Psychological studies have shown that risk Perception can be greatly influenced by the framework in which investors are when they make investment decisions.Thus, it can be said that the
Objectives Of the SfUCỈY - - G c 11H ng nh ng 6
Research SCOD - G1 119019 ng 8 4 The new characteristics and contribution of the topic .- ô5s ô<5sô+ 8 5 Structure of the Study 0 eee eeeeesscecsseeesseceeaceseaeeseaeessaeeceaeessaeecsaeeceaeeceeeseeeseaee 9
- Content scope: Factors affecting the decision to invest in the product
- Time range: Primary data research period: First quarter of 2023
- Spatial extent: Asia-Pacific Investment JSC (APEC).
4 The new characteristics and contribution of the topic
The article "The Influence of Factors on Investment Decisions in A-Partner Products of APEC GROUP" explores the significant impact of economic, political, financial, and sociological factors on investment choices during economic downturns This study aims to systematize theoretical frameworks and identify key factors influencing investor decisions through surveys and interviews By analyzing data, it offers valuable insights into investor psychology and needs, ultimately assisting APEC businesses and others in enhancing their investment efficiency.
This article highlights the significance of A-partner products from APEC GROUP in analyzing investment decision factors Utilizing both surveys and interviews, the study aims for a thorough examination of the topic Additionally, data table analysis will offer a quantitative and objective perspective on the influences affecting investment choices Ultimately, this research seeks to enhance the understanding of investor behavior and guide business strategies to boost investment efficiency during challenging economic conditions.
This study consists of three main parts: Introduction, Contents, and Conclusion In the content section, the topic is specifically divided into four chapters:
Chapter 1: THEORITICAL BASISChapter 2: RESEARCH METHODSChapter 3: RESEARCH RESULTSChapter 4: POLICY IMPLICATIONS
THEORITICAL BASIS - 5555 S+x£+cseeeesereres 10
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1.2.1.1 Definition of investor behavior According to W Fred van Raaij (2016) investor behavior refers to the actions, decisions, and patterns of behavior exhibited by individuals or institutions that invest their money in financial markets or assets This includes the factors that influence investment decisions, such as risk tolerance, financial goals, past experiences, market trends, and emotional responses to market fluctuations Investor behavior also encompasses the impact of social, cultural, and institutional factors on investment decisions, as well as the effects of information and communication technologies on investment practices Understanding investor behavior 1S crucial for developing effective investment strategies, assessing market trends and risks, and optimizing investment outcomes.
1.2.1.2 Model of investment behavior According to Rusbult et al (2018) There are several models of investor behavior, each with its own assumptions and variables Here are a few examples:
The rational model posits that investors are logical decision-makers equipped with complete information, enabling efficient processing of data It operates on the premise that investment choices are made based on objective factors, including anticipated returns and associated risks Within this framework, investors are viewed as risk-averse, making decisions guided by expected utility Widely utilized in financial economics, the rational model serves as the cornerstone for various financial models, including the Capital Asset Pricing Model (CAPM).
The behavioral model highlights that investors often make decisions influenced by biases and heuristics, rather than purely rational thinking By integrating concepts from psychology and sociology, this model reveals how cognitive biases, social norms, emotions, and the behavior of other investors can shape investment choices A key example is herding behavior, where individuals follow the crowd instead of relying on objective data, leading to potentially irrational market actions.
The prospect theory model posits that investors exhibit greater sensitivity to potential losses than to potential gains, leading them to take risks primarily when confronted with losses This phenomenon, known as "loss aversion," indicates that the emotional impact of a loss is felt more intensely than the satisfaction derived from an equivalent gain.
16 recognizes the role of emotions in investment decisions, with feelings of regret or satisfaction influencing future choices.
The cultural model highlights the significant role that cultural and social factors play in shaping investment decisions It emphasizes that cultural norms, values, and expectations influence individuals' perceptions of risk and return Additionally, social networks and the opinions of friends, family, and colleagues can significantly affect investment choices For instance, in certain cultures, stock market investments may be perceived as risky or unsuitable, whereas in others, they are regarded as essential for effective financial planning.
These models illustrate the various factors that shape investor behavior, including rational decision-making, emotional reactions, and social and cultural influences Each model possesses unique strengths and weaknesses, making them valuable for analyzing different dimensions of investor behavior.
Here's an example that illustrates the difference between the rational model and the behavioral model:
When contemplating the purchase of stock in Company A, an investor using the rational model would possess comprehensive information about the company's financial statements, industry trends, and competitive environment This investor would analyze the gathered data to assess the expected return and associated risks of the investment, ultimately making a decision grounded in objective criteria.
The behavioral model acknowledges that investors often lack complete information about companies and are susceptible to cognitive biases and social influences For instance, they may exhibit herding behavior, mimicking the actions of other investors instead of relying on objective data Additionally, emotions like fear and greed can drive investors to make poor investment choices, leading to suboptimal outcomes.
Understanding the differences between the rational and behavioral models is crucial for grasping the factors that drive investor behavior Acknowledging the limitations of the rational model while integrating insights from the behavioral model enables researchers and practitioners to create more effective investment strategies and enhance investment outcomes.
1.2.1.3 The investor's investment decision-making process According to Glenn Barklie, Christine Patton (2020) investor's investment decision-making process involves several steps, including:
Effective goal setting is crucial in the investment decision-making process, as it helps investors clarify their financial objectives These objectives can encompass generating specific income levels, attaining long-term capital growth, or reducing risk exposure.
Risk assessment is crucial in determining an investor's willingness to accept potential risks It involves a thorough evaluation of the risks and rewards linked to various investment opportunities, helping investors make informed decisions.
Asset allocation is a crucial step in investment strategy, occurring after defining the investor's goals and risk tolerance It involves strategically distributing capital among various asset classes, including stocks, bonds, and real estate, to optimize returns while managing risk.
After establishing the right asset allocation, investors should focus on security selection by identifying specific investments within each asset class This process requires thorough research and analysis to pinpoint securities that are expected to perform favorably, taking into account historical performance, prevailing industry trends, and current economic conditions.
Portfolio management: Finally, investors must manage their portfolios over time, monitoring performance, rebalancing asset allocations as needed, and adjusting their investment strategies to reflect changing market conditions.
Investors should maintain a clear focus on their financial goals during the investment decision-making process, ensuring that their choices are backed by thorough research and analysis Adopting a disciplined and systematic approach can enhance the likelihood of reaching financial objectives while simultaneously reducing risk.
1.2.2 The Factors Affecting the Investment Behavior of Investors
1.2.2.1 The influence of the market on investors' investment decisions
Market influences play a crucial role in shaping investors' decisions, significantly affecting their investment behavior Factors such as economic conditions, market trends, and global events collectively impact investor sentiment and decision-making processes, as highlighted by Uttam Koirala (2014).
