Table 1. 1: Comparison of Online Marketing and Traditional Marketing 11
Table 1.2 Scale of assessing factors affecting the acceptance of online marketing system at Philip Entertainment company 22
Table 2.1: Products and services of Philip Entertainment 33
Table 2. 2: Philip Entertainment's labor situation over 3 years (2018 - 2020) 37
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Table 2. 3: Number of customers of Philip Entertainment in the period of 2018 - 2020 ...39 Table 2. 4: Business performance of Philip Entertainment LLC in the period of 2018 - 2020 40
Table 2.5: Capital assets situation in the period 2018 - 2020 41
Table 2.6: Media advertising through newspapers in month 48
Table 2.7: Characteristics of the survey sample 53
Table 2.8: Online channels used by customers when searching for information 54
Table 2.9: Media information search activities 55
Table 2. 10: Sources of information that customers know about Philip Entertainment company...57 Table 2. 11: Types of services that customers have used and are using from Philip Entertainment company 57
Table 2. 12: Monitoring activities of Fanpage “Philip Entertainment & Digital Marketing” ...58 Table 2. 13: Descriptive statistics of observed variables of the factor “Attraction” 59
Table 2.14: Descriptive statistics of observed variables of the factor “Attractiveness” 60
Table 2.15: Descriptive statistics of observed variables of the factor “Search” 61
Table 2.16: Descriptive statistics of observed variables of the factor “Action” 62
Table 2.17: Descriptive statistics of observed variables of the factor “Sharing” 63
Table 2.18: Descriptive statistics of dependent variable factors “Acceptance" 63
Table 2.19: Reliability test of independent variables 64
Table 2.20: Reliability test of the scale of dependent variable 65
Table 2. 21: KMO test and Bartlett's Test of independent variables 66
Table 2. 22: Exploratory factor analysis EFA of independent variables 67
Table 2. 23 KMO test and Bartlett's Test of dependent variable 68
Table 2. 24 Exploratory factor analysis EFA of dependent variable “MO” 69
Table 2. 25 Pearson correlation analysis 70
Table 2. 26: Statistical analysis of regression coefficient 72
Table 2. 27: ANOVA analysis of variance 72
Table 2. 28 Regression analysis results 73
Table 2. 29 Testing gender differences in online marketing system acceptance 78
Table 2. 30 Levene test results of age variable 80
Table 2.31 Welch test results of age variable 80
Table 2. 32 Results of One – Sample T Test of factor “Acceptance” 81
PART I: PROBLEM STATEMENT
1. Reason for researching the topic
In the 4.0 era, with the strong development of information technology, especially the emergence of digital applications, customers' information search behavior has changed. Previously, instead of searching for information through TV commercials or newspapers, people searched on social networking sites.
According to VNETWORK 's Digital 2020 report , Vietnam has a population of 96.9 million; the number of mobile subscribers is 145.8 million (accounting for 150% of the total population of the country); the number of internet users is 68.17 million (accounting for 70% of the population); the number of social network users is 65 million (accounting for 67% of the population). In the past, consumers looked to daily marketing newspapers to find products, but now they just need to search on the internet anytime, anywhere. From these numbers, business owners have seen the importance of Online Marketing activities in their business strategy.
The importance of Online Marketing is especially evident in the context of the current global economic crisis caused by Covid 19. Businesses must minimize costs to maintain business operations and Marketing is no exception. Therefore, Online Marketing is the most perfect choice in Marketing strategies because it not only helps businesses reach customers in the fastest and most effective way but also helps businesses reduce investment costs.
Philip Entertainment Media and Entertainment Company Limited has been operating for 3 years (since January 4, 2018) and is a unit specializing in producing TVC advertisements, movies, live streaming services, etc., and has established a foothold in Hue. However, in the context of fierce competition and the negative impact of the Covid-19 epidemic, the company is required to change to quickly reach customers; bring the company's image and brand to customers in other provinces (cities) across the country. Therefore, completing Online Marketing activities
is an optimal solution, suitable for the development trend of the enterprise. Although Online Marketing has been applied to approach customers, the company's Online Marketing activities still have many limitations and the work of evaluating the effectiveness of the activities has not been fully implemented. Therefore, the topic "Evaluation of Online Marketing activities of Philip Entertainment Media and Entertainment Company Limited" has practical significance.
2. Research objectives
2.1. General research objectives
Generalize theoretical and practical issues of Online Marketing, thereby evaluating the Online Marketing activities of Philip Entertainment Media and Entertainment Company.
2.2. Specific research objectives
The topic is addressed through the following objectives:
First, systematize theoretical and practical issues related to Online Marketing activities.
Second, analyze the current status of Online Marketing application of Philip Entertainment Media and Entertainment Company.
Third, propose some solutions to help the company improve the Online Marketing activities of Philip Entertainment Media and Entertainment Company.
3. Research questions
What is Online Marketing? Online Marketing activities include the following activities:
any?
Online Marketing Activities of Philip Media and Entertainment Company
Entertainment.
How does it work?
What should Philip Entertainment Media and Entertainment do to improve its operations?
Online Marketing for yourself?
4. Research object and scope
4.1. Research subjects
Research object: Online Marketing activities.
Survey target: Current customers of Media and Entertainment Company
Philip Entertainment.
4.2. Scope of research
Spatial scope: Hue City.
Time range: Secondary data collected from the period 01/2018 – 12/2020; data
Primary data collected from October 20, 2020 to January 15, 2020.
