Research Article

DOI :10.26650/jot.2022.8.1.1047512   IUP :10.26650/jot.2022.8.1.1047512    Full Text (PDF)

Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul

Semra Aktaş Polat

This paper analyzes the perceptions of Turkish customers regarding their experiences at Asian restaurants in Istanbul. Within the scope of the study, 1,348 online reviews written in Turkish on TripAdvisor for Asian restaurants operating in Istanbul were analyzed with the latent Dirichlet allocation (LDA) algorithm and sentiment analysis. As a result of the analysis nine dimensions affecting the experiences of Turkish customers at Asian restaurants were determined, four of which were specific to the restaurant (view, staff, place, order) and five of which were related to food (real taste, food, sauce and spice, sushi, flavor). It was found that flavor and food are the main dimensions that positively affect Turkish customers’ Asian restaurant experiences. Order was found to be the most important dimension that negatively affects them. To my knowledge, this is the first study interpreting the perception of Turkish customers’ experiences of Asian restaurants through online reviews in Turkish.

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  • Aktas-Polat, S., & Polat, S. (2022). Discovery of factors affecting tourists’ fine dining experiences at five-star hotel restaurants in İstanbul. British Food Journal, 124(1), 221-238. https://doi. org/10.1108/BFJ-02-2021-0138 google scholar
  • Alba, J., & Chattopadhyay, A. (1986). Salience effects in brand recall. Journal of Marketing Research, 23(4), 363-369. google scholar
  • Alghamdi, R., & Alfalqi, K. (2015). A survey of topic modeling in text mining. International Journal of Advanced Computer Science and Applications, 6(1), 147-153. google scholar
  • Arora, R., & Singer, J. (2006). Cognitive and affective service marketing strategies for fine dining resturant managers. Journal of Small Business Strategy, 17(1), 51-62. google scholar
  • Arvela, P. (2013). Ethnic food: The Other in Ourselves. In D. Sanderson, & M. Crouch (Eds.), Food: Expressions and impressions (pp. 45-56). Oxford, United Kingdom: Inter-Disciplinary Press. google scholar
  • Barrett, L. F. (1996). Hedonic tone, perceived arousal, and item desirability: Three components ofself-reported mood. Cognition & Emotion, 10(1), 47-68. google scholar
  • Bholowalia, P., & Kumar, A. (2014). EBK-means: A clustering technique based on elbow method and k-means in WSN. International Journal of Computer Applications, 105(9), 17-24. https:// google scholar
  • Blei, D. M., & Lafferty, J. (2009). Topic Models. In A. Srivastava, & M. Sahami (Eds.), Text Mining: Classification, Clustering, and Applications (pp. 71-94). London: Taylor and Francis. google scholar
  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993-1022. google scholar
  • Büschken, J., & Allenby, G. M. (2016). Sentence-based text analysis for customer reviews. Marketing Science 35(6), 953-975. google scholar
  • Chicco, D., & Jurman, G. (2020). The advantages of the matthews correlation coefficient (mcc) over F1 score and accuracy in binary classification evaluation. BMC Genomics, 21(1), 1-13. google scholar
  • Debortoli, S., Müller, O., Junglas, I., & vom Brocke, J. (2016). Text mining for information systems researchers: An annotated topic modeling tutorial. Communications of the Association for Information Systems, 39(1). google scholar
  • Ebster, C., & Guist, I. (2004). The role of authenticity in ethnic restaurants. Journal of Foodservice Business Research, 7(2), 41-52. google scholar
  • Fanelli, R. M., & Di Nocera, A. (2018). Customer perceptions ofjapanese foods in Italy. Journal of Ethnic Foods, 5(3), 167-176. google scholar
  • Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82-89. google scholar
  • Ferdman, R. A. (2015). Asian food: The fastest growing food in the world. The Washington Post, Washington. Retrieved from 31.05.2021 google scholar
  • Germann Molz, J. (20079. Eating difference: The cosmopolitan mobilities of culinary tourism. Space and Culture, 10(1), 77-93. google scholar
  • Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(1), 5228-5235. google scholar
  • Guo, Y., Barnes, S. J., & Jia, Q. (2017). Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent Dirichlet allocation. Tourism Management, 59, 467-483. google scholar
  • Gustafsson, I.-B. (2004). Culinary arts and meal science-a new scientific research discipline. Food Service Technology, 4(1), 9-20. google scholar
  • Gustafsson , I.-B., Öström, A., Johansson, J., & Mossberg, L. (2006). The five aspects meal model: A tool for developing meal services in restaurants. Journal of Foodservice, 17, 84-93. https:// google scholar
  • Ha, J., & Jang, S.C.S. (2010). Effects of service quality and food quality: The moderating role of atmospherics in an ethnic restaurant segment. International Journal of Hospitality Management, 29(3), 520-529. google scholar
  • Hallowell, I. (1955). Culture and Experience. Philadelphia: University of Pennsylvania Press. google scholar
  • Hindle, A., Ernst, N. A., Godfrey, M. W., & Mylopoulos, J. (2013). Automated topic naming. Empirical Software Engineering, 18(6), 1125-1155. google scholar
  • Hofstede, G., Hofstede, G. J., & Minkov, M. (2010). Cultures and Organizations, Software of the Mind, Intercultural Cooperation and its Importance for Survival. New York: Mcgraw-Hill. google scholar
  • Hua, T., Lu, C.-T., Choo, J., & Reddy, C. K. (2020). Probabilistic topic modeling for comparative analysis of document collections. ACM Transactions on Knowledge Discovery from Data (TKDD), 14(2), 1-27. google scholar
  • Huang, J., Rogers, S., & Joo, E. (2014). Improving restaurants by extracting subtopics from Yelp reviews. Social Media Expo 2014. google scholar
  • Jang, S. C. S., Ha, A., & Silkes, C. A. (2009). Perceived attributes of asian foods: From the perspective of the American customers. International Journal of Hospitality Management, 28(1), 63-70. google scholar
  • Jang, S. C. S., & Ha, A. (2009). Asian foods in the U.S: Developments, customer profiles, and experiences. Journal of Foodservice Business Research, 12(4), 403-412. https://doi. org/10.1080/15378020903344372 google scholar
  • Jia, S. S. (2020). Motivation and satisfaction of Chinese and US tourists in restaurants: A cross-cultural text mining of online reviews. Tourism Management, 78, 104071. https://doi. org/10.1016/j.tourman.2019.104071 google scholar
  • Jiao, Y., & Du, P. (2016). Performance measures in evaluating machine learning based bioinformatics predictors for classifications. Quantitative Biology, 4(4), 320-330. s40484-016-0081-2 google scholar
  • Jo, Y., & Oh, A. H. (2011). Aspect and sentiment unification model for online review analysis. In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, 815-824. google scholar
  • Johns, N., & Pine, R. (2002). Consumer behaviour in the food service industry: A review. International Journal of Hospitality Management, 21(2), 119-134. S0278-4319(02)00008-7 google scholar
  • Josiam, B., Sohail, M. S., & Monteiro, P. (2007). Curry cuisine: Perceptions of Indian restaurants in Malaysia. Tourismos: An International Journal of Tourism, 2(2), 25-38. google scholar
  • Kirilenko, A. P., Stepchenkova, S. O., Kim, H., & Li, X. R. (2018). Automated sentiment analysis in tourism: Comparison of approaches. Journal of Travel Research, 57(8), 1012-1025. https:// google scholar
  • La Pastina, A. C., & Straubhaar, J. D. (2005). Multiple proximities between television genres and audiences: The Schism between telenovelas’ global distribution and local consumption. International Communication Gazette, 67(3), 271-288. https://doi. org/10.1177/0016549205052231 google scholar
  • Le, T. H., Arcodia, C., Novais, M. A., Kralj, A., & Phan, T. C. (2021). Exploring the multi-dimensionality of authenticity in dining experiences using online reviews. Tourism Management, 85, 104292. google scholar
  • Lee, L. E., Niode, O., Simonne, A. H., & Bruhn, C. M. (2012). Consumer perceptions on food safety in Asian and Mexican restaurants. Food Control, 26(2), 531-538. foodcont.2012.02.010 google scholar