The mobilization of the investment capital contribution
1.3.1 The concept of the mobilization of the investment capital contribution
Mobilization of investment capital involves raising funds from diverse sources to finance specific projects or ventures, as outlined by Vi Tran, Ngan Nguyen, and Thao Bui (2022) This process utilizes various financial instruments and institutions, such as banks, financial markets, venture capitalists, and crowdfunding platforms, to secure the necessary capital for investment.
Mobilizing investment capital is essential for the success of projects and ventures, as it supplies the funds needed for operations, research and development, and other crucial activities This mobilization can be categorized into two primary types: debt financing and equity financing.
1.3.1.1 The debt financing Debt financing involves borrowing money from lenders or investors who expect to receive a return on their investment in the form of interest payments Debt financing can take various forms such as bank loans, bonds, and other debt instruments When a business or individual borrows money, they agree to repay the principal amount plus interest over a specified period of time This type of financing can be attractive for projects or ventures with predictable cash flows because it allows the borrower to manage debt service payments and retain ownership of the business (JAMES CHEN, 2022)
1.3.1.2 The equity financing Equity financing, on the other hand, involves selling ownership shares in the business to investors who receive a share of profits in exchange for their investment Equity financing can take various forms such as common stock, preferred stock, and convertible securities When a business or individual raises equity capital, they are selling a stake in the company and giving up some control over the decision-making process However, equity financing can be attractive for projects or ventures with high growth potential because it allows the business to raise funds without incurring debt and can provide investors with significant returns on their investment.
Other forms of investment capital mobilization include venture capital and crowdfunding Venture capitalists provide funds to start-up companies in
Crowdfunding platforms enable entrepreneurs to raise capital by exchanging ownership stakes and management roles for investments from a diverse group of investors, often facilitated through social media and online campaigns.
Mobilizing investment capital is essential for businesses and entrepreneurs aiming to finance their projects By recognizing various sources and types of investment capital, companies can make informed funding decisions to meet their financial goals.
1.3.2 Assess the pros and cons of debt financing
According to CHELSKY and JEFF (2016), each type of investment has its pros and cons Debt financing is the same, here are the pros and cons of debt financing:
Table 1-1 Debt financing pros and cons comparison chart
Debt financing offers the advantage of lower costs compared to equity financing, as it involves fixed interest payments to lenders rather than sharing profits However, it also carries disadvantages, such as the obligation to repay the principal and interest regardless of the company's financial performance, which can strain cash flow and increase financial risk.
Repayment obligations: Businesses are obligated to repay the principal amount and interest on the loan, which can be challenging if cash flow is insufficient.
Tax advantages: Interest payments on debt financing are often tax deductible, providing a tax advantage for businesses.
Debt financing typically incurs higher interest costs compared to equity financing, leading to an increased overall cost of capital for businesses Additionally, debt financing requires fixed payments, which can strain cash flow Furthermore, reliance on debt may result in a loss of control for business owners, as lenders often impose restrictions and covenants.
Fixed repayment schedules and interest rates in business loans simplify financial planning, but lenders may impose restrictions that can limit existing shareholders' control over cash flow management.
Retained ownership: Debt financing | Dilution of ownership: Debt does not dilute ownership, allowing businesses to maintain full control while raising capital. financing does not result in dilution of ownership.
No sharing of profits: Lenders do not share in the profits of the business, allowing businesses to keep all profits for themselves.
Limited access to additional capital: Taking on too much debt can limit a business's ability to secure further debt financing.
(Source: CHELSKY and JEFF 2016) 1.3.3 Assess the pros and cons of equity financing
After assessing the pros and cons of debt financing, CHELSKY and JEFF (2016) have similar assessments with equity financing:
Table 1-2 Equity financing pros and cons comparison chart
Advantages of equity financing Disadvantages of equity financing
No obligation to repay: Equity financing does not require repayment, providing businesses with greater
Loss of control: Equity investors may require a say in the management of the business, leading to a potential cash flow flexibility and reducinngllos of control for existing financial risk shareholders.
Shared risk: Equity investors share in| Dilution of ownership: Equity
29 the risk of the business, aligning their financing involves selling shares of interests with the success of the] ownership, which dilutes the company ownership stake of existing shareholders.
Equity investors offer essential expertise and industry connections while providing resources that support business growth In return, they receive a share of profits through dividends, which decreases the amount of profits retained by the business.
Access to additional capital: As a business expands, equity financing offers the potential for accessing additional capital.
Cost of capital: While interest rates may be lower than debt financing, equity financing generally requires a higher rate of return to compensate for increased risk.
Increased credibility: Raising funds through equity financing can enhance a business's credibility, making it more attractive to other investors and lenders.
Time-consuming process: Equity financing involves preparing financial statements and documents for potential investors, which can be a time-consuming process.
Models involving the investment behavior of investors in the market 30 1 Theory of Planned BeliaVIOT .- ô+ +11 9k9 vk n gey 30
The Theory of Planned Behavior (TPB), introduced by Elisabeth Brookes in 2023, is a social psychology framework that elucidates how human behavior is influenced by attitudes, beliefs, and intentions This theory has found extensive application across diverse domains such as marketing, health, and environmental psychology.
According to TPB, human behavior is influenced by three factors: attitudes, subjective norms, and perceived behavioral control (Elisabeth Brookes, 2023)
Figure I-1 Theory of intended behavior TPB
The Attitude Toward Behavior (AB) factor reflects an individual's positive or negative evaluation of a behavior, influenced by psychological factors and situational contexts This assessment plays a crucial role in determining how one perceives a particular behavior Additionally, the subjective norm (SN), also known as social influence, highlights the impact of societal expectations on an individual's decision-making process.
Social influence plays a crucial role in shaping an individual's behavior, driven by the perceived social pressure from significant others, such as family, friends, and colleagues This concept, known as subjective norms, highlights how these close relationships can motivate or discourage specific actions Additionally, perceived behavioral control (PBC) reflects an individual's assessment of how easy or challenging it is to execute a behavior, influencing their intention to act When consumers accurately perceive their behavioral control, it can effectively predict their actual behavior Understanding these dynamics is essential for comprehending consumer actions and motivations.
The theory assumes that intentions are the best predictors of behavior. Intentions are determined by attitudes, subjective norms, and perceived
The Theory of Planned Behavior (TPB) suggests that a stronger intention significantly increases the likelihood of a behavior occurring However, it also recognizes that additional factors, including habits, emotions, and external constraints, can influence behavior outcomes.
Perceived behavioral control refers to the ease or difficulty of executing a behavior, influenced by the availability of resources and opportunities According to Ajzen, factors affecting behavioral control directly impact the likelihood of engaging in the behavior If individuals accurately perceive their level of control, then this perception can effectively predict their behavior.
