INTRODUCE
BACKGROUND OF THE STUDY
Vietnam is an active member of key international organizations such as ASEAN, APEC, ASEM, and the World Trade Organization, highlighting its commitment to global economic integration As the country embraces a policy of market openness, Vietnamese firms are compelled to innovate and adopt advanced technologies This strategic focus not only aims to boost export performance but also enhances the quality and competitiveness of products in both domestic and international markets.
Despite the modest long-term investment in Vietnamese enterprises, companies primarily rely on commercial banks for funding their business plans Small and medium-sized enterprises, particularly newly established ones lacking sufficient collateral and reputation, face significant challenges in securing bank loans A survey by the Vietnam Academy of Social Sciences reveals that small and micro-sized businesses represent 96.7 percent of all businesses in the country In this context, leasing emerges as a highly advantageous solution, gaining traction in the global market Financial leasing offers numerous benefits, alleviating the challenges businesses encounter in raising finance and enabling access to modern equipment and technology.
Japan boasts 240 finance leasing organizations, with nearly 97% of businesses utilizing these services, while China has over 3,200 financial leasing companies and approximately 65% adoption among businesses (Construction Economics Journal, No 4/2019) This indicates that financial leasing presents a promising market opportunity However, in Vietnam, the growth of financial leasing has not matched its potential, with only a small number of businesses accessing these services for operational and investment funding Despite the industry being present in Vietnam for over 15 years, only ten financial leasing companies are currently operational, highlighting that this concept remains relatively new for many organizations.
In order to contribute more opportunities, the author chose the topic "Factors affecting the decision to employ financial leasing services for small and medium-sized firms in
The research and analysis department has conducted a study on the behavior of small and medium-sized businesses (SMEs) in Ho Chi Minh City that utilize Financial Leasing services This study aims to provide insights for the Board of Directors of Financial Leasing Company, identifying key factors that influence SMEs' decisions The findings will assist in developing strategies to attract new customers, enhance customer retention, and increase market share in the competitive landscape.
OBJECTIVE
This study aims to identify the key characteristics influencing small and medium-sized businesses in Ho Chi Minh City (HCMC) to adopt financial leasing services, while also analyzing the impact of each factor By providing actionable recommendations, the research contributes to the growth of the financial leasing market and supports the development of Vietnam's economy.
The specific objectives for achieving the overall goal are as follows:
- Determining the elements that influence small and medium enterprises’ owner’s decisions to employ financial leasing services in Ho Chi Minh City (HCMC)
- Evaluating the impact of factors influencing the decision to employ financial leasing services for small and medium enterprises in HCMC
- Proposing recommendations to help the Finance Leasing market grow and meet customer demand.
RESEARCH QUESTIONS
To achieve higher targets, the study explores key questions regarding small and medium enterprises (SMEs) in Ho Chi Minh City and their decisions to utilize financial leasing services for funding It investigates the factors influencing these decisions and examines how these factors impact the choice to engage in financial leasing Additionally, the study provides recommendations for financial leasing organizations to enhance customer attraction and retention.
SUBJECT AND SCOPE
Subject: Factors affecting the decision to use financial leasing services for small and medium enterprises in Ho Chi Minh City
Space: Financial leasing companies with large outstanding balance in HCMC as of 2019, namely: CILC, VCB Leasing, Vietinbank leasing, Sacombank Leasing, BIDV Leasing (BIDV - Sumi Trust), VILC
A survey will be conducted to identify small and medium enterprises that require investment in equipment, machinery, and working capital, as well as those with outstanding loans from financial leasing companies The focus will be on representatives of these businesses who are authorized to make financial decisions and select loan options.
METHODOLOGY
The thesis employs both qualitative and quantitative research methods to investigate the factors influencing the decision to utilize financial leasing services among small and medium enterprises in Ho Chi Minh City Initially, qualitative research is conducted to identify and analyze these influencing factors, followed by the development of scales for quantitative research The quantitative phase utilizes SPSS to analyze questionnaire data, enabling the redefinition of the factors affecting the use of financial leasing services and measuring the impact of each factor on decision-making.
- Evaluate the reliability of the scales by Cronbach's Alpha test
The thesis employs a variety of methods, including descriptive statistics to categorize data based on specific characteristics, comparative analysis to evaluate the differences between theoretical models and practical applications, and meta-analytic techniques to analyze and synthesize pertinent data throughout the research process.
SIGNIFICANCE OF THE RESEARCH
The research results of the thesis have scientific and practical significance shown in the following main aspects:
Experimental research on the behavior of customers of small and medium enterprises in making decisions on choosing financial leasing services for capital sources
This study aims to identify an effective model for assessing the factors influencing the decision of small and medium enterprises in Ho Chi Minh City to utilize financial leasing services The findings will assist financial leasing companies in evaluating current policies, enabling them to refine and enhance their strategies to leverage the key elements that drive the adoption of financial leasing services.
STRUCTURE OF THE RESEARCH
This chapter highlights the significance and urgency of the research issue, leading the author to define the research content, objectives, questions, and methods pertinent to the topic.
THEORETICAL LITERATURE
OVERVIEW OF FINANCIAL LEASING
2.1.1 The concept of financial leasing
Financial leasing, a capital financing solution for businesses that emerged in the U.S during the 1950s, gained traction in Europe in the 1960s due to its efficient use of capital This financing option has since expanded globally, distinguishing itself from traditional asset leasing in several key ways.
Financial leasing combines asset leasing with credit provision, where the lessor transfers property to the lessee However, the lessee effectively receives capital, as the total rent paid is at least equal to the value of the leased asset at the time the contract is signed.
- Second, the lease term is medium-term, whereas long-term accounts for the majority of the asset's useful life
- Third, the lessee sets the criteria and technical specifications of the leased asset with the lessor
- Fourth, the financing lease contract cannot be terminated due to the will of one of the contracting parties
Although it is a form of capital supply, financial leasing differs from lending in that the assets created from the lessor's money remain in the lessor's possession
A finance lease is a leasing arrangement where the lessor provides credit to the lessee, allowing the leasing company to purchase the necessary assets on behalf of the lessee At the conclusion of the lease term, the lessee is required to make payments to the financial leasing firm for the use of these properties.
In 1982, the International Accounting Standards Committee (IASC) introduced a standard on financial leasing to address the requirements of international trade For a transaction to qualify as a financing lease under IASC regulations, it must fulfill at least one specific condition.
- First, after the lease period expires, the property's ownership can be transferred to the lessee based on the parties' agreement in the contract
- Second, the contract establishes the lessee's bargaining right to purchase the property Lease
- Third, the lease period accounts for the majority of the asset's useful life
In a financial leasing transaction, it is essential that the present value of the leases is equal to or exceeds the asset's worth Typically, three parties are involved: the lessor, the lessee, and the supplier of the asset A finance lease contract specifically outlines the agreement between the lessor and the lessee, where the lessor, acting as a financial leasing company, provides the asset at the request of the lessee.
