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Adaptation of the Online Susceptibility Scale into Turkish

Year 2025, Volume: 9 Issue: 2, 939 - 949, 25.05.2025
https://doi.org/10.25295/fsecon.1588934

Abstract

Accurately measuring customer susceptibility to online shopping experiences plays an increasingly large role in businesses' strategic decisions and academic studies. This study aims to adapt the Online Susceptibility Scale into Turkish and test its validity and reliability in this context. Linguistic and contextual adaptation processes were carefully carried out to make an internationally valid scale usable in the context of Turkish consumers. The scale items were back-translated into Turkish with the opinions of experts, and then the final adapted version of the scale was created by evaluating the linguistic and semantic equivalence. The research data was collected from 257 participants with online shopping experience, and the factor analysis of the scale was analyzed using the Confirmatory Factor Analysis (CFA). The findings indicate that the scale retains its original structure and that the Turkish Online Susceptibility Scale can be used as a reliable and valid instrument to examine online shopping behaviors. The study contributes to the addition of a Turkish scale to the marketing literature and allows for a more in-depth investigation of online shopper behaviors.

References

  • Aghekyan-Simonian, M., Forsythe, S., Kwon, W. S. & Chattaraman, V. (2012). The role of product brand image and online store image on perceived risks and online purchase intentions for apparel. Journal of Retailing and Consumer Services, 19(3), 325–331.
  • Akram, U. (2023). Understanding the consumer’s luxury webrooming intention: Moderating role of perceived risk and review. Journal of Consumer Behaviour, 23(3), 1602–1619. https://doi.org/10.1002/cb.2295
  • Baumgartner, H. & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review. International Journal of Research in Marketing, 13(2), 139–161. https://doi.org/10.1016/0167-8116(95)00038-0
  • Bollen, K. A. (1989). Structural equations with latent variables. Wiley Interscience.
  • Chrimes, C., Boardman, R., Vignali, G. & McCormick, H. (2022). Investigating how online fashion product page design affects the consumer’s clothing fit appraisal. Journal of Consumer Behaviour, 21(6), 1478–1493. https://doi.org/10.1002/cb.2100
  • Cowart, K. & Goldsmith, R. E. (2007). The influence of consumer decision‐making styles on online apparel consumption by college students. International Journal of Consumer Studies, 31(6), 639–647. https://doi.org/10.1111/j.1470-6431.2007.00615.x
  • Dhaigude, S. A. & Mohan, B. C. (2023). Customer experience in social commerce: A systematic literature review and research agenda. International Journal of Consumer Studies, 47(5), 1629–1668. https://doi.org/10.1111/ijcs.12954
  • Duong, C. (2023). The effect of shopping channel (online vs. offline) on message framing of naturalness. Journal of Consumer Behaviour, 23(2), 987–1001. https://doi.org/10.1002/cb.2259
  • Fernandes, S., Venkatesh, V. G., Panda, R. & Shi, Y. (2021). Measurement of factors influencing online shopper buying decisions: A scale development and validation. Journal of Retailing and Consumer Services, 59, 102394. https://doi.org/10.1016/j.jretconser.2020.102394
  • 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/10.1177/002224378101800104
  • George, A., Joseph, A., Mathew, A. & Joseph, E. T. (2023). Brand trust and engagement in social commerce. International Journal of Consumer Studies, 47(5), 1791–1809. https://doi.org/10.1111/ijcs.12947
  • Gold, A. H., Malhotra, A. & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214. https://doi.org/10.1080/07421222.2001.11045669
  • Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning EMEA.
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P. & Ray, S. (2021). An introduction to structural equation modeling. In Partial least squares structural equation modeling (PLS-SEM) (1–29). Springer. https://doi.org/10.1007/978-3-030-80519-7_1
  • Halibas, A. S., Nguyen, A. T. V., Akbari, M., Akram, U. & Hoang, M. H. (2023). Developing trends in showrooming, webrooming, and omnichannel shopping behaviors: Performance analysis, conceptual mapping, and future directions. Journal of Consumer Behaviour, 22(5), 1237–1264. https://doi.org/10.1002/cb.2186
