COMPARING ONLINE SHOPPER AND NON-SHOPPER ELDERLY CONSUMERS BASED ON THE THEORY OF PLANNED BEHAVIOR: HOW DO THE DEMOGRAPHIC FACTORS MAKE A DIFFERENCE?

Year 2021, Volume: 14 Issue: 2, 8 - 24, 31.12.2021

Sevgi Ayşe Öztürk , Seran Yüksel

https://doi.org/10.18221/bujss.1004887

Abstract

Aging may lead to shopping difficulties for consumers and online shopping which is mostly associated with young consumers may provide elderly people easy access to the products needed. This article expands our understanding of online shopping behavior of elderly consumers by comparing elder consumers who had previous online shopping experience with the consumers without such an experience in terms of their demographic characteristics. Theory of Planned Behavior is used to explore the future online shopping intentions of two groups, their attitudes towards online shopping, perceived behavioral control and subjective norms. The findings of this research illustrate the differences between two groups in terms of age, education, and income. At the same time the research shows the importance of elderly consumers’ demographic characteristics especially on the perceived behavioral control dimension of The Theory of Planned Behavior.

Keywords

Older consumers, Online shopping, Theory of Planned Behavior, Demographic characteristics

Supporting Institution

No

Project Number

No

Thanks

No

ÇEVRİMİÇİ ALIŞVERİŞ YAPAN VE ALIŞVERİŞ YAPMAYAN YAŞLI TÜKETİCİLERİN PLANLI DAVRANIŞ TEORİSİNE GÖRE KARŞILAŞTIRILMASI: DEMOGRAFİK FAKTÖRLER NASIL FARK YARATIR?

Abstract

Yaşlanma tüketiciler için alışveriş yapma konusunda zorluklara neden olabilir ve genellikle genç tüketiciler ile ilişkilendirilen online alışveriş, yaşlı tüketicilerin ihtiyaç duydukları ürünlere daha kolay erişimini sağlayabilir. Bu makale online alışveriş deneyimi olan ve olmayan yaşlı tüketicileri demografik faktörler açısından karşılaştırarak yaşlı tüketicilerin online alışveriş davranışlarını anlamamıza yardımcı olmaktadır. Bu çalışmada Planlı Davranış Teorisi kullanılarak iki grup tüketici; online alışveriş yapma niyetleri, online alışverişe yönelik tutumları, algılanan davranışsal kontrol ve öznel normlar açısından karşılaştırılmıştır. Bu araştırmanın bulguları online alışveriş yapan ve yapmayan yaşlılar arasında yaş, eğitim ve gelir açısından farklılıklar olduğunu göstermektedir. Aynı zamanda araştırma yaşlı tüketicilerin demografik özelliklerinin Planlı Davranış Teorisinin algılanan davranışsal kontrol değişkeni üzerindeki önemli etkisini ortaya koymaktadır.

Keywords

Planlı Davranış Teorisi, Yaşlı Tüketiciler, Online Alışveriş, Demografik Faktörler

