JIEM, 2012 – 5(1):229-258 – Online ISSN: 2013-0953 – P in ISSN: 2013-8423
h p://dx.doi.o g/10.3926/jiem.408
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Applying an empha ic design model o gain an unde s anding
o consume s’ cogni i e o ien a ions and de elop a p oduc
p o o ype
Ding-Bang Luh1, Chia-Hsiang Ma1, Ming-Hsuan Hsieh1, Cheng-Yong Huang2
1Na ional Cheng Kung Uni e si y, 2Kao Yuan Uni e si y (TAIWAN, ROC)
[email protected]. w; yu [email protected]. w; [email protected]; y[email p o ec ed]
Recei ed Oc obe 2011
Accep ed Feb ua y 2012
Abs ac :
Pu pose:
Conside a ion o consume opinion is a key success ac o when i
comes o de eloping a new p oduc . Howe e , businesses may lack sui able
me hods o his, and designe s may lack p ac ical aining, wi h bo h si ua ions
meaning ha i ms a e unable o p ecisely adop consume opinions. Mo eo e ,
consume cogni ions o a p oduc a e widely ega ded as changeable and abs ac .
I is wo h s udying how o de e mine consume s’ opinions and ans o m hem
in o e e ences o p o o ype de elopmen . The pu pose o his s udy is hus o
c ea e an Empa hic Design Model which would be able o de e mine consume
cogni i e o ien a ion.
Design/me hodology/app oach:
This model includes obse ing ela ed
phenomena, ladde ing he cogni ion, connec ing he elemen s o he Associa ions
Ma ix, p oducing he hie a chy o he ollowing ou i ems, a ibu es, unc ional
consequences, psychosocial consequences and alues, and hen p oducing a
p o o ype o help designe s and consume s each a consensus on he cogni i e
s uc u e o p oduc s.
Findings:
As demons a ed in a case s udy o he design o an “elec onic ou
guide”, he au ho s de eloped a p o o ype ha can help a guide o pe o m hei
job on a g oup package ou . Consequen ly, he Empa hic Design Model can be
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ope a ed and pu in o p ac ice. By Mind Mapping, he p o o ype can be hen
imi a ed and ein en ed by designe s as needed.
O iginali y/ alue:
This model ocuses on he ea ly phase o he design p ocess,
p o iding he designing indus y wi h a echnique o o ecas consume s’ po en ial
needs and de elop a p o o ype e ec i ely.
Keywo ds:
empa hic design, consume demand, cogni i e s uc u e, p oduc p o o ypes,
demand o ecas ing
1 In oduc ion
The key o deciding i a p oduc is success ul in he ma ke place is whe he o no i
mee s consume demands and p e e ences, a he han whe he he e is a
b eak h ough in echnology (Bax e , 1995). Fo mode n businesses, he eal
compe i i e ad an age lies in p o iding wha consume s a e looking o a he han
wha businesses a e good a p o iding. The explosion o p oduc a ie y may
gene a e in o ma ion o e load and lead o cus ome s who a e highly he e ogeneous
in hei willingness and abili y o in e ac wi h businesses (Miceli, Rico a &
Cos abile, 2007). Klee , T ijp and Luning (2005) men ioned ha in he ini ial
p ocess o new p oduc de elopmen , lis ening o consume s is undoub edly a key
o success. Howe e , his s ep has long been igno ed o wo ked ques ionably o
mos businesses. Ulwick (2002) no ed he o en-hea d a gumen ha asking
consume s wha hey need is useless, because hey do no know wha hey need.
Howe e , al hough hey may no be able o a icula e wha hey need,
unde s anding how consume needs a e shaped and in luenced is s ill e y
impo an in ensu ing ha po en ially used p oduc concep s a e no igno ed.
A consume has eelings owa d a p oduc because he p oduc has meaning o he
consume , and his meaning is gene a ed by cogni ion: he e alua ion as o
whe he o no a p oduc will be bough (Gu man, 1982; Zanoli & Naspe i, 2002).
The e o e, designe s no only design a p oduc , bu also he ela ed consume
cogni ion. When i comes o p oduc cogni ion, he designe ’s in e p e a ions do no
necessa ily ma ch he consume s’ desi es, and many p oduc s which a e success ul
om a designe ’s pe spec i e ha e no sold well in he ma ke place, meaning ha
he e was a gap be ween designe s’ and consume s’ cogni ion models (Chuang,
Chang & Hsu, 2001). In o he wo ds, he meaning o a p oduc o consume s is no
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necessa ily he same as i s meaning o designe s. In an e a o p oduc
di e si ica ion, designe s should hus no analyze consume s’ demands and
p e e ences solely based on hei own p o essional and in e nalized hough
p ocesses.
