Key factors affecting house purchase decision of customers in vietnam

4 5 6 7External Design Construction Quality Construction Duration Type of House Private Living Space 8 9 10 11 12 13 14 Quantity of Bedroom Quantity of Bathroom Living room size Storey o

ACKNOWLEGEMENTS

Firstofall,Iwouldliketoexpressmydeepappreciationtomysupervisor,Dr.DinhT h a i Hoangw h o instructedandhelpedmeenthusiasticallyduringperiodo f thethesis

IalsowouldliketothankyouallmycolleaguesandfriendsofHoaBinhCorporationa n d Sacomrealfortheirvaluablecontributionstogivecommentsandsuggestiontorevisethequestionnairesurvey

Iamgratefultothesupervisoryboardforprovidingmewiththeiravailableadvicesa n d patientsupportswhenIneed

Iwillneverforgetthefriendlypostgraduatestudentsforhelpingmeduringstudyinga n d doingthesis

Themostspecialthanksgotomyparents,mybrothersandsisterswhoalwayscreatet h e mostconvenientconditionsformeaswellassupportmealltime

ThemainpurposeofthestudyistoinvestigatetheeffectingofkeyfactorsonhousingpurchasedecisionofcustomersinVietnam.First,amodelwhichisproposedbasedo n analyzingofpreviousliterature.Thenthemodelistestedonapilottestwhichisconductedofasmallrealestateprofessionalgroupandanothergroupof15respondents,andona largersurveyof263samples.Thestudyfindsouta strongpositiverelationshipbetweentoptwofactors,including“livingspace”,“distance”a n d customers’housingpurchasedecision.Thethreeweakerpositiverelationshipfactorsare“feature”,“finance”and“environment”tohousingdecisionmakers.Itisa l s o foundthatthereisnodifferenceindecisionmakingofcustomersaccordingtodiff

