INTRODUCTION
REASON FOR CHOOSING A RESEARCH TOPIC
In today's digital age, smart devices, particularly smartphones, have become integral to our daily lives, facilitating communication and entertainment anytime, anywhere These devices not only allow for swift transmission of confidential information but also cater to the diverse needs of individuals and businesses alike Consequently, choosing the right smartphone is crucial, given the plethora of retailers like Mobile World, Nguyen Kim, Home Center, and Mobile Viet It’s essential to find a reputable seller that offers quality products at reasonable prices, along with attractive promotions and reliable after-purchase customer support.
In Da Nang city, retail companies are thriving, with FPT Shop emerging as a leading player in the smartphone market despite facing stiff competition from rivals like The Gioi Di Dong, Viettel, and Vien Thong A With numerous options available, customers often wonder why FPT Shop stands out as their preferred choice for purchasing smartphones.
With the approval of the lecturers at the International Training Institute of Duy Tan University and the support of FPT Digital Retail Joint Stock Company, I have chosen the topic "Factors Influencing Smartphone Purchase Decisions at FPT Shop Da Nang" for my graduation thesis.
RESEARCH OBJECTIVES
Analyzing the factors influencing customers' purchasing decisions for smartphones at FPT Shop Da Nang is essential for identifying strategies to enhance sales quality By understanding these factors, FPT Shop can implement targeted solutions that create a competitive advantage, ultimately leading to increased sales in their Da Nang locations.
Learn and systematize the theoretical issues along with the practical analysis related to the customer's decision to buy Smartphone at FPT Shop Da Nang.
Clearly identify the factors affecting the decision to buy Smartphone at FPT Shop Da Nang.
Understanding the factors that influence customers' smartphone purchasing decisions is crucial for identifying how these elements impact each stage of the decision-making process By analyzing these influences, businesses can better cater to consumer needs and preferences, ultimately enhancing their marketing strategies and improving sales outcomes in the competitive smartphone market.
To enhance customer engagement and drive smartphone sales at FPT Shop, it is essential to implement strategic solutions that effectively persuade potential buyers By focusing on unique selling points, offering competitive pricing, and providing exceptional customer service, FPT Shop can strengthen its market position These initiatives will not only boost the company's business performance but also foster significant growth, enabling it to compete more effectively with rivals like Mobile World.
REASEARCH QUESTION
- What factors affect customers' decision to buy smartphones at FPT Shop Da Nang?
- How much influence do these factors have on customers' purchasing decisions?
- How to influence those factors to increase the number of customers' purchases?
OBJECT AND SCOPE OF THE STUDY
- The object of this research is the factors that affect the decision to buy Smartphone of customers at FPT Shop Da Nang.
-The object of investigation focuses on customers who have bought, are buying and intend to buy Smartphone at FPT Shop Da Nang.
FPT Shop, located at 186 Ton Duc Thang, Da Nang City, offers comprehensive sales research, technical support, and customer care services throughout the entire purchasing process, including before, during, and after the product acquisition.
The graduation internship at FPT Shop branch 186 Ton Duc Thang took place over a two-month period from March 8, 2022, to May 8, 2022 The research utilized secondary data from 2019 to 2021, while primary data was gathered through customer surveys conducted during the internship period.
RESEARCH METHODS
The qualitative research method involves conducting interviews with customers who have made purchases at the shop, as well as with the shop's staff, including the manager, to gather valuable insights and data.
The quantitative research method employs the SPSS tool to analyze data gathered from questionnaires, assessing the impact of various factors on customer purchase decisions.
STRUCTURE OF THE THESIS
The study consists of 5 chapters:
LITERATURE REVIEW
OVERVIEW OF THE THEORY OF CUSTOMERS' BUYING
2.1.1 Concepts of customer buying behavior
Customer behavior encompasses all actions consumers take in the process of product exchange, including researching, buying, using, assessing, and disposing of products and services to meet their needs (Schiffman & Kanuk, 1997).
Customer behavior encompasses the actions associated with acquiring, consuming, and disposing of goods and services, as well as the decision-making processes that precede and follow these activities (Engal, Blackwell & Miniard, 2006).
Consumer behavior, as defined by Philip Kotler (2001), encompasses the examination of how individuals, groups, and organizations make decisions regarding the selection, purchase, usage, and disposal of goods, services, ideas, and experiences to fulfill their needs and desires.
Consumer behavior, as defined by Peter D Bennet in 1988, refers to the actions exhibited by consumers in the processes of searching for, purchasing, utilizing, and assessing products and services that they believe will meet their personal needs.
In summary, I will apply philip Kotler's theory of customers’ buying behavior.
Figure 2.1: Consumer behavior Philip Kotler (1999)
(Source: Consumer behavior model of Philip Kotler)
According to Philip Kotler (1999), the customer buying process consists of five stages The first stage is need recognition, where consumers become aware of their needs due to problems in their daily lives For instance, a student learning a foreign language may realize the necessity of owning a dictionary The second stage involves seeking information about the product, as consumers turn to friends, relatives, the Internet, newspapers, and consultants to gather insights In the third stage, consumers compare products from different brands, focusing on those that meet their specific needs and desires.
Evaluate alternatives Decide to buy
- Satisfied: continue to use in the future, let people around know about the product.