The Theory of Planned Behavior (TPB) is utilized in diverse fields to analyze and forecast behaviors, including consumer, environmental, and health-related actions It aids in crafting interventions aimed at modifying behaviors by addressing individual attitudes, social norms, and perceived control Ultimately, TPB serves as a robust framework for comprehending the intricacies of human behavior, proving beneficial for researchers and practitioners across multiple disciplines.
The Theory of Reasoned Action (TRA) posits that behavioral intention serves as the primary predictor of actual behavior This intention reflects how strongly an individual plans to engage in a specific behavior and is shaped by two key elements: personal attitude and subjective norms.
Attitude represents a person's comprehensive assessment of a specific behavior, encompassing their beliefs regarding its positive and negative outcomes This evaluation significantly influences decisions, such as a consumer's perception of purchasing organic food, highlighting the importance of attitudes in shaping consumer behavior.
32 may be influenced by their belief that organic food is healthier and better for the environment, and their evaluation of those benefits ( Charlotte Nickerson, 2023)
Subjective norm encompasses the social influences that shape an individual's intention to engage in a specific behavior It highlights how a person's beliefs about the expectations of significant others, such as family and friends, impact their motivation to align with those beliefs For instance, a consumer's decision to purchase organic food can be significantly swayed by the perceptions and opinions of their social circle.
Perceived behavioral control significantly influences behavioral intention, as it reflects an individual's confidence in their ability to execute a specific behavior and their perception of the ease or difficulty associated with it For instance, a consumer's intention to purchase organic food can be shaped by factors such as the local availability and accessibility of organic products, along with their financial capacity to afford these items.
The Theory of Reasoned Action (TRA) model explains consumer behavior by highlighting the impact of attitudes and subjective norms on purchasing decisions For instance, when a consumer contemplates buying a hybrid car, their decision is shaped by their personal feelings about hybrid vehicles and the societal pressures or expectations surrounding the purchase.
Consumers who perceive hybrid cars as environmentally friendly, fuel-efficient, and reliable are more likely to intend to purchase them However, negative opinions from significant others, such as family and friends, can diminish this purchasing intention.
Consumer perception plays a crucial role in the intention to purchase hybrid cars; if they view buying a hybrid as easy and affordable, their likelihood of purchase increases Conversely, if they see the process as difficult or costly, their intention to buy may decrease significantly.
The TRA model highlights the importance of understanding consumer attitudes, subjective norms, and perceived behavioral control to effectively influence purchasing behavior Marketers can enhance positive perceptions of hybrid cars by promoting their environmental benefits and dispelling common myths, which can lead to a higher intention to buy Additionally, implementing pricing strategies that make hybrid cars more affordable can improve perceived behavioral control, further encouraging consumers to consider purchasing these vehicles.
The Theory of Reasoned Action (TRA) posits that behavioral intention (BI) serves as the primary predictor of behavior (B), with BI influenced by two key components: attitude (A) and subjective norm (SN) This relationship can be represented mathematically, highlighting the significance of both attitude and social influences in shaping our intentions and actions.
BI = f(A, SN) where "f" represents the function that relates attitude and subjective norm to behavioral intention.
RESEARCH METHOD 56c + +kEsveEseeseerreeree 43
Analysis ÍTaIWOTK .- - G1 1 HH HH Ho ng 43
The research process consists of three basic steps:
Step 1: Define the research objective, collect theoretical and secondary data and consider the study context.
Step 2: Build a research model and process data using STATA.
Step 3: Extract the research results, discuss these results, and make recommendations.
(Source:Suggested by author) 2.2 Analysis framework
The author proposes a research model tailored for investor decision-making regarding A-Partner investment products offered by Asia-Pacific Investment JSC (APEC) This model is developed by integrating key factors identified in previous studies on investor behavior, aiming to enhance the understanding of investment choices in the region.
Based on various research models such as MAVERICK (2022), A. Lusardi and O S Mitchell (2014) J.o jansson (2016), D.Swanson, E P Kim
Several factors influence investors' decisions, including investment goals, market conditions, investor experience, product benefits, profit expectations, investment risk, and behavior Understanding these elements is crucial for making informed investment choices.
2.2.1.1 Investment goals According to research on investment goals of, D.Swanson and E P Kim (2013) investment goals (IG) have a positive influence on investors’ investment decisions Individual investors' desired outcomes and objectives significantly impact the choices they make in their investment strategies. Depending on factors such as risk tolerance, financial situation, and personal preferences, investors set short-term or long-term investment goals These goals guide their decision-making process and determine the types of investments they are more likely to pursue Whether investors prioritize wealth accumulation, capital preservation, or social responsibility, their investment goals play a crucial role in shaping their investment decisions and portfolio allocation Understanding their investment goals and risk tolerance allows investors to make well-informed investment decisions that align with their desired outcomes.
HI: (+) Investment goals (IG) positively affect investors’ investment decisions
2.2.1.2 Market Factor Market Factors (MF) have a positive influence on investors' investment decisions Various market factors, including macroeconomic conditions, market volatility, interest rates, and the behavior of other market participants, can significantly impact investor behavior and the mobilization of investment capital According to J S Hastings, B C Madrian, and W L Skimmyhorn
Changes in market factors significantly impact investors' willingness to invest capital, which in turn affects the overall availability of investment funds essential for economic growth and development Research indicates that elements such as market volatility and interest rates are crucial in shaping these investment decisions.
Understanding how market factors influence investor behavior is essential for policymakers and market participants The behavior of institutional investors and hedge funds significantly impacts the allocation of investment capital Developing strategies that enhance the mobilization of investment capital is crucial for fostering sustainable economic growth.
H2: (+) Market Factor (MF) positively affects investors’ investment decisions
2.2.1.3 Product Benefits Product Benefits (PB) have a positive impact on investors’ investment decisions When clients are aware of the benefits associated with mobilizing investment capital, it influences their investment behavior and decision- making process Research on the importance of financial literacy indicates that increased awareness of these benefits leads to higher levels of investment, contributing to economic growth and development Factors such as financial literacy and financial education programs play a significant role in enhancing awareness and positively influencing investment behavior Individuals with higher financial literacy are more likely to invest and make informed investment decisions, while financial education programs have shown positive effects on investment behavior, especially for individuals from disadvantaged backgrounds Promoting awareness of the benefits of mobilizing investment capital, along with efforts to enhance financial literacy and provide financial education programs, can encourage investment behavior and support economic growth.