The p oduc -cen ic app oach aces ce ain challenges o success ha can be
o e come by he consume -cen ic app oach (Jain & Singh, 2002). A ulle
unde s anding o consume cogni ion and a ca e ul obse a ion o consume
beha io a e necessa y o good design, and in his ega d empa hic design is a
consume -cen ic design p ocess ha emphasizes he obse a ion o he a ious
phenomena ha eme ge when consume s use p oduc s o se ices. I can be used
o apply he esul s gained om an analysis o he emo ional aspec s o using a
p oduc o se ice o new p oduc de elopmen . In con as o adi ional esea ch
ha ocuses on well-unde s ood p oduc s o se ices, empa hic design concen a es
on obse ing consume s’ daily li es, and hus is able o ga he he ollowing ha d-
o- ind in o ma ion (Leona d & Raypo , 1997): igge s o use, in e ac ions wi h
he use ’s en i onmen , use cus omiza ion, in angible a ibu es o he p oduc and
una icula ed use needs. Lo house, Bham a and Bu ow (2005) applied empa hic
design o one ex ile manu ac u e , Tencel L d. When his i m called o employee
eedback on i s cu en p oduc lines, and hus ob ained g ea e unde s anding o
co ec and inco ec ea u es, he manage s immedia ely decided o imp o e he
ela ed wo k a eas. Koup ie & Visse (2009) p oposed a amewo k ha could be
applied in design p ac ice, wi h empa hic design appea ing in ou phases:
disco e y, imme sion, connec ion and de achmen . Disco e y means en e ing he
consume ’s wo ld, imme sion means adop ing he consume ’s poin o e e ence,
connec ion means achie ing emo ional esonance and finding meaning, while
de achmen means designing om a use ’s pe spec i e. Howe e , al hough i is
widely belie ed ha consume s’ needs a e impo an and he e a e a ious
echniques o su ey hese, bo h a undamen al unde s anding o empa hic design
and a amewo k o how o apply i o p oduc p o o ypes a e s ill lacking in he
design indus y. This s udy hus a emp s o es ablish an Empa hic Design Model
(EDM) o ga he , selec , analyze and make use o eedback om consume s,
o ming a design guideline in he ini ial s age o p oduc de elopmen .
2 Backg ound
The majo ask o EDM is o unde s and consume s’ cogni i e o ien a ions and gain
insigh in o he cogni i e s uc u e o consume s’ imp essions o he p oduc .
Use ul in o ma ion ex ac ed om consume s’ needs is hen used o de elop a
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p o o ype. The e o e, he ollowing e iew o he li e a u e is aimed a explo ing
ele an s udies on consume cogni ion, p oduc p o o ypes and empa hic design
as a basis o de eloping an EDM.
2.1 Consume cogni ion
A ms ong and Ko le (2000) pos ula ed ha cogni ion is he p ocess o consume s’
selec ing, o ganizing and in e p e ing o ex e nal in o ma ion and ans o ming i
in o in e nal in o ma ion. I s main ocus is he ype o in o ma ion and he me hod
o p ocessing i . He e, in o ma ion means some hing s o ed in human memo ies,
while p ocessing me hods e e s o acqui ing, s o ing and using ha in o ma ion. In
Schi man and Kanuk (2000) de ini ion, he p ocess o cogni ion includes s imuli,
senso y ecep o s, a en ion, in e p e a ion, esponse and ecep ion. In he ea ly
phases o he cogni i e p ocess, s imuli, senso y ecep o s and a en ion a e all
ela ed o sensa ion, wi h he senso y sys em ecei ing ex e nal s imuli and
eac ing immedia ely. In he la e phases, in e p e a ion, esponse and ecep ion,
he senso y sys em explains sensa ions and con e s hem o pe cep ions.
Sensa ion is a simple psychological p ocess based on physiology which can be
explo ed h ough obse a ion. In con as , pe cep ion is a complica ed
psychological p ocess which can be explo ed h ough in-dep h in e iews.
Sensa ion and pe cep ion a e a se ies o psychological ac i i ies. When consume s
decide o buy a p oduc , he in insic messages o he p oduc can be sensed
h ough he senso y sys em, in eg a ing ex insic messages o o m pe cep ion.
Pe cep ion hen in luences consume a i udes and beha io s. In insic messages
include he unc ions, ma e ials and he appea ance o p oduc s, while ex insic
ones include he p ices, b ands and gua an ees.
2.2 P oduc p o o ypes
In o de o mee a ious pu poses, p o o ypes come in many o ms. Jo dan (1998)
poin ed ou ha in a cycle o design and e alua ion he e a e a numbe o dis inc
p o o yping op ions. Examples o hese op ions a e e bal o w i en desc ip ions o
p oduc appea ance and unc ions, physical ep esen a ions on pape o sc een,
p oduc models, sc een-based in e ac i e p o o ypes and ully wo king objec s. In
e ms o he p incipal s ages o a design p ocess, S an on and Young (1999)
di ided p o o ypes in o concep , design, analy ical p o o ype, s uc u al p o o ype
and ope a ional p o o ype. Ullman (2003) desc ibed ou di e en kinds o
p o o ypes based on hei unc ions and hei p ocess o p oduc de elopmen . In
he ini ial s age, a p oo -o -concep p o o ype le s a i m know wha kind o p oduc
i will design. Second, he p oo -o -p oduc p o o ype embodies he design and
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cla i ies p oduc ion easibili y. Thi d, he p oo -o -p ocess p o o ype can ep esen
he me hods and ma e ials associa ed wi h a success ul design. Las ly, he p oo -
o -p oduc ion p o o ype p o es ha he whole manu ac u ing p ocess is e ec i e.
In his s udy, p o o ype is de ined as a p oo -o -concep p o o ype, e e ing o
nuclea design concep s and ea u es which can hen be ex ended. The main aims
wi h his kind o p o o ype a e o cla i y p oduc unc ions and con igu a ions, as
well as i s p ac ical uses, he eby helping o indica e a co ec di ec ion o p oduc
de elopmen . A good p o o ype is designed wi hin clea limi a ions, helping
de elopmen pe sonnel o mo e easily unde s and he desi ed ea u es o he
p oduc and hus engage in meaning ul g oup discussions, leading o he
de elopmen o imp o ed p oduc s and sho ening he ime o ma ke .