  • Lin, C., & He, Y. (2009). Joint sentiment/topic model for sentiment analysis. In Proceedings of the 18th ACM Conference on Information and Knowledge Management, 375-384. CIKM’09, November 2-6, 2009, Hong Kong, China google scholar
  • Liu, Y., & Jang, S. C. S. (2009). Perceptions of Chinese restaurants in the US: What affects customer satisfaction and behavioral intentions? International Journal of Hospitality Management, 28(3), 338-348. google scholar
  • Lu, S., & Fine, G. A. (1995). The presentation of ethnic authenticity: Chinese food as a social accomplishment. The Sociological Quarterly, 36(3), 535-553. google scholar
  • Lupton, D. (1994). Food, memory and meaning: The symbolic and social nature of food events. Sociological Review, 42(4), 664-687. google scholar
  • Ma, J. E., Qu, H., Njite, D., & Chen, S. (2011). Western and Asian customers’ perception towards Chinese restaurants in the United States. Journal of Quality Assurance in Hospitality & Tourism, 12(2), 121-139. google scholar
  • Mathayomchan, B., & Taecharungroj, V. (2020). “How was your meal?” Examining customer experience using google maps reviews. International Journal of Hospitality Management, 90, 102641. google scholar
  • Min, K.-H., & Han, S. (2017). Local consumers’ perceptions and preferences for Asian ethnic foods. International Journal of Tourism Sciences, 17(3), 165-179. 80634.2017.1349628 google scholar
  • Nakayama, M., & Wan, Y. (2019). Same sushi, different impressions: A cross-cultural analysis of Yelp reviews. Information Technology & Tourism, 21(2), 181-207. s40558-018-0136-5 google scholar
  • Oh, M. M., & Kim, S. S. (2020). Dimensionality of ethnic food fine dining experience: An application of semantic network analysis. Tourism Management Perspectives, 35, 100719. google scholar
  • Onorati, M. G., & Giardullo, P. (2020). Social media as taste re-mediators: Emerging patterns of food taste on TripAdvisor. Food, Culture & Society, 23(3), 347-365. 528014.2020.1715074 google scholar
  • Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and Trends® in Information Retrieval, 2(1-2), 1-135. google scholar
  • Park, S. B., Jang, J., & Ok, C. M. (2016). Analyzing Twitter to explore perceptions of Asian restaurants. Journal of Hospitality and Tourism Technology, 7(4), 405-422. https://doi. org/10.1108/JHTT-08-2016-0042 google scholar
  • Pezenka, I., & Weismayer, C. (2020). Which factors influence locals’ and visitors’ overall restaurant evaluations? International Journal of Contemporary Hospitality Management, 32(9), 27932812. google scholar
  • Polat, S., & Aktas-Polat, S. (2020). Transformation of local culinary through gastronomy tourism. Sosyoekonomi, 28(43), 243-256. google scholar
  • Ponnam, A., & Balaji, M. (2014). Matching visitation-motives and restaurant attributes in casual dining restaurants. International Journal of Hospitality Management, 37, 47-57. https://doi. org/10.1016/j.ijhm.2013.10.004 google scholar
  • Raudenbush, B., & Capiola, A. (2012). Physiological responses of food neophobics and food neophilics to food and non-food stimuli. Appetite, 58(3), 1106-1108. appet.2012.02.042 google scholar
  • Rhee, H. T., Yang, S. B., & Kim, K. (2016). Exploring the comparative salience of restaurant attributes: A conjoint analysis approach. International Journal of Information Management, 36(6), 1360-1370. google scholar
  • Rozin, P., & Vollmecke, T. A. (1986). Food likes and dislikes. Annual Review of Nutrition, 6(1), 433-456. google scholar
  • Sangkaew, N., & Zhu, H. (2020). Understanding tourists’ experiences at local markets in Phuket: An analysis of TripAdvisor reviews. Journal of Quality Assurance in Hospitality & Tourism. google scholar
  • Situmeang, F., de Boer, N., & Zhang, A. (2020). Looking beyond the stars: A description of text mining technique to extract latent dimensions from online product reviews. International Journal of Market Research, 62(2), 195-215. google scholar
  • Sloan, E. A. (2001). Ethnic foods in the decade ahead. Food Technology, 55(10), 18-26. google scholar
