Elektronik Ağızdan Ağıza İletişimin Turizm Destinasyon Seçimi Üzerindeki Etkisi: Planlı Davranış Teorisi Bağlamında Bir İnceleme

Öz

Çalışma, Planlı Davranış Teorisi bağlamında, elektronik ağızdan ağıza iletişimin turistlerin seyahat niyetleri üzerindeki etkisini incelemek amacıyla gerçekleştirilmiştir. Bu bağlamda e-ağızdan ağıza iletişimin, Planlı Davranış Teorisi kapsamında tutum, öznel normlar, algılanan davranışsal kontrol ve niyet üzerindeki etkilerini incelemiştir. Araştırmanın evrenini, Instagram, Facebook gibi sosyal paylaşım sitelerinden ya da farklı çevrimiçi bilgi kaynakları vasıtasıyla konaklama yapma niyetine sahip oldukları belirlenen ve destinasyonlar hakkında deneyim sahibi olmuş 400 tüketiciden toplanan veriler üzerinden gerçekleştirilmiştir. Evrenin geniş bir alanı kapsaması nedeniyle araştırmada “kolayda örneklem yöntemi” kullanılmıştır. Veriler, çevrim içi ortamlar aracılığıyla toplanmıştır. Araştırmada hipotezlerin test edilmesi için Smart PLS 3 istatistik programı kullanılmıştır. Gerçekleştirilen analiz sonuçlarına göre, e-ağızdan ağıza iletişimin bir destinasyona yönelik ziyarete ilişkin tutumlar, subjektif (öznel) normlar, algılanan davranışsal kontrol ve seyahat etme niyeti üzerinde anlamlı etkisi olduğu tespit edilmiştir. Diğer yandan bir destinasyonu ziyaret etmeye yönelik tutumların, subjektif normların ve algılanan davranışsal kontrolün seyahat etme niyeti üzerinde anlamlı etkisinin olduğu da belirlenmiştir.

Anahtar Kelimeler

• Elektronik ağızdan ağıza iletişim
• Planlı davranış teorisi
• Seyahat etme niyeti

The Effect of Electronic Word-of-Mouth on Tourism Destination Selection: An Investigation in The Theory of Planned Behavior

Öz

The study was carried out in the context of Planned Behavior Theory to examine the effect of electronic word-of-mouth on tourists' travel intentions. In this context, the effects of e-word of mouth on attitude, subjective norms, perceived behavioral control and intention within the scope of Planned Behavior Theory are examined. The universe of the research was carried out on the data collected from 400 consumers who were determined to have an intention to stay through social networking sites such as Instagram, Facebook or different online information sources and who had experience about destinations. Since the universe covers a large area, the "convenience sampling method" was used in the research. Data were collected through online environments. In the research, Smart PLS 3 statistical program was used to test the hypotheses. According to the results of the analysis, it was determined that e-word of mouth communication has a significant effect on attitudes towards visiting a destination, subjective (subjective) norms, perceived behavioral control and intention to travel. On the other hand, it was determined that attitudes towards visiting a destination, subjective norms and perceived behavioral control had a significant effect on the intention to travel.

Anahtar Kelimeler

• Electronic word of mouth
• Theory of planned behavior
• Intention to travel

Kaynakça

1. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11-39). Springer, Berlin, Heidelberg.
2. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
3. Ajzen, I. (2002). Perceived behavioral control, self‐efficacy, locus of control, and the theory of planned behavior 1. Journal of applied social psychology, 32(4), 665-683.
4. Ajzen, I. (2006). Behavioral interventions based on the theory of planned behavior. In P. Gollwitzer and J.A. Bargh (eds) Psychology of Action. New York: Guilford, 385-403.
5. Ajzen, I. (2015). Consumer attitudes and behavi or: the theory of planned behavior applied to food consumption decisions. Rivista di Economia Agraria, 70(2), 121-138.
6. Ajzen, I., & Driver, B. L. (1992). Application of the theory of planned behavior to leisure choice. Journal of leisure research, 24(3), 207-224.
7. Albarq, A. N. (2014). Measuring the impacts of online word-of-mouth on tourists' attitude and intentions to visit Jordan: An empirical study. International Business Research, 7(1), 14-22.
8. Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the theory of planned behavior. Journal of research in personality, 25(3), 285-301.