2.3 Empha ic design
Leona d and Raypo (1997) p oposed he empa hic design p ocess includes i e
s eps.
S ep 1: Obse a ion. Who should be obse ed, who should do he
obse ing, wha he obse e should be wa ching?
S ep 2: Cap u ing da a. Use pho og aphy o ideog aphy as ools o s o e
and con ey da a ha migh o he wise be omi ed. Empa hic design s esses
accompanying inqui y o obse e consume s, asking open-ended ques ions
like “Why a e you doing ha ?” The use ul in o ma ion ga he ed a e
sc eening will be much less han he o iginal in o ma ion.
S ep 3: Re lec ion and analysis. A e ga he ing in o ma ion in a ious
o ms, eam membe s should hink wha hey ha e obse ed, and e iew all
he isual da a wi h each o he .
S ep 4: B ains o ming o solu ions. Inspi a ion is he mos aluable pa in
any inno a ion p ocess. In he p ocess o empa hic design, inspi a ion is
speci ically used by ans o ming obse a ions in o g aphics, and i uses
isual ep esen a ions o p esen possible solu ions.
S ep 5: De eloping p o o ypes o possible solu ions. P o o ypes speci ically
cla i y he appea ance and ea u es o p oduc s o se ices as well as how
hey a e used. This helps he discussion wi h po en ial consume s.
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Empa hic design unde s ands consume s mainly h ough obse a ion and inqui y;
howe e , his me hod has he ollowing weaknesses (Deszca, Mun o & Noo i, 1999;
E ans & Bu ns, 2007):
A conside able amoun o he esea che s’ ime is was ed. This is because
hey mus cla i y who should be obse ed and wha beha io should be
wa ched, and en e he ac ual obse a ion en i onmen o con inuously
eco d he daily beha io o consume s o ind any hidden demands.
Rela i e o adi ional esea ch, empa hic design hus undoub edly is a
longe and mo e ime-consuming p ocess.
I has less his o y o implemen a ion han adi ional esea ch.
Theo e ically, empa hic design is easible, bu i aces some challenges
when being pu in o p ac ice. Fo example, i is no an easy ask o obse e
consume s who do no wan o be moni o ed, and e en hose ha doe may
show beha io s di e en om hei usual ones when hey a e awa e o
being wa ched, and his leads o inaccu a e da a. Ano he challenge is ha
esea che s need o wo k ha d o o e come hei own p econcep ions and
be ca e ul no o in e ene in consume s’ ac i i ies.
Resea che s need o ha e a speci ic se o capabili ies, such as being adep
a collabo a i e and in e disciplina y in e ac ions. A he same ime, hey
need o ha e a good unde s anding o isual, spoken, and nume ical da a.
Mos impo an o all, hey ha e o possess he skills equi ed o analyze
and p esen inno a i e p oduc p o o ypes.
2.4 Resea ch ques ions
Empa hic design pu s emphasis on pa icipa ing in empa hic expe iences and in-
dep h in e iews o unco e consume s’ una icula ed issues and needs; howe e ,
he ollowing issues a ise when i is being implemen ed:
Since empa hic design’s i e s eps ha e no been de eloped in o a speci ic
and ope able p ocedu e, i akes mo e ime o conduc a s udy and
esea che s need o ha e conside able expe ience and expe ise.
Empa hic design does no de ine he esul s om each s ep and does no
indica e how he esul s should be p esen ed when mo ed on o he nex
s ep. This p esen s a numbe o p oblems, such as making he goal o ask
unclea and making i ha d o connec be ween each s ep.
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Resea che s should no limi hemsel es o consume s’ cu en cogni i e
s uc u es, and ins ead hey need o success ully d aw consume s’ a en ion
o hose ha seem unimpo an and apply e ec i e ools o ans o m he
da a on consume demands ha hey ob ain in o use ul design in o ma ion.
3 EDM cons uc ion
Figu e 1. Empa hic design model
I is di icul o unde s and consume cogni i e o ien a ions h ough adi ional
ma ke su eys, and he bes way o do so is h ough in e ac ion. The e o e,
e ec i ely handling obse a ions and in e iews collec ed in he ield is necessa y
o unde s and consume cogni ion, as hey can help explain he meaning behind
he ele an phenomena. To mee his equi emen , empa hic design is a new
ma ke esea ch echnique ha aims o mee he needs o consume s h ough
analysis o de ailed obse a ions. The whole p ocess includes obse a ion,
cap u ing da a, e lec ion and analysis, and b ains o ming and de eloping
p o o ypes o possible solu ions (Leona d & Raypo , 1997). Howe e , due o
limi a ions o ime, budge , ools and manpowe , in mos design indus ies
empa hic design has a ely ca ied ou . This s udy u ilizes Pa icipan Obse a ion
and a Means-End Chain o cap u ing da a, an Associa ions Ma ix o analysis, a
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Hie a chical Value Map o p oduce solu ions, and Mind Mapping o de elop
p o o ypes o o m an EDM (see Figu e 1) ha can su ey consume opinions and
deal wi h di e en consume needs unde di e en ci cums ances.
3.1 Me hod o unde s anding Consume Cogni i e O ien a ions
In he ollowing subsec ions he au ho s e iew Pa icipan Obse a ion, an
e ec i e me hod o obse ing ac i i ies when esea che s ha e di ec con ac wi h
consume s. Second, Ladde ing, a communica ion echnique ha can c ea e good
in e ac ion wi h consume s and help be e app ecia e consume s’ expe iences and
cogni ions, is in oduced. Thi d, an Associa ions Ma ix, used o quan i y he
associa ions be ween he elemen s which sco ed by esponden s, is b ie ly
desc ibed. The esul s o his quan i ica ion a e he basis o d awing he
Hie a chical Value Map (HVM).
