30TO STUDY THE ATTITUDE OF THE POPULATION TO TOURISM THROUGH ECONOMETRIC MODEL
Bahtiyor Iskandarovich Ashurov
Samarkand Institute of Economics and Service ashrovbakhtiyor89@gmail.com
Odil Nurmuminovich Tagayev
Samarkand Institute of Economics and Service tagayev 1988@mail.ru
ABSTRACT
The study examines whether the socio-demographics of the local population and public relations can influence their impact on tourism (economic, environmental and socio-cultural impacts), as well as their satisfaction with local tourism management. Checks for According to a survey of local residents, the relationship with tourism and the requirements of domestic tour packages were assessed.
Keywords: tourist demand, perceptions of the population, socio-demographic characteristics
INTRODUCTION
Several studies have shown that the population's perception of tourism explores the importance of socio-demographic characteristics, particularly gender and habitat, in socio-cultural, economic and environmental influences. This article helps to study the satisfaction of tourism with local management and to determine the impact of the impact of tourism on their satisfaction.
Tourism is considered an important source of income for many countries around the world. The tourism sector produced 10.4 percent of world GDP and provided 319 million jobs in 2018 (WTTC, 2019). These figures show how important tourism is for the world economy. It is seen not only as a global business, but also as an important source of income for vulnerable segments of society, such as women, the disabled, and others. The locals have little idea of tourism. In addition, although a lot of research has been done on archeological sites in Samarkand, Bukhara and Khorezm regions, little research has been done to study how the population perceives the impact of tourism. This study was conducted to meet the need to analyze the perception of the population of Samarkand, Bukhara and Khorezm regions in relation
to tourism leaders. In our view, this study aims to educate tourism leaders on the importance of managing the impact of tourism on the local community and the impact on the local community in creating a healthy environment and clarifying the important factors that support sustainable tourism development.
LITERATURE REVIEW
Ribeiro, MA; Pinto, P .; Silva, JA; Woosnam, the attitude of KM residents and the perception of tourist behavior, concepts are explained in the example of developing countries. (2017)
Ko, DW; Stewart, WP Concepts are presented through a model of the structural equation of the population's attitude to the development of tourism (2002)
Jurovskiy, C .; Gursoy, D. The results of remote effects on the attitude of the population to tourism are studied. (2004)
Madrigal, R. Concepts of tourism in cities are covered. (1993) Gursoy, D .; Chi, CG; Dyer, P. The attitude of the local population to mass and alternative tourism was studied. (2010)
Vargas-Sanches, A .; Porras-Bueno, N .; de los Ángeles Plaza-Mejía, M. A study of the population's attitude to tourism and the season (2014)
Sharma, B .; Dyer, P. Explains the perception of the population in relation to tourism and their impact on tourism. (2009)
Alrwajfah M. et al (2020) highlighted the challenges faced by women working in the tourism industry in Muslim developing countries.
METHODOLOGY
Sampling and data collection
The impact of population perceptions on tourism can be analyzed using hypotheses based on the following factors. Community consolidation
H1a. There is a positive correlation between the level of engagement and the impact of tourism on tourism.
H1b. There is a positive correlation between the level of involvement and the perceived negative impact of tourism. Distance from tourist area.
H2a. There is a negative correlation between distance from tourist zones and the positive tourism impact received.
H2b. There is a positive correlation between the distance from tourist zones and the perceived tourism effects.
Gender.
H3a. Women are less optimistic about the positive impact of tourism than men.
H3b. Women are more concerned about the negative impact of tourism than
men.
Age.
H4a.There is a negative relationship between the positive effects of age and tourism.
H4b. There is a negative correlation between the age of tourism and the perceived negative impact.
Tourism-related jobs.
H5a. Residents engaged in tourism-related activities are more likely to experience a positive tourism impact.
H5b. Residents engaged in tourism-related activities are less likely to experience the effects of tourism.
Level of education.
H6a. There is a positive correlation between the level of education and the perceived positive impact of tourism.
H6b. There is a positive correlation between the level of education and the perceived negative impact of tourism.
Satisfaction with local governance.
H 7. The benefits of tourism development have a positive impact on local government satisfaction.
H 8. Tourism development costs have a negative impact on local government satisfaction.
Data on the attitude of the population to tourism were collected from the population of Samarkand, Bukhara and Khorezm regions, who were at least 18 years old. After reviewing the previously mentioned literature and participating in the Code of Ethics and Practice established by the American Public Opinion Research Association [1,3,5], a questionnaire was developed. Data collection was done via telegram messenger, email address and similar social networks.
Research factor analysis (type R) with analysis of the main components replaced by varimax was used to form a general understanding of the population in relation to different effects. Assumptions on factor analysis are not broken. The Kaiser-Meyer-Olkin statistic is 0.816, which exceeds the recommended threshold
value of 0.06 [1, 4.6], and it is convenient to analyze the correlation factors between these elements. The data show that Bartlett's Sphericity test is important (approximately chi-square = 4649.167, df = 300, p <0.001). Items with a coefficient value less than 0.4 were deleted. A determined (regression) method was used to calculate the score of each factor. This method maximizes validity and gives real factor scores [1,5,8]. These scores were then used as related variables in a regression analysis to test the effect of several independent variables on residents 'perceptions. Accordingly, after several studies, five pure models were produced from the data. The specific values of the factors are greater than one and account for 56.464% of the total variance of the data.
