آرشیو

آرشیو شماره ها:
۴۸

چکیده

امروزه رقابت به عنوان یک مفهوم اقتصادی بر توسعه ی پایدار صنعت سفر و گردشگری تأثیر به سزایی گذاشته است. هدف از این پژوهش ارایه مدل تفسیری ساختاری شاخص های رقابت پذیری سفر و گردشگری استان فارس مبتنی بر گزارش مجمع جهانی اقتصاد در سال 2015 می باشد. تحقیق حاضر به دلیل ایجاد درک و دانشی کاربردی برای مسئولان و سیاست گذاران صنعت گردشگری استان فارس در زمینه شناسایی و سطح بندی شاخص های مؤثر بر رقابت پذیری گردشگری، از نظر هدف یک تحقیق کاربردی است و از منظر روش جمع آوری داده، توصیفی از نوع پیمایشی است. به منظور نهایی کردن شاخص های رقابت پذیری سفر و گردشگری در استان فارس از روایی محتوایی و با نظرسنجی از 10 نفر از متخصصان علمی و اجرایی حوزه گردشگری استان فارس و جهت سطح بندی این شاخص ها از مدل سازی تفسیری ساختاری استفاده شده است. یافته های حاصل از انجام روش روایی محتوایی در نهایت 17 شاخص کلیدی در شش سطح را معرفی می کند. نتایج پژوهش نشان می دهد که اولویت صنعت گردشگری برای دولت کلیدی ترین شاخص در جهت افزایش رقابت پذیری صنعت گردشگری استان فارس بوده و جایگاه نازل ایران از منظر این شاخص در آخرین رتبه بندی مجمع جهانی اقتصاد بیانگر لزوم توجه روزافزون دولت به توسعه صنعت گردشگری است. از سوی دیگر  شاخص هایی مانند نحوه برخورد با مشتری، پایداری توسعه صنعت سفر و گردشگری و شمار سایت های تاریخی ثبت جهانی بیشترین وابستگی را به دیگر شاخص ها داشته و تحت تأثیر آنها می باشند.

Explanation an Interpretive Structural Model of Travel and Tourism Competitiveness Indicators (Case Study: Fars Province)

ExtendedToday the competition as an economic concept of sustainable development has a significant impact travel and tourism industry. The aim of this study is to provide a structural interpretation Modeling of the Travel and Tourism Competitiveness indicators of the in Fars province's on based 2015 world Economic Forum report. This research Study due to understanding and practical knowledge for officials and policy makers in identifying and ranking the province's tourism industry index affecting tourism competitiveness, in term of the aim is an applied research and in terms of data collection methods is descriptive survey. In order to finalize the indicators of competitiveness the travel and tourism in the Fars province, the content validity and a survey of 10 experts from the academic and administrative areas of Fars Province Tourism is used and for levelling of indicators, the interpretive structural modeling is employed. The findings from the content analysis method illustrate that finally 17 key indicators at 6 levels are considered important. The study results show that the tourism industry priority for the government is the key indicator for increase the competitiveness of tourism industry in the Fars province and Iran's weak position in the latest rankings from the perspective of the world Economic Forum indicates that there is a need for government attention to the development of the tourism industry. On the other hand indicators such as how to deal with customers, sustainability of travel and tourism industry development and the number of World Heritage Centers are most dependent on other indices and are influenced by them.   Introduction Considering the tourism industry in the economy of the province a great impact on improving the province's economy, increase employment and per capita income and the development of the province. Achieve these goals without more attention curators and tourism facilities and infrastructure, and facilitating the introduction of tourism and archaeological attractions, cultural and natural would not be possible Which One of the most important things that can be done to identify indicators of competitiveness, development of travel and tourism in the province. According to the Global Competitiveness Index reports that defines conditions and Based on Ability to compare large number of countries in the field of tourism provides. The aim of this study structural interpretation Modeling of Travel and Tourism Competitiveness Index of the World Economic Forum index is based Fars province. Interpretive structural model when large number of elements and the relationships between complex components, can be simple and tangible relationships and the complexity overcome (Agarwal et al, 2007). In general, what distinguishes this study from other internal and external research, providing a new framework and Scientific of travel and tourism competitiveness index using interpretive structural model for ranking and the relationship between these indicators.   Materials and Methods This research Study due to understanding and practical knowledge for officials and policy makers in identifying and ranking the province's tourism industry index affecting tourism competitiveness, in term of the aim is an applied research and in terms of data collection methods is descriptive survey. The sample consisted of 10 experts from the academic and administrative areas of Fars Province Tourism, four of them Shiraz University faculty members, Three of them have a master's degree in the field of Province Tourism and tourism, And three of them visiting professor at the university and has organized activities in the tourism industry in Shiraz. The research tools are two questionnaires. The first questionnaire is the for the finalization of the method and content validity index and the second questionnaire to the leveling of the indexes, and is using interpretive structural modeling   Discussion and Results To extract the indicators of the development of travel and tourism experts in the field of travel and tourism in the province were used. For this purpose, 10 of these experts have expressed willingness to cooperate in this research. The experts, including faculty members and experts in the had field of tourism and high experience in various fields. The opinions of the experts in carrying out and content validity of the questionnaire was used to the structural interpretation modeling. After extraction, according to the 2015 Index of the World Economic Forum and Validity of the 17 key indicators that the CVR was greater than 0.75 Table 2 were obtained. After determining the final travel and tourism, using interpretive structural modeling, structural matrix of variables extracted relations. It is necessary to prepare a matrix to identify dependencies between all the elements to be considered in pair. After these two ideas from experts matrix of relationships of variables in Table 3 were extracted. The study results show that the tourism industry priority for the government is the key indicator for increase the competitiveness of tourism industry in the Fars province and Iran's weak position in the latest rankings from the perspective of the world Economic Forum indicates that there is a need for government attention to the development of the tourism industry. On the other hand, indicators such as how to deal with customers, sustainability of travel and tourism industry development and the number of World Heritage Centers are most dependent on other indices and are influenced by them.   Conclusions The results of this research model has six levels so that whatever we go from lower levels to higher levels The indicators will be less effective. The results show that the tourism industry priority for the government and then government spending, which is one sixth pillar of the World Economic Forum report are the key indicators or roots. The results show that both the province and the entire country are not suitable as independent variables in the field of travel and tourism. And somehow this analysis can be found in other provinces. It is necessary to state the tourism industry, cost management and training in this industry is the most important strategies and measures they must be at the micro level and the macro level in the country and the provinces must be done.   Keywords: Competitiveness Indicators, Interpretive Structural Modeling, World Economic Forum, Content Validity.   References Aazami, M. Jalilian, S. and Hashemi Amin, N. (2015). Analyzing the Socio-economic and Environmental Effects of Rural Tourism (Case Study: Navareh Village), Tourism Planning and Development , 4(14): 154-174. (In Persian) Abby Liu, G.W. (2006). Planning tourism employment: a developing country perspective, Tourism Management , 40(27): 159-170. Agarwal, A; Shankar, R. and Tiwari. M.K. (2007). Modeling Agility of Supply Chain, Industrial Marketing Management , 36: 443-457. Balan, D., Balaure, V. and Veghes, C. (2009). 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