Consumers who are dissatisfied with a product should refrain from continued use and share their experiences regarding product defects Each consumer has specific criteria that influence their purchasing decisions; for instance, those seeking a durable and affordable mobile phone may gravitate towards Nokia, while others might prefer the stylish options from Sony, despite the higher price Once a brand is chosen, the consumer proceeds to the store to make the purchase, although external factors such as the opinions of others or unexpected events can alter their decision For example, if a family member disapproves of the chosen product or if an unforeseen incident, like theft, occurs, the consumer may opt for a different item After purchasing and using the product, consumers evaluate it based on quality, features, service, and after-sales support Therefore, it is crucial for marketers to assess customer satisfaction post-purchase, as this significantly influences future buying intentions.
In 2005 Philip Kotler systematized the factors that lead to consumers' purchasing decisions and created a model of buyer behavior:
Figure 2.2 Model of buying behavior Philip Kotler (2005)
(Source: Model of buying behavior Philip Kotler, 2005)
2.1.4 Theories that explain customer buying behavior
2.1.4.1 Theory of rational action (TRA)
The Theory of Rational Action (TRA), established by Ajzen and Fishbein in 1975, posits that an individual's behavior is driven by their intention to engage in that behavior This intention is primarily influenced by two key factors: personal attitudes and subjective norms Over the years, the TRA model has been refined and expanded to enhance its applicability.
Diagram 2.1 Theory of Rational Action (TRA)
(Source: Fishbein and Ajzen, 1975) 2.1.4.2 Theory of Planned Behavior (TPB)
The Theory of Planned Behavior (TPB), introduced by Ajzen in 1991 and evolved from the Theory of Rational Action (TRA) by Ajzen and Fishbein in 1975, posits that an individual's intention to engage in a behavior is a key predictor of that behavior Additionally, Ajzen identifies perceived behavioral control as a crucial factor influencing people's intentions, highlighting its significance in understanding and predicting behavior.
Diagram 2.2 Theory of Planned Behavior (TPB)
2.1.4.3 Theory of the technology acceptance model (TAM)
The Technology Acceptance Model (TAM), as outlined by Davis (1986), is designed to explain and forecast the acceptance and utilization of technological products This model incorporates five key variables: extrinsic variables, perceived benefits, perceived ease of use, usage attitudes, and purchase intentions.
In which, the two basic elements of the model are perceived benefits and perceived ease of use.
Diagram 2.3: Technology Acceptance Model (TAM)
2.1.4.5 Development situation of Smartphone in the world
We are currently in the 4.0 era, characterized by rapid technological advancements and significant growth in the electronic industry, leading to an increasing demand for convenient information related to entertainment The journey began in 1973 with the invention of the first mobile phone, which addressed the need for remote communication However, as human needs evolved, the desire for more functionality and convenience led to the creation of the world's first smartphone, Simon, developed by IBM and launched at the Wireless Conference in 1993.
Smartphones have become essential tools for communication, work, and entertainment, offering features like video call capabilities that enhance user experience They are increasingly replacing laptops due to their versatility and affordable pricing, contributing to a competitive retail market As a result, many individuals now own multiple smartphones, often two or three, to better meet their diverse needs.
Smartphones not only enhance communication, work, and entertainment but also serve as a reflection of personal style and social status High-end models with unique and aesthetically pleasing designs allow individuals to express their class and individuality.
As of January 2021, there are 5.22 billion smartphone users globally, representing 66.6% of the world's population Since January 2020, the number of smartphone users has risen by 1.8%, adding 93 million users, while the total number of mobile connections has grown by 0.9%, reaching 8.02 billion.
(Source: data from vov.vn)
2.1.4.6 The situation of using smartphones in Vietnam
In Vietnam, owning a smartphone with a wide range of convenient features is now possible for just over 1 million VND The country has seen significant advancements in mobile connectivity, with 3G, 4G, and even 5G networks available in major cities This growth is complemented by the rapid development of the Internet and smart applications, enabling users to accomplish virtually anything they desire using just their smartphones.
Network operators, businesses, and retailers are competing to broaden their market reach, leading to a wider array of smartphone services such as shopping, travel, payments, and navigation The decline in smartphone prices, coupled with enticing promotions, allows consumers to select devices that fit their preferences and budgets Consequently, it's common for individuals to own multiple smartphones—often one, two, or even three—based on their specific needs and financial capabilities.
PRIVIOUS RESEARCH MODELS
2.2.1 Analysis of factors affecting customers' decision to buy mobile phones at FPT Shop, Le Thi Diem My (2019)
Figure 2.3 Le Thi Diem My's revised research model
(Source: Le Thi Diem My, 2019)
This study identifies five key factors influencing customers' mobile phone purchase decisions at FPT Shop: Product, Price, Brand, Employee, and Promotion, as determined through Cronbach's Alpha testing.
Anova test shows that there is no difference in purchasing decisions with customer groups in terms of gender, occupation and information retrieval method.
Besides, there is a difference between the purchase decision and the age and income of customers for mobile phone products at FPT Shop.
In addition, the study also found a strong influence between the factors of product, price, brand, staff, promotion on customer's decision to buy mobile phone in FPT Shop.
2.2.2 Factors affecting consumers' smartphone buying behavior in Da Nang city, MSc Le Nhan My, Le Thi My Ngan (2019)
Figure 2.4 Proposed research model of MSc Le Nhan My, Le Thi My Ngan
(Source: MSc Le Nhan My, Le Thi My Ngan 2019)
The study reveals that in Da Nang City, the primary factors influencing consumers' smartphone shopping behavior include perceived quality, brand loyalty, brand reputation, pricing, and the impact of word-of-mouth marketing, particularly through promotional strategies.
