SPOR TÜKETİM NİYETİ ÖLÇEĞİ: TÜRKÇEYE UYARLAMA, GEÇERLİLİK VE GÜVENİLİRLİK ÇALIŞMASI

Abstract

Bu çalışma, Trail vd., (2025) tarafından geliştirilen Spor Tüketim Niyeti Ölçeğinin Türkçeye uyarlanması amacıyla yapılmıştır. Araştırmanın evrenini spor kulübü taraftarları oluşturmaktadır. Örneklem seçiminde, katılımcılara ulaşılabilirliği esas alan kolayda örnekleme yöntemi tercih edilmiştir. Çalışma kapsamında veri toplama süreci iki aşamalı olarak yürütülmüş ve toplamda 246 katılımcıdan veri toplanmıştır (AFA= 124 ve DFA=122). Çeviri-geri çeviri yöntemi ile orijinali İngilizce olan ölçek Türkçeye uyarlanmıştır. Araştırma verilerinin analiz sürecinde SPSS 26.0 ve AMOS 24.0 istatistiksel programlarından yararlanılmıştır. Bulgular AFA sonuçlarının ölçme aracının yapısal geçerliliği ve güvenilirliği açısından makul ve güçlü kanıtlar sunduğunu göstermektedir (KMO: 0,896; AV: %75,957; FY: 0,739-0,915, α=0,961). DFA sonucunda elde edilen sonuçlar ise modelin verilerle uyumunun 'iyi' düzeyde olduğunu göstermiştir (X2 =11,86; X2 /sd=2,37; SRMR=0,04; NFI=0,921; CFI=0,933; GFI=0,880; AVE>0,50; CR>AVE; α=0,935). Sonuçlar tek boyutlu ve altı maddeden oluşan 'Spor Tüketim Niyeti Ölçeği' nin (STNÖ) geçerli ve güvenilir bir ölçme aracı olduğunu ortaya koymaktadır.

Keywords

• Spor Tüketimi
• Satın Alma Niyeti
• Spor Pazarlaması

SPORTS CONSUMPTION INTENTIONS SCALE: A TURKISH ADAPTATION, VALIDITY, AND RELIABILITY STUDY

Abstract

This study has been conducted to adapt the Sports Consumption Intentions Scale developed by Trail et al (2025) and translated into Turkish. The population of the study consists of sports club supporters. In selecting the sample, convenience sampling has been preferred based on the accessibility of participants. Data collection has been conducted in two stages, with data collected from a total of 246 participants (AFA= 124 and DFA=122). The scale, originally in English, has been adapted into Turkish using the translation-back translation method. SPSS 26.0 and AMOS 24.0 statistical programmes have been used to analyse the research data. The findings show that the AFA results provide reasonable and strong evidence in terms of the structural validity and reliability of the measurement tool (KMO: 0,896; EV: %75,957; FL: 0,739-0,915, α=0,961). The results obtained from DFA indicate that the model fits the data at a “good” level (X² = 11.86; X²/df = 2.37; SRMR = 0.04; NFI=0.921; CFI=0.933; GFI=0.880; AVE>0.50; CR>AVE; α=0.935). The results demonstrate that the unidimensional, six-item Sport Consumption Intention Scale (SCIS) is a valid and reliable measurement instrument.

Keywords

• Sports Consumption
• Purchase Intention
• Sports Marketing

References

1. Abeza, G., O’Reilly, N., & Seguin, B. (2019). Social media in relationship marketing: The perspective of professional sport managers in the MLB, NBA, NFL, and NHL. Communication & Sport, 7(1), 80-109. https://doi.org/10.1177/2167479517740343
2. Abeza, G., O’Reilly, N., Nadeau, J., & Abdourazakou, Y. (2023). Big data in professional sport: the perspective of practitioners in the NFL, MLB, NBA, and NHL. Journal of Strategic Marketing, 31(8), 1413-1433. https://doi.org/10.1080/0965254X.2022.2108881
3. Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
4. Bayram, N. (2016). Yapısal eşitlik modellemesine giriş: AMOS Uygulamaları. Ezgi Kitabevi.
5. Billings, A. C., Qiao, F., Conlin, L., & Nie, T. (2017). Permanently desiring the temporary? Snapchat, social media, and the shifting motivations of sports fans. Communication & Sport, 5(1), 10–26. https://doi.org/10.1177/2167479515588760
6. Biscaia, R. (2015). Spectators’ experiences at the sport and entertainment facility: The key for increasing attendance over the season. Sport & Entertainment Review, 1(2), 57–64.
7. Boehmer, J. (2025). It’s all about community: how new niche sports franchises can create highly engaged fans that are willing to pay more. European Sport Management Quarterly, 25(6), 966-987. https://doi.org/10.1080/16184742.2025.2462643
8. Büyüköztürk, Ş. (2018). Sosyal bilimler için veri analizi el kitabı (24 ed.). Pegem Akademik.

