JM Keynes' general theory in the 1930s explained the phenomenon of the world economic crisis and changed the concept of economists at that time when they used the concept of national income as the only way to evaluate a country's economy.
In the early 1950s, the need for international comparisons required the establishment of a national accounting system according to international standards. In 1953, the League of Nations (the predecessor of the United Nations) based on the report of Richard Stone - the head of the research team at Cambridge University to build the first SNA. This was the first version of the SNA, also known as SNA 1953.
After ten years of applying the 1953 SNA, the United Nations statistical agency comprehensively incorporated economic theories, revised and published the 1968 version of the SNA. This version was also revised by Richard Stone himself, the head of the Cambridge team. A very important addition of this version was to put the IO Table at the center of the system.
In the next ten years, the world economy developed rapidly, and it was necessary to continue to unify the concepts and definitions of socio-economic indicators between the United Nations Statistical Organization and other organizations such as the World Bank, IMF, European Statistical Commission (EUROSTAT), the Organization for European Cooperation and Development (OECD), the World Trade Organization (WTO), UNWTO, etc. Members of these organizations and the world's leading economic experts held a joint workshop and the SNA 1993 was born.
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Mobile Phone Usage in Hanoi Inner City Area
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zt2a3gsconsumer,consumption,consumer behavior,marketing,mobile marketing
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zc2o3n4t5e6n7ts
- Test the relationship between demographic variables and consumer behavior for Mobile Marketing activities
The analysis method used is the Chi-square test (χ2), with statistical hypotheses H0 and H1 and significance level α = 0.05. In case the P index (p-value) or Sig. index in SPSS has a value less than or equal to the significance level α, the hypothesis H0 is rejected and vice versa. With this testing procedure, the study can evaluate the difference in behavioral trends between demographic groups.
CHAPTER 4
RESEARCH RESULTS
During two months, 1,100 survey questionnaires were distributed to mobile phone users in the inner city of Hanoi using various methods such as direct interviews, sending via email or using questionnaires designed on the Internet. At the end of the survey, after checking and eliminating erroneous questionnaires, the study collected 858 complete questionnaires, equivalent to a rate of about 78%. In addition, the research subjects of the thesis are only people who are using mobile phones, so people who do not use mobile phones are not within the scope of the thesis, therefore, the questionnaires with the option of not using mobile phones were excluded from the scope of analysis. The number of suitable survey questionnaires included in the statistical analysis was 835.
4.1 Demographic characteristics of the sample
The structure of the survey sample is divided and statistically analyzed according to criteria such as gender, age, occupation, education level and personal income. (Detailed statistical table in Appendix 6)
- Gender structure: Of the 835 completed questionnaires, 49.8% of respondents were male, equivalent to 416 people, and 50.2% were female, equivalent to 419 people. The survey results of the study are completely consistent with the gender ratio in the population structure of Vietnam in general and Hanoi in particular (Male/Female: 49/51).
- Age structure: 36.6% of respondents are <23 years old, equivalent to 306 people. People from 23-34 years old
accounting for the highest proportion: 44.8% equivalent to 374 people, people aged 35-45 and >45 are 70 and 85 people equivalent to 8.4% and 10.2% respectively. Looking at the results of this survey, we can see that the young people - youth account for a large proportion of the total number of people participating in the survey. Meanwhile, the middle-aged people including two age groups of 35 - 45 and >45 have a low rate of participation in the survey. This is completely consistent with the reality when Mobile Marketing is identified as a Marketing service aimed at young people (people under 35 years old).
- Structure by educational level: among 835 valid responses, 541 respondents had university degrees, accounting for the highest proportion of ~ 75%, 102 had secondary school degrees, ~ 13.1%, and 93 had post-graduate degrees, ~ 11.9%.
- Occupational structure: office workers and civil servants are the group with the highest rate of participation with 39.4%, followed by students with 36.6%. Self-employed people account for 12%, retired housewives are 7.8% and other occupational groups account for 4.2%. The survey results show that the student group has the same rate as the group aged <23 at 36.6%. This shows the accuracy of the survey data. In addition, the survey results distributed by occupational criteria have a rate almost similar to the sample division rate in chapter 3. Therefore, it can be concluded that the survey data is suitable for use in analysis activities.
- Income structure: the group with income from 3 to 5 million has the highest rate with 39% of the total number of respondents. This is consistent with the income structure of Hanoi people and corresponds to the average income of the group of civil servants and office workers. Those
People with no income account for 23%, income under 3 million VND accounts for 13% and income over 5 million VND accounts for 25%.
4.2 Mobile phone usage in Hanoi inner city area
According to the survey results, most respondents said they had used the phone for more than 1 year, specifically: 68.4% used mobile phones from 4 to 10 years, 23.2% used from 1 to 3 years, 7.8% used for more than 10 years. Those who used mobile phones for less than 1 year accounted for only a very small proportion of ~ 0.6%. (Table 4.1)
Table 4.1: Time spent using mobile phones
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Alid
<1 year
5
.6
.6
.6
1-3 years
194
23.2
23.2
23.8
4-10 years
571
68.4
68.4
92.2
>10 years
65
7.8
7.8
100.0
Total
835
100.0
100.0
The survey indexes on the time of using mobile phones of consumers in the inner city of Hanoi are very impressive for a developing country like Vietnam and also prove that Vietnamese consumers have a lot of experience using this high-tech device. Moreover, with the majority of consumers surveyed having a relatively long time of use (4-10 years), it partly proves that mobile phones have become an important and essential item in people's daily lives.
