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

Year 2022, Volume: 8 Issue: 1, 27 - 48, 30.06.2022
https://doi.org/10.26650/jot.2022.8.1.1047512

Abstract

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.

References

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Year 2022, Volume: 8 Issue: 1, 27 - 48, 30.06.2022
https://doi.org/10.26650/jot.2022.8.1.1047512

Abstract

References

  • Aktas-Polat, S., & Polat, S. (2021). Discovery of factors affecting tourists’ fine dining experiences at five-star hotel restaurants in Istanbul. British Food Journal. https://doi.org/10.1108/BFJ-02-2021-0138
  • Alba, J., & Chattopadhyay, A. (1986). Salience effects in brand recall. Journal of Marketing Research, 23(4), 363–369.
  • 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.
  • 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.
  • 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.
  • Barrett, L. F. (1996). Hedonic tone, perceived arousal, and item desirability: Three components of self-reported mood. Cognition & Emotion, 10(1), 47–68. https://doi.org/10.1080/026999396380385
  • 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://doi.org/10.5120/18405-9674
  • 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.
  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.
  • Büschken, J., & Allenby, G. M. (2016). Sentence-based text analysis for customer reviews. Marketing Science 35(6), 953–975. http://dx.doi.org/10.1287/mksc.2016.0993
  • 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. https://doi.org/10.1186/s12864-019-6413-7
  • 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).
  • Ebster, C., & Guist, I. (2004). The role of authenticity in ethnic restaurants. Journal of Foodservice Business Research, 7(2), 41–52. https://doi.org/10.1300/J369v07n02_04
  • Fanelli, R. M., & Di Nocera, A. (2018). Customer perceptions of japanese foods in Italy. Journal of Ethnic Foods, 5(3), 167–176. https://doi.org/10.1016/j.jef.2018.07.001
  • Feldman, R. (2013). Techniques and applications for sentiment analysis. Communications of the ACM, 56(4), 82–89. https://doi.org/10.1145/2436256.2436274
  • Ferdman, R. A. (2015). Asian food: The fastest growing food in the world. The Washington Post, Washington. Retrieved from https://www.washingtonpost.com/news/wonk/wp/2015/02/03/the-fastest-growing-food-in-the-world/ 31.05.2021
  • Germann Molz, J. (20079. Eating difference: The cosmopolitan mobilities of culinary tourism. Space and Culture, 10(1), 77–93. https://doi.org/10.1177/1206331206296383
  • Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences, 101(1), 5228–5235. https://doi.org/10.1073pnas.0307752101
  • 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. https://doi.org/10.1016/j.tourman.2016.09.009
  • Gustafsson, I.-B. (2004). Culinary arts and meal science–a new scientific research discipline. Food Service Technology, 4(1), 9–20. https://doi.org/10.1111/j.1471-5740.2003.00083.x
  • Gustafsson , I.-B., Öström, Å., 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://doi.org/10.1111/j.1745-4506.2006.00023.x
  • 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. https://doi.org/10.1016/j.ijhm.2009.12.005
  • Hallowell, I. (1955). Culture and Experience. Philadelphia: University of Pennsylvania Press.
  • Hindle, A., Ernst, N. A., Godfrey, M. W., & Mylopoulos, J. (2013). Automated topic naming. Empirical Software Engineering, 18(6), 1125–1155. https://doi.org/10.1007/s10664-012-9209-9
  • 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.
  • 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. https://doi.org/10.1145/3369873
  • Huang, J., Rogers, S., & Joo, E. (2014). Improving restaurants by extracting subtopics from Yelp reviews. Social Media Expo 2014.
  • 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. https://doi.org/10.1016/j.ijhm.2008.03.007
  • 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
  • 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
  • Jiao, Y., & Du, P. (2016). Performance measures in evaluating machine learning based bioinformatics predictors for classifications. Quantitative Biology, 4(4), 320–330. https://doi.org/10.1007/s40484-016-0081-2
  • 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.
  • Johns, N., & Pine, R. (2002). Consumer behaviour in the food service industry: A review. International Journal of Hospitality Management, 21(2), 119–134. https://doi.org/10.1016/S0278-4319(02)00008-7
  • 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.
  • 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://doi.org/10.1177/0047287517729757
  • 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
  • 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. https://doi.org/10.1016/j.tourman.2021.104292
  • 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. https://doi.org/10.1016/j.foodcont.2012.02.010
  • 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
  • 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. https://doi.org/10.1016/j.ijhm.2008.10.008
  • Lu, S., & Fine, G. A. (1995). The presentation of ethnic authenticity: Chinese food as a social accomplishment. The Sociological Quarterly, 36(3), 535–553.
  • Lupton, D. (1994). Food, memory and meaning: The symbolic and social nature of food events. Sociological Review, 42(4), 664–687. https://doi.org/10.1111/j.1467-954X.1994.tb00105.x.
  • 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. https://doi.org/10.1080/1528008X.2011.541818
  • Mathayomchan, B., & Taecharungroj, V. (2020). “How was your meal?” Examining customer experience using google maps reviews. International Journal of Hospitality Management, 90, 102641. https://doi.org/10.1016/j.ijhm.2020.102641
  • Min, K.-H., & Han, S. (2017). Local consumers’ perceptions and preferences for Asian ethnic foods. International Journal of Tourism Sciences, 17(3), 165–179. https://doi.org/10.1080/15980634.2017.1349628
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There are 73 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Semra Aktas Polat 0000-0002-2324-2200

Publication Date June 30, 2022
Submission Date December 26, 2021
Published in Issue Year 2022 Volume: 8 Issue: 1

Cite

APA Aktas Polat, S. (2022). Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology, 8(1), 27-48. https://doi.org/10.26650/jot.2022.8.1.1047512
AMA Aktas Polat S. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology. June 2022;8(1):27-48. doi:10.26650/jot.2022.8.1.1047512
Chicago Aktas Polat, Semra. “Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul”. Journal of Tourismology 8, no. 1 (June 2022): 27-48. https://doi.org/10.26650/jot.2022.8.1.1047512.
EndNote Aktas Polat S (June 1, 2022) Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology 8 1 27–48.
IEEE S. Aktas Polat, “Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul”, Journal of Tourismology, vol. 8, no. 1, pp. 27–48, 2022, doi: 10.26650/jot.2022.8.1.1047512.
ISNAD Aktas Polat, Semra. “Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul”. Journal of Tourismology 8/1 (June 2022), 27-48. https://doi.org/10.26650/jot.2022.8.1.1047512.
JAMA Aktas Polat S. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology. 2022;8:27–48.
MLA Aktas Polat, Semra. “Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul”. Journal of Tourismology, vol. 8, no. 1, 2022, pp. 27-48, doi:10.26650/jot.2022.8.1.1047512.
Vancouver Aktas Polat S. Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul. Journal of Tourismology. 2022;8(1):27-48.