The notion of financial leasing in Vietnam is described as follows in Clause 7 – Article 3 – Decree No 39/2014-CP on the operation of financing firms and finance leasing companies:
Financial leasing involves the provision of medium- to long-term credit through a contract between a financial lessor and a finance lessee In this arrangement, the finance lessor agrees to acquire the leased asset at the lessee's request, retaining ownership rights to the asset for the duration of the lease term outlined in the contract.
The laws regulating Financial Leasing transactions vary by country and are influenced by the state's management at any given time Nonetheless, certain essential characteristics are consistently found in Finance Leasing transactions.
- For the term of the Financial Leasing contract, the lessor retains ownership of the property
- The lessee has the right to utilize the leased asset and to profit from its use value
At the conclusion of a financial leasing agreement, the lessee is entitled to request the purchase of the leased item at its nominal value, prompting the lessor to transfer ownership of the property to the lessee.
In Vietnam, only finance leasing businesses are authorized to engage in financial leasing activities, as stipulated by the "Law on Credit Institutions." These finance leasing entities are classified as non-banking organizations and include various types such as 100% foreign-owned finance leasing companies, state financial leasing companies, joint stock finance companies, and joint venture finance leasing companies Notably, manufacturing companies are prohibited from conducting financial leasing activities, as they do not qualify as finance leasing companies.
A finance lease is a unique type of asset lease that differs significantly from other lease agreements, primarily because the risks and benefits of ownership of the leased asset are allocated differently.
Financial leasing is a medium- to long-term financing option that involves a lease agreement between the lessee and a financial leasing company, known as the lessor, focusing on the use of specific assets.
The parties do not have the power to unilaterally terminate the lease agreement during the lease period
In financial leasing, the lessor retains ownership of the asset while the lessee is obligated to pay rent At the end of the lease term, the lessee has the option to either purchase the property or continue leasing it based on the agreed terms.
Leasing machinery and equipment allows the lessee to avoid upfront costs and the need to mortgage assets, unlike traditional loans This approach also protects the lessee from the risks associated with asset depreciation.
2.1.3 The popular types of financial leasing in Vietnam
Under Decree No 39/2014/ND-CP, issued on May 7, 2014, financial companies and finance leasing companies in Vietnam are permitted to engage in specific forms of financial leasing operations.
Domestic financial leasing involves a finance leasing company acquiring an asset from a local supplier and subsequently subleasing it to the lessee based on the payment terms specified in the lease contract.
Domestic financial leasing is also a medium- and long-term credit granting option for business investment projects such as the purchase of machinery, equipment, production lines, and transportation
CONCEPTS OF SMALL AND MEDIUM ENTERPRISES
2.2.1 Definitons of small and medium enterprises
Small and Medium Enterprises (SMEs) are defined differently across countries, reflecting local circumstances that influence their success A business considered small in one nation may not be classified the same way in another While each country has its own criteria for defining the SME sector, the World Trade Organization (WTO) has outlined three key factors: (1) the number of employees, (2) the amount of capital or assets for investment, and (3) business income or average revenue over time Among these, the number of employees is the most commonly used criterion for defining SMEs.
The World Bank categorizes businesses into four distinct groups based on employee count: micro companies employ fewer than ten individuals, small businesses have fewer than 50 employees, medium-sized enterprises consist of fewer than 300 employees, and large businesses employ more than 300 individuals.
The classification of small and medium-sized enterprises (SMEs) varies significantly across countries and time periods In the European Union, SMEs are defined as businesses with fewer than 250 employees, an annual turnover of less than €50 million, and total assets below €43 million In the United States, SMEs typically have fewer than 500 employees and an annual turnover of less than $7 million, which can increase to $35.5 million for manufacturing firms Meanwhile, in Canada, a company is classified as an SME if it employs between 10 and 250 individuals and generates less than C$50 million in annual revenue.
On March 11, 2018, the Vietnamese Government issued Decree 39/2018/ND-CP, which provides guidance on the Law supporting Small and Medium Enterprises (SMEs) This decree outlines the criteria for identifying SMEs, as detailed in Article 6.
“Small and medium enterprises are classified by size including micro enterprises, small enterprises and medium enterprises
1 Micro-enterprises in the fields of agriculture, forestry, fishery and industry and construction have an average number of employees participating in social insurance of no more than 10 people per year and total annual revenue of not more than 10 people VND 3 billion or total capital not exceeding VND 3 billion Micro-enterprises in the field of commerce and services with an average number of employees participating in social insurance of no more than 10 people and a total annual revenue of not more than VND 10 billion or a total capital of not more than VND 3 billion
2 Small enterprises in the fields of agriculture, forestry, fishery and industry and construction with an average number of employees participating in social insurance of no more than 100 people per year and a total annual turnover of not more than VND 50 billion or the total capital must not exceed 20 billion VND, but is not a microenterprise as prescribed in Clause 1 of this Article Small enterprises in the field of commerce and services have an average number of employees participating in social insurance of not more than 50 people per year and a total annual revenue of not more than 100 billion VND or total capital not exceeding 50 billion VND, but is not a micro-enterprise as prescribed in Clause 1 of this Article
4 Medium-sized enterprises in the fields of agriculture, forestry, fishery and industry and construction have an average number of employees participating in social insurance not exceeding 200 people per year and total annual turnover not exceeding 200 people billion dong or the total capital must not exceed 100 billion dong, but it is not a small enterprise or a micro-enterprise as prescribed in Clauses 1 and 2 of this Article
A medium-sized enterprise in commerce and service typically employs up to 100 individuals annually and generates an annual turnover not exceeding VND 300 billion, with total capital capped at VND 100 billion It is important to note that this classification excludes micro and small enterprises as defined in the relevant regulations.
Small and medium enterprises (SMEs) are classified into three categories: micro enterprises, small enterprises, and medium enterprises This article presents a method for identifying SMEs, supported by a summary table for clarity.
Table 2.1: Criteria for identifying small and medium enterprises
Size Micro enterprises Small enterprises Medium enterprises Field Number of employees participati ng in social insurance (average year)
Total revenue/To tal capital
Number of employees participati ng in social insurance (average year)
Total revenue/To tal capital
Number of employees participati ng in social insurance (average year)
Total revenue/To tal capital
Total revenue of the year is not more than 3 billion
Total revenue of the year is not more than 50 billion
Total revenue of the year is not more than 200 billion
VND or total capital is not more than 3 billion VND
VND or total capital is not more than 20 billion VND
VND or total capital is not more than 100 billion VND
Total revenue of the year is not more than 3 billion VND or total capital is not more than 3 billion VND
Total revenue of the year is not more than 50 billion VND or total capital is not more than 20 billion VND
Total revenue of the year is not more than 200 billion VND or total capital is not more than 100 billion VND
Total revenue of the year is not more than 10 billion VND or total capital is not more than 3
Total revenue of the year is not more than 100 billion VND or total capital is not more than 50
Total revenue of the year is not more than 300 billion VND or total capital is not more than 100 billion VND billion VND billion VND
2.2.2 Features of small and medium enterprises
• Establishment, legal, labor, and financial characteristics
SMEs typically operate with a straightforward structure, often managed by an individual or family, which results in lower management costs due to a smaller management apparatus This direct management approach enables quick decision-making in response to changes in the business environment The primary focus of SMEs is on direct services, where high technology is not essential, yet they cater to a substantial market demand.