H3: (+) Product Benefits (PB) positively affect investors' investment decisions
2.2.1.4 Investment Experience Investment experience (JE) positively affects investors' investment decisions The theory of customer experience highlights the importance of past experiences in the decision-making process of mobilizing investment capital Customers are more inclined to invest in a product or service if they have had positive experiences with similar offerings in the past The prospect theory suggests that individuals evaluate potential gains and losses based on their previous experiences Positive investment experiences, such as significant returns, increase the likelihood of future investments, while negative experiences, such as losses, make individuals more hesitant to invest. Additionally, According to H Subagio, S.H Satoto, S.I Ediningsih (2020) research indicates that customers who have positive experiences with financial advisors or investment professionals are more likely to follow their recommendations in the future, whereas those with negative experiences are less likely to do so Understanding the influence of investment experience on investor behavior can help shape strategies to enhance customer satisfaction and foster positive investment decisions (Siska Atmaningrum, Dwi Sunu Kanto, 2021)
H4: (+) Investment experience (IE) positively affects investors’ investment decisions
2.2.1.5 Profit Expectation Profit expectation (PE) positively affects investors' investment decisions The client's expectation of profit plays a crucial role in their decision to mobilize investment capital According to A E.Bernardo and I.Welch (2004) Clients anticipate receiving a return on their investment that aligns with the level of risk they are willing to take Research indicates that
Profit expectations among investors are influenced by various factors, including investment type, market conditions, and investor demographics Wealthy investors typically have higher profit expectations for stocks due to their greater risk tolerance and desire for substantial returns Additionally, those investing in initial public offerings (IPOs) often anticipate higher profits linked to significant growth potential Market conditions play a crucial role as well, with investors in a bull market expecting rapid growth, while those in a bear market prioritize capital preservation Understanding these profit expectations is essential for developing investment strategies that align with client goals and desired outcomes.
HS: (+) Profit expectation (PE) positively affects investors' investment decisions.
2.2.1.6 Investment Risk Investment risk (IR) negatively affects investors’ investment decisions. The theory of customers’ risk tolerance on capital mobilization states that customers’ willingness to take risks when investing capital is influenced by their individual characteristics, as well as external factors According to Y. Huang and J R Ritter (2015), factors such as age, income, education, and investing experience shape customers' risk tolerance Additionally, the characteristics of the investment product, current economic conditions, and overall market sentiment also influence risk tolerance Research has demonstrated that customers with high risk tolerance are more inclined to invest in high-risk, high-reward assets like stocks, while customers with low
Understanding customers' risk tolerance is vital for effectively designing and marketing investment products, as 47% prefer low-risk, low-reward assets like bonds External factors, such as the regulatory environment and economic conditions, significantly influence this risk tolerance During economic downturns or market volatility, customers typically become more risk-averse, opting for safer investments to protect their capital Conversely, in periods of economic growth and stability, they may show a greater willingness to take risks Recognizing how investment risk affects decision-making is essential for tailoring products and marketing strategies to align with customers' risk preferences.
H6: (-) Investment risk (IR) negatively affects investors’ investment decisions.
2.2.1.7 Investment behavior Investment Behavior (IB) positively affects investors’ investment decisions The theory of investment behavior factor on investment decisions emphasizes the significant role of investors' behavior in shaping their investment choices Research has demonstrated that investors' behavior has a notable impact on their investment decisions For instance, investors with aggressive investment behavior are more inclined to invest in high-risk, high- reward assets like stocks, while conservative investors prefer low-risk, low- reward assets such as bonds Designing investment products and implementing effective marketing strategies should consider investors' unique investment behavior External factors, including regulatory policies and economic conditions, also influence investment behavior During economic
During periods of market volatility, investors typically become more risk-averse, favoring low-risk investments to protect their capital In contrast, during economic upswings with low volatility, they are more inclined to take risks Understanding how investment behavior affects decision-making is essential for creating investment products and developing marketing strategies that align with these behavioral patterns.
H7: (+) Investment Behavior (IB) positively affects investors’ investment decisions.
The legal framework is grounded in the Investment Decision Model, which takes into account several key factors that affect an investor's decision-making These factors include investment objectives, risk tolerance, perceived benefits of the product, personal experience, and profit expectations.
Research ImetẽO(S - . ô+ + E1 1E 91 91 E1 3 vn nh ngư 58
2.3.1 Qualitative research The research methodology involves the implementation of qualitative research to identify, supplement, and refine the observed variables used to measure the concepts in the model The group discussion technique is utilized with selected subjects to reflect the characteristics of the observed sample set but through a convenient method The qualitative research targets subjects with investment experience and knowledge, and the content of the group discussion centers on the components that influence investment intention in challenging market times The focus is on reviewing and refining the words, semantics, and content for each observed variable in the scale that comprises the components in the model.
The procedure involves individual discussions with participants to share insights and assess the questionnaire's content The qualitative research concludes when all subjects reach a consensus Subsequently, the findings from these discussions are synthesized, leading to adjustments in the quantitative questionnaire.
The discussions led to a re-evaluation of the scale's content, with qualitative survey participants reviewing their results to identify necessary adjustments This evaluation focused on the clarity of the scale's content and the need to add or remove variables Following the adjustments to the observed variables, all qualitative survey participants reached a consensus on the key factors influencing investment decisions for APEC company products.
The qualitative research involves 110 observed variables, and basic customer information is collected, such as the subject's identifier, full name,
The survey targets individuals aged 58, focusing on their city of residence, gender, investment experience—including the types of products they have invested in and the duration of their investments—and their knowledge of the business and its offerings Furthermore, it evaluates whether respondents have prior investment experience in a business context.
Step 1: The research author learns the information and data to be collected for the topic.
Step 2: Based on previous research documents and qualitative research results, the research author proceeds to build a survey table in accordance with the objectives and research hypotheses that have been proposed previously.
Step 3: The author researches and edits words and science to make the survey more reasonable and easy to understand, thereby giving a complete survey.
Layout: The survey consists of 3 parts:
Part 1: Personal information of survey participants, including questions about gender, address, age, experience, seniority The respondents ticked the answers corresponding to your information.
Part 2: Qualitative survey of the types of investments and the amount invested in APEC.
Part 3: Comments on factors affecting investment decisions of investors To answer this part, respondents ticked the appropriate box on a 5-
59 point Likert scale: 1 — Strongly disagree, 2 — Disagree, 3 — Neutral, 4 — Agree,
Quantitative research begins with a survey, which is developed from a calibrated questionnaire created during the qualitative research phase This survey serves as the official tool for data collection, allowing researchers to assess scale reliability and validity while evaluating model appropriateness The careful development of scales and surveys is crucial for maintaining methodological rigor and creating effective research instruments.
The questionnaire is designed and tested through several stages to ensure the collection of necessary information for the data analysis process.
