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Öğe Acculturation Research in Residential Tourism(University of Primorska, 2024) Cibere, Gabriela Uslu; Kantarci, Kemal; Başaran, Murat Alper; Uslu, YakupAlthough the acculturation theory has been tested in tourism, there are almost no empirical studies in residential tourism. It needs to be clarified whether the general assumptions of the acculturation theory can be applied or whether the specifics of residential tourism call anew for an evaluation of the preconditions of acculturation theory in this setting. The existing studies, however limited, are misleading. This article calls attention to this fact and shows the necessity of testing the presumptions of acculturation theory in residential tourism before further research is conducted. A questionnaire research was conducted among residential tourists in Alanya. A total of 489 questionnaires from over 12 countries were included, reflecting the residential market in Alanya. The preference for a specific acculturation strategy was tested in relation to the influencing factors and level of satisfaction with life in the destination. The most preferred strategy by international residential tourists was integration, followed by assimilation and marginalisation. The strategy preference was influenced by demographic characteristics, holiday behaviour factors, second home characteristics, personality traits, and level of knowledge about Turkish culture. The overall level of satisfaction with life was 4.3 out of 5, which implies a very high level of satisfaction. Following limited previous research, the article uncovers the pitfalls and proposes a more suitable approach for acculturation research in this area. If the unique circumstances of residential tourism are taken into consideration, the study reveals some results that oppose the general acculturation theory and thus calls for further research. © 2024 University of Primorska. All rights reserved.Öğe Analysis of Almaty's Restaurant Reviews through Topic Modelling(University of Primorska, 2024) Uysal, Alper Kürşat; Tükenmez, Egemen Güneş; Nurbulatovna, Madina Abdikarimova; Başaran, Murat Alper; Kantarci, Kemal; Kurmanbaevich, Turganbai Abdrassilov; Agytaevna, Kultay AdilovaThis research investigates customers’ reviews of the restaurant sector in Almaty, Kazakhstan. Although Kazakhstan offers unique foods, beverages, and establishments, few studies have investigated customers’ reviews of the restaurant business. Hence, this is a pioneering study examining problems and concerns of the restaurant sector in the eyes of customers in Almaty, Kazakhstan by implementing big data analysis. The scraped dataset from the TripAdvisor website contains more than 13,000 restaurant reviews in different languages between 2010 through 2023. Generally, English and Russian are the two dominant languages used in reviews in Almaty. Text mining techniques of topic modelling and sentiment analysis are applied in order to derive and understand the main focuses, problems, and concerns of restaurant customers. To do this the collected data between 2010–2023 is split into two roughly equal datasets that cover the periods between 2010–2017 and 2018–2023, respectively. It is revealed that while restaurant customers were less satisfied with the service process, the most positive reviews, written in both English and Russian, were obtained for the topic ‘Atmosphere and Events’. Considering the service process as a holistic process, analysing the conditions affecting good service delivery and making improvements will urge restaurant customers to form positive opinions. This study provides an opportunity for managerial, operational, and marketing departments in Almaty to improve the restaurant business in the eyes of customers. Since no precise information about the themes of the restaurants is available on the restaurant pages, no thematic distinction could be provided. © 2024 University of Primorska. All rights reserved.Öğe Analysis of Online User Reviews for Popular Tourist At-tractions: Almaty Case(Institute of Economics Committee of Science MSHE RK, 2024) Uysala, Alper Kürşat; Başaran, Murat Alper; Kantarci, KemalAttractions in the tourism industry are one of the components that motivate tourists to visit destinations, such as entertainment, natural, cultural, and historical richness. For such reasons, people decide to visit unique destinations and spend time there. Almaty, the largest city of Kazakhstan, is one of the significant attraction centers of the Central Asia region, offering tourists unique and pleasant features with several tourist attractions. This study aims to analyze online user reviews of tourist attractions in Almaty, Kazakh-stan, using machine learning and text mining methods. The primary focus is on identifying the main the-matic clusters of reviews and their sentiment and comparing these themes with the types of attractions: historical, natural, and man-made. A total of 7,515 reviews were collected from the TripAdvisor website. The data was processed using sentiment analysis, topic modeling, and hierarchical clustering methods. The analysis revealed that 38% of the reviews were related to natural attractions, 34% to man-made, and 28% to historical ones. The most positive reviews were associated with natural attractions, while historical and man-made attractions received 79.38% and 81.40% positive reviews, respectively. In addition, the items that make up these attractions are identified, and their sentiment levels are pointed out. In addition to this situation, visitors have the most positive expressions for natural attractions, especially landscapes and lakes. The findings emphasize the importance of considering review themes to improve the quality of tourist services and to enhance the positive image of Almaty as a tourist destination. © 2024, Institute of Economics Committee of Science MSHE RK. All rights reserved.Öğe Tourism Competitiveness Performances of the Most Visited Muslim-Majority Countries through Multi-Dimensional Scaling(Statistical Economic and Social Research and, 2022) Kantarci, Kemal; Başaran, Murat Alper; Özyurt, Paşa MustafaCompetitiveness has become a vital issue for tourism destinations, which provides destinations a high ground to strengthen their positions in the marketplace and benefit more from the positive impacts of tourism, as well as preserving the resources. In this study, tourism and travel competitiveness performances of the ten most-visited Muslim-majority countries are examined comparatively by using the data issued by World Economic Forum’s Competitiveness Indexes. The study aims to determine the power and the directions of the sub-competitiveness factors as well as reveal the differences among those countries, benefiting from both Multidimensional Scaling Analysis and ANOVA, which are employed together. Findings indicate that Infrastructure Index shows the highest correlation with the Overall Competitiveness Index, followed by the T&T Policy-Enabling Condition index. On the other hand, the correlations between Enabling Environment and T&T Policy Enabling Conditions and, Enabling Environment and Natural-Cultural Resources is found to be negatively correlated which provides a vital issue for practitioners. © 2022, Statistical Economic and Social Research and. All rights reserved.Öğe Öğe
