Backgroundto theresearchandresearchproblem
Vietnam’se c o n o m y hasbeengrowingrapidlysincethelate1990swhensignificanteconomi creformedandthecountry’sOpenDoorPolicy wereimplemented.Vietnam’sgrowthrateisona v e r a g e 6.4%i n thelastdecade (TheWo rl d Bank,2015) Followingthesechanges,Vietnam’sresid entialhousing industryalsoexperiencedfastdevelopmentandexpansion.However,Vietnampopula tionwasnearly91 millionpeoplein
2014andthepopulationincreasedby1.06percentannually(TheWorldBank,2015).Additionally,the urbanizationrateinVietnamisalsoincreasingat3.3percentannuallyand33.1percentofthepopulationi slivinginurbanareas(ThanhNienNews,2014).InmostofthebigcitiesinVietnam,particularlyinHo
C h i MinhCity,thebusinesscenterofVietnam,hasaround7.9millionpeoplein2014andtheurba nizationtoitssuburbsisquitefast.Thus,theincreasinginpopulationandrapidurbanizationi n thedevel opingcountrieslikeVietnamcreatethehouseorapartmentshortageatcriticallevels(Morel,Mesbah,O ggero&Walker,2001).Moreover,anincreasinghouseorapartmentdemandoftensurplusthepaceofits supply(Zang,ascitedinPhan,2012).Asaresult,thedemandforah o u s e oranapartmentistheurgentd emandforeachindividualandhouseholds.
TherealestatemarketinVietnamhasbeensignificantlyfluctuatingsince1990.Itmightb e seen asthreetimesfeverandd e c l i n i n g p r i c e s i n t h e twodecades(Phan,2012).Aftert h e economicdepr essionintheperiodof2012-
2013,therealestatemarkethasbeenshownsignsofrecovery.ThesuccessfulrealestatetransactionsinHa noiin2014are11,450transactions(upbymorethan2 timescomparedt o 2 0 1 3 ) andi n HCMC i t y a re1 0 , 3 5 0 transactions(up3 0 % comparedwith2 0 1 3 )
( M a n h Tung,2014).Ingeneral,Vietnamreale s t a t e markethastakenadvantagesofp o p u l a t i o n increasingandrapidurbanizationwhichcreatedahugeh o u s e o r apartmentdemand,butneverthelessitstillfacesmanydifficulties.Thelargerealestateoutstandingl oansanda bi g numbero f inventoriescreateda serious crisis (XuanThan, 2014),p a r t i c u l a r l y thea pa rt me n t inventoriesandlandinventories.Theapartmentcurrentinventoriesarer o u g h l y e quivalentt o 2 6 0 0 0 b i l l i o n VNDandlandinventoriesarer o u g h l y equivalentt o 2 8 , 5 0 0 b i l l i o n VND (ManhTung,2014).
The Vietnamese government has implemented amended land laws and a VND 30 trillion credit package to support homebuyers, aiming to revitalize the real estate market As a result, Vietnam's residential housing market is currently experiencing a recovery period, aligning with the government's efforts to innovate the real estate industry However, challenges persist in the economy, with real estate inventories reaching 92.690 trillion VND and 19,210 unsold apartments, including 7,520 in Ho Chi Minh City, along with 13,516 unsold low-rise buildings, 755 of which are also in Ho Chi Minh City (CBRE Vietnam, 2014).
According to Trinh Dinh Dung (as cited in Nguoi Dua Tin News, 2014), government efforts alone are insufficient to revive Vietnam's real estate market A significant factor contributing to this crisis is that the supply of housing and apartments does not align with customer demand, primarily because builders lack accurate information about their target customers and market conditions To navigate and thrive in this challenging environment, marketers and analysts in the real estate sector must possess a comprehensive understanding of home or apartment buyers' decision-making criteria (Ratchatakulpat, Miller & Marchant, 2009) and their satisfaction levels concerning housing attributes and service quality (Torbica & Stroh, 2001).
The lack of accurate information about customer preferences and real estate market conditions compels real estate companies to prioritize understanding their customers A significant challenge lies in deeply comprehending customer insights and their decision-making behavior when purchasing an apartment Bettman, Luce, and Payne (1998) highlight that customer choices involve the selection, consumption, and disposal of products and services, which can be complex and vital for consumers, marketers, and policymakers They assert that "customer decision-making is one of the most important areas of customer behavior and requires gathering a lot of relevant information" (p 187) Therefore, understanding customer decision-making can enable real estate companies to develop effective marketing strategies that resonate with consumers, which is crucial for business success.
In recent decades, the concept of real estate purchasing decisions has evolved significantly, as highlighted in various managerial literature This evolution has encouraged real estate developers to respond effectively to customer buying decisions to meet sales targets and enhance customer satisfaction Real estate purchases are recognized as one of the most significant decisions in a person's life, involving long-term commitments that can profoundly impact their future The unique characteristics of real estate make apartment purchasing a distinct behavioral process, differing from typical business transactions Understanding purchaser behavior is crucial for suppliers to tailor their responses effectively.
National and cultural characteristics significantly influence house purchasing decisions, particularly in Vietnam's transitional market, which exhibits unique cultural traits As a collectivist society, Vietnamese culture prioritizes interpersonal relationships, where individuals often seek the opinions and support of family, colleagues, and seniors before making decisions This collaborative approach underscores the importance of understanding consumer behavior in the apartment market Therefore, developers in Vietnam should conduct thorough examinations of consumer purchasing behaviors to gain deeper insights into their customers' needs and preferences.
Uptopresenttime,thenumerousstudieshavebeenundertakenabouttheperceptionsofapartm entpurchasersintermsoftheapartmentattributes,financialstatus,servicequality,purchasingdecisiona ndcustomersatisfactionlevelinothercountries(Haddad,Judeh,Haddad,2 0 1 1 ; Zeng,2 0 1 3 ; Opoku& Abdul-
Despite existing studies on purchasing decisions, few scholars have explored this issue within the context of Vietnam's collectivist culture Notably, Phan's (2012) research examined key factors influencing house purchase decisions in Vietnam, but it primarily focused on house attributes and did not address customer behavior or satisfaction regarding apartment purchases Therefore, this study aims to investigate how apartment purchasers in Ho Chi Minh City make their purchasing decisions based on their satisfaction with apartment attributes and the service quality provided by real estate developers.