Project Number

No

References

• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Process, 50, 179 – 211. https://doi.org/10.1016/0749-5978(91)90020-T
• Ajzen, I. (2011). The theory of planned behavior: Reactions and reflections. Psychology & Health, 26(9), 1113 – 1127. https://doi.org/10.1080/08870446.2011.613995
• Chang, M.K., Cheung, W., & Lai, V, S. (2005). Literature derived reference models for the adoption of online shopping. Information & Management, 42(4), 543 – 559. https://doi.org/10.1016/j.im.2004.02.006
• Chakraborty, R., Lee, J., Bagchi-Sen, S., Upadhyaya, S., & Rao, H.R. (2016). Online shopping intention in the context of data breach in online retail stores: An examination of older and younger adults. Decision Support Systems, 83, 47 – 56. https://doi.org/10.1016/j.dss.2015.12.007
• Daoust, J.-F. (2020). Elderly people and responses to COVID-19 in 27 countries. PLOS ONE. https://doi.org/10.1371/journal.pone.0235590
• Debicka, O., Gutowski, T., & Borodo, A. (2018, September 18-20). Determinants of consumer purchasing decision in the e-commerce sector in Poland – Generation perspective. SHS Web of Conferences 57, 1 – 10. http://dx.doi.org/10.1051/shsconf/20185701010 E-commerce for the elderly (n.d.). E-commerce Guide. https://ecommerceguide.com/guides/older-shopper/
• Gong, W., Stump, R.L., & Maddox, L.M. (2013). Factors influencing consumers’ online shopping in China. Journal of Asia Business Studies, 7(3), 214 – 230. https://doi.org/10.1108/JABS-02-2013-0006
• Hansen, T. (2008). Consumer values, the theory of planned behaviour and online grocery shopping. International Journal of Consumer Studies, 32, 128 137. https://doi.org/10.1111/j.1470-6431.2007.00655.x
• Hernández, B., Jiménez-Martínez, J., & Martín, J.M. (2011). Age, gender and income: Do they really moderate online shopping behaviour? Online Information Review, 35(1), 113 – 133. https://doi.org/10.1108/14684521111113614
• Herrero-Crespo, A., & Rodríguez del Bosque, I. (2008). The effect of innovativeness on the adoption of B2C e-commerce: A model based on the theory of planned behavior. Computers in Human Behavior, 24(6), 2830 – 2847. https://doi.org/10.1016/j.chb.2008.04.008
• Hsu, M.-H., Yen, C.-H., Chiu, C.-M., & Chang, C.-M. (2006). A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human-Computer Studies, 64, 889 – 904. https://doi.org/10.1016/j.ijhcs.2006.04.004
• Hui, T.-K., & Wan, D. (2007). Factors affecting internet shopping behaviour in Singapore: Gender and educational issues. International Journal of Consumer Studies, 31(3), 310 – 316. https://doi.org/10.1111/j.1470-6431.2006.00554.x
• Joung, H.-M., & Miller N.J. (2006). Factors of dress affecting self-esteem in older females. Journal of Fashion Marketing and Management, 10(4), 466 – 478. https://doi.org/10.1108/13612020610701983
• Kemp, S. (2019, January 31). Digital 2019: Turkey. Datereportal. https://datareportal.com/reports/digital-2019-turkey
• Kim, H.S. (2006). The hedonic and utilitarian shopping motivations of inner city consumers. Journal of Shopping Center Research, 13(1), 57 – 59.
• Kuoppamӓki, S.-M., Taipale, S., & Wilska, T.-A. (2017). The use of mobile technology for online shopping and entertainment among older adults in Finland. Telematics and Informatics, 34(4), 110 – 117. https://doi.org/10.1016/j.tele.2017.01.005
• Kwon, W.-S., & Noh, M. (2010). The influence of prior experience and age on mature consumers’ perceptions and intentions of internet apparel shopping. Journal of Fashion Marketing and Management, 14(3), 335 – 349. https://doi.org/10.1108/13612021011061825
• Leppel, K., & McCloskey, D.W. (2011). A cross-generational examination of electronic commerce adoption. Journal of Consumer Marketing, 28(4), 261 – 268. https://doi.org/10.1108/07363761111143150
• Lian, J.-W., & Yen, D.C. (2014). Online shopping drivers and barriers for older adults: Age and gender differences. Computers in Human Behavior, 37, 133 – 143. https://doi.org/10.1016/j.chb.2014.04.028
• Lim, Y.M., Yap, C.S., & Lee, T.H. (2011). Intention to shop online: A study of Malaysian baby boomers. African Journal of Business Management, 5(5), 1711 – 1717.
