چکیده:
گردشگری به‌عنوان یک فعالیت جهانی امروزه با توجه به هم‌پوشی سه اصل ایجاد اشتغال و درآمدزایی، رضایت گردشگر و حفظ محیط‌زیست اهمیتی دوچندان یافته است. هدف تحقیق حاضر مدل‌سازی عوامل موثر بر تصویر مقصد گردشگری و تأثیر آن بر رضایتمندی گردشگران در شهر تهران است. این پژوهش از نظر هدف، کاربردی و از نظر ماهیت توصیفی ـ تحلیلی است. جامعه آماری پژوهش حاضر، گردشگران شهر تهران در بازه زمانی مشخص می‌باشند، که با توجه به نامشخص بودن تعداد جامعه، با استفاده جدول مورگان 354 نفر انتخاب‌شده است. داده‌های موردنیاز با استفاده از پرسشنامه استاندارد گردآوری‌شده روایی ابزار تحقیق با استفاده از مدل تحلیل عاملی تأییدی و پایایی آن با استفاده از آلفای کرونباخ محاسبه‌شده است. به‌منظور تحلیل داده‌ها از آزمون آماری تحلیل عاملی و T تک نمونه‌ای در نرم‌افزار Spss و از معادلات ساختاری در محیط نرم‌افزار Amos Graphics استفاده گردید. نتایج حاصل از تحلیل عاملی نشان داد که شش عامل شناسایی‌شده توانسته‌اند 63% واریانس اثرات مؤلفه‌های تصویر مقصدهای گردشگری بر رضایتمندی گردشگران را تبیین نمایند. نتایج تحلیل معادلات ساختاری نشان داد که تصویر کلی مقصد بر رضایتمندی گردشگران با 60 درصد از واریانس متغیر وابسته را پیش‌بینی نماید. همچنین تأثیر تصویر شناختی بر تصویر کلی برابر با (21/0) درصد واریانس، تأثیر تصویر عاطفی بر تصویر کلی برابر با (18/0) درصد واریانس، تأثیر تصویر ترغیبی بر تصویر کلی برابر با (30/0) درصد واریانس و تأثیر تصویر کلی بر رضایتمندی گردشگران با توجه به مدل تحلیل مسیر برابر با (27/0) درصد واریانس برآورد شده است.
A B S T R A C T Tourism as a global activity today has doubled in importance due to the overlap of the three principles of job creation and income generation, tourist satisfaction, and environmental protection. Since different tourist destinations are competitive in attracting tourists, improving and promoting effective indicators in attracting tourists to tourist destinations is of great importance. This study aims to model the factors affecting the image of tourist destinations and their impact on tourist satisfaction in Tehran. The research method is descriptive-analytical, which has been done by the survey method. The statistical population of this study is tourists visiting Tehran. In order to determine the number of research samples, due to the unknown number of the statistical population, the required number of samples was 354 questionnaires. In order to analyze the data, a factor analysis statistical test, one-sample T in SPSS software, and structural equations in Amos Graphics software environment were used. The results show that using a factor analysis test to measure the effects of image components of tourist destinations on tourist satisfaction, 6 factors whose specific values were greater than 1 were extracted. These six identified factors were able to 63% of the variance of component image effects. Explain tourism on the satisfaction of tourists. Also, the results of the one-sample t-test to calculate the final score of the level of satisfaction with the image of tourist destinations, with a value of (2.39), were in an undesirable and unacceptable situation. Also, the results of second-order structural equation analysis showed that the overall image of the destination factor has the highest factor load on tourists' satisfaction with 60%. The final results of the structural equation model show that the effect of cognitive image on the overall image is equal to (0.21), the effect of the emotional image on the overall image is equal to (0.18), the effect of the persuasive image on the overall image is equal to (0.30), and the effect of the overall image on the satisfaction of tourists according to the route analysis model is equal to (0.27). Extended Abstract Introduction Tourism is one of the most important economic activities around the world, and it is an essential part of the economy of many countries at different stages of development. Spreading tourism on a global scale as a strategic part of socioeconomic and regional development requires planning has highlighted more sustainable tourism; its development limit has yet to be reached, so its relevance has increased in recent decades, and by 2019 it has become a significant factor for several local and national economies. The tourism industry is expected to grow at a rate of 3.3% per year and reach 1.8 billion tourists by 2030. This growth in the number of tourists visiting different destinations in the world increases the competition between destinations, which shows that a destination depends on its ability to maintain a competitive advantage. It should be noted that since March 2020, the situation has worsened, and there has been a significant reduction in expected revenue in the tourism sector due to the COVID-19 pandemic. The World Tourism Organization (UNWTO) announced the negative effects of this pandemic on the tourism industry, with a 74% decrease in international tourism in 2020. Methodology The present study is of descriptive-analytical type, which has been done by survey method and is based explicitly on structural equation modeling. Structural equations are a comprehensive statistical approach to test hypotheses related to the relationships of observable and latent variables and determine the extent to which data