Researchobjectives
Researchmethodologyandresearchscope
Inthisresearch,twophasesofstudywereundertaken:aqualitativestudyandaquantitative study.Thequestionnairewast r a n s l a t e d fromEnglishi n t o Vietnamese.Throughqualitativestudy, in- depthinterviewswithsixpeoplewereconductedinordertoadjusttheitemsclosingtofeaturesofVietnam eseculturesandtomaketheimprovementfortheofficialquestionnaire.Inthequantitativestudy,theau thorcollecteddatabyusingaconveniencesamplingapproachandemployedself- administeredsurvey.Foranalyzingt h e collectedd a t a , SPSS16andAmos22wereusedtotestthemode l.Forthereliabilityandvalidity,theresearcherusedCFA.Then,SEMwasusedtotestthehypothesizedmo del.
Duetothelimitationoftime,thisresearchisthereforelimitedtoVietnamesecustomerswhohav eapartmentpurchasingtransactionsi n realestatei n d u s t r y i n t h e HoC h i M i n h City;sinceit is oneofthebiggestcitiesinVietnamandmostof realestatecompaniescentralize here.
Researchsignificance
Basedo n t h e researchr e s u l t s , s o m e usefulmanagerialimplicationsw e r e suggestedt o he lpt h e realestatecompaniest o havet he marketingandsalesstrategiesimpactinggreatly oncustomerp urchased e c i s i o n andhelpp o l i c y makerst o u s e suitablep o l i c i e s t o developt h e Vietna mrealestate industry.
Researchstructure
This thesis is structured into five chapters The introductory chapter outlines the research background, problem, objectives, significance for management practice, and the methodology for data analysis The second chapter reviews and synthesizes relevant theories, focusing on apartment purchase decisions and their relationships with apartment attributes, financial status, service quality, and customer satisfaction It also presents the conceptual model and hypotheses The third chapter details the research methodology employed to empirically test the research model Chapter four showcases the results of the data analysis and discusses their relevance to the research questions and hypotheses The final chapter concludes by addressing the research hypotheses and problems, offering implications for theories, policies, and practices based on the findings, while also identifying limitations for future research.
Thischapterm a i n l y introducest h e theories,w h i c h a r e p r o p o s e d bym a n y scholarsi n academicfieldandarerelatedtoalltheconceptsandresearchmodel.Theauthorfirstlyclarifiest h e def initionso f purchasedecisionandthent h e relationshipsamongpurchased e c i s i o n withapartmentattri butes,financialstatus,servicequalityandcustomers’satisfactionlevelconductedbypreviousstudiesare alsodiscussedforproposingaconceptualmodelandhypotheses.
The purchase decision is a critical phase in customer purchasing behavior, evolving over a specific timeframe (Piron, 1993; Kotler & Keller, 2009) Recently, this behavior has attracted significant attention from marketers and researchers due to its vital role in predicting operational success and achieving sustainable competitive advantage (Parasuraman, Zeithaml & Berry, 1985) Insights from research and the experiences of successful marketers reveal how customers make purchasing decisions and where they choose to buy products The purchase decision-making process involves various stages that reflect the customer's experiences (Zeng, 2013) Typically, selecting a product entails multiple comparisons to align customer characteristics with the product’s attributes Consequently, customers may apply different criteria to evaluate which product best meets their needs, influenced by the type of purchase and their expectations regarding performance (Blackwell et al., as cited in Zeng, 2013).
The purchasing decision process consists of five stages: need recognition, information search, evaluation of alternatives, purchase, and post-purchase evaluation However, not all customers follow every step, as their past experiences and preferred brands can lead them to make immediate choices Additionally, consumers from different market segments may make varying purchasing decisions based on their perceptions of the attributes they deem important.
Purchasinganapartmenti s o n e o f t h e m o s t significanteconomicd e c i s i o n s thatpeoplemake,anditrequiresthepurchasertogatheralotofinformationregardingitsfeatures(Haddad,
Real estate serves as both a financial asset and a physical entity, encompassing intrinsic and extrinsic attributes that influence consumer behavior (Judeh & Haddad, 2011; Anastasia & Suwitro, 2015) The decision-making process for purchasing an apartment is distinct from other business decisions, primarily due to the unique, durable, and long-term characteristics of real estate (Kinnard, as cited in Phan, 2012) Each property is a highly differentiated product, with its specific site being unique and fixed in location (Kinnard, as cited in Phan, 2012) Understanding the factors that influence buyer behavior is crucial for apartment developers to enhance their insights and predictions regarding purchasing decisions in real estate markets (Daly, Gronow, Jenkins & Plimmer, as cited in Anastasia & Suwitro, 2015).
Therearevariouscustomerdecision- makingmodelshavebeenproposedintheliteraturei n recentdecades.However,m a n y researchersbe lievethata specific,situationandproduct- orientedmodelis neededin studyingpurchasing(Erasmusm,Boshoff&Rousseau,ascitedin Koklic
&Vida,2009).Theyalsoadmitthattherearelacksstudiesofpurchasingdecisionsthatconsumersarem ostconcernedabout“behavioralpurchasingdecisionmaking”.Additionally,thestudiesaboutrealestate purchasingbehavioraldecisionsinVietnamarenotyettobefoundinp u b l i c literatures.Thus,th isstudywillprovideabetterunderstandingofpurchasingbehavioraldecisionmakingcontext andin fluencesto allapartmentparticipantswhicharethedevelopers,purchasers,andrealestateagents.
The abundance of apartment developers offers numerous choices for customers, but making a purchase decision requires clear evaluation criteria According to Hawkins, Mothersbaugh, and Best (2011), apartment features that align with customer expectations serve as essential criteria for evaluating options Generally, apartment customers prioritize the main attributes they perceive as most valuable, assess these different attributes, and determine their willingness to pay for desirable features (Kotler & Keller, 2009) Various real estate attributes have been extensively studied as influential factors in apartment customers' purchasing decisions (Ratchatakulpat et al., 2009; Haddad et al., 2011; Opoku & Abdul).
