Trang 1 VIETNAM NATIONAL UNIVERSITY, HO CHI MINH CITYUNIVERSITY OF ECONOMICS AND LAWFinal ReportTopic: INVESTIGATE THE REAL ESTATE FACTORSTHAT AFFECT PURCHASE DECISIONS BYCUSTOMER GROUPS
OVERVIEW
Reasons for choosing
In recent years, the Vietnamese real estate market has experienced significant growth and transformation This growth has attracted a diverse range of customers,including first-time home buyers, investors, and families The factors that influence purchase decisions by these customer groups can vary, and it is essential to understand these factors to better serve the Vietnamese real estate market In this report, we will investigate the real estate factors that affect purchase decisions by customer groups in Vietnam.
Factors affecting purchase decisions by customer groups
Suitable Apartment Size:One of the primary considerations for customers when purchasing real estate is the size of the apartment Different customer groups have varying requirements based on their family size, lifestyle, and future plans For example, young professionals or small families may prefer smaller apartments that are more affordable and easier to maintain On the other hand, larger families may seek spacious apartments with multiple bedrooms to accommodate their needs.
Surrounding Infrastructure: The availability of surrounding infrastructure plays a crucial role in purchase decisions Customers consider factors such as proximity to recreational facilities, waste management facilities, green spaces, and public amenities Living near parks, playgrounds, and other recreational areas is particularly desirable for families with children Access to quality schools,workplaces, markets, supermarkets, and shopping centers also influences purchase decisions.
Proximity to Schools and Workplaces:The location of a property in relation to schools and workplaces is an important consideration for customers Families with school-going children prefer properties that are close to reputable educational institutions Similarly, professionals seek properties that offer convenient access to their workplaces, reducing commuting time and enhancing work-life balance.
Accessibility to Markets and Commercial Centers:The proximity to markets, supermarkets, and commercial centers is another crucial factor influencing purchase decisions Customers prefer properties located near vibrant markets or commercial hubs where they can easily access essential goods and services This convenience adds value to the property and enhances the overall living experience.
Community Environment:The community environment surrounding a property significantly impacts purchase decisions Customers consider factors such as the quality of neighbors, safety, and overall community atmosphere A well-maintained and secure neighborhood with a strong sense of community can greatly influence the decision to purchase a property.
Proximity to Main Roads and Highways: Easy access to main roads and highways is an essential factor for many customers Properties located near major transportation routes provide convenience in terms of commuting and accessibility to other parts of the city or region This factor is particularly important for individuals who rely on public transportation or frequently travel by car.
Attractive Interior Design:The interior design of a property is an influential factor in purchase decisions, especially for those seeking aesthetic appeal Customers often prefer well-designed apartments with modern finishes, functional layouts, and high-quality materials The visual attractiveness and overall ambiance of the interior space can significantly impact a customer’s decision to purchase a property.
Competitive Pricing: The price of a property compared to the market value is a critical factor influencing customer decisions Customers are more likely to choose properties that offer good value for money or are reasonably priced compared to similar options in the market Developers who offer competitive pricing strategies often attract more potential buyers.
Financing Options:The availability of financing options, such as installment plans or flexible payment schedules, can greatly influence purchase decisions Many customers prefer properties that offer convenient payment options, allowing them to manage their finances effectively while acquiring their desired real estate assets.
Legal Assurance:Ensuring legal compliance and proper documentation is crucial for customers when making real estate purchases Customers want assurance that the property they are buying has clear legal ownership and all necessary permits and approvals from relevant authorities Trustworthy developers who prioritize legal compliance can instill confidence in potential buyers.
Reputation of Developer and Construction Contractor: The reputation of the developer and construction contractor involved in a real estate project can significantly impact purchase decisions Customers often consider the track record and credibility of the developer and contractor before investing in a property A reputable developer with a history of delivering high-quality projects can attract more customers.
Document continues below data mining
Bài tập lấy điểm giữa kỳ và quá trình
AI Application - hay l ắ m coi đuy
THEORY - METHODS of DATA MINING
Data Classification
Classification is a form of data analysis that extracts models describing important data classes Such models, called classifiers, predict categorical (discrete, unordered) class labels To divide bank loan applications into safe and dangerous categories, for instance, we may create a classification model Our comprehension of the facts as a whole may improve with the use of such analysis Researchers in machine learning, statistics, and pattern recognition have put forth many classification techniques Given a minimal amount of data, the majority of algorithms are
File giáo trình b ả n pdf HSK 2
Giáo trình chủ nghĩ… 100% (11)8 memory-resident Based on earlier research, data mining algorithms have been developed recently that can handle enormous volumes of disk-resident data using scalable categorization and prediction methods.