9. Chang, H. H., & Wu, L. H. (2014). An examination of negative e-WOM adoption: Brand commitment as a moderator. Decision Support Systems, 59, 206-218.
10. Christodoulides, G., Michaelidou, N., & Argyriou, E. (2012). Cross‐national differences in e‐WOM influence. European Journal of Marketing, 46(11/12), 1689-1707.
11. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. (2nd Ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
12. Conner, M., & Armitage, C. J. (1998). Extending the theory of planned behavior: A review and avenues for further research. Journal of applied social psychology, 28(15), 1429-1464.
13. Crawley III, F. E. (1990). Intentions of science teachers to use investigative teaching methods: A test of the theory of planned behavior. Journal of Research in Science Teaching, 27(7), 685-697.
14. Dennis, C., Merrilees, B., Jayawardhena, C., & Wright, L. T. (2009). E‐consumer behaviour. European journal of Marketing, 43(9/10), 1121-1139.
15. DeVellis, B. M., Blalock, S. J., & Sandler, R. S. (1990). Predicting Participation in Cancer Screening: The Role of Perceived Behavioral Control 1. Journal of Applied Social Psychology, 20(8), 639-660.
16. Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British journal of management, 17(4), 263-282.
17. Doosti, S., Jalilvand, M. R., Asadi, A., Pool, J. K., & Adl, P. M. (2016). Analyzing the influence of electronic word of mouth on visit intention: the mediating role of tourists’ attitude and city image. International Journal of Tourism Cities, 2(2), 137-148.
18. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
19. Godin, G., & Kok, G. (1996). The theory of planned behavior: a review of its applications to health-related behaviors. American journal of health promotion, 11(2), 87-98.
20. Godin, G., Valois, P., & Lepage, L. (1993). The pattern of influence of perceived behavioral control upon exercising behavior: an application of Ajzen's theory of planned behavior. Journal of Behavioral Medicine, 16(1), 81-102.
21. Gosal, J., Andajani, E., & Rahayu, S. (2020, January). The Effect of e-WOM on Travel Intention, Travel Decision, City Image, and Attitude to Visit a Tourism City. In 17th International Symposium on Management (INSYMA 2020) (pp. 261-265). Atlantis Press.
22. Goyette, I., Ricard, L., Bergeron, J., & Marticotte, F. (2010). e‐WOM Scale: word‐of‐mouth measurement scale for e‐services context. Canadian Journal of Administrative Sciences/Revue Canadienne des Sciences de l'Administration, 27(1), 5-23.
23. Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European business review, 26(2), 106-121.
24. Hair Jr, J. F., Sarstedt, M., Matthews, L. M., & Ringle, C. M. (2016). Identifying and treating unobserved heterogeneity with FIMIX-PLS: Part I–method. European Business Review, 28(1), 63-76.
25. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long range planning, 46(1-2), 1-12.
26. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
27. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the Internet?, Journal of Interactive Marketing, 18(1), 38-52.
28. Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2-20.
29. Hsiao, C. H., & Yang, C. (2010). Predicting the travel intention to take High Speed Rail among college students. Transportation research part F: traffic psychology and behaviour, 13(4), 277-287.
30. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
31. Ikhsan, R. B., & Ohliati, J. (2020, August). E-WOM And Social Commerce Purchase Intentions: Applying The Theory of Planned Behavior. In 2020 International Conference on Information Management and Technology (ICIMTech) (pp. 34-39). IEEE.
32. Jalilvand, M. R., & Samiei, N. (2012). The impact of electronic word of mouth on a tourism destination choice: Testing the theory of planned behavior (TPB). Internet Research, 22(5), 591-612.
33. Kassem, N. O., Lee, J. W., Modeste, N. N., & Johnston, P.K. (2010). Understanding soft drinkconsumption among female adolescents using the theory of planned behavior. Health Education Research, 18(3), 278-91.
34. Kimmel, A. J., & Kitchen, P. J. (2014). WOM and social media: Presaging future directions for research and practice. Journal of Marketing Communications, 20(1-2), 5-20.
35. Kitcharoen, K. (2019). The Effect of E-Word of Mouth (E-WOM) on Various Factors Influencing Customers’ Hotel Booking Intention. ABAC ODI Journal Vision. Action. Outcome, 6(1), 62-74.
36. La Barbera, F., & Ajzen, I. (2020). Control Interactions in the Theory of Planned Behavior: Rethinking the Role of Subjective Norm. Europe’s Journal of Psychology, 16(3), 401-417.
37. Lam, T., & Hsu, C. H. (2006). Predicting behavioral intention of choosing a travel destination. Tourism management, 27(4), 589-599.
38. Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and social psychology Bulletin, 18(1), 3-9.
39. Miao, Y. (2015). The influence of electronic-WOM on tourists' behavioral intention to choose a destination: A case of chinese tourists visiting thailand. AU-GSB e-journal, 8(1), 13-31.
