+----------+----------+
+--------------------------------------------+
| Fit Measures for Binomial Choice Model |
| Logit model for variable Y |
+--------------------------------------------+
| Proportions P0= .341193 P1= .658807 |
| N = 721 N0= 246 N1= 475 |
| LogL = -92.82782 LogL0 = -462.7547 |
| Estrella = 1-(L/L0)^(-2L0/n) = .87282 |
+--------------------------------------------+
| Efron | McFadden | Ben./Lerman |
| .83759 | .79940 | .92626 |
| Cramer | Veall/Zim. | Rsqrd_ML |
| .83598 | .90100 | .64162 |
+--------------------------------------------+
| Information Akaike IC Schwarz IC |
| Criteria .28801 258.04268 |
+--------------------------------------------+
Frequencies of actual & predicted outcomes Predicted outcome has maximum probability. Threshold value for prediction Y=1 = .5000
Predicted
---------------- | + | ----- | |
Actual | 0 1 | | | Total |
------ | ---------- | + | ----- |
0 | 226 20 | | | 246 |
1 | 16 459 | | | 475 |
------ | ---------- | + | ----- |
Total | 242 479 | | | 721 |
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Mobile Phone Usage in Hanoi Inner City Area
zt2i3t4l5ee
zt2a3gsconsumer,consumption,consumer behavior,marketing,mobile marketing
zt2a3ge
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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Building a system to monitor water level, temperature and send warnings via SMS/GSM network - 2 -
Theoretical Research Method: Collecting Documents Related to the Thesis, Analyzing, Synthesizing to Build a Theoretical Framework -
Principles for Perfecting the FDI Economic Efficiency Indicator System in Vietnam

================================================================ =====================
Analysis of Binary Choice Model Predictions Based on Threshold = .5000
-------------------------------------------------- ---------------------
Prediction Success
-------------------------------------------------- ---------------------
Sensitivity = actual 1s correctly predicted 96.632%
Specificity = actual 0s correctly predicted 91.870% Positive predictive value = predicted 1s that were actual 1s 95.825% Negative predictive value = predicted 0s that were actual 0s 93.388% Correct prediction = actual 1s and 0s correctly predicted 95.007%
-------------------------------------------------- ---------------------
Prediction Failure
-------------------------------------------------- ---------------------
False pos. for true negation. = actual 0s predicted as 1s8.130% | |
False neg. for true pos. = actual 1s predicted as 0s | 3.368% |
False pos. for predicted pos. = predicted 1s actual 0s | 4.175% |
False neg. for predicted neg. = predicted 0s actual 1s | 6.612% |
False predictions = actual 1s and 0s incorrectly predicted | 4.993% |
================================================================ =====================
Appendix 3a: METHODS AND SYSTEM OF INDICATORS FOR ASSESSING ECOTOURISM POTENTIAL
------------------
Assessing tourism potential is a process of examining resources according to certain criteria to serve tourism purposes. Assessing ecotourism potential is a direction in assessing tourism potential. Previously, tourism potential assessment was often used as "technical assessment" or also known as: "favorability assessment" or "comprehensive assessment" (Nguyen Thi Hai, 2002 [11]. With the development of information technology tools, today in many studies on the assessment of ecotourism resources, people apply econometrics in the assessment. In particular, for ecotourism, people also apply the Zonal travel cost zonal method (ZTCM). However, this method is only suitable for assessing each resource point such as national parks, beaches, etc., where ecotourism activities have developed. However, to assess an area consisting of many resource points, or resource points that have not yet developed ecotourism activities, this method is not suitable, because it does not determine the starting area of tourists and cannot accurately separate the travel costs of tourists by region.
From the reality of VDLTB, after reviewing the current status of resources, many resource points in key areas are in the potential aspect. Therefore, in this thesis we apply the "comprehensive assessment" method to evaluate the value of resources for exploitation and development of ecotourism activities. The method is most commonly used today.