SMEs employ a small number of employees, who are frequently low-skilled or unskilled
Small and medium-sized enterprises (SMEs) face significant challenges in attracting qualified employees due to their limited financial resources, less favorable working conditions, and inadequate compensation packages Additionally, the lack of sufficient promotion opportunities and job stability, along with minimal employee benefits, makes it difficult for SMEs to entice skilled professionals to join their workforce.
As a result of this fact, SMEs confront numerous challenges, particularly in financial management and the development, management, and implementation of investment projects/production and busniess plan
In today's rapidly evolving technological landscape, small and medium-sized enterprises (SMEs) face significant challenges in adopting advanced technologies, often relying on outdated systems that lead to high production costs and stagnant product quality To enhance competitiveness, it is essential for SMEs to invest in innovative technologies that improve their products and services However, barriers such as limited technical skills, insufficient capital, and inadequate professional capacity hinder their ability to innovate effectively.
SMEs often rely on a mix of personal and credit capital to grow, given their limited resources Small-scale operations offer benefits like easy setup, market entry, and quick capital recovery, creating favorable conditions for SME growth across diverse fields and regions However, these same factors can also hinder their ability to expand production and operations.
Small and medium-sized enterprises (SMEs) encounter significant challenges in production and business operations, particularly in securing bank financing due to limited capital resources With insufficient initial investment, SMEs are particularly susceptible to capital shortages, especially when they seek to expand operations, innovate, upgrade equipment, or invest in new technologies Furthermore, accessing bank credit is often problematic, as SMEs frequently lack adequate collateral for loans and struggle to prepare comprehensive loan documentation and business plans.
• Characteristics of the ability to access commercial bank loans
Small and medium-sized enterprises (SMEs) often face challenges in accessing bank capital due to their limited equity This lack of financial resources makes obtaining loans essential for the growth and development of their production and business activities.
THEORETICAL BACKGROUND
2.3.1 Theory of reasoned action (TRA)
The Theory of Reasoned Action (TRA), established by Fishbein and Ajzen in 1975, explores the connection between attitudes, intentions, and behavior TRA posits that behavioral intention, a key predictor of actual behavior, is influenced by two main factors: attitude, which reflects a positive or negative evaluation of a behavior, and subjective norm, which considers the perceived social influences on that behavior Generally, as attitudes and subjective norms improve, the strength of behavioral intentions increases.
Picture 2.4: Theory of reasoned action (TRA)
- Attitude: If a person thinks that their actions can lead to good or bad results, their feelings about the action will be positive, negative, or neutral
- Subjective criteria: Perceptions and thoughts about influencers such as family members, friends, colleagues
Behavioral intention Realistic behavior Subjective standards
- Behavioral intention: a function of attitude towards subjective and subjective standards for that behavior
Consumer behavior, which emerged as a distinct area of study in marketing during the 1940s, encompasses the activities and emotions linked to purchasing by individuals or groups It involves the comprehensive analysis of purchasing actions, from pre-purchase considerations to the final transaction As defined by Kotler and Levy (1969), consumer behavior refers to the specific actions of individuals or entities in making purchasing decisions, as well as the usage and disposal of products or services Engel, Blackwell, and Miniard (1993) further elaborate that consumer behavior includes the actions associated with acquiring, consuming, and disposing of goods and services, along with the decision-making processes before and after these actions.
Customer behavior encompasses the thoughts, feelings, and actions individuals exhibit during the purchasing and consumption of products and services Influencing factors include consumer reviews, service quality, product information, pricing, packaging, advertising efforts, and promotional activities, all of which shape customers' perceptions and decision-making processes.
Table 2.2 Consumer Behavior by Philip Kotler
Buying decision process Decide to buy
Economy Motivation Cultural Problem awareness Select product
Price Technology Awareness Society Search for information Choose brand
Distribution Politics Learn Mentality Option evaluation Choose an agent
The media Cultural Memory Personal Buying decision Determine the time of purchase
Post-purchase behavior Payment method
According to Philip Kotler (2001), to come to the action of purchasing a product, consumers often go through a continuous process consisting of 5 stages which are summarized as follows:
Picture 2.5: Process of purchase decision
The buying process begins with the buyer becoming aware of a need Buyers feel there is a difference between the actual state and the desired state Needs can originate from
Post- purchase internal stimuli (normal human needs such as hunger, thirst, love, ) and external stimuli (press, advertising, friends, society, …etc.)
When a consumer identifies a need, they begin to search for information If the desire is strong and a suitable product is readily available, they are likely to make an immediate purchase Conversely, if the product isn't easily accessible, consumers may simply remember their need without taking action Their approach to seeking information can vary; some may hesitate to look for more details, while others may actively pursue relevant information to address their needs.
Consumers evaluate competing brands by processing information about product attributes, which they prioritize based on their individual needs This evaluation leads to the formation of beliefs about the brands, guiding their purchasing decisions Ultimately, after assessing their options, consumers develop a purchase intention; however, this decision can be influenced by external factors, such as the opinions of friends and family, as well as unexpected elements like price fluctuations and anticipated benefits.
Post-purchase behavior significantly influences consumer satisfaction; when customers are pleased with their purchase, they are likely to engage in positive shopping behaviors, such as recommending the product to others Conversely, dissatisfaction can lead consumers to switch to competing brands and share negative opinions about their experience with the product.
LITERATURE REVIEW
2.4.1 Studies in some other countries
A study by Prince and Schulux (1990) involving 508 business samples in the United States identified five key factors that influence small business customers' decisions to utilize financial services: secrecy, professional human resources, business counseling, convenience, and the quality of products and services Notably, the cost of service was not considered a significant issue in their findings.
In a study by Buerger and Ulrich (1986) involving 475 small businesses in Pennsylvania, it was found that the pricing of banking services was the most significant factor influencing the choice of banks Despite this key finding, no additional important variables were identified in the research.