support the theoretical model presented by the researcher. The research has two parts: documentary and quantitative. In the documentary part, the research literature was collected through a library study. In the quantitative part, which includes field survey, the data collection tool is a questionnaire. The research questionnaire was designed based on the indicators, and the Likert scale evaluation method (very low: 1 to very high: 5) was used to score the indicators. The statistical population of this study is tourists visiting Tehran. Since the exact statistics of the number of tourists entering the tourist destinations are unknown, the Cochran sampling method was used for an indefinite and unlimited comprehensive with a 95% confidence level; the estimated number of samples is 354 questionnaires. Internal consistency and validity of the designed questionnaires using Cronbach's alpha coefficient were used. For this purpose, 60 questionnaires were completed and pre-tested, and the obtained alpha coefficient generally equals 0.975. Also, to analyze the data, a factor analysis test was used. A single sample T from the tourist destination image and structural equations in Amos Graphics software were exerted to measure the tourists' satisfaction. Results and discussion In order to measure the effects of image components of tourist destinations on tourist satisfaction in the form of several important and limited factors, a factor analysis statistical test has been used. The reason for choosing factor analysis is to evaluate the image of tourist destinations and summarize the research indicators to explain the image of the tourist destination better. In this regard, in order to determine the appropriateness of data related to the set of analyzed variables regarding the image of tourist destinations, the Bartlett test and KMO index were exerted. The significance of the Bartlett test with the number 5646.5466 at the level of 99% confidence and the appropriate value of KMO (0.898) indicates the correlation and appropriateness of the variables for factor analysis. It should be noted that factors have been accepted to determine the number of factors in this study. Whose specific value is greater than 1. Accordingly, 6 factors whose specific values were greater than 1 were extracted. The results show that the six identified factors have been able to explain 63% of the variance of the effects of image components of tourist destinations on tourist satisfaction. The percentage of explanation of each of the identified factors are in order of importance: the first factor is 10.257%, the second factor is 2.661%, the third factor is 2.141%, the fourth factor is 16.776, and the fifth factor is 1.458%, and the sixth factor is 252. / Is allocated to itself. Conclusion Then, the structural equations in the Amos Graphics software environment were used for first-order factor analysis for all four factors obtained from factor analysis, all of which had a very good fit. After identifying the indicators and image indicators of tourist destinations, first, based on the conceptual model of the research, the destination image indices, and satisfaction, the second-order factor model, a kind of structural equation model, was used. The results of the second-order model test show that the variables of the cognitive image, emotional image, and persuasive image can measure the overall image of tourist destinations, among which cognitive image and emotional image, each with a coefficient of 54%, have the most significant impact on the image. According to the research results of Hernandez-Mogulon et al. (2018), Stylus et al. (2017), and Zhang et al. (2018) showed that the cognitive and emotional image index has the greatest effect on the overall image in attracting and Tourist satisfaction has been aligned. In order to explain the relationship between tourism destination image and tourist satisfaction, the structural model based on the research's conceptual model shows that the overall image's effect on tourist satisfaction is estimated to be 0.27, which can be said to be effective. The overall picture of tourist satisfaction has been positive and significant and aligns with the results of research by Kiani Feyzabadi et al. (2015) and Shahbazi et al. (2016). It has been found that the results of the study are in line with the results of the research of Hernandez-Mogulon et al. (2018), Stylus et al. (2017), and Zhang et al. (2018). The result is equal to or (0.25), which according to the level of significance can be said that the effect of the persuasive image on the satisfaction of tourists has become significantly positive, which is in line with the results of Papadimitriou et al. (2018), Praiag et al. (2007), Silva Lopez et al. (2021), and Kiani Feyzabadi (2017). Funding There is no funding support. Authors’ Contribution All of the authors approved thecontent of the manuscript and agreed on all aspects of the work. Conflict of Interest Authors declared no conflict of interest. Acknowledgments We are grateful to all the scientific consultants of this paper.
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