The buying behavior of consumers will greatly affect the business development strategy of businesses in the smartphone market, represented by technology retailers.
Brand loyalty Marketing form Word of mouth
2.2.3 Factors affecting the smartphone purchase decision of
Malaysian millennials, Karen Lim Lay-Yee et al., 2013
Figure 2.5 Proposed research model of Karen Lim Lay-Yee, Han Kok-Siew,
Research by Karen Lim Lay-Yee et al (2013) indicates that most smartphone users prioritize functionality when evaluating a product To meet consumer demands, smartphone manufacturers should conduct thorough research to identify essential features, such as improved camera resolution, enhanced operating systems, and innovative, lightweight designs, along with other software and hardware advancements.
Convenience is a key factor influencing smartphone purchases, as research shows that users prefer smartphones for their ability to complete tasks quickly without the need for laptops Additionally, brand reputation plays a significant role in the buying decision, highlighting the importance for smartphone manufacturers to establish strong brands through innovation and pioneering features.
The consumer decision process is influenced not only by the smartphone's unique selling proposition but also by factors such as exceptional customer service and social responsibility Additionally, dependence on smartphones significantly impacts purchasing decisions, as many users feel insecure without their devices.
2.2.4 Factors Influencing Purchasing Intention Of Smartphone Among University Students, Azira Rahim et al, 2015
Figure 2.6 Azira Rahim 's proposed research model, Siti Zaharah Safin,
Law Kuan Kheng, Nurliyana Abas, Siti Meriam Ali
This study examines the factors affecting smartphone purchase intentions among Malaysian university students, focusing on the interplay between product features, brand name, social influence, and product sacrifice Data was gathered from 367 graduates at UiM Kedah and analyzed to uncover these relationships.
This study confirms a significant positive relationship between product features and smartphone purchase intention, aligning with previous research (Ling et al., 2006; Lay-Yee et al., 2013) Additionally, the findings support Hypothesis 2, indicating that brand name also positively influences purchase intention, as evidenced by Lay-Yee et al (2013) among Malaysian millennials Furthermore, a notable correlation between social influence and smartphone purchase intention was identified, consistent with earlier studies (Mohd Azam, 2012; Suki & Suki, 2013; Lay-Yee et al., 2013) Ibrahim et al (2013) reported a moderate positive association of social influence with smartphone purchase intention, specifically among adolescents aged 19 to 26 in Perlis.
Research indicates that college students' reliance on smartphones is significantly shaped by social influence, which in turn positively affects their purchasing behavior (Ting et al., 2011) To enhance smartphone adoption among this demographic, marketers are encouraged to foster positive word-of-mouth among friends and family Furthermore, the decision to utilize smartphones often extends beyond individual choice, highlighting the critical role of social dynamics in this trend (Park et al., 2013).
2.2.5 Factors effecting smartphone purchase decisions of generation Y, Nushrat Shabrin et al., 2017
Figure 2.7 Nushrat Shabrin's proposed research model, Sarod Khandaker, Saad Bin
Abul Kashem, Chan Kit Hie, Teresa Susila
(Source Lay-Yee et al (2013) and Wei and Lo (2006)
Hypothesis 1 posits a significant relationship between brand interest and the smartphone purchase decisions of Generation Y in Kuching Research by Liew (2012), Lay-Yee et al (2013), Ding et al (2011), Mudondo (2014), and Suki (2013) indicates a notable connection between convenience and smartphone buying behavior Consequently, it is anticipated that a strong correlation exists between these two variables within our sample, leading to the formulation of Hypothesis 2.
Hypothesis 2 posits a significant relationship between convenience and the smartphone purchase decisions of Generation Y in Kuching Research has extensively explored the concept of dependence, revealing a strong correlation between dependence and smartphone purchases (Ding et al., 2011; Lay-Yee et al Suki, 2013).
- Hypothesis 3: There is a significant relationship between the dependency and smartphone purchase decision of Generation Y in Kuching.
Price is a critical factor influencing smartphone demand, as highlighted by researchers such as Chow (2011), Chew (2012), and Khan et al Their studies confirm that price significantly impacts consumers' purchasing decisions when it comes to smartphones.
(2014) and Lay-Yee et al (two thousand and thirteen).
Hypothesis 4 posits a significant correlation between price and the smartphone purchasing decisions of millennials in Kuching Smartphones, equipped with various features, play a crucial role in influencing consumer choices According to Mudondo (2014), the design features of smartphones can significantly impact the decision-making process for potential buyers.
- Hypothesis 5: There is a significant relationship between product features and the decisive smartphone purchase of Generation Y in Kuching.
- Hypothesis 6: There is a significant relationship between social influence and smartphone purchase decision of Generation Y in Kuching.
Smartphones are a useful tool for communication It is argued that smartphones have revolutionized communication We find evidence of a statistically significant correlation between smartphone purchase decisions by
Millennials in Kuching, brand of smartphone device, product feature, and social influence festival.
The study's findings align with existing literature that emphasizes the significance of brand image in smartphone purchase decisions, as noted in prior research (Liew 2012; Lim et al 2013; Ding et al 2011; Mudondo 2014; Suki 2013) Additionally, social influence has been identified as a key factor affecting smartphone purchases (Ding et al 2011; Suki 2013; Chew 2012), thereby validating hypotheses H1, H5, and H6 However, the research did not find a distinct correlation between dependence, price, convenience, and social needs with the smartphone purchasing decisions of Generation Y, leading to the rejection of hypotheses H2, H3, H4, and H7.