9. Cattell, R. B., & Baggaley, A. R. (1960). The salient variable similarity index for factor matching. British Journal of Statistical Psychology, 13(1), 33-46. https://doi. org/10.1111/J.2044-8317.1960.TB00037.X
10. Chiu, W., Kim, T., & Won, D. (2018). Predicting consumers’ intention to purchase sporting goods online: An application of the model of goal-directed behavior. Asia Pacific Journal of Marketing and Logistics, 30(2), 333-351. https://doi.org/10.1108/APJML-02-2017-0028
11. Coates, D., & Humphreys, B. R. (2007). Ticket prices, concessions and attendance at professional sporting events. International Journal of Sport Finance, 2(3), 161. https://doi.org/10.1177/155862350700200305
12. Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2012). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (Vol. 2). Ankara: Pegem akademi.
13. Delia, E. B., Melton, E. N., Sveinson, K., Cunningham, G. B., & Lock, D. (2022). Understanding the lack of diversity in sport consumer behavior research. Journal of Sport Management, 36(3), 265-276. https://doi.org/10.1123/jsm.2021-0227
14. Field, A. (2005). Discovering statistics using SPSS. Sage.
15. Filo, K., Lock, D., & Karg, A. (2015). Sport and social media research: A review. Sport Management Review, 18 (2), 166–181. https://doi.org/10.1016/j.smr.2014.11.001
16. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. https://doi.org/10.2307/3151312
17. Glebova, E., Desbordes, M., & Geczi, G. (2022). Mass diffusion of modern digital technologies as the main driver of change in sports-spectating audiences. Frontiers in Psychology, 13, 805043. https://doi.org/10.3389/fpsyg.2022.805043
18. Gogoi, B. (2013). Study of antecedents of purchase intention and its effect on brand loyalty of private label brand of apparel. International Journal of Sales & Marketing, 3(2), 73-78.
19. Grainger, A., Andrews, D. L., & Yang, J. (2025). Sport consumption across cultures. In Handbook on Sport and Culture (pp. 246-263). Edward Elgar Publishing. https://doi.org/10.4337/9781035339983.00031
20. Gürbüz, S. (2019). AMOS ile yapısal eşitlik modellemesi. Seçkin Yayıncılık.
21. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Exploratory factor analysis. Multivariate data analysis, 7, 100-100.
22. Hutchins, B., & Rowe, D. (2012). Sport beyond television: The internet, digital media and the rise of networked media sport. Routledge. http://dx.doi.org/10.1123/IJSC.2014-0029
23. Karaçam, Z. (2019). Ölçme araçlarının Türkçe’ye uyarlanması. Ebelik ve Sağlık Bilimleri Dergisi, 2(1), 28-37. https://izlik.org/JA86CE46MY
24. Karagöz, Yalçın (2019). SPSS-AMOS-META Uygulamalı İstatistiksel Analizler. 2. Baskı. Ankara: Nobel Akademik Yayıncılık.
25. Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and gratifications research. The public opinion quarterly, 37(4), 509-523.
26. King, S., & Karabas, I. (2025). The effect of message framing and team identification on sport consumption: A regulatory focus perspective. Journal of Global Scholars of Marketing Science, 35(3), 282-297. https://doi.org/10.1080/21639159.2025.2501038
27. Kline, T. (2005). Psychological testing: A practical approach to design and evaluation. Sage.
28. Koronios, K., Travlos, A., Douvis, J., & Papadopoulos, A. (2020). Sport, media and actual consumption behavior: An examination of spectator motives and constraints for sport media consumption. EuroMed Journal of Business, 15(2), 151-166. https://doi.org/10.1108/EMJB-10-2019-0130
29. Kural, S., & Özbek, O. (2023). Sports consumption behaviors of football fans: the relationship between social identity, team loyalty and behavioral intention toward consumption. Sport, Business and Management: An International Journal, 13(6), 685-703. https://doi.org/10.1108/SBM-08-2022-0069
30. Lee, J. H. (2021a). Effect of sports psychology on enhancing consumer purchase intention for retailers of sports shops: Literature content analysis. Journal of Distribution Science, 19(4), 5-13. DOI: 10.15722/jds.19.4.202104.5