age,maritalstatus,monthlyincomeandeducationlevel

Keyworks:realestate,purchasefactors,Vietnam

ACKNOWLEGEMENTS ii

ABSTRACT iii

LISTOFTABLES vii

LISTOFFIGURES viii

ABBREVATIONS viii

CHAPTER1 INTRODUCTION 1

1.1 BACKGROUND 1

1.2 RESEARCHPROBLEMS &RESEARCHQUESTIONS 1

1.3 RESEARCHPURPOSE 3

1.4 SCOPEOFTHERESEARCH 3

1.5 RESEARCHSTRUCTURES 3

CHAPTER2 LITERATUREREVIEW 4

2.1 LITERATUREREVIEW 4

2.1.1 Feature 4

2.1.2 Livingspace 4

2.1.3 Finance 5

2.1.4 Distance 5

2.1.5 Environment 5

2.1.6 Purchasedecision 6

2.1.7 Demography 6

2.2 CONCEPTUALFRAMEWORK 7

CHAPTER3 RESEARCHMETHODOLOGY 8

3.1 RESEARCHPROCESS 8

3.2 SAMPLESIZE 11

3.3 MEASUREMENTSCALE 11

3.3.1 Measurementscale 11

3.3.2 Pilottest 11

3.4 MAINSURVEY 15

3.5 DATAANALYSISMETHOD 15

3.5.1 Reliabilitymeasure 15

3.5.2 ValiditymeasurebyEFA(Exploratory FactorAnalysis) 16

3.5.3 Multipleregressionanalysis 16

CHAPTER4 DATAANALYSIS&RESULTS 18

4.1 PREPARATIONDATA 18

4.1.1 Editing 18

4.1.2 Coding 18

4.2 DESCRIPTIVEDATA 21

4.3 ASSESSMENTMEASUREMENTSCALE 23

4.3.1 Cronbach’sAlpha 23

4.3.2 ExploratoryFactorAnalysis(EFA) 26

4.3.2.1 Assessmentofdata 26

4.3.2.2 Definingnumberofextractedfactors 27

4.4 HYPOTHESESTESTINGBYMULTIPLE REGRESSION 30

4.4.1 CheckingassumptionofMultipleRegression 30

4.4.1.1 Samplesize 30

4.4.1.2 Assessmentmulticollinearityofindependentvariables 30

4.4.1.3 Normality,linearity,homoscedasticity&outliers 30

4.4.2 Evaluatingthemodel 31

4.4.3 Evaluatingtheindependentofvariables 31

4.4.4 Checkinghypothesesofmodel 32

4.4.5 Analysiseffect of controlvariablesby MultipleRegression 34

CHAPTER5 CONCLUSIONSANDIMPLICATIONS 35

5.1 RESEARCHOVERVIEW 35

5.2 RESEACHFINDINGS 35

5.3 MANAGERIALIMPLICATIONS 36

5.4 RESEARCHLIMITATIONS&DIRECTIONSFORFUTURERESEARCH 37

REFERENCES 38

Appendix1:Thefirstdraftofthequestionnaire 42 Appendix2:TheEnglishquestionnaire 45 Appendix3:TheVietnamesequestionnaire 49

Table3.1:Mainfactorsaffectingcustomers’housingpurchasedecision 13

Table4.1:Codebookofquestionnaireitems 18

Table4.2:Characteristicsofrespondents 22

Table4.3:Cronbach’sAlphatestresults 25

Table4.4:EFAresults 28

Table4.5:Correlationsamongvariables 29

Table4.6:CoefficienttableofMLR 32

Table4.7:Hypothesesresults 33

Table4.8:Descriptivestatistics 54

Table4.9:Cronbach’sAlphawithfullitemsforeachconstructs 54

Table4.10:KMOandBartlett’stest 56

Table4.11:Totalvarianceexplained 56

Table4.12:Correlationamongvariables(Partialonly) 57

Table4.13:FactorMatrix 59

Table4.14:FactorCorrelationMatrix 60

Table4.15:Modelsummary 60

Table4.16:Anova 60

Table4.17:Casewisediagnostics 60

Table4.18:Residualsstatistics 61

Table4.19:CofficientsofMLRincludingSex_Render 63

Table4.20:CofficientsofMLRincludingMarital_Render 64

Table4.21:CofficientsofMLRincludingEducation_Render 64

Table4.22:CofficientsofMLRincludingAge_Render 64

Table4.23:CofficientsofMLRincludingCareer_Render 65

Table4.24:CofficientsofMLRincludingIncome_Render 65

LISTOFFIGURES

Figure2.1:Conceptualframework 7

Figure3.1:Researchprocess 10

Figure4.1:Screeplot 58

Figure4.2:Regressionstandardizedresidual 62

Figure4.3:NormalP-Pplot 62

Figure4.4:Scatterplot 63

ABBREVATIONS

EFA :ExploratoryFactorAnalysis

GSO :VietnamGovernmentStatisticsOfficeH

C M C :HoChiMinhCity

Mil :Million

MLR :MultipleLinearRegressionU

E H :UniversityofEconomic

Asu n i v e r s a l p o p u l a t i o n levelsc o n t i n u e t o rise,

theh o u s i n g shortageinmanyd e v e l o p i n g countrieshasreachedcriticallevels(Morel,2001,p.1119).Realestateisoneofthemostimportantthingstocitizens,so“thehousepurchasedecisionoft h e m canchangetheirlife”(Wells,1993).Thehousepurchasedecisionsaredifferentfromotherb usi ness decisions d u e to“thein na

te, d u r a b l e an d l on

g-te rm c h a r a c t e r i s t i c s ofrealestag-te”.Itisahighlydifferentiag-tedproductwith“eachspecificsiteuniqueandfixedinlocation”(Kinnard,1968)

InVietnam,itisknownasthethirdlargestpopulationinSouthEastAsiaandrankedt h e 14thlargest

intheworldintermsoftotalpopulation.Itspopulationestimatedof8 9 millionin2010(GSO,2011).TheannualaveragegrowthpopulationofVietnamf r o m 2000to2010wasapproximately1.03millionpeopleperyearor1.2%annualgrowth.Particularly,oneofthetopeconomiccentersofVietnamisHoChiMinhCity

wh ich hasaround7.2millionpeopleasinApril2009,butitsactualpopulationislikelytobesignificantlyhigherbecauseofunrecordedmigrationfromruralareas