A survey by File and Prince (1991) involving 582 businesses in the United States revealed key factors influencing companies' decisions to utilize financial services, including prestige, competitive interest rates, consulting, and strong employee relations The study identified three distinct customer segments: Return Seekers (40%), who are highly price-sensitive and quick to adopt innovative banking products; Relevance Seekers (33%), who are skeptical and conservative, requiring assurance that services are directly applicable to their business; and Relationship Seekers (16%), who prioritize personal referrals and support, demonstrating the highest level of loyalty to financial institutions.
A study by Pandey (2020) reveals that small businesses' loan decisions are primarily affected by their awareness of funding sources, seasonal factors, collateral, and interest rates, while the business owners' disposition does not have a statistically significant impact In the Kathmandu Valley, many small enterprises are seasonal, and their borrowing choices are shaped by client spending patterns throughout the year The research highlights the critical role of collateral in determining which loan options to pursue, as well as the influence of interest rates on the borrowing decisions of numerous small businesses.
J Nielsen et al (1995) investigated how well the banking community understands the demands of small business customers It was based on the results of a countrywide poll conducted in 1992 The findings are based on feedback from 115 small businesses and
A study involving 296 commercial banks revealed that key factors influencing bank selection for small businesses included credit accommodation, convenient location, product delivery, personal relationships, financial health, and competitive pricing However, significant differences emerged in the importance placed on other selection criteria, with bankers prioritizing community reputation, recommendations from friends, and the ability to make quick decisions more than small business owners did These findings indicate a disconnect between bankers' perceptions and the actual needs of small business clients, highlighting the necessity for improved understanding and communication to enhance financial health for both parties in the future.
In Ghana, Obodai (2019) identified several obstacles contributing to the limited availability of lease finance for SMEs, including inadequate business records, lack of guarantors and collateral, and insufficient knowledge about lease financing options Additionally, financial institutions impose excessively strict criteria for lease applications, further restricting SMEs' access to these financing products The study revealed that there is minimal demand for lease finance among SMEs, primarily due to rigid payment conditions and high interest rates.
In her 2013 study, Hoang Thi Thanh Hang examined the competitiveness of financial leasing companies in Ho Chi Minh City using the matrix method by Thompson-Strickland The research aimed to assess the competitiveness of these firms and identify external environmental factors influencing it, employing a 5-point Likert scale for surveys conducted with customers, managers, and experts The findings indicate that while financial leasing companies possess strengths such as network development, product innovation, brand competitiveness, marketing abilities, and human resources, they also face significant weaknesses that require attention Additionally, the study highlights various external factors positively impacting business competitiveness, including the rapid increase of trust organizations and supportive policies for SME development However, challenges such as capital mobilization competition, inadequate infrastructure, and the quality of education and training negatively affect the competitiveness of financial leasing companies in the region.
In his 2014 study, Chu Hai Son analyzes the development of the financial leasing market in Vietnam by examining demand and supply factors, as well as macroeconomic variables He investigates the roles of both lessees and lessors, identifying key influences such as interest rate policies, the limited popularity of financial leasing, cumbersome procedures, and a lack of diverse leasing products, all of which hinder market growth Internal business factors, including marketing strategies, capital mobilization, record management, customer identification, and post-lease monitoring, significantly impact the success of financial leasing companies Utilizing actual data on GDP, medium and long-term lending rates, and outstanding loans, the study explores how macroeconomic conditions and competition from bank credit markets affect the financial leasing sector Additionally, the author highlights legal restrictions and regulatory limitations that pose challenges for financial leasing companies and their clients, ultimately affecting the market's potential for development.
In his 2016 article published in "Talking about solutions to develop Vietnam's financial leasing market," Dang Van Dan analyzes the key factors influencing Vietnam's financial leasing sector and suggests strategies for its enhancement He highlights critical aspects such as business capital, the range of products and services, business processes, marketing strategies, and human resources The author notes that limited mobilization channels and high capital raising costs lead to elevated interest rates for finance leasing companies Furthermore, the restricted variety of products and services offered hinders business efficiency, as companies struggle to meet diverse customer needs, particularly since financial leasing is primarily applicable to movable assets like machinery and equipment To improve operational efficiency, financial leasing firms must focus on consumer satisfaction, safety, and transaction effectiveness Additionally, effective communication with clients is crucial, as the financial leasing market remains underutilized by businesses and has a limited network.
Nguyen Viet Kha (2020) conducted a study on the factors influencing the competitiveness of Vietinbank Leasing, a finance leasing company under the Joint Stock Commercial Bank for Industry and Trade of Vietnam Utilizing statistical methods and comparative analysis, the research assessed the current competitive landscape of Vietinbank Leasing The study applied the internal factors evaluation model by Thompson, Strickland & Gamble (2007) and identified key factors impacting competitiveness, including financial capacity, human resource capacity, marketing capacity, service quality, interest rate capacity, and brand reputation.
Table 2.3 : Summary of related studies
No Author Purpose Method Research
Examine the factors that attract small companies
508 small businesses in the USA
Examines existing buyer behavior models and assesses their applicability to financial services
582 small businesses in the USA
Study the important factors for small companies in selecting a financial institution
The expectations of both small businesses and bankers about the bank choosing procedure are examined
Identify the issues that leasing financing companies in Ghana face
Population of the study consisted of all Lease
Companies in Greater Accra Region and all SMEs in Greater Accra Region
6 Pandey ( 2020) Examine the factors that influence small company loan decisions in Nepal's Kathmandu Valley
The descriptive and analytical research
216 samples through self structured and administered questionnaire
Comprehensive assessment of strengths and weaknesses in the competitiveness of financial leasing companies in Ho Chi Minh City
Expert methods, systems thinking methods and descriptive statistics methods
Data from a survey of 328 votes from leaders and managers of financial leasing companies in
Ho Chi Minh City Ho Chi Minh City
Present the factors affecting the development of the financial leasing market from three aspects: supply side, demand side and macro factors
Direct phone interview, email exchange with
(25 production companies, 25 service companies) are using financial leasing services in Ho Chi Minh City and surrounding areas
Evaluate the factors affecting the financial leasing market in Vietnam, and provide solutions for the market's development
Evaluate factors affecting the competitiveness of the Finance Leasing company of Joint Stock Commercial Bank for Industry and Trade of Vietnam
Source :Synthesis by the author
Table 2.4: Factors expected to be included in the model
( +) File and Prince (1991) ; J Nielsen et al (1995);
(1986) ; Pandey ( 2020); Philip Kotler( 1988); Nguyen Viet Kha ( 2020 ); Chu Hai Son (2014); Dang Van Dan (2016)
( +) File and Prince (1991); J Nielsen et al (1995);
Chu Hai Son (2014); Dang Van Dan (2016)
(+) Prince and Schulux (1990); File and Prince
(1991); Nguyen Viet Kha ( 2020 ); Hoang Thi Thanh Hang ( 2013); Dang Van Dan (2016)
Hoang Thi Thanh Hang ( 2013); Chu Hai Son (2014); Dang Van Dan (2016)
( +) File and Prince (1991) ; J Nielsen et al (1995);
Nguyen Viet Kha ( 2020 ); Hoang Thi Thanh Hang ( 2013); Chu Hai Son (2014); Dang Van Dan (2016)
( +) Prince and Schulux (1990); J Nielsen et al
(1995); Obodai ( 2019 ); Pandey ( 2020); Hoang Thi Thanh Hang ( 2013); Chu Hai Son (2014); Dang Van Dan (2016);
Source : Synthesis by the author
DATA AND RESEARCH METHODS
RESEARCH MODEL AND RESEARCH HYPOTHESIS
The research model identifies seven independent variables influencing the decision to utilize financial leasing services among small and medium enterprises in Ho Chi Minh City These variables include competitive pricing, the application process, the attitude of service staff, awareness of finance leasing opportunities, the reputation of finance leasing companies, suitable policies and products, and social influence The dependent variable is the decision-making process regarding financial leasing services.