Muhmin,2010;Alonso,2002;Pope,2008;Speticetal.,2005;Wang&Li,2006).Basingontheresearch es,Zeng(2013)andRatchatakulpatetal.
In 2009, key housing attributes were categorized into four main types: intrinsic, extrinsic, environmental, and location attributes Intrinsic housing attributes encompass factors such as housing size, type, and internal design (Cupchik, Ritterfeld & Levin, as cited in Zeng, 2013; Ratchatakulpat et al., 2009) Extrinsic attributes focus on the exterior design and outdoor space of the property (Bhatti & Church, as cited in Zeng, 2013; Ratchatakulpat et al., 2009) Environmental attributes relate to the surrounding neighborhood, highlighting the importance of community context in housing decisions (Cheshire & Sheppard; Fierro, Fullerton & Donjuan).
Callejo;Pasha& B u t t , ascitedi n Zeng,2 0 1 3 , & Ratchatakulpatetal.,2 0 0 9 ) andp o l l u t i o n (Y usuf& Resosudarmo;Zabel& Kiel,ascitedinZeng,2013).Locationattributescompriseofthedistancet othenearestcentralbusinessd i s t r i c t , schools,andt r a n s p o r t ( C h a y & Greenstone;Pasha
Researchers, including Pope and Jaren (2013) and Ratchatakulpat et al (2009), have utilized Rosen’s hedonic model (1974) to explore customer preferences for housing structural amenities and attributes Residential apartments are viewed as unique products valued for their utility-bearing characteristics and other purchase factors (Bitter, Mulligan, & Dall'erba, 2007; Taylor, 2008; Fierro et al., 2009) Potential homebuyers initially identify key attributes and benefits that align with their expectations, subsequently assessing the importance of each attribute Ultimately, they are inclined to invest in the attributes that offer the greatest perceived value (Bao & Wan).
Insummary,itisindicatedthatmanyattributesofresidentialhousespresentedcanhavedirecto rindirect,positiveornegativeimpactsonconsumers’housingpurchasechoicedecisions(Alonso,20 02;Opoku&Abdul-
Muhmin,2010;Speticetal.,2005;Wang&Li,2006).However,theresearchersalsorealize thattherel ativeimportanceofvarioushousing attributesmightvaryacrossnational contexts.Hence,basedon theliteratures,it ishypothesized:
H1.Customer’sresidentialapartmentpurchasingdecisioni n Vietnami s p o s i t i v e l y influencedbyap artmentattributes.
Purchasing an apartment is often regarded as the most significant financial decision in a person's life, impacting the household budget due to the long-term commitment involved, from the initial down payment to future monthly payments (Abdullah et al., 2012) Therefore, understanding one's financial status is crucial for potential apartment buyers According to Xiao and Tan (2007), having a clear grasp of their current financial situation helps customers ensure they can afford an apartment comfortably Financial status encompasses not only the availability of capital but also borrowing costs associated with real estate transactions (Xiao & Tan, 2007) Moreover, it includes factors such as house prices, mortgage loans, income, and payment terms (Opoku & Abdul).
In 2003, it was emphasized that the financial factors influencing apartment purchases extend beyond mere house prices, taking into account the unique characteristics of the apartment and its payment transactions Key considerations include interest rates, maximum mortgage limits, maximum monthly payments, and the duration of payment terms Today, apartment buyers exhibit diverse attitudes and possess strong bargaining power, along with a wide range of available options and low switching costs Consequently, they are increasingly critical and sensitive when making purchasing decisions, particularly regarding apartment prices and payment methods (Opoku & Abdul-Muhmin, 2010).
Numerous studies have utilized the hedonic price model, as established by Rosen (cited in Taylor, 2008), to analyze customers' apartment selection criteria and the demand for housing amenities (Fierro et al., 2009) These studies indicate that buyers assess the marginal utility of each apartment attribute in relation to its marginal price, suggesting that an apartment is valued for its utility-bearing characteristics However, purchasing an apartment poses significant financial challenges, particularly for young families in developing countries, who often find it difficult to pay a substantial sum upfront (Xiao & Tan, 2007) To align with customer needs, willingness to pay, and developers' price expectations, it is crucial to focus on the apartment's equilibrium prices in terms of payment options (Sunding & Swoboda, 2010) Furthermore, comparisons between apartment purchasers will help evaluate the costs of buying versus renting, aiding in making more informed decisions.
(2009)realizeifapurchaser evaluatesthecoststouse capitaltopurchaseischeapandeasytoachieve,heorshewillshiftfromrentingtopurchasinganapart ment.Intelligentcustomersareassumedtobeutilitymaximizing,withintheboundsofsearchcostsand limitedknowledge,mobility,andincome(Kotler&Keller,2009).Theyestimatewhichofferwilldelive rthemostperceivedvalueandmakepurchasedecisionsbasedo n theirestimate(Hawkinsetal.;Sol omon,ascitedinZeng,2013).So,thisstudyisgoingtoe x a m i n e bothapartmentattributes’ costsandpayingmethodscancreatemoreperceivedvaluetostimulatecustomers’willingnesstopayt o p urchaseanapartment.Giventhisdiversifyingresults,thecurrentstudyproposesandteststhesecondhypo thesis:
Service quality is recognized as a crucial factor that enhances organizational competitiveness and success Initially developed by Parasuraman et al (1985), the service quality model comprises five key dimensions: reliability, responsiveness, assurance, empathy, and tangibles This model has been widely utilized in various market disciplines (Gannage, as cited in Nahmens & Ikuma, 2009; Kotler & Keller, 2009) According to Nahmens & Ikuma (2009), apartment developers deliver housing services that customers perceive through interactions and dynamic events within residential housing systems Customers actively seek information, evaluate, and compare services from different housing suppliers to make informed decisions The purchasing decisions of homebuyers can be influenced by the quality attributes of apartment developers, highlighting that the quality of services impacts both purchase decisions and post-purchase satisfaction (Torbica & Stroh, 2005; Forsythe, 2008; Nahmens & Ikuma, 2009).