5. Research methods
5.1. Data collection method
5.1.1. Secondary data collection methods
Secondary data to be collected includes:
First, general information about Philip Entertainment Media and Entertainment Company, this information is collected through data provided by the company, information from the company's website.
Second, research theories about Online Marketing, as well as indicators to evaluate Online Marketing services in businesses. Collect and learn information through books, reports, magazines, websites, social networking sites, etc.
Third, collect statistical results on Online Marketing activities as well as tools being used by Philip Entertainment Media and Entertainment Company for evaluation such as Facebook statistics on reach, interaction, feedback, etc.
5.1.2. Primary data collection methods
Qualitative research by in-depth interviews with employees performing Online Marketing activities of Philip Entertainment Media and Entertainment Company; to know and understand more about the Marketing activities that the company is using, the KPIs systems used to evaluate as well as the company's orientation. The interview content will revolve around the methods and goals of the Online Marketing activities that Philip Entertainment is implementing.
Quantitative research by collecting information through questionnaires for Philip Entertainment customers, to learn and analyze the reality.
as well as the effectiveness of Online Marketing activities that Philip Entertainment is implementing.
implementation, from which to propose additional solutions and complete the activities. The questionnaire consists of 3 parts: Part 1: Guiding questions.
Part 2: Main content of the questionnaire (asking questions related to the assessment)
company's online marketing activities).
Part 3: Personal information of the respondent.
Then conduct a pilot survey with a few interviewees. Adjust, remove or add questions to get the official questionnaire to conduct the survey. The official survey data will be used throughout the processing and analysis process.
5.2. Sampling method
Determine sampling method: use convenient non-random method.
Determining sample size: With a research model consisting of 5 independent variables including 22 observed variables and 1 dependent variable to meet the investigation requirements and ensure representation of the overall research, as well as the methods of exploratory factor analysis EFA and multiple linear regression of independent factors with dependent variables in data analysis and processing, the sample size must satisfy the following conditions:
(1) According to “Analyzing research data with SPSS” (Hoang Trong & Chu Nguyen Mong Ngoc, 2008), the number of samples needed for factor analysis must be greater than or equal to five times the number of observed variables: Nmin = Number of observed variables * 5 = 22*5 = 110.
(2) According to "Research methods in business" (Nguyen Dinh Tho, 2014), the number of design samples to be able to conduct regression analysis must satisfy the following condition: Nmin = 50 + 8p = 50 +8*5 = 90 (In which, p is the independent variable).
From the above sample size calculation, we will choose the smallest sample size of 110. However, to ensure the accuracy of the data and the collection of survey forms during the investigation, the author chose the sample size of 130.
5.3. Data analysis and processing methods
5.3.1. Cronbach's Alpha scale reliability test
It is a test that allows to evaluate the reliability of establishing a composite variable on the basis of many single variables. According to many researchers, variables with a Corrected Item Total Correlation coefficient greater than 0.3 and a Cronbach's Alpha coefficient greater than 0.6 will be accepted and included in the next steps of analysis and processing. Specifically:
Cronbach's Alpha coefficient greater than 0.8: high correlation coefficient.
Cronbach's Alpha coefficient from 0.7 to 0.8: acceptable.
Cronbach's Alpha coefficient from 0.6 to 0.7: acceptable if the scale is new.
5.3.2. Exploratory factor analysis EFA
Used to test the convergence of component variables on concepts. Variables with a simple correlation coefficient between variables and factors (factor loading) less than 0.5 will be eliminated. Exploratory factor analysis EFA is the main technique for reducing and summarizing data. Exploratory factor analysis is useful in determining the sets of variables necessary for the research problem as well as essential in finding the relationship between variables.
The extraction of representative factors by observed variables is performed by principal factor analysis with rotation (Promax). To conduct exploratory factor analysis EFA must ensure the following factors:
(1) Factor loading > 0.5
(2) The KMO coefficient (Kaiser-Meyer-Olkin) must be in the range 0.5 ≤ KMO ≤ 1
(3) Percentage of variance > 50%
(4) Eigenvalue ≥ 1 (Gerbing & Anderson, 1998)
5.3.3. Correlation regression analysis
Consider the necessary assumptions in the linear regression model as part of the test.
standardized residuals, VIF variance inflation factor test, Durbin Watson value test.
If the above assumptions are not violated, the regression model is built. The coefficient shows how much of the variation in the dependent variable is explained by the independent variables included in the model.
The regression model has the form:
Y = β0 + β1X1 + β2X2 +…+ βkXi + ei
In there:
Y: dependent variable
β0: intercept coefficient (constant)
βk: partial regression coefficient
Xi: independent variables in the model ei: random independent variables
Based on the standard Beta coefficient with the corresponding significance level Sig. to determine which independent variables affect the dependent variable in the model and to what extent.
5.3.4. Test for differences
Independent – Sample – test to test whether there is a gender difference in the acceptance of the Online Marketing system at Philip Entertainment company. Hypothesis to be tested:
H 0 : There is no difference between the 2 gender groups H 1 : There is a difference between the 2 gender groups
If Sig > 0.05: hypothesis H 0 is accepted. If Sig < 0.05: hypothesis H 0 is rejected.
One-Way ANOVA test to test the difference between age groups in the acceptance of Online Marketing system at Philip Entertainment company. Hypothesis to be tested:
H 0 : there is no difference between age groups H 1 : there is a difference between age groups
If Sig > 0.05: hypothesis H 0 is accepted