We created a five-question questionnaire among the population of Samarkand, Bukhara and Khorezm regions, which was used to assess the attitude of the population to tourism.
Models Items
Factor Loading
Mean SD
PSC
Tourism provides entertainment opportunities for the local 0.757 community
Tourism helps to creates more ^ ^ „ a (0 732) ii • 0.584
a ) local associations
e (6.200) VE
(24.800)
Tourism helps to improve the government provided facilities (Health centres, better schools, post office, sport centres, etc.)
Tourism helps to preserve local traditions
0.656
0.663
PEn
a (0.730) Tourism helps to pr°tect the 0 736 e (3.220) environment .
Tourism help to creates more 0.549
VE
2.92 2.76
2.96
2.74 3.02 3.07 2.91
1.408
2.83 1.229
1.351
1.363
1.243 1.290
Models Items
Factor Loading
Mean SD
PE
a (0.819) e (1.834) VE
(7.335)
(12.879) natural parks
Tourism encourages people to protect surrounding environment
Tourism helps to keep my village\city clean
Tourism increases my family incomes
Tourism creates better public transportation infrastructure
Tourism helps to build more roads
Tourism helps to creates business
Tourism helps to creates more jobs
Tourism increases the uses of alcohol
Tourism increases the amount of crime
Tourism reduces my outdoor recreation
Tourism makes crowding of public spaces and facilities
Tourism hazards the citizen rights by using the lands and
0.704
0.784
0.544 0.674 0.802 0.805 0.725
NSEn
a (0.809) e (1.447) VE
(5.789)
0.598 0.756 0.643 0.549 0.594
2.99
3.11
2.92 2.47
2.82
2.93
3.22 2.93 3.34
2.99 3.06
1.269 1.278
1.249 1.308 1.267
3.15 1.325
1.379
1.413
2.76 1.373
2.61 1.207
1.216 1.283
Models Items
Factor Loading
Mean SD
NE
properties to create more hotels and borders from national parks
Tourism creates more social needs
Tourism negatively affects the family relationships
Tourism increases pollution (noise, air, etc.)
Tourism hazard the natural landscape
Tourism increases the price of
0.595
0.498
0.596
0.542
a (0.829) properties
e (1.415) Tourism increases the cost of VE living
(5 661) Tourism generates seasonal unemployment
0.845
0.804
0.665
2.87 1.175
2.78 1.211
3.12 1.304
3.21 3.08 3.40
3.51
3.53
1.378
1.393 1.343 1.390
Kaiser-Meyer-Olkin Measure of Sampling Adequacy = 0.816; total variance explained data = 56.464%; a: Cronbach's Alpha; e: Eigenvalues; VE: percentage of variance explained.
Factor loads for the derived models and Cronbach's Alpha are shown, [1,4,7,8] i.e. Model 1: Positive Sociocultural (PSC); Model 2: Positive environment (PEn); Model 3: Positive Economics (PE); Model 4: Negative social environment (NSEn); Model 5: Negative economic (NE). Five models derived from factor analysis were then tested for reliability. The values of Kronbach's Alpha coefficient from this study range from 0.730 to 0.829, indicating a high correlation with their variable factors and the presence of internal compatibility of the substances. Examination of the correlation matrix shows that no correlation between factors is greater than 0.50.
We thought it would be possible to include five models in the list of dependent variables and use the following independent variables (attachment, gender, place of residence, age, employed, education level). The average score was calculated based on the average scores of the public attachment elements to create a variable score.
RESULTS AND DISCUSSION
The GLM model results indicate that all five models were significant (p < 0.01) explaining the variation of (6.3% of PCS), (10.6% of PEn), (14% of PE), (8.6% of NSEn), and (7.7% of NE). Linear regression was applied to examine whether the perceptions' domains influence the residents' satisfaction. [19] The model was significant (F = 39.524; p = 0.000) and explained 30% of the variation. Perceived positive economic impact was the strongest predictor of satisfaction (P = 0.307) followed by positive environment (P = 0.243) and positive socio-culture domain (P = 0.196). Negative perceived impacts were found not to be a significant predictor of the residents' satisfaction. It should be noted that only significant results are shown further on
DV IV B Hypothesis Supported?
PSC
Distance 0.240 *** H2a yes
a R2 0.064 Education 0.120 ** H6a yes
R2 adJusted 0.0479 F 4.289 Attachment T- employed 0.071 * -0.500 ** H1a H5a yes no
PEn
Distance 0.211 *** H2a yes
R2 0.107 Attachment 0.340 *** H1a yes
r2 adJusted 0.094 F 7.856 T- employed -0.587 ** H5a no
Age 0.082 * H4a yes
PE
R2 0.139 Distance 0 191 *** H2a yes
Academic Research, Uzbekistan 125 www.ares.uz
DV IV B Hypothesis Supported?
