The influence of brand equity on customer purchase decision a case study of co opmart

1.1 Research problem

Objectives of the study

The general objective of this study investigate the influence of brand equity on customer purchase decision of products at Co.opmart in Ho Chi Minh city, Vietnam

The specific objectives of this study were to:

- Identify and analyze factors of brand equity affecting customer buying decision of products at Co.opmart in Ho Chi Minh city, Vietnam

- Examine the relationship between brand equity and consumer behavior on buying products at Co.opmart in Ho Chi Minh city, Vietnam

- Give recommendations to increase efficiency in attracting customers who buy products at Co.opmart in Ho Chi Minh city, Vietnam

Based on the objectives, the research finds out three main questions:

- Which are the factors influencing consumer purchase decision at Co.opmart in Ho Chi Minh city, Vietnam?

- How do factors affect customer buying decision at Co.opmart in Ho Chi Minh city, Vietnam?

- Which recommendations are suitable and effective to attract customers who consume products at Co.opmart in Ho Chi Minh city, Vietnam?

Subject and scope of the study

The subject of the study investigates the effect of brand equity on consumer purchase decision at Co.opmart in Ho Chi Minh city, Vietnam

The scope of the study analyzes customer who bought products at Co.opmart in Ho Chi Minh City, Vietnam.

Research methodology

The qualitative methodology is used to find out the study’s problem and based on related research about brand equity influence on consumer purchase

4 decision to propose a model In addition, the qualitative research is to discover variables and scales of each variable in the research model

Quantitative research was conducted through a model questionnaire for the purpose of doing a survey by respondents who consume products at Co.opmart in

In Ho Chi Minh City, Vietnam, a range of statistical tools, such as correlation and regression analysis, are utilized to examine survey data, with the analysis conducted using SPSS 22 software.

Organization of the study

The organization of this study will present a simply general description, with a total of five chapters:

This chapter describes the background of study, research objectives, scope of the study and research methodology

This chapter examines key theories relevant to the study, including brand equity and its essential components, the factors influencing customer purchase decisions, and the interplay between brand equity and customer purchasing behavior.

The theory gives explanation about method that used for collecting and analyzing on this study, including data sources, methodology, qualitative and quantitative research

In this chapter, data processing and step of analysis will be specific presented and discussed In addition, chapter 4 will conclude the hypotheses proposed in the

5 previous chapter and present the accepted and rejected hypotheses through the proven data

This chapter summarizes the key findings from Chapters 1 to 4, addressing the main issues and their corresponding solutions It also outlines the study's limitations and offers recommendations for future research The insights gained aim to effectively tackle the study's identified problems.

Summary

Chapter 1 provided an overview of this study and identified the objectives of the topic and questions to clarify the research problem In addition, this chapter presented research methodology and structure of the current study The next chapter will discuss theoretical perspectives of purchase decision

2.1 The basic of concepts

The concept of brand equity

Different writers have defined the word brand equity from various perspectives, and several methodologies with the purpose of assessing brand equity have been established in the existing literature

Brand equity is a vital marketing asset that fosters strong relationships between a company and its stakeholders, ultimately encouraging long-term purchasing behavior Understanding brand equity allows businesses to invest in their intangible assets, enhance brand value, and strengthen competitive advantages Increasing brand equity is crucial for companies, as it helps attract connections and emotional ties with potential customers.

Brand equity, as defined by Farquhar (1989), refers to the value that a brand adds to a product, often described as the extra utility associated with its brand name (Srivastava & Shocker, 1991) Recognized as a crucial intangible asset, brand equity enhances the perceived value of a product or service, significantly influencing consumer choices and brand loyalty.

7 people feel, remember and act in relation to a brand, prices as well as the market share (Hung, Su & Zhuang, 2016)

Brand equity refers to the collection of brand assets and liabilities linked to a brand name and symbol, which can enhance or diminish the value of a product or service According to Aaker (1991), it encompasses various factors that contribute to a brand's overall worth In contrast, Keller (1993) emphasizes that brand equity is shaped by brand knowledge, influencing customer reactions to marketing efforts when the brand is recognized and associated with strong, positive sentiments.

Brand equity theory

In the late 1980s, brand equity emerged as a pivotal concept in management philosophy, significantly influencing management theory and practice (Gonul & Srinivasan, 1996) This rise in importance has led to the creation of over 300 brand equity models worldwide, many of which emphasize consumer perspectives (Amirkhizi, 2005; Aaker & Joachimsthaler, 1999) This research specifically examines consumer-based brand equity as defined by Aaker (1991) and Keller (1993), highlighting how brand knowledge distinctly affects customer decision-making.

Aaker's (1991) conceptual definition of brand equity provides a foundational framework for understanding brand equity from the consumer's perspective, integrating both behavioral and attitudinal dimensions This model is recognized as a comprehensive tool for analyzing brand equity, making it essential for effective brand management and offering valuable insights into customer perceptions.

Brand equity is a multifaceted concept that can be understood in various ways According to Keller (2002), it consists of two primary elements: awareness and association In contrast, Aaker (1991) identifies five key components of brand equity: brand awareness, brand association, brand loyalty, perceived quality, and proprietary brand assets, which include trademarks, patents, and channel relationships.

Figure 2.1: Brand equity model (Aaker, 1991)

This study utilizes Aaker's (1991) brand equity model, which is one of the most frequently referenced frameworks in the literature The model has been validated through various experimental studies, confirming its relevance and applicability.

9 research to examine the influence of brand equity on customer purchase decision: A case study of Co.opmart.

The concept of customer behavior

Customer behavior encompasses the study of how individuals, groups, and organizations make decisions regarding the selection, purchase, consumption, and disposal of products, services, ideas, or experiences to satisfy their needs and desires (Kotler & Keller, 2008) It involves examining the purchasing units and the exchange processes linked to acquiring, using, and discarding these offerings (Michael, 2000) Research in this field focuses on how individuals allocate their resources—such as money, time, and effort—toward purchasing products or services (Schiffman & Kanuk, 2007) Additionally, consumer behavior involves the various activities individuals engage in while searching for, selecting, buying, consuming, reviewing, and disposing of goods and services to fulfill their wants and needs (Belch and Belch, 1998) This behavior can be observed at both individual and organizational levels.

Customers can be categorized into two main groups: personal and industrial Personal consumers purchase products and services for personal use or as gifts, while organizational customers acquire them to support business operations, encompassing both profit-driven and non-profit entities, including government and non-government organizations.