When asked about the mobile phone network they are using, 31% of respondents said they are using the network of Vietel company, 29% use the network of
of Mobifone company, 27% use Vinaphone company's network and 13% use networks of other providers such as E-VN telecom, S-fone, Beeline, Vietnammobile. (Figure 4.1).
Figure 4.1: Mobile phone network in use
Compared with the announced market share of mobile telecommunications service providers in Vietnam (Vietel: 36%, Mobifone: 29%, Vinaphone: 28%, the remaining networks: 7%), we see that the survey results do not have many differences. However, the statistics show that there is a difference in the market share of other networks because the Hanoi market is one of the two main markets of small networks, so their market share in this area will certainly be higher than that of the whole country.
According to a report by NielsenMobile (2009) [8], the number of prepaid mobile phone subscribers in Hanoi accounts for 95% of the total number of subscribers, however, the results of this survey show that the percentage of prepaid subscribers has decreased by more than 20%, only at 70.8%. On the contrary, the number of postpaid subscribers tends to increase from 5% in 2009 to 19.2%. Those who are simultaneously using both types of subscriptions account for 10%. (Table 4.2).
Table 4.2: Types of mobile phone subscribers
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Prepay
591
70.8
70.8
70.8
Pay later
160
19.2
19.2
89.9
Both of the above
84
10.1
10.1
100.0
Total
835
100.0
100.0
The above figures show the change in the psychology and consumption habits of Vietnamese consumers towards mobile telecommunications services, when the use of prepaid subscriptions and junk SIMs is replaced by the use of two types of subscriptions for different purposes and needs or switching to postpaid subscriptions to enjoy better customer care services.
In addition, the majority of respondents have an average spending level for mobile phone services from 100 to 300 thousand VND (406 ~ 48.6% of total respondents). The high spending level (> 500 thousand VND) is the spending level with the lowest number of people with only 8.4%, on the contrary, the low spending level (under 100 thousand VND) accounts for the second highest proportion among the groups of respondents with 25.4%. People with low spending levels mainly fall into the group of students and retirees/housewives - those who have little need to use or mainly use promotional SIM cards. (Table 4.3).
Table 4.3: Spending on mobile phone charges
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<100,000
212
25.4
25.4
25.4
100-300,000
406
48.6
48.6
74.0
300,000-500,000
147
17.6
17.6
91.6
>500,000
70
8.4
8.4
100.0
Total
835
100.0
100.0
The statistics in Table 4.3 are similar to the percentages in the NielsenMobile survey results (2009) with 73% of mobile phone users having medium spending levels and only 13% having high spending levels.
The survey results also showed that up to 31% ~ nearly one-third of respondents said they sent more than 10 SMS messages/day, meaning that on average they sent 1 SMS message for every working hour. Those with an average SMS message volume (from 3 to 10 messages/day) accounted for 51.1% and those with a low SMS message volume (less than 3 messages/day) accounted for 17%. (Table 4.4)
Table 4.4: Number of SMS messages sent per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
142
17.0
17.0
17.0
3-10 news
427
51.1
51.1
68.1
>10 news
266
31.9
31.9
100.0
Total
835
100.0
100.0
Similar to sending messages, those with an average message receiving rate (from 3-10 messages/day) accounted for the highest percentage of ~ 55%, followed by those with a high number of messages (over 10 messages/day) ~ 24% and those with a low number of messages received daily (under 3 messages/day) remained at the bottom with 21%. (Table 4.5)
Table 4.5: Number of SMS messages received per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
175
21.0
21.0
21.0
3-10 news
436
55.0
55.0
76.0
>10 news
197
24.0
24.0
100.0
Total
835
100.0
100.0
When comparing the data of the two result tables 4.4 and 4.5, we can see the reasonableness between the ratio of the number of messages sent and the number of messages received daily by the interview participants.
4.3 Current status of SMS advertising and Mobile Marketing
According to the interview results, in the 3 months from the time of the survey and before, 94% of respondents, equivalent to 785 people, said they received advertising messages, while only a very small percentage of 6% (only 50 people) did not receive advertising messages (Table 4.6).
Table 4.6: Percentage of people receiving advertising messages in the last 3 months
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Have
785
94.0
94.0
94.0
Are not
50
6.0
6.0
100.0
Total
835
100.0
100.0
The results of Table 4.6 show that consumers in the inner city of Hanoi are very familiar with advertising messages. This result is also the basis for assessing the knowledge, experience and understanding of the respondents in the interview. This is also one of the important factors determining the accuracy of the survey results.