Stage 1: Building a raw questionnaire based on the information to be collected in the theoretical research model and related studies
Stage 2: Evaluating the content of the questionnaire by checking the trust level of the questions The assessment is done by calling directly to the interview and filling out the questionnaire for the subjects who are professional investors, long-time customers, and have known APEC's products to assess the extent of factors affecting their investment decisions.
Stage 3: Editing the content of the questionnaire and completing the survey questionnaire, then sending it directly and online via email to the subjects the author is researching related to customer behavior, factors affecting customers’ investment decisions on the company's A-Partner products, and from there evaluating similar products in the market.
This article outlines a test aimed at identifying the factors influencing investment decisions in equity products for project implementation The research is conducted in two phases: Phase 1 involves preliminary quantitative research, while Phase 2 focuses on formal quantitative research.
In the initial phase, a preliminary quantitative study was conducted using a questionnaire with observed variables, targeting a sample size of 30 participants The study aimed to refine the sentences and identify key variables To implement this, reliability testing was performed using the Cronbach Alpha coefficient, resulting in the exclusion of variables with low total correlation.
Phase two: Formal quantitative research is carried out with a Questionnaire of observed variables
Phase two includes the following main tasks:
The preliminary evaluation of the scales utilized the Cronbach Alpha reliability test, leading to the exclusion of variables with a total variable correlation below 0.3 and components exhibiting a Cronbach Alpha reliability coefficient of less than 0.6.
(2) Testing the value and reliability of latent variables through exploratory factor analysis (EFA)Variables with small weights or extracted on many factors with low difference will be excluded.
(3) Correlation analysis and multiple linear regression analysis.
(4) Analysis of variance (ANOVA) and deep analysis of ANOVA.
The research utilizes data gathered from direct surveys conducted via questionnaires targeting investor customers to effectively introduce and leverage insights about A-Partner products from Asia-Pacific Investment JSC.
2.3.3.1 Methods of collecting secondary information Including journal articles and scientific reports in the industry, outside the industry, scientific works, mass information collected via the internet, in schools, bookstores
2.3.3.2 Primary data collection method The main information collection tool is a questionnaire used to poll and collect opinions of research subjects, in which:
The question form is a structured format that includes predefined types of questions and answers for respondents to select from This includes binary questions, single-choice questions, and multiple-answer questions, with options for evaluation based on a specified scale The question content is divided into two primary components.
Part 1: Designed to collect information related to factors affecting customers’ investment decisions for Asia - Pacific Investment JSC's A-partner products.
Part 2: Design the scale to collect descriptive information about the object, participate in answering and screening the object from the country.
The quantitative research design process is divided into two phases:
Phase 1: Coding variables and conducting a general survey to assess the reliability of the model and remove inappropriate variables.
Table 2-2 Coding research variables Observable variable Encode
(Source: Compiled by the author)
Phase 2: The research conducts a formal quantitative study Firstly, they will directly contact the investors to introduce the product (A-Partner). When the customer agrees, a face-to-face interview will be conducted and a questionnaire will be filled out After achieving the target number of samples,
63 the research team will analyze the collected data through the SEM structural model using SPSS 26.0 software and finally report the research results.
Currently, there are many different research samples based on different points of view as follows:
There is a view that the population size must be larger than 200 samples to obtain a reliable estimate (The analysis of covariance structures: Goodness-of-fit indices, 1983, pp 325-344)
To determine the minimum number of samples required for analysis, it is suggested that the total number of observed variables be multiplied by a factor of 5 With 40 observed variables in this study, a minimum of 200 samples is necessary (Boomsma, 1993).
According to another study, the sample size is also calculated based on the formula: JAMES CHEN, 2021)
- N is the number of research samples for the research paper.
- mis the number of independent variables of the study.
RESEARCH RESULTS AND DISCUSSION 71 3.1 Company overview and research prOdUCfS - - ô+5 + + +++*++seeeseeeezs 71 3.1.1 Company OVTVICW . TH HH HH ng 71 3.1.2 Investment product OV€TVICW .- - Gv ng ng ng cư 73 3.2 DescrIptIon SfAfISẨICS - << 11 HH nà 75 3.3 Reliability assessment of the measurement scaÌe .- ô- -s ô+ ++s+++ 78 3.3.1 Investment ỉOaèS .- . - ô+ 1 1v ng ng ngư 78 3.3.2 Market Factor - << 1n HH 79 3.3.3 Product Benefits - - - - kkc S111 0 vớ 79
Correlation analysis 8h
The linear correlation between two variables is characterized by data points that align along a straight line when plotted on a graph According to Gayen (1951), the Pearson correlation coefficient (r) is utilized in statistics to measure the strength of the linear relationship between two quantitative variables It is important to note that Pearson correlation analysis is not applicable if one or both variables are non-quantitative, such as qualitative or binary variables.
The Pearson correlation factor r has values ranging from -1 to 1:
- The more r progresses towards 1, the closer it is Progress to 1 is positive; progress to -1 is negative.
- The more r advances towards 0, the weaker the linear correlation.
- Ifr=1, which 1s an absolute linear correlation, when represented on the scatter chart as shown above, the representation points are entered back into a straight line.
When the correlation coefficient (r) is equal to 0, it indicates the absence of a linear correlation between two variables This scenario can manifest in two distinct ways: either there is no relationship whatsoever between the variables, or they may be related through a non-linear connection.
After identifying two variables with a significant linear correlation (p-value less than 0.05), we assess the correlation's strength or weakness by examining the absolute value of r, as outlined by Andy Field (2009).
- Irl < 0.3: weak correlation e lrl 0.5: strong correlation
Table 3-13 Analyze the correlation between the representative variables in the model
** Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
The correlation analysis indicates that none of the variable pairs exhibit a significant coefficient, with all values exceeding 0.5 Consequently, these variables lack a linear correlation, prompting the decision to exclude them from the regression analysis.
The analysis of the Pearson Correlation factor reveals that the following pairs of variables exhibit a significant linear correlation at the 99% confidence level: (ID;NI), (D;N3), (ID;N4), (ID;N6), (N1;N3), (N1;N4), (N2;N3), (N2;N5), (N2;N6), (N3;N4), (N3;N5), (N3;N6), (N4;N5), (N4;N6), and (N5;N6) This correlation is significant at a 1% significance level (0.01).
The analysis of the Pearson Correlation reveals that the variable pairs (ID;N5) and (N2;N4) exhibit a linear correlation at a 95% confidence level, which corresponds to a significance level of 5% (α = 0.05).