The concept of purchase decision

Customer buying decisions involve gathering and processing information to identify and evaluate the best options for addressing a specific need or problem, ultimately leading to a purchasing choice (Prasad & Jha, 2014).

10 unpredictable process and buyer can rely on the data on a specific items as well as their own experience to make a buying decision

According to Schiffman and Kanuk (2007), customers typically rely on their past purchase experiences as an internal source of information before seeking additional information from external sources This previous buying experience, along with marketing efforts and non-commercial information, plays a significant role in shaping customer decision-making.

To effectively understand customers' purchase decisions, marketing managers must comprehend the consumption process and the perceived benefits of their products and services (Blackwell et al., 2001) The authors emphasize that customers navigate several stages when planning to purchase specific items, which significantly influence their decision-making and subsequent behavior after the purchase.

Philip Kotler (2003) outlines a five-stage model of the customer purchase decision process, which serves as a valuable framework for understanding how consumers select products or services These stages are crucial for analyzing consumer behavior during the buying process.

Third stage: Evaluation of alternatives

Fifth stage: Post - purchase behavior

Figure 2.2: Customer buying decision process (Phillip Kotler, 2003)

Problem recognition is the crucial first stage in the customer purchase decision process, where consumers identify their needs or problems and consider products that can address them This stage is vital because without recognizing a need, customers are unlikely to contemplate a purchase Additionally, customer demand can be influenced by various internal and external stimuli.

Information search is the second stage in customer buying decision process

At this stage, customers aware of a specific problem or need are motivated to seek information to evaluate the value of a product or service They consult various sources, including personal recommendations from family and friends, public feedback such as customer reviews and magazines, as well as commercial sources like advertisements and salespeople, along with their own experiences.

The evaluation of alternatives is the third step in the consumer buying decision process, where customers assess various product and brand options to identify which one offers the best value.

Customer attitudes and their level of involvement with a product or brand play a crucial role in the decision-making process When consumer involvement is high, individuals are likely to assess multiple brands; conversely, if involvement is low, they tend to focus on just one brand.

The purchase decision is the crucial fourth stage in the customer buying process, where consumers intend to buy their preferred brand, product, or service after evaluating alternatives and assessing the value offered However, this final decision can be influenced by factors such as the opinions of social circles like friends and family, as well as specific buying conditions including the location of the transaction and payment methods Consequently, sales promotions and after-sales services are vital in enhancing competitiveness in the market.

Post-purchase behavior is the final phase of the customer buying decision process, where consumers evaluate their satisfaction with a purchase Their feelings about the product can significantly influence their likelihood of repurchasing Additionally, consumers' experiences—whether positive or negative—can impact the purchasing decisions of others, as they often share their opinions about the product or service.

Previous studies

This study examines how brand equity affects customer purchasing decisions for cell phones in Addis Ababa Data was collected through questionnaires distributed to 404 respondents in the city The research employed statistical and descriptive analysis, utilizing correlation and regression analysis in SPSS to interpret the results Findings indicate that both brand awareness and perceived quality positively influence customer buying decisions for cell phones in Addis Ababa.

However, this research has conceptual, geographical and technical limitations (Beyene & Daniel, 2021)

Figure 2.3: A model of purchase decision, Beyene & Daniel (2021)

The study titled "Impact of Brand Equity on Consumer Purchase Decision of Smartphones: A Study on University Students in Chittagong, Bangladesh" investigates how brand equity influences smartphone purchasing decisions among university students in Chittagong A survey of 300 respondents, primarily university students, employed convenience sampling and was analyzed using reliability and regression analysis in SPSS The findings indicate that brand equity factors—such as brand awareness, brand association, perceived quality, and brand loyalty—positively impact customer behavior (Syed et al., 2020).

Figure 2.4: A model of consumer purchase decision, Syed, Kazi, Zohir, Ishtiak

This study investigates how brand equity impacts customer purchase intent, focusing on key factors such as brand awareness, brand association, perceived quality, and brand loyalty Data was gathered from various marketplaces in Kuala Lumpur and Selangor, Malaysia, using close-ended questionnaires The findings reveal a strong correlation between brand loyalty and brand association with consumer purchase intent, while brand awareness and perceived quality show no significant relationship with purchase intent (S Rungsrisawat et al., 2019).

Figure 2.5: A model of purchase intention, Rungsrisawat & Sirinapatpokin

This research investigates how brand awareness and brand loyalty influence customer purchase behavior in Faisalabad's garment industry A questionnaire was distributed to a sample of 300 respondents, and data analysis was conducted using regression and correlation techniques via SPSS - 21 software The findings indicate that both brand awareness and brand loyalty significantly and positively affect buying decisions However, the study is limited to these two factors impacting customer buying behavior (Muhammad & Arshia, 2019).

Figure 2.6: A model of purchase behavior, Muhammad & Arshia (2019)

The study “The infuence of brand equity toward consumer purchase decision

In the study "A Case Study of Samsung Smartphone in Bekasi" by Rocky Simon Hia (2017), the author investigates the significance of brand equity and its components—brand awareness, brand association, perceived quality, and brand loyalty—on customer purchasing decisions Utilizing a quantitative approach, the researcher analyzed data from 300 Samsung smartphone users in Bekasi with the help of SPSS and AMOS tools The findings reveal that brand loyalty and perceived quality significantly impact consumer buying behavior.

Purchase Decision associated with consumer purchase intention, whereas brand awareness and brand association are not significantly related to buying decision

Figure 2.7: A model of purchase decision, Rocky Simon Hia (2017)

The study "Impact of Brand Equity on Consumer Purchase Decision of Dairy Products" by Maulik & Ashish (2017) investigates the relationship between brand equity and consumer purchasing decisions in Anand, a city known for its dairy products The research identifies four key components of brand equity: brand awareness, perceived quality, brand association, and brand loyalty Utilizing a convenience sampling method, data was gathered from 200 dairy product consumers in Anand Findings indicate that brand awareness significantly influences customer purchase intentions, while brand association does not affect purchasing decisions However, the study's limitation lies in its focus on Anand, which may not accurately represent the broader population of the country.

Figure 2.8: A model of purchase decision, Maulik & Ashish (2017)

The research conducted by Muhammad & Sameen (2016) examines the influence of brand equity on consumer purchasing decisions for mobile phones, emphasizing key factors such as brand association, brand awareness, brand quality, and brand loyalty The study gathered data from 300 respondents, both male and female, across various regions of Karachi and Lahore through simple random sampling Utilizing correlation and regression analysis via SPSS, the findings reveal that all four components of brand equity significantly affect consumer buying decisions, with brand loyalty identified as the most crucial factor influencing cell phone purchases.