TherealestatemarketinVietnamhassignificantlychangedduringfromthe1990st o nowanditmightbeseenasthreetimesfeveranddecliningpricesinthelast20years.U p t

o t h e e n d of2 0 1 2 , t h e larger e a l e s t a t e o u t s t a n d i n g l o a n s a n d a bignumbero f inventoriescreatedase ri ous crisis.However,accordingtothe Dep ut y M in i

“Therea r e t w o mainf i e l d s o f customerr e s e a r c h a r e h o w c u s t o m e r s go

a b o u t makingd e c i s i o n s a n d h o w d e c i s i o n s s h o u l d b e made.Ina d d i t i o n , “

c r e a t i n g t r u e valueforcustomerandcustomernotionfocusedapproach”isconfirmed(Edwards

&F a s o l o , 2 0 0 1 ) Iti s f o u n d t h a t “customerd e c i s i o n m a k i n g i s o n e o f t h emostimportanta reas o f customerb e h a v i o r and it r e q u i r e s g a t h e r i n g al o t of reg

ardinginformation”(Bettmanetal.,1998&Simonsonetal.,2001).

Therehavebeenmanypublishedacademic researchaboutcustomerhousepurchasew i t h varietyo f b o t h developedanddeveloping countries.H o w e v e r, “thenational a n d culturalcharacteristicsplayaverysignificantroleinhousepurchasedecision,thatmeanf i n d i n g whichisap pl ie d i n sp eci fi c contextma ynotext en d t o anotherc o n te x t ” (Opoku&Abdul-Muhmin,2010)

Ther e a l e s t a t e inV i e t n a m h a s gots p e c i f i c c h a r a c t e r i s t i c s t o w h

i c h c o n n e c t e d customerdemandsclosely.Inrecentyears,researchers,domesticandforeigncompaniesattractedtorealestatefieldinVietnamwithanumberofresearchworks.However,thereh a s b e e n n o t enoughr e s e a r c h i n t o t h e w a y customersmakingd e c i si o n tobuyrealestateaswellaswhichmajorfactorshavegotrelationshipwithcustomerdecision

Consequently,inthetermofrealestatepurchasedecisionofcustomers,theresearchquestionsofthethesisareraisedastwofollowingquestions:

 WhatarethekeyfactorsaffectingthehousepurchasedecisionofcustomersinV ietnam?

t h e s e factorsinfluencetheirdecisionofbuyinghouseinVietnam

1.4 SCOPEOFTHERESEARCH

TheresearchisconductedinHoChiMinhCitywiththerespondentswhoarethepostgraduatesandstudentsofUEHwithvariouscareers,aswellascustomersofasmallbook-

coffee.ThetimeframeofresearchlastsfromthemiddleofSeptembertot h e endofOctoberin2012

1.5 RESEARCHSTRUCTURES

Theresearchisdividedintofivechapters.Thefirstchapterintroducesaboutbackgroun

purpose,scopeofr e s e a r c h andresearchstructures.Thesecondchaptercoversliteraturereviewofthepreviousresearchandshowshypotheses,aswellastheconceptualframeworkoftheresearch.Thethirdchapterpresentstheresearchprocess,samplingsize,measurement s c a l e , mainsurvey,a n d d a t a a n a l y s i s method.T h e f o u r t h c h a p

t e r concentrateso n p r e p a r a t i o n d a t a , descriptived a t a , assessmentmeasuremen

ts c a l e a n d h y p o t h e s e s testing.F i n a l l y , t h e f i f t h c h a p t e r p o i n t s o u

t r e s e a r c h overview,r e s e a r c h findings,managerialimplications, r esea rc h limitationsa n d directions forf u t u r e research