In addition, most respondents said they had received promotional messages, but only 24% of them had ever taken the action of registering to receive promotional messages, while 76% of the remaining respondents did not register to receive promotional messages but still received promotional messages every day. This is the first sign indicating the weaknesses and shortcomings of lax management of this activity in Vietnam. (Table 4.7)
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Identify Rating Levels and Rating Scales
zt2i3t4l5ee
zt2a3gstourism,quan lan,quang ninh,ecology,ecotourism,minh chau,van don,geography,geographical basis,tourism development,science
zt2a3ge
zc2o3n4t5e6n7ts
of the islanders. Therefore, this indicator will be divided into two sub-indicators:
a1. Natural tourism attractiveness a2. Cultural tourism attractiveness
b. Tourist capacity
The two island communes in Quan Lan have different capacities to receive tourists. Minh Chau Commune is home to many standard hotels and resorts, attracting high-income domestic and international tourists. Meanwhile, Quan Lan Commune has many motels mainly built and operated by local people, so the scale and quality are not high, and will be suitable for ordinary tourists such as students.
c. Time of exploitation of Quan Lan Island Commune:
Quan Lan tourism is seasonal due to weather and climate conditions and festivals only take place on certain days of the year, specifically in spring. In Quan Lan commune, the period from April to June and from September to November is considered the best time to visit Quan Lan because the cultural tourism activities are mainly associated with festivals taking place during this time.
Minh Chau island commune:
Tourism exploitation time is all year round, because this is a place with a number of tourist attractions with diverse ecosystems such as Bai Tu Long National Park Research Center, Tram forest, Turtle Laying Beach, so besides coming to the beach for tourism and vacation in the summer, Minh Chau will attract research groups to come for tourism combined with research at other times of the year.
d. Sustainability
The sustainability of ecotourism sites in Quan Lan and Minh Chau communes depends on the sensitivity of the ecosystems to climate changes.
landscape. In general, these tourist destinations have a fairly high level of sustainability, because they are natural ecosystems, planned and protected. However, if a large number of tourists gather at certain times, it can exceed the carrying capacity and affect the sustainability of the environment (polluted beaches, damaged trees, animals moving away from their habitats, etc.), then the sustainability of the above ecosystems (natural ecosystems, human ecosystems) will also be affected and become less sustainable.
e. Location and accessibility
Both island communes have ports to take tourists to visit from Van Don wharf:
- Quan Lan – Van Don traffic route:
Phuc Thinh – Viet Anh high-speed boat and Quang Minh high-speed boat, depart at 8am and 2pm from Van Don to Quan Lan, and at 7am and 1pm from Quan Lan to Van Don. There are also wooden boats departing at 7am and 1pm.
- Van Don - Minh Chau traffic route:
Chung Huong high-speed train, Minh Chau train, morning 7:30 and afternoon 13:30 from Van Don to Minh Chau, morning 6:30 and afternoon 13:00 from Minh Chau to Van Don.
f. Infrastructure
Despite receiving investment attention, the issue of infrastructure and technical facilities for tourism on Quan Lan Island is still an issue that needs to be resolved because it has a direct impact on the implementation of ecotourism activities. The minimum conditions for serving tourists such as accommodation, electricity, water, communication, especially medical services, and security work need to be given top priority. Ecotourism spots in Minh Chau commune are assessed to have better infrastructure and technical facilities for tourism because there are quite complete and synchronous conditions for serving tourists, meeting many needs of domestic and foreign tourists.
3.2.1.4. Determine assessment levels and assessment scales
Corresponding to the levels of each criterion, the index is the score of those levels in the order of 4, 3, 2, 1 decreasing according to the standard of each level: very attractive (4), attractive (3), average (2), less attractive (1).
3.2.1.5. Determining the coefficients of the criteria
For the assessment of DLST in the two communes of Quan Lan and Minh Chau islands, the students added evaluation coefficients to show the importance of the criteria and indicators as follows:
Coefficient 3 with criteria: Attractiveness, Exploitation time. These are the 2 most important criteria for attracting tourists to tourism in general and eco-tourism in particular, so they have the highest coefficient.
Coefficient 2 with criteria: Capacity, Infrastructure, Location and accessibility . Because the assessment area is an island commune of Van Don district, the above criteria are selected by the author with appropriate coefficients at the average level.
Coefficient 1 with criteria: Sustainability. Quan Lan has natural and human-made ecotourism sites, with high biodiversity and little impact from local human factors. Most of the ecotourism sites are still wild, so they are highly sustainable.
3.2.1.6. Results of DLST assessment on Quan Lan island
a. Assessment of the potential for natural tourism development
For Minh Chau commune:
+ Natural tourism attractiveness is determined to be very attractive (4 points) and the most important coefficient (coefficient 3), so the score of the Attractiveness criterion is 4 x 3 = 12.
+ Capacity is determined as average (2 points) and the coefficient is quite important (coefficient 2), then the score of Capacity criterion is 2 x 2 = 4.
+ Exploitation time is long (4 points), the most important coefficient (coefficient 3) so the score of the Exploitation time criterion is 4 x 3 = 12.
+ Sustainability is determined as sustainable (4 points), the important coefficient is the average coefficient (coefficient 1), so the score of the Sustainability criterion is 4 x 1 = 4 points
+ Location and accessibility are determined to be quite favorable (2 points), the coefficient is quite important (coefficient 2), the criterion score is 2 x 2 = 4 points.