Source: Recommended by the author
Philip Kotler (1988) defines price as the total expense a business incurs when utilizing a product or service, necessitating a careful evaluation of costs versus benefits If the perceived costs are minimal relative to the advantages gained, businesses are likely to adopt the service Conversely, research by Obodai (2019) identified rigid payment conditions and high interest rates as significant factors limiting service demand in the study area Therefore, a hypothesis is proposed to address these issues.
H1: Competive prices have a positive impact on the decision to use financial leasing services
In the age of Technology 4.0, banks and financial institutions are experiencing a significant transformation, focusing on in-house file transfer software and online applications to ensure timely and efficient record handling These advancements allow for quick loan processing and disbursement notifications, which are heavily promoted by these institutions to attract customers As a result, the speed of service has become a key competitive factor, influencing customers' decisions when selecting a lending institution.
H2: Application process have a positive impact on the decision to use financial leasing services
Staff members are essential representatives of financial institutions, directly influencing customer relationships and embodying the institution's image and reputation Their service attitude—before, during, and after transactions—plays a crucial role in customers' decisions to select a loan Employees who demonstrate respect, friendliness, politeness, and professionalism are vital in addressing customer needs and resolving issues that may arise, ultimately guiding customer choices and contributing to the success of transactions.
US showed that the suitability services provided by financial institutions is a factor affecting the choice of business customers Therefore, the author hypothesizes:
H3: Service/ Staff’s attitude have a positive impact on the decision to use financial leasing services
3.2.2.4 Awareness of financial leasing opportunities
A study by Pandey (2020) indicates that small businesses' loan decisions are heavily influenced by their awareness of available funding opportunities Additionally, research by Chu Hai Son (2014) demonstrates that the lack of popularity of Financial Leasing adversely affects lessee demand, thereby restricting the growth of the Financial Leasing market Based on these findings, the following hypothesis is proposed.
H4: Awareness of finance leasing opportunities have a positive impact on the decision to use financial leasing services
3.2.2.5 Reputation of financial leasing company
Reputation is a long-term asset shaped by market perceptions, customer trust, and partner relationships It reflects a commitment to prioritizing customer interests and contributing positively to society Financial institutions with strong brand reputations enjoy a competitive edge in attracting customers, as evidenced by research, including Nielsen et al (1998), which highlights the significant influence of reputation on business decision-making Thus, we propose the following hypothesis:
H5: Reputation of fiance leasing company have a positive impact on the decision to use financial leasing services
Lending policies vary significantly among financial institutions and are tailored to specific business sectors and enterprise needs Each institution's risk appetite influences its lending criteria, resulting in distinct financing policies based on business type, loan purpose, required documentation, loan-to-value ratios, credit limits, and post-financing oversight Consequently, only borrowers who meet these stringent requirements can access loans Therefore, corporate clients must thoroughly research and select financial institutions that align with their business financing needs.
(1990) in the US proved that the suitability of products provided by financial institutions will affect the choice of business customers Therefore, the author hypothesizes:
H6: Appropriate policy and products have a positive impact on the decision to use financial leasing services
Philip Kotler highlights that consumer behavior is significantly shaped by influences from family and reference groups The impact of third parties, such as friends, colleagues, and family members, who have experience with banks or organizations, plays a crucial role in shaping psychological and behavioral choices Nielsen et al (1995) emphasize that these third-party influences are vital reference factors for businesses in Australia Therefore, it is proposed that understanding these influences can enhance marketing strategies.
H7: Social influence have a positive impact on the decision to use financial leasing services
RESEARCH SCALE
Primary and secondary data are examples of data sources
Primary data was collected through surveys and interviews, with a focus on survey questionnaires for ease of completion by respondents These questionnaires were distributed via various media in the customers' immediate vicinity Responses were recorded using the researcher's email address to ensure efficient data collection.
Secondary data is collected from external sources like books, journals, research articles, and online databases to provide insights into theoretical foundations, research models, methodologies, and scales.
The scale's establishment is one of the study's two research aims, which include:
- Measuring the qualities of the research participants from the respondents' point of view
- Ask participants to rate how much they agree with the primary criteria influencing the decision to use financial leasing services for small and medium enterprises in
The hierarchical scale is designed to systematically quantify and organize issues by measuring attitudes, consciousness, opinions, interests, and perceptions In this study, the Likert scale (consisting of five levels) is employed to assess various observed variables, which are detailed in a table This approach aims to identify the key factors influencing the decision to utilize financial leasing services among small and midsize enterprises in Ho Chi Minh City.
The following are the scales that were built in the study:
Table The scale of variables
No I decided to use financial leasing service because Symbol INDEPENDENT VARIABLES
1 I use the financial leasing service because it has an interest rate in line with the market
2 I use financial leasing service because it has a competitive fee compared to banks/other institutions
3 Flexible and attractive lease interest CP3
4 Financial leasing company has a quick property appraisal and loan application time
5 The financial leasing company handles well and timely issues that arise
6 Financial leasing companies have short processing time for loan applications
7 Financial leasing company specifically commits to the business the maximum loan processing time
8 Financial leasing company staffs are polite and respect customers SA1
9 Finance leasing company staffs have good ethics and reputation with customers
10 Financial leasing company staffs have qualifications and professional knowledge
11 Financial leasing company staffs are always looking for the best financial solutions for customers
12 Financial leasing company staffs effectively handle customer complaints and problems
13 Financial leasing company employees listen, share and sympathize with businesses
Awareness of Finance Leasing opportunities
14 I understand the advantages of using financial leasing service AO1
15 I understand that using financial leasing service help me to reduce income tax
16 Land property can be used for other purposes AO3
Reputation of Finance Leasing company
17 Financial leasing companies have good reputation and brand names in the market
18 I use the service from the long established financial leasing company
19 I use the service from financial leasing company with healthy and transparent finance
20 Have policies consistent with the needs of enterprise PP1
21 Have policy priority for the business enterprise specific sector PP2
22 Not require collateral real estate PP3
23 There are many forms of leasing PP4
24 Diverse products and services PP5
25 I use financial services because of the recommendation of relatives and friends who are using financial leasing services
26 I use financial services due to the recommendation of relatives and friends who are working at a financial leasing company
27 I use financial services because of the recommendation of a partner who is using financial leasing services
28 I use the financial leasing service because of the recommendation of the supplier
Decide to use financial leasing services
29 I decided to use financial leasing service DC1
30 I feel relieved when using financial leasing services DC2
31 I will recommend to my family, friends, … to use the financial leasing service
Source: Author's synthesis from related studies
SAMPLING METHOD
The sampling design employs a convenience method to select a sample size of 300 observations The survey targets customers utilizing financial leasing services, irrespective of their business type, industry, or operational duration.