There are many uses for classification, such as in production, target marketing, fraud detection, performance prediction, and medicine.
2.1.2 How does classification technique work? a) In the first step: Building the Classification Model
In this initial phase, the focus is on constructing a robust classification model leveraging historical or previous data This stage encompasses several key actions: Data Collection and Preparation: Gathering a comprehensive dataset that includes both input features and their corresponding labeled classes or categories This data is preprocessed to handle missing values, normalize features, and ensure its suitability for model training.
Model Training:Utilizing various classification algorithms such as Decision Trees, Support Vector Machines (SVM), Logistic Regression, or Neural Networks, among others The selected algorithm learns from the provided dataset, establishing patterns and relationships between input features and their associated classes.
Evaluation: Assessing the trained model's performance using validation techniques like cross-validation or by splitting the dataset into training and testing subsets This step ensures that the model has learned effectively without overfitting to the training data. b) In the second step: Model Validation and Application
The second step involves evaluating the model's accuracy and readiness for real- world application:
Accuracy Assessment: Checking the model's performance metrics, such as accuracy, precision, recall, or F1-score, to determine its effectiveness in correctly classifying instances This assessment ensures that the model generalizes well to new, unseen data.
Application to New Data:If the model demonstrates acceptable accuracy and reliability during evaluation, it is deployed to classify new or incoming data. The validated model becomes a predictive tool, assigning classes or categories to new instances based on the learned patterns from the training data.
This two-step approach ensures a systematic and thorough process in developing, evaluating, and deploying classification models It emphasizes the importance of not only constructing an accurate model but also validating its performance before utilizing it for real-time classification tasks, thereby ensuring reliable decision- making based on data-driven insights.
2.1.3 The basic techniques for data classification such as a) Decision tree classifiers
Flow Chart Structure: Decision tree classifiers create a tree-like structure resembling a flowchart This hierarchical representation begins with a root node,branches out into intermediate nodes, and concludes with leaf nodes.
Support in Decision-Making: These classifiers assist in decision-making by systematically processing input features and arriving at a decision or prediction. Each node in the tree represents a feature or attribute, guiding the classification process based on specific conditions.
Visual Representation of Rules:The rules for classification are visually defined within this tree structure As data moves through the tree, it undergoes a series of binary decisions based on feature thresholds, ultimately leading to the assignment of a class label at the leaf nodes.
Key Components: ã Root Node: Represents the primary question used to split the dataset based on the most significant feature. ã Branch Nodes: Intermediate nodes that embody the decision-making process, branching based on feature conditions. ã Leaf Nodes: Terminal nodes that provide the final outcome or class label for a specific subset of data.
Considerafinancialinstitutionutilizingadecisiontreeclassifiertoassesscredit scoresforloanapplications.Theinstitutionclassifiescreditscoresintofour categories: ã AforAverage ã BforBad ã CforGood ã DforExcellent
Using a decision tree, explain the sequential process the institution might follow to determine the credit score ratings for loan applicants Elaborate on the hypothetical criteria that the decision tree could employ at each node to classify applicants into these categories Describe how this decision-making process aids in categorizing individuals applying for loans based on their creditworthiness.
In establishing classification criteria for credit scores, several defining rules are in place denoted as A, B, C, and D These rules act as guiding principles within a decision-making framework designed to assess creditworthiness based on specific demographic and financial factors For instance, within this classification system, age and income thresholds play a pivotal role in determining an individual's credit score category Should an applicant fall under the age of 30 and have an income less than 15 million, the classification rule would allocate them to the 'Bad' credit score category, signifying a potential risk associated with this particular demographic segment Continuing within this decision tree framework, individuals under the age of 30 but with an income falling within the range of 15 million to 20 million are classified under the 'Good' credit score category This delineation highlights a different risk profile, acknowledging a more favorable credit assessment for individuals in this income bracket within the specified age group.