  • Stickel, C., Ebner, M., Steinbach-Nordmann, S., Searle, G., & Holzinger, A. (2009). Emotion detection: Application of the valence arousal space for rapid biological usability testing to enhance universal access. International Conference on Universal Access in Human-Computer Interaction (pp. 615-624). Berlin, Heidelberg: Springer. google scholar
  • Sukalakamala, P., & Boyce, J. B. (2007). Customer perceptions for expectations and acceptance of an authentic dining experience in Thai restaurants. Journal of Foodservice, 18(2), 69-75. https:// google scholar
  • Sutherland, I., & Kiatkawsin, K. (2020). Determinants of guest experience in airbnb: A Topic modeling approach using LDA. Sustainability, 12(8), 3402. google scholar
  • Sutherland, I., Sim, Y., Lee, S. K., Byun, J., & Kiatkawsin, K. (2020). Topic modeling of online accommodation reviews via latent Dirichlet allocation. Sustainability, 12(5), 1821. https://doi. org/10.3390/su12051821 google scholar
  • Taecharungroj, V., & Mathayomchan, B. (2019). Analysing TripAdvisor reviews of tourist attractions in Phuket, Thailand. Tourism Management, 75: 550-568. https://doi.Org/10.1016/j. tourman.2019.06.020 google scholar
  • Taecharungroj, V., Warnaby, G., & Parker, C. (2021). Responding to the voice of the markets: An analysis of Tripadvisor reviews of UK retail markets. Journal of Place Management and Development, 14(2), 180-200. google scholar
  • Tey, Y. S., Arsil, P., Brindal, M., Liew, S. Y., Teoh, C. T., & Terano, R. (2018). Personal values underlying ethnic food choice: Means-end evidence for Japanese food. Journal of Ethnic Foods, 5(1), 33-39. google scholar
  • Turgeon, L., & Pastinelli, M. (2002). “Eat the world”: Postcolonial encounters in Quebec city’s ethnic restaurants. Journal of American Folklore, 115(456), 247-268. stable/4129222 google scholar
  • Van den Berghe, P. L. (1984). Ethnic cuisine: Culture in nature. Ethnic and Racial Studies, 7(3), 387-397. google scholar
  • van Trijp, Hans, C. M., & van Kleef, E. (2008). Newness, value and new product performance. Trends in Food Science & Technology, 19(11), 562-573. google scholar
  • Vermeulen, I. E., & Seegers, D. (2009). Tried and tested: The impact of online hotel reviews on consumer consideration. Tourism Management, 30(1), 123-127. tourman.2008.04.008 google scholar
  • Wang, W., Feng, Y., & Dai, W. (2018). Topic analysis of online reviews for two competitive products using latent Dirichlet allocation. Electronic Commerce Research and Applications, 29, 142-156. google scholar
  • Warde, A. (2000). Cultural flows and spread of ethnic restaurants. In, D. Kalb, M. Van der Land, R. Staring, B. Van Steenbergen, & N. Wilterdink (Eds.), The Ends of Globalization: Bringing Society Back In (pp. 299-316). USA: Rowman & Littlefield Inc. google scholar
  • Wong, T.-T. (2015). Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation. Pattern Recognition, 48(9), 2839-2846. patcog.2015.03.009 google scholar


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Aktaş Polat, S. (2022). Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology, 8(1), 27-48.


Aktaş Polat S. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology. 2022;8(1):27-48.


Aktaş Polat, S. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology, [Publisher Location], v. 8, n. 1, p. 27-48, 2022.

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Aktaş Polat, Semra,. 2022. “Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul.” Journal of Tourismology 8, no. 1: 27-48.

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Aktaş Polat, Semra,. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul.” Journal of Tourismology 8, no. 1 (Jul. 2024): 27-48.

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Aktaş Polat S. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology [Internet]. 20 Jul. 2024 [cited 20 Jul. 2024];8(1):27-48. Available from: doi: 10.26650/jot.2022.8.1.1047512


Aktaş Polat, Semra. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul”. Journal of Tourismology 8/1 (Jul. 2024): 27-48.


Published Online05.05.2022


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