Adaptation of the Consumer Wisdom Scale into Turkish

Year 2025, Volume: 32 Issue: 3, 501 - 515, 25.09.2025

Mertcan Taşçıoğlu

https://doi.org/10.18657/yonveek.1631932

Abstract

This study deals with the adaptation of the Consumer Wisdom Scale (CWS), the original English version of which is the ‘Consumer Wisdom Scale’ (CWS), into Turkish and a systematic process involving psychometric validity-reliability analyses. Consumer wisdom is a multidimensional construct that represents the ability of individuals to make informed, ethical and sustainable consumption decisions. In the study, back translation method was used to ensure the cross-cultural validity of the scale, and language and conceptual equivalence were tested with expert opinions. The sample consists of 287 undergraduate students representing social and economic diversity, a group widely acknowledged in the marketing literature as a meaningful consumer segment. Confirmatory factor analysis (CFA) for structural validity, Cronbach's alpha and composite reliability analyses were applied for reliability. CFA results showed that the scale retained its original structure (6 sub-dimensions: reasoning, purpose, flexibility, perspective, responsibility, sustainability) and the fit indices were at an acceptable level. Cronbach's alpha and composite reliability values indicate high internal consistency. The Turkish version not only enables more comprehensive analyses of consumer behavior but also offers new opportunities for research on ethical consumption, sustainability, and value-driven decision making. Thus, the scale contributes to diversifying measurement tools and deepening consumer behavior research in the marketing literature.
Key Words: Scale Adaptation, Consumer Behavior, Consumer Wisdom
JEL Classification: M30, M31, M39

Keywords

Scale Adaptation , Consumer Behavior , Consumer Wisdom

Tüketici Bilgeliği Ölçeği'nin Türkçeye Uyarlanması

Abstract

Bu araştırma, orijinal İngilizce versiyonu "Consumer Wisdom Scale" (CWS) olan Tüketici Bilgeliği Ölçeği’nin Türkçeye uyarlanmasını ve psikometrik geçerlik-güvenirlik analizlerini kapsayan sistematik bir süreci ele almaktadır. Tüketici bilgeliği, bireylerin bilinçli, etik ve sürdürülebilir tüketim kararları alabilme yetkinliğini temsil eden çok boyutlu bir yapıdır. Araştırmada, ölçeğin kültürlerarası geçerliğini sağlamak için geri çeviri yöntemi kullanılmış, dil ve kavramsal eşdeğerlik uzman görüşleriyle test edilmiştir. Çalışmanın örneklemini, sosyal ve ekonomik çeşitliliği temsil eden 287 üniversite öğrencisi oluşturmaktadır; bu grup, pazarlama literatüründe önemli bir tüketici segmenti olarak kabul edilmektedir. Yapısal geçerlik için doğrulayıcı faktör analizi (DFA), güvenirlik için Cronbach alfa ve bileşik güvenilirlik analizleri uygulanmıştır. DFA sonuçları, ölçeğin orijinal yapısını koruduğunu (6 alt boyut: akıl yürütme, amaç, esneklik, perspektif, sorumluluk, sürdürülebilirlik) ve uyum indekslerinin kabul edilebilir düzeyde olduğunu göstermiştir. Cronbach alfa ve bileşik güvenilirlik değerleri yüksek iç tutarlılığa işaret etmektedir. Türkçe versiyon, hem bireysel tüketici davranışlarını daha kapsamlı analiz etmeyi mümkün kılmakta hem de etik tüketim, sürdürülebilirlik ve değerlerle uyumlu karar verme süreçlerine dair araştırmalara yeni açılımlar sunmaktadır. Böylece ölçek, pazarlama yazınında ölçüm araçlarının çeşitlenmesine ve tüketici davranışı araştırmalarının derinleşmesine önemli bir katkı sağlamaktadır.
Anahtar Kelimeler: Ölçek Uyarlama, Tüketici Davranışı, Tüketici Bilgeliği
JEL Sınıflandırması: M30, M31, M39

Keywords

Ölçek Uyarlama , Tüketici Davranışı , Tüketici Bilgeliği

Thanks

Bu çalışma kapsamında ölçeğin İngilizce ve Türkçe çevirilerinde ve Türkçe dil uygunluğunun değerlendirilmesinde verdikleri destekle katkı sağlayan Dr. Öğr. Üyesi Rıfgı Buğra Bağcı, Umut Ünal ve Ercan Saraçoğlu'na teşekkürlerimi sunarım.