R2 adjusted 0.126 Age -0.079 ** H4a no
F 10.721 Gender -0.675 *** H3a yes
NSEn
R2 0.091 T- employed 0.340 * H5b no
R2 adjusted 0.162 Distance 0.345 *** H2b no
F 6.201 Education 0.152 ** H6b yes
Gender -0.462 ** H3b no
NE
R2 0.079 Education 0.091 * H6b yes
r2 adjusted 0.065 F 5.493 Attachment 0 171 *** H1b yes
Hypothesis 1, if there is a higher level of connection, the perceived negative and positive effects increase. This hypothesis was supported in terms of negative economic effects (b = 0.150, p <0.01); positive socio-cultural (b = 0.064, p <0.1); and a positive environment (ph = 0.230, p <0.01). Hypothesis 2 hypothesizes that the farther away the population lives from the tourist zone, the more they are concerned about the negative effects [4,3] and the less they like the positive effects. The results of the PE model support the H3a hypothesis (b = -0.565, p <0.01) Conversely, the NSEn results (b = -0.355, p = 0.003) reject the H3b hypothesis.
Hypothesis 4a was supported by the results of the PEn model (b = 0.076, p <0.1). It was predicted that the older the participant, the more negative they would perceive the positive tourism impact. Furthermore, in terms of the PE model, it was rejected (d = -0.086, p <0.05). There are no significant findings in negative areas.Tourism-related work is expected to have a positive impact on tourism. Thus, H5a was rejected in terms of PSC (b = -0.400, p <0.05) and PEn (p = -0.491, p <0.05). H5b was also rejected with NSEn results (b = 0.280, p <0.1). According to Hypothesis 6, the higher the level of knowledge of the population, the higher the perception of negative and positive effects. H6a was supported during the PSC (b = 0.116, p <0.05) period, and H6b was supported by the NE (b = 0.089, p <0.1) and
NSEn (b = 0.135, p <0.05) results. In addition, Hypothesis 7 assumes that the acceptable benefits of tourism will have a positive effect on the satisfaction of the population with local government. This hypothesis was supported by PSC (b = 0.196, p <0.01), Pen (b = 0.243, p <0.01), and pe (b = 0.307, p <0.01). Finally, Hypothesis 8 suggests that once the population understands the costs of tourism development, their dissatisfaction with local management [2,3] becomes clear. This hypothesis was rejected.
As an example of the results, the b-value of the sex in the PE area (regression coefficient) can be deduced from this, women receive less positive economic effects than men, and the average score is 0.565. Similarly, the age b value in the PEn model shows that as the age group increases (e.g., 25-34 to 35-44), the positive impact on the environment increases by 0.076.
In general, the results give an idea of the impact of the population on tourism in Samarkand, Bukhara and Khorezm regions. Regardless of the theoretical support of the results of the hypotheses, the addition was found to have the highest regression coefficient in the positive environment, the distance in the negative social environment, the highest age in the positive economic field. those who are employed in the tourism industry (those who are employed) have the highest level in a positive environment.
CONCLUSION
This study provides a broad understanding of the attitude and satisfaction of the population with the development of tourism in Samarkand, Bukhara and Khorezm regions. The main contribution of this study is the study of local satisfaction, employment of women through the development of domestic tourism. In addition, it reflects the profile of the impact of various external factors and internal factors on the types of tourism perceptions (economic, socio-cultural and environmental), which contributes to current knowledge and understanding of the population's attitude to tourism development. The results of the study show that there is a need to pay more attention to the concepts of the local population, to involve women in the industry and to involve the population in tourism planning. Future research should explore supporting sustainable tourism development and community participation in decision-making.
In our view, tourism is an area where women and other vulnerable groups are more equal than in other sectors. In addition, the sector plays an important role in
personal social well-being and cultural integration. In this regard, tourism can be considered as a means of social transformation.
REFERENCES
1. Alrwajfah M.M. , Garcia F.A., Cortes-Marcias R. (2020) Females 'perspective on tourism's impact and their employment in the sector: The case of Petra, Jordan. Sustainable Tourism and Hospitality Management. 11 (7), https://doi.org/10.3390/su11071907
2. Ribeyro, MA; Pinto, P .; Silva, JA; Woosnam, the attitude of KM residents and the perception of tourist behavior, concepts are explained in the example of developing countries. (2017)
3. Ko, DW; Stewart, WP Concepts are presented through a model of the structural equation of the population's attitude to the development of tourism (2002)
4. Jurovskiy, C .; Gursoy, D. The results of remote effects on the attitude of the population to tourism are studied. (2004)
5. Madrigal, R. The concepts of tourism in cities are covered. (1993)
6. Gursoy, D .; Chi, CG; Dyer, P. The attitude of the local population to mass and alternative tourism was studied. (2010)
7. Vargas-Sanches, A .; Porras-Bueno, N .; de los Ángeles Plaza-Mejía, M. A study of the population's attitude to tourism and the season (2014)
8. Sharma, B .; Dyer, P. Explains the perception of the population in relation to tourism and their impact on tourism. (2009)