Evaluation steps
The steps are carried out in the comprehensive evaluation model according to diagram 1. In current research and practice, to evaluate the attractiveness of natural potentials, people use the scoring method according to each characteristic criterion. The evaluation "first needs to determine the scale for evaluation. The number of levels can have many or few types, depending on the level of necessity of the evaluation" . The evaluation usually has to be determined by a panel of judges" (Nguyen Van Hoa, 2006b) [20, 46].
The scoring method used in the topic is to determine the potential for ecotourism. Specifically , it is considered according to two criteria: the ability to attract and the ability to exploit each resource . We have collected the opinions of 16 experts with deep expertise and experience in the field of ecotourism at VDLTB. In addition , we also consulted the opinions of other experts to get more information for the experts to score ( see appendix 13a, 13b, 16a, 16b) . This method is conducted based on a criterion built in accordance with the reality of the research area in the current period . In order to build the scoring scale and criteria to be accurate and highly convincing , in addition to referring to some assessments
Regarding the potential of DLST of some studies, we have sought comments from some
Step 6: Review and rate the assessment results.
Step 2: Select evaluation factors
Step 3: Determine the levels of each factor
Step 4: Determine the score of each level & coefficients of factors
Step 5: Score each factor
Step 1: Build a rating scale
Overall rating
Evaluate each component
expert (see appendix 16a).
Figure 1: Comprehensive assessment model
This method has also been applied to evaluate in some localities in the region such as Thua Thien Hue... However, in this section, although the method is the same, through reviewing the studies , we have proposed a standard system with some different points for evaluation.
General assessment and ranking
* Calculate total score
After calculating the factors' scores, the total score is calculated as follows:
- Calculate the total score of the evaluation factors
n
F=
i=1
Mi*Xi
(1)
- Calculate the score of the factors :
n
F = M i X i i 1
(2)
In which: Mi: is the multiplier; Xi: Evaluation index; i= 1 n ; n: number of elements
In current research, people use both scoring methods. The scoring method will have advantages when the resource is still too wild or located in a sensitive area such as: located in a defense area... so that resource is attractive to
cannot be exploited for DLST anywhere. In this thesis we use the calculation method
total score because the resources considered have all been put in place for the development of ecotourism.
*Resource Point Classification
After the overall assessment, the ratio of the total or sum of the assessment scores to the maximum possible score is compared to classify. This is a fairly common method used in current research.
Second way: Apply Avasian's formula (1988). Distance between levels
can be calculated by
S = S max - S min
1+LogH (1)
S max: Maximum suction value ; S min: Minimum suction value ;
H: Number of points selected for evaluation
Or use the formula c Armand (1975) to calculate the rating number
S =
B: is the rating term
S max - S min
B (2)
In addition, in some studies, people can classify as follows: Type 1: resources with 70% or more points; Type 2: Resources with 50% to less than 70% points, Type 3: less than 50% points. In the thesis, we use formula (2) to classify resources. In order to see more clearly the tourism potential of resources, the thesis also combines the assessment of attraction and exploitation ability. In some previous studies, people also combined the calculation of the total score or the accumulation of the scores of these two criteria, then classified resources into type I, type II, type III. However, many experts do not agree with this method because these two criteria are not identical. Therefore, the thesis uses an analytical method to combine these two criteria.
1.1. Evaluation of the ability to attract customers
Built for 4 main criteria: Attractiveness; safety ; connectivity ; quality of infrastructure and technical facilities for tourism.
- The attractiveness of natural tourism resources to tourists is the beauty and uniqueness of natural landscapes, the diversity of terrain, geomorphology, biodiversity, the suitability of climate for human health, the unique and original nature of relics, indigenous culture and natural phenomena.
- Safety is determined by political security, social order, and environmental sanitation.
- Connectivity is determined by the number of tourist attractions and the distance between tourist attractions in a certain space and the level of convenience for linking tourist attractions into tourist routes or clusters.
- Tourism infrastructure and technical facilities are determined by the convenience and synchronization of the transportation network, communications, electricity, water, facilities serving the needs of food, accommodation, entertainment and other support conditions... for tourists.
