Müşterilerin Zincir Restoran Seçimini Etkileyen Faktörler

Öz

Bu çalışma, Türkiye'deki zincir restoranlarda müşteri tercih faktörlerini anlamayı hedefleyen ve bu tercihlerin demografik özelliklerle ilişkisini inceleyen bir araştırmayı kapsamaktadır. Veri toplama amacıyla anket yöntemi kullanılmıştır. Katılımcıların yaş, cinsiyet, öğrenim düzeyi ve gelir seviyeleri gibi demografik özellikleri ile restoran tercihlerini şekillendiren faktörler arasındaki anlamlı farklılık için analiz edilmiştir. Araştırmanın evreni, Türkiye'deki zincir restoranların müşteri tabanını içermektedir. Örneklem büyüklüğü, kullanılan ölçekte yer alan maddelerin beş katı olarak belirlenen 125 katılımcı üzerine kurulmuştur. Veriler, çevrimiçi anket formu aracılığıyla toplanmıştır. Pilot çalışma ve kartopu örnekleme yöntemi kullanılarak veri toplama süreci yürütülmüştür. Veri analizi, SPSS istatistiksel yazılım aracılığıyla gerçekleştirilmiştir. Doğrulayıcı faktör analizi (DFA), ölçeklerin yapısıyla uyum ve ayırma geçerliliğini değerlendirmek için kullanılmıştır. Bu aşamadan sonra, ölçeklerin güvenirliği Cronbach Alfa (CA) güvenirlik katsayısı ile değerlendirilmiş ve hipotezlerin test edilmesi için Kruskal-Wallis ve Mann-Whitney U testleri gibi istatistiksel metotlardan faydalanılmıştır. Araştırmanın sonuçları, demografik faktörlerin restoran tercihlerini belirlemedeki rolünü ortaya koymaktadır. Yaş, öğrenim düzeyi, gelir düzeyi, restorana gitme sıklığı ve cinsiyet gibi demografik özellikler, müşterilerin restoran tercihlerini etkileyen faktörler arasında anlamlı farklılıklar göstermektedir. Bu bulgular, restoran işletmecilerine ve pazarlamacılara, müşteri segmentasyonu ve hedef kitleye yönelik stratejiler geliştirme konusunda pratik rehberlik sunabilir. Ayrıca, gelecekteki araştırmaların daha geniş ve çeşitli katılımcı gruplarını içeren çalışmalar yaparak daha geniş kapsamlı sonuçlar elde etmeyi amaçlaması önerilebilir.

Anahtar Kelimeler

• Zincir Restoran
• Müşteri
• Müşteri seçim kriterleri
• Restoran tercihi
• Tüketici davranışı

Factors Affecting Customers' Choice of Chain Restaurants

Öz

This study encompasses research aimed at understanding customer preference factors in chain restaurants in Turkey and examining their relationship with demographic characteristics. A survey method was employed for data collection. Significant differences among participants' demographic characteristics such as age, gender, education level, and income levels, and factors shaping restaurant preferences were analysed. The scope of the study includes the customer base of chain restaurants in Turkey. The sample size was determined based on 125 participants, five times the items in the scale used. Data were collected through an online survey form, and the data collection process was carried out through a pilot study and snowball sampling method. Data analysis was conducted using the SPSS statistical software. Confirmatory factor analysis (CFA) was used to assess the structure and discriminant validity of the scales. Subsequently, the reliability of the scales was evaluated using Cronbach's Alpha (CA) reliability coefficient, and statistical methods such as Kruskal-Wallis and Mann-Whitney U tests were employed to test hypotheses. The results of the study highlight the role of demographic factors in determining restaurant preferences. Demographic characteristics such as age, education level, income level, frequency of restaurant visits, and gender show significant differences among factors influencing customers' restaurant preferences. These findings can provide practical guidance to restaurant operators and marketers in developing strategies for customer segmentation and target audience. Additionally, it is recommended that future research aims for more comprehensive results by conducting studies with larger and more diverse participant groups.

Anahtar Kelimeler

• Chain Restaurant
• Customer
• Customer Choice Criteria
• Restaurant Preference
• Consumer Behavior