These rules underscore the granularity and specificity of criteria used in evaluating creditworthiness By establishing such parameters based on age and income bands, the decision tree classifier effectively segregates applicants into distinct credit score categories, aiding financial institutions in assessing risk and making informed lending decisions. b) Bayesian classifiers
Bayesian classifiers are a fascinating subset of statistical classifiers that employ a probabilistic approach to make predictions about the class membership of data items. These classifiers are rooted in Bayes' theorem, a fundamental principle in probability theory, and offer insightful ways to estimate the likelihood of an item belonging to a particular class or category.
Data association
Association rules are derived from itemsets, which are sets of one or more items present in the data These sets could contain various attributes or features For instance, in market basket analysis, items purchased together might form an itemset.
ExampleRule:Consider the association rule: (Age > 25, Career) -> (Salary > 20m). This rule suggests that individuals over the age of 25 with a certain career tend to have salaries exceeding 20 million, revealing an association between age, career, and salary range.
Unearthing Hidden Patterns: Association rules are valuable for uncovering concealed or implicit patterns within vast datasets They reveal connections between seemingly unrelated items or attributes, providing insights into customer behavior, market trends, or associations in various domains.
Scalable Pattern Discovery: One of the strengths of association rules lies in their ability to learn scalable methods for pattern discovery from massive datasets. Algorithms like Apriori and FP-Growth efficiently mine frequent itemsets, identifying sets of data items strongly correlated to each other despite the dataset's size.
Definition: Support measures the frequency or occurrence of a specific itemset or rule within the dataset It indicates how frequently a particular combination of items appears together in the dataset.
Significance: Higher support values imply that the itemset or rule appears frequently in the dataset Items or itemsets with high support are considered more significant and can be considered for further analysis.
Example:Fraction of transactions that contain the itemset : (Milk, Disapers) =>Beer) The support is:
Confidence measures the reliability or strength of the rule It signifies the likelihood that the consequent of a rule holds true when the antecedent is present.
Example:Fraction of times items in Y appear in transactions that contain X : (Milk, Diapers) => (Beer)
Lift is to measures how much the likelihood of buying Y increases after knowing that X is also purchased
Lift = 1 implies no association between A and B.
Lift > 1 indicates that the presence of A positively influences the presence of B.Lift < 1 suggests that the presence of A has a negative effect on the presence ofB.
2.2.6 Significance in association rule mining:
Support: Helps in identifying frequently occurring itemsets or rules.
Confidence: Assesses the strength of association between items in a rule. Lift: Indicates the significance of the association; values greater than 1 are typically considered meaningful.
Association rules are a powerful tool in the data mining toolkit, offering a means to extract valuable insights from extensive datasets Their ability to reveal hidden connections between data items allows for informed decision-making and a deeper understanding of underlying patterns within complex data environments.
PRACTICE
Biometric characteristics of each customer group
Based on these characteristics, we can observe that this survey focuses on gathering information about the distribution according to gender, age, and marital status of a group of people It is possible to identify 5 distinctive groups based on the data: 3.1.1 Group 1 - Singles, Mainly Purchasing Real Estate for Residence: Group 1 in the survey data primarily focuses on individuals who are single, constituting a significant proportion of the total customers (54.8%) This demographic exhibits distinctive biometric characteristics, being unmarried and without significant family responsibilities The main purpose of property acquisition for this group is residence, accounting for 78.6% This group often demonstrates independence and high autonomy in home-buying decisions With a planned budget ranging from low to medium, they may concentrate on finding homes with convenient locations and amenities suited to a single lifestyle.
The flexibility and adaptability of this group may drive the demand for stable living spaces that can easily be adjusted to changes in individual life circumstances.Therefore, understanding this group can assist developers and real estate professionals in formulating effective strategies to meet their specific needs.3.1.2 Group 2 - Young Families, Newly Married, Investing for the Future:Group 2 in the survey data represents Young Families, Newly Married, comprising26.2% of the total customers This is a particularly crucial demographic in the real estate sector as they are in the midst of the newlywed stage and are preparing to build a happy family life The primary purpose of property acquisition for this group is to invest in the future, which may involve generating income through renting or establishing a stable family home With potentially limited budgets and financial planning, young families often focus on finding homes with amenities that cater to family needs, such as proximity to educational centers and parks.