In the developing residential housing service market, it is crucial to understand what customers seek and how they evaluate services Housing customers prioritize service quality from providers, which influences their perception of value and competitive advantage Research by Schiffman, Hansen, and Kanuk (2012) highlights that customer perceptions significantly impact their service choices and evaluations Nahmens and Ikuma (2009) and Forsythe (2008) utilize the five dimensions of service quality to assess perceived service quality among homebuyers, determining whether the actual service met or exceeded expectations Their findings categorize these dimensions into 21 attributes, which measure service quality from apartment developers during the design and construction phases Studies by Torbica and Stroh (2001) emphasize that homebuyers' satisfaction with service quality directly affects their purchasing decisions Additionally, all five dimensions—reliability, responsiveness, assurance, empathy, and tangibles—play a significant role in overall satisfaction Atterhog (2005) suggests that residential service providers can enhance customer satisfaction and decision-making by bridging the gap between service quality expectations and perceptions This research identifies housing service quality as a key factor influencing purchasing decisions and consumer value perception in the apartment buying process.
H3.Consumer’sapartmentpurchasingdecision i s p o s i t i v e l y influencedbytheservicequ al it y p rovidedbyapartmentdevelopers.
Customer satisfaction is defined as the relationship between customer expectations and perceived performance or product quality (Oliver, as cited in Zeng, 2013) It serves as an objective evaluation of how well a service encounter meets customer expectations (Mossel & Valk, as cited in Zeng, 2013) Research on customer satisfaction and dissatisfaction emphasizes the importance of the difference between pre-purchase expectations and post-purchase perceptions (Peter & Olson, as cited in Nahmens & Ikuma, 2009) Dissatisfaction arises when product performance falls short of expectations, while satisfaction increases when performance exceeds those expectations (Peter & Olson, as cited in Nahmens & Ikuma, 2009).
2 0 0 9 ) Intuitively,i t i s expectedthatt h e customers’satisfactionleveli s t h e q u a l i t y o f c u s t o m e r comparisonbetweentheirexpectationsa b o u t anapartmentandapartmentattributesp r o v i d e d by reale s t a t e developers.
Research has highlighted the critical role of housing attributes in determining overall customer satisfaction in the real estate industry (Nahmens & Ikuma, 2009) Longenecker et al (as cited in Nahmens & Ikuma, 2009) emphasize that customer satisfaction should be assessed in post-purchase evaluations, which consider various factors such as housing attributes, performance, and services Customer expectations are significantly shaped by the value derived from apartments and the services provided by real estate developers Studies indicate that a buyer's overall satisfaction is linked to the comprehensive offering of housing attributes that fulfill consumer needs and desires (Torbica & Stroh, 2001; Forsythe, 2008) The findings suggest that more favorable perceptions of housing attributes correlate with higher satisfaction levels among home purchasers (Opoku & Abdul).
M u h m i n (2010)realizethatthefollowingaspectsofhousingattributescansignificantly influ encehousebuyers’expectationsoftheirnewhouse:housingstructure,housingsalesdealer,w o r k m a n s h i p , h o us i n g construction,materials,priceandappreciationvalue.Asa result,investigatingt hepositiverelationshipbetweenapartmentattributesandapartmentowners’post- purchasesatisfactionmayhelpthemarketerstoprovidetherighthousingproductsandservicest o bot hpotentialhomebuyersandhouseownerswhointendtobuyasecondhouse.Hence,thefourthhypothe sisis:
Basingo n t h e literatureo f h o u s i n g i n d u s t r y andservicequality,s t u d y byN a h m e n s & I kuma( 2 0 0 9 ) revealsthattherea r e s o m e serviceq u a l i t y determinantsthatcans a t i s f y andd i s s a t i s f y housingcustomers.Thepredominantsatisfiersareattentiveness,responsiveness,carean dfriendlinessandt h e predominantdissatisfiesareintegrity,reliability,responsiveness,availability,andf unctionality.O t h e r workbyP o w e r andAssociates(ascitedi n N a h m e n s &
According to Ikuma (2009), the services offered by sales staff and daily housing maintenance are crucial for meeting the selection criteria and overall satisfaction of homeowners in Florida The study highlights that expediting transaction processes significantly enhances customer satisfaction, while minimizing inefficiencies, chaos, incompetence, and isolation in housing services is essential to reduce customer dissatisfaction To maintain and grow their apartment customer base, real estate developers must understand the criteria that customers use to evaluate housing services, as these factors directly influence their perceptions of overall service quality and satisfaction with the offerings provided by apartment developers.
Apartmentattributesandapartmentpurchasingdecision
The wide range of apartment developers offers numerous options for potential buyers, but without clear criteria, making a purchasing decision can be challenging According to Hawkins, Mothersbaugh, and Best (2011), apartment features that align with customer expectations serve as essential criteria for evaluating choices Typically, customers assess the main attributes they find most valuable, evaluate these features, and determine their willingness to pay for desirable attributes (Kotler & Keller, 2009) Previous studies have identified various real estate attributes that significantly influence apartment customers' purchasing decisions (Ratchatakulpat et al., 2009; Haddad et al., 2011; Opoku & Abdul).
Muhmin,2010;Alonso,2002;Pope,2008;Speticetal.,2005;Wang&Li,2006).Basingontheresearch es,Zeng(2013)andRatchatakulpatetal.
In 2009, key housing attributes were classified into four categories: intrinsic, extrinsic, environmental, and location attributes Intrinsic housing attributes encompass factors such as housing size, type, and internal design (Cupchik, Ritterfeld & Levin, as cited in Zeng, 2013; Ratchatakulpat et al., 2009) Extrinsic attributes focus on exterior design and available outdoor space (Bhatti & Church, as cited in Zeng, 2013; Ratchatakulpat et al., 2009) Environmental attributes reflect aspects related to the neighborhood (Cheshire & Sheppard; Fierro, Fullerton & Donjuan).