+ Infrastructure is assessed as good (3 points), the coefficient is quite important (coefficient 2), then the score of the Infrastructure criterion is 3 x 2 = 6 points.
The total score for evaluating DLST in Minh Chau commune according to 6 evaluation criteria is determined as: 12 + 4 + 12 + 4 + 4 + 6 = 42 points
Similar assessment for Quan Lan commune, we have the following table:
Table 3.3: Assessment of the potential for natural ecotourism development in Quan Lan and Minh Chau communes
Attractiveness of self-tourismof course
Capacity
Mining time
Sustainability
Location and accessibility
Infrastructure
Result
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
CommuneMinh Chau
12
12
4
8
12
12
4
4
4
8
6
8
42/52
Quan CommuneLan
6
12
6
8
9
12
4
4
4
8
4
8
33/52
b. Assessment of the potential for humanistic tourism development
For Quan Lan commune:
+ The attractiveness of human tourism is determined to be very attractive (4 points) and the most important coefficient (coefficient 3), so the score of the Attractiveness criterion is 4 x 3 = 12.
+ Capacity is determined to be large (3 points) and the coefficient is quite important (coefficient 2), then the score of the Capacity criterion is 3 x 2 = 6.
+ Mining time is average (3 points), the most important coefficient (coefficient 3) so the score of the Mining time criterion is 3 x 3 = 9.
+ Sustainability is determined as sustainable (4 points), the important coefficient is the average coefficient (coefficient 1), so the score of the Sustainability criterion is 4 x 1 = 4 points.
+ Location and accessibility are determined to be quite favorable (2 points), the coefficient is quite important (coefficient 2), the criterion score is 2 x 2 = 4 points.
+ Infrastructure is rated as average (2 points), the coefficient is quite important (coefficient 2), then the score of the Infrastructure criterion is 2 x 2 = 4 points.
The total score for evaluating DLST in Quan Lan commune according to 6 evaluation criteria is determined as: 12 + 6 + 6 + 4 + 4 + 4 = 36 points.
Similar assessment with Minh Chau commune we have the following table:
Table 3.4: Assessment of the potential for developing humanistic eco-tourism in Quan Lan and Minh Chau communes
Attractiveness of human tourismliterature
Capacity
Mining time
Sustainability
Location and accessibility
Infrastructure
Result
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Point
DarkMulti
Quan CommuneLan
12
12
6
8
9
12
4
4
4
8
4
8
39/52
Minh CommuneChau
6
12
4
8
12
12
4
4
4
8
6
8
36/52
Basically, both Minh Chau and Quan Lan localities have quite favorable conditions for developing ecotourism. However, Quan Lan commune has more advantages to develop ecotourism in a humanistic direction, because this is an area with many famous historical relics such as Quan Lan Communal House, Quan Lan Pagoda, Temple worshiping the hero Tran Khanh Du, ... along with local festivals held annually such as the wind praying ceremony (March 15), Quan Lan festival (June 10-19); due to its location near the port and long exploitation time, the beaches in Quan Lan commune (especially Quan Lan beach) are no longer hygienic and clean to ensure the needs of tourists coming to relax and swim; this is also an area with many beautiful landscapes such as Got Beo wind pass, Ong Phong head, Voi Voi cave, but the ability to access these places is still very limited (dirt hill road, lots of gravel and rocks), especially during rainy and windy times; In addition, other natural resources such as mangrove forests and sea worms have not been really exploited for tourism purposes and ecotourism development. On the contrary, Minh Chau commune has more advantages in developing ecotourism in the direction of natural tourism, this is an area with diverse ecosystems such as at Rua De Beach, Bai Tu Long National Park Conservation Center...; Minh Chau beach is highly appreciated for its natural beauty and cleanliness, ranked in the top ten most beautiful beaches in Vietnam; Minh Chau commune is also home to Tram forest with a large area and a purity of up to 90%, suitable for building bridges through the forest (a very effective type of natural ecotourism currently applied by many countries) for tourists to sightsee, as well as for the purpose of studying and researching.
Figure 3.1: Thenmala Forest Bridge (India) Source: https://www.thenmalaecotourism.com/(August 21, 2019)
3.2.2. Using SWOT matrix to evaluate Quan Lan island tourism
General assessment of current tourism activities of Quan Lan island is shown through the following SWOT matrix:
Table 3.5: SWOT matrix evaluating tourism activities on Quan Lan island
Internal agent
Strengths- There is a lot of potential for tourism development, especially natural ecotourism and humanistic ecotourism.- The unskilled labor force is relatively abundant.- resource environmentunpolluted, still
Weaknesses- Poorly developed infrastructure, especially traffic routes to tourist destinations on the island.- The team of professional staff is still weak.- Tourism products in general
quite wild, originalintact
general and DLST in particularalone is monotonous.
External agents
Opportunity- Tourism is a key industry in the socio-economic development strategy of the province and Van Don economic zone.- Quan Lan was selected as a pilot area for eco-tourism development within the framework of the green growth project between Quang Ninh province and the Japanese organization JICA.- The flow of tourists and especially ecotourism in the world tends toincreasing
Challenge- Weather and climate change abnormally.- Competition in tourism products is increasingly fierce, especially with other localities in the province such as Ha Long, Mong Cai...- Awareness of tourists, especially domestic tourists, about ecotourism and nature conservation is not high.