Figure 2.9: A model of consumer purchase decision, Muhammad & Sameen

The study by Naeem et al (2016) examined the impact of brand equity on consumer purchasing decisions regarding L’Oreal skincare products, identifying four key elements: brand awareness, perceived quality, brand association, and brand loyalty Data was collected through questionnaires distributed to 100 L’Oreal users using a probability sampling technique, and the relationship between independent and dependent variables was analyzed using correlation and regression methods via SPSS software The findings revealed a significant relationship between brand equity and purchase decisions However, the study faced limitations, including a small sample size and geographical constraints, suggesting that future research could explore additional variables influencing consumer purchasing behavior.

Figure 2.10: A model of consumer purchase decision, Naeem, Qurat-ul-ain,

This research examines the impact of smartphone brand factors—such as perceived quality, brand awareness, brand association, and brand loyalty—on consumer purchase decisions Data was collected through distributed questionnaires to analyze these relationships.

A study conducted on 171 smartphone users in Istanbul, Turkey, utilized convenience sampling to gather data The analysis was performed using the SPSS software, employing methods such as frequencies, cross-tabulations, correlations, and regression analyses The results indicated that brand loyalty and brand awareness significantly influence buying intentions, while other factors have a lesser impact on customer choices (Ulas & Javad, 2016).

Figure 2.11: A model of customer purchase decision, Ulas & Javad (2016)

The research conducted by Ren - Fang Chao and Ping - Chu Liao (2016) examines the influence of brand image and discounted prices on purchase intentions in outlet malls, utilizing consumer attitudes as a mediator The study collected data from 450 participants, both male and female, residing in Taiwan through random sampling Employing structural equation modeling (SEM) and Amos 22 for analysis, the findings reveal that both brand image and discounted prices significantly affect customers' buying decisions in outlet malls.

Figure 2.12: A model of purchase intention, Ren - Fang Chao & Ping - Chu

Cristina et al (2015) conducted a study examining the impact of customer-based store brand equity on mobile phone purchase intentions The research identified six key components of brand equity: store brand awareness, perceived quality, loyalty, price image, reputation, and commercial image Focusing on store brands in Spain, the study gathered insights from 362 consumers to analyze their purchasing decisions.

Research indicates that key elements of brand equity, including store brand awareness, loyalty, and perceived quality, have a significant impact on consumer intention.

Figure 2.13: A model of purchase intention, Cristina, Valentín-Alejandro,

The study titled "The Influence of Brand Equity on Consumer Behavior in Vietnam's Mobile Phone Market" examines the relationship between brand equity and consumer behavior within this sector It aims to understand how brand equity impacts purchasing decisions and preferences among consumers in Vietnam's mobile phone market.

A study conducted in Vietnam involved distributing questionnaires to 400 smartphone consumers through convenience sampling The results indicate that brand equity—encompassing brand awareness, brand association, perceived quality, and brand loyalty—significantly influences consumer purchase decisions (Nguyen Truong Son, 2008).

Figure 2.14: A model of consumer behavior, Nguyen Truong Son (2008)

Author Research topic Model Factors

The effect of brand equity on consumer purchase decision:

The case of cell phone in Ethiopia

Impact of brand equity on consumer’s purchase decision of smartphone - A study on university students in Chittagong, Bangladesh

Conceptual framework for customer purchase decision of smartphone

Impact of brand equity on consumer purchase intent

The effect of brand equity on purchase intention at market places in Malaysia

Analyze the effect of customer based brand equity on consumer’s purchase behavior: A case of branded

The impact of brand equity on customer purchase behavior

The influence of brand equity toward consumer purchase decision: A study case of Samsung smartphone in Bekasi

Impact of brand equity on consumer purchase decision of dairy products

The impact of brand equity on consumer purchase decision of cell phones

Impact of a brand equity on consumer purchase decision in L’Oreal skincare products

The impact of brands on consumer buying behavior: An empirical study on smartphone buyers

The influence of brand equity on customer purchase behavior

The impact of brand image and discounted price on purchase intention in outlet mall: Consumer attitude as mediator

The effect of brand image and discounted price on buying decision

Measuring the influence of customer

- based store brand equity in the purchase intention

Model of store brand equity impacting on buying intention

The influence of brand equity on consumer behavior on the Vietnam’s mobile phone market

The impact of brand equity on customer behavior

Table 2.2: Factors identified in the literature that impact of branding on customer purchase decision

Factors identified in prior studies Researchers

Research model and hypothesis

This study develops a theoretical model of brand equity that affects customer purchase decisions at Co.opmart, drawing on Aaker's (1991) framework and prior research by Ren-Fang Chao and Ping-Chu Liao (2016) The model identifies five key components: brand awareness, brand association, and brand loyalty, which collectively influence consumer behavior.

The perceived quality and price discount significantly impact customer purchase decisions, although these factors may vary from those identified in previous studies This understanding serves as the foundation for developing the hypotheses and research model presented in this study.

2.3.2.1 The relationship between brand awareness and purchase decision

Brand awareness encompasses both brand recognition and brand recall, where recognition is the ability to identify a brand among others, and recall is the ability to remember a brand when thinking of a product category (Keller, 1993) It includes various levels such as brand recognition, brand recall, top of mind awareness, brand dominance, brand knowledge, and brand opinion (Aaker, 1991) Essentially, brand awareness reflects how well consumers can identify and understand a brand (S Rungsrisawat et al., 2019) Furthermore, Grewal et al (1998) emphasize that brand awareness plays a crucial role in influencing consumer buying intentions, as certain brands can significantly impact purchasing decisions.

A study by Muhammad and Arshia (2019) investigated the effects of brand awareness and brand loyalty on customer purchasing decisions The results indicate that brand awareness significantly influences customer purchase decisions.

The study "Impact of Brand Equity on Consumer Purchase Decision of Dairy Products" by Maulik & Ashish (2017) investigates the relationship between brand equity and consumer purchasing decisions in Anand, known as the milk city It identifies four key factors of brand equity: brand awareness, perceived quality, brand association, and brand loyalty The findings reveal that brand awareness is the most significant factor influencing customer purchasing decisions in the dairy sector.