2.2.6 Comparison table of variables of the premise research
Table 2.1 Comparison table of variables of the premise research:
Product Price Brand Staff Promotion Warranty andcare dependency belong Socialinfluence Marketingform Convenience
Analysis of factors affecting customers' decision to buy mobile phones at FPT
Nhan My, Le Thi My
Factors affecting the intention to buy a phone
Factors affecting the smartphone purchase decision of millennials - Nushrat
The variable comparison table of these antecedent studies has high reliability, helps to filter out and draw reasonable research variables, similar to the topic that I am researching.
RESEARCH METHODOLOGY
OVERVIEW OF DIGITAL RETAIL JOINT STOCK COMPANY FPT .27
- Company name: FPT Digital Retail Joint Stock Company (referred to as FPT Retail)
- Business fields: Technological products and equipment, technology services, household appliances, pharmaceuticals, medical instruments, genuine functional foods,
- Website: https://fptshop.com.vn/
Partners: Apple, Samsung, Oppo, Xiaomi, Dell, Acer, Asus, Lenovo, HP,
Toshiba, Fujitsu, SonyErisson, Canon, Panasonic, AAA,
Corporate customers: Pepsico, Manulife, Thai Tuan, Kinh Do, BMW, Hoa
Individual customers: consumers all over the country
FPT Digital Retail Joint Stock Company, commonly known as FPT Retail, was established in 2012 in Vietnam and operates two retail chains: FPT Shop and F.Studio By FPT With a total of 630 stores across 63 provinces and cities in Vietnam, FPT Retail employs approximately 6,000 staff members Additionally, the company has a subsidiary, FPT Pharma, further expanding its business portfolio.
On April 26, 2018, FPT Retail's shares were listed on the Ho Chi Minh City Stock Exchange (HOSE) under the trading code FRT FPT Shop operates a retail chain focusing on mobile digital products and home appliances, offering a wide range of items including mobile phones, tablets, laptops, watches, components, accessories, and public services.
FPT Shop, the first retail system in Vietnam to receive the ISO 9001:2000 quality management certification, is currently the second largest technology retail chain in the country.
F.Studio by FPT is Vietnam's premier authorized Apple store chain, specializing in genuine Apple products As the first retailer to establish a comprehensive Apple store model, FPT Retail offers a full range of services, including Level 1 APR (Apple Premium Reseller), Level 2 AAR (Apple Authorized Reseller), and iCorner Customers can enjoy an exceptional experience with Apple's innovative technology, complemented by top-tier sales and customer care.
FPT Pharma (founded on September 13, 2018) owns a chain of Long Chau Pharmacy specializing in trading in genuine pharmaceuticals, medical instruments, and functional foods.
Figure 3.1 Affiliated member units FPT
FPT Digital Retail Joint Stock Company aims to be a trusted partner for top global digital manufacturers while serving as a reliable choice for Vietnamese customers As society and technology evolve, the company is committed to continuous improvement and establishing a strong reputation in the digital market.
Mission: With the goal of expanding store coverage nationwide, FPT
Digital Retail Joint Stock Company aspires to be Vietnam's premier retail system for digital telecommunications products As FPT Shop expands, it is committed to delivering exceptional shopping experiences to all customers by offering high-quality, competitively priced genuine digital products, complemented by outstanding customer service The company's friendly customer care is backed by its strong reputation in the industry.
-Quality: Always taking the lead in building credibility and responsibility to ensure product quality, FPT Retail gives customers absolute peace of mind when shopping for technology products.
-Trust: The word "credibility" is what FPT Retail always focuses on in brand development, a solid fulcrum for customers, and a reliable partner with technology companies.
-Friendly: The image of FPT Retail being customer-friendly and active in community activities is the long-term direction.
-Care: With the goal of serving customers as the number one priority, FPT
Retail is increasingly improving service quality, training enthusiastic, honest,sincere staff to satisfy any customer who comes to us shopping.
3.1.1.2 Organization chart of Digital Retail Joint Stock Company FPT
(Source: Human resources department FPT Shop)
Figure 3.2 Oganizational structure of FPT Digital Retail joint stock company
FPT Retail has achieved significant recognition, including being listed in the Top 100 for "Prestigious and Quality Products and Services" by the Vietnam Standards and Consumer Protection Association The company has also been honored as Vietnam's Strong Brand for three consecutive years (2013, 2014, 2015) and was voted the Most Favorite Retailer in 2016 by Economic Times VN.
In July 2017, FPT Retail ranked among the Top 4 leading retailers in Vietnam and the Top 500 in the Asia-Pacific region, according to Retail Asia By November 2017, it was recognized as one of the 10 most reputable retailers in a survey conducted by Vietnam Report and Vietnamnet With a turnover of $15,717 per square meter, FPT Retail has been identified as the most efficient retailer in Vietnam, as reported by Euromonitor and Retail Asia Publishing.
In 2019, FPT Retail reported a revenue of VND 16,634 billion, reflecting a 9% increase from the previous year Online sales significantly contributed to this growth, generating VND 3,899 billion, a remarkable 60% rise compared to 2018, and comprising 23.4% of the company's total revenue However, the company's pre-tax profit saw a decline, reaching VND 278 billion, down 36% year-on-year.
