About Papa’s Food
Papa’s Food is a small private restaurant founded in 2019 with the goal to deliver a delicious and nutritious lunch, which is beneficial to health, for busy people, particularly office workers Because the target customers are office workers and students with little time to rest, the operating time is 8am - 2pm, especially 12pm (Papa’s Food, 2019).
Justification for the chosen topic
RomeA Shopping Mall is one of Ho Chi Minh City’s largest shopping centers, with a large number of rich and diverse facilities Especially eye-catching is the first-class food court with more than 10 top-class restaurants, each with its own personality to suit guests’ tastes Usually, Papa’s Food restaurant is his one of the most famous brands here, but it’s fairly new and faces stiff competition from big name brands in the same space, such as SanFuLou, My Tho Noodle Soup, etc
According Duong (2021), there are over 540,000 dining options in Vietnam The number of stores is approximately 278,424 for the micro model, 34,128 for the medium model, 153,576 for the small model, and 73,872 for the large model Of course, these numbers will continue to grow as the mining potential is still huge
Due to the feasibility and urgency of the above issues, the author chose the topic “ Factors affecting the decision to choose Papa’s Food restaurant for diners at RomeA shopping mall food court, District 3, Ho Chi Minh City”
Object of the topic
An investigation of the factors that can influence patrons’ choice to choose the Papa’s Food restaurant in the RomeA Shopping Center Food Hall, District 3, Ho Chi Minh City, Vietnam
Identifying the factors that impact customers’ decisions to eat at Papa’s Food eatery in the food court of RomeA Shopping Center
Measuring the influence of elements that affect the choice to select the Ho Chi Minh City, Vietnam, food market and eatery Papa’s Food District 3
Based on the study findings, the author will make recommendations to assist Papa’s Food restaurant draw in more customers when they visit RomeA shopping mall in District 3, Ho Chi Minh City.
Research Questions
What factors affect customers’ choice of Papa’s Food restaurant in the food court at RomeA Shopping Center, District 3, Ho Chi Minh City?
The degree of influence of factors affecting customers’ choice of Papa’s Food restaurant at RomeA shopping mall food court, District 3, Ho Chi Minh City?
Recommendations based on an analysis of the factors affecting customers’ decision to choose Papa’s Food restaurant at the RomeA shopping mall food court, District 3, Ho Chi Minh City.
The study's objective and scope
Research object: Factors affecting the decision to choose Papa’s Food restaurant of diners at RomeA shopping mall food court, District 3, Ho Chi Minh City
Survey object: Customers who have used the food service at Papa’s Food restaurant of diners at RomeA shopping center food court, District 3, Ho Chi Minh City
Scope of research space: Food court of RomeA Shopping Center, District 3, City
Primary data collection period: from November 2021 to January 2022
Secondary data collection period: from July 2021 to March 2022
Research Methods
To accomplish the stated research objectives, the dissertation will utilize a combination of the following research methods:
Building model research and preliminary scales based on theory and the findings of a number of prior studies, including studies in Vietnam and other nations Conduct in-depth interviews with customers who have used and routinely use food service at RomeA Shopping Center, District 3, Ho Chi Minh City, based on the preliminary model and scale Concurrently, Ho Chi Minh City talks with food and beverage industry experts and experienced individuals to modify and perfect the study model and scale
After building the draft scale and complete questionnaire, the author uses the draft scale to conduct a preliminary quantitative survey of 40-50 votes From the obtained results, complete the draft scale and give the official scale
Utilizing data obtained from a survey distributed to customers who used food services at RomeA Shopping Center in District 3, Ho Chi Minh City Surveys can be conducted via live stream or through the Internet Data will be processed with the support of SPSS software version 20.0 The scale will be applied following the EFA preliminary factor analysis, correlation analysis, and Cronbach’s Alpha reliable numerical system method evaluation to test the model and research hypotheses
Requirements in quantitative research: (1) Preliminary quantitative survey 40-50 votes; (2) Analysis of sample characteristics; (3) Reliability testing; (4) EFA analysis; (5) Pearson correlation analysis; (5) Regression analysis; (6) Testing the research hypothesis; (7) Test the differences in individual characteristics of respondents; (8) Analysis of mean (means)
Summary
In Chapter 1, the author presents the selected organization for the research, justifies the research topic, and concurrently proposes all three aspects of the study, including the area of investigation, research subjects, and research questions The impact of organization on job satisfaction will be discussed in detail in the chapter that follows, along with a review of the relevant literature and studies.
LITERATURE REVIEW
The basic concept
2.1.1: Shopping mall and food court
A shopping mall is a contemporary, multifaceted commercial business structure that includes a range of commercial and service facilities, including halls, meeting spaces, and rental offices (Lawnet, 2019) Concentrated in one or more nearby building factories, while adhering to industry standards for business divisions, technical equipment, and management levels, as well as organizational structure Shopping malls are typically constructed on large lots in city centers to guarantee customer convenience and profitability Additionally, compared to supermarkets, shopping centers are much bigger
A food court is a large dining area that sells various kinds of food and is typically found in a mall, supermarket, or small restaurant Food courts have been around for years in the worldwide market However, since it has only been available in Vietnam for five years, it has become a popular new venture for many consumers
2.1.2: Restaurants and restaurants in the food court of the shopping mall
A restaurant may engage in the business of providing dietary advantages and other complimentary services in order to turn a profit According to the trade justification and the target showcase area that the trade uses to develop business goals and serve the target gathering of people, the restaurant serves many different types of customers, and the target audience is very diverse and affluent
Particularly for restaurants within the shopping mall’s nourishment court, it can be customers who come to shop at the shopping mall, customers who are office workers working in the building, or residents living in the building The restaurant that is a part of the shopping center’s culinary collection can be a part of the shopping center or it can also be an independent business unit because the target audience is quite diverse
Consumer behavior is used as a dynamic interplay of factors influencing perception, behavior, and environment through which individuals navigate their lives (Bennet, 1988; Kardes et al, 2014) Cbehavior the actions consumers undertake while seeking, using, evaluating, and disposing of products or services they believe will fulfill their needs (Schiffman 1994 cited in Szmigin and Piacentini, 2019)
Businesses can gain a better understanding of what customers buy, why they buy it, and when they should buy it by analyzing and forecasting consumer purchasing behavior Investigating the variables that influence consumer behavior helps you learn how to use, where to buy, how frequently to buy, how to buy, and how to dispose of products (Miller, 1975; Stávková et al, 2008)
Kotler & Keller (2006) argues that the complexity of consumer behavior studies is due to the large number of variables that are frequently interacted with The buyer learns about marketing and outside influences
Specific purchasing decisions are influenced by the buyer’s characteristics and decision-making processes Although there is no single model that can account for all aspects of consumer behavior, the majority of studies on the subject indicate that both external and internal factors have an impact on it (Islamoglu, 1999).