Numerous studies have demonstrated the significant influence of brand awareness on customer purchase decisions Research by Beyene & Feyisa (2021), Syed et al (2020), Rungsrisawat & Sirinapatpokin (2019), Rocky Simon Hia (2017), Muhammad & Sameen (2016), and Naeem et al highlights this correlation, emphasizing the importance of brand recognition in shaping consumer behavior.

Muniba (2016); Ulas & Javad (2016); Cristina, Valentín-Alejandro, Oscar & Jean- Pierre (2015); Nguyen Truong Son (2008) As a result of the previous discussion about brand awareness, the first hypothesis is formulated:

H1: There is a relationship between brand awareness and customer purchase decision at Co.opmart

2.3.2.2 The relationship between brand association and purchase decision

Brand associations are defined as the connections and memories linked to a brand (Aaker, 1991) These associations can enhance customer value by offering reasons for consumers to choose a brand and fostering positive feelings towards it They can be established through various elements such as attitudes, attributes, or benefits (Keller, 1993) Additionally, brand associations encompass the attributes that customers recall when discussing a brand (Syed et al., 2020).

S Rungsrisawat et al (2019) explore how brand equity affects customer purchase intent, focusing on key factors such as brand awareness, brand association, perceived quality, and brand loyalty The findings reveal a strong and positive correlation between brand association and customer purchase decisions, highlighting the importance of brand perception in influencing consumer behavior.

Numerous studies, including those by Beyene & Feyisa (2021) and Syed et al (2020), have demonstrated the significant influence of brand association on customer purchasing decisions Research conducted by Muhammad & Arshia (2019), Rocky Simon Hia (2017), and others further supports this finding, highlighting the importance of brand perception in consumer behavior The collective insights from these studies underscore the critical role that brand association plays in shaping customer choices.

(2008) Based on these contributions, the second hypothesis is formulated:

H2: There is a relationship between brand association and customer purchase decision at Co.opmart

2.3.2.3 The relationship between brand loyalty and purchase decision

Brand loyalty reflects the relationship between a customer and a brand, indicating the likelihood of a customer switching to a different brand when changes occur in price or product features This concept, as defined by Keller (2003) and Aaker (1991), highlights the importance of understanding customer attachment to brands in order to maintain their loyalty.

Brand loyalty is defined as a commitment to repurchase a preferred product or service, regardless of changing marketing strategies or external factors (1997) Assael (1998) emphasizes that positive past experiences with a brand drive customers to repurchase it Yoo et al (2000) highlight that brand loyalty influences customers' decisions to continue buying the same product and reduces the likelihood of switching to competitors.

(2008) found that the brand - loyal customers will simple buy products or services of a brand based on past experiences without any evaluation

Numerous studies, including those by Beyene & Feyisa (2021) and Syed et al (2020), have demonstrated the significant influence of brand loyalty on customer purchase decisions This body of research highlights the essential role that brand loyalty plays in shaping consumer behavior, leading to the formulation of the third hypothesis.

H3: There is a relationship between brand loyalty and customer purchase decision at Co.opmart

2.3.2.4 The relationship between perceived quality and purchase decision

Perceived value refers to how customers view the strengths of a product and their expectations of a particular brand (S Rungsrisawat et al., 2019) Additionally, perceived quality plays a crucial role in brand equity, reflecting a customer's assessment of a product's quality.

32 perception of the overall quality or superiority of a product or service (Aaker,

Perceived quality, as defined by Zeithaml (1988), is the overall impression customers have about a brand's products or services, rather than their actual quality Ulas & Javad (2016) emphasize that this perception stems from customers' experiences and interactions with a product Bhuian (1997) further supports this by describing perceived quality as the customer's assessment of a product's added value A positive perception of quality can significantly influence purchasing decisions, enhance brand differentiation, facilitate brand extension, and enable companies to set premium prices, ultimately linking perceived quality to corporate profitability (Aaker, 1991).

Numerous studies have demonstrated the significant influence of perceived quality on customer purchase decisions Research by Beyene & Feyisa (2021) and Syed et al (2020) highlights this relationship, alongside findings from Rungsrisawat & Sirinapatpokin (2019) and Rocky Simon Hia (2017) Additional insights from Maulik & Ashish (2017), Muhammad & Sameen (2016), and Naeem et al (2016) further reinforce the importance of perceived quality Ulas & Javad (2016) and Cristina et al (2015) also contribute to this body of evidence, underscoring the critical role that perceived quality plays in shaping consumer behavior, as noted by Nguyen Truong Son.

(2008) Based on these contributions, the fourth hypothesis is formulated:

H4: There is a relationship between perceived quality and customer purchase decision at Co.opmart

2.3.2.5 The relationship between pricing policy and purchase decision

Summary

Chapter 2 identified a variety of factors that can influence on customer purchase decision in Co.opmart It also provided the concept of brand equity, customer behavior, purchase decision and discussed the literature review of previous studies An overview of the research design, methods and analysis will be provided in the following chapter

3.1 Research design

Research process

The research process begins by identifying a research problem, also known as the problem statement This is followed by establishing a theoretical basis and reviewing relevant previous studies in the field Next, a research design is conceptualized to effectively address the identified problem Subsequently, a scale is developed and refined to align with the study's objectives, followed by the determination of sample groups Finally, data is collected and analyzed from these groups, leading to the reporting of findings A visual representation of this research process is provided below.

The survey questionnaire comprised two sections: personal information and a five-point Likert scale Personal information was gathered through closed-ended questions, while the factors influencing customer purchase decisions were assessed using the Likert scale, which ranged from 1 (strongly disagree) to 5 (strongly agree).

Focus group

This study employs a qualitative research method, utilizing in-depth interviews to identify the key factors that influence customer choices By interviewing a diverse group of participants across various age groups, the research aims to gather comprehensive insights and establish a theoretical foundation for scaling qualitative research.

The research employed this technique to create a survey questionnaire for quantitative analysis, ensuring it is theoretically grounded and relevant to the specific context of Co.opmart.

Based on the literature review, this research provides several questions in a focused group:

How long do you visit Co.opmart?

How much do you spend on products?

What kind of products do you buy at Co.opmart?

What are the factors that affect customer purchase decisions? (Brand awareness, brand association, brand loyalty, perceived quality, pricing policy)

Why do you buy products at Co.opmart?

What makes you choose products at Co.opmart?

Do you have any other comments?

A study involving 10 customers revealed that factors such as brand awareness, brand association, brand loyalty, perceived quality, and pricing policy significantly influence their purchasing decisions at Co.opmart Customers identified the brand as the primary determinant in their product choices, highlighting Co.opmart's status as a well-known and recognizable brand in the market.