Specifically, the independent variables will have a relationship with the dependent variable which is a private decision as follows:
- Investment risk (IR) negative impact with strong correlation with investment decision (Pearson Correlation = -0.539)
- Investor's context (IC) positive impact and weak correlation with investment decision (Pearson Correlation = 0.195)
- Profit expectation (PE) positive impact and mean correlation with investment decision (Pearson Correlation = 0.455)
- Investment experience (IE) positive impact with strong correlation with investment decisions (Pearson Correlation = 0.548)
- Investment information (II positive impact and weak correlation with investment decision (Pearson Correlation = 0.219)
- Product Benefits (PB) positive impact and weak correlation with investment decision (Pearson Correlation = 0.259)
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In research, we often have to test hypotheses about the relationship between two or more variables, including one dependent variable and one or more independent variables.
Univariate regression equation: Y = B0+ BI*NI + B2*N2 + B3*N3 + B4*N4 + B5*NS5 + B6*N6 + €
Investment Decision = B0+ BI* Investment Risk + B2 Investor's context + B3* Profit Expectation + B4* Investment Experience + Š*Investment information + B6* Product Benefits + ¢
- Bk: is the regression coefficient.
(The variable selection is based on the rotation matrix EFA)
Table 3-14 Summary of linear regression model
Mode |R R Square | Adjusted R Std Error of | Durbin-
| 652° 425 391 64924 1.375 a Predictors: (Constant), N6, N1, N5, N3, N2, N4 b Dependent Variable: ID
The coefficient of determination, known as R², is a key metric for assessing the fit of a linear regression model A high R² value indicates that the majority of data points are closely aligned with the regression line, while a low R² suggests that the data points are widely dispersed from the line This important statistic can be found in the Model Summary table.
R Square and Adjusted R Square values range from 0 to 1, indicating the strength of the relationship between independent and dependent variables A value closer to 1 signifies that the independent variables provide a greater explanation of the dependent variable, while a value nearer to 0 indicates that they offer minimal explanatory power.
The adjusted R² value of 0.391 in the regression model analysis indicates that there is no causal relationship between the regression model fit and the study's value However, this interpretation may be misleading, as the evaluation of the R² value is significantly influenced by factors such as the research area.
98 research nature, sample size, number of variables participating in regression and results of other indices of the regression, etc.
In the Durbin-Watson test, a significance level of 1% for a sample size of n = 100 and k = 6 yields a lower critical value (dl) of approximately 1.485 and an upper critical value (du) of about 1.535 These critical values are essential for assessing the presence of autocorrelation in the residuals of a regression model.
The Durbin-Watson value of 1.375 indicates that the error terms are positively correlated, falling within the range of 0 to dl This suggests that the assumption of first-order series autocorrelation is not violated (Yahua Qiao, 2011).
We need to evaluate the model fit accurately through hypothesis testing To test the regression model fit, we hypothesize H0: R* = 0 The F test is used to test this hypothesis Inspection results:
Sig < 0.05: Reject the hypothesis HO, that is, R* # 0 statistically significant, the regression model is suitable.
Sig > 0.05: Accept the hypothesis H0, that is, R? = 0 statistically significant, the regression model is not suitable.
In SPSS, the data of the F-test are taken from the ANOVA table.
Model Sum of df Mean F Sig.
Residual 43.416 103 422 Total 75.455 109 a Dependent Variable: ID b Predictors: (Constant), N6, N1, N5, N3, N2, N4
The ANOVA table presents the F test results, which are essential for assessing the fit of the regression model With an F-test significance value of 0.000, which is less than the threshold of 0.05, we conclude that the regression model is appropriate and effectively fits the data.
We will assess the significance of the regression coefficient for each independent variable in the model using the t-test, with the null hypothesis stating that the regression coefficient of the independent variable Xi is zero The number of hypotheses tested will correspond to the number of independent variables present in the model.
Sig < 0.05: Reject the hypothesis HO, which means that the regression coefficient of the variable Xi is statistically different from zero, the variable
X1 has an impact on the dependent variable.
Sig > 0.05: Accept the hypothesis HO, which means that the regression coefficient of the variable Xi is zero statistically significant, the variable Xi has no impact on the dependent variable.
In regression analysis, two key coefficients are typically present: the unnormalized coefficient (referred to as B in SPSS) and the normalized coefficient (known as Beta in SPSS) Each coefficient serves a distinct purpose in the interpretation of the regression results.
100 governance implications of the regression model To understand when to use which regression equation, you can see the article Difference between normalized and unnormalized regression coefficients.
A negative regression coefficient (B or Beta) indicates that the independent variable adversely affects the dependent variable, while a positive coefficient signifies a beneficial impact To assess the strength of the independent variable's influence on the dependent variable, we examine the absolute value of Beta; a larger absolute value denotes a stronger effect For more information, refer to the article on Regression coefficient B and Negative Beta in SPSS analysis.
In SPSS, the t-test data is derived from the Coefficients table If an independent variable shows no statistical significance in the regression results, we can conclude that it does not influence the dependent variable, negating the need for further variable type and regression analysis.
The Coefficients table gives us the t test results to evaluate the hypothesis of significance of the regression coefficient, the VIF index to evaluate multicollinearity and the regression coefficients.
Model Unstandardized Standar | t Sig | Collinearity
The t-test significance values for variables N2, N3, and N5 are 0.581, 0.078, and 0.958, respectively, all exceeding the 0.05 threshold Consequently, these variables are not significant within the regression model, indicating that they do not have an effect on the dependent variable ID.
All remaining variables, including N1 and N4, exhibit statistical significance with t-test significance values less than 0.05, indicating their impact on the dependent variable ID The regression analysis reveals that the independent variable N4 positively influences the dependent variable, while the independent variable N1 negatively affects it.
N1: (-) Investment risk (IR) negatively affects investors’ investment decisions (Accept)
N2: (+) Investor's context (IC) positively influences investors’ investment decisions (Remove variable)
N3: (+) Profit expectation (PE) positively affects investors’ investment decisions (Remove variable)
N4: (+) Investment experience (IE) positively affects investors’ investment decisions (Accept)
N5: (+) Investment information (II) positively influences investors’ investment decisions (Remove variable)
N6: (+) Product Benefits (PB) positively affect investors' investment decisions (Remove variable)
According to Table 3.17, the variance inflation factor (VIF) values are all below 2, indicating that the independent variables in the research model are not closely related This absence of multicollinearity ensures that the relationships between the independent variables do not influence the explanatory power of the regression model.
From the regression coefficients, we can build two normalized and unnormalized regression equations in the following order:
3.5.2.4 Frequency diagram of the standardized histogram:
Residuals may not follow a normal distribution for reasons such as incorrect model usage, non-constant variance, insufficient number of residuals
103 for analysis, etc Therefore, we need to conduct a variety of surveys The simplest way to investigate is to build a histogram of the residual histogram below.
Figure 3-2 Frequency diagram of the standardized histogram.
