ASSESSING THE ECONOMIC IMPACT OF INTERNATIONAL TOURISM ON LOCAL COMMUNITIES IN UZBEKISTAN: AN EMPIRICAL STUDY OF SAMARKAND, BUKHARA, AND KHIVA

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Kamola Nazarova;Nilufar Rakhimova

Description

The paper discusses the impact international tourism has on the local community life of Uzbekistan, in particular on the heritage cities of Samarkand, Bukhara and Khiva. Even though the field of tourism has evolved rapidly since 2017, there is a lack of empirical evidence regarding the allocation of the economic profits on the community level. The research involving the assistance of a mixed-methods research design includes quantitative survey data of 55 tourism workers and qualitative information materials on the basis of open-ended questions and informal interview. The analysis is devoted to the reliance of the tourism-associated income, character of employment, participation in the value chain as well as distribution and governance of benefits.The outcomes have demonstrated that tourism is an important source of livelihood and that the respondents received an average of 56 per cent of their household earnings in the tourism industry and had an experience of eight years in the tourism related activities. The consumer benefits are, however, not equally spread and little involvement in community in tourism planning. It was also only in one variable, which is the local spending retention where Khiva showed more local economic relations compared to Samarkand and Bukhara. The qualitative data identifies the poor structural barriers, including, but not limited to, lack of adequate financial resources, poor infrastructure, and inability of small producers to enter the market, and bureaucracies. Despite these limitations, the respondents indicated that there was the potential to improve local participation through community-based tourism (CBT), more appropriate integration of local suppliers into tourism value chain as well as its introduction of capacity building services.

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Publication Details

DOI

Publisher

Zenodo

Assigned Domain

Subfield

Sociology and Political Science

Field

Social Sciences

Domain

Social Sciences

Confidence Score

51%

Source

Scholar Data Model