Callejo;Pasha& B u t t , ascitedi n Zeng,2 0 1 3 , & Ratchatakulpatetal.,2 0 0 9 ) andp o l l u t i o n (Y usuf& Resosudarmo;Zabel& Kiel,ascitedinZeng,2013).Locationattributescompriseofthedistancet othenearestcentralbusinessd i s t r i c t , schools,andt r a n s p o r t ( C h a y & Greenstone;Pasha
Researchers, including Pope and Jaren (2013) and Ratchatakulpa et al (2009), have utilized Rosen's hedonic model (1974) to explore customer preferences for housing amenities and attributes Residential apartments are viewed as unique products valued for their utility-bearing characteristics and various purchasing factors (Bitter, Mulligan, & Dall'erba, 2007; Taylor, 2008; Fierro et al., 2009) Potential homebuyers first identify key attributes and benefits that align with their expectations, subsequently assessing the importance of each Ultimately, they prioritize and are willing to invest in those attributes that they perceive as delivering the greatest value.
Insummary,itisindicatedthatmanyattributesofresidentialhousespresentedcanhavedirecto rindirect,positiveornegativeimpactsonconsumers’housingpurchasechoicedecisions(Alonso,20 02;Opoku&Abdul-
Muhmin,2010;Speticetal.,2005;Wang&Li,2006).However,theresearchersalsorealize thattherel ativeimportanceofvarioushousing attributesmightvaryacrossnational contexts.Hence,basedon theliteratures,it ishypothesized:
H1.Customer’sresidentialapartmentpurchasingdecisioni n Vietnami s p o s i t i v e l y influencedbyap artmentattributes.
Financialstatusandapartmentpurchasingdecision
Purchasing an apartment is often regarded as the most significant financial decision in a person's life, impacting household budgets due to the long-term commitment involved, from the initial down payment to ongoing monthly payments (Abdullah et al., 2012) Consequently, understanding one's financial status is crucial for potential apartment buyers According to Xiao and Tan (2007), being aware of their current financial situation enables customers to choose apartments they can afford comfortably They categorize financial status into two main elements: the need for substantial capital and the associated borrowing costs (Xiao & Tan, 2007) This suggests that financial status encompasses not only available funds but also the overall costs involved in purchasing an apartment Additionally, it includes factors such as house prices, mortgage loans, income, and payment terms (Opoku & Abdul).
In 2003, it was emphasized that financial factors influencing apartment purchases extend beyond just the house price, taking into account the unique characteristics of the apartment and its payment transactions Key considerations include interest rates, maximum mortgage amounts, maximum monthly payments, and the duration of payments Today’s apartment buyers exhibit diverse attitudes, possess strong bargaining power, have a wide range of choices, and face lower switching costs Consequently, they are highly critical and sensitive when making purchasing decisions regarding apartment prices and payment methods (Opoku & Abdul-Muhmin, 2010).
Several studies have utilized the hedonic price model developed by Rosen to investigate customers' apartment selection criteria, focusing on housing amenities and attributes (Taylor, 2008; Fierro et al., 2009) These studies reveal that customers tend to assess the marginal utility of each apartment in relation to its marginal price, indicating that apartments are valued for their utility-bearing characteristics and other purchasing factors However, purchasing an apartment poses a significant financial challenge, particularly for young families in developing countries, as they often struggle to pay a large sum upfront (Xiao & Tan, 2007) To align with customer needs, willingness to pay, and developers' price expectations, it is essential to focus on the terms of payment when determining apartment equilibrium prices (Sunding & Swoboda, 2010) Comparisons among apartment purchasers will help evaluate the costs of buying versus renting, aiding in making informed decisions.
(2009)realizeifapurchaser evaluatesthecoststouse capitaltopurchaseischeapandeasytoachieve,heorshewillshiftfromrentingtopurchasinganapart ment.Intelligentcustomersareassumedtobeutilitymaximizing,withintheboundsofsearchcostsand limitedknowledge,mobility,andincome(Kotler&Keller,2009).Theyestimatewhichofferwilldelive rthemostperceivedvalueandmakepurchasedecisionsbasedo n theirestimate(Hawkinsetal.;Sol omon,ascitedinZeng,2013).So,thisstudyisgoingtoe x a m i n e bothapartmentattributes’ costsandpayingmethodscancreatemoreperceivedvaluetostimulatecustomers’willingnesstopayt o p urchaseanapartment.Giventhisdiversifyingresults,thecurrentstudyproposesandteststhesecondhypo thesis:
Apartmentservicequalityandapartmentpurchasingdecision
Service quality is recognized as a crucial factor that enhances organizational competitiveness The concept, initially developed by Parasuraman et al (1985), includes five dimensions: reliability, responsiveness, assurance, empathy, and tangibles This model has been widely utilized in various market research studies (Gannage, as cited in Nahmens & Ikuma, 2009; Kotler & Keller, 2009) According to Nahmens & Ikuma (2009), apartment developers deliver housing services that customers perceive through interactions and activities within residential housing systems Customers actively seek information, evaluate services from different suppliers, and choose the options they find most suitable Their purchasing decisions can be influenced by personal circumstances and the quality attributes of apartment developers Consequently, the quality of services offered by these developers significantly impacts homebuyers' purchasing decisions and their satisfaction after the purchase (Torbica & Stroh, 2005; Forsythe, 2008; Nahmens & Ikuma, 2009).
In the developing residential housing service market, it is crucial to understand customer expectations and how they evaluate services Housing customers prioritize service quality from providers, which influences their perceived value of housing services and serves as a competitive advantage Research by Schiffman, Hansen, and Kanuk (2012) indicates that customer perceptions significantly impact their service evaluations and provider choices Nahmens and Ikuma (2009) and Forsythe (2008) identified five main dimensions of service quality to assess homebuyers' perceived service quality in the U.S., revealing whether the actual service quality met or exceeded expectations Their findings led to the SERQUAL model, which includes 21 attributes to measure service quality in apartment development Studies by Torbica and Stroh (2001) further emphasize that homebuyers are more likely to make purchasing decisions when satisfied with service quality, which is influenced by reliability, responsiveness, assurance, empathy, and tangibles Additionally, Atterhog (2005) suggests that residential service providers can enhance customer satisfaction and influence purchasing decisions by effectively bridging the gap between service quality expectations and perceptions This body of research highlights the importance of service quality as a precursor to housing purchase decisions, underscoring its significant role in shaping consumer value perception and decision-making in the apartment buying process.
H3.Consumer’sapartmentpurchasingdecision i s p o s i t i v e l y influencedbytheservicequ al it y p rovidedbyapartmentdevelopers.