Related studies
2.2.1: Foreign study cases a) Research model of Yong Azrina Ali Akbar and Muharratul Sharifah Shaik Alaudeen (2012)
According to the 2012 research “Determining factors affecting consumers in choosing a full-service restaurant: A case at Seri Iskandar, Perak” by Yong Azrina Ali Akbar and Muharratul Sharifah Shaik Alaudeen According to the author’s study, six factors impact consumer decision-making: reliability factor, food quality, service quality, location, price, and surroundings Which lists reliability, service quality, expense, the environment, and location as the consumer’s top concerns, with meal quality coming in second Customers from different countries have varying requirements due to four factors Indians, for example, are very concerned with product quality, Chinese, on the other hand, are very concerned with location and the climate, and Malaysians are very concerned with dependability (Akbar and Alaudeen, 2012) b) Research model of Mohammad Badruzzaman Bhuiyan, Shahin Kadir Bhuiyan and Jannatul Mawa (2019)
According to the research “Factors affecting customer choice and restaurant preferences: A study in Dhaka city, Bangladesh.” The authors identify six variables that influence customers’ purchasing decisions: brand image, price-quality relationship, environment, service, entertainment facilities, behavior and service attitude The findings indicate that consumers are always interested in high-quality goods and services (Bhuiyan et al., 2019) But in reality, the majority of eatery managers only pay attention to the standard of the food and drink they serve, ignoring the proper price point Additionally, customers are very interested in the staff’s attitude and customer-oriented mindset, which affects how they feel when they dine here (Bhuiyan et al., 2019) c) Research by Wahida Shahan Tinne (2012)
According to Wahida Shahan Tinne, there are six groups of factors that influence the decision to dine at a high-end restaurant, including the “promotional” factors, which include opulent interior and exterior architecture, additional services, and media advertising Cleanliness, savory cuisine, and qualified staff fall under the group of “internal restaurant” components The “situational” factors include things like food quality, parking, and protection in the dining area The expense and accessibility of local cuisine are included in the “price” component group Among the set of “image” variables are the restaurant’s name and its address in the center of the city The final group of factors is “luxury,” which includes the specialties of the dishes and serving items in an upscale restaurant (Tinne, 2012)
According to Wahida Shahan Tinne’s study, the following factors influence the people of
Dhaka’s choice of high-class restaurant:
Diverse Food Luxury interior design Bonus services
-The speciality of the dish
-Restaurant’s location from the center
Figure 1: Factors affecting the choice of high-class restaurants of Dhaka people (Tinne, 2012) 2.2.2: Related research by domestic author a) Research was done by Truong Thi Xuan Dao on “Factors influencing the decision to choose a restaurant for a wedding reception in Ho Chi Minh City.” (2016)
Figure 2 Research model of Trương Thị Xuân Đào (2016) The author of the study asserts that the following seven elements have an impact on consumers’ decisions when selecting a wedding venue in Ho Chi Minh City: (1) food quality, (2) service quality, (3) restaurant atmosphere, (4) location, (5) price, (6) the reference group, and
The decision to choose is positively impacted by the quality of the food, the quality of the service, the atmosphere of the restaurant, the location, the price, the reference group, and positive feelings Select a venue for your bridal celebration Furthermore, the quality of the cuisine, the quality of the service, the ambiance of the restaurant, as well as positive emotions, all have a direct influence on the decision to choose a bridal restaurant Choosing a restaurant for a wedding is influenced both directly and indirectly by the three factors of cuisine quality, service quality, and restaurant atmosphere (Dao, 2016) b) According to Tran Thi Thai’s “Research on Factors Affecting Consumers’ Decision to
Choose Fast Food Restaurants in Da Nang City,” (2016)
According to research, consumers in Da Nang city must consider the following five criteria when choosing a fast food establishment: price, brand, attitude and service style, and product quality Which identifies four elements—convenience, brand, service attitude and style, and product quality—as having a positive impact on the decision to choose a fast food establishment Furthermore, choosing a restaurant is negatively impacted by the price element (Thai, 2016) c) “Factors Affecting Consumers’ Decision to Choose Fast Food Restaurants in Ho Chi Minh
City,” by Tran Tien Lam (2014)
The importance of the following factors influencing the desire to select a fast-food restaurant is listed in descending order: restaurant space, quality of service, cost, quality of the product, and marketing The price issue in particular has a detrimental impact on customers’ intents to choose a fast-food business
Figure 3 Research model of Tran Tien Lam (2014)
Yong Azrina Ali Akbar và Muharratul Sharifa
Table 1: Summary of factors in a review of some studies
Proposed research model
Each research is distinct, as are the variables used, and no two studies yield the same results The residential market at RomeA Shopping Center, District 3, Ho Chi Minh City varies from the markets in Bangkok and Dhaka, as does the intended audience, according to the studies of Dao (2016) and Thai (2016) Therefore, when performing this study, the author does not prototype any pre-existing research findings but rather modifies and chooses inherited variables for the best fit
Decisions to choose the restaurant
Figure 4: Author’s conceptual framework a “Product quality” factor