S ep 1: Pa icipan Obse a ion
Kelley, Li man and Pe e s (2001), Gene al Manage o he in e na ionally
enowned design i m IDEO, once no ed ha p oduc inno a ion begins wi h an
eye, and pe sonal expe ience always wins o e ic ion and imagina ion. A IDEO,
obse ing consume s is a necessa y s ep in e e y design p ojec ini ia ion.
Psychologis s, sociologis s and designe s obse e he in e ac ion be ween
consume s, p oduc s and en i onmen . They e alua e he la en needs o
consume s in ega d o new p oduc s, in o de o p o ide e e y possible solu ion.
Pa icipan Obse a ion means esea che s ac ually become pa o he obse ed
g oup and obse e i om wi hin by pa aking in ac i i ies wi h subjec s.
Pa icipan Obse a ion is used because consump ion phenomena and p oduc
de ini ions a y acco ding o ime and place, and a e hus dynamic in na u e. This
me hod can p o ide di ec and de ailed in o ma ion wi h ega d o how phenomena
occu , and allow a mo e ho ough unde s anding o hem. Pedgley (2007)
demons a ed ha Pa icipan Obse a ion is a sui able me hod o collec ing and
eco ding da a in design ac i i ies. In addi ion, Je a d, Ba nes and Reid (2008)
pos ula ed ha in new p oduc de elopmen ma ke needs can be de e mined
h ough Pa icipan Obse a ion, including empa hic in ol emen , eco ding and
analyzing consume s’ expe iences.
S ep 2: Ladde ing
The Means-End Chain en ails he p ocess o o ming links among p oduc
a ibu es, consump ion consequences and pe sonal alues. I some a ibu e can
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be linked o a ela i ely abs ac alue, ha a ibu e is impo an (Fe an &
G une , 2007; Gu man, 1982; Klenosky, 2002). Olson and Reynolds (1983) hen
so ed his chain in o six sub-le els, o ming he Means-End Chain Model (see
Figu e 2). The Means-End Chain has since been success ully used in new p oduc
de elopmen and s a egic ma ke ing managemen (Gu man & Miaoulis, 2003;
Pie e s, Baumga ne & Allen, 1995).
Figu e 2. Compa ison be ween Means-End Chain Model and his s udy
Ladde ing is simply a echnique o collec ing Means-End Chains om esponden s.
I uses one-on-one in-dep h in e iews o ob ain he consume s’ psychological
pe spec i es, and is done s ep by s ep ia di ec elici a ion (Chiu, 2005; Ho s ede,
Audenae , S eenkamp & Wedel, 1998). A ypical ques ion o Ladde ing is “Why is
his (based on he subjec ’s p e ious answe ) impo an o you?” This inqui y
p ocess keeps being epea ed un il answe s such as “I don’ know” o “This is he
way i is” show up (Reynolds & Gu man, 1988). Reynolds and Olson (2001) ci ed
nume ous ac ual examples o Ladde ing, and om hese examples we can see ha
mos subjec s i s answe ed hei ques ions wi h he mo e angible a ibu es. I
he in e iewe keeps asking ques ions, mo e abs ac consequences will s a o
show up, and inally he mos abs ac pe sonal alues will appea . A ca e ully
de ailed p ocess om he lowes le el (a ibu es) o he highes le el ( alues) can
explain he mo i es o consume s and how p oduc in o ma ion is being
in e p e ed. In addi ion, he easons why a ce ain a ibu e o consequence a e
impo an can be clea ly p io i ized.
The au ho s had ied o use he Means-End Chains (Gu man, 1982) on he
p oduc . The esul s a e oo ske chy, and hey can no ully p esen he opinions o
consume s. When using he classi ica ion which was p oposed by Olson and
Reynolds (1983). Mos o he consume s can no desc ibe he sub-le els o physical
cha ac e is ics, abs ac cha ac e is ics, ins umen al-ex e nal and e minal-in e nal
alues in de ail, bu hey can easily desc ibe unc ional and psychosocial
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asked i any alues ha had no been men ioned could be linked o ce ain
consequences. Each mee ing las ed o 1.5 hou s and was bo h audio- and ideo-
eco ded. A e he mee ing, he wo ds collec ed we e hen examined ia Con en
Analysis and classi ied in o a ibu es, unc ional consequences, psychosocial
consequences and alues le els, be o e all-inclusi e and mu ually exclusi e
p inciples we e used o u he simpli y and code he wo ds. The i s g oup
collec ed 20 elemen s, he second g oup 25, wi h nine newly added, he hi d
g oup 27, wi h h ee newly added and he ou h 23, wi h ze o newly added,
meaning ha he numbe o g oups was su icien and he elemen s we e
sa u a ed. The coding is shown in Figu e 4.
Reliabili y Analysis was used o coded in o ma ion. Th ee code s (A, B and C) who
we e amilia wi h Means-End Chains and Con en Analysis, coded and classi ied he
elemen s. Mu ual ag eemen among he h ee code s was used as he c i e ia o
in e -judge eliabili y. Wimme & Dominick (2006) sugges ed a eliabili y o mo e
han 0.9. Reliabili y can be ob ained h ough he ollowing o mula:
Reliabili y=n×(a e age mu ual ag eemen )/{1+[(n-1)×a e age mu ual ag eemen ]}
(1)
whe e n ep esen s he numbe o code s; mu ual ag eemen =(2×M)/(N1+N2),
whe e M is he numbe o ques ions wi h he same esponses; N1 is he numbe o
ques ions coded by he i s code , and N2 is he numbe o ques ions coded by he
second code . The o e all eliabili y was 0.959, which eaches a sa is ac o y le el.