Table 3.1: Statistics of participants in the focus group

Age The number of survey Note

Using questionnaires to test 40 consumers who bought products at Co.opmart in Ho Chi Minh city

Formal research

Quantitative methods were used in formal research to analyze and test hypotheses in the model This study uses a 5 point Likert - scale questionnaire instrument to collect information

According to Hair, Anderson, Tatham, and Black (1998), the minimum sample size for exploratory factor analysis should be five times the total number of observed variables, expressed as n=5*m Comrey (1973) and Roger (2006) support this guideline, indicating that a sample size of 130 customers is suitable for factor analysis research.

The survey questionnaire aims to gather information related to the study objectives and is divided into two main sections: personal information and a Likert scale The personal information section consists of closed-ended questions, while the factors influencing customer purchase decisions are assessed using a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree) The variables included in this study were selected based on a thorough literature review.

The first section of the survey form is a profile questionnaire It requests information on the participants' backgrounds such as gender, age, occupation,

The second section of the survey form is a survey questionnaire It is designed to determine the preference of the customers when it comes to the factors

39 that impact purchase decision It is made up of five elements that impact on customer purchase decision: brand awareness, brand association, brand loyalty, perceived quality and pricing policy

Quantitative research is an empirical approach that presents data in numerical form, as noted by Punch (2005) This method is designed to test pre-formulated assumptions, commonly expressed as hypotheses, according to Flick (2009).

Descriptive research involves meticulous observations and detailed documentation of a specific phenomenon (Bhattacherjee, 2012) Its primary aim is to outline the characteristics of that phenomenon In this study, a sample of 251 respondents who purchased products at Co.opmart in Ho Chi Minh City was analyzed The data collected from primary sources were processed using the Statistical Package for Social Science (SPSS) version 22.

Modified the scale of factors influencing customer purchase decision at

3.2.1 The scale of brand awareness

Brand awareness plays a crucial role in influencing customer purchase decisions, as it enables customers to recognize and differentiate a brand from its competitors According to Yoo et al (2000), this recognition is a key factor that impacts consumers' choices, making brand awareness an essential component in the purchasing process.

Table 3.2: Encode the brand awareness scale

BAW1 I am aware of Co.opmart’s brand Yoo et al (2000) BAW2 I know what Co.opmart’s brand looks like Yoo et al (2000)

When I think about consumer goods such as frozen food, canned food, drink etc

Co.opmart's brand is the brand that comes to my mind first

BAW4 I can recognize Co.opmart’s brand among other competing brands

BAW5 I am quite familiar with Co.opmart’s brand Gómez & Giraldo

3.2.2 The scale of brand association

Brand associations refer to the connections that consumers make in their memory related to a brand (Aaker, 1991) These associations can enhance customer value by providing compelling reasons to choose a brand and fostering positive feelings towards it They can be formed through various elements, including attitudes, attributes, or benefits (Keller, 1993) As noted by Syed et al (2020), brand associations are the attributes that come to mind when customers discuss a brand, making them a crucial factor influencing purchasing decisions.

Table 3.3: Encode the brand association scale

BAS1 Some characteristics of Co.opmart’s brand come to my quickly

BAS2 I can quickly recall the symbol or logo of

Co.opmart’s brand Yoo et al (2000)

BAS3 Co.opmart’s brand is different from its competing brands

BAS4 Co.opmart brand is interesting Beyene & Daniel

3.2.3 The scale of brand loyalty

Brand loyalty is defined as the connection between a customer and a brand, indicating the likelihood of a customer switching to another brand when changes occur in price or product features (Keller, 2003; Aaker, 1991) It significantly influences a customer's decision to repurchase the same brand and reduces the tendency to switch to competitors (Yoo et al., 2000) Moreover, research by Yee and Sidek (2008) shows that loyal customers often make purchases based on previous experiences without reevaluating their choices Thus, brand loyalty plays a crucial role in shaping customer purchasing decisions.

Table 3.4: Encode the brand loyalty scale

BL1 My first purchase option is Co.opmart brand Yoo et al (2000)

BL2 I am loyal to Co.opmart’s brand Beyene & Daniel

BL3 I recommended Co.opmart's brand to anyone who seeks my opinion

BL4 I will not buy other brands if Co.opmart stores are available Yoo et al (2000)

3.2.4 The scale of perceived quality

Perceived quality is a crucial component of brand equity, defined as the customer's assessment of a product or service's overall quality and superiority (Aaker, 1991) According to Ulas & Javad (2016), perceived quality encompasses customers' insights based on their visual and tactile experiences with a company's product Furthermore, a positive perception of quality can significantly impact purchasing decisions, aid in brand differentiation, support brand extension strategies, enable premium pricing, and is closely associated with corporate profitability (Aaker).

1991) Therefore, perceived quality is considered as a component that affects customer purchase decision

Table 3.5: Encode the perceived quality scale

PQ1 The products of Co.opmart's brand have a high quality Dodds et al (1991)

PQ2 The products of Co.opmart's brand are trustworthy Dodds et al (1991)

PQ3 I'm satisfied with the quality of

PQ4 Co.opmart’s brand lives up to its promises with customers Lehman et al (2008)

3.2.5 The scale of pricing policy

Price significantly influences brand equity, as highlighted by Aaker (1991) Sato K notes that pricing is a multifaceted concept that varies by company, necessitating tailored pricing strategies in competitive markets In small businesses, owners typically set prices, while larger firms often rely on high-level managers to establish pricing based on specific objectives Thus, pricing policy reflects the unique philosophy of each business (Ivana Hustić & Iva Gregurec, 2015) and plays a crucial role in shaping customer purchasing decisions.

Table 3.6: Encode the pricing policy scale

PP1 Pricing policies of Co.opmart are always in line with customer preference Njeru, I M (2017)

In comparison with the competitors’ pricing policies, pricing policies of Co.opmart are better

PP3 When shopping at Co.opmart, good price policy encourages me to buy more products Njeru, I M (2017)

PP4 Co.opmart frequently offer good pricing policies Njeru, I M (2017)

3.2.6 The scale of customer purchase decision

Consumer purchase decision - making may be an unpredictable process and buyer can rely on the data on a specific items as well as their own experience to make a buying decision

Table 3.7: Encode the purchase decision scale

Even if another brand has the same features as this brand, I would prefer to buy products of Co.opmart

If another brand is not different form this brand in any way, it seems smarter to purchase products at Co.opmart

PD3 I depend on the brand to make my purchase decision

PD4 I feel satisfied when purchasing

PD5 I will continue paying for products of

Statistical analysis

3.3.1 Test validity by Cronbach’s Alpha

Reliability, as defined by Cooper & Schindler (2006), emphasizes the accuracy and precision of testing methods and design in assessing stability, equivalence, and internal consistency coefficients These reliability coefficients are quantified numerically using correlation formulas.