Customers’ decisions to choose a restaurant are influenced by elements that are associated with product quality In general, patrons will value a restaurant with high-quality meals This makes customers a “regular” Lewis (1981) According to Sulek & Hensley (2004), the most important factor influencing customer dining experiences is food quality Taste, freshness, temperature, presentation, and variety are all aspects of food quality (Liu & Jang, 2009) Furthermore, food must be safe, appealing, and diet-friendly Richness and variety in dishes are required Dishes that are regularly updated improve the customer experience Providing customers with the opportunity to try new dishes and diversify their menu options (Sulek & Hensley, 2004)
H1: “Product quality” has a positive (+) influence on customers’ restaurant choice b “Service quality” factor
Customers’ decisions to choose a restaurant are influenced by the service quality factor Currently, the culinary market is becoming increasingly competitive; in addition to quality and price, customers are interested in service quality (Alonso et al, 2013) The clothes and appearance of the staff, their friendliness and ability to handle customer requests, their knowledge of the products, and the speed with which they respond to customer requests all reflect the quality of customer service The service quality factor also influences customer loyalty, as well as the frequency with which customers visit the restaurant (Pugazhenthi, 2011)
H2: “Service quality” has a positive (+) influence on customers’ decision to choose a restaurant c “Suitable price” factor
Each restaurant must target its target customer in order to be successful; depending on the customer, there will be an appropriate price, and the price requirements will also vary In addition, the pricing strategy also requires the restaurant to have many different prices, to diversify the number of customers and to match the price of ingredients and produce a different dish Customers are more likely to rate the dining experience negatively if they believe the value they receive is less than the price paid (Mill, 2007)
H3: “Suitable price” has a positive (+) influence on customers’ decision to choose a restaurant d “Promotion” factor
Marketing influences customers’ restaurant selection decisions When customers need to find a restaurant that sells food, they will look for information such as “can they see if the restaurant has promotions or discounts?” (Lam, 2014) Restaurants that have attractive promotions or sales on a regular basis will attract more customers than other restaurants Customers are “affected by advertising information in the media,” according to Lam (2014), in addition to information from relatives, which helps the restaurant “stimulate purchasing ability.”
H4: Marketing factors have a positive (+) influence on customers’ decision to choose a restaurant e “Additional service” factor
A customer’s restaurant selection decision is influenced by complementary services Two restaurants serve similar food and service, but one may be chosen because of a lower price or other secondary
Customers prefer restaurants that offer home delivery services Because, in addition to going directly to the restaurant, customers may want to buy at the restaurant but have it delivered to a location that is convenient for them Because it emphasizes convenience and flexibility, the additional service will make a difference in the restaurant’s offerings Furthermore, flexible payment methods such as cash, wire transfer, credit card, QR code, or payment support applications will enable customers to form their payments in advance Reservations and pre-ordering activities must also be prioritized so that the restaurant can attract customers and arrange seats proactively, especially during peak service hours Customers can take the initiative and feel secure because they have reserved a table ahead of time Furthermore, forms of ordering food through online applications, delivery apps, or on the restaurant’s website, official Facebook page help customers be satisfied when making their decisions
H5: “Additional service” factors have a positive (+) influence on restaurant selection a “Location” factor
Customers’ decisions to choose a restaurant are influenced by the location aspect The location of a restaurant is critical to the retail business and drawing customers A good location is critical to the success of the hotel and restaurant industry (Tzeng et al., 2002) Customers in some sorts of restaurant businesses like eateries close to where they live and work since it is convenient and convenient Restaurants near the city center, easy to find, or with convenient traffic and large traffic typically have a significant competitive edge Furthermore, a good location raises the value of the product when it is sold to clients (Bull, 1994)
H6: “Location” factor has a positive (+) influence on customers’ decision to choose a restaurant b “Reference group” factor
The reference group includes relatives, friends, personal experience, restaurant preference or popularity, and other factors that influence the customer’s selection (Dao, 2016) More than half of the respondents in research conducted by Callan and Hoyes (2000) stated that their initial knowledge of the location came from excellent recommendations from others who had used the product Furthermore, the mass media is powerful nowadays, and it plays a key role in customers’ decisions According to Phuong’s (2021) research, “needing to search for a specific product, customers will access it online, providing an opportunity for businesses to introduce and sell products.” Restaurant information is also quite diversified, as seen by reviews from customers who have used the restaurant’s services and products, it will have a significant impact on customers’ decisions
H7: Reference group factors have a positive (+) influence on customers’ decision to choose a restaurant
Summary
In this chapter, the author has discussed ideas relating to the food industry, consumption decisions, theories of customer choice behavior, a review of some documents, and previous research models Related to the topic Since then, the author has proposed a study model that outlines the significance of 7 factors that diners may consider when selecting Papa’s Food restaurant in District 3 of Ho Chi Minh City’s RomeA Shopping Mall Using the parameters of the proposed model, develop research hypotheses.