Apartmentattributesandcustomer satisfactionlevel
Customer satisfaction is defined as the relationship between customer expectations and perceived performance or product quality (Oliver, as cited in Zeng, 2013) It represents an objective evaluation of how well a service encounter meets customer expectations (Mossel & Valk, as cited in Zeng, 2013) In studies of customer satisfaction and dissatisfaction, the focus is on the difference between pre-purchase expectations and post-purchase perceptions (Peter & Olson, as cited in Nahmens & Ikuma, 2009) Dissatisfaction arises when product performance falls short of expectations, while satisfaction is more likely when performance exceeds those expectations (Peter & Olson, as cited in Nahmens & Ikuma, 2009).
2 0 0 9 ) Intuitively,i t i s expectedthatt h e customers’satisfactionleveli s t h e q u a l i t y o f c u s t o m e r comparisonbetweentheirexpectationsa b o u t anapartmentandapartmentattributesp r o v i d e d by reale s t a t e developers.
Previous research has highlighted the significance of key housing attributes in determining overall customer satisfaction in the real estate industry According to Longenecker et al (as cited in Nahmens & Ikuma, 2009), customer satisfaction should be evaluated post-purchase, considering factors such as housing attributes, performance, and services Customer expectations are notably shaped by the value derived from apartments and the services offered by real estate developers Studies indicate that a home buyer's overall satisfaction correlates with the total housing attributes provided by developers, which align with consumer needs and desires (Torbica & Stroh, 2001; Forsythe, 2008) The findings suggest that more favorable customer perceptions of housing attributes lead to higher overall satisfaction among home purchasers (Opoku & Abdul).
M u h m i n (2010)realizethatthefollowingaspectsofhousingattributescansignificantly influ encehousebuyers’expectationsoftheirnewhouse:housingstructure,housingsalesdealer,w o r k m a n s h i p , h o us i n g construction,materials,priceandappreciationvalue.Asa result,investigatingt hepositiverelationshipbetweenapartmentattributesandapartmentowners’post- purchasesatisfactionmayhelpthemarketerstoprovidetherighthousingproductsandservicest o bot hpotentialhomebuyersandhouseownerswhointendtobuyasecondhouse.Hence,thefourthhypothe sisis:
Apartmentservicequalityandcustomer’ssatisfactionlevel
Basingo n t h e literatureo f h o u s i n g i n d u s t r y andservicequality,s t u d y byN a h m e n s & I kuma( 2 0 0 9 ) revealsthattherea r e s o m e serviceq u a l i t y determinantsthatcans a t i s f y andd i s s a t i s f y housingcustomers.Thepredominantsatisfiersareattentiveness,responsiveness,carean dfriendlinessandt h e predominantdissatisfiesareintegrity,reliability,responsiveness,availability,andf unctionality.O t h e r workbyP o w e r andAssociates(ascitedi n N a h m e n s &
Ikuma (2009) highlights that the services offered by sales staff and daily housing maintenance are crucial for meeting homeowners' selection criteria and overall satisfaction in Florida They emphasize that streamlining transaction processes significantly enhances customer satisfaction, while avoiding inefficiencies, chaos, incompetence, and isolation in housing services can reduce customer dissatisfaction To maintain and grow their apartment customer base, real estate developers must understand the criteria customers use to evaluate housing services and how these factors influence their perceptions of service quality and satisfaction.
The theory suggests a strong relationship between apartment service quality and customer satisfaction levels According to Torbica and Stroh (as cited in Zeng, 2013), customer satisfaction arises from an evaluation process that compares pre-purchase expectations with actual performance during and after the apartment experience Nahmens and Ikuma (2009) further highlight the significant positive correlation between housing service quality and satisfaction To foster customer loyalty and maintain a competitive edge, real estate companies must monitor satisfaction, adapt their operations, and exceed consumer expectations Ultimately, a more favorable perception of housing service quality is likely to enhance overall satisfaction with the apartment developer The strength of this relationship hinges on customer evaluations of the overall attributes of apartment service quality.
Apartment service quality influencedbytheir evaluationsoftheservicequalityprovidedbyapartmentdevelopers.
Conceptualmodel
Figure1 d e p i c t s a conceptualmodele x p l a i n i n g t h e r o l e o f antecedentso f apartme ntpurchasingdecision such asapartmentattributes,financialstatus,apartment servicequality on purchasingdecisiona n d customersatisfactionlevelo f customerswhohaveapartmenttransactionsint herealestateindustryinHoChiMinhCity,Vietnam.Specifically,themodelproposesthatapartme ntattributes,financialstatus,apartmentservicequalityhavepositiveimpactsonpurchasingdecisionand customer satisfactionlevel.
H3.Consumer’sapartmentpurchasingdecisioni s p o s i t i v e l y influencedbythe serviceq u a l i t y providedbyapartmentdevelopers.
Insummary,thischapterpresentstheoreticalbackgroundofeachconceptinthemodel.Basedon discussionofliteraturereview,purchasingdecisionisaffectedbyapartmentattributes,financialstatus,a ndapartmentservicequality.Then,t h e influenceo f t h e s e antecedents(e.g.apartmentattributesanda partmentservicequality)oncustomersatisfactionlevelisalsoconsidered.Therelationshipofthesefacto rsalreadytestedbymanypreviousscholarsispresentedfortheconceptualmodel.Hence,therearefiveh ypothesesproposedforthisresearch.Thenextchapterwilldiscussaboutmethodologythatusedtoan alyzethedataandtesthypothesesoftheresearchmodel.
Thischapterpresentsdetailinformationofaresearchmethodologyofthisstudy.First,itstarts withresearchprocessandsampledescription.Then,measurementscalesarepresentedtodevelopquest ionnaires,followedbyd a t a collectionmethod.Afterthat,in- depthinterviewi s conductedtohelpmeasurementscalesclearerandunderstandable.Throughthefinalq uestionnaire,t h e datao f quantitatives u r v e y i s usedt o testt h e measurementandstructuralmodels.
