Analysis of Factors Affecting the Development of Ecotourism in Phong Dien District

Bicycles were the least chosen means of transport, with 26 people choosing this means of transport, accounting for 14.69%. There was 1 respondent choosing another means of transport, accounting for 0.56%.

b. Accompanying person

16,384

Go alone

Go on tour

19,209

22,034

Rate (%)

Frequency

Family, relatives

42,373

Friends, colleagues

Figure 4.5 People accompanying tourists

(Source: Results of 2016 survey data processing)

Of the 177 respondents, 75 people came to visit with friends and colleagues, accounting for 42.37%. There were 39 respondents who went with family and relatives, accounting for 22.03%. The number of people who went on tours also accounted for a relatively large proportion of 19.21%, with 34 people choosing this form. There were 29 respondents who went alone, accounting for 16.38%. Thus, the majority of tourists visiting tourist areas in Phong Dien district chose to go with friends, colleagues, family, and relatives. Choosing family, relatives, and friends to go with them when traveling is the top choice because traveling time is a time to rest, relax, ... relatives sharing relaxing moments together will be more comfortable and this is also the time for family and friends to gather together.

4.2 ANALYSIS OF FACTORS AFFECTING THE DEVELOPMENT OF ECOTOURISM IN PHONG DIEN DISTRICT

4.2.1 Testing the reliability of scales using Cronbach's Alpha

To use the proposed scales, it is necessary to test the reliability of these scales. Cronbach's Alpha coefficient is used to test the reliability of each scale. In this study, observed variables with a total correlation coefficient <0.3 will be eliminated and scales with Cronbach's Alpha coefficient of 0.6 or higher will be selected.

The group of factors affecting the development of ecotourism includes 25 variables and is divided into 6 groups of factors: human resources; infrastructure; accommodation; services; service prices; security and order and safety. The Cronbach's Alpha coefficient of these groups of factors is 0.920 and is presented in Table 4.5.

Table 4.5 Cronbach's Alpha of factors affecting the development of ecotourism in Phong Dien district

Cronbach's Alpha

0.920
Measured variable		Correlation variable total	Cronbach's Alpha if drop variable
Q6NL1	Good reception and service attitude of staff	0.472	0.918
Q6NL2	Good communication and behavioral skills	0.368	0.920
Q6NL3	Friendly, polite and genuine staff	0.511	0.917
Q6NL4	High level of staff knowledge and skills	0.526	0.917
Q6HT1	Convenient access to tourist attractions	0.459	0.918
Q6HT2	Spacious and clean parking lot	0.654	0.915
Q6HT3	Spacious and clean cruise ship terminal	0.574	0.916
Q6HT4	Adequacy and cleanliness of toilets	0.634	0.915
Q6LT1	Clean, spacious, airy rooms	0.529	0.917
Q6LT2	Rooms are fully furnished	0.643	0.915
Q6LT3	Wifi access – strong internet	0.572	0.916
Q6LT4	Convenient location	0.444	0.919
Q6DV1	There is a spacious, airy and clean dining area.	0.498	0.918
Q6DV2	There is a souvenir shop and a variety of products. product	0.474	0.918
Q6DV3	There are entertainment services suitable for tourism. Ecology	0.503	0.918
Q6DV4	There are many interesting places to visit.	0.479	0.918
Q6GDV1	Reasonable tour price	0.514	0.917
Q6GDV2	Reasonable accommodation prices	0.554	0.917
Q6GDV3	Reasonable shopping prices	0.538	0.917

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Measured variable

Total variable correlation	Cronbach's Alpha if drop variable
Q6GDV4	Reasonable food prices	0.524	0.917
Q6GDV5	Reasonable entertainment service prices	0.513	0.917
Q6AN1	No haggling or price gouging	0.606	0.916
Q6AN2	No begging	0.627	0.916
Q6AN3	No theft	0.676	0.914
Q6AN4	Safety level of means of transport	0.580	0.916

(Source: Results of 2016 survey data processing)

Through table 4.5, we can see that the components of the tourist satisfaction scale have a Cronbach's Alpha reliability coefficient of 0.92, greater than 0.6, proving that the scale has high reliability. All observed variables have a total variable correlation > 0.3, so they meet the requirements and are included in the exploratory factor analysis in the next step.