By the end of 2021, FPT Digital Retail Joint Stock Company achieved remarkable financial growth, with a revenue increase of 53% and a pre-tax profit soaring to VND 554 billion, which is 19.5 times higher than the previous year The Long Chau Pharmacy chain significantly contributed to this success, generating VND 3,977 billion in revenue, a 3.3-fold increase compared to 2020, and enabling Long Chau to turn a profit for the year.
Regarding the store network, by the end of 2021, the FPT Shop chain has
As of now, there are 647 stores, marking an increase of 52 stores since the start of 2021 Additionally, the Long Chau chain has expanded to 400 pharmacies, which is a growth of 200 pharmacies compared to the beginning of 2021.
In 2021, FPT Shop's laptop segment earned VND 5,700 billion, an increase of2.2 times compared to 2020 According to GfK, in the first 11 months of 2021, FPT
Shop maintains its position as the No 1 laptop retailer in the market when 35% market share.
About FPT Shop retail system
Established in August 2007, FPT Shop has grown to over 630 retail locations across 63 provinces and cities in Vietnam The stores feature modern, comfortable shopping environments situated along major routes for easy customer access With a professional and friendly staff dedicated to providing attentive service, FPT Shop prioritizes customer satisfaction to enhance the shopping experience Customers can explore a wide selection of high-quality, genuine products, including popular smartphone brands such as Apple, Samsung, Oppo, Xiaomi, Nokia, Huawei, Vsmart, and Vivo.
- Currently FPT Digital Retail Joint Stock Company Da Nang branch has the following facilities:
+ FPT Shop A1 Nguyen Van Linh is extended
+ FPT Shop Store 671-673 Ton Duc Thang
+ FPT Shop Shop 7-9 Nguyen Van Thoai
+ Shop F.Studio by FPT 240 Hoang Dieu (2B Nguyen Van Linh)
+ FPT Shop 204-206 Nguyen Tri Phuong
+ FPT Shop 592 Dien Bien Phu
+ FPT Shop 137 Ong Ich Duong
+ FPT Shop 186 Ton Duc Thang
+ FPT Shop A8 Vo Van Kiet
+ Extended A1 Nguyen Van Linh Laptop Center
+ FPT Shop 360 Le Van Hien
3.1.2 The organizational structure of FPT Shop's store department
Figure 3.3 Structure of FPT Shop's stores
(Source: FPT Shop Human Resources Department)
Functions and duties of each department:
- Responsible for the organization, management of people and assets, running all activities of the establishment.
- In charge of developing the store development plan, implementing the store's sales targets.
- External relations with local government agencies, agencies inside and outside the industry in the area of operation of the establishment.
- Implement market work to attract customers.
- Manage and support employees to complete their work.
- Ensure the image according to the standards at the store.
- Customer care during and after the sale
- Support management to solve store problems.
- Responsible for the achievement of the store's sales targets.
- Ensure the full range of goods at the store.
- Implement marketing activities to attract customers.
- Manage and support employees to complete the work.
- Ensure the image according to the standards at the store.
- Customer care during and after the sale
Including PG staff of partner companies to mobilize to increase consulting capacity for customers, companies such as: Samsung, Oppo, Xiaomi, …
- Actively welcome customers to the store.
- Communicate happily with customers about expectations for the products and services they are looking for in the store.
- Handle customer complaints and inquiries.
- Achieving the assigned monthly sales target.
- Support agents, point of sale in equipping advertising publications, providing information and sales operations.
- Coordinating with the accounting department for loan payment and return of goods Quantity: 2 Sales people, 3 PG
- Receive information about customers, products and services sold from sales consultants.
- Update customer information, products sold on the system.
- Collect money accurately, issue invoices quickly to customers.
- Manage and hand over the treasury in the working shift.
- Prepare in-store revenue and expenditure reports.
- Check products before handing over to customers.
- Get the machine to do technical installation, warranty, repair and cleaning at the store.
- Participate in communication programs to attract customers such as handing out leaflets, pasting posters,
- Check all documents and goods in stock.
- Organize and manage goods in the warehouse according to the correct method.
- Periodic inventory of goods in the warehouse
- Keep the car, arrange the customer's car to the store.
- Actively welcome customers to the store.
- Happy to communicate and exchange with customers
3.2 BUSINESS ACTIVITIES OF THE COMPANY
3.2.1 Business results in 2020 compared to 2019
Figure 3.4 Graph showing business results in 2019-2020 of FPT Shop
(Source: Annual Report 2020, http://www.fpts.com.vn/)
Looking at the chart above, we can see that FPT Shop's operating revenue in
2020 increased very little, and operating expenses increased even more than in
In 2020, FPT Shop experienced a significant decline in pre-tax accounting profit, dropping by approximately 25 billion VND compared to 2019, largely due to the adverse effects of the COVID-19 pandemic on the business landscape and a sharp decrease in revenue from financial activities In response, the company has proactively sought strategies and initiatives aimed at enhancing its business performance and achieving better results in 2021.
3.2.2 Outstanding financial indicators for 3 years 2019, 2020 and 2021
Figure 3.5 Outstanding financial indicators of FPT Shop in 3 years 2019,
(Source: Annual Report 2021, http://www.fpts.com.vn/)
Between 2019 and 2021, the company demonstrated significant efforts to revitalize its operations by implementing new business strategies that transformed its landscape In 2021, the profit after tax surged to approximately 845.97 trillion VND, marking a remarkable increase of nearly four times compared to 214.30 trillion VND in 2019 Additionally, this figure reflects a fivefold growth from the profit after tax of 170.55 trillion VND in 2020, highlighting the company's impressive financial turnaround.