Kaynakça

1. Alonso, D. A., O’Neill, M., Liu, Y. ve O’Shea, M. (2013). Factors Driving Consumer Restaurant Choice: An Exploratory Study from the Southeastern United States, Journal of Hospitality Marketing & Management, 22 (5): 547-567
2. Anderson, J. C., ve Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
3. aScozzafava, G., Contini, C., Romano, C., & Casini, L. (2017). Eating out: which restaurant to choose?. British Food Journal, 119(8), 1870-1883.
4. Bae, S., Slevitch, L., & Tomas, S. (2018). The effects of restaurant attributes on satisfaction and return patronage intentions: Evidence from solo diners’ experiences in the United States. Cogent Business & Management, 5(1), 1493903.
5. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16, 74-94.
6. Beer, C. L., Ottenbacher, M. C., & Harrington, R. J. (2012). Food tourism implementation in the Black Forest destination. Journal of Culinary Science & Technology, 10(2), 106-128.
7. Bolton, L. E., Warlop, L., & Alba, J. W. (2003). Consumer perceptions of price (un) fairness. Journal of consumer research, 29(4), 474-491.
8. Bufquin, D., DiPietro, R., Orlowski, M., & Partlow, C. (2017). The influence of restaurant co-workers’ perceived warmth and competence on employees’ turnover intentions: The mediating role of job attitudes. International Journal of Hospitality Management, 60, 13-22.