H2.Therei s a positivei m p a c t o f livings p a c e o n c u s t o m e r s ’ h o u s e purc

hased e c i s i o n

2.1.3 Finance

Thirdly,“financial”statusismuchsignificanttocustomerhouse

choice(HinkleandCombs,1987,p.375;Kaynak&Stevenson,ascitedinSenguletal.,2

010,p.220).T h e“financial”elementofrealestaterequiresaccesstoarelativelargeamountof“capital”andaswellas“borrowingcosts”(Xiao&Tan,2007,p.865).Inaddition,“ f i n a n c i a l ” statusbaseson combinationof“houseprice”,“mortgageloans

( 2 0 0 3 , p 3 0 6 ) group“interestrat e”, “maximummortgage”,“maximummonthlypay

ment”,a n d “lengtho f timepayment”into“financial”factor.Consequently,

&Kiel,ascitedinOpoku&ce n t ” a n d “locationt o sc ho ol” (Opoku&

Abdul-Muhmin,2 0 1 0 ) M o r e o v e r , “distancet o c e n t r a l b u s i n e s s ” , “distancet o s c h o

o l ” a n d “distancet o work”a r e c o n s i d e r e d (Adaireta l , 1 9 9 6 , p 2 3 ).Inadditi on,“accesstorecreationalfacilities”and“accesstomainroads”arep ro p o sed (Imane

tal.,2012,p.30).Hence,

H4.Thereisapositiveimpactofdistanceoncustomers’housepurchasedecision.

2.1.5 Environment

Fifthly,“environment”i n c l u d i n g “ n e i g h b o r h o o d ” , “areaa t t r a c t i v e n e

s s ” , “view”,“noisefromarounddistricts”and“generalsecurity”isstatedasoneofthedeterminantsofahousehold’s residential d e c i s i o n (Adair,1996, p 23) Itisconfirmedthat“environment”hasabiginfluenttohousingbuyer(Tajima,ascitedi n Opo

ku& Abdul-Muhmin,2010, p 224) anditisagreedbyMoreletal.

2.1.7 Demography

“Demographic”characteristicsofcustomersareinternalfactorsrelatedtodecisionmaking(Mateja&Irena,2009).“Demographic”characteristicsconsistoftheindividualsi n termo f “gender,age,e d u c a t i o n a l s t a t u s , maritals t a t u s , c a r e e r , t h e q u a

n t i t y offamilymembersandchildren,aswellastheresidenceproperty”.“Demographic”ch ar acte ri st ics consist o f age(Y alc h & Spangenberg,1 9 9 0 ) , e d u c a t i o n (

Gattikeretal.,2000),incomelevel(Dawsonetal.,1990),gender(Zhange t al.,2007)whic

harefactorsinfluencedonthe“purchaseintention”ofcustomer.P art icu l arl y , “gender”h a s significantlyi n f l u e n c e o n t h e f i n a n c i a l f e a t u r e o f theh o u s e (Se

ngule t a l ,2 0 1 0 , p 2 1 4 ) Itis a l s o c o n f i r m e d t h a t t he r e i s a s i g n i f i c a n t

differenceinrealestatebuyingdecisionsto“age”and“gender”,andnotto“edu cat i

al.,2011).Correspondingly,int h i s study,“gender”and“age”characteristicsareconsi

deredascontrolvariablessothatinvestigatewhethereffectofthosedemographyvariablesonhousingpurchased e c i s i o n makingofcustomersornot

Aconceptualframeworkwhichisproposedtoshowtherelationshipbetweenfiv

ei n d e p e n d e n t v a r i a b l e s c o n s i s t i n g o f “ f e a t u r e ” , “livings p a c e ” , “financials t a t u s ” , “ d i s t a n c e ” and“environment”andonedependentvariable,namely

“housepurchased e c i s i o n ” Ita l s o s h o w s t h e e f f e c t i n g o f d e m o g r a p h y i n c

l u d i n g “gender”,“age”,“maritals t a t u s ” , “income”and“ e d u c a t i o n ” ascontrol variableso nt h e dependent variable.Theconceptualframeworkisshownasthemodel(seeFigure2.1)

Step5 :E d i t , c o d e a n d a d j u s t missingda t a b e f o r e t e s t i n g re li ab le a n d validity

o f data

Inor de rt o p r e p a r e t h e d a t a t oa n a l y s is , d a t a weree d i t e d , c o d e d a n d adjustedf or missingdata.Next,reliabilityofmeasuring

a r regression.AllstepswereillustratedbythefollowingFigure3.1

Design

SamplingDesign

InstrumentDevelopment

Pilottesting

DataCollection&Preparation

Figure3.1:Researchp rocess

DataAnalysis&Interpretation

Deduction-Hypothesessubstantiated?

