Experienced Problems with Online Shopping: The Case of Turkey

Year 2022, Volume: 9 Issue: Special Issue 2nd International Symposium of Sustainable Logistics “Circular Economy”, 87 - 96, 09.12.2022

Şeyda Ünver Ömer Alkan

https://doi.org/10.54709/iisbf.1152952

Cited By: 1

Abstract

This study’s objective is to investigate the sociodemographic and economic elements that are important in cases when people experience problems with their online purchases. A microdata set from the 2021 Information and Communication Technology Usage Survey in Households conducted by the Turkish Statistical Institute is used in the study. The factors connected to the problem individuals have with online purchases have been determined using binary logistic regression analysis. In the data set included in the analysis in this study, 52.4% of the men reported that they had encountered problems with their purchases made on the website or mobile application in the last three months. According to the study, 51.9% of individuals in the eastern region reported having difficulty with transactions made through a website or mobile application. As a result of the research, it has been discovered that education level, income level, age, gender, profession, family size, financial transactions conducted over the Internet, and regional characteristics are all linked to experiencing problems with online shopping.

Keywords

online shopping, binary logistic regression, Turkey.

References

• Ağaç, S., Sevinir, S. D., & Yılmaz, T. (2018). Online Giyim Alışverişinde Tüketicilerin Karşılaştıkları Sorunların Cinsiyet Değişkenine Göre İncelenmesi. Karadeniz Teknik Üniversitesi Sosyal Bilimler Enstitüsü Sosyal Bilimler Dergisi, 8 (15), 57-71.
• Akman, I., & Mishra, A. (2010). Gender, age and income differences in internet usage among employees in organizations. Computers in Human Behavior, 26, 482–490.
• Akman, I. & M. Rehan, (2014). Online purchase behaviour among professionals: a socio-demographic perspective for Turkey. Economic Research-Ekonomska Istraživanja, 27 (1), 689-699.
• Alam, S.S., et al., (2008). Young consumers online shopping: an empirical study. Journal of Internet Business, (5), 81-98.
• Alkan, Ö., Oktay, E., & Genç, A. (2015). Determination of Factors Affecting the Children's Internet Use. American International Journal of Contemporary Research, 5(6), 57-67.
• Alkan, Ö., Oktay, E., Ünver, Ş., & Gerni, E. (2020). Determination of Factors Affecting the Financial Literacy of University Students in Eastern Anatolia Using Ordered Regression Models, Asian Economic and Financial Review, 10(5), 536-546.
• Alkan, Ö., & Ünver, Ş. (2020). Determinants of Domestic Physical Violence Against Women in Turkey. Humanities & Social Sciences Reviews, 8(6), 55-67.
• Alkan, Ö., & Ünver, Ş. (2020). Türkiye’de E-Devlet Hizmetlerinin Kullanımını Etkileyen Faktörlerin Analizi . Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 34(4), 1431-1453.
• Alkan, Ö., & Ünver, Ş. (2021). Determination of Factors That Affect Use of E-Commerce in Eastern Turkey Through Categorical Data Analysis. Toros University FEASS Journal of Social Sciences, 8(Special Issue), 22-36.
• Alkan, Ö., & Ünver, Ş. (2022). Secondhand smoke exposure for different education levels: findings from a large, nationally representative survey in Turkey. BMJ Open, 12:e057360., 1-12.
• Alkan, Ö., Özar, Ş., & Ünver, Ş. (2021). Economic violence against women: A case in Turkey. PLoS ONE 16(3): e0248630, 1-23.
• Alqahtani, A. S., Goodwin, R. D., & de Vries, D. B. (2018). Cultural factors influencing e-commerce usability in Saudi Arabia. International Journal of Advanced and Applied Sciences, 5 (6), 1-10.
• Alkibay, S., & Demirgunes, B. (2016). Evaluating Trust and Perceived Risk Dimensions in Online Clothing Shopping. Research Journal of Business and Management, 3 (2), 157-172. Almousa, M., (2011). Perceived risk in apparel online shopping: a multi dimensional perspective. Canadian Social Science, 7 (2), 23-31. Beneke, J., Scheffer, M., & Du, W. (2010). Beyond Price – An Exploration into the Factors That Drive Young Adults to Purchase Online. International Journal of Marketing Studies, 2(2), 212-222. Bhatnagar, A., & Ghose, S. (2004). A latent class segmentation analysis of e-shoppers. Journal of Business Research, 57, 758-67.