A survey was carried out using questionnaires based on research variables, which were refined with the lecturer's guidance prior to the official distribution A total of 300 questionnaires are planned for distribution, and the collected data will undergo a cleaning process before analysis.
According to Nguyen Dinh Tho (2013), the minimum sample size for research should be five times the number of observed variables in the model With 31 observed variables identified, this means a minimum of 155 observations is required Thus, a collected sample size of 300 observations is deemed suitable for analysis.
DATA ANALYSIS METHODS
To analyze statistical data, the study used SPSS 20.0 software to test the reliability of the scale along with other inferential statistics
3.5.1 Evaluate the reliability of the scales by Cronbach’s Alpha test
Cronbach's Alpha is a statistical measure that assesses the reliability and internal consistency of observed variables, with a higher coefficient indicating greater homogeneity among them It is essential to evaluate Cronbach's Alpha for preliminary scales derived from qualitative studies to identify and eliminate variables that do not align with the scale, ensuring that only relevant variables are included in exploratory factor analysis.
Cronbach's Alpha coefficient is a statistical test of how closely the items on the scale correlate with each other This coefficient is calculated according to the following formula:
Cronbach's Alpha coefficient is a crucial measure of scale reliability, applicable when analyzing three or more observed variables It ranges from 0 to 1, with a value of 0.3 or higher indicating a qualified scale While a higher Cronbach's Alpha suggests greater reliability, excessively high values may also raise concerns regarding the scale's effectiveness The coefficient incorporates the number of variables (K) and the variances of the observed variables (σ²Yi) and the sum variable (σ²x).
(above 0.95), it shows that many variables in the scale have no difference, this phenomenon is called overlap in the scale, Nguyen Dinh Tho ( 2013)
Exploratory factor analysis (EFA) is employed to assess the convergent, discriminant, and collapsing values of estimated parameters across variable groups The Bartlett test evaluates the correlation matrix to determine if it is a unit matrix, with statistical significance indicated by a p-value (Sig) less than 0.05 This significance reveals that the observed variables are correlated within the population.
Factor analysis is applicable only when the KMO (Kaiser-Meyer-Olkin) coefficient is 0.5 or higher; if it falls below 0.5, the data is deemed unsuitable for this analysis (Hoang Trong and Chu Nguyen Mong Ngoc, 2005) Additionally, variables with a factor loading of less than 0.5 will be excluded from the analysis.
Factor analysis was conducted using the Principal Component method for factor extraction and Varimax rotation to maximize variance among observed variables (Hair et al., 2010) The extraction criterion set Eigenvalues at 1 or higher, ensuring that each factor adequately explains the variation of at least one observed variable (Hair et al., 2010) The selection criteria for variables within the factors adhere to specific conditions to maintain analytical integrity.
- Ensure coefficient of variance extraction in the total of variables Communality
- Key Factor Upload Factor |>0.50| considered to be of practical significance
- Minimum of variables with multifactor cross-load coefficients (gap of load factor magnitude between two factors)
Following the removal of non-conforming variables, a reassessment of the variable suitability was conducted using the Cronbach's Alpha test This adjustment aimed to confirm the reliability of the scale.
The data used in the correlation regression analysis selected by the researcher is the normalized data exported from the SPSS software after the exploratory factor analysis
To establish the causal relationship between variables in a model, the initial step involves analyzing the correlation to identify any linear relationship between the independent and dependent variables While this correlation analysis does not confirm a cause-and-effect relationship, it lays the groundwork for subsequent regression analysis A strong correlation indicates a potential latent relationship between the variables, while also helping to identify multicollinearity, which occurs when independent variables are highly correlated with each other If the mean value of the relationship between the independent and dependent variables is less than 0.05, those variables will be included in the analytical procedure.
Linear regression analysis quantifies the impact of independent variables on a dependent variable, utilizing the F-statistical value to assess the relationship between the sample and population through the coefficient of determination, R² To identify collinearity in the data, the Variance Inflation Factor (VIF) is employed, with a VIF exceeding 10 indicating potential multicollinearity issues (Hoang Trong & Chu Nguyen Mong Ngoc, 2005, p 218).
RESULTS OF EXPERIMENTAL RESEARCH
INTRODUCE OF FINANCIAL LEASING COMPANIES IN VIETNAM 48
As of 2020, Vietnam has ten licensed financial leasing businesses, primarily concentrated in the economically vibrant cities of Hanoi and Ho Chi Minh City Some companies have expanded their presence to provinces such as Hai Phong, Quang Ninh, Da Nang, Binh Duong, and Can Tho to capitalize on emerging market opportunities Additionally, financial leasing operations within the commercial banking sector have been diversified by delegating these functions to the branches of parent banks.
Table 4.1: List Of Financial Leasing Companies
(Until June 30, 2021) Unit: Billion VND
2nd floor, 120 Hang Trong, Hoan Kiem, Hanoi
9th floor Diamond Plaza, 34 Le Duan, District
72/GP- NHNN dated 2/7/2018 (issued changed)
9th floor of ACB Tower,
No 444A-446 Cach Mang Thang Tam, Ward 11, District 3, City Ho Chi Minh
Commercial Bank of Vietnam Leasing
16 Phan Dinh Phung, Ba Dinh District, Hanoi
25T1, N05, Hoang Dao Thuy street, Trung Hoa ward, Cau Giay, Hanoi
No 4 Pham Ngoc Thach, Dong Da, Hanoi
Vo Thi Sau Ward, District
Minh Khai, Ward 6, District 3, Ho Chi Minh City
04, 28th floor, Saigon Trade Center, 37 Ton Duc Thang, Ben Nghe Ward, District
20th floor, Tower A, Vincom, No
Le Dai Hanh ward, Hai Ba Trung district, Hanoi
Source: State bank of Vietnam
Over the past two decades, financial leasing companies have expanded rapidly in scale and network; however, their capital and operational reach remain significantly smaller compared to commercial banks This limited capital restricts their ability to fund large, viable projects, which in turn hampers their development and operational efficiency Consequently, small and medium enterprises have become the primary target customers for Vietnamese financial leasing companies A table detailing the outstanding balances of these companies is provided in Chapter 1.