-Researchquestions answered?

ReportWriting

ReportPresentation

3.2 SAMPLESIZE

Thereliableandvalidityofvariablesweretestedby usingCronbach’sAlphaandEFA,afterthatthemultipleregressionwasappliedtotest modelandhypotheses.Fi r st ofall,thesamplesizewasrequiredtohaveenoughquantityfortheanalysis

50+(8xm)=50+(80x5)=90samples

Wherem:isthenumberofindependentfactorsofthemodel

Consequently,theminimumsamplesizeshouldbe170.Basedontheactualc o l l e c t i o

n data,thequantityofavailablerespondentsfromthequestionnairesurveyestimated230,sothatsamplesmettherequirementsabove

3.3.1 Measurementscale

Inordertooperateconcepts,itwasnecessarytomeasuretheminsomemanners,sodiffere

nt variableswererequiredtochooseanappropriatescale.Theindependent variableswereappliedintervalscalewithfive-

pointofLikertscaleconsistingoft o t a l l y unimportant(1),unimportant(2),neutral(3),important(4),veryimportant( 5 ) ; b e s i d e , t h e d e p e n d e n t variablew a s a

p p l i e d t h e samemeasurec o n s i s t i n g o f stronglydisagree(1),disagree(2),neutral(3),agree(4)andstronglyagree(5)

3.3.2 Pilottest

Inordertotestlogisticsofthequestionnairespriorcollectiondataonlargecover,apilo ttestwascarriedoutwitha smallgroupconsisting oftworealestate

w o u l d b e d e l e t e d o r wh ich partswouldbeadded.TheresultswerepresentedinAppendix01.

Foritemsofthe“housefeature”factor,theitem“typeoffinishing”and“qualityoffinishing”shouldbedeletedbecausetheircontentwasinsidethecontentof“constructionquality”

Whilea l l itemso f “privatel i v i n g s i z e ” f a c t o r w e r e agreed,theitem“tax”o f

“Finance”factorshouldbechangedinto“theregistrationfee”

For“distance”f a c t o r s , t h e “houseo n a mainb u s r o u t e ” i t e m s h o u l d b e d e l e t

e d becausethisitemwasnotpaidattentionbycustomers.The“distancefromthehouset o shoppingcentre”itemwasalsoproposedtodeletebecauseitwastoospecificandr e l a t e d tofemaleonly.Inaddition,thegrouprecommendedthatcustomershadgott e n d e n c y t o ignoret h e “locationa w a y fromi n d u s t r i a l a r e a s ” items o t h i s items h o u l d beremoved

For“environment”factor,its“theattractivenessofthearea”itemhadgotthesamemeaningof“view”item,so“theattractivenessofthearea”shouldbedeleted

Thelast“decision”factor, itshouldchange“Iwillwanttobuyanewhouse”into“Iwillmakemyefforttobuyanewhouse”

Finally,afteradjustingthefirstquestionnaire ta ble, asmallsamplesizeoffifteenconvenientc o l l e a g u e s w a s d e l i v e r e d t h e q u e s t i o n n a i r e s t o recognizew h e

t h e r anyparts ofitsuncleartounderstandor

misunderstand.Howeverallofthemunderstoodmeaningofquestionnaires quite well

a n d knewt h e waytoanswer, sothe

questionnairewa s t h e la s t v e r s i o n to ca r r y outi n t he massivea r e as Aftert h a t , a mainsurveywasconducted.