METHODOLOGY
Research process and methodology
The author relied on existing theories to develop hypotheses, which guided the research strategy for data collection These hypotheses will be examined and either validated entirely or partially, or refuted, leading to the development of new theories that will be further tested in subsequent research This study emphasizes quantitative observations that can be statistically analyzed to assess hypotheses (Saunders et al., 2012)
This research began with the formulation of hypotheses based on a review of academic literature, followed by the creation of a research strategy to test the theoretical framework Consequently, the author employed a deductive approach Blaikie (2010) states that a deductive approach advances the study by utilizing existing literature or specifying the conditions under which the theories are anticipated to hold, deriving testable propositions, and examining the premises and logic of the argument that produced them This argument is then compared to existing theories to evaluate its contribution to understanding Subsequently, the researcher collects and analyzes relevant data to measure the concepts or variables If the analysis results are consistent with the premises, the theory is corroborated (Saunders et al, 2012; Blaikie, 2010)
Testing the reliability of scales through Cronbach’s Alpha
Conclusion, recommendations, and limitations of the research
Constructing scales to develop survey questions
Proposing hypotheses and theoretical framework
Proposing research questions and objectives Defining research topic
With this research topic, the author constructed a proper research process as illustrated in Figure 5 below
This study combine both qualitative and quantitative methods c Qualitative method:
The qualitative research process involved talking with ten customers who enjoyed the food service at the food court of RomeA Shopping Mall about the factors affecting their decision to choose a restaurant The author and these clients discussed providing the fundamental aspects as a foundation for building a scale and a service model for this study based on all the components of prior studies
Following that, there will be a conversation with ten shopping mall and restaurant executives, as well as several industry specialists
The following information will be gathered from the survey:
Are there any more elements that should be included in the factors influencing customers’ decisions to choose a restaurant?
Understand the contents of each statement on the scale
Should any observed variables be added (or subtracted) from each research concept?
The scales were chosen to help with the creation of the survey questionnaire and subsequent quantitative research after the qualitative research phase
Figure 5: Research process (Source: Author’s construct)
The following factors were accepted by everyone involved after discussion: Product quality, Service quality, Perceived Relevance of Price, Promotion, Additional Services, Reference group, Location Continuance, normative commitment, and involvement on job satisfaction d Quantitative method:
The scales in the research model were retested through quantitative research This is a detailed analysis of the data collected through questionnaires from customers and from there giving specific results on the research topic
The author conducted the questionnaire surveys in the food court of RomeA Shopping Mall The SPSS software, Excel, and other tools will be used to process all of the supplied data These tools include descriptive statistics tools, frequency tables, graphs, reliability testing of scales, EFA factor analysis, regression analysis, and other tests (t-test, ).
Constructing scales
a) The scale of product quality:
Customers’ decisions to choose a restaurant are influenced by factors related to product quality Customers ”frequent” restaurants with good meal (Lewis, 1981; Suk and HenSley, 2004; Liu and Jang, 2009) Richness and freshness should be present in the ingredients used in dishes (Ryu et al., 2012)
PQ1 The restaurant provides savoury and nutritious dishes Lewis (1981); Sulek &
Table 2: Product qualty scale b) The scale of service quality:
The employees’ demeanor, appearance, friendliness, and ability to manage customer needs, as well as their product knowledge and reaction times, all speak to the caliber of the business’s customer service Customer loyalty is also affected by the level of service quality The number of regular restaurant customers (Pugazhenthi, 2010; Kuo et al, 2011)
SQ1 The employees serve the right dishes as ordered
Ryu et Al (2012); Kuo et al
SQ2 The food is served within proper timing
SQ3 The employees are enthusiastic and willing to help customers when needed
SQ4 I feel comfortable when communicating with the employees
PQ3 The menu consists various kind of food Jang (2009); Ryu et al
(2012) PQ4 The quality of the ingredients
PQ5 The sanitary within the cooking process
PQ6 The menu is often updated and has seasonal dishes c) The scale of price:
Customers are likely to have a negative opinion of their dining experience if they think they got less for their money (Mill, 2007) Diners use “price paid” as a “metric for the quality of restaurants,” according to Muller and Woods (1994) Another advantage for attracting customers is competitive selling prices The impact of price is always discernible and always prevails over other considerations Additionally, the transparent selling price fosters customer confidence Additionally, when utilizing the product at the restaurant, people can determine their own financial capacity (Hyun and Kang, 2014)
PR1 The food price in general is reasonable
Hyun and Kang (2014); Mill (2007); Muller and Woods
The price is competitive compare to other restaurants in the mall
PR3 All the prices are listed in the menu
PR4 Various price point for different level of income
Table 4: Price scale d) The scale of additional service:
Two restaurants that offer similar cuisine and service might be selected based on a lower price or other secondary factors (Brookes, 2004) Customers are huge fans of restaurants that offer home delivery Customers can be satisfied by using flexible payment options, table reservation services, pre-ordering, meal ordering forms via online applications, delivery applications, or on the restaurant’s website or
Table 5: Additional service scale e) The scale of location:
An advantageous position is crucial (Tzeng et al., 2002) Customers frequently prefer restaurants that are close to their homes, places of employment, and frequented destinations since it is handy There is close by parking (Bowdin et al, 2006) Restaurants that are easily accessible, in the heart of the city, or in areas with heavy foot traffic can have a significant competitive edge When a product is sold to clients, a good location also raises its worth (Bull, 1994)
LO1 The restaurant is located in the city centre Hyun and Kang (2014);
Tzeng et al,(2002); Bowdin et al (2006); Bull (1994) LO2 The restaurant is near where I live or work