Table 4.2 : Outstanding balance of financial leasing companies 2015 – 2019
Source : Synthesis by the author
RESEARCH RESULTS
Number of times using financial leasing service
Source: Results extracted from the author's analysis in SPSS
The business landscape is predominantly composed of joint stock companies, which represent 41.6% with 94 enterprises Following this, joint venture companies account for 23.5% with 53 enterprises Company Limited – Individual households make up 15.9% with 36 enterprises, while private enterprises consist of 14.6% with 33 companies Lastly, other types of enterprises total 10, comprising 4.4% of the overall business types.
The majority of enterprises, 52.2% or 118 companies, have been operating for 5 to 10 years, making this the largest group Following this, 31% of enterprises, totaling 70, have been in operation for over 10 years Lastly, 16.8% of enterprises, which equates to 38 companies, are under 5 years old.
In the business landscape, manufacturing leads with 130 enterprises, representing 57.5% of the total Following closely is the construction sector, which comprises 62 enterprises, accounting for 27.4% The trade and service industries include 26 enterprises, making up 11.5%, while other business sectors contribute 8 enterprises, or 3.5%.
In a recent analysis of service usage among enterprises, it was found that 45.6% of 103 businesses utilized services between 3 to 5 times annually Additionally, 31.4% of the enterprises, totaling 71, reported using services less than 3 times a year, while 23% of the businesses, amounting to 52, engaged with services more than 5 times annually.
4.2.2 Evaluate the reliability of the scales by Cronbach’s Alpha test
4.2.2.1 Testing the reliability of the scale by Cronbach's Alpha coefficient for the independent variable
Cronbach's Alpha coefficient tests the reliability of the scale, allowing us to eliminate inappropriate variables in the research model
The summary table of Cronbach's Alpha test results is presented as follows:
Table 4.4: Cronbach's Alpha test results for independent variables
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted Reliability Statistics Competive Price Cronbach's Alpha : 0.793
Reliability Statistics Application Process Cronbach's Alpha : 0.853
Reliability Statistics Service/ Staff’s Attitude Cronbach's Alpha 0.675
Service/ Staff’s Attitude Scale after eliminating variables: Cronbach's Alpha is
Awareness of financial leasing opportunities Scale: Cronbach's Alpha is 0.886
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted Reliability Statistics Competive Price Cronbach's Alpha : 0.793
Reliability Statistics Application Process Cronbach's Alpha : 0.853
Reputation of financial leasing companies Scale: Cronbach's Alpha is 0.869
Appropriate policy and products Scale: The factor's Cronbach's Alpha is 0.798
Appropriate policy and products Scale after eliminating variables: Cronbach's
Source: Results extracted from the author's analysis in SPSS
In testing the reliability of the independent variable, the observed variables PP5, RR2, SA4, and SA6 were found to have a total correlation coefficient of less than 0.3, failing to meet the required standards when the Cronbach Alpha coefficient is excluded Consequently, these variables do not align with the current value of Cronbach's Alpha, as detailed in Appendix 2 As a result, these observed variables will be removed from the scales, and subsequent testing will proceed with the remaining observed variables.
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted Reliability Statistics Competive Price Cronbach's Alpha : 0.793
Reliability Statistics Application Process Cronbach's Alpha : 0.853
Social Influence Scale: Cronbach's Alpha of the factor is 0.783
Social Influence Scale after eliminating variables: Cronbach's Alpha is 0.923
The Cronbach's Alpha reliability test results indicate that all research components have a Cronbach's Alpha coefficient exceeding 0.6, with observed variable correlation coefficients greater than 0.3 This confirms that the scale utilized in the study is both appropriate and reliable, making it suitable for further tests and analyses.
4.2.2.2 Testing the reliability of the scale using Cronbach's Alpha coefficient for the dependent variable
Table 4.5: Result of Cronbach's Alpha test of dependent variable
Source: Results extracted from the author's analysis in SPSS
The DC factor demonstrates a strong reliability with a Cronbach's Alpha coefficient of 0.821, and all individual variable correlations exceed 0.3, indicating that it meets the necessary criteria for inclusion in subsequent factor analysis.
4.2.3.1 EFA factor analysis for the independent variable
The initial scale of the independent variable comprised 28 observed variables, but after conducting a reliability test using Cronbach's Alpha coefficient, 4 variables were excluded To further assess the convergence and discriminant validity of the remaining 24 observed variables, exploratory factor analysis (EFA) was employed.
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Decision to use financial leasing services: Cronbach's Alpha of factor is 0.821
The results of factor analysis to explore the independent variable are shown below:
Table 4.6: Factor analysis with independent variables
Source: Results extracted from the author's analysis in SPSS
- The KMO coefficient in the analysis is 0.741 > 0.5, showing that the factor analysis results are reliable
- Bartlett's Test has a Sig coefficient of 0.000 < 0.05, showing that the results of factor analysis ensure statistical significance
- The extracted variance is 75,419, showing that the variation of the analyzed factors can explain 75.419% of the variation of the original survey data, which is a good level of significance
- The Eigenvalues coefficient of factor 7 is 1,048 > 1, showing the convergence of the analysis stopping at factor 7, or the analysis results showing that there are 7 factors extracted from the survey data
Each observed variable's factor loading coefficient exceeds 0.5, indicating a significant influence of these variables on the factors they represent.
- Thus, after conducting EFA exploratory factor analysis, the number of observed variables kept is 24 observed variables
4.2.3.2 EFA factor analysis for the dependent variable
Table 4.7: Factor analysis with dependent variable Item
Source: Results extracted from the author's analysis in SPSS
- The KMO coefficient in the analysis is 0.713 > 0.5, showing that the factor analysis results are reliable
- Bartlett's Test has a Sig coefficient of 0.000 < 0.05, showing that the results of factor analysis ensure statistical significance
- The extracted variance is 73,761, showing that the variation of the analyzed factors can explain 73.761% of the variation of the original survey data, this is a fairly high level of significance
The Eigenvalues coefficient of the first factor is 2.213, which is greater than 1, indicating that the analysis converges at this point This result confirms that only one factor has been extracted from the survey data.
The factor loading coefficients for all observed variables exceed 0.8, indicating a strong influence of these variables on the factors they represent.
The factor analysis results indicate that the average scores of the observed variables have been calculated to identify key factors These factors are essential for conducting regression and correlation analysis, highlighting the most significant variables in the study.