References

• 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.
• Bahl, S., Milne, G. R., & Miller, E. G. (2023). Expanding consumer mindfulness for collective sustainable well‐being: Overview of the special issue and future research directions. Journal of Consumer Affairs, 57(2), 699-720.
• Escadas, M., Jalali, M. S., & Farhangmehr, M. (2020). What goes around comes around: The integrated role of emotions on consumer ethical decision‐making. Journal of Consumer Behaviour, 19(5), 409-422.
• Fornell, C. and Larcker, D.F. (1981), “Evaluating Structural Equation Models with Unobservable Variables and Measurement Error”, Journal of Marketing Research, Vol. 18 No. 1, doi: 10.1177/002224378101800104.
• Ganassali, S., & Matysiewicz, J. (2021). “What a lot of things I don’t need!”: consumption satiation, self-transcendence and consumer wisdom. Journal of Consumer Marketing, 38(5), 540-551.
• 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. www.cengage.com/highered
• Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). An Introduction to Structural Equation Modeling. 1–29. https://doi.org/10.1007/978-3-030-80519-7_1
• He, H., & Mukherjee, A. (2007). I am, ergo I shop: does store image congruity explain shopping behaviour of Chinese consumers?. Journal of Marketing Management, 23(5-6), 443-460.
• Hopcan, S., Polat, E., & Türkmen, G. (2021). Validity and reliability study of a Turkish form of the machine learning attitude scale. Research on Education and Psychology, 5(2), 246-266.
• Hu, L., & 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). https://doi.org/10.1080/10705519909540118
• Im, H., Lee, G., & Parr, J. (2023). Why consumers support local: Moral foundations theory and identity perspective. Journal of Consumer Marketing, 40(1), 15-26.
• Kahneman, D., & Tversky, A. (2013). Prospect theory: An analysis of decision under risk. In Handbook of the fundamentals of financial decision making: Part I (pp. 99-127).
• Kidwell, B., Hardesty, D. M., & Childers, T. L. (2008). Consumer emotional intelligence: Conceptualization, measurement, and the prediction of consumer decision making. Journal of Consumer Research, 35(1), 154-166.
• Kim, C., Lee, H., & Tomiuk, M. A. (2009). Adolescents' perceptions of family communication patterns and some aspects of their consumer socialization. Psychology & Marketing, 26(10), 888-907.
• Kline, R. B. (2023). Principles and practice of structural equation modeling. Guilford publications.
• Li, Y., Geng, L., Chang, Y., & Ning, P. (2023). Research online and purchase offline: The disruptive impact of consumers' online information on offline sales interaction. Psychology & Marketing, 40(12), 2642-2652.
• Loebnitz, N., & Grunert, K. G. (2019). The moderating impact of perceived globalness on consumers’ purchase intentions for copycats: The pleasure of hurting global brands. Psychology & Marketing, 36(10), 936-950.
• 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.
• Luchs, M. G., & Mick, D. G. (2018). Consumer wisdom: A theoretical framework of five integrated facets. Journal of Consumer Psychology, 28(3), 365-392.
• Luchs, M. G., Mick, D. G., & Haws, K. L. (2021). Consumer wisdom for personal well‐being and the greater good: Scale development and validation. Journal of Consumer Psychology, 31(3), 587-611.
• Ortiz, J. A., Santos Corrada, M., Perez, S., Dones, V., & Rodriguez, L. H. (2024). Exploring the influence of uncontrolled social media use, fear of missing out, fear of better options, and fear of doing anything on consumer purchase intent. International Journal of Consumer Studies, 48(1), e12990.
• 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/FULL/PDF
• Mrisha, S. H., & Xixiang, S. (2024). The power of influence: How social media influencers are shaping consumer decision making in the digital age. Journal of Consumer Behaviour.
• Orçan, F. (2018). Exploratory and confirmatory factor analysis: which one to use first?. Journal of Measurement and Evaluation in Education and Psychology, 9(4), 414-421.
• Ovaz, F., & Haşıloğlu, S. B. (2024). Pazarlama Araştırmalarında Ölçekleri̇n Türkçeye Uyarlama Süreci̇ne Yöneli̇k Karar Ağacı Tabanlı Bi̇r Yaklaşım. Pazarlama Ve Pazarlama Araştırmaları Dergisi, 17(3), 775-800.
• Sangari, M. S., & Mashatan, A. (2024). What is driving consumer resistance to crypto‐payment? A multianalytical investigation. Psychology & Marketing, 41(3), 575-591.
• Simon, H. A. (1986). Rationality in psychology and economics. Journal of business, S209-S224.
• Sharma, K., Aswal, C., & Paul, J. (2023). Factors affecting green purchase behavior: A systematic literature review. Business Strategy and the Environment, 32(4), 2078-2092.
• Shaw, D., Grehan, E., Shiu, E., Hassan, L., & Thomson, J. (2005). An exploration of values in ethical consumer decision making. Journal of Consumer Behaviour: An International Research Review, 4(3), 185-200.
• Ünal, 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 platform through self‐enhancement motive. Journal of Consumer Behaviour, 21(3), 468-480. https://doi.org/10.1002/cb.1973.