4.2.2 Exploratory factor analysis EFA

Factor analysis is used to identify important factors influencing ecotourism development and measured through service quality at tourist destinations.

The results of Cronbach's Alpha test of factors affecting the development of ecotourism did not exclude any variables, so the 25 observed variables will continue to be included in the exploratory factor analysis. The results of the first exploratory factor analysis with the Principal Component extraction method and Varimax rotation are presented in Table 4.6.

The results of factor analysis with 25 initially observed variables show that: variable HT1 has a factor loading coefficient < 0.5, so this variable is eliminated from the research model; variables LT4 and AN4 are eliminated from the research model because there is no difference between the factors.

Table 4.6 Rotated matrix of factors affecting the development of ecotourism, first time

Observation variable

Group of factors
F1	F2	F3	F4	F5	F6
DV4	0.866
GDV1	0.847
GDV2	0.751
GDV3	0.746
GDV4	0.784
HT3		0.732
GDV5		0.704
AN1		0.633
AN2		0.667
LT4		0.519		0.515
AN4		0.523				0.502
HT2			0.509
HT4			0.666
LT1			0.737
AN3			0.616
NL1				0.558
NL2				0.833
NL3				0.627
NL4				0.590
LT2					0.671
LT3					0.815
DV1					0.665
DV2						0.777
DV3						0.552
Value	8,715	2,456	1,589	1,384	1,211	1,054
Extracted variance	34,861	9,823	6,275	5,536	4,843	4,215
Total extracted variance	65,553
KMO	0.875
Significance level Sig.	0.000

(Source: Results of 2016 survey data processing)

After removing three variables HT1, LT4, AN4 from the scale, we continued to analyze the second exploratory factor with 22 observed variables.

Table 4.7 Rotated matrix of factors affecting the development of ecotourism, second time

Observation variable

Group of factors
F1	F2	F3	F4	F5	F6
DV4	0.858
GDV1	0.849
GDV2	0.760
GDV3	0.756
GDV4	0.786
HT3		0.661
GDV5		0.791
AN1		0.719
AN2		0.683
HT2			0.564
HT4			0.726
LT1			0.747
AN3			0.596
LT2				0.659
LT3				0.833
DV1				0.692
NL1					0.562
NL2					0.819
NL3					0.651
NL4					0.635
DV2						0.806
DV3						0.654
Value	7,893	2,366	1,490	1,315	1,075	1,034
Extracted variance	35,875	10,756	6,771	5,979	4,885	4,699
Total extracted variance	68,966
KMO	0.868
Significance level Sig.	0.000

(Source: Results of 2016 survey data processing)

The results of factor analysis show that there are 6 factors extracted at Eigenvalue of 1.034 and the extracted variance of 6 factors is 68.97% > 50%. Thus, the variance meets the requirements, meaning that the 6 factors above explain 68.97% of the variation in the data. The KMO coefficient = 0.868 reaches the allowable level (0.5 ≤ KMO ≤ 1), so factor analysis is suitable for market data; Bartlett's test with statistical significance level Sig. = 0.000 means that the observed variables are correlated with the population.

Through table 4.7, we can see that factor 5, including variables NL1, NL2, NL3 and NL4, has no change between the observed variables, so it still retains the name "Human Resources"; factor 6 is still called factor "Service" because this factor only loses 2 variables DV1 and DV4 but there is no change in the observed variables in the group. The remaining factors have some changes in the observed variables compared to the original, we can rely on the observed variables in the factor to rename the factor group appropriately, specifically:

- Factor 1 includes variables: DV4 (many interesting places to visit), GDV1 (cheap sightseeing prices), GDV2 (cheap accommodation prices), GDV3 (cheap shopping prices), GDV4 (cheap food prices), this factor reflects the prices of services at tourist destinations, so we still keep the original name of the factor "Service prices".