From 2019 to 2021, the company's total assets experienced substantial growth, rising from 8.53 trillion to 13.17 trillion This significant increase reflects a major transformation in the company's operational processes and overall business performance.
3.2.3 Revenue results of FPT Shop 186 Ton Duc Thang in March 2022
Figure 3.6 FPT Shop's March 2022 revenue 186 Ton Duc Thang
(Source: FPT Shop manager 186 Ton Duc Thang)
From the image of the March 2022 revenue report at FPT Shop at 186 Ton Duc Thang- Da Nang, we can see that smartphones are a source of revenue.
RESEARCH PROCESS
RESEARCH RESULTS
DESCRIBED SAMPLES
A total of 239 questionnaires were distributed to managers, employees at FPT Shop, and customers who purchased smartphones from the store, resulting in 200 valid responses This sample size of 200 meets the minimum requirements for validity, and the classification structure is based on specific criteria.
Frequency Percent Valid Percent Cumulative Percent Valid
Figure 4.1 Graph showing gender of survey participants
A recent survey of 200 valid questionnaires revealed a significant gender disparity, with 130 male respondents (65%) and 70 female respondents (35%) This data highlights the pronounced difference in the sex ratio, which mirrors the employee and customer demographics at FPT Shop, maintaining an economic ratio of 65/35.
Figure 4.2 Graph showing the age of survey participants
Frequency Percent Valid Percent Cumulative Percent
The survey analyzed 200 valid questionnaires, revealing that 39% of respondents are aged 26 to 40, while 37.5% fall within the 18 to 25 age group Additionally, 13.5% of participants are between 41 and 50 years old, 11% are under 18, and 9% are over 50.
We see that the age with the most demand for smartphones is from 18 to 40 years old.
Frequency Percent Valid Percent Cumulative Percent
Looking at the results, we can see that the majority of
Figure 4.3 Graph showing the job of survey participants
Missing 0 customers who buy smartphones at FPT Shop do business with 66 people and account for 33% of those who participated in the survey Next are 58 people working as officials and office workers, accounting for 29% There are 42 students and students, accounting for 21%, 22 workers account for 11% and the rest 12 people work in other occupations, accounting for 6%.
Frequency Percent Valid Percent Cumulative Percent
The results show that most of the survey participants have an
The survey results indicate that among participants with incomes ranging from 6 to 20 million, 72 individuals (36%) earn between 10 to 20 million Additionally, 55 participants (27.5%) fall within the 6 to 10 million income bracket Furthermore, 26 respondents (13%) reported incomes between 3 to 6 million, while 25 participants (11%) earn below 3 million Notably, there are also 22 survey participants with incomes exceeding 20 million, representing 11% of the total.
4.1.5 Where do you know FPT Shop from?
The number of survey participants who know FPT Shop through friends is 69 people (accounting for 34.5%), the number of people who know FPT
Shop through self-study is
61 people Figure 4.5 Graph showing where did the survey (accounting participants know FPT Shop
Frequency Percent Valid Percent Cumulative Percent
A survey revealed that 30.5% of respondents are aware of FPT Shop, with 14.5% learning about it through advertising and leaflets, while 13% were informed by family members Additionally, 7.5% of participants discovered FPT Shop through other means.
4.1.6 Relationship between Age and Sex
Value df Asymp Sig (2- sided)
N of Valid Cases 200 a 2 cells (20.0%) have expected count less than 5 The minimum expected count is 3.15.
The relationship between age and sex was analyzed using a chi-square test, revealing that men comprised 65% of the total participants, with the majority falling within the 26-40 age range (42.3%) and 18-25 age range (38.5%) In contrast, women accounted for 35% of the participants, with the highest proportions found in the 18-25 age group (35.7%) and the 26-40 age group (32.9%).
The Pearson Chi-Square value is 4.392, with no cell frequency below 5, degrees of freedom (df) at 4, and a statistical significance level (Sig 2-sided) of 0.356, which is greater than 5% This indicates that the two variables, gender and age, are independent, leading to the conclusion that there is no relationship between them.
The bar graph illustrates the distribution of data across various combinations of paired variables, revealing significant differences between men and women at all age groups.
4.1.7 Relationship between Job and Income
Student Business officers, office staff
Value df Asymp Sig (2- sided)
N of Valid Cases 200 a 9 cells (36.0%) have expected count less than 5 The minimum expected count is 1.32.
A chi-squared test was conducted to analyze the relationship between occupational variables and income, revealing that 33% of the 200 survey respondents, or 66 individuals, are employed in the business/trade sector.
The survey reveals that 36 respondents, or 54.5%, earn between 10 to 20 million Among the 58 office workers surveyed, 29% reported incomes of 6 to 10 million, with 30 individuals (51.7%) falling within this range Additionally, 42 students participated, making up 21% of the total, and 24 of them (57.1%) earned less than 3 million The survey also included 22 workers (11%), with 15 (68%) earning between 6 to 10 million Furthermore, 12 participants from other occupations accounted for 6% of the total, with 6 individuals (50%) earning 10 to 20 million Overall, a significant portion of the respondents, totaling 72 people (36%), reported salaries between 10 to 20 million.
The Pearson Chi-Square value is 206.836 with 16 degrees of freedom, and the statistical significance level (2-sided) is 0.000, which is less than 5% This indicates a significant relationship between occupation and income, suggesting that these two variables are dependent on each other.