40. Notani, A. S. (1998). Moderators of Perceived Behavioral Control's Predictiveness in the Theory of Planned Behavior: A Meta-Analysis. Journal of Consumer Psychology, 3(7), 247-271.
41. O’brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & quantity, 41(5), 673-690.
42. O'Reilly, K., & Marx, S. (2011). How young, technical consumers assess online WOM credibility, Qualitative Market Research, 14(4), 330-359.
43. Özer, L. Kement, Ü., & Gültekin, B. (2015). Genişletilmiş planlanmış davranış teorisi kapsamında yeşil yıldızlı otelleri tekrar ziyaret etme niyeti. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 33(4), 59-85.
44. Park, S. H., Hsieh, C. M., & Lee, C. K. (2017). Examining Chinese college students’ intention to travel to Japan using the extended theory of planned behavior: Testing destination image and the mediating role of travel constraints. Journal of Travel & Tourism Marketing, 34(1), 113-131.
45. Parker, D., Manstead, A. S., Stradling, S. G., Reason, J. T., & Baxter, J. S. (1992). Intention to commit driving violations: An application of the theory of planned behavior. Journal of applied psychology, 77(1), 94.
46. Prayogo, R. R., & Kusumawardhani, A. (2017). Examining relationships of destination image, service quality, e-WOM, and revisit intention to Sabang Island, Indonesia. APMBA (Asia Pacific Management and Business Application), 5(2), 89-102.
47. Purbadharmaja, I. B. P., Setiawan, P. Y., Hayashi, T., & Widanta, A. A. B. P. (2021). How electronic word of mouth (e-WOM) triggers intention to visit through destination image, trust and satisfaction: the perception of a potential tourist in Japan and Indonesia, Online Information Review, ahead-of-print(ahead-of-print).
48. Quintal, V. A., Lee, J. A., & Soutar, G. N. (2010). Risk, uncertainty and the theory of planned behavior: A tourism example. Tourism management, 31(6), 797-805.
49. Reyes-Menendez, A., Saura, J. R., & Martinez-Navalon, J. G. (2019). The impact of e-WOM on hotels management reputation: exploring tripadvisor review credibility with the ELM model. IEEE Access, 7, 68868-68877.
50. Rhodes, R. E., Jones, L. W., & Courneya, K. S. (2002). Extending the theory of planned behavior in the exercise domain: A comparison of social support and subjective norm. Research quarterly for exercise and sport, 73(2), 193-199.
51. Rizky, R. M., Kusdi, R., & Yusri, A. (2017). The impact of e-WOM on destination image, attitude toward destination and travel intention. Russian Journal of Agricultural and Socio-Economic Sciences, 61(1).94-104.
52. Setiawan, P. Y., Troena, E. A., & Armanu, N. (2014). The effect of e-WOM on destination image, satisfaction and loyalty. International Journal of Business and Management Invention, 3(1), 22-29.
53. Shan, G., Yee, C. L., & Ji, G. (2020). Effects of attitude, subjective norm, perceived behavioral control, customer value and accessibility on intention to visit Haizhou Gulf in China. Journal of Marketing Advances and Practices, 2(1), 26-37.
54. Soliman, M. (2019). Extending the theory of planned behavior to predict tourism destination revisit intention. International Journal of Hospitality & Tourism Administration, 22(5), 524-549.
55. Sotiriadis, M. D., & Van Zyl, C. (2013). Electronic word-of-mouth and online reviews in tourism services: the use of twitter by tourists. Electronic Co mmerce Research, 13(1), 103-124.
56. Sönmez Çakır, F. (2020). Kısmi en küçük kareler yapısal eşitlik modellemesi (PLS-SEM) SmartPLS 3.2. Uygulamaları. Gazi Kitabevi.
57. Sparks, P., & Shepherd, R. (1992). Self-identity and the theory of planned behavior: assessing the role of identification with'green consumerism'. Social Psychology Quarterly, 55, 388-399.
58. Tabbane, R. S., & Hamouda, M. (2013). Impact of e-WOM on the Tunisian Consumer's Attitude towards the Product. In Advances in Business-Related Scientific Research Conference (pp. 20-22).
59. Teng, S., Wei Khong, K., Wei Goh, W., & Yee Loong Chong, A. (2014). Examining the antecedents of persuasive eWOM messages in social media, Online Information Review, 38(6), 746-768.
60. Tiono, M. V. (2016). Pengaruh e-WOM Terhadap Intention Wisata di Banyuwangi: Theory of Planned Bahavior. Undergraduate Thesis.
61. Tran, G. A., & Strutton, D. (2020). Comparing email and SNS users: Investigating e-servicescape, customer reviews, trust, loyalty and E-WOM. Journal of Retailing and Consumer Services, 53, 1-17.
62. TUİK (2020). Hanehalkı Bilişim Teknolojileri (BT) Kullanım Araştırması. https://data.tuik.gov.tr/Bulten/Index?p=Survey-on-Information-and-Communication-Technology-(ICT)-Usage-in-Households-and-by-Individuals-2020-33679 (Erişim Tarihi: 07.11.2021).
63. Ünlüönen, K., & Işın, A. (2018). Türkiye’ye Gelen Yabancı Turistlerin Yerel Yiyecekleri Tüketme Niyeti Üzerine Planlı Davranış Teorisi Kapsamında Bir Araştırma. Journal of Tourism and Gastronomy Studies, 6(4), 662-689.
64. Yoo, C. W., Sanders, G. L., & Moon, J. (2013). Exploring the effect of e-WOM participation on e-Loyalty in e-commerce. Decision Support Systems, 55(3), 669-678.