Internal reliability was assessed using Cronbach's Alpha, which measures the internal consistency and average correlation among survey items to evaluate reliability The Alpha value ranges from 0, indicating no internal consistency, to 1.0, indicating complete internal consistency According to Nunnally & Burnstein (1994), variables with a correlation coefficient below 0.3 should be removed, while a Cronbach's Alpha above 0.6 is considered acceptable, with higher values indicating better reliability A Cronbach's Alpha coefficient of 0.70 or higher is regarded as indicative of good internal consistency.

46 dependable measurements for further analysis (Hair et al., 1998; Gliem & Gliem,

This study evaluates the scale based on specific criteria, eliminating observation variables with a total correlation of less than 0.3, as they contribute minimally to the concept being measured Additionally, a Cronbach's Alpha reliability threshold of greater than 0.6 will be applied to ensure the scale's robustness in this research.

Exploratory factor analysis (EFA) is crucial for assessing convergent and discriminant validity in research As an interdependence technique, EFA focuses on the relationships among variables without designating dependent or independent variables The principal components analysis combined with varimax rotation is the most commonly employed approach in factor analysis (Mayers et al., 2000).

According to Hair et al (1998), factor loading is the criterion to ensure the practical significance of EFA:

The conditions for analyzing exploratory factors must satisfy the following requirements:

- 0.5 ≤ KMO ≤ 1: The KMO coefficient is an index used to assess the suitability of factor analysis For factor analysis, a high KMO value is appropriate

- Bartlett's test - determine whether the variables have an overall connection

If this test is statistically significant (Sig < 0.05), the observed variables are correlated with each other in the population

- Percentage of variance > 50% - represents the percentage variation of the observed variables In other words, considering the 100% variation, this result indicates how much percentage the factor analysis explains

3.3.3 Regression analysis and hypothesis testing

In SPSS, regression analysis is utilized to assess a research model following comprehensive studies on Cronbach's Alpha, Exploratory Factor Analysis (EFA), and correlations to identify suitable independent variables This process quantifies the impact of each independent variable on the dependent factor, ultimately producing a regression equation that reflects their relationships.

In this study, the dependent variable is purchase decision, while the independent variables are brand awareness brand association, brand loyalty, perceived quality and pricing policy.

Summary

Chapter 3 describes the research methodology used in the study This chapter discusses procedures and activities under taken, focusing on namely the research design, data collection, sample size and data analysis In this study, the quantitative method was used to determine the elements of brand equity that affect customer purchase decisions at Co.opmart The next chapter will report on the survey results

4.1 Sample descriptions

Retail brands are chosen during the Covid - 19 pandemic

Table 4.1: Respondents who choosing retail brands

Source: Result of data processing

The researcher discovered 499 retail brands were chosen among 251 respondents after doing research and collecting a total of 251 responses, implying

According to the survey results, Co.opmart is the most preferred retail brand, receiving 178 responses, which accounts for 35.7% of the total Following Co.opmart, BigC garnered 79 responses (15.8%) and Vinmart received 75 responses (15%) Other brands such as AEON, LotteMart, and Emart attracted 37 (7.4%), 38 (7.6%), and 22 responses (4.4%) respectively Additionally, respondents also selected Satramart, METRO, and other brands, contributing to the overall diversity of retail preferences.

The way of shopping during the Covid - 19 pandemic

Table 4.2: The way of shopping

Table 4.2 reveals that 51.4% of respondents engaged in online shopping during the Covid-19 pandemic, while 29.1% preferred offline shopping The remaining respondents utilized a combination of both online and offline shopping methods.

Gender

Table 4.3: Distribution of respondents by gender

Frequency Percent Valid Percent Cumulative

Table 4.3 reveals that out of 251 respondents, 179 are female, representing 71.3%, while 69 are male, accounting for 27.5% Additionally, there are 3 respondents from another gender group, making up 1.2% This data aligns with the observation that female shoppers typically outnumber male shoppers.

Age

Table 4.4: Distribution of respondents by age

Table 4.4 reveals that the majority of respondents, 149 individuals or 59.4%, fall within the 18 to 24 age group The next largest group comprises 48 respondents aged 25 to 34, representing 19.1% Additionally, there are 24 respondents, or 9.6%, in the 35 to 44 age range Among those aged 45 to 55, there are 13 respondents, accounting for 5.2%, while the group of respondents over 55 years old includes 17 individuals, making up 6.8% of the total.

Occupation

Table 4.5: Distribution of respondents by occupation

Frequency Percent Valid Percent Cumulative

Based on the table 4.5, the majority in this research are students, which dominated by 51.4% or 129 respondents, 39.8% of employees with the number of

100 and 22 respondents or 8.8% are unemployed.

Frequency visiting Co.opmart

Table 4.6: Frequency visiting Co.opmart

4 - 5 times a month 30 12.0 12.0 94.0 more than 5 times a month 15 6.0 6.0 100.0

According to Table 4.6, a significant portion of respondents, 44.2%, visit Co.opmart once a month, while 37.8% shop there 2 to 3 times monthly Additionally, 12% of individuals report visiting Co.opmart 4 to 5 times each month.

In addition, 6% is the percentage of respondents who visit Co.opmart more than 5 times a month.

Spending at Co.opmart

Table 4.7: Distribution of respondents by spending at Co.opmart

In a study involving 251 respondents, spending patterns at Co.opmart revealed that 35.9% (90 respondents) spent under 500,000 VND, while 23.9% (60 respondents) spent between 500,000 VND and 1,000,000 VND The largest group, accounting for 37.8%, spent between 1,000,000 VND and 2,000,000 VND on products at Co.opmart Additionally, a small number of respondents, specifically 4 individuals, reported spending above this range.

2.000.000 VND to 3.000.000 VND and 2 respondents who spent more than 3.000.000 VND on products at Co.opmart, with 1.6% and 0.8% respectively.