3.1.3 Group 3 - Elderly Families with Children, Purchasing Real Estate for Savings or Investment:
Group 3, focusing on Elderly Families with Children and showing a tendency to purchase real estate (RE) for savings or investment (19%), represents a significant demographic in the real estate market This group, characterized by family and parental responsibilities, brings stability and financial management experience to the table The presence of a previous home raises the need to cut costs or invest to optimize family finances Their investment strategy focuses on selecting real estate with the potential for appreciation and ensuring long-term profitability Their choice of real estate is also influenced by preferences for amenities and security in the residential area.
3.1.4 Group 4 - Affluent Families, Purchasing Multiple Real Estates for Investment:
Group 4, representing "Affluent Families, Purchasing Multiple Real Estates for Investment" in the survey data, is a significant segment in the real estate sector. With a high income ratio of up to 7.2%, this group stands out with a strategy of acquiring multiple real estates for investment purposes (21.4%) This group often demonstrates diversification in their investment strategy, focusing on risk management and optimizing returns from a diverse real estate portfolio It can be expected that these affluent families have a close relationship with the financial market and utilize real estate as a strategic tool to achieve financial goals and contribute to international asset diversification.
3.1.5 Group 5 - Professional Real Estate Investors
This group, comprising professional investors in the late stages of their careers, all of whom are parents and intend to purchase real estate (RE) primarily for investment and savings, accounts for a proportion of up to 11.9% This demonstrates the maturity and strategic approach in financial management and investment by this group, showcasing their understanding of the value of growth and asset preservation through real estate.
Some key characteristics of Group 5 include innovation in asset management, the ability to assess prior partnerships with RE, and the desire to expand their investment portfolio It's likely that they already own homes and are seeking opportunities to expand their investments, especially in the real estate sector For
Group 5, real estate is not just an investment tool but also a means to preserve asset value and optimize returns over time They tend to choose RE projects with potential for appreciation and stability, reflecting a particular interest in safeguarding asset values during the post-retirement phase.
To better understand this demographic, real estate businesses should focus on developing projects and flexible business strategies that cater to their specific needs.This approach can provide attractive investment solutions and support them in managing and expanding their asset portfolios effectively.
Characteristics of Customers' Real Estate Preferences
3.2.1 Purpose of Real Estate Acquisition
According to the chart, it can be observed that the primary purpose of real estate acquisition for the research participants is for residential purposes, accounting for the majority at 78.6% The remaining portion is attributed to investment purposes, constituting 21.4% Within the residential category, the predominant group is Group
2 (young couples purchasing their first apartment for independent living), followed by Group 1 and some participants from Group 3 and Group 4 Additionally, the investment-oriented purpose is mainly associated with participants from Group 5 and Group 4.
The reason for the higher percentage of real estate acquisition for residential purposes compared to investment purposes is that the majority of research participants fall into Groups 1, 2, and 3 When they have sufficient capital to purchase real estate, they prioritize acquiring properties to meet their housing and living needs After accumulating surplus capital, demonstrating good financial capabilities and high income, they then tend to consider additional investments. According to the research data, most of the research participants have the financial capacity to purchase homes, but not all of them have surplus financial resources for further real estate investments Therefore, residential purposes remain the primary choice for these groups, with investment being a secondary consideration for those with greater financial capacity and resources.
3.2.2 Type of Real Estate Desired for Purchase
According to the data, it can be observed that the most desired type of property for research participants is condominiums, accounting for 52.4%, followed by standalone houses at 30.9%, and finally, purchasing land for self-construction (land) at 16.7% One of the significant reasons many people choose to buy condominiums is the potential cost savings compared to purchasing a standalone house. Maintenance and repair costs for condominiums are often shared among residents, helping alleviate financial pressure for each individual family Additionally, living in urban areas can save commuting costs and provide daily conveniences.
Condominium buildings typically offer amenities such as gyms, playgrounds, tennis courts, and are conveniently located near shopping centers, schools, and hospitals. This brings convenience and time savings for residents Furthermore, buying a pre- built house is often cheaper than purchasing land and constructing a house from scratch This is because land acquisition costs, construction materials, labor, and other expenses are already factored into the house price Additionally, it saves time, as constructing a house from scratch can take several months to a year or more,depending on the complexity of the design and the availability of materials.