31. Lee, J.K. (2021b). The effects of team identification on consumer purchase intention in sports in-fluencer marketing: The mediation effect of ad content value moderated by sports influencercredibility. Cogent Business and Management, 8(1). https://doi.org/10.1080/23311975.2021.1957073.
32. Lee, S., Lee, Y., & Kang, M. (2025). Association between team identification and sport consumption behaviors: A meta-analysis. Journal of Global Sport Management, 10(2), 252-276. https://doi.org/10.1080/24704067.2023.2246137
33. Leszczyński, M., Metelski, A., & Litwiński, M. (2023). Modern sport fans and their purchase intentions. Ekonomia-Wroclaw Economic Review, 29(4), 117-135. DOI: 10.19195/2658-1310.29.4.9
34. Meydan, C. H., & Şeşen, H. (2015). Yapısal eşitlik modellemesi AMOS uygulamaları. Detay Yayıncılık.
35. Neale, J. M., & Liebert, R. M. (1973). Science and behavior: An introduction to methods of research. Prentice-Hall International, Inc.
36. Nikkhah, M., Heravi-Karimooi, M., Montazeri, A., Rejeh, N., & Sharif Nia, H. (2018). Psychometric properties the Iranian version of older People’s quality of life questionnaire (OPQOL). Health and quality of life outcomes, 16(1), 174. https://doi.org/10.1186/s12955-018-1002-z
37. Nunnally, J. C., & Bernstein, I. H. (1967). Psychometric theory. McGraw-Hill.
38. Park, J. A., & Dittmore, S. (2014). The relationship among social media consumption, team identification, and behavioral intentions. Journal of Physical Education and Sport, 14, 331-336. http://dx.doi.org/10.2139/ssrn.2504608
39. Phua, J., Jin, S. V., & Kim, J. J. (2017). Gratifications of using Facebook, Twitter, Instagram, or Snapchat to follow brands: The moderating effect of social comparison, trust, tie strength, and network homophily on brand identification, brand engagement, brand commitment, and membership intention. Telematics and Informatics, 34(1), 412-424. https://doi.org/10.1016/j.tele.2016.06.004
40. Sutrisno, S. (2023). Changes in media consumption patterns and their implications for people's cultural identity. Technology and Society Perspectives (TACIT), 1(1), 18-25. https://doi.org/10.61100/tacit.v1i1.31
41. Staab, P., & Thiel, T. (2022). Social media and the digital structural transformation of the public sphere. Theory, Culture & Society, 39(4), 129-143. https://doi.org/10.1177/02632764221103527
42. Şencan, H. (2005). Sosyal ve davranışsal ölçümlerde güvenilirlik ve geçerlilik. Seçkin Yayıncılık.
43. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2013). Using multivariate statistics (Vol. 6). Pearson Boston, MA.
44. Tavşancıl, E. (2018). Tutumların ölçülmesi ve SPSS ile veri analizi (6 ed.). Nobel.
45. Trail, G. T., Dees, W., & Bang, H. (2025). The Varied Influence of Social and Digital Media Channels on Sport Consumption Intentions. Journal of Global Sport Management, 1-25. https://doi.org/10.1080/24704067.2025.2512236
46. Xiao, X., Tan, F. T. C., Lim, E. T., Henningsson, S., Vatrapu, R., Hedman, J., ... & Van Hillegersberg, J. (2018). Sports digitalization: An overview and A research agenda. In 38th International Conference on Information Systems, ICIS 2017.
47. Warm, D. L. (2002). Preliminary validation of a measure for assessing identification as a sport fan: The Sport Fandom Questionnaire. International Journal of Sport Management, 3, 103-115.
48. Watkins, M. W. (2018). Exploratory factor analysis: A guide to best practice. Journal of black psychology, 44(3), 219-246. https://doi.org/10.1177/0095798418771807
49. Yaşlıoğlu, M. M. (2017). Sosyal bilimlerde faktör analizi ve geçerlilik: Keşfedici ve doğrulayıcı faktör analizlerinin kullanılması. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 46, 74-85. https://izlik.org/JA83ZA74BA
50. Zhang, Y., Hou, Y., Cao, L., Xiong, Y., & Huang, Q. (2023). Analyzing the influence of internet usage behavior on spectator sports consumption among college students: An empirical SEM study based on the SOR model. Journal of Internet Technology, 24(6), 1379-1389. DOI: 10.53106/160792642023112406020