Dependent Variable: ID ew = 7 BBE-tô z1 ‘Std Dey =0 172
The histogram analysis reveals that the distribution of residual values is approximately normal This conclusion is supported by the mean, which is 7.89E-16 (or 0.00000), indicating it is close to 0, and the standard deviation of 0.972, which is near 1 Therefore, the residual distribution aligns with the characteristics of a standard normal distribution, confirming that the assumption of normality for the residuals is not violated.
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According to Pituch & Stevens (2016), a good condition for confirming no variance is indicated by residual data points in a scatter plot that primarily fluctuate between -3 and 3 The results from the scatter plot demonstrate that the residual data points create a cloud of consistent magnitude along the 0 coordinate line, remaining within the -3 to 3 range.
3, thus assuming the erroneous changes are not violated.
3.6.1 Independent Sample analysis for sex variable
Table 3-17 Independent Sample analysis for sex variable
Levene's Test | t-test for Equality of Means for Equality of Variances
F Sig | t df Sig Mean Std 95% Confidence
(2- Differe | Error Interval of the tailed) | nce Differe | Difference nce Lower Upper
The sig F test result of 0.358, which is greater than 0.05, indicates no difference in variance between male and female groups Consequently, we refer to the t test results under the Equal variances assumed row, where the sig test t value of 0.983 also exceeds 0.05 This leads us to accept the null hypothesis (HO), suggesting that there is no significant difference in the mean investment decisions between male and female investors.
3.6.2 One-way ANOVA test for age difference
To categorize age groups in a sample of 100 investors, we can use various methods depending on the research question and the data distribution.
A prevalent method for categorizing data is through equal interval ranges, which segment the sample into uniformly sized groups based on the value range For instance, we could classify a sample of 100 investors into three distinct age groups.
106 e Under 35 years old: 33 investors (ages 18-34) e Between 35-50 years old: 34 investors (ages 35-49) e Over 50 years old: 33 investors (ages 50 and above)
This method ensures that each age group has a similar number of investors and can be useful in comparing demographic characteristics across different groups.
Table 3-18 Levene test results of the variable age distribution of investment
Test of Homogeneity of Variances
Based on Median 4.518 2 107 013 Based on Median and | 4.518 2 85.240 | 014 with adjusted df
Sig test Levene equals 0.003 < 0.05, there are variances between age groups, we will use Welch test results in Robust Tests of Equality of Means table.
Table 3-19 Robust Tests of Equality of Means table
Robust Tests of Equality of Means
Sig Welch test equals 0.068 > 0.05, that is, there is no difference in mean F_HL between different age groups Thus, there is no difference in investment decisions of different age groups.
Figure 3-5 Line graph showing the relationship between age mean and investment decisions
Under 35 years old Between 35-50 years old Over 50 years old
The graph illustrates a positive correlation between age and investment inclination, as indicated by the Mean column value in the Descriptives table This trend suggests that older investors are more likely to engage with the product.
3.6.3 Test differences in APEC investment experience of subjects using one-way ANOVA method
Table 3-20 Levene test results of the variable investment experience in
Test of Homogeneity of Variances
Based on Median 479 2 107 621 Based on Median and_ | 479 2 97.757 |.621 with adjusted df
Sig test Levene is equal to 0.222 > 0.05, the variances of the groups have the same value, so we will use the ANOVA table.
Sum of df Mean F Sig.
Sig F-test equals 0.649 > 0.05, accepting hypothesis HO, that is, there is no mean difference F_HL between investment experience of different
110 investors Thus, there is no difference in investment decision among experienced investors.
Figure 3-6 The line graph shows the relationship between average investment experience at APEC companies and investment decisions.
Never invested Researching on investment Invested in several channels in the market EXPERIENCE
The analysis reveals a significant trend where the Mean column value in the Descriptives table indicates a sharp increase among individuals studying investment, followed by a decline for those with investment experience This pattern suggests that experienced investors may exercise greater caution in their decision-making processes.
3.6.4 Check the object's investment seniority by one-way ANOVA
Table 3-22 Levene test results of the investment seniority variable
Test of Homogeneity of Variances
Based on Median 4.202 5 104 002 Based on Medianand | 4.202 5 73.506 |.002 with adjusted df
Sig test Levene is equal to 0.00 < 0.05, there is no difference in variance between investment seniority, we will use F test results in ANOVA table.
Table 3-23 Robust Tests of Equality of Means table
Robust Tests of Equality of Means
Sig test F is 0.001 < 0.05, accepting hypothesis HO, that is, there is a mean difference in ID between different age groups Thus, there is a
112 difference between the seniority of the investor and the decision to invest in the product.
Figure 3-7 Line graph showing the relationship between average seniority and investment decision
Never invested |nvasladlass investedfromo westad from 1 Invest! than G month: months 7 year year-2years years -
The line graph illustrates the correlation between average investment decisions and investor seniority, with data derived from the Mean column in the Descriptives table As investor seniority rises, the line exhibits an upward trend, indicating that more experienced investors are more likely to invest in this product.
New investors with 6 months - 1 year experience tend to participate more in investment research
Discussion Of model T€SUẽfS - <6 + 33+ 1331 +2 EEÊvEEEeereeeersrsererreree 114
The group has developed a model identifying seven key factors that influence an investor's decision to invest in A-Partner: investment goals, market factors, product benefits, investment experience, profit expectations, investment risks, and investment behavior.
The study conducts preliminary research involving 30 investors to evaluate the group's draft scales This process aims to test the reliability of the scales, allowing for the elimination of unsuitable variables Subsequently, the official scale is developed, and the questionnaire is finalized.
The study utilized selective sampling through an online survey, engaging with consultants via a questionnaire tool to gather research data.
300, contacted through phone calls and consultations After direct survey and Internet survey, we collected 110 satisfactory tables From there, analyze the results with SPSS 26 software.
Evaluation of Cronbach's Alpha reliability on the scales of 7 influencing factors with 39 observed variables all gave results with high confidence coefficient Sig > 0.05.
After performing exploratory factor analysis (EFA) and rotating the factors six times, I identified three consistent factors: Investment Goals, Market Factors, and Investment Behavior Consequently, the research model has been revised to include five factors that influence an investor's decision to invest in A-partner.
NI: (-) Investment risk (IR) negatively affects investors' investment decisions.
N2: (+) Investor's context (IC) positively influences investors’ investment decisions.
N3: (+) Profit expectation (PE) positively affects investors’ investment decisions.
N4: (+) Investment experience (IE) positively affects investors’ investment decisions.
NS: (+) Investment information (II) positively influences investors’ investment decisions.
N6: (+) Product Benefits (PB) positively affect investors' investment decisions.
Testing the correlation between the independent and dependent variables with Pearson's test, the independent variables are eligible to continue to be included in the regression model.