Among these, Group 1 and Group 2 comprise the majority when it comes to choosing condominiums as their residence This is because young individuals tend to prioritize time and effort savings when buying a home, avoiding concerns related to urban planning, permits, construction, or additional costs Additionally, meeting the needs of the younger demographic involves having a prime location with convenient transportation, either in the city center or near densely populated and developing residential areas Condominiums offer various upscale and modern amenities such as shopping centers, restaurants, cafes, playgrounds, hospitals, schools, swimming pools, gyms, BBQ areas, and more.
On the other hand, standalone houses are typically preferred by research participants in Group 3 and some in Group 4 and 5 These groups often prioritize a long-term perspective Additionally, standalone houses are viewed as having a high appreciation potential, can be passed down to future generations, or sold to upgrade to another house when needed.
Finally, purchasing land for self-construction is the most common among participants in Group 5 Land is considered the highest-priced type of real estate compared to condominiums and standalone houses It offers long-term ownership rights, high appreciation potential, the flexibility to build according to personal preferences, and is exempt from management fees, services, and parking fees. Therefore, it is seen as a prudent choice for investors seeking to reap long-term benefits.
The desired property size for research participants often falls within the range of 50- 80m2 (40.5%) and 80-110m2 (26.2%), with the majority leaning towards smaller sizes Following this, we have the range of 110-150m2 (21.4%) and over 150m2 (11.9%) It is evident that research participants prioritize purchasing homes with smaller sizes This is likely because buying a smaller-sized home often entails lower costs compared to purchasing a larger one, enabling buyers to save money and manage repayments more easily Additionally, smaller homes are generally easier to manage, requiring less time for cleaning and maintenance.
With the modern living trend, many young individuals prefer to live in apartments or houses with smaller sizes to maximize space utilization, amenities, and cost savings Therefore, they often choose condominiums with sizes ranging from 50- 80m2, fitting their needs and financial capabilities Hence, Group 1, consisting of young singles, and Group 2, young families, mostly prioritize sizes within the range of 50-80m2 On the other hand, for families with children (Group 3), they may prefer larger sizes to accommodate household activities and provide ample space for family members.
Considering the above, Group 4 tends to choose sizes ranging from 80-110m2 or110-150m2 to meet the needs of each family Finally, the choices regarding property size for Group 5 are quite complex, depending on investment trends,market demands, and individual investment goals Therefore, they are evenly distributed across all four size categories.
Financial Structures
Observing the chart, it can be noted that the majority of the research subjects tend to accumulate a portion of the funds, while the remaining part is financed through loans (80.9%) Additionally, some individuals also opt for a combination of existing savings and loans The stability in finances and seizing opportunities quickly are the primary reasons why many people choose to accumulate a portion and finance the rest This is driven by the desire to secure a property that meets their criteria as soon as it becomes available in the market However, lacking sufficient savings to make the purchase outright often leads individuals to consider the unavoidable option of taking a bank loan The emergence of additional incidental costs during the home buying or construction process also influences the decision to resort to bank loans among the research subjects Moreover, this trend aims to capitalize on opportunities and prospects when selecting a desirable home or a rare investment opportunity, contributing long-term value for individuals, families, and future investors However, when choosing this trend, it is crucial to understand financial principles, estimate the payback period, to avoid unfortunate risks and achieve the most efficient profit values.
The trend of accumulating a portion and financing the rest is prevalent across all five groups of subjects, with the highest representation in Group 1 (successful, independent, high-income young individuals) and Group 5 (professional real estate investors) In Group 1, young individuals often lack a significant amount of money to purchase a property outright, but due to financial independence, stable jobs, and incomes, they possess stable financial resources to repay the borrowed amount when buying a house Additionally, in Group 5 (professional real estate investors),they tend to seize the opportunity to buy property based on future potential, land values, etc To capitalize on this, they need strong and timely financial resources.Therefore, borrowing from a bank to choose investments is a wise choice for investors, aiming to bring economic benefits to this group.