• Limayem, M., Khalifa, M., & Frini, A. (2000). What makes consumers buy from internet? Longitudinal study of online shopping. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 30(4), 421 – 432. https://doi.org/10.1109/3468.852436
• 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. https://doi.org/10.1016/j.elerap.2007.02.002
• Morris, M. & Venkatesh, V. (2000). Age differences in technology adoption decisions: Implications for a changing workforce. Personnel Psychology, 53(2), 375 – 402. https://doi.org/10.1111/j.1744-6570.2000.tb00206.x
• Moschis, G.P. (2012). Consumer behavior in later life: Current knowledge, issues, and new directions for research. Psychology & Marketing, 29(2), 57 – 75. https://doi.org/10.1002/mar.20504
• Naseri, M.B. & Elliot, G. (2011). Role of demographics, social connectedness and prior internet experience in adoption of online shopping: Applications for direct marketing. Journal of Targeting, Measurement and Analysis for Marketing, 19(2), 69 – 84. https://doi.org/10.1057/jt.2011.9
• On-at, S., Canut, M.-F., Péninou, A., & Sédes, F. (2014). Deriving user’s profile sparse egocentric networks using snowball sampling and link prediction. Ninth International Conference on Digital Information Management (ICDM 2014), 80 – 85. https://doi.org/10.1109/icdim.2014.6991421
• Oeser, G., Aygün, T., Balan, C.-L., Paffrath, R. & Schuckel, M.T. (2019). Segmenting elder German grocery shoppers based on shopping motivations. International Journal of Retail & Distribution Management, (47)2, 129-156. https://doi.org/10.1108/IJRDM-02-2018-0033
• Pak, C. & Kambil, A. (2006). Over 50 and ready to shop: serving the aging consumer. Journal of Business Strategy, 27(6), 18-28. http://dx.doi.org/10.1108/02756660610710319
• Soh, P.Y., Heng, H.B., Selvachandran, G., Anh, L.Q., Chau, H.T.M., Son, L.H., Abdel-Baset, M., Manogaran, G., & Varathajaran, R. (2020). Perception, acceptance and willingness of older adults in Malaysia towards online shopping: A study using the ATAUT and IRT models. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-020-01718-4
• Sorce, P., Perotti, V., & Widrick, S. (2005). Attitude and age differences in online buying. International Journal of Retail & Distribution Management, 33(2), 122 – 132. https://doi.org/ 10.1108/09590550510581458
• To, P.-L., Liao, C., & Lin, T.-H. (2007). Shopping motivations on internet: A study based on utilitarian and hedonic value. Technovation, 27, 774 – 787. https://doi.org/10.1016/j.technovation.2007.01.001
• Trocchia, P.J. & Janda, S. (2000). A phenomenological investigation of internet usage among older individuals. Journal of Consumer Marketing, 17(7), 605 – 616. https://doi.org/10.1108/07363760010357804
• United Nations. (2017). World population prospects: The 2017 revision. https://population.un.org/wpp/publications/files/wpp2017_keyfindings.pdf
• Veenhof, B., & Timusk, P. (2007). Online Activities of Canadian Boomers and Seniors. Statistics Canada. https://www150.statcan.gc.ca/n1/pub/11-008-x/2009002/article/10910-eng.htm
• Vicente, P., & Lopes, I. (2016). Attitudes of older mobile phone users towards mobile phones. The European Journal of Communication Research, 41(7), 71 – 86. https://doi.org/10.1515/commun-2015-0026
• Wang, M.-S., Chen, C.-C., Chang, S.-C, & Yang, Y.-H. (2007). Effects of online shopping attitudes, subjective norms and control beliefs on online shopping intentions: A test of the theory of planned behaviour. International Journal of Management, 24(2), 296 – 302.
• World Health Organization. (2015). Health Aging. World Report on Aging and Health, 25 – 43. https://apps.who.int/iris/bitstream/handle/10665/186463/9789240694811_eng.pdf;jsessionid=C31B8AF577BD19B3F3F0E2F48580DF5D?sequence=1
• Yalçın, F.G. (2019, September 19). Türkiye‘de Yaşlılık Tahayyülleri ve Pratikleri Araştırma Sonuçları Paylaşıldı. Fintechtime. http://fintechtime.com/tr/2019/09/turkiyede-yaslilik-tahayyulleri-ve-pratikleri-arastirma-sonuclari-paylasildi/
• Yin, Y., Pei, E., & Ranchhod, A. (2013). The shopping experience of older supermarket consumers. Journal of Enterprise Information Management, 26(4), 444 – 471. https://doi.org/10.1108/JEIM-05-2013-0025
• Zhou, L., Dai, L., & Zhang, D. (2007). Online shopping acceptance model – A critical survey of consumer factors in online shopping. Journal of Electronic Commerce Research, 8(1), 41 – 62