Researchdesign
Researchprocess
Due to the unique characteristics of the real estate industry, which necessitate strong marketing competencies for companies to maintain a sustainable competitive advantage, a study was conducted in Ho Chi Minh City, a major hub for real estate in Vietnam This study comprised two phases: a qualitative study and a main survey The survey questionnaire was initially crafted in English and later translated into Vietnamese with the assistance of language experts The qualitative phase involved in-depth interviews with six customers who had purchased apartments, conducted over a week in various suitable locations such as real estate offices and cafés During these interviews, the researcher read each item on the measurement scale to the interviewees, seeking their understanding and clarifying any misunderstandings to gather valuable insights and suggestions.
Basedonthefeedbackofrespondents,thesurveyquestionnairewasslightlymodifiedtomakei tclearerandmoreunderstandable(seeAppendixA,B,&C).Afterthequestionnairewasmodified,the se lf-administratedquantitativesurvey withconveniencesampling wasconductedt o collectdata fortesting theresearch’shypotheses.
Participantsself-completeda s u r v e y withalli t e m s weremeasuredbyfive- pointLikertscale,anchorpoints including “stronglydisagree”(=1),“disagree”(=2),“neitherdisagre enoragree”(=3),“agree”(=4),and“stronglyagree”(=5).Thequestionnairewasmainlydeliveredtor espondentsv i a electronicmail,Googles u r v e y andhardcopies( s e e Table3.1).S P S S andAMOS wereused totestthemeasurementandstructuralmodels.
Measurementscales
Asmentionedabove,thefinalquestionnairesconsistedoffivemainmeasurementscales:apartm entattributes,financialstatus,apartmentdevelopers’servicequality,apartmentpurchasingdecision, andcustomer satisfactionlevel.
Apartmentp u r c h a s i n g decisionwasmeasuredbyf o u r items,a c c e s s i n g customerpurch asingbehavioralprocess(Piron,1993).
2 IfeltlikeIhadto purchaseitfromthefirsttimeIsaw the apartment PurchasD2
(2009)toVietnamc o n t e x t byeliminatingu n s u i t a b l e itemsandsplittingitemst o helpresponde ntst o understand.Thus,t h e finalmeasurementscalefort h i s constructhasfiveitems,accessingcustome rp o s t - purchasingbehavior.
3.The attributesoftheapartmentthatIhaveboughtmeetsmyexpectations SatisfLev3 4.Theservicesp r o v i d e bysupplierso f t h e apartmentthatI haveboughtmeets myexpectations
5.Mypurchasedecision ismuchbetter thanotherbuyingdecisions in thepast SatisfLev5
Nahmens&Ikuma(2009)developedmeasurementscaleforapartmentdevelopers’servicequal ityfromthescalesofParasuramanetal.(1993),Forsythe(2008),Kotler&Keller,(2009)
(ascitedinNahmens&Ikuma,2009).ThisscalewasadaptedtobesuitableinVietnamrealestatemarket. These itemsarereferredto ascomponentservicesofapartmentandhavealargeimpacto n endcustomer s,andt h i s shouldb e takeni n t o accountwhendevelopingt h e specificationsfortheapartmentservice sprovidedbydevelopers.
Apartment service quality(adaptedfromNahmens &Ikuma,2009) Coding
(ascitedinRatchatakulpatetal.,2009).Theseitemswereadaptedt o Vietnamc o n t e x t byeliminatingu n s u i t a b l e itemst o help respondentstounderstand.Thus,thefinalmeasurementscalehasfouritems,accessingarelativelarge amountofcapital,borrowingcostsandpaymentterms.
Measurementscalesforthefourcomponentsofapartmentattributeswouldbeusedfromt h o s e developedbyAdairetal.,(1996),Dalyetal.,(2003),Abelson&Chung(2005)
The study by Ratchatakulpat et al (2009) identifies four key categories of apartment attributes: intrinsic, extrinsic, environmental, and location attributes To align with Vietnamese cultural features, intrinsic apartment attributes were assessed through five specific items, including the structure, size and number of rooms, layout and decorative style, and architectural materials Extrinsic attributes were evaluated using three criteria, which encompass the overall appearance of the building, the garden and its size, and exterior spaces Additionally, environmental and location attributes were measured through eleven items, with five focusing on the quality of the living environment and six on the characteristics of the apartment's location.
2 Sizeofroomsin theapartment(livingroom,bedroom,kitchen…) IntrinsA2 3.Numberofroomsin theapartment(livingroom,bedroom,kitchen…) IntrinsA3
3.Exteriorspacesrefertop u b l i c area,suchast h e pu bl ic aisle,elevator, recreationroom
Finally,t h e completedquestionnairei n EnglishversionandV i e t n a m e s e versionwerepresen tedin AppendixDandE.
Quantitativestudy
Sample
Themodelandhypothesesweretestedusingdatasetcollectedfromcustomerswhohaveapartme ntpurchasingtransactionsinrealestateindustryintheHoChiMinhCity.Duetolimitedtime,theconvenie ncesamplingapproachwithself-administratedquestionnaireswasconductedi n HoChi MinhCity.
Aboutsamples i z e , t h e s i z e o f t h e samplewasn e c e s s a r i l y b i g e n o u g h t o gu aranteestatisticalsignificance.Hair,Black,Babin,AndersonandTatham(ascitedin Prajogo,2007) statedthattheminimumsampleforappropriateuseforstatisticalanalysisisequaltoorgreaterthanfivet imesofnumberofvariables,butnotlessthan100.Themodelinthisstudyconsistedo f thirty- ninevariablessothatthenecessarysamplesizeshouldbe:n7*55observations.Theauthor delivered337questionnairestoparticipantsinordertoobtainasamplesizeofabout
185.Afterdatacollection,total299responsesfromrespondentswhohaveapartmentpurchasingdemand andhavehadapartmentbusinesstransactionsinHCMCitywerecollected;theresponserate wasapproximately88.72percent(Table3.1).
Table3.1Sourceofdatacollection Source Distributed Collected Response rate Eliminated Valid
Then,total85questionnaireswereeliminatedbecausetheywereinvalid(45respondentswhodo nothaveapartmentpurchasingdemandandhavenothadapartmentpurchasingtransactionsinreal estateindustryintheHoChiMinhCity;14 respondents justchoseoneoptionforallq u e s t i o n s ; and2 6 surveyswerereturnedb a c k withoutanswers).Final ly,2 1 4 questionnaireswereusedasvaliddataforthisresearch.Incomparisonwithminimumsamples i z e , t h i s numberofdata wassatisfactory.