  • Hu, L. & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • Kanwal, M., Burki, U., Raza, A. & Dahlstrøm, R. (2021). Systematic review of gender differences and similarities in online consumers’ shopping behavior. Journal of Consumer Marketing, 39(1), 29–43. https://doi.org/10.1108/JCM-01-2021-4356
  • Katsikeas, C. S., Madan, S., Brendl, C. M., Calder, B. J., Lehmann, D. R., Baumgartner, H. & Huber, J. (2022). Commentaries on “Scale use and abuse: Toward best practices in the deployment of scales.” Journal of Consumer Psychology, 33(1), 244–258. https://doi.org/10.1002/jcpy.1319
  • Kim, M. (2022). How can I be as attractive as a fitness YouTuber in the era of COVID-19? The impact of digital attributes on flow experience, satisfaction, and behavioral intention. Journal of Retailing and Consumer Services, 64,102778. https://doi.org/10.1016/j.jretconser.2021.102778
  • LaCour, M. & Serra, M. J. (2021). Average user ratings prompt disparate decision strategies in online retail shopping. Journal of Consumer Behaviour, 21(2), 231–244. https://doi.org/10.1002/cb.1995
  • Lorenzo-Seva, U. & Ferrando, P. J. (2021). MSA: The forgotten index for identifying inappropriate items before computing exploratory item factor analysis. Methodology, 17(4), 296–306.
  • Martínez-López, F. J., Gázquez-Abad, J. C. & Sousa, C. M. P. (2013). Structural equation modelling in marketing and business research: Critical issues and practical recommendations. European Journal of Marketing, 47(1), 115–152. https://doi.org/10.1108/03090561311285484
  • Natarajan, M. (2024). Revealing consumer review attitude through online review and website cues. Journal of Consumer Marketing, 41(3), 261–280. https://doi.org/10.1108/JCM-07-2020-3938
  • Nikbin, D., Aramo, T., Iranmanesh, M. & Ghobakhloo, M. (2022). Impact of brands’ Facebook page characteristics and followers’ comments on trust building and purchase intention: Alternative attractiveness as moderator. Journal of Consumer Behaviour, 21(3), 494–508. https://doi.org/10.1002/cb.2018
  • Oghazi, P., Karlsson, S., Hellström, D. & Hjort, K. (2018). Online purchase return policy leniency and purchase decision: Mediating role of consumer trust. Journal of Retailing and Consumer Services, 41, 190–200.
  • Rahmani, V. & Kordrostami, E. (2023). Price sensitivity and online shopping behavior during the COVID-19 pandemic. Journal of Consumer Marketing, 40(4), 481–492. https://doi.org/10.1108/JCM-07-2021-4777
  • Rasty, F., Mirghafoori, S. H., Ardekani, S. S. & Ajdari, P. (2020). Trust barriers to online shopping: Investigating and prioritizing trust barriers in an intuitionistic fuzzy environment. International Journal of Consumer Studies, 45(5), 1030–1046. https://doi.org/10.1111/ijcs.12629
  • Singh, D. (2023). The dimensions and roles of online content in social commerce: A systematic literature review and future research agenda. International Journal of Consumer Studies, 48(1). https://doi.org/10.1111/ijcs.13004
  • Stenius, M. & Eriksson, N. (2022). What beliefs underlie decisions to buy groceries online? International Journal of Consumer Studies, 47(3), 922–935. https://doi.org/10.1111/ijcs.12874
  • Sun, B., Liang, T. & Zhao, S. (2023). How online reviews with different influencing factors affect the diffusion of new products. International Journal of Consumer Studies, 47(4), 1377–1396. https://doi.org/10.1111/ijcs.12915
  • Szász, L., Bálint, C., Csíki, O., Nagy, B. Z., Rácz, B.-G., Csala, D. & Harris, L. C. (2022). The impact of COVID-19 on the evolution of online retail: The pandemic as a window of opportunity. Journal of Retailing and Consumer Services, 69, 103089. https://doi.org/10.1016/j.jretconser.2022.103089
  • Unal, U. (2021). Structural equation modeling as a marketing research tool: A guideline for SEM users about critical issues and problematic practices. İstatistik ve Uygulamalı Bilimler Dergisi, 2(2), 65–77.
  • Wu, Y., Niu, G., Chen, Z. & Zhang, D. (2021). Purchasing social attention by tipping: Materialism predicts online tipping in live‐streaming platforms through self‐enhancement motive. Journal of Consumer Behaviour, 21(3), 468–480. https://doi.org/10.1002/cb.1973
  • Yasin, M. M., Liébana‐Cabanillas, F., Porcu, L. & Kayed, R. N. (2020). The role of customer online brand experience in customers' intention to forward online company-generated content: The case of the Islamic online banking sector in Palestine. Journal of Retailing and Consumer Services, 52, 101902. https://doi.org/10.1016/j.jretconser.2019.101902