4.3 Associa ing he Ma ix
The elemen s ca ego ized in Figu e 4 o m he AC( ), C( )C(p) and C(p)V
Associa ions Ma ix. In he beginning, he a ibu es we e in columns and he
unc ional consequences we e in ows, o ming an AC( ) ma ix. The esponden s
indica ed he pe cei ed associa ions wi h ega d o each unc ional consequence in
each a ibu e. The e alua ion used a i e-poin scale. Ve y s ongly associa ed was
5; s ong associa ed, 4; a e age, 3; sligh ly associa ed, 2; and no associa ed, 1.
Simila ly, he C( )C(p) ma ix lis ed unc ional consequences and psychosocial
consequences, while in he C(p)V ma ix lis ed he psychosocial consequences and
alues. The ques ionnai e (including AC( ), C( )C(p) and C(p)V) was gi en o 107
esponden s. The inal sample was a popula ion o 91, gi ing a esponse a e o
85%. Table 1 e eals he demog aphic cha ac e is ics o he esponden s.
An agg ega e Associa ions Ma ix was hen p oduced based on he da a p o ided
by he 91 esponden s, as shown in Tables 2, 3 and 4.
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Demog aphic cha ac e is ics
N
Pe cen age
Gende
Male
Female
52
39
57.1%
42.9%
Age
18-25
26-35
36-45
46-55
56-65
O e 65
23
29
16
12
9
2
25.3%
31.9%
17.6%
13.2%
9.9%
2.2%
Educa ion
Elemen a y school/Junio high school
Senio high school/Voca ional school
Junio college
Uni e si y
Mas e
PhD
3
14
12
44
15
3
3.3%
15.4%
13.2%
48.4%
16.5%
3.3%
P o ession
Manage ial posi ion
Middle managemen
En ep eneu
Specialis
Employee
S uden
Re i ed
Unemployed
3
6
7
10
28
24
7
6
3.3%
6.6%
7.7%
11.0%
30.8%
26.4%
7.7%
6.6%
Expe ience wi h GPT
No expe ience
1-3 imes
4-6 imes
7-9 imes
Mo e han 10 imes
To al
3
25
36
21
6
91
3.3%
27.5%
39.6%
23.1%
6.6%
100%
Table 1. P o ile o esponden s (N=91)
The o mula o calcula ing he associa ion weigh o each cell in he agg ega e
AC( ) Associa ions Ma ix is as ollows:
(2)
whe e i is he numbe o a ibu es, anging om 1 o 13; j he numbe o
unc ional consequences, anging om 1 o 9; N he numbe o esponden s, which
alue is 91; he a e age associa ion a ing be ween he a ibu e i and he
consequence j, anging om 1 o 5.
Th ough he Associa ions Ma ix, all he esponden s’ pe cei ed associa ions could
be quan i ied, and he S ep 4 HVM was d awn based on his. In addi ion, Tables 2,
3 and 4 sum up all he elemen s’ “mean a ings” o u he calcula e he
in ensi y o each linkage, which is discussed in mo e de ail in he nex sec ion.
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(3)
Whe e i is he numbe o a ibu es, anging om 1 o 13; j he numbe o
unc ional consequences, anging om 1 o 9; n he o al numbe o unc ional
consequences, wi h he alue o 9; is he mean associa ion a ing o
a ibu e i, anging om 1 o 5.
Elemen s
C( )1
C( )2
C( )3
C( )4
C( )5
C( )6
C( )7
C( )8
C( )9
i
AX
(To)
A1
3.09
4.53
2.37
3.23
1.70
3.41
2.96
2.25
1.88
2.82
A2
3.69
1.73
3.57
2.93
3.19
3.19
3.16
4.13
3.33
3.21
A3
2.49
1.80
1.36
4.15
1.31
2.10
3.98
1.46
1.62
2.25
A4
2.90
3.05
1.46
4.02
1.40
3.32
4.25
1.43
2.93
2.75
A5
2.89
1.37
2.60
1.78
2.90
4.62
1.33
3.25
1.44
2.46
A6
1.55
1.47
3.95
1.37
2.40
4.13
1.44
3.30
1.73
2.37
A7
3.00
2.80
2.57
3.51
1.31
2.14
3.52
1.30
4.61
2.75
A8
2.89
2.34
3.81
2.56
3.70
3.46
2.85
4.32
2.54
3.16
A9
3.51
1.52
4.31
1.76
1.88
3.26
2.78
2.81
2.81
2.74
A10
2.95
4.10
2.65
2.25
2.76
3.47
2.90
3.89
2.60
3.06
A11
2.49
1.45
1.47
2.05
4.49
3.32
2.58
4.38
1.35
2.62
A12
3.22
1.89
2.00
3.57
2.79
3.19
3.38
2.99
4.21
3.03
A13
3.43
2.98
4.42
3.30
1.38
2.90
3.27
2.37
2.77
2.98
i
CX )(
(F om)
2.93
2.39
2.81
2.81
2.40
3.27
2.95
2.91
2.60
Table 2. Associa ions Ma ix summa y o he elec onic ou guide design s udy
Elemen s
C(p)1
C(p)2
C(p)3
C(p)4
C(p)5
C(p)6
i
CX )(
(To)
C( )1
3.43
3.54
4.49
3.29
4.34
2.30
3.57
C( )2
3.53
4.14
2.93
2.48
1.81
4.69
3.26
C( )3
2.16
3.85
1.54
4.44
3.14
3.38
3.09
C( )4
4.48
3.44
3.29
2.33
3.48
2.07
3.18
C( )5
1.40
1.69
2.47
4.36
2.95
1.97
2.47
C( )6
3.42
3.57
2.78
3.47
4.38
1.64
3.21
C( )7
4.16
3.09
2.21
2.86
3.47
2.14
2.99
C( )8
3.41
3.55
1.95
4.73
3.99
1.47
3.18
C( )9
3.04
4.57