Product purchase

Table 4.8: Distribution of respondents by product purchase

After analyzing 251 responses, the researcher found that a total of 492 products were purchased, indicating that some respondents bought multiple items According to Table 4.8, consumer goods were the most popular choice, with 242 respondents (49.2%) selecting them Following this, 79 respondents (16.1%) purchased cosmetics, while 148 respondents (30.1%) opted for household products, and 23 respondents (4.7%) bought garments.

Cronbach’s Alpha

Table 4.9: Result of the reliability assessment of brand awareness

Scale Variance if Item Deleted

Cronbach's Alpha if Item Deleted

The Cronbach's Alpha analysis revealed a high reliability coefficient of 0.897 for brand awareness, with all observation variable correlation coefficients exceeding 0.3 Furthermore, none of the observation variables could be eliminated to improve the scale's reliability, confirming that all observed variables will be retained for subsequent factor analysis.

Table 4.10: Result of the reliability assessment of brand association

The reliability analysis of brand awareness yielded a Cronbach's Alpha coefficient of 0.871, indicating strong reliability All correlation coefficients of the observed variables exceeded 0.3, and no variables were identified for elimination that could enhance the scale's reliability beyond 0.871 Consequently, all observed variables are deemed acceptable for inclusion in the subsequent factor analysis.

Table 4.11: Result of the reliability assessment of brand loyalty

The reliability analysis using Cronbach's Alpha revealed a coefficient of 0.870 for brand awareness, with all observation variable correlation coefficients exceeding 0.3 Notably, removing the variable BL4 increased the reliability coefficient to 0.886 Consequently, the researcher decided to eliminate BL4 and re-conduct the Cronbach's Alpha test.

Table 4.12: Result of the reliability assessment of brand loyalty after removing BL4

The Cronbach's Alpha result shows a strong reliability coefficient of 0.886 for brand awareness, with all correlation coefficients of the observed variables exceeding 0.3 Additionally, no observed variables were found that could improve the scale's reliability beyond 0.886, leading to the acceptance of all observed variables for subsequent factor analysis.

Table 4.13: Result of the reliability assessment of perceived quality

The reliability analysis using Cronbach's Alpha revealed a high coefficient of 0.944 for brand awareness All correlation coefficients for the observed variables exceeded 0.3, and no variables were identified for elimination that would enhance the scale's reliability beyond 0.944 Consequently, all observed variables were accepted for subsequent factor analysis.

Table 4.14: Result of the reliability assessment of pricing policy

The reliability coefficient for brand awareness, as measured by Cronbach's Alpha, is 0.889, indicating strong reliability All correlation coefficients of the observed variables exceed 0.3, and no variables were identified for removal that would enhance the scale's reliability beyond 0.889 Consequently, all observed variables are deemed acceptable for inclusion in subsequent factor analysis.

Table 4.15: Result of the reliability assessment of purchase decision Cronbach’s Alpha: 0.885

The reliability analysis using Cronbach's Alpha revealed a coefficient of 0.885 for brand awareness, indicating strong reliability All correlation coefficients for the observed variables exceeded 0.3, and no observation variable was identified for elimination that would improve the scale's reliability beyond 0.885 Consequently, all observed variables are deemed acceptable and will be utilized in the subsequent factor analysis.

Table 4.16: Synthesize Cronbach’s Alpha of each variable

In summary, Table 4.16 reveals that the Cronbach’s Alpha results for six factors (n = 25) demonstrate a reliability coefficient exceeding 0.6 for all observed variables Additionally, the correlation coefficients among the total variables are greater than 0.3, confirming the acceptance of all observed variables for subsequent factor analysis.

Result of exploratory factor analysis (EFA)

4.3.1 Factor analysis for independent variable

According to the result of scale reliability assessment above, the researcher performed a factor analysis of 20 observation variables of independent variables influencing customer purchase decision at Co.opmart

Table 4.17: The result of KMO and Bartlett's Test for independent variables

KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy .913

Table 4.17 indicates a KMO coefficient of 0.913, which falls within the acceptable range of 0.5 to 1 Furthermore, Bartlett's test yields a result of 3813.753 with a significance level of 0.000, which is below the 0.05 threshold These findings confirm that the data is suitable for factor analysis.

Table 4.18: Eigenvalues and covariance deviations for independent variables

The table 4.18 shows that at a value of Eigenvalue  1 with factor extraction method, varimax rotation allows extracting 5 factors from the observation variable Total value of deviation is 77.864% > 50%: satisfactory

Table 4.19: Result of independent factor analysis with principal varimax rotation method

According to the analysis result, 20 variables have a loading factor coefficient greater than 0.5, which is satisfactory As a result, no variables are removed from the scale

In conclusion, there are 20 observed variables are accepted and will be used in the next factor analysis

4.3.2 Factor analysis for dependent variables

Table 4.20: The result of KMO and Bartlett’s Test for dependent variable

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .831 Bartlett's Test of Sphericity

Table 4.20 indicates a KMO coefficient of 0.831, which falls within the acceptable range of 0.5 to 1 Furthermore, Bartlett's test yields a result of 669.036 with a significance level of 0.000, well below the 0.05 threshold Therefore, the data is deemed suitable for factor analysis.

Table 4.21: Eigenvalue and covariance deviations for dependent variables

The table 4.21 shows that the Eigenvalue coefficient of the factor is 3.431 (greater than 1) In addition, total value of deviation is 68.619% > 50%: satisfactory

Table 4.22: The factor rotation matrix of the dependent variable

Table 4.22 indicates that following the varimax factor rotation, five observed variables have successfully formed a single convergent group, with all convergence values exceeding the minimum threshold of 0.5.

Correlation analysis

BAW BAS BL PQ PP PD

** Correlation is significant at the 0.01 level (2-tailed)

The significance level of the dependent variable, purchase decision, in relation to the independent variables is 0.000, which is below the 0.05 threshold This finding demonstrates a strong correlation between the dependent and independent variables, justifying their inclusion in the model to effectively explain the purchase decision.

The Pearson correlation analysis shows that some independent variables correlate with each other, so regression analysis needs to focus on the multicollinearity problem.

Test of regression analysis

Factors extracted from factor analysis will be used for regression analysis to validate the research model and associated hypotheses The validations of the statistical hypothesis apply a significance level of 5%

Table 4.24: Model summary Model Summary

Std Error of the Estimate

1 775 a 601 593 46770 a Predictors: (Constant), PP, BL, BAS, BAW, PQ

According to the result of the analysis (Table 4.24), the value of the adjusted

The R-squared value of 0.593 indicates that the five independent variables included in the model account for 59.3% of the variation in the dependent variable, while the remaining 40.7% is attributed to external factors Additionally, the adjusted R-squared exceeding 50% suggests significant management implications from this study.