Muhmin(2010),Ratchatakulpat(2009)

An important person

purchaseaffecting

0 1 2 toattheendofOctober,2012

Therewere263hand-deliveredquestionnaires,only239respondentsgavefeedbackimmediately,butquantityofavailablerespondentswas230

Also,thecorrecteditem-totalcorrelationvaluesshouldbeatleast.3toensureeacho fitemswasmeasuringthesamefromthescaleasawhole(Pallant,2011)

3.5.2 ValiditymeasurebyEFA(ExploratoryFactorAnalysis)

Ino r d e r t o evaluatet h e validitya n d t h e c o r r e l a t i o n amongv a r i a b l e s t o i d e

n t i f y u n d e r l y i n g factorsordefinenumberofextractedfactors,EFAwasappliedwiththeo b li q u e approachusingthePromaxmethod.However,somerequirementsofEFAsho ul d besatisfied(Pallant,2011):

- Theminimumofsamplesizeshouldbeatleast100andrateofobservationsperitems

o f modelss h o u l d b e fivec a s e s f o r eacho f t h e items,s o t h a t meantt h e minimumrequiredsamplesizeshouldbeatleast5m=5x34=170cases(wherem:quantityo fitemsfromt h e c o n c e p t u a l model).T h e a c t u a l samplesizew a s 2 3 0 , biggerthan170soitmettherequirement

ng conditionsshouldbes a t i s f i e d :

- Theminimumsamplesizebasedontheformula:

n> 50+8m= 50+8x5=

90samples,wherem:numberofindependentvariablesi n theconceptualmodel

o=aconstant,thevalueofYwhenallXvaluesarezero

1=theslopeoftheregressionsurface(therepresentstheregressionc o e f f i c i e n t associatedwitheachXi)

=anerrorterm,normallydistributedaboutameanof0

Varia- ble name Fea01 Fea02

n g a l m o s t choosingnumber1or3or4.Thelastavailablenumbersofcaseswas230,andeachofallcaseswasmarkedareferencenumberonittofindeasily.Othersdidnothaveanyc a s e s ofmissingdataforcontendofINDEPENDENTVARIABLEsanddependentvariable

4.1.2 Coding

Answerswereassignednumbersofsymbolssothattheresponsesweregroupedintoa limitednumberofcategories(seeTable4.1)

Table4.1:Codebookofquestionnaireitems

4 5 6 7

External Design Construction Quality Construction Duration Type of House

Private Living Space 8

9 10 11 12 13 14

Quantity of Bedroom Quantity of Bathroom Living room size Storey of House House Price Maximum mortgage Maximum monthly repaymentInterest rate Income

Payment duration The registration fee Width of adjacent street

Distance to work Distance to market Distance to school Distance to recreation centre

Distance to the central

Liv02 Liv03 Liv04 Liv05 Fin01 Fin02Fin03

Finance

15

16 17 18 19

Fin04 Fin05 Fin06 Fin07Dis01

Distance 20

21 22 23

Dis02 Dis03 Dis04Dis05

24

business district Access to the main street

Neighbour’s condition General security View

Noise Pollution Nearby Traffic

Plan to buy a new house

Making effort to buy a new house

An important person to make decision to buy a new house

1 = “less than 35”; 0 = “above35”

Creating dummy variable 1 = “Single”; 0 = “Married” Creating dummy variable

38

0=“morethan14mil.”

1=“notyetgraduateduniversity”;0=“graduateduniversity”

1=“staff”;0=“managementboard”

4.2 DESCRIPTIVEDATA

AccordingtoTable4.2,therewere230availablerespondents,

themalewastwo-t h i r d s o f themalewastwo-t o themalewastwo-t a l o f c a s e s a n d a l m o s themalewastwo-t r e s p o n d e n themalewastwo-t s w e r e singlewithemalewastwo-thp e r c

e n t o f 8 3 percent Also,61.3percentrespondentsgraduateduniversityand31.7percentpostgraduates studyingmasterprograms.Theiragesrangefrom18yearoldsto35y e a r o l ds w i t h 9 9 1 pe r c e n t o f t o t a lc a se s Almosta l l o f themwereo f f i c e r swiththeiragesatleast18yearsoldandlessthan36yearsold.Besides,themaincareerofrespondentswasofficerswith87.8percentpertotalofcases,theirincomewaslessthan15millionpermonthwith89.6percentrate,whilethegroupofmanagerso r ownersatleast15millionpermonthwith3.9percentrate