AS1 The restaurant supports reservations and organizes special occasions such as anniversaries or birthdays
AS2 The restaurant offers online ordering through delivery apps
AS3 The restaurant offers app payment service and QR code to help diversify payment methods
AS4 The restaurant’s door-to-door delivery service is very convenient
LO3 The restaurant is located near where I often hang out
Table 6: Location scale f) The scale of reference group:
A customer's decision to dine at a certain restaurant could be impacted by their friends, family, past experiences, or the reputation of the business (Dao, 2016) In a survey conducted by Callan and Hoyes (2000), more than 50% of participants stated that the reason they visited a place for the first time was because of the favorable recommendations of earlier users of the product or service They usually choose trustworthy companies (Chen et al., 2008) Phuong (2021) asserts that when consumers are looking for a specific product, they will search online for information Many restaurants' revenue increase can be attributed in large part to positive media coverage
RG1 The restaurant has good reputation
Dao (2016); Callan and Hoyes (2000); Chen et al (2008); Phuong (2021)
RG2 The restaurant is recommended by friends or relatives
The restaurant is well-reviewed by many people on social networks and food review sites
Table 7: Reference group scale g) The scale of promotion:
Restaurants will stand out from the competition and attract more customers if they regularly conduct appealing specials or promotions According to Tran Tien Lam (2014), customers are also "affected by power." By employing promotions to advertise new products and services, restaurants may reach a larger audience The opportunity to develop the restaurant's brand, inform more people about it, and create a positive impression in their minds is provided by media marketing and advertising campaigns
PRO1 The restaurant often offers good deals and discounts
PRO2 The restaurant's promotion is more alluring than that of other restaurants
PRO3 I became familiar with the restaurant through media advertisements
Table 8: Promotion scale h) The scale of consumer decision:
Intention to buy is influenced by unforeseen customer factors such as comments from family or advertising on social networking sites As a result, there is still a certain distance between the intention to buy and the actual purchase at which clients can change their minds If the purchased product satisfies the customer's expectations, the consumer is satisfied; otherwise, the customer is disappointed In the event of dissatisfaction, customers might complain to their friends or refuse to buy that product or brand again As a result, managers must be truthful in their advertising, present accurate information, and have adequate post-buy customer care practices in place to resolve customer concerns and satisfy customers after purchase
CD1 I will choose the restaurant because it meets the needs of mine
I will choose the restaurant because it suits my ability
CD3 I will choose the restaurant because it brings me high benefits best
I will recommend the restaurant to my friends and relatives
Data collecting
In quantitative research, surveys are the most commonly used data collection approach The author employs the two survey methodologies listed below:
Direct survey: In person, distribute surveys to clients and ask them to fill them out, then collect the distributed questionnaires
Online survey: Customers should be sent online survey surveys in the form of Google Docs via email and social media
The samples were chosen at random The author distributed the questionnaires and conducted customer interviews with the assistance of the restaurant personnel at the RomeA shopping mall food court b) Sample size:
For the exploratory factor analysis (EFA), according to Hair et al (2006), the sample size is determined based on:
(2) the number of variables included in the model's analysis
The number of observations necessary for each analyte variable (k) is 5/1 or 10/1, implying that at least
5 observed variables (5/1) or 10 observed variables (10) are required for each analyte variable
The research model has 7 scales, with a total of 31 observed variables If k = 5/1, the observed sample will be: 5*31 = 155 questionnaires If k = 10/1, the observed sample will be: 10*31 = 310 survey votes As a result, we require a minimum sample size of 155 or 310 questionnaires to perform exploratory factor analysis, depending on the selection rate based on survey ability
Thus, the required sample size is 155 - 310 The sampling period will run from November 2021 to January 2022
Participants’ personal information will be kept completely confidential throughout the data colleting process Please refer to the Appendix for the research ethics checklist form.
Data analysis method
The frequency descriptive statistical method calculates the distribution of data, such as gender, age, education level, position, and seniority of responses, thus illustrating the sample's characteristics The frequency of occurrence of these attributes is based on personal information used to review and comment on the collected sample with the responses
3.4.2: Evaluating the reliability of scales using Cronbach’s Alpha coefficients
Evaluate the scale's reliability using Cronbach's Alpha and remove variables with total variable correlation 0.3; the scale will accept when Cronbach's Alpha >=0.60 (Tho, 2011) is removed from the model because these observed variables are not suitable or meaningful for the scale However, the variables do not match the requirements, thus the decision to exclude or not is based not only on statistics but also on the concept's content value (Tho, 2011)
The Exploratory Factor Analysis (EFA) approach analyzes the correlation between the measured variables by the Barllet test with the level of significance after deleting factors that do not provide reliability using Cronbach's Alpha analysis To determine the suitability of factor analysis, use a 5% mean (Hair et al., 2006) and a KMO test using a coefficient of 0.5 = KMO = 1 (Tho, 2011)
Factor selection criteria: Based on Eigenvalues index >=1 (Tho, 2011)
Kaiser - Meyer - Olkin (KMO): This is the indicator used to assess the suitability of factor analysis If 0.5 KMO 1, the data used for factor analysis is suitable The data utilized for factor
The statistical quantity used to assess the hypothesis H0 is Bartlett's test of sphericity If the significance threshold Sig.< 0.05 is met, hypothesis H0 is rejected, indicating that the variables may be connected with one another overall This demonstrates that the data utilized for factor analysis is correct
The proportion of total variance attributable to factors: This demonstrates the extent to which factors can explain the variability of the observed variables The necessary criterion for the cumulative explained variance is that it should exceed 50%