Based on the observed data, it can be seen that bank loans are the primary source of financial borrowing for the majority of the research subjects (73.8%), followed by loans from family and relatives (21.4%), and lastly, loans from credit institutions (7.8%) Bank loans are evenly distributed across all five groups of research subjects, with Groups 1 (successful, independent, high-income young individuals) and 5 (professional real estate investors) having the highest proportions These trends are influenced by factors such as trustworthiness and reputation Banks are reputable financial institutions with a long history of lending to customers, providing borrowers with a sense of security Additionally, banks offer various repayment options based on individual borrower characteristics, providing flexibility. Moreover, banks often present competitive interest rates on their loans, helping borrowers save money on interest payments throughout the loan period This can be particularly crucial for those requiring a substantial loan amount In addition, many individuals tend to borrow from family and relatives rather than credit institutions due to concerns about risk, fraud, credibility, and high interest rates associated with credit institutions.
Group Purpose Type of Real
Financial form Financial loan source
1 Living Apartment 50-80 Accumulate in portion Bank
2 Living Apartment 50-80 Accumulate in portion Family,
Investment Land All Accumulate in portion
Financial Characteristics of Customers
3.4.1 Planned Budget for Home Purchase by Customers with Monthly Income of 20-30 Million VND
In the context of an increasingly diverse real estate market, understanding and meeting the needs of each target group become crucial Group 1, consisting of singles whose main purpose of purchasing real estate is for residence, with a stable income ranging from 20-30 million VND per month, is a particularly noteworthy group in the real estate market This group, characterized by independence and a primary goal of finding a home to live in, presents both challenges and opportunities According to detailed analysis, approximately 30% of the total 20 individuals in the group are interested in homes priced under 1 billion VND The number of interested individuals increases to 45% when the price limit is between 1-2 billion VND, while 15% have a budget of 2-3 billion VND, and 10% are willing to make a purchasing decision for homes priced over 3 billion VND.
The characteristics and needs of Group 1 often revolve around stability, demanding privacy, and convenience for independent living This group may also have a particular interest in social amenities and convenient transportation This poses a challenge for developers and real estate agents to better understand the specific desires and needs of the target group, while creating effective marketing strategies to connect with them and provide suitable solutions This includes focusing on sharing information about affordable housing projects while emphasizing amenities and living spaces that align with the specific needs of the target group This helps build a flexible marketing environment that can optimally meet the unique requirements of this customer group, fostering positive interaction and customer satisfaction.
Group 2, characterized by newlywed young families entering the early stages of marital life, is a significant part of the current real estate market With a principle of investing for the future and building a stable foundation for their new home, this group exhibits diversity in financial management and real estate choices In the planned budget allocation for home purchase, especially with a primary income ranging from 20-30 million VND per month, 30% of families are interested in homes priced under 1 billion VND, while 45% and 15% opt for price ranges from 1-2 billion VND and 2-3 billion VND, respectively Additionally, this group also includes a small portion with an income of 50-70 million VND per month, with a similar budget allocation.
These young families, with an investment focus on the future, often aspire to build a stable home and value real estate as a means of preserving value and enhancing assets For them, it is not just a place to live but a strategic investment that can bring profit and social security to the family.
3.4.2 Planned Budget for Home Purchase of Customers with Monthly Incomes of 50-70 Million VND
Group 3, consisting of older families with children and monthly incomes ranging from 50-70 million VND, is a significant target group in the current real estate market With a principle of saving and investing for the future, this group demonstrates maturity and strategic financial management in their real estate choices The data on the planned budget for home purchase describes their budget distribution and priorities in the real estate shopping process.
Older families with children and monthly incomes between 50-70 million VND focus on utility and stability when determining their housing choices Statistical data indicates that 42.86% of the total 14 individuals plan to choose homes in the price range of 2-3 billion VND, aiming for urban development and amenities.Meanwhile, 28.58% and 14.28% will concentrate on homes priced between 1-2 billion VND and under 1 billion VND, respectively, representing diversity and prudent choices within their budget.
3.4.3 Planned Budget for Home Purchase of Customers with Monthly Incomes Above 70 Million VND
Groups 4 and 5 emerge as particularly important and influential segments in the current real estate market, especially when examining their planned home purchase budgets.
Both of these groups, with monthly incomes exceeding 70 million VND, demonstrate significant interest in real estate investment With diverse budgets and a primary focus on high-value projects, they are constructing a diversified real estate portfolio with profit potential Their budget distribution, ranging from below
1 billion to over 3 billion VND, reflects a strategic and deep investment approach.