Each of the above criteria is evaluated according to 4 levels of scores: 4, 3, 2, 1 corresponding to the evaluation level from high to low (good, fair, average and poor) . The scoring criteria for each criterion are evaluated as follows:
a. Attractiveness
+ Very attractive (4 points): At least 5 beautiful landscapes, diverse terrain, unique and well-preserved ecosystems, able to organize at least 5 types of tourism, including at least one typical type. Great resources.
+ Quite attractive (3 points): There are 3 beautiful landscapes, a relatively diverse ecosystem in a well-preserved state, and 4 types of tourism can be organized. The resources are quite large.
+ Average (2 points): Has 1-2 beautiful landscapes, moderate biodiversity
Yes , can meet 1-2 types of tourism .
+ Poor (1 point ): Monotonous landscape , rich and diverse ecosystem, atypical , can only organize 1 type of tourism.
b. Safety (ecological and social)
- Very safe (4 points): No cases of instability in security, ecology and natural disasters; no terrorism , harassment, theft, robbery, kidnapping, street vending , begging, no epidemics.
- Quite safe (3 points): Has the above characteristics, however, there are only occasional harassment, begging, and street vending.
- Average (2 points): No robbery, extortion, terrorism,
kidnapping, natural disasters, epidemics, however, begging and street vending activities are still active.
- Poor (1 point): There is robbery , kidnapping, epidemic, threat to life.
human life , infringe on the property of tourists.
c. Connectivity
- Very good (4 points): There are at least 4 additional tourist resource points (including natural and human) located near the considered point within a radius of no more than 25 km, and 30 km for islands.
- Good (3 points ): There are 2 - 3 more tourist resource points within the area .
The point of consideration is not more than 25 km, except for islands, it is 30 km.
- Average (2 points): There is only 1 additional tourist resource point within 25 km.
- Poor (1 point ): There are no other linked tourism resource points within a 25 km radius of the considered point.
d. Tourism infrastructure and technical facilities
- Very good (4 points): Tourism infrastructure and technical facilities are synchronous and fully equipped; convenient access by road, river... with all types of accommodation, food and beverage facilities and services that meet standards, and sufficient additional services.
- Good (3 points): Tourism infrastructure and technical facilities are synchronous and convenient.
convenient access, with full range of accommodation , dining and entertainment services.
- Average (2 points): Infrastructure and technical facilities are not yet synchronized.
( lacking some elements such as: electricity supply, water supply and drainage, communication and some services ...).
- Poor (1 point): Tourism infrastructure and technical facilities are in poor condition or
low quality or lacking in many, difficult to get to those points, time consuming.
The above criteria have different levels of impact on tourist attraction. Therefore, to have an accurate overall assessment, it is necessary to determine the multiplier for each criterion according to its level of impact. Based on the overall score after multiplying the coefficient, tourism resource points will be divided into 3 types as follows :
- Type with high tourist attraction: Tourist resource points in the group
This has the potential to attract both international and domestic visitors.
- Medium attractiveness: Tourist resources in this group are currently capable of attracting mainly domestic visitors. To attract international visitors, there must be a larger investment.
- Low attraction type: Tourist resource spots in this group only have
ability to attract local customers.
1.2. Assessment of the ability to exploit ecotourism resources
In addition to the criteria of attractiveness, safety, connectivity, and tourism infrastructure, people also use three other criteria: seasonality, sustainability, and tourist capacity of each resource point.
- Seasonality is determined by the number of suitable days in the year for organizing tourism activities, welcoming and serving the needs of tourists. The seasonality of resources is affected by many factors, including the number of types of organizations.
- Sustainability is the ability to preserve and maintain natural components and parts under pressure from tourism activities and natural phenomena.
- Tourist capacity is the total maximum capacity of tourists at one time.
certain points in a day of a tourist resource site. The above criteria are also evaluated according to 4 points: 4, 3, 2, 1.
a. Seasonality
- Very long (4 points): Can organize tourism activities for more than 270 days/year.