Through summary analysis using SWOT matrix we see that:
To exploit strengths and take advantage of opportunities, it is necessary to:
- Diversify products and service types (build more tourism routes aimed at specific needs of tourists: experiential tourism immersed in nature, spiritual cultural tourism...)
- Effective exploitation of resources and differentiated products (natural resources and human resources)
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Group of Indicators Reflecting Factors Affecting Agribank's Agricultural Lending -
Determining Weights for the Group of Indicators on Natural Resources and Environment -
Calculating Indicators Reflecting the Level of Credit Expansion for State-owned Enterprises at VP Bank Giang Vo.
The changes in both quality and quantity of all economic activities worldwide require national accounting to continue to change to suit the socio-economic development situation. The United Nations Statistics Division has conducted research, updated, supplemented and the SNA 2008 version is the most recent version that has been published and applied uniformly worldwide.
SNA is a statistical system that serves the need to comprehensively analyze all economic activities in an economy at the macro level. It is an advanced socio-economic information system applied in most countries in the world. SNA includes a system of accounts and statistical tables with closely linked relationships to describe and analyze basic economic phenomena from production, consumption to asset accumulation of the economy. SNA also reflects the process of generating income from production; distributing income among production factors; using income for final consumption and transferring income between sectors in the economy and the outside. SNA includes a set of appropriate and flexible macroeconomic accounts, built on the

internationally recognized concepts, definitions, and accounting rules.
On that basis, SNA reflects the economic structure, development trends in terms of level and efficiency of total production, reflects the relationships between sectors, important coefficients of the country's social reproduction process in each specific period such as: Between production and final consumption, production and asset accumulation, between domestic and foreign production, ...
The system of national accounts is considered the most comprehensive economic picture describing the production, distribution, exchange and use of products of a country in a certain period. Therefore, SNA is a general model of the economy applied in economic analysis, analysis of the impact of policies on production and business results, planning and economic forecasting at the macro level.
According to SNA, economic growth is the increase in quantity of indicators reflecting the results of production activities of the entire economy in a certain period, often reflected by an increase in GDP. The thesis applies the theory of economic growth according to the SNA methodology to serve statistical research to evaluate the overall impact of tourism activities on economic growth in Vietnam.
1.2.2. Method of determining some indicators reflecting economic growth
Currently, most countries in the world calculate and announce economic growth according to the increase in the quantity of GDP. GDP growth is expressed in relative numbers called GDP growth rate. To calculate GDP and GDP growth rate, it is necessary to determine and calculate the following indicators: GO, intermediate costs (IC), VA. In SNA, these are the basic indicators calculated for each industry and for the entire economy.
According to the method of determining some indicators reflecting economic growth of SNA2008 mentioned in the scientific research topic "Research to complete and computerize the Process of synthesizing indicators of production value and added value applied to the Central and local levels" by author Nguyen Thi Huong (2012), this subsection selects, presents the concept and method of calculating the indicators GO, IC and VA as follows:
1.2.2.1. Concept and method of calculating production value index
a. Concept
Production value is the total value of material products and services produced by
Production establishments of all economic sectors create in a certain period (quarter or year). GO is only calculated for products produced by production establishments for other units, not for products circulated internally in production stages at production establishments of the unit (except for the agricultural sector). Revenue from price differences is not included in GO, but production subsidies are included in GO. The double counting of GO depends on the level of production specialization and the level of detail of the economic sub-sector.
Production value is calculated at basic prices and producer prices (abbreviated as production prices ).
The basic price is the amount a producer receives from a buyer for selling a unit of a physical product or service produced, minus any product taxes and plus any production subsidies received by the producer. The basic price does not include transportation costs, which are invoiced separately by the producer.
The basic price does not include any taxes on the product, which the producer receives from the buyer and pays to the government. The basic price includes production subsidies (product subsidies and other production subsidies) that the producer receives from the government to lower the selling price to the buyer.
The base price measures the amount of money the producer receives, so it is the closest price relevant to the producer's decisions.
The production price is the amount received by the producer for selling a unit of the physical product or service produced minus the deductible value added tax (VAT) paid by the buyer. The production price does not include transportation costs, which the producer records separately on the invoice.
Neither the manufacturer's price nor the basic price includes VAT, or similar tax, on the goods sold.
Unlike the basic price, the producer price includes product taxes other than VAT and excludes product subsidies (subsidies received per unit of output). (The producer price is the price excluding VAT that the buyer must pay.)