4.2 CHECK THE RELIABILITY OF THE SCALE BY CRONBACH’S ALPHA 4.2.1 Cronbach's alpha test for the independent variable
4.2.1.1 Cronbach's Alpha test for the factor “Products”
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The "Product" factor is established from three observed variables, PD1, PD2, and PD3 Data analysis reveals a high Cronbach's Alpha coefficient of 0.989, indicating strong internal consistency, as it exceeds the acceptable threshold of 0.6 Furthermore, the corrected item-total correlation for the observed variables is greater than 0.3, confirming the reliability of the "Product" factor scale for subsequent analysis.
4.2.1.2 Cronbach's Alpha test for the factor “Price”
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
The "Price" factor is determined by three observed variables: PR1, PR2, and PR3 Data analysis reveals a Cronbach's Alpha coefficient of 0.768, which exceeds the acceptable threshold of 0.6 Additionally, the Corrected Item-Total Correlation for all observed variables is greater than 0.3, indicating that the "Price" scale is reliable for further analysis.
4.2.1.3 Cronbach's Alpha test for the factor “Brand”
Factor “Brand” is established from five observed variables from BR1 to BR3. Data analysis shows that the Cronbach's Alpha coefficient of the population is 0.897
The correlation coefficient for the observed variables in the "Brand" factor scale exceeds 0.3, indicating a strong relationship Consequently, the reliability of the scale, measured by the three observed variables BR1, BR2, and BR3, is confirmed for subsequent analysis.
4.2.1.4 Cronbach's Alpha test for the factor “Form of marketing and promotion”
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's Alpha if Item Deleted
Scale Mean if Item Deleted
Scale Variance if Item Deleted
FAVORITE ANALYSIS OF FACTORS EFA
4.3.1 EFA factor analysis for the independent variable
4.3.1.1 Testing the suitability of the EFA model (Kaiser-Meyer-Olkin)
Table KMO-EFA coefficient of components Factors affecting the decision to buy Smartphone at FPT Shop Da Nang
The KMO measure (Kaiser-Meyer-Olkin) has a value = 0.851, satisfying the condition 0.5 ≤KMO ≤ 1, so the exploratory factor analysis is consistent with the actual data.
4.3.1.2 Test the correlation between observed variables (Bartlett’s test)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .851
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .851
The results of Bartlett's test (Bartlett's test) have Sig value = 0.000 < 0.05. Therefore, the observed variables are correlated with each other in each factor group.
Component Initial Eigenvalues Extraction Sums of Squared
Rotation Sums of Squared Loadings
Extraction Method: Principal Component Analysis.
4.3.1.3 Check the extracted variance of the factors (% Cumulative variance)
The analysis results indicate that the total variance extracted (Total Variance Explained) for Component line No 5 is 68.915%, which exceeds the accepted threshold of 50% This signifies that 68.915% of the variation in the factors is effectively explained by the observed variables, meeting the required criteria for variance extraction.
Factor loading factor loading 0.5 in a sample of about 100 – 350, this study uses a sample size of 200 people including managers and employees at FPT Shop
186 Ton Duc Thang along with customers who have Buy smartphones here.
Extraction Method: Principal Component Analysis
Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 6 iterations.
The EFA analysis results indicate that all observed variables meet the criterion of a Factor Loading coefficient of at least 0.5, except for FMP2 and SI3, which will be excluded from further analysis Consequently, the factor analysis identified a total of six factors.
4.3.2 Factor analysis EFA for the dependent variable “Decision to buy smartphone”
4.3.2.1 Check the suitability of the EFA factor analysis model (Kaiser-Meyer- Olkin)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .851
The KMO measure (Kaiser-Meyer-Olkin) has a value = 0.851, satisfying the condition 0.5 ≤KMO ≤1 Therefore, factor analysis is consistent with the actual data.
4.3.2.2 Test the correlation between observed variables (Bartlett’s test)
Use Bartlett's test Test hypothesis H1: similarity level correlation of the variables is zero.
Bartlett's Test results have Sig value = 0.000 < 0.05 It can be concluded that observed variables are correlated with each other in each factor group.
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .851
4.3.2.3 Check the extracted variance of the factors (% Cumulative variance)
Component Initial Eigenvalues Extraction Sums of Squared
Rotation Sums of Squared Loadings
Extraction Method: Principal Component Analysis.
The analysis reveals that the total variance extracted exceeds the acceptable threshold of 50%, with a cumulative variance of 68.910% in Component row No 1, as indicated in the Total Variance Explained table This result confirms that the criteria for extracted variance are met.
MULTI-Variable Linear Regression ANALYSIS
4.4.1 Check correlation matrix between factors
The results of the test of correlation coefficient R are as follows:
F_DC F_PD F_PR F_BR F_FMP F_WC F_SI
** Correlation is significant at the 0.01 level (2-tailed).
The analysis of the correlation coefficient reveals a significant relationship between the smartphone purchase decision and various independent variables, including PD, PR, BR, FMP, WC, and SI These factors play a crucial role in influencing customer decision-making.
4.4.2 Check model fit (Adjusted R Square, ANOVA)
4.4.2.1 Explanatory level of the model (Adjusted R Square)
The analysis reveals an adjusted R value of 0.779, with a significance level of 0.000, indicating strong statistical relevance This suggests that 88.6% of the variation in smartphone purchasing decisions can be attributed to six key independent variables: Product (PD), Price (PR), Brand (BR), Form of Marketing and Promotion (FMP), Sales Consultant and Warranty (WC), and Social Influence (SI).