In statistics, the Pearson correlation coefficient (symbol: r) is utilized by researchers to assess the strength of a linear relationship between two quantitative variables (Gayen 1951 cited in
Schober et al 2018) Pearson correlation analysis will not be performed for non-quantitative variables (e.g., qualitative or binary variables) The Pearson correlation coefficient r ranges from -1 to 1:
- The closer r is to one, the stronger and tighter the linear association Moving towards 1 indicates a positive connection, whereas moving towards -1 indicates a negative correlation
- As r approaches zero, the linear correlation weakens
- If r = 1: absolute linear correlation, the points on the scatter plot will be combined to form a straight line
- There is no linear association if r = 0 There will be two options at this time For starters, there is no correlation between the two factors Second, they have a nonlinear interaction with one another
Field (2009) states that although the Pearson correlation coefficient is employed to analyze the linear relationship between two variables, it is essential to test the statistical significance of this correlation value The following hypothesis is proposed: H0: r = 0 This hypothesis is tested using the t-test The inspection findings are as follows:
- Sig < 0.05: Reject hypothesis H0; that is, r ≠ 0 is statistically significant, and the two variables are linearly associated
- Sig > 0.05: Accept the hypothesis H0, which states that r = 0 is statistically significant and that the two variables have no linear association
Once we've selected two variables having a linear correlation, we'll look at the correlation's strength/weakness using the absolute value of r Andy Field (2009) states:
The correlation analysis results reveal that there is a correlation between the independent factors and the dependent variable We construct and test the regression model as follows:
CD = β0 + β1*PQ + β2*SQ + β3*PR + β4*AS + β5*LO + β6*RG + β7*PRO
PRO: Promotion β0 : Intercept βi: Regression coefficient (i = 1, 4): Reflects the level of influence of indepent variables on dependent variable ε: Residual
The author employed regression analysis to evaluate the suitability of the research model and the degree to which the factors influenced it The values in this column allow the author to examine the hypotheses proposed in chapter two Consequently, after inputting the data into the SPSS software, the author will focus on the coefficients, particularly the standardized coefficients Following the regression analysis on the data, the author generated three tables: Model Summary, ANOVA, and Coefficients (Hoang & Chu, 2008)
Adjusted R Square: This value more accurately reflects the regression model's relevance At the same time, this index indicates the degree to which the independent factors are interpreted for the dependent variables
To examine the autocorrelation of nearby mistakes, the Durbin-Watson (DW) coefficient is used The
DW value will be between 1 and 3 if the mistakes are not autocorrelated The absence of autocorrelation indicates that the data collected is of high quality
Using the F test in the ANOVA table to assess the regression model's applicability to the entire The regression model is significant if sig.< 0.05 In other words, the regression model is appropriate if at least one independent variable can explain the change in the dependent variable
Variance Inflation Factor (VIF): This measure indicates whether or not independent variables are multicollinear If VIF > 2, there is collinearity, which suggests that the independent variables are closely related to each other In contrast, a result of VIF 2 indicates that there is no multi-collinear phenomenon
Standardized coefficients (Beta): This figure illustrates the strength and ranking of the independent variables' impact on the dependent variable The independent variable with the highest Beta coefficient exerts the greatest effect on the change in the dependent variable A negative Beta coefficient signifies a negative influence from the independent variable, while a positive Beta coefficient suggests a positive impact.
Summary
Building upon the literature review presented in Chapter 2, Chapter 3 delineates the research showcases the questionnaire design, which utilizes the Likert scale for 20 observed variables, sets the intended sample size, and elaborates on the survey methodology Furthermore, Chapter 3 clarifies the data processing procedure using SPSS 20 software, encompassing reliability evaluation through Cronbach's alpha coefficient, EFA, and regression analysis Following the survey framework outlined in Chapter 3, the next chapter will employ SPSS 22 software to process the collected data and delve into the analysis of research outcomes This will cover descriptive statistics of the sample, reliability assessment of the scales using Cronbach's Alpha, exploratory factor analysis, regression analysis, and the examination of sample differences for each factor analysis, demonstrating a coherent and comprehensive analysis.
Descriptive statistics of the samples
The sample structure was chosen in accordance with the norm sampling method (quota), and the samples were chosen based on the features of the food quality, service quality, promotion, price, and complementary services addition, place, and reference group The author determined that 310 people would be an adequate sample size for this study based on the research of Hair et al (2006) and Gorsuch
The information is gathered by means of survey submission For six weeks, data were gathered through in-person interviews and online surveys 400 questionnaires were sent to participants in order to reach the sample size goal of 310 After cleaning the remaining data and rejecting 55 questionnaires, the survey received 400 responses 345 acceptable tables were checked and analyzed using SPSS 20.0 software
The collected data is processed and has the following statistical description:
Gender: Research results show that there are 196 males (accounting for 56.8%) and 149 females (accounting for 43.2%)
About age: The majority age group is from 26 to 40 years old, including 213 people (accounting for 61.7%) Next is the age group of 18-25 years old, including 80 people (accounting for 23.2%) The age group 40-55 has 52 people (accounting for 15.1%)
Occupation: The group “Students” includes 72 people (accounting for 20.9%) “Office workers” group includes 206 people (accounting for 59.7%) “Workers” group includes 17 people (accounting for 4.9%) “Other” has 50 people (accounting for 14.5%)
About average income: The group with income from less than 10 million VND/month includes 65 people (accounting for 18.8%) The group with income from 10 to 15 million VND per month has
84 people (accounting for 24.3%) The group with income from 15 to 25 million VND/month includes 80 people (accounting for 23.2%) Finally, the group with an income of over 25 million
VND/month, including 116 people (accounting for 33.6%) is the survey object with the highest percentage
Research results
4.2.1: Cronbach’s Alpha test of scales