The relationship between GO at producer price and at basic price is expressed by the following formula :
GO at production cost
GO by price
= +
basic
Product tax
-
(excluding VAT)
Product allowance
The GO calculation method is built in accordance with the economic characteristics, production techniques and production activities of each economic sector. Below is the GO calculation method based on basic prices that is mainly applied in most countries in the world.
b. Calculation method
The method of calculating GO at basic prices is suitable for the main industry groups in the economy including:
b1. Calculate directly from product output
The GO of the agricultural and mining industries is calculated directly from product output as follows:






In there:
- GO: Is production value
- Q i : Is the output of product i
- P i: Is the average unit production price of product i (here, the unit price does not include product tax but includes production subsidy)
- n: Is the number of products
- i: Is the i-th product
b2. Calculated from sales revenue
Industries that easily collect information on sales revenue include processing and manufacturing industries and service industries (except wholesale and retail; banking and insurance activities; real estate business activities). GO is calculated from revenue as follows:
GO at base price
Net revenue
= sales and supply
service level
Subsidy
+ production
(if any)
End-of-period minus beginning-of-period difference
+ finished goods inventory, goods on consignment, unfinished products
Here net sales and service revenue does not include product tax.
b3. Method of calculating from sales
This calculation applies to wholesale and retail; real estate business activities.
movables.
GO base price =
Sales revenue
Cost of goods sold
-
transfer sale
Production allowance
+
Product (if any)
Here sales revenue does not include product tax.
b4. Method of calculating from production cost factors
GO at base price
Total cost
=
manufacture
Operating profit
+
business
This is a calculation method that applies to most industries. However, to apply this calculation method, it is necessary to have information about the costs of production and business activities and profits.
b5. Separate calculation method for specific production and business activities: activities
banking and insurance
+ For banking activities
GO at base price
In there:
GO underground service translation
GO translate
= +
undercover
Ownership income
= -
receivable
GO straight service
Total interest payable
The value of productionO straight service equals the straight service fee.
+ For insurance activities
GO basic price
Fee
=
insurance
Compensation
+ -
insurance
Attend
+
room fee
Income
invest
1.2.2.2. Concept and method of calculating added value index
a. Concept
Value added (VA) is the new value of goods and services created from the production process in an economic sector.
b. Calculation method
General formula for calculating VA according to production method:
VA = GO – IC
Intermediate costs (IC) are a component of GO, including all costs of material products and services for production that are accounted for in product cost. IC must be the result of production produced by industries or imported from abroad. IC is always calculated at the usage price, meaning it includes transportation costs and other types of costs.
Other costs paid by the manufacturing unit to bring raw materials, fuels, etc. into production. IC includes material costs and service costs:
- Material costs include: Main and auxiliary raw materials; fuel, gas; costs of small production tools, cheap and perishable materials; costs of other material products.
- Service costs include: Transportation; post; insurance; banking services; legal services; advertising services; other service costs.
In theory, the IC index is calculated by summing all the input costs for the above production. However, in practice, this index is usually estimated by multiplying (x) GO by the IC coefficient compared to GO of the survey year.
IC is always charged at usage price.
GO is calculated at basic price or production price. The price at which GO is calculated is the price at which VA is calculated.
Value added at basic prices is calculated as GO at basic prices minus (-) intermediate consumption at user prices.
VA at basic prices, including: All types of subsidies (product subsidies and other production subsidies) but excluding all types of product taxes.
The components of VA at basic price include:
(1) Employees' income includes salaries, wages (including in-kind payments); social insurance, health insurance, union fees and other support expenses for employees included in production costs (excluding amounts from funds set aside after the unit's production results).
(2) Other production taxes are taxes levied on the production process of production and business units . Other production taxes include: Business license tax, environmental tax, resource tax, etc. and fees considered as taxes (registration fees, fees related to production and business, etc.).
(3) Fixed asset depreciation is the amount of fixed asset depreciation (TSCD)
at the unit allocated to production and business costs.
(4) Surplus Value or Mixed Income
(4.1) Surplus value includes net income from business activities, interest paid on bank loans, and property insurance expenses.
(4.2) Mixed income only appears in the case of individual business households.
because in practice it is difficult to separate the wages and salaries of the household head and the household workers from the surplus value.
VA is also calculated using the income method by directly adding the above components.
1.2.2.3. Concept and method of calculating gross domestic product index
a. Concept
Gross domestic product (GDP) is a synthetic economic indicator reflecting the new value of goods and services created by the entire economy in a certain period of time (month, quarter, 6 months, 9 months, year).
GDP is always measured at consumer prices.
b. Calculation method
GDP is calculated using three methods: the production method, the income method, and the expenditure method.
According to the production method , GDP is calculated from the sum of VA at basic prices of all economic sectors as follows:
GDP =
Total VA according to
base price +
All types
-
product tax
All types of product subsidies
Here product taxes and product subsidies include both import duties and import subsidies.
According to the income method : GDP is equal to the total income generated from factors participating in the production process such as: Labor, capital, land, machinery. According to this method, GDP includes 4 factors: Income of workers from production (in cash and in kind), production tax (after deducting product subsidies), depreciation of fixed assets used in production and production surplus or mixed income. The formula for calculating GDP is as follows:
GDP =
Workers' income
verb +
manufacture
Production tax
(minus product allowance)
Fixed Asset Depreciation
used in production
Surplus or
+
income
mixed
According to the method used : GDP is the sum of 3 factors: Final consumption of households and the state; accumulation of assets (fixed, current and rare) and the difference between export and import of goods and services. The formula for calculating GDP is as follows:
GDP =
Consumption
+
Final
Accumulate assets
Import-export difference
+
export of goods and services
1.2.2.4. Concept and method of calculating growth rate of gross domestic product
a. Concept
GDP growth rate is the percentage increase in GDP in the following period compared to the previous period. GDP growth rate is usually calculated from GDP at comparable prices (base year prices) of the reporting year compared to the year before the reporting year.