3.51
1.75
3.46
2.17
3.08
i
pCX )(
(F om)
3.23
3.49
2.80
3.30
3.45
2.43
Table 3. Associa ions Ma ix summa y o he elec onic ou guide design s udy
Elemen s
V1
V2
V3
V4
i
pCX )(
(To)
C(p)1
2.21
3.49
4.36
4.64
3.68
C(p)2
3.44
4.05
4.57
3.48
3.89
C(p)3
3.75
3.57
4.22
4.14
3.92
C(p)4
4.60
1.96
3.18
3.13
3.22
C(p)5
3.66
4.54
3.51
3.45
3.79
C(p)6
1.46
1.65
4.08
3.32
2.63
i
VX
(F om)
3.19
3.21
3.99
3.69
Table 4. Associa ions Ma ix summa y o he elec onic ou guide design s udy
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4.4 Hie achy o he AC( )C(p)V
The A-C( )-C(p)-V Associa ions Ma ix can be shown in he o m o a ee diag am,
which is he HVM. Howe e , i would be oo complica ed and he impo an linkage
could no be shown i all he elemen s’ associa ions we e d awn in o he HVM. To
main ain he balance be ween de ail and in e p e abili y, he au ho s e e ed o
Nielsen’s (1993) i e-poin scale. Speci ically, i he mean is mo e han 3.60, he
sco e will be posi i e, meaning signi ican ly associa ed. Figu e 5 shows he links
wi h a mean abo e 3.60. To make he discussion and eading easie , lines o
di e en hickness show associa ions o di e en s eng h be ween he elemen s.
In his case, o a sco e 3.60-3.80 he line is 0.75p ; o 3.81-4.00, 1.25p ; o
4.01-4.20, 1.75p; o 4.21-4.40, 2.25p ; o 4.41-4.60, 2.75p , and o any sco e
mo e han 4.61, 3.25p . G aphs can help designe s cla i y hei hinking and
simpli y communica ion wi h o he s.
In he HVM shown in Figu e 5, 53 comple e Means-End Chains can be seen. Each
chain’s in ensi y can be ob ained by e e ing o Tables 2,3 and 4 and summing up
he “F om and To” alues o e e y elemen in each chain. Fo example, o he
chain A1→C( )2→C(p)6→V3, he “F om” alue o A1 is 0 and i s “To” alue is
2.82. The “F om” alue o C( )2 is 2.39 and i s “To” alue is 3.26. The “F om”
alue o C(p)6 is 2.43 and i s “To” alue is 2.63. The “F om” alue o V3 is 3.99
and i s “To” alue is 0. The e o e, he s eng h o his chain is:
(0+2.82) + (2.39+3.26) + (2.43+2.63) + (3.99+0) = 17.52
Table 5 shows he op i e chains wi h he highes in ensi y ou o he o al o 53.
The mos impo an chain is A8→C( )3→C(p)2→V3, wi h an in ensi y o 20.43,
which can be called a c i ical pa h. This demons a es ha he esponden s
ega ded he “elec onic map” a ibu e as impo an , and hoped ha ia his
a ibu e hey could ge “in o ma ion ele an o his jou ney”, ha e “beau i ul
memo ies” and ul ima ely eel “happiness”. To de ine he ela ed goals, designe s
can simpli y he HVM in Figu e 5 i needed. Figu e 6 shows ha he op i e chains
should be aken in o conside a ion i s .
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Figu e 5. Hie a chical Value Map o elec onic ou guide design
Chain
“F om” and “To” alues o elemen s
S eng h
A8→C( )3→C(p)2→V3
(0+3.16)+(2.81+3.09)+(3.49+3.89)+(3.99+0)
20.43
A2→C( )1→C(p)3→V3
(0+3.21)+(2.93+3.57)+(2.80+3.92)+(3.99+0)
20.42
A13→C( )3→C(p)2→V3
(0+2.98)+(2.81+3.09)+(3.49+3.89)+(3.99+0)
20.25
A2→C( )1→C(p)5→V2
(0+3.21)+(2.93+3.57)+(3.45+3.79)+(3.21+0)
20.16
A2→C( )1→C(p)5→V1
(0+3.21)+(2.93+3.57)+(3.45+3.79)+(3.19+0)
20.14
Table 5. Top i e chains wi h he highes s eng h
Figu e 6. S eamlined Hie a chical Value Map
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4.5 De eloping he p o o ype
Consume s usually ha e igid, p e-exis ing hough s abou he ea u es o e e y
p oduc and se ice, and i is di icul o change his men ali y. Because consume s
lack knowledge and demand expe iences om p oduc s in a new ield, he e is li le
help de i ed om hem ega ding sugges ions o he a ibu e le els o inno a i e
p oduc s. Mos ela ed s udies ocus on he ea u es and unc ionali ies o p oduc s
o se ices and he ins an sa is ac ion b ough o consume s, bu hey neglec he
emo ional bene i s behind he p oduc s o se ices. Consequen ly, hey ail o ully
unde s and consume s’ in angible hough s and eelings and he o ces ha d i e
hem. The e o e, when designe s conduc an inno a i e p oduc design, mo e ocus
should be pu on “consequences” and “ alues” le els.