• Cheng, F., Liu, T., & Wu, C. (2013). Perceived Risks and Risk Reduction Strategies in Online Group-Bu. Perceived Risks and Risk Reduction Strategies in Online Group-Buying, (s. 18-25). Phuket, Thailand.
• Chirkov, V., et al., (2003). Differentiating autonomy from individualism and independence: A self-determination theory perspective on internalization of cultural orientations and well-being. Journal of Personality and Social Psychology, 84 (1), 97-110. Çera, G., et al., (2020). Financial capability and technology implications for online shopping. E&M Economics and Management, 23 (2), 156–172.
• Erceg, A. and Z. Kilic. (2018). Interconnection of e-commerce and logistics: examples from Croatia and Turkey. in Business Logistics in Modern Management. Osijek, Croatia: Boris Crnković, Dean of Faculty of Economics in Osijek Farag, S., Krizek, K. J., & Dijst, M. (2006). E-Shopping and its relationship with in-store shopping: Empirical evidence from the Netherlands and the USA. Transport Reviews, 26, 43–61.
• Ganesan-Lim, C., R. Russell-Bennett., & T. Dagger. (2008). The Impact of Service Contact Type and Demographic Characteristics on Service Quality Perceptions. Journal of Services Marketing, 22 (7), 550–561. Huseynov, F. and S.Ö. Yıldırım, (2016). Internet users’ attitudes toward business-to-consumer online shopping: A survey. Information Development, 32 (3),452-465. Hsu, S., & Bayarsaikhan, B. (2012). Factors Influencing on Online Shopping Attitude and Intention of Mongolian Consumers. The Journal of International Managemenet Studies, 7 (2), 167-176.
• Ko, H., et al., (2004). Cross-cultural differences in perceived risk of online shopping. Journal of Interactive Advertising, 4(2): p. 20-29. Lian, J.-W. and T.-M. Lin, (2008). Effects of consumer characteristics on their acceptance of online shopping: Comparisons among different product types. Computers in Human Behavior, 24(1), 48-65. Lightner, N.J., (2003). What users want in e-commerce design: effects of age, education and income. Ergonomics, 46 (1-3), 153-168. Lin, H.-F., (2007). Predicting consumer intentions to shop online: An empirical test of competing theories. Electronic Commerce Research and Applications, 6 (4), 433-442.
• Ono, H., & Zavodny, M. (2007). Digital inequality: A five country comparison using microdata. Social Science Research, 36(3), 1135-1155.
• Potosky, D. (2007). The Internet knowledge measure. Computers in HumanBehavior, 23, 2760–2777.
• Phung, K., K. Yen, and M. Hsiao. (2009). Examining the factors associated with consumer's trust in the context of business-to-consumer e-commerce. in International Conference on Industrial Engineering and Engineering Management. Hong Kong, China: IEEE.
• Ranganathan, C. and S. Ganapathy, (2002). Key dimensions of business-to-consumer web sites. Information & Management, 39 (6), 457-465.
• Smith, P., Smith, N., Sherman, K., Kriplani, K., Goodwin, I., Bell, A., & Crothers, C. (2008). The Internet: Social and Demographic Impacts in Aotearoa NewZealand. Observatorio (OBS) Journal, 6, 307–330.
• Usunier, J.-C., J.A. Lee, and J. Lee, Marketing across cultures. 2005, Harlow, Essex: Prentice Hall Financial Times.
• Ünver, Ş., & Alkan, Ö. (2020). Türkiye’de Bireylerin Maddi Yoksunluk Durumlarını Etkileyen Faktörlerin Modellenmesi. BMIJ, 8(2), 1334-1370.
• Ünver, Ş., & Alkan, Ö. (2021). Determinants of e-Commerce Use at Different Educational Levels: Empirical Evidence from Turkey. International Journal of Advanced Computer Science and Applications;12(3), 40-49.
• Yang, S. C., & Tung, C.-J. (2007). Comparison of Internet addicts and non-addicts in Taiwanese high school. Computers in Human Behavior, 23(1), 79-96.
• Yu, U., Lee, H., & Damhorst, M. (2012). Exploring Multidimensions of Product Performance Risk in the Online Apparel Shopping Context: Visual, Tactile and Trial Risks. Clothing & Textiles Research Journal, 30 (4), 251-266.
• Zhang, Y. (2005). Age, gender, and Internet attitudes among employees in the business world. Computers in Human Behavior, 21(1), 1–10.