Nowadays, when referring to economic growth rate, it is often associated with GDP growth rate and some related synthetic economic indicators.
b. Calculation method
- The GDP growth rate of the reporting year compared to the previous year is calculated at comparable prices (base year prices) according to the following formula:
In there:
dGDP =
GDP n GDP n-1
x 100 - 100
d GDP - GDP growth rate of the reporting year compared to the year before the reporting year (%) GDP n - Gross domestic product of the reporting year at comparable prices;
GDP n-1 - Gross domestic product of the year prior to the reporting year at constant prices;
GDP n
n
GDP 0
- Calculate the average GDP growth rate over time (many years). Formula for calculating the average GDP growth rate over time:
In there:
dGDP (
1) x 100
d GDP - Average GDP growth rate over the period from the base year to year n;
GDP n - Gross domestic product at constant prices of the last year (year n) of

![Mobile Phone Usage in Hanoi Inner City Area
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- Test the relationship between demographic variables and consumer behavior for Mobile Marketing activities
The analysis method used is the Chi-square test (χ2), with statistical hypotheses H0 and H1 and significance level α = 0.05. In case the P index (p-value) or Sig. index in SPSS has a value less than or equal to the significance level α, the hypothesis H0 is rejected and vice versa. With this testing procedure, the study can evaluate the difference in behavioral trends between demographic groups.
CHAPTER 4
RESEARCH RESULTS
During two months, 1,100 survey questionnaires were distributed to mobile phone users in the inner city of Hanoi using various methods such as direct interviews, sending via email or using questionnaires designed on the Internet. At the end of the survey, after checking and eliminating erroneous questionnaires, the study collected 858 complete questionnaires, equivalent to a rate of about 78%. In addition, the research subjects of the thesis are only people who are using mobile phones, so people who do not use mobile phones are not within the scope of the thesis, therefore, the questionnaires with the option of not using mobile phones were excluded from the scope of analysis. The number of suitable survey questionnaires included in the statistical analysis was 835.
4.1 Demographic characteristics of the sample
The structure of the survey sample is divided and statistically analyzed according to criteria such as gender, age, occupation, education level and personal income. (Detailed statistical table in Appendix 6)
- Gender structure: Of the 835 completed questionnaires, 49.8% of respondents were male, equivalent to 416 people, and 50.2% were female, equivalent to 419 people. The survey results of the study are completely consistent with the gender ratio in the population structure of Vietnam in general and Hanoi in particular (Male/Female: 49/51).
- Age structure: 36.6% of respondents are <23 years old, equivalent to 306 people. People from 23-34 years old
accounting for the highest proportion: 44.8% equivalent to 374 people, people aged 35-45 and >45 are 70 and 85 people equivalent to 8.4% and 10.2% respectively. Looking at the results of this survey, we can see that the young people - youth account for a large proportion of the total number of people participating in the survey. Meanwhile, the middle-aged people including two age groups of 35 - 45 and >45 have a low rate of participation in the survey. This is completely consistent with the reality when Mobile Marketing is identified as a Marketing service aimed at young people (people under 35 years old).
- Structure by educational level: among 835 valid responses, 541 respondents had university degrees, accounting for the highest proportion of ~ 75%, 102 had secondary school degrees, ~ 13.1%, and 93 had post-graduate degrees, ~ 11.9%.
- Occupational structure: office workers and civil servants are the group with the highest rate of participation with 39.4%, followed by students with 36.6%. Self-employed people account for 12%, retired housewives are 7.8% and other occupational groups account for 4.2%. The survey results show that the student group has the same rate as the group aged <23 at 36.6%. This shows the accuracy of the survey data. In addition, the survey results distributed by occupational criteria have a rate almost similar to the sample division rate in chapter 3. Therefore, it can be concluded that the survey data is suitable for use in analysis activities.
- Income structure: the group with income from 3 to 5 million has the highest rate with 39% of the total number of respondents. This is consistent with the income structure of Hanoi people and corresponds to the average income of the group of civil servants and office workers. Those
People with no income account for 23%, income under 3 million VND accounts for 13% and income over 5 million VND accounts for 25%.
4.2 Mobile phone usage in Hanoi inner city area
According to the survey results, most respondents said they had used the phone for more than 1 year, specifically: 68.4% used mobile phones from 4 to 10 years, 23.2% used from 1 to 3 years, 7.8% used for more than 10 years. Those who used mobile phones for less than 1 year accounted for only a very small proportion of ~ 0.6%. (Table 4.1)
Table 4.1: Time spent using mobile phones
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Alid
<1 year
5
.6
.6
.6
1-3 years
194
23.2
23.2
23.8
4-10 years
571
68.4
68.4
92.2
>10 years
65
7.8
7.8
100.0
Total
835
100.0
100.0
The survey indexes on the time of using mobile phones of consumers in the inner city of Hanoi are very impressive for a developing country like Vietnam and also prove that Vietnamese consumers have a lot of experience using this high-tech device. Moreover, with the majority of consumers surveyed having a relatively long time of use (4-10 years), it partly proves that mobile phones have become an important and essential item in peoples daily lives.
