A11, I6, P2,P14

A9

Env.

protection

A11, P2, I6,

P14

A9, I8

Good

looking

I6, I8, P2, P14 C6, A11,

L1, L7,

L10, P12,

S2, S5, S6Plain A11, I6, I8, P2,

P14

A

9

Natural M7 A4, A9,

A11, E7, E9,

P9, P10, I5

Safe M11, M14 A8, I2, C9,

P13

.

Table 8: Examples of technologies with positive

correlation with Kansei descriptors

Technologies

(Highly

positive

corr)

Technologies

(Positive

Corr)

Kanseidescriptors

Energy

savingb j o f

Env

protectionb j o f

Good

lookingb j o

plain b j o f

.. .

relaxing s

leisure a p

friendly e

warm r u

simple f l j o

5. CONCLUSIONS

Two approaches to facilitate DfSB are proposed withconcept of case based reasoning. Cases of existing DfSB

are collected and expressed with a domain model that

includes target behavior, Kansei descriptor, design pattern

and technology used. In the first approach, relationship

between target behavior and design patterns andtechnologies used is established via statistical analysis

based on the fifty cases. Designers can start with target

sustainable behavior and find suggestion of design

patterns and technologies using the tables provided.

In the second approach, Kansei descriptors for

sustainable lifestyle are chosen to describe customerfeelings for each case so that relationships between Kansei

sustainable description and design patterns and

technologies used are established. For each case, measures

of multiple Kansei description from customer opinion are

collected via a questionnaire survey. Designers can start

with intended Kansei descriptors and find useful design

patterns and technologies based on the correlationanalysis.

Both approaches would provide recommended design

patterns and technologies that could be basis for

conceptual design of DfSB. Two approaches could be

adopted simultaneously, starting with both target

behaviors and Kansei descriptors and obtaining multiple

suggestions of design patterns and technologies using the

tables resulted from statistical analysis.

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REFERENCES

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Sustainable use: changing consumer behavior

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[2] Herring, H. and Roy, R (2007). Technologicalinnovation, energy efficient design and the rebound

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[12] Verbreek, P. and Slob, A. (2006) User behavior and

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