Data analysisprocedures
The author utilized SPSS 16 to calculate Cronbach’s alpha and AMOS 20 for conducting Confirmatory Factor Analysis (CFA) to assess the reliability of each measurement component and the validity of all scales Additionally, the reliability of the measurement scale among constructs in the research model was evaluated using composite reliability (CR) CFA results indicated that average variance extracted (AVE) was employed to determine convergent validity, while the correlation between items (r) was used to assess discriminant validity To ensure the measurement's adequacy, Cronbach’s alpha for each construct should be at least 0.6 (Nunnally & Bernstein, as cited in Prajogo, 2007), factor loadings should reach a minimum of 0.5 (Hair et al., as cited in Prajogo, 2007), and the minimum value of AVE should be 0.5 (Molina, Montes & Ruiz).
According to Moreno et al (2010), as cited in Chong, Ooi, and Tan (2010), a composite reliability of over 0.7 is recommended by Nunnally In assessing convergent and discriminant validity, any inappropriate items will be removed if necessary Furthermore, the Confirmatory Factor Analysis (CFA) will indicate model fit if the CMIN/DF is less than 2 with a p-value greater than 5% The Comparative Fit Index (CFI) evaluates model fit by examining the discrepancy between the data and the hypothesized model while accounting for sample size issues inherent in the chi-squared test of model fit A CFI value of 0.90 or higher is generally considered to indicate an acceptable model fit Additionally, the Non-Normed Fit Index (NNFI), also known as the Tucker-Lewis Index, provides further insights into model fit.
TLI)resolveds o m e o f t h e issueso f negativebias,thoughNNFIv a l u e s m a y sometimesfallbeyon dthe0to1range.ValuesforboththeNFI andNNFIshouldrangebetween0and1,withacutoffof.95 orgreater,indicating agoodmodel fit.The rootmeansquareerrorofapproximation
(RMSEA)avoidedissuesofsamplesizebyanalyzingthediscrepancybetweenthehypothesizedmodel, witho p t i m a l l y c h o s e n parameterestimates,andt h e populationcovariancem a t r i x A valueo f 0 0 6 o r lessw a s indicatedanacceptablemodelfit.RMSEAwassmallerthan8 %
(NguyenDinhTho&NguyenThiMaiTrang,2008).Then,structuralequationmodeling(SEM)testedthe hypothesizedmodelandestimatedpathcoefficientsforeachproposedrelationshipinthestructuralmodel Finally,bootstrapwasu s e d t o r e - t e s t t h e suitableandreliabilityofthemodel.
Asbeingmentionedabove, fivemeasurementscalesweresufficientforconvergentanddiscri minantvalidity,wereanalyzedbytheConfirmatoryfactoranalysisbeforethehypothesizedmodelwastes tedbySEM.The first-orderconstructswere financialstatus,apartmentdevelopers’servicequality,a p a r t m e n tpurchasingd e c i s i o n behavio ralprocess,andsatisfactionlevel.Thesecond- orderconstructwereapartmentattributes,whichconsistedoffoursub- components:intrinsicapartmentattributes,extrinsicapartmentattributes,environmentattributes,andl ocationattributes.
Insummary,thischapterdescribedtheresearchprocess,measurementscaleconstruction,calcul ationo f samples i z e , andresearchmethodconductedt o analyzet h e collecteddata.Thiss t u d y was designedintotwostages:firstwasqualitativestudy(in- depthinterview),secondwasquantitatives t u d y ( m a i n survey).Thei n - d e p t h interviewwasconductedt o m o d i f y t h e measurementscaleandthequestionnairewasadjuste dslightlyandbeforethequantitativesurvey.Mains u r v e y h a d samples i z e whichi n c l u d e d total2 1
Chapter4presentstheanalysisresultsofthesamplesizen!4.ThisprocessusedSPSSt o revie wt h e sample’scharactersandthedescriptivestatistictestedthenormaldistributionofvariablesbasing onrespondents’demographics.Then,AMOSwasusedforconfirmatoryfactoranalysist o e x a m i n e t h e reliabilityandv a l i d i t y o f t h e firstorderconstructs,t h e secondorderconstructandthefinalmeas urementmodel.Inaddition,structuralequationmodelingwasusedt o testtheconceptualmodelandb ootstrapmethodwasusedt o measuret h e parameterestimates.Basedontheanalysis’sresults,theexpla nationforfindingresearchwasfinallydiscussed.
Respondents’ demographics
CFA forthefirst-order constructs
Financialstatuswasmeasuredby4items.ForthefirstrunofCFA,theCFAmodeloffinancials tatusfittedthedatawell.However,thefactorloadingofFinanSta2wasnotsignificant(-.0110.70).Abouttheconvergentvalidity,t h e averagedvarianceextracted(AV E)valueo f apartmentattributes’sub- componentsweresignificant(>0.5).Inaddition,correlationsofeachpairofsub- componentswerelessthan0.8insignificantat0 0 0 1 Therefore,thesefindingssupportedreliability,c onvergentvalidity,andwithin-constructdiscriminantvalidity.(SeeTable4.5,Table4.6)
Table4.5SummarizedofCR,AVEandCronbach’α(Apartment Attributes)
CFA forthefinalmeasurementmodel
RunningtheCFAforthefinalmeasurementmodel,theauthorremovedtheinsignificantitems( FinanSta2,SerQua6,PurchasD2,SatisfLev5,IntrinsA1,IntrinsA5,EnvirA3,LocA4,LocA5,andLocA 6)becausetheirfactorloadingswerelowerthan0.5(-0.01,0.04,0.15, 0.15,
0.15,0.12,0.06,-0.01,-0.07and-0.07respectively).Alltheconstructsandsub- constructsweres t i l l measuredbyover3observeditems.Therefore,themeasurementscalesarestill retainedthecontentvalidityofconstructs.Thefinalmeasurementmodelalsoachievedagoodfittotheda ta(seefigure4.6).Thefactorloadingsoftherestitemsoffirstandsecondorderconstructsweresignific antandsubstantial(>0.5,p