When asked about the mobile phone network they are using, 31% of respondents said they are using the network of Vietel company, 29% use the network of
of Mobifone company, 27% use Vinaphone companys network and 13% use networks of other providers such as E-VN telecom, S-fone, Beeline, Vietnammobile. (Figure 4.1).
Figure 4.1: Mobile phone network in use
Compared with the announced market share of mobile telecommunications service providers in Vietnam (Vietel: 36%, Mobifone: 29%, Vinaphone: 28%, the remaining networks: 7%), we see that the survey results do not have many differences. However, the statistics show that there is a difference in the market share of other networks because the Hanoi market is one of the two main markets of small networks, so their market share in this area will certainly be higher than that of the whole country.
According to a report by NielsenMobile (2009) [8], the number of prepaid mobile phone subscribers in Hanoi accounts for 95% of the total number of subscribers, however, the results of this survey show that the percentage of prepaid subscribers has decreased by more than 20%, only at 70.8%. On the contrary, the number of postpaid subscribers tends to increase from 5% in 2009 to 19.2%. Those who are simultaneously using both types of subscriptions account for 10%. (Table 4.2).
Table 4.2: Types of mobile phone subscribers
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Prepay
591
70.8
70.8
70.8
Pay later
160
19.2
19.2
89.9
Both of the above
84
10.1
10.1
100.0
Total
835
100.0
100.0
The above figures show the change in the psychology and consumption habits of Vietnamese consumers towards mobile telecommunications services, when the use of prepaid subscriptions and junk SIMs is replaced by the use of two types of subscriptions for different purposes and needs or switching to postpaid subscriptions to enjoy better customer care services.
In addition, the majority of respondents have an average spending level for mobile phone services from 100 to 300 thousand VND (406 ~ 48.6% of total respondents). The high spending level (> 500 thousand VND) is the spending level with the lowest number of people with only 8.4%, on the contrary, the low spending level (under 100 thousand VND) accounts for the second highest proportion among the groups of respondents with 25.4%. People with low spending levels mainly fall into the group of students and retirees/housewives - those who have little need to use or mainly use promotional SIM cards. (Table 4.3).
Table 4.3: Spending on mobile phone charges
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<100,000
212
25.4
25.4
25.4
100-300,000
406
48.6
48.6
74.0
300,000-500,000
147
17.6
17.6
91.6
>500,000
70
8.4
8.4
100.0
Total
835
100.0
100.0
The statistics in Table 4.3 are similar to the percentages in the NielsenMobile survey results (2009) with 73% of mobile phone users having medium spending levels and only 13% having high spending levels.
The survey results also showed that up to 31% ~ nearly one-third of respondents said they sent more than 10 SMS messages/day, meaning that on average they sent 1 SMS message for every working hour. Those with an average SMS message volume (from 3 to 10 messages/day) accounted for 51.1% and those with a low SMS message volume (less than 3 messages/day) accounted for 17%. (Table 4.4)
Table 4.4: Number of SMS messages sent per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
142
17.0
17.0
17.0
3-10 news
427
51.1
51.1
68.1
>10 news
266
31.9
31.9
100.0
Total
835
100.0
100.0
Similar to sending messages, those with an average message receiving rate (from 3-10 messages/day) accounted for the highest percentage of ~ 55%, followed by those with a high number of messages (over 10 messages/day) ~ 24% and those with a low number of messages received daily (under 3 messages/day) remained at the bottom with 21%. (Table 4.5)
Table 4.5: Number of SMS messages received per day
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
<3 news
175
21.0
21.0
21.0
3-10 news
436
55.0
55.0
76.0
>10 news
197
24.0
24.0
100.0
Total
835
100.0
100.0
When comparing the data of the two result tables 4.4 and 4.5, we can see the reasonableness between the ratio of the number of messages sent and the number of messages received daily by the interview participants.
4.3 Current status of SMS advertising and Mobile Marketing
According to the interview results, in the 3 months from the time of the survey and before, 94% of respondents, equivalent to 785 people, said they received advertising messages, while only a very small percentage of 6% (only 50 people) did not receive advertising messages (Table 4.6).
Table 4.6: Percentage of people receiving advertising messages in the last 3 months
Frequency
Ratio (%)
Valid Percentage
Cumulative Percentage
Valid
Have
785
94.0
94.0
94.0
Are not
50
6.0
6.0
100.0
Total
835
100.0
100.0
The results of Table 4.6 show that consumers in the inner city of Hanoi are very familiar with advertising messages. This result is also the basis for assessing the knowledge, experience and understanding of the respondents in the interview. This is also one of the important factors determining the accuracy of the survey results.
In addition, most respondents said they had received promotional messages, but only 24% of them had ever taken the action of registering to receive promotional messages, while 76% of the remaining respondents did not register to receive promotional messages but still received promotional messages every day. This is the first sign indicating the weaknesses and shortcomings of lax management of this activity in Vietnam. (Table 4.7)
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