A e se ing up he goals by means o a s eamlined HVM (see Figu e 6), Mind
Mapping can be used o de elop a p o o ype. When d awing Mind Maps, he e a e a
ew essen ial echniques (Gelb, 1998; Men o, Ma inelli & Jones, 1999; Reed,
2005):
Show he opic in wo ds o pic u es in he cen e o he pape , and hen
d aw unks
On he b anches ex ended om he unk he e should be a g aph o a e m
All o he b anches should o m a s uc u e o nodes wi h di e en
hicknesses in he unk and he b anch
When no hing comes o mind, a ew blank lines can be added o he key
e ms o s imula e he use o ill hem in la e , i possible
The e a e wo ways o hink: B ain Flow is hinking om one key e m o
ano he one, while B ain Bloom is hinking om one key e m o many
o he s
Symbols, colo s, o pic u es can be placed on o key poin s o s imula e he
b ain o c ea e o he combina ions
The Basic O de ing Ideas p inciple should be used o ca ego ize he i ems
ha appea . Mind Mapping uses hinking, selec ing and unde s anding
ele an in o ma ion o help analyze decisions h ough he p ocess o
w i ing down key e ms and d awing associa ions.
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Unde aking e ec i e Basic O de ing Ideas is a key s ep in d awing Mind Maps,
allowing o he ideas o be o ganized (Buzan, 2002). Fo ins ance, i “elec onic
map” o “audio guide” (a he a ibu es le el) a e w i en on he unk igh a e
he s a o he “elec onic ou guide design” b ains o ming session, he
subsequen i ems on he b anches will be limi ed, hus ceasing he low o he
hough p ocess. We can use Basic O de ing Ideas as he sou ces o associa ions.
This me hod sepa a es he associa ion o key e ms in o a ew ca ego ies o le els,
le ing he b ain hink in a na u al way. Once he main ideas a e exp essed, he
sub-ideas a e easily p esen ed. The elemen s a he “consequences” and “ alues”
le els in Figu e 6, i.e. in o ma ion, memo y, in e pe sonal ela ions, a mosphe e,
happiness, com o and sa e y, a e used as he bases o associa ion wi h he unk
o he Mind Map, o ex end possible p oduc s o se ices a he b anch le el, and
hen he unc ions o e ec s p o ided a he sub-b anch le el.
Figu e 7. Mind Map o elec onic ou guide design s udy
Designe s hen pe o med c ea i e hinking acco ding o hei own expe iences and
knowledge, wi h he assis ance o key e m ca ego iza ion in o de o cla i y he
p o o ype o he elec onic ou guide, and he esul s a e shown in Figu e 7.
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P oduc s o se ices ha a e ex ended om in o ma ion, a mosphe e and sa e y
can be p o ided be ween he guide and he membe s o inc ease he dep h and
sa e y o he jou ney, while p oduc s and se ices ha a e ex ended om memo y,
in e pe sonal ela ions, happiness and com o can help inc ease sa is ac ion wi h
he jou ney and in e pe sonal in e ac ion.
5 Discussion and limi a ions
When de eloping a new sys em ha is bo h la ge and complex, analys s and
de elope s end o collec a huge amoun o gene al consume da a, hinking ha
in his way consume demand can be known. Howe e , such da a can only e eal
supe icial in o ma ion and has a ious o he limi s, ul ima ely indica ing only he
s a ing poin s o hose ac o s ha a e mos impo an . The e o e, when doing
su eys o consume s, mo e a en ion should be paid o he na u e o hei needs.
Many echniques ha e eme ged o elici hese, bu hese mos ly deal wi h decisions
wi h ega d o he p oduc ’s unc ions and in e ace ea u es. Unde s anding
consume s’ cogni i e s uc u es and ela ed ac o s and d awing ou he concep o
a p oduc ’s p o o ype based on hese has ecei ed ela i ely li le a en ion. This
s udy hus combined Pa icipan Obse a ion, Means-End Chain and Mind Mapping
o ob ain pe inen in o ma ion on consume s and de elop he p o o ype o an
elec onic ou guide sys em. The con ibu ion o his s udy has been o
demons a e ha using EDM o elici consume s’ needs and de elop p o o ypes o
p oduc s is an e ec i e app oach. Ano he con ibu ion is ha he au ho s ha e
al e ed he a ibu e–consequence– alue model o a phenomenon–a ibu e–
unc ional consequence–psychosocial consequences– alue one, which can help
esea che s be e unde s and consume s’ beha io al in en ions when using ce ain
p oduc s.
EDM o e s an elec onic ou guide wi h a numbe o p oduc o se ice unc ions
ha a e mo e meaning ul in e ms o in o ma ion, memo ies, in e pe sonal
ela ions, a mosphe e, happiness, com o and sa e y. The elec onic ou guide
makes he GPT sa e as well as mo e con enien and enjoyable. In addi ion, his
sys em in eg a es ele an in o ma ion and unc ions ha can sa e on manpowe ,
ime and social cos s. Howe e we canno e alua e he amoun o cos sa ings
in ol ed. This s udy a ached g ea impo ance o applying Pa icipan
Obse a ions o explo ing phenomena and using he Means-End Chain o
unde s and esponden s’ cogni i e o ien a ions, as well as using Mind Mapping o
de elop a p oduc p o o ype. Also, clea ly de ining each s ep and he p ocess o
in o ma ion ansmission can help sol e con en ional p oblems, such as unde ined
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asks and he di icul y in linking each s ep, which a e common in empa hic design
ope a ions.