Also,thesinglehousewaschosenmostwith73.6percentrate,thesecondchoiceoft y p e ofhousewasapartmentwith21.6percentrate.Thehousepricewhichwaslessthan20mil./

o f l e s s than1 0 0 s q u a r e meterswasc h o s e n mostwith8 4 3 p er c e n t rate

Characteristics Frequency % Cumulative%

4.3.1 Cronbach’sAlpha

RefertotheCaseprocessingsummaryofallvariablesoffiveconcepts,thenumbersamplesofeachconceptswasvalidwith230availablecases

BasedontheRel ia bi li ty StatisticsTa bl e 4.3and Table4.9,allCronbach’s Alphavaluesofallconceptswereabove.7afterdeletingitemsthatthe“Correcteditem-

valueincreasedfrom.748to.830

concept,the“Correcteditem-Totalcorrelation”valueof“L i v 0 4 _ L iv i n g rooms i z e ” itemw a s l o w with 3 7 1 , o f

“Liv05_Storeyo f h o u s e ” i t e m was.012.Allotheritemsensuredthecontentof“livingspace”,sothosetwoitemsshouldbedeletedandtheCronbach’sAlphavalueof“privatelivingspace”i n c r e a s e d from.619to.739,thisvaluewasnothigh,butitcouldbeacceptable

For“environment”concept,the“Correcteditem-Totalcorrelation”valueof“Env03_View”itemand“Env06_Nearbytraffic”whichwere

.284and.272.Thosevaluesw e r e lesst h a n 3a n d t h e “ E n v 0 6 _ N e a r b y T r a f f i

c ” a n d “ V i e w ” c o u l d b e

explainedb y c h a r a c t e r i s t i c s o f “Noise”,“Pollution”,“NeighbourC o n d i t i o n ” , a n

environment,sotheywereremoved.TheCronbach’sAlphavalueo f “environment”conceptwasincreasedfrom.767to.846afterdeletingtwoitemsabove

Finally,“decision”c o n c e p t h a d gota l l t h e “ C o r r e c t e d

item-T o t a l c o r r e l a t i o n ” valueofallitemswereabove.4,anditsCronbach’sAlphavaluewas.816,thosevalueswerequitegood

Table4.3:Cronbach’sAlphatestresults

Variables

ScaleM eanifIte mDelet ed

ScaleVar ianceifIte mDelete d

Corrected Item- TotalC orr elation

Cronbach's AlphaifItem Deleted

4.3.2.1 AssessmentofdataS

amplesize

Samplesizeandthestrengthoftherelationshipamongthevariableswererequiredt o testsuitabilityofdata(seeTable4.12).Thesamplesizewas230availablecasesandshowndetailinchapter3thatthisrequirementwasmettheminimumrequiredsamplesize

Fromthepatternmatrix,lowcommunalityvaluesshouldberemovedtoincreasethet o t a l explainedvariance.Removingsomelowcommunalityvariablesandrepeatingt h e sameanalysis,theresultofEFAwaspresentedintheTable4.4.FromthepartialC o rr e l a t i o n MatrixTable4.5,someofthe correlationcoefficientsbetween variablesea c h otherswereabove.3.TheKMOvaluewas 7 7 9 , exceeding valueo f 6andBartlett’s testo f Sphericityvaluewas.000,thatmeanslessthanthestatisticallysignificantatp<.05(seeTable4 1 0 ) Therefore,theconditionaboutthefactorabilityofthecorrelationmatrixwasap p r o p