- Quite long (3 points): Can organize tourism activities from 180 days to less
270 days/year.
- Average (2 points): Can organize tourism activities from 120 days to less than 180 days/year.
- Poor (1 point): Can organize tourism activities less than 120 days/year.
b. Sustainability
+ Very sustainable (4 points): The resource is in its original form with no natural components or parts destroyed, the ecological recovery ability of the environment is fast, and it exists firmly for over 100 years.
+ Quite sustainable (3 points): 1-2 natural components are damaged but not significantly, have the ability to recover quickly, and exist firmly for 50-100 years.
+ Average (2 points): There are 1-2 natural components that are damaged at a significant level.
It costs too much to restore and can last from 10 to 50 years.
+ Poor (1 point ): 2-3 natural components or parts are damaged at a significant level.
It costs too much to restore but is slow and will last less than 10 years.
c. Tourist capacity
+ Very large (4 points): Able to safely receive and accommodate (both visitors and natural resources) at least 250 people /visit.
+ Quite large (3 points): from 150 to 249 people/visit.
+ Average (2 points): from 50 to 149 people/visit.
+ 1 point less: under 50 people/tour.
The overall assessment score after processing the expert's dissenting opinions and being
Multiply the coefficient to determine the importance of the criteria for tourism activities.
Based on the total score of the criteria, the ability to exploit tourism resources is divided into 3 types as follows:
Type 1 : This type of tourism resourcehas many advantages in terms of exploitation potential.
serving both international and domestic guests .
Type 2 : This type has advantages at medium exploitation level. Usually requires investment projects.
with a large capital to organize to serve tourists.
Type 3: This type is not advantageous in terms of exploitation, so it is very difficult to exploit.
Organizing tourism activities. Usually this type requires a very large investment to exploit .
serve tourists
Appendix 3b: SUMMARY OF POTENTIAL ASSESSMENT CRITERIA






ECO TOURISM
A. ABILITY TO ATTRACTION
1. Attractiveness (HD) | Very attractive | Quite attractive | Medium | Least |
- Minimal photo style | 0 5 | 03 | 1 – 2 | 1 |
- Diversity of ecosystems | Unique, diverse | Diversity | TB | Least |
form | ||||
- Types of events that can be organized | At least 5 types | 04 types | 1- 2 | 1 |
2. Safety (AT) | Very safe | Quite safe | Medium | Least |
- Ecologically safe | Very good | Very good | Very good | - |
- Social evils | Do not have | - | - | - |
+ Begging, street vending | Do not have | Not often | Work | Work |
through | strong | strong | ||
+ Theft, robbery | Do not have | Do not have | Do not have | Have |
- Disease, pollution | Do not have | Do not have | Do not have | Do not have |
3. Connectivity (LK) | Very good | Rather | Medium | Least |
Number of neighboring TN points | At least 04 | 2 - 3 | 1 - 2 | 0 |
4. Infrastructure & Technical Facilities | Very good | Rather | Medium | Least |
- Synchronization | Very synchronized | Synchronize | Not synchronized | Least |
- Convenience | Enough | Enough | Missing some | Least |
- Accessibility | Favorable | Favorable | Relative | Hard |
B. EXPLOITATION ABILITY | ||||
1. Seasonality (TV) | very long | Quite long | Medium | Least |
Number of days available | Over 250 | 180 - 250 | 100 – 180 | Less than 100 |
2. Sustainability (BV) | High durability | Quite durable | Medium | Least |
- TN part was damaged | Protoplasm | 1 - 2 | 1-2, significant | 2 - 3 |
- Recovery ability | Fast | Fast | Slow | very slow |
- Viability | Over 100 years | 5- 100 years | 10 - 50 n | 10 years |
3. Capacity (CPI) | Very large | Sizable | Medium | Least |
Time Containment | over 250 people | 150 - 249 people | 5- 149 people | Less than 50 |
Big | Quite big | Medium | Th | |







(Source : author's synthesis )

![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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