Al hough EDM can e ec i ely imp o e he de elopmen o an elec onic ou guide,
he e a e some limi s o his s udy. Fi s , each esponden has a di e en le el o
in ol emen in GPT, which may a ec hei i e-poin scale e alua ions. The bes
es ees would be people who had jus come back om a GPT o o en join one.
Second, he au ho s conside ed only he connec ions be ween neighbo ing
elemen s, like AC( ), C( )C(p) and C(p)V. Inc easing C( )C( ), C(p)C(p) and VV may
educe he limi s, bu he ex a Associa ions Ma ix would sha ply inc ease he
bu den o he esponden s and he bene i s could be ques ionable. Thi d, o help
each eade unde s and he meaning o each b anch, he Mind Map in his case was
exp essed in key e ms. When using Mind Maps o p esen he p o o ype,
indi iduals o g oups could use ske ches o communica e hei design ideas.
6 Conclusions
In he pas , in o de o deal wi h mos cus ome demands,, businesses only needed
o manu ac u e p oduc s in la ge quan i ies and main ain su icien in en o y o
ensu e he e was no sho age o supply. Howe e , o oday’s businesses, highe
lexibili y is needed in bo h design and p oduc ion p ocesses in o de o cope wi h
dynamic ma ke eac ions. The EDM buil up in his s udy has se e al ad an ages
when dealing wi h his si ua ion: Fi s , i is based on ca e ul obse a ions: Human
beha io s ha e o be ollowed consis en ly and obse ed p ecisely o acqui e
consume phenomena which a e closely ela ed o he opic. Second, EDM is
di e en om in o ma ion ga he ed by a Means-End Chain. I equi es ha he
esponden s exp ess he associa ions among elemen s a each le el. In addi ion,
EDM is di e en om su ey ques ionnai es which use s a is ical echniques o
explo e hese associa ions, as i collec s he associa ions di ec ly indica ed by
consume s. Thi d, s eamlined HVM ocuses on he cogni i e s uc u e o he
consume ma ke , making he key links mo e ob ious and hus use ul o designe s
who a e se ing goals and making decisions. Fou h, Mind Mapping can e ec i ely
so he uno ganized hough s ha appea in he p ocess o c ea i e hinking, and
c ea e new, comp ehensi e associa ions o aise he inno a i e alue o he
p o o ype. Las ly, h ough EDM, he cogni i e communica ion be ween designe s
and consume s can be imp o ed, and he p ecision and c ea i i y o p oblem-
sol ing can be aised so ha consume s’ needs can be mo e pe ec ly me . To sum
up, he consume demands ha a e conside ed in he design p ocess should be
based mo e on wha has ac ually been obse ed, a he han on designe s’
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imagina ion. The A-C( )-C(p)-V connec ion ne wo k behind each phenomenon can
be clea ly iden i ied s ep by s ep h ough he elici a ion o phenomena ca ds and
ladde ing in e iews. The HVM, a e being o ganized, ocuses on he cogni i e
s uc u e o he consume s, and i can be used in g oup b ains o ming. A
s eamlined HVM can be applied o se up design goals, acili a e he p og ess o
adian hinking in mind mapping, and u he c ea e p o o ypes.
In he case s udy o he design o an “elec onic ou guide”, he au ho s ound ha
he EDM was easy o handle and e y use ul, and his may lead o widesp ead
u u e use o his model. Mo eo e , applying he EDM p ac i ione s and esea che s
gain he ollowing ad an ages. (i) Each s ep o EDM can be execu ed easily and is
closely connec ed o he nex s ep, and his can sho en he design ime. (ii) They
can accomplish classi ica ion o consume demands and unde s and he
ela ionships be ween each demand e ec i ely. (iii) They can se up he design
goals based on he s a is ics, and p oceed o de elop p oduc p o o ypes. The
me hods o EDM emphasize isualizing in o ma ion, and i u u e s udies a ge
di e en p oduc s o di e en consume s, he senses o ouch, smell, hea ing o
as e may also be aken in o conside a ion and used o mo e p ecisely p edic and
explain consume needs. To summa ize, EDM is composed o a se ies o sys ema ic
me hods o unco e consume demands, hen ans o m he ga he ed da a in o
design in o ma ion o de elop a p oduc o se ice, in his case an elec onic ou
guide. Based on he in o ma ion collec ed, designe s can p ecisely iden i y and
o ecas consume s’ unde lying demands.
Re e ences
Ap, J., & Wong, K. K. F. (2001). Case s udy on ou guiding: P o essionalism, issues
and p oblems. Tou ism Managemen , 22(5), 551-563.
h p://dx.doi.o g/10.1016/S0261-5177(01)00013-9
A ms ong, G., & Ko le , P. (2000). Ma ke ing: An in oduc ion (5 h Ed.). New
Je sey: P en ice Hall.
Bax e , M. (1995). P oduc design: A p ac ical guide o sys ema ic me hods o new
p oduc de elopmen . London: Chapman & Hall.
Bo schen, G., & Heme sbe ge , A. (1998). Diagnosing means-end s uc u es o
de e mine he deg ee o po en ial ma ke ing p og am s anda diza ion. Jou nal o
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