Çevrim içi Müşteri Hassasiyeti Ölçeği'nin Türkçe'ye Uyarlanması

Year 2025, Volume: 9 Issue: 2, 939 - 949, 25.05.2025
https://doi.org/10.25295/fsecon.1588934

Abstract

Çevrim içi alışveriş deneyimlerinde müşterilerin hassasiyetlerini doğru bir şekilde ölçmek, işletmelerin stratejik kararlarında ve akademik çalışmalarda giderek daha büyük bir rol oynamaktadır. Bu çalışmada, Çevrim içi Müşteri Hassasiyeti Ölçeği’nin Türkçe’ye uyarlanması ve bu bağlamda geçerlilik ve güvenilirliğinin test edilmesi hedeflenmiştir. Uluslararası geçerliliği olan bir ölçeğin Türk tüketicileri bağlamında kullanılabilir hale getirilmesi için dilsel ve bağlamsal uyarlama süreçleri dikkatle yürütülmüştür. Ölçek maddeleri uzmanların görüşleriyle geri-çeviri yöntemiyle Türkçeleştirilmiş, ardından dil ve anlam eşdeğerliğini değerlendirilip ölçeğin son uyarlanmış hali oluşturulmuştur. Araştırma verisi, çevrim içi alışveriş deneyimi olan 257 katılımcıdan toplanmış ve Doğrulayıcı Faktör Analizi (DFA) kullanılarak ölçeğin faktör yapısı incelenmiştir. Bulgular, ölçeğin orijinal yapısını koruduğunu ve Türkçe Çevrim içi Müşteri Hassasiyeti Ölçeği'nin çevrim içi alışveriş davranışlarının incelenmesinde güvenilir ve geçerli bir araç olarak kullanılabileceğini göstermektedir. Çalışma, pazarlama literatürüne Türkçe ölçüm araçlarının eklenmesine katkı sağlamakta ve çevrim içi müşteri davranışlarının daha derinlemesine araştırılmasına olanak tanımaktadır.