For professional investors in real estate, the emphasis is on treating real estate investment as a specialized career With a diverse home purchase budget and a distribution strategy ranging from below 1 billion to over 3 billion VND, they are experienced investors with a clear investment strategy With a higher percentage in the price range of 2-3 billion VND, they may be seeking strategic projects with high profit potential.
Both of these groups represent customers with unique shopping and investment strategies in the real estate market For real estate businesses, understanding the specific characteristics and requirements of Group 4 and Group 5 will help optimize marketing strategies and efficiently develop projects, from providing detailed information to focusing on decisive factors such as location, amenities, and investment potential.
The Most Important Factors in Deciding to Buy a Home
A home is not just a place we live; it also lays the foundation for the happiness and growth of our families In the process of selecting the dream home, there are many factors to consider However, according to a survey with 42 participants, three key factors have been identified as the most important: apartment size, surrounding infrastructure, and proximity to schools or workplaces.
3.5.1 Apartment Size: Comfort and Flexibility
Apartment size is considered a decisive factor by over 95% of survey participants when deciding to purchase a home Beyond providing living space, apartment size contributes to values of comfort and flexibility Families find happiness in living spaces that are sufficiently large to meet their daily needs and create memorable experiences A spacious apartment generates a sense of comfort for residents When living space is ample, families can enjoy daily life without the constraints of feeling cramped or confined Expansive spaces and natural light not only create a favorable living environment but also positively impact the mood and health of the residents.A larger apartment not only provides a comfortable atmosphere but also allows for functional flexibility Residents can design and utilize the space to meet their specific needs, creating private areas and communal spaces to enjoy family life. Exploiting the benefits of a larger space, such as incorporating a home office, entertainment room, gym, or play area for children, can be achieved without compromising shared living areas In essence, apartment size is crucial in influencing the satisfaction and well-being of residents The perceived comfort, flexibility, and ability to personalize the living space contribute significantly to the decision-making process of potential homebuyers.
3.5.2 Surrounding Infrastructure: The Foundation of Social LivingNot confined solely within the walls of a home, but extending outward, the surrounding infrastructure is deemed crucial by 67% of survey participants.Families find happiness in living within a thriving and quality community.Surrounding infrastructure includes elements such as transportation systems, public amenities, schools, hospitals, stores and services, security and safety, and social environment A high-quality and convenient transportation system is a pivotal factor when individuals decide to purchase a home Favorable transportation reduces daily commute time, providing favorable conditions for work and personal life. Particularly, an efficient transportation system also positively impacts the real estate value in the area The presence of public amenities such as parks, playgrounds, golf courses, swimming pools, gyms, and other entertainment areas is also a crucial factor when people consider buying a home These amenities not only enhance the quality of life but also create an ideal living environment for the entire family. Another crucial aspect of surrounding infrastructure is the presence of quality schools and reputable hospitals Having good educational and health care facilities not only benefits the residents in the area but also adds value to the real estate. Security and safety in the surrounding environment are indispensable considerations when individuals contemplate buying a home The safety of the surrounding area significantly influences people's decisions to purchase a home Finally, the social environment, meaning the development of culture, arts, entertainment, and other community activities, is also a crucial factor when people decide to buy a home A diverse and dynamic social environment can attract many individuals who wish to live and work in the area.
3.5.3 Proximity to Schools or Workplace: Time-Saving, Lifestyle
With 55% of survey participants indicating that proximity to schools or workplaces is one of the crucial factors influencing their home-buying decisions, it underscores the significance of this factor for today's home buyers This can be explained by the convenience and benefits that this location offers, including time savings and lifestyle optimization.
One of the primary reasons that make the proximity to schools or workplaces important for home buyers is time savings When a home is located near their children's school or workplace, residents can easily commute without investing significant time and effort This enables them to make the most of their time for other important tasks, ranging from work to family responsibilities Furthermore,being close to schools or workplaces also helps optimize the residents' lifestyle The absence of concerns about lengthy daily commutes reduces stress and improves the overall quality of life Additionally, living near the workplace allows residents easy access to social amenities and entertainment within the area, creating a convenient and comfortable living environment Therefore, proximity to schools or workplaces not only provides the benefit of time savings but also contributes to the optimization of residents' lifestyles This has been evidenced by the attention and priority given to this aspect by home buyers.