Squares df Mean Square F Sig

Total 134.222 250 a Dependent Variable: PD b Predictors: (Constant), PP, BL, BAS, BAW, PQ

In Anova analysis (Table 4.25), the significance level is 0.000 (less than 0.05), F = 73.724 Thus, the linear regression model was constructed in accordance with the whole

Table 4.26: Result of dependent variables’ linear regression

The analysis in Table 4.26 shows that multicollinearity is absent, as the Variance Inflation Factor (VIF) for each variable is below 3 (Knock and Lynn, 2012) The regression coefficient for the variable BL exceeds 0.05, leading to its exclusion from the model In contrast, the independent variables BAW, BAS, PQ, and PP have significance levels below 0.05, indicating their meaningful contribution to explaining the dependent variable.

H1: There is a relationship between brand awareness and customer purchase decision at Co.opmart

The analysis reveals that BAW has a coefficient of 0.110, with a t-value of 1.981 and a significance level of 0.049, indicating that it is statistically significant at the 11% level This suggests that any changes in BAW will directly influence the purchase decision (PD) by 11%, highlighting BAW as a crucial factor affecting customer decisions at Co.opmart Consequently, the hypothesis H1, which posits a relationship between brand awareness and customer purchase decisions at Co.opmart, is accepted.

H2: There is a relationship between brand association and customer purchase decision at Co.opmart

The variable BAS is statistically significant at 9.7%, with a t-value of 2.083 and a significance level of 0.038 This indicates that, when other factors are held constant, changes in BAS will affect the purchase decision (PD) by 9.7% Consequently, BAS is identified as a sensitive factor that directly influences customer purchase decisions at Co.opmart Thus, the hypothesis H2, which posits a relationship between brand association and customer purchase decisions at Co.opmart, is accepted.

H3: There is a relationship between brand loyalty and customer purchase decision at Co.opmart

The analysis revealed a BL value of 0.077 with a t-value of 1.942 and a significance level of 0.053, indicating that the BL variable is not statistically significant and should be excluded from the "Brand Loyalty" variable Factors such as the preference for Co.opmart as a first purchase option, loyalty to the Co.opmart brand, and recommending Co.opmart to others do not significantly influence customers' purchasing decisions Consequently, the hypothesis H3, which posits a relationship between brand loyalty and customer purchase decisions at Co.opmart, is rejected.

H4: There is a relationship between perceived quality and customer purchase decision at Co.opmart

PQ = 0.411 (t = 7.274, significance level = 0.000) Therefore, the variable

PQ is statistically significant at 41.1% In other words, when other factors remain unchanged, an impact on the factor PQ will change the PD by 41.1% Thus, the

The factor PQ significantly influences customer purchasing decisions at Co.opmart, leading to the acceptance of the hypothesis H4: a relationship exists between perceived quality and customer purchase decisions at Co.opmart.

H5: There is a relationship between pricing policy and customer purchase decision at Co.opmart

The variable PP shows a statistically significant impact of 21.1% on customer purchase decisions at Co.opmart, with a t-value of 3.892 and a significance level of 0.000 This indicates that changes in the pricing policy (PP) directly influence customer decisions, confirming the hypothesis H5 that a relationship exists between pricing policy and customer purchase decisions at Co.opmart.

PD = 0.110 * BAW + 0.097 * BAS + 0.411 * PQ + 0.211 * PP

The analysis reveals that perceived quality holds the highest beta coefficient among all independent variables, indicating its significant impact on customer purchase decisions at Co.opmart Following perceived quality, pricing policy, brand awareness, and brand association also play important roles in influencing consumer choices.

Purchase decision based on demographic profile

The comparative test for purchasing decisions assesses the differences among the specified object groups, with meaningful distinctions identified only when the significance level is below 0.05.

4.6.1 Purchase decision based on gender

Table 4.27: One-way test of purchase decision based on gender

Table 4.27 indicates that the Levene test result of 0.308, which is greater than 0.05, confirms that there is no variance difference, making the data suitable for ANOVA analysis The ANOVA analysis reveals a significant level of 0.000, which is less than 0.05, indicating a statistically significant difference in purchase decisions across different genders.

4.6.2 Purchase decision based on age

Table 4.28: One-way test of purchase decision based on age

Table 4.28 indicates that the Levene test yielded a significance level of 0.778, exceeding the threshold of 0.05, suggesting no variance differences, thus validating the use of ANOVA analysis Furthermore, the ANOVA analysis revealed a significance level of 0.545, also greater than 0.05, indicating that there are no statistically significant differences in purchase decisions across various age groups.

4.6.3 Purchase decision based on occupation

Table 4.29: One-way test of purchase decision based on occupation

Table 4.29 indicates that the Levene test results in a significance level of 0.375, which is greater than 0.05, confirming that the variances are equal and suitable for ANOVA analysis Additionally, the ANOVA analysis yields a significance level of 0.898, also exceeding 0.05, suggesting that there are no statistically significant differences in purchase decisions across various occupations.

4.6.4 Purchase decision based on frequency visiting Co.opmart

Table 4.30: One-way test of purchase decision based on frequency visiting

N Mean Std Deviation once a month 111 3.4829 75725

4 - 5 times a month 30 3.8733 64857 more than 5 times a month 15 4.0133 81229

Table 4.30 indicates that the Levene test yields a significance level of 0.511, which is greater than 0.05, confirming that there is no variance difference and thus qualifies for ANOVA analysis Furthermore, the ANOVA results show a significance level of 0.002, which is less than 0.05, indicating a statistically significant difference in purchase decisions across various frequency groups.

4.6.5 Purchase decision based on spending

Table 4.31: One-way test of purchase decision based on spending

Table 4.31 indicates that the Levene test's significance level of 0.098 exceeds 0.05, confirming no variance differences and validating the use of ANOVA analysis The ANOVA results show a significance level of 0.007, which is below 0.05, indicating a statistically significant difference in purchase decisions across various spending groups.

Summary

Chapter 4 analyzes the descriptive statistics of the sample, evaluated the reliability of the scale by using Cronbach’s alpha, EFA, and regression analysis Based on the result obtained after processing and analyzing data in this chapter, the following chapter will present the conclusion of the study, the implications of these findings and identify limitations as well as propose direction for further research

5.1 Conclusion

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