References

  • Aghekyan-Simonian, M., Forsythe, S., Kwon, W. S. & Chattaraman, V. (2012). The role of product brand image and online store image on perceived risks and online purchase intentions for apparel. Journal of Retailing and Consumer Services, 19(3), 325–331.
  • Akram, U. (2023). Understanding the consumer’s luxury webrooming intention: Moderating role of perceived risk and review. Journal of Consumer Behaviour, 23(3), 1602–1619. https://doi.org/10.1002/cb.2295
  • Baumgartner, H. & Homburg, C. (1996). Applications of structural equation modeling in marketing and consumer research: A review. International Journal of Research in Marketing, 13(2), 139–161. https://doi.org/10.1016/0167-8116(95)00038-0
  • Bollen, K. A. (1989). Structural equations with latent variables. Wiley Interscience.
  • Chrimes, C., Boardman, R., Vignali, G. & McCormick, H. (2022). Investigating how online fashion product page design affects the consumer’s clothing fit appraisal. Journal of Consumer Behaviour, 21(6), 1478–1493. https://doi.org/10.1002/cb.2100
  • Cowart, K. & Goldsmith, R. E. (2007). The influence of consumer decision‐making styles on online apparel consumption by college students. International Journal of Consumer Studies, 31(6), 639–647. https://doi.org/10.1111/j.1470-6431.2007.00615.x
  • Dhaigude, S. A. & Mohan, B. C. (2023). Customer experience in social commerce: A systematic literature review and research agenda. International Journal of Consumer Studies, 47(5), 1629–1668. https://doi.org/10.1111/ijcs.12954
  • Duong, C. (2023). The effect of shopping channel (online vs. offline) on message framing of naturalness. Journal of Consumer Behaviour, 23(2), 987–1001. https://doi.org/10.1002/cb.2259
  • Fernandes, S., Venkatesh, V. G., Panda, R. & Shi, Y. (2021). Measurement of factors influencing online shopper buying decisions: A scale development and validation. Journal of Retailing and Consumer Services, 59, 102394. https://doi.org/10.1016/j.jretconser.2020.102394
  • 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/10.1177/002224378101800104
  • George, A., Joseph, A., Mathew, A. & Joseph, E. T. (2023). Brand trust and engagement in social commerce. International Journal of Consumer Studies, 47(5), 1791–1809. https://doi.org/10.1111/ijcs.12947
  • Gold, A. H., Malhotra, A. & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214. https://doi.org/10.1080/07421222.2001.11045669
  • Hair, J. F., Black, W. C., Babin, B. J. & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning EMEA.
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P. & Ray, S. (2021). An introduction to structural equation modeling. In Partial least squares structural equation modeling (PLS-SEM) (1–29). Springer. https://doi.org/10.1007/978-3-030-80519-7_1
  • Halibas, A. S., Nguyen, A. T. V., Akbari, M., Akram, U. & Hoang, M. H. (2023). Developing trends in showrooming, webrooming, and omnichannel shopping behaviors: Performance analysis, conceptual mapping, and future directions. Journal of Consumer Behaviour, 22(5), 1237–1264. https://doi.org/10.1002/cb.2186
  • Hu, L. & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • Kanwal, M., Burki, U., Raza, A. & Dahlstrøm, R. (2021). Systematic review of gender differences and similarities in online consumers’ shopping behavior. Journal of Consumer Marketing, 39(1), 29–43. https://doi.org/10.1108/JCM-01-2021-4356
  • Katsikeas, C. S., Madan, S., Brendl, C. M., Calder, B. J., Lehmann, D. R., Baumgartner, H. & Huber, J. (2022). Commentaries on “Scale use and abuse: Toward best practices in the deployment of scales.” Journal of Consumer Psychology, 33(1), 244–258. https://doi.org/10.1002/jcpy.1319
  • Kim, M. (2022). How can I be as attractive as a fitness YouTuber in the era of COVID-19? The impact of digital attributes on flow experience, satisfaction, and behavioral intention. Journal of Retailing and Consumer Services, 64,102778. https://doi.org/10.1016/j.jretconser.2021.102778
