Analisis Perbedaan Gender Dalam Hubungan Perceived Value Dan Information Search Pada Produk Fashion: Studi Pengguna Instagram & Tiktok
Keywords:
EWOM, fashion, gender, Online information source, social media platformAbstract
Latar belakang: Saat ini konsumen cenderung mencari informasi melalui internet dan media sosial. Laki-laki dan perempuan memiliki strategi pemrosesan informasi yang berbeda. Akibatnya, terdapat kebutuhan untuk menyelidiki potensi kesenjangan dalam nilai-nilai informasi yang dikejar oleh laki-laki dan perempuan di media sosial. Beberapa penelitian sebelumnya mengungkapkan bahwa konsumen dapat menggunakan berbagai sumber informasi online (misalnya, sumber elektronik dari mulut ke mulut, atau sumber eWOM, sumber netral/pihak ketiga, dan sumber produsen/pengecer) untuk mendapatkan informasi mengenai suatu merek dan produk. Namun, masih ada kekurangan dalam pemahaman mengenai bagaimana gender mempengaruhi perceived value terhadap informasi pencarian produk fashion di platform-platform sosial media. Tujuan: tujuan dari penelitian ini adalah untuk menggali lebih dalam pengaruh perbedaan jenis kelamin dalam memoderasi hubungan antara perceived value terhadap information search pada produk fashion di Instagram dan TikTok. Metode: Populasi pada penelitian ini adalah pengguna Instagram dan TikTok. Teknik pengambilan sampel yang digunakan adalah non probability sampling dengan metode purposive sampling. Kriteria sampel yaitu pengguna Instagram dan TikTok yang pernah melakukan pencarian produk fashion. Data dalam penelitian ini dianalisis menggunakan Structural Equation Model – Partial Least Square (SEM-PLS). Hasil: Hasil penelitian menunjukkan bahwa perempuan cenderung menggunakan sumber informasi EWOM, sumber informasi manufaktur/retail, dan sumber informasi dari pihak ketiga. Selain itu perempuan juga cenderung lebih termotivasi untuk mencari nilai-nilai yang memberikan kepuasan selama mencari informasi di media sosial Instagram dan TikTok dibandingkan dengan laki-laki. Pada penelitian ini juga menemukan bahwa perempuan menghasilkan nilai yang tinggi pada semua nilai informasi kecuali pada functional value. Penelitian ini juga menemukan perbedaan antara laki-laki dan perempuan dalam hal pengaruh nilai pencarian terhadap jenis sumber informasi (EWOM, third party source, dan manufacture/retailer source) yang digunakan di Instagram dan TikTok untuk mencari informasi produk fashion. Kesimpulan: Perempuan lebih dominan dalam menggunakan sumber informasi terkait fashion melalui Instagram dan Tiktok
References
Ajzen, I., & Fishbein, M. (2000). Attitudes and the Attitude-Behavior Relation: Reasoned and Automatic Processes. European Review of Social Psychology,11(1):1-33. https://doi.org/10.1080/14792779943000116
Alba, J., Lynch, J., Weitz, B., Janiszewski, chris, lutz, richard, sawyer, alan, & wood, stacy. (1997). Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to Participate in Electronic Marketplaces. Journal of Marketing, 61(3).https://doi.org/10.2307/1251788
Atkins, K., & Hyun, S.-Y. (2016). Smart Shoppers’ Purchasing Experiences: Functions of Product Type, Gender, and Generation. International Journal of Marketing Studies, 8(2). https://doi.org/10.5539/ijms.v8n2p1
Barber, N., Dodd, T., & Kolyesnikova, N. (2009). Gender differences in information search: Implications for retailing. Journal of Consumer Marketing, 26(6), 415–426. https://doi.org/10.1108/07363760910988238
Bei, L.-T., Chen, E. Y. I., & Widdows, R. (2004). Consumers’ Online Information Search Behavior and the Phenomenon of Search vs. Experience Products. Journal of Family and Economic Issues, 25(4), 449–467. https://doi.org/10.1007/s10834-004-5490-0
Bickart, B., & Schindler, R. M. (2001). Internet forums as influential sources of consumer information. Journal of Interactive Marketing, 15(3), 31–40. https://doi.org/10.1002/dir.1014
Cantallops, A. S., & Salvi, F. (2014). New consumer behavior: A review of research on eWOM and hotels. International Journal of Hospitality Management, 36, 41–51. https://doi.org/10.1016/j.ijhm.2013.08.007
Chatterjee, A. (2017). Chapter B - Information Sources. In A. Chatterjee (Ed.), Elements of Information Organization and Dissemination (pp. 9–45). Chandos Publishing. https://doi.org/10.1016/B978-0-08-102025-8.00002-8
Chen, C. C., Hsiao, K.-L., & Wu, S.-J. (2018). Purchase intention in social commerce: An empirical examination of perceived value and social awareness. Library Hi Tech, 36(4), 583–604. https://doi.org/10.1108/LHT-01-2018-0007