Group1- Singles,PrimaryPurposeofRealEstatePurchase:ResidencyorShort- TermInvestment:
This customer segment typically has stable income, minimal family responsibilities, and aims to buy a home for residency or short-term investment They often prioritize reasonably priced homes with installment options, proximity to schools or workplaces, aesthetically pleasing interior design, and suitable living space.
Customers in this group usually have a substantial income and seek to purchase a home for long-term residency and future investment They prioritize homes with a reputable developer, construction contractor, assured legal aspects in construction, a community environment (neighbors, security, social norms), proximity to hospitals, and surrounding infrastructure (playgrounds, waste disposal, green spaces).
Group3-Older Families,WithChildren,Purchasing forSavings orInvestment: This customer segment typically has high income, intending to purchase a home for long-term savings or investment They often prioritize homes with a convenient location near main roads/national highways, high potential for appreciation, spacious area, and favorable orientation and Feng Shui.
Group4-Affluent Families, Purchasing MultiplePropertiesfor Investment:
Affluent families investing in multiple properties usually prioritize homes with prices closely aligned with the market, proximity to markets/supermarkets/shopping centers, and high potential for renting out or resale These factors help optimize profits, increase liquidity, and reduce risks in real estate investments.
Customers in this group typically have very high income and a need to purchase multiple properties for investment They prioritize homes with prices closely aligned with the market, proximity to markets/supermarkets/shopping centers, and high potential for renting out or resale.
In summary, the process of home buying is not only an investment in real estate but also an investment in family happiness The apartment size, surrounding infrastructure, and proximity to schools or workplaces play crucial roles in creating a warm and happy home for each family Therefore, when faced with the decision to buy a home, focusing on these factors is not only important but also the key to unlocking family happiness.
Overall, in the search for and decision to purchase a home, not only traditional factors such as apartment size, comfort, and flexibility matter but also the surrounding infrastructure and proximity to schools or workplaces All three factors have proven to significantly influence daily life quality and purchasing decisions. The apartment size is not merely a numerical figure; it is the foundation for comfort and flexibility in daily life Surrounding infrastructure, especially social amenities, creates a developed and vibrant community Proximity to schools or workplaces not only brings convenience but also helps optimize time and enhance social life quality. These factors not only reflect housing preferences but also determine satisfaction and convenience in daily life for residents Real estate businesses that understand and flexibly meet the unique needs of customers have the opportunity to create distinctive and effective projects In total, these factors play a crucial role in shaping an ideal and cozy living space for buyers, highlighting the true value of real estate in modern life.
In conclusion, the real estate factors that affect purchase decisions by customer groups in Vietnam vary depending on the group’s specific needs and objectives. Location, affordability, amenities, and investment potential are essential factors for singles and young families, while elderly families prioritize financial goals, low maintenance, and proximity to essential services Wealthy families and professional real estate investors focus on diversification, market trends, expert advice, networking, and risk management By understanding these factors, real estate professionals can better serve their clients and help them make informed decisions in the Vietnamese real estate market.
Al-Nahdi, T S., Ghazzawi, O H., & Bakar, A A (2015) Behavioral factors affecting real estate purchasing InternationalJournalofBusinessand SocialScience,6(8), 146-154.
Giao, H N K., & Mơ, N T H (2017) Các yếu tố ảnh hưởng đến quyết định mua hàng ngẫu hứng qua truyền hình của khách hàng tại công ty Best Buy Vietnam.Tạpchíkhoa học ĐạihọcMởThànhphốHồChíMinh-Kinh tế VàQuảnTrị KInhDoanh,12(3), 228-243.
Nguyễn Đình Hiển, Nguyễn Thanh Huy, Trần Thị Lan Di & Phạm Hoàng Uyên,
“ Khám phá các yếu tố bất động sản tác động đến quyết định mua và ứng dụng thiết kế hệ thống thông minh hỗ trợ tư vấn chọn bất động sản”,Tạp chíkhoahọc-TrườngĐạihọcQuốctếHồngBàng, Số Đặc biệt 12/2022, 705-717.
LUONG, H T., Dung Manh, T R A N., NGUYEN, D L N., Anh Thuc, L E., &Van PHAM, H (2023) Determinants Influencing Housing-OptionDecision of Gen Y: The Case of Vietnam.JournalofDistributionScience,21(7), 51-63.
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