  • LaCour, M. & Serra, M. J. (2021). Average user ratings prompt disparate decision strategies in online retail shopping. Journal of Consumer Behaviour, 21(2), 231–244. https://doi.org/10.1002/cb.1995
  • Lorenzo-Seva, U. & Ferrando, P. J. (2021). MSA: The forgotten index for identifying inappropriate items before computing exploratory item factor analysis. Methodology, 17(4), 296–306.
  • Martínez-López, F. J., Gázquez-Abad, J. C. & Sousa, C. M. P. (2013). Structural equation modelling in marketing and business research: Critical issues and practical recommendations. European Journal of Marketing, 47(1), 115–152. https://doi.org/10.1108/03090561311285484
  • Natarajan, M. (2024). Revealing consumer review attitude through online review and website cues. Journal of Consumer Marketing, 41(3), 261–280. https://doi.org/10.1108/JCM-07-2020-3938
  • Nikbin, D., Aramo, T., Iranmanesh, M. & Ghobakhloo, M. (2022). Impact of brands’ Facebook page characteristics and followers’ comments on trust building and purchase intention: Alternative attractiveness as moderator. Journal of Consumer Behaviour, 21(3), 494–508. https://doi.org/10.1002/cb.2018
  • Oghazi, P., Karlsson, S., Hellström, D. & Hjort, K. (2018). Online purchase return policy leniency and purchase decision: Mediating role of consumer trust. Journal of Retailing and Consumer Services, 41, 190–200.
  • Rahmani, V. & Kordrostami, E. (2023). Price sensitivity and online shopping behavior during the COVID-19 pandemic. Journal of Consumer Marketing, 40(4), 481–492. https://doi.org/10.1108/JCM-07-2021-4777
  • Rasty, F., Mirghafoori, S. H., Ardekani, S. S. & Ajdari, P. (2020). Trust barriers to online shopping: Investigating and prioritizing trust barriers in an intuitionistic fuzzy environment. International Journal of Consumer Studies, 45(5), 1030–1046. https://doi.org/10.1111/ijcs.12629
  • Singh, D. (2023). The dimensions and roles of online content in social commerce: A systematic literature review and future research agenda. International Journal of Consumer Studies, 48(1). https://doi.org/10.1111/ijcs.13004
  • Stenius, M. & Eriksson, N. (2022). What beliefs underlie decisions to buy groceries online? International Journal of Consumer Studies, 47(3), 922–935. https://doi.org/10.1111/ijcs.12874
  • Sun, B., Liang, T. & Zhao, S. (2023). How online reviews with different influencing factors affect the diffusion of new products. International Journal of Consumer Studies, 47(4), 1377–1396. https://doi.org/10.1111/ijcs.12915
  • Szász, L., Bálint, C., Csíki, O., Nagy, B. Z., Rácz, B.-G., Csala, D. & Harris, L. C. (2022). The impact of COVID-19 on the evolution of online retail: The pandemic as a window of opportunity. Journal of Retailing and Consumer Services, 69, 103089. https://doi.org/10.1016/j.jretconser.2022.103089
  • Unal, U. (2021). Structural equation modeling as a marketing research tool: A guideline for SEM users about critical issues and problematic practices. İstatistik ve Uygulamalı Bilimler Dergisi, 2(2), 65–77.
  • Wu, Y., Niu, G., Chen, Z. & Zhang, D. (2021). Purchasing social attention by tipping: Materialism predicts online tipping in live‐streaming platforms through self‐enhancement motive. Journal of Consumer Behaviour, 21(3), 468–480. https://doi.org/10.1002/cb.1973
  • Yasin, M. M., Liébana‐Cabanillas, F., Porcu, L. & Kayed, R. N. (2020). The role of customer online brand experience in customers' intention to forward online company-generated content: The case of the Islamic online banking sector in Palestine. Journal of Retailing and Consumer Services, 52, 101902. https://doi.org/10.1016/j.jretconser.2019.101902
There are 34 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Articles
Authors

Mertcan Taşçıoğlu 0000-0003-4024-2453

Publication Date May 25, 2025
Submission Date November 21, 2024
Acceptance Date January 6, 2025
Published in Issue Year 2025 Volume: 9 Issue: 2

Cite

APA Taşçıoğlu, M. (2025). Çevrim içi Müşteri Hassasiyeti Ölçeği’nin Türkçe’ye Uyarlanması. Fiscaoeconomia, 9(2), 939-949. https://doi.org/10.25295/fsecon.1588934

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