4.4.2.2 Model fit: Analysis of variance ANOVA
Model R R Square Adjusted R Square Std Error of the
1 886 a 786 779 15575 1.042 a Predictors: (Constant), F_SI, F_PD, F_BR, F_PR, F_WC, F_FMP b Dependent Variable: F_DC
Model Sum of Squares df Mean Square F Sig.
Total 21.857 199 a Dependent Variable: F_DC b Predictors: (Constant), F_SI, F_PD, F_BR, F_PR, F_WC, F_FMP
The confidence 99% (Sig 0.01) Show that the theoretical model is consistent with reality The independent variables have a linear correlation with the dependent variable in the model.
4.4.3 Check for autocorrelation of residuals (Autocorrelation)
Statistical analysis of residual autocorrelation of the regression equation
The statistical analysis reveals a value of d = 1.042 based on 200 observations and five parameters at a significance level of 0.01 According to the Durbin-Watson statistical table, the lower limit (dL) is 1.557 and the upper limit (dU) is 1.693 Since dU = 1.557 < d = 1.042 < (4 - dU = 2.443), it can be concluded that there is no autocorrelation among the residuals in the model, indicating that the model is statistically significant.
4.4.4 Testing regression coefficients and multicollinearity (Multiple Collinearity)
Standardized Coefficients t Sig Collinearity Statistics
B Std Error Beta Tolerance VIF
From the table results above, we can see that the independent variables PD,
PR, BR, FMP, WC and SI have the Sig t-test value greater than 0.05, the
Model R R Square Adjusted R Square Std Error of the
1 886 a 786 779 15575 1.042 a Predictors: (Constant), F_SI, F_PD, F_BR, F_PR, F_WC, F_FMP b Dependent Variable: F_DC independent variables are statistically significant and significant with the dependent variable DC.
The table above also shows the value of Variance Inflation Factor VIF < 2. Therefore, there is no multicollinearity in the model.
4.4.5 Testing the hypotheses of the research model
The coefficient of the regression model to test the hypotheses of the research model
Standardized Coefficients t Sig Collinearity Statistics
B Std Error Beta Tolerance VIF
4.4.5.1 Regression model with unnormalized regression coefficients
• B_PD = 0.119 Sign (+): The relationship is in the same direction When the product evaluation of FPT Shop (PD) increases by 1 point, the customer's purchasing decision level will increase by 0.119 points.
The analysis reveals a positive correlation between smartphone pricing at FPT Shop Danang and customer purchasing decisions, indicated by a B_PR value of 0.058 Specifically, for every 1-point increase in the evaluation of smartphone prices, there is a corresponding 0.058-point increase in the likelihood of customers making a purchase.
• B_BR = 0.156 Sign (+): The relationship is in the same direction When the brand rating of FPT Shop (BR) increases by 1 point, the customer's purchasing decision level will increase by 0.156 points.
The analysis reveals a positive correlation between the marketing and promotion security of FPT Shop (FMP) and customer purchasing decisions, indicated by a B_FMP value of 0.056 Specifically, for each 1-point increase in FMP, there is a corresponding increase of 0.056 points in the likelihood of customers making a purchase.
A positive correlation exists between the evaluation of sales and warranty advice at FPT Shop (WC) and customer purchasing decisions Specifically, for every 1-point increase in the evaluation, there is a corresponding 0.333-point increase in the likelihood of customers making a purchase.
Regression model of the form:
We have a regression model with unnormalized regression coefficients:
4.4.5.2 Regression model with normalized regression coefficients
This coefficient determines the position of influence of the independent variables From the results in the table above, the author builds a regression model with a standardized regression coefficient:
Deciding to buy a smartphone = 0.119 Product + 0.058 Price + 0.156 Brand + 0.056 Forms of Marketing and Promotion + 0.333 Sales and warranty consulting + 0.136 Social influence
In addition, the normalized regression coefficients can be converted to percentages as shown in the following table:
NO Variable Standard.Beta % Order of influence
4 FMP- Forms of Marketing and
5 WC- Sales and warranty consultancy 0.452 32% 1
Table 4.1 Normalized regression coefficient Variable WC - Sales and warranty consultant contributes 32%, variable SI - Social influence contributes 18%, variable BR - Brand contributes 16%, variable
PD - Product contributes 14% , variable PR - Price contributed 12% and variable FMP - Marketing and promotion form contributed 7%
Thus, the order that affects the decision to buy a smartphone at FPT Shop Danang is WC - Sales and warranty consulting, SI - Social influence, BR - Brand,
PD - Product, PR – Price and FMP - Form of Marketing and Promotion.
Table 4.2 Hypothesis testing of the model
H1: Products affect the decision to buy smartphones at FPT Shop Da Nang Accept H1 4
H2: Price affects smartphone purchase decision at FPT Shop Da Nang Accept H2 5
H3: Brand affect smartphone purchase decisions at FPT Shop Da Nang Accept H3 3
H4: Marketing and promotions affect smartphone purchase decision at FPT Shop
H5: Sales and warranty consultancy affect smartphone purchase decisions at FPT
H6: Social influence affects smartphone purchase decision at FPT Shop Da Nang Accept H6 2
In conclusion, the decision-making process for Duy Tan students when renting accommodation is influenced by several key factors: WC (Sales and Warranty Consultancy), SI (Social Influence), BR (Brand), PD (Product), PR (Price), and FMP (Form of Marketing and Promotion).