After collecting survey data, the author evaluated the scale with Crobach's Alpha coefficients, the scale of the factors had the following results: a Product quality scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach's alpha if Item Deleted
Table 11: Cronbach’s Alpha of Product quality scale
The scale has a high reliability coefficient, or Cronbach's Alpha, of 0.781 Except for the variable PQ3, which has a total correlation coefficient of 0.187 0.3, the total correlation coefficients of the variables making up the variable assessing this factor are all standard (higher than 0.3) So, in order to conduct an EFA analysis, we remove the observed variable PQ3 from this scale
Scale Mean if Scale Variance Corrected Item – Total Cronbach's alpha if
Table 12: Cronbach’s Alpha of Product quality scale
When the variable PQ3 is taken out, the second Cronbach's Alpha result, the product quality component (FQ), has a Cronbach's Alpha coefficient of 0.827 All of the total variable correlation coefficients for this factor measure are over the threshold (higher than 0.3) b Service quality scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach’s Alpha if Item Deleted
Table 13: Cronbach’s Alpha of Service quality scale
In table 9, the Cronbach's Alpha coefficient for the service quality (SQ) component is 0.844, which is very high compared to the satisfactory level and indicates a high level of reliability The correlation coefficients for the entire set of variables all meet the requirement (higher than 0.3); the lowest is SQ1 0.615 and the highest is SQ2 = 0.755 Cronbach's Alpha values if all variables fall below 0.844 Therefore, for the purposes of EFA analysis, the observed variables of this scale are left unmodified c Promotion scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach’s Alpha if Item Deleted
Table 14: Cronbach’s Alpha of Promotion scale With a Cronbach's Alpha coefficient of 0.823, the promotional component (PRO) likewise has a very high level of reliability All of the total variables' correlation coefficients are standard (higher than 0.3); the lowest is PRO2 = 0.632 and the best is PRO1 = 0.704 if all variables are less than 0.85, the Cronbach's Alpha coefficients The promotion component scale thus satisfies the criteria, and EFA analysis is performed using the observed variables of this scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach’s 39lpha if Item Deleted
Table 15: Cronbach’s Alpha of Price scale
The pricing (PR) component has a Cronbach's Alpha coefficient of 0.814, which is also a very trustworthy coefficient when compared to the satisfactory level All of the total variables' correlation coefficients are standard (greater than 0.3), with PR3 = 0.563 being the lowest and PR1 = 0.700 being the highest if all variables are less than 0.814, the Cronbach's Alpha coefficients As a result, the price component scale satisfies the criteria, and the EFA analysis uses the observed variables of this scale e Additional service scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach’s Alpha if Item Deleted
Table 16: Cronbach’s Alpha of Additional service scale
The Cronbach's Alpha coefficient for the supplementary service component is 0.855, which is likewise a rather high reliability coefficient when compared to the satisfactory level All of the total variables' correlation coefficients are standard (higher than 0.3); the lowest is for PS4 (0.641), and the highest is for PS3 (0.733) if all the variables are equal or less than 0.855, the Cronbach's Alpha coefficients The observed variables of the added service component scale are employed for EFA analysis as a result, which is why it is satisfactory e Location scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach’s Alpha if Item Deleted
Table 17: Cronbach’s Alpha of Location scale
Cronbach's Alpha coefficient for the location component is 0.774, which is likewise a good reliability coefficient when compared to the satisfactory level The lowest correlation coefficient for the total variables is LO3 = 0.492, and the highest is LO1 = 0.691 All correlation values are standard (higher than 0.3) if all variables are less than 0.774, the Cronbach's Alpha coefficients The location/place component scale thus satisfies the criteria, and the observed variables from this scale are employed in the EFA analysis g Reference group scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach’s Alpha if Item Deleted
Table 18: Cronbach’s Alpha of Reference group scale The reference group (RG) component has a Cronbach's Alpha coefficient of 0.863, which is likewise a very trustworthy coefficient when compared to the satisfactory level All of the total variables' correlation coefficients are over the limit (higher than 0.3); the lowest is RG2's coefficient of 0.730 and the highest is RG3's coefficient of 0.763 if all variables have Cronbach's Alpha values less than 0.86 As a result, the reference group composition scale satisfies the criteria, and EFA analysis is performed using the observed variables of this scale h Consumer decision scale
Scale Mean if Item Deleted
Scale Variance if Item Deleted
Cronbach’s Alpha if Item Deleted
Table 19: Cronbach’s Alpha of Consumer decision scale The consumer decision component has a satisfactory reliability Cronbach's Alpha coefficient of 0.849, which is also the coefficient All of the total variables' correlation coefficients are standard (higher than selection decision variable satisfies the criteria
4.2.2: Exploratory Factor Analysis (EFA) a Independent variables:
Principal Axis Factoring method with Promax rotation is applied The author proceeded to put the observed variables of the scales into the EFA factor analysis, we got the following results:
The scales in these 7 factors all have factor loading > 0.5, satisfactory That is, the scale for the factor
"Product quality", "Quality of service", "Promotion", "Perceived appropriateness of price", "Additional service", "Location/location", The “reference group” has achieved convergent and discriminant validity
KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy
Initial Eigenvalues Extraction Sums of
Rotation Sums of Squared Loadings
Table 20,21: KMO and Bartlett's Test and Total Variance Explained
At the value of Eigenvalues = 1.312 with Principal Axis Factoring extraction method and Promax rotation with 7 factors extracted, extracted variance of 69.273% (> 50%) is sufficient This suggests that these 7 extracted components may satisfactorily account for about 69.273% of the variation in the data
Extraction Method: Principal Component Analysis Table 22: Rotated Component Matrix a b Depedent variable:
The analysis results of the observed variables of the dependent variable in the EFA factor analysis have the following results:
The concept of "Decision to choose"
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .817
Bartlett's Test of Sphericity Approx Chi-Square 570.779 df 6
Table 23: KMO and Bartlett's Test of Consumer decision
Initial Eigenvalues Extraction Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative %
Extraction Method: Principal Component Analysis
At Eigenvalues = 2.756 with Principal Components extraction method and Varimax rotation with 1 factor extracted with extracted variance of 68,902% (> 50%), satisfactory This indicates that this single extracted factor can explain 68.902% of the variation in the data, which is a satisfactory result
The four scales in this factor all have factor loading coefficient > 0.5, satisfactory That is, the scale for the factor “Selection decision” has achieved convergent value and discriminant value
Extraction Method: Principal Component Analysis
Table 25: Component matrix of consumer decision
In comparison to the suggested original observed variables, the observed variable components of the independent and dependent variables are left unchanged Cronbach's Alpha coefficient remains unchanged as a result
DC PRO PR PS PQ LO SQ RG
** Correlation is significant at the 0.01 level (2-tailed)
Table 26: Pearson correlation analysis results The correlation coefficient matrix demonstrates the relationship between the independent variables and the dependent variable, which has an impact on the decision A comparison of the range of correlation coefficients (r) for independent variables such as product quality (PQ), service quality (SQ), perceived price suitability (PR), promotion (PRO), additional services (AS), location/location (LO), and reference group (RG) reveals that the independent variables and the dependent variable are highly correlated It is acceptable to include these independent variables in the regression analysis model to explain the dependent variable
The study used multiple linear regression analysis method with 7 independent variables including product quality (FQ), service quality (SQ), perceived fit of price (PR), promotion (PRO) ), additional
N 345 345 345 345 345 345 345 345 services (PS), location/location (LO), reference group (RG) and dependent variable is decision of choice (DC) applying the one-pass method to obtain the following results :
Std Error of the Estimate
1 825 a 681 675 35201 2.122 a Predictors: (Constant), RG, PQ, PS, PRO, SQ, LO, PR b Dependent Variable: CD
The adjusted R square = 0.603 Therefore, we can say that the built linear regression model fits the sample data set of 60.3 The Durbin–Watson statistic (d) = 1.88 shows that there is no correlation between the residuals This means that the regression model does not violate the assumption of error independence
Squares df Mean Square F Sig
Squares df Mean Square F Sig
Total 131.008 344 a Predictors: (Constant), RG, PQ, AS, PRO, SQ, LO, PR b Dependent Variable: CD
Table 28: ANOVA a The Anova analysis reveals that the Sig coefficient is equal to 0.00 0.01 and that the regression variation of 89,250 is significantly greater than the residual variation of 41,758 This indicates that the population is fit into the multiple linear regression model
Hypotheses Testing
The following section presents the findings of the author's hypotheses that were put out in chapter two in accordance with the findings of the regression analysis
H1: “Product quality” has a positive (+) influence on customers' restaurant choice
The research findings reveal that product quality (PQ) has the strongest impact on consumer decisions when purchasing Papa's Food products, with β = 0.261 specifically, assume other factors remain constant, a 1-unit change in product quality leads to a 0.261-unit increase in consumer decision This indicates that Papa's Food's consumer decisions are preeminently inspired by the company's product quality As a result, hypothesis H1 is accepted with a 1% significance level, meaning product quality affects 26.1% of consumer decisions
H2: “Service quality” has a positive (+) influence on customers' decision to choose a restaurant The study also shows that service quality (SQ) has a β = 0.153 Assuming other factors remain constant, a 1-unit change in service quality leads to a 0.153-unit increase in consumer decision Thus, hypothesis H2 is accepted with a 1% significance level, meaning service quality affects 15.3% of consumer decisions
H3: “Suitable price” has a positive (+) influence on customers' decision to choose a restaurant Additionally, suitable price (PR) has a β = 0.087, making it the second least influential factor on consumer decisions Assuming other factors remain constant, a 1-unit change in suitable price leads to a 0.087-unit increase in consumer decision Therefore, hypothesis H3 is accepted with a 1% significance level, meaning suitable price affects 8.7% of consumer decisions
H4: “Promotion” has a positive (+) influence on customers' decision to choose a restaurant
The findings also indicate that promotion (PRO) strongly impacts consumer decisions with a β = 0.167 Assuming other factors remain constant, a 1-unit change in promotion leads to a 0.167-unit increase in consumer decisions Thus, hypothesis H4 is accepted with a 1% significance level, meaning promotion affects 16.7% of consumer decisions
H5: “Additional service” has a positive (+) influence on restaurant selection
Moreover, the research results show that additional service (AS) has a β = 0.153, equal in influence to the service quality factor Assuming other factors remain constant, a 1-unit change in additional service leads to a 0.153-unit increase in consumer decision Consequently, hypothesis H5 is accepted with a 1% significance level, meaning additional service affects 15.3% of consumer decisions
H6: “Location” has a positive (+) influence on restaurant selection
Furthermore, location (LO) has the lowest impact on consumer decisions with a β = 0.072 Assuming other factors remain constant, a 1-unit change in location leads to a 0.072-unit increase in consumer decisions Thus, hypothesis H6 is accepted with a 1% significance level, meaning location affects 7.2% of consumer decisions
H7: “Reference group” has a positive (+) influence on restaurant selection
Lastly, the research findings indicate that the reference group (RG) significantly influences consumer decisions, with a β = 0.164, similar in importance to product quality and promotion Assuming other factors remain constant, a 1-unit change in the reference group factor leads to a 0.153-unit increase in consumer decisions Therefore, hypothesis H7 is accepted with a 1% significance level, meaning the reference group affects 16.4% of consumer decisions
Hypotheses Statements Expected Research results Conclusion
“Product quality” has a positive influence on customers' restaurant choice
“Service quality” has a positive influence on customers' decision to choose a restaurant
“Suitable price” has a positive influence on customers' decision to choose a restaurant
“Promotion” has a positive influence on customers' decision to choose a restaurant
“Additional service” has a positive influence on restaurant selection
“Location” has a positive influence on restaurant selection
“Reference group” has a positive influence on restaurant selection
Hypotheses Statements Expected Research results Conclusion sig = 0.000