A regression analysis was conducted using seven independent variables and one dependent variable, demonstrating a strong model consistency at a 5% significance level The adjusted R² coefficient of 0.585 indicates that the model effectively explains 58.5% of the overall relationship influencing the decision to utilize financial leasing services among medium and large enterprises in Ho Chi Minh City.
Table 4.8: Evaluation table of model fit according to adjusted R2
Std Error of the Estimate
Source: Results extracted from the author's analysis in SPSS
The F test in the ANOVA table assesses the suitability of the overall linear regression model As indicated in Table 4.9, the ANOVA analysis yields a significant result (sig = 0.000), confirming that the regression model is appropriate for the dataset and can be effectively utilized.
Table 4.9: Results of ANOVA test
Model Sum of Squares Df Mean Square F Sig
Source: Results extracted from the author's analysis in SPSS
The regression analysis reveals the impact of various factors on the decision-making process regarding the use of financial leasing services by small and medium enterprises in Ho Chi Minh City This study identifies key determinants that influence these businesses' choices, providing valuable insights for stakeholders in the financial leasing sector.
Table 4.10: Results of multivariable regression analysis
Source: Results extracted from the author's analysis in SPSS
DISCUSSION RESEARCH RESULTS
Table 4.12: Summary of Test Hypothesis
H1 Competive prices have a positive impact on the decision to use financial leasing services
H2 Application process have a positive impact on the decision to use financial leasing services
H3 Service/ Staff’s attitude have a positive impact on the decision to use financial leasing services
Awareness of finance leasing opportunities have a positive impact on the decision to use financial leasing services
Reputation of fiance leasing company have a positive impact on the decision to use financial leasing services
Appropriate policy and products have a positive impact on the decision to use financial leasing services
H7 Social influence have a positive impact on the decision to use financial leasing services
Source: Results extracted from the author's analysis in SPSS
Research indicates that five key factors significantly influence customer satisfaction in financial leasing These factors, ranked by their impact, are: (1) the reputation of the financial leasing company, (2) competitive pricing, (3) the attitude of the service staff, and (4) the application process.
(5) Social influence; (6) Appropriate policies and products and (7) Awareness of financial leasing opportunities
The reputation of a financial leasing company significantly influences the decision-making process for small and medium enterprises (SMEs) in Ho Chi Minh City when considering financial leasing services This relationship is supported by a statistically significant Sig value of less than 0.05 and a standardized Beta coefficient of 0.378, indicating that a one-unit increase in the company's reputation correlates with a 0.378 unit increase in the likelihood of SMEs opting for these services This finding underscores the importance of a financial leasing company's reputation as a critical predictor in business decision-making, aligning with Nielsen et al (1998), which emphasizes reputation as a key factor in influencing business choices.
The competitive price significantly influences the decision of small and medium enterprises (SMEs) in Ho Chi Minh City to utilize financial leasing services, as evidenced by a standardized Beta coefficient of 0.256 and a Sig value below 0.05 This indicates that a 1-unit increase in competitive pricing leads to a 0.256-unit increase in the likelihood of SMEs opting for financial leasing Despite this correlation, high interest rates at finance leasing companies compared to commercial banks hinder their competitiveness Thus, the impact of competitive pricing on the decision-making process aligns with previous research by File and Prince.
1991) ; J Nielsen et al (1995); Obodai ( 2019) , etc
The attitude of service staff significantly influences the decision to utilize financial leasing services among small and medium enterprises in Ho Chi Minh City This relationship is validated by a significance value below 0.05 and a standardized Beta coefficient of 0.196, indicating that a one-unit increase in staff attitude correlates with a 0.196-unit increase in the decision to adopt these services This finding aligns with previous research conducted by Prince and Schulux (1990), File and Prince (1991), Nguyen Viet Kha (2020), Hoang Thi Thanh Hang (2013), and Dang Van Dan, confirming that staff attitude is the third most important factor affecting leasing service decisions in this context.
The application process significantly influences the decision to utilize financial leasing services among small and medium enterprises (SMEs) in Ho Chi Minh City (HCMC) With a significance value below 0.05 and a standardized Beta coefficient of 0.186, this relationship indicates that an increase in the application process factor by one unit correlates with a 0.186 unit increase in the decision to engage in financial leasing Consequently, for SMEs surveyed, it is essential for financial leasing companies to implement straightforward and efficient loan application procedures, along with competitive interest rates and fees, to reduce the waiting time for loan processing These findings align with previous research conducted by File and Prince (1991), J Nielsen et al (1995), Chu Hai Son (2014), and Dang Van Dan (2016).
Social influence significantly impacts the decision of small and medium enterprises in Ho Chi Minh City to utilize financial leasing services This correlation is validated by a significance value below 0.05 and a standardized Beta coefficient of 0.183, indicating a positive relationship between social influence and the adoption of financial leasing services in this region.
An increase of 1 unit in the Social Influence factor leads to a 0.183 unit rise in the likelihood of small and medium-sized enterprises in Ho Chi Minh City opting for financial leasing services, positioning it as the fifth key influencing factor This indicates that businesses are more inclined to choose a finance leasing company when it is recommended by relatives, associations, or partners, as these endorsements provide valuable information and foster trust, ultimately aiding their decision to secure capital This finding aligns with the research conducted by Ajzen (2013) and Prince and Schulux (1990).
The decision to utilize financial leasing services among small and medium enterprises (SMEs) in Ho Chi Minh City is significantly influenced by appropriate policies and products, as evidenced by a standardized Beta coefficient of 0.169 and a significance value below 0.05 This indicates that a one-unit increase in suitable policies and products correlates with a 0.169 unit increase in the decision to engage in financial leasing Furthermore, the relevance of lending policies is crucial for businesses when selecting a credit institution, as even the lowest interest rates cannot compensate for a lack of suitable lending strategies Each enterprise, with its unique needs and industry specifics, requires financial leasing companies to adapt and enhance their offerings to effectively meet market demands This aligns with findings from previous research by Prince and Schulux (1990), J Nielsen et al (1995), Obodai (2019), Pandey (2020), Hoang Thi Thanh Hang (2013), Chu Hai Son (2014), and Dang Van Dan (2016).
Awareness of financial leasing opportunities significantly influences the decision to utilize financial leasing services among small and medium enterprises in Ho Chi Minh City This relationship is supported by a significance value below 0.05 and a standardized Beta coefficient of 0.146, indicating a positive correlation Specifically, a one-unit increase in awareness leads to a 0.146 unit increase in the likelihood of adopting financial leasing services, suggesting that while the influence is present, it is relatively weak.
Research from 2014 indicates that the lack of popularity of Financial Leasing negatively impacts lessee demand, ultimately restricting market growth These findings align with earlier studies conducted by Pandey (2020), Nguyen Viet Kha (2020), Hoang Thi Thanh Hang (2013), Chu Hai Son (2014), and Dang Van Dan (2016), as discussed in Chapter 2.