9. Bujisic, M., Hutchinson, J., & Parsa, H. G. (2014). The effects of restaurant quality attributes on customer behavioral intentions. International Journal of Contemporary Hospitality Management, 26(8), 1270-1291.
10. Canziani, B. F., Almanza, B., Frash, R. E., McKeig, M. J., & Sullivan-Reid, C. (2016). Classifying restaurants to improve usability of restaurant research. International Journal of Contemporary Hospitality Management, 28(7), 1467–1483.
11. Cattell, R. (1978). The scientific use of factor analysis. New York: Plenum.
12. Chiciudean, G. O., Harun, R., Muresan, I. C., Arion, F. H., Chiciudean, D. I., Ilies, G. L., & Dumitras, D. E. (2019). Assessing the importance of health in choosing a restaurant: An empirical study from Romania. International Journal of Environmental Research and Public Health, 16(12), 2224.
13. Choi, J., & Zhao, J. (2010). Factors influencing restaurant selection in south florida: Is health issue one of the factors influencing consumers' behavior when selecting a restaurant?. Journal of Foodservice Business Research, 13(3), 237-251.
14. Cullen, F. (2005). Factors influencing restaurant selection in Dublin. Journal of Foodservice Business Research, 7(2), 53-85.
15. Dash, K. (2005). McDonald’s in India. A07-05-0015.Thunderbird. The Garvin School of International Management.
16. Dutta, K., Parsa, H. G., Parsa, R. A., & Bujisic, M. (2014). Change in consumer patronage and willingness to pay at different levels of service attributes in restaurants: A study in India. Journal of Quality Assurance in Hospitality & Tourism, 15(2), 149-174.
17. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
18. Gregory, S., & Kim, J. (2005). Restaurant choice: The role of information. Journal of Foodservice Business Research, 7(1), 81-95.
19. Ha, J., & Jang, S. 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.
20. Haghighi, M., Dorosti, A., Rahnama, A., & Hoseinpour, A. (2012). Evaluation of factors affecting customer loyalty in the restaurant industry. African journal of business management, 6(14), 5039.
21. Hair, J. F., Black, W. C., Tatham, R. L. ve Anderson, R. E. (2010). Multivariate data analysis. Upper Saddle River, NJ: Prentice Hall.
22. Han, H., & Ryu, K. (2009). The roles of the physical environment, price perception, and customer satisfaction in determining customer loyalty in the restaurant industry. Journal of hospitality & tourism research, 33(4), 487-510.
23. Hanefors, M., & Mossberg, L. (2003). Searching for the extraordinary meal experience. Journal of Business and Management, 9(3), 249-270.
24. Harrington, R. J., Ottenbacher, M. C., & Kendall, K. W. (2011). Fine-dining restaurant selection: Direct and moderating effects of customer attributes. Journal of foodservice business research, 14(3), 272-289.
25. Harris, K. J., DiPietro, R. B., Murphy, K. S., & Rivera, G. (2014). Critical food safety violations in Florida: Relationship to location and chain vs. non-chain restaurants. International Journal of Hospitality Management, 38, 57–64.
26. Hawkins, D., & David L, M. (2015). Consumer Behavior: Building Marketing Strategy 11th Ed.
27. Heung, V. C., & Gu, T. (2012). Influence of restaurant atmospherics on patron satisfaction and behavioral intentions. International Journal of Hospitality Management, 31(4), 1167-1177.
28. Hwang, J., & Ok, C. (2013). The antecedents and consequence of consumer attitudes toward restaurant brands: A comparative study between casual and fine dining restaurants. International Journal of Hospitality Management, 32, 121-131.
29. Hwang, J., Cho, S. B., & Kim, W. (2019). Consequences of psychological benefits of using eco-friendly services in the context of drone food delivery services. Journal of Travel & Tourism Marketing, 36(7), 835-846.
30. Jekanowski, M. D., Binkley, J. K., & Eales, J. (2001). Convenience, accessibility, and the demand for fast food. Journal of Agricultural and Resource Economics, 58-74.
31. Katsigris, C., & Thomas, C. (2012). The bar and beverage book. John Wiley & Sons.
32. Kim, J., Jin, B., & Swinney, J. L. (2009). The role of etail quality, e-satisfaction and e-trust in online loyalty development process. Journal of retailing and Consumer services, 16(4), 239-247.
33. Klassen, K. J., Trybus, E., & Kumar, A. (2005). Planning food services for a campus setting. International journal of hospitality management, 24(4), 579-609.
34. Ladhari, R. (2008). Alternative measures of service quality: a review. Managing Service Quality: An International Journal, 18(1), 65-86.
35. Liu, Y., & Jang, S. 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.
36. Marković, S., Raspor, S., & Šegarić, K. (2010). Does restaurant performance meet customers' expectations? An assessment of restaurant service quality using a modified DINESERV approach. Tourism and Hospitality Management, 16(2), 181-195.
37. Muller, C. C. (1999). A simple measure of restaurant efficiency. Cornell Hotel and Restaurant Administration Quarterly, 40(3), 31-37.
38. Namkung, Y., & Jang, S. (2007). Does food quality really matter in restaurants? Its impact on customer satisfaction and behavioral intentions. Journal of Hospitality & Tourism Research, 31(3), 387-409.
39. Nunnally, J. C. (1978). An overview of psychological measurement. Clinical diagnosis of mental disorders, 97-146.
40. Oronsky, C. R., &Chathoth, P. K. (2007). An exploratory study examining information technology adoption and implementation in full-service restaurant firms. International Journal of Hospitality Management, 26(4), 941–956.
41. Parasuraman, A. B. L. L., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. 1988, 64(1), 12-40.
42. Parsa, H. G., Self, J. T., Njite, D., & King, T. (2005). Why Restaurants Fail. Cornell Hotel and Restaurant Administration Quarterly, 46(3), 304–322.
43. Pedraja, M., & Yagüe, J. (2001). What information do customers use when choosing a restaurant?. International Journal of Contemporary Hospitality Management, 13(6), 316-318.
44. Peri, C. (2006). The universe of food quality. Food quality and preference, 17(1-2), 3-8.
45. Ponnam, A., & Balaji, M. S. (2014). Matching visitation-motives and restaurant attributes in casual dining restaurants. International Journal of Hospitality Management, 37, 47-57.
46. Qin, H., & Prybutok, V. R. (2009). Service quality, customer satisfaction, and behavioral intentions in fast‐food restaurants. International journal of quality and service sciences, 1(1), 78-95.
47. Ryu, K., & Han, H. (2010). Influence of the quality of food, service, and physical environment on customer satisfaction and behavioral intention in quick-casual restaurants: Moderating role of perceived price. Journal of Hospitality & Tourism Research, 34(3), 310-329.
48. Ryu, K., Lee, H. R., & Kim, W. G. (2012). The influence of the quality of the physical environment, food, and service on restaurant image, customer perceived value, customer satisfaction, and behavioral intentions. International journal of contemporary hospitality management, 24(2), 200-223.
49. Skinner, H., Chatzopoulou, E., & Gorton, M. (2020). Perceptions of localness and authenticity regarding restaurant choice in tourism settings. Journal of Travel & Tourism Marketing, 37(2), 155-168.
50. Sulek, J. M., & Hensley, R. L. (2004). The relative importance of food, atmosphere, and fairness of wait: The case of a full-service restaurant. Cornell hotel and restaurant administration quarterly, 45(3), 235-247.
51. Tabachnick, B. G., Fidell, L. S., ve Ullman, J. B. (2013). Using multivariate statistics (Vol. 6, pp. 497-516). Boston, MA: pearson.
52. Walker, J. R. (2014). The restaurant: From concept to operation (Seventh Edition). Hoboken, New Jersey: John Wiley & Sons, Inc.
53. Wall, E. A., & Berry, L. L. (2007). The combined effects of the physical environment and employee behavior on customer perception of restaurant service quality. Cornell hotel and restaurant administration quarterly, 48(1), 59-69.
54. Wang, Y., Wu, Y., & Zhang, Q. (2013). Fast-food consumption: Its association with food prices and dietary quality. Diet Quality: An Evidence-Based Approach, Volume 2, 141-150.
55. Xia, L., Monroe, K. B., & Cox, J. L. (2004). The price is unfair! A conceptual framework of price fairness perceptions. Journal of marketing, 68(4), 1-15.
56. Yüksel, A., & Yüksel, F. (2003). Measurement of tourist satisfaction with restaurant services: A segment-based approach. Journal of vacation marketing, 9(1), 52-68.