- Factor 2 includes: HT3 (Spacious tourist wharf), GDV5 (cheap entertainment service prices), AN1 (no haggling or price gouging), AN2 (no begging), this factor shows customers' concern about the level of security and convenience at tourist destinations, so it should be renamed "Security, safety and convenience".

- Factor 3 includes 4 variables: HT2 (spacious, clean parking lot), HT4 (adequate and clean level of toilets), LT1 (clean, spacious, airy rooms), AN3 (no theft), although the factor has changes in observed variables, it is still called the factor "Infrastructure" because it represents all infrastructure factors at tourist destinations.

- Factor 4 includes: LT2 (fully furnished rooms), LT3 (strong wifi access), DV1 (spacious, airy, clean dining area), variables in the factor represent content related to the characteristics of accommodation facilities at tourist destinations, so it is called "Accommodation facilities".

Table 4.8 Factor rotation matrix

Observation variable

Group of factors
F1	F2	F3	F4	F5	F6
DV4	0.283
GDV1	0.293
GDV2	0.235
GDV3	0.230
GDV4	0.251
HT3		0.278
GDV5		0.433
AN1		0.320
AN2		0.272
HT2			0.233
HT4			0.381
LT1			0.439
AN3			0.267
LT2				0.361
LT3				0.499
DV1				0.382
NL1					0.313
NL2					0.522
NL3					0.334
NL4					0.318
DV2						0.633
DV3						0.482

(Source: Results of 2016 survey data processing)

Through the factor score matrix, we can see that in factor group 1, variable GDV1 (there are many interesting places to visit) has the largest factor score of 0.293, so group 1 is most affected by variable GDV1. Similarly, with the largest factor score of 0.433, factor group 2 is most affected by variable AN1 (no haggling or price gouging). Variable LT1 (clean, spacious, airy rooms) has a factor score of 0.439, which has the largest impact on factor group 3. Factor group 4 is most affected by variable LT3 (wifi access - strong internet) with a factor score of 0.499. Variable NL2 (good communication skills) has a factor score of 0.522, which is the variable that influences factor group 5 the most, and variable DV2 (having a souvenir shop and diverse products) influences factor group 6 the most with a factor score of 0.633.

From the above factor score results, we can rewrite the exploratory factor equation as follows:

F1 = .283 DV4 + .346 GDV1 + .330 GDV2 + .330 GDV3 + .343 GDV4

F2 = 0.278 HT3 + 0.320 GDV5 + 0.433 AN1 + 0.272 AN3

F3 = 0.233 HT2 + 0.381 HT4 + 0.439 LT1 + 0.267 AN3 F4 = 0.361 LT2 + 0.499 LT3 + 0.382 DV1

F5 = 0.313 NL1 + 0.522 NL2 + 0.334 NL3 + 0.318 NL4 F6 = 0.633 DV2 + 0.482 DV3

To determine which group of factors has the most influence on the development of ecotourism in Phong Dien district, we continue to analyze the average score of the factor groups through visitors' evaluation and shown in Figure 4.6.

Through the average score analysis, we can see that tourists rate factor group 6 "Service" as the most influential with 3.622 points; followed by factor group 2 "Security, safety and convenience" with an average score of 3.579 points; ranked 3rd is factor group 4 "Accommodation facilities" with an average score of 3.345 points; followed by factor group "Infrastructure" with an average score of 3.291 points; ranked 5th with an average score of 3.077 is factor group 3 "Service price" and finally factor 1 "Human resources" is rated the lowest among the factors because it has the smallest score of 3.014 points.

Service

3,622

Security, safety and convenience

3,579

Accommodation

3.345

Infrastructure

3,291

Service price

3,077

Human resources 3,014

0.000 0.500 1.000 1.500 2.000 2.500 3.000 3.500 4.000