The t-test significance values for variables N2 (Investor's context), N3 (Profit expectation), N5 (Investment information), and N6 (Product Benefits) are 0.581, 0.078, 0.958, and 0.527, respectively, all exceeding the 0.05 threshold Consequently, these factors are not significant within the regression model Following the exclusion of these four variables, the regression model has been updated accordingly.
The regression model with adjusted R? was 39.1%, that is, the model with the independent variable explained 39.1% of the data fit.
The independent sample t-test analysis revealed no significant differences in investment decisions based on gender Additionally, the One-way ANOVA analysis indicated that investment experience and age do not significantly impact investors' decisions regarding partnerships.
An analysis of one-way ANOVA reveals that investment decisions vary significantly based on investor seniority Specifically, as seniority increases, investors show a greater tendency to invest in A-PARTNER.
The study on "Investment risk" revealed significant insights, demonstrating its strong influence on the multivariate research model Aligning with Donna Cirillo's 2023 findings, factors like loss aversion, emotions, and overconfidence negatively affect investors' decisions As a result, understanding risk perception is crucial for investors To reduce risks, it is essential for investors to acquire extensive knowledge, stay informed, and thoroughly understand legal documents.
Changes in the investor's background did not produce the expected quantitative results due to a lack of statistical significance, diverging from the findings of Vo Thi Hieu, Bui Huu Phuoc, and Bui Nhat Vuong (2020) The present investor landscape, characterized by customers in the real environment, may influence their investment outcomes.
116 psychological dispositions I hold high expectations for delving into the research angle concerning the client's context and environment in future investigations.
The "Profit expectation" variable did not show statistical significance, contrary to initial expectations This finding suggests that further investigation is necessary, including a reassessment of the questionnaire and the surveyor's file in future studies.
The "Investment experience" variable positively influences investment decisions; however, unlike the findings of Thai Van Dai and Tran Minh Trang (2019), this research did not find statistical significance for this variable Understanding the impact of investment experience on decision-making helps identify opportunities for improvement for both investors and businesses.
"Investment experience" refers to both the length of time investors have engaged in investing and their level of expertise in the field Assessing this experience is crucial for the model, as it underpins further research into investment choices, the selection of companies for analysis, and essential sample criteria Additionally, it is important to include experienced individuals as participants in the study.
In contrast to the findings of D Kim & E P Swanson (2013), the investment information variable related to product profits and customer benefits did not show statistical significance Nevertheless, investment product information remains a focal point for investors, highlighting the ongoing interest in such data despite the lack of significance in this particular study.
Disparities in product information may contribute to the inconsistencies observed in the model Consequently, this study has not established a specific plan for the research model Future research efforts will require necessary adjustments.
Regarding the "Product Benefits" variable, distinct from the findings of
J S Madrian, B C Skimmyhorn and W L Hastings (2013), the variable within the model failed to demonstrate statistical significance Assessing the benefits of the product may prove unsuitable for the research subject The representation of product benefits within the survey instrument might have engendered misinterpretation among investors Given that the product pertains to the confluence of finance and real estate, the variable has not been adequately integrated into the research model, as per my calculations Future research should target alternative survey subjects more aligned with the research model.
4.1 Orientation and strategy of APEC for the product A partner in the coming time
POLICY IMPLICATIONS c 7c Series 119
Orientation and strategy of APEC for the product A partner in the coming
Investors prioritize stable profit levels and consistent returns when assessing investment opportunities, making these factors crucial in their evaluation process.
In addition to profit, they also prioritize safety Investors want some form of guarantee or security for their invested capital.
Investors prioritize transparency and access to reliable, regularly updated information when evaluating investment opportunities This clarity enables them to make informed decisions Additionally, they are drawn to ventures with strong potential for growth and profitability, seeking out opportunities that show promising prospects.
Investors prioritize specific sectors that present favorable market conditions, significantly influencing their decision-making process They are particularly attracted to companies with a strong reputation and positive brand image, viewing these brands as reliable and trustworthy investment opportunities.
Investors prioritize maintaining control over their invested capital, seeking opportunities that enable active participation in decision-making processes For instance, advantages gained from the General Partner's involvement can significantly enhance their investment experience.
Meeting of Shareholders provide investors with a sense of control and involvement.
Investors are more likely to invest in reputable companies with a history of success, as they tend to trust businesses that consistently deliver positive results from their core operations This reliability and stability make such enterprises more appealing to potential investors.
Understanding investor demands is essential for businesses and investment institutions By aligning their offerings with these expectations, they can effectively attract and retain discerning investors Key factors such as profit stability, safety, transparency, investment potential, promising sectors, reputable brands, capital control, and strong business performance significantly enhance the appeal of investment opportunities and build investor confidence.
A-Partner's core values as an investment opportunity revolve around several key aspects.
The A-Partner offers a redeemable preferred stock mortgage, providing investors with security comparable to a bank savings deposit without a set maturity date, ensuring both stability and potential returns on their investment.
A-Partner offers a compelling investment opportunity by prioritizing value addition and profit generation, ensuring that investors can anticipate growth in their investments over time This alignment of interests fosters a shared commitment to the project's success.
Investing in real estate offers a reciprocal benefit, as investors acquire ownership of valuable properties that have the potential to appreciate over time, creating a tangible and lucrative opportunity for financial growth.
A-Partner is supported by a well-established and reputable corporation, offering investors enhanced security and reliability This backing ensures that their investments are protected by a strong and trustworthy entity.
The A-Partner project is executed under a well-defined plan and is managed by APEC, ensuring professional and efficient investment practices that minimize risks and maximize returns.
Finally, A-Partner is backed by secure and legally binding securities trading contracts This provides investors with clear rights and protections, enhancing the overall security and transparency of their investment.
Together, A-Partner core values create an attractive investment opportunity that combines stability, profitability, tangible assets, reputational support, professional management and legal protection physical
Investing in real estate projects offers substantial potential for investors, leveraging both real estate appreciation and value growth As the real estate market expands, investors can anticipate an increase in their investment value, leading to promising returns.
Furthermore, the potential for profits in these projects is substantial, ranging from 60% to 150% This presents an attractive opportunity for investors seeking high returns on their investment.
The potential for significant investment returns is enhanced by the availability of a large land fund that can be purchased at low prices This advantageous entry point positions investors to maximize their profits as land values appreciate over time.
The investment opportunity capitalizes on APEC's operational framework, allowing investors to optimize different facets of their business systems This encompasses the effective use of their HR system for product development, the application of their construction system for efficient project execution, and the advantages of their established business system for enhanced operational efficiency.
Investing in real estate projects presents a unique opportunity for dual benefits, including real estate value appreciation and substantial profit potential This investment approach provides access to a vast land fund at a low cost, enhanced by APEC's operational expertise across various systems Together, these elements form a compelling investment proposition with significant growth prospects.