ri a t ed withassumptionsofEFA

4.3.2.2 Definingnumberofextractedfactors

From

TotalvarianceexplainedvalueinTable4.11,therewerefirstsixcomponentsw i t h eigenvaluesabove1including followingvalues:6 335;3 099; 2.860;2 259; 1 6 4 7

a n d 1 1 6 6 Andt h o s e c o m p o n e n t s e x p l a i n e d t o t a l 6 4 2 6 % o f t h e variance,e

x c e e d i n g than50%explainedtotal,sothisvaluewasappropriate

Ina d d i t i o n , t h e S c r e e P l o t Figure4 1 s h o w e d t h a t t h e r e w a s h a r dbreakfromcomponents2and3,andbothofcomponents1and2xplained36.64%thanfourremainingcomponents.However,therewasslightbreakaftercomponent6,sothenumberofextractedfactorswassix

FromtheFactorMatrixTable4.13,thefirstcomponent

presentedmostoftheitemsloadedonitwhilethesecondthreecomponentsloadedquitethesame,andthefinaltwo componentsloadedtheleast

InthePatternMatrixTable4.4,allitemsloadingonsixcomponentswereabove.4.B e s i d

e s , t h e r e w e r e fiveitemsl o a d i n g o n c o m p o n e n t 1 , f o u r itemsl o a d i n goncomponent2,fiveitemsloadingoncomponent3,

threeitemsloadingoncomponent4 , fouritemsloadingoncomponent5,andfouritemsloadingoncomponent6

Table4.4:EFAresults

FromtheCorrelationTable4.5,theinformationaboutsampleswasenoughwithNe q u

a l 230availablecases.Also,thedirectionoftherelationshipbetweenthevariables,thecorrelationsvalueswerepositive,thatmeansonevariablewaschanged,theotherswouldchangefollowthesamedirection.AllthePearsonC o r r e l a t i o n valueswerelessthan.7comparedwiththepermittedrangefrom-

1to1 , andshouldlessthan.7(Pallant,2011).Moreover,thesignificantlevelalmostlesst h a

n 05,exceptthesignificantofcorrelationbetweenFinancevariableandFeaturevariable,alongwithFinancevariableandLivSpacevariable,soallvariableshadgota quitestrongcorrelationandsupportedtoexplaintogether

230 230 230 230 230 230.118 1 092 205** 175** 189**.075 165 002 008 004

230 230 230 230 230 230.303** 092 1 287** 307** 399**.000 165 000 000 000

230 230 230 230 230 230.216** 205** 287** 1 411** 574**.001 002 000 000 000

230 230 230 230 230 230.144* 175** 307** 411** 1 214**.029 008 000 000 001

230 230 230 230 230 230.156* 189** 399** 574** 214** 1.018 004 000 000 001

230 230 230 230 230 230

4.4.1.3 Normality,linearity,homoscedasticity&outliers

IntheNormalProbabilityPlot(P-P)oftheRegressionStandardisedResidual,mosto f scoresconcentratedinthecentreandalongthe0point(seeTable4.3).Also,theScatterplotFigure4.4showedthatalmostthepresenceofoutlierswerefrom-2to

+2,therewereonlyfewofoutlinelessthan-3.0,sothosevaluewereacceptable.Ino rd er todiscoverwhichitemshadgottheirvaluesexceedpermittedrange(-3;3),the CasewiseDiagnosticsTable4.17wascheckedandrecognizedthatthecase105w i t h a s t a n d a r d r e s i d u a l valueo f minus3 2 3 a n d t h e c a s e 2 0 5 w i t h a s t a n d a r d residualvalueofminus3 3 7, tho

se valueslessthanminus3 andf e l l outsidethenormallydistributedsample.However,thisvaluewaslessthan1percentofcasestof a l l o u t s i d e t h e

r a n g e o f b e l o w minus3.0orabove3.0,sot h e Normalityco n d i t i o n wasappropriated

Outliersw e r e c h e c k e d t h r o u g h t h e M a h a l D i s t a n c e valueo f R e s i d u a

l S t a t i s t i c s Table4.18.This researchhadgotfiveindependentvariables,sothecriticalvalue