Chen, J., Teng, L., Yu, Y., & Yu, X. (2016). The effect of online information sources on purchase intentions between consumers with high and low susceptibility to informational influence. Journal of Business Research, 69(2), 467–475. https://doi.org/10.1016/j.jbusres.2015.05.003
Chevalier, J., & Goolsbee, A. (2003). Measuring prices and price competition online: Amazon.com and BarnesandNoble.com. Quantitative Marketing and Economics, 1(2), 203–222. https://doi.org/10.1023/A:1024634613982
Chiu, Y.-P., Lo, S.-K., Hsieh, A.-Y., & Hwang, Y. (2019). Exploring why people spend more time shopping online than in offline stores. Computers in Human Behavior, 95, 24–30. https://doi.org/10.1016/j.chb.2019.01.029
Cotter, K. (2019). Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram. New Media & Society, 21(4), 895–913. https://doi.org/10.1177/1461444818815684
Dholakia, R., & Chiang, K.-P. (2003). Shoppers in Cyberspace: Are They From Venus or Mars and Does It Matter? Journal of Consumer Psychology - J CONSUM PSYCHOL, 13, 171–176. https://doi.org/10.1207/S15327663JCP13-1&2_15
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison: Wesley.
Gan, C., & Wang, W. (2017). The influence of perceived value on purchase intention in social commerce context. Internet Research, 27(4), 772–785. https://doi.org/10.1108/IntR-06-2016-0164
Gupta, P., & Harris, J. (2010). How e-WOM recommendations influence product consideration and quality of choice: A motivation to process information perspective. Journal of Business Research, 63 (9), 1041–1049. https://doi.org/10.1016/j.jbusres.2009.01.015
Gvili, Y., Kol, O., & Levy, S. (2020). The value(s) of information on social network sites: The role of user personality traits. European Review of Applied Psychology, 70(2), 100511. https://doi.org/10.1016/j.erap.2019.100511
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis. Pearson Education Limited: London.
Haridasan, A. C., Fernando, A. G., & Saju, B. (2021). A systematic review of consumer information search in online and offline environments. RAUSP Management Journal, 56(2), 234–253. https://doi.org/10.1108/RAUSP-08-2019-0174
Häubl, G., & Trifts, V. (2000). Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids. Marketing Science, 19(1), 4–21. https://www.jstor.org/stable/193256
Hinton, P. R., McMurray, I., & Brownlow, C. (2014). SPSS Explained (2nd ed.). Routledge. https://doi.org/10.4324/9781315797298
Hofstede, G. (2001). Culture’s Consequences: Comparing Values, Behaviors, Institutions and Organizations Across Nations. SAGE: California.
Jin, S.-A. A., & Phua, J. (2014). Following Celebrities’ Tweets About Brands: The Impact of Twitter-Based Electronic Word-of-Mouth on Consumers’ Source Credibility Perception, Buying Intention, and Social Identification With Celebrities. Journal of Advertising. https://www.tandfonline.com/doi/full/10.1080/00913367.2013.827606
Kanwal, M., Burki, U., Ali, R., & Dahlstrom, R. (2022). 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
Kim, J.-H., Kim, M., Yoo, J., & Park, M. (2020). Consumer decision-making in a retail store: The role of mental imagery and gender difference. International Journal of Retail & Distribution Management, 49(3), 421–445. https://doi.org/10.1108/IJRDM-10-2019-0353
Klepek, M. (2020). The Role of Demographic Factors in Consumer Perception of Value from Brand Communication on Facebook. Central European Business Review, 9(3), 56–73. https://doi.org/10.18267/j.cebr.239
Kol, O., & Levy, S. (2022). The Whole Is More than Its Parts: A Multidimensional Construct of Values in Consumer Information Search Behavior on SNS. Journal of Theoretical and Applied Electronic Commerce Research, 17(4), https://doi.org/10.3390/jtaer17040085
Kol, O., & Levy, S. (2023). Men on a mission, women on a journey - Gender differences in consumer information search behavior via SNS: The perceived value perspective. Journal of Retailing and Consumer Services, 75, 103476. https://doi.org/10.1016/j.jretconser.2023.103476
Kol, O., & Lissitsa, S. (2023). Looking for accommodations? What motivates consumer information search behavior on Instagram, Facebook groups and personal profiles on social networking sites. Information Technology & People, ahead-of-print(ahead-of-print). https://doi.org/10.1108/ITP-05-2022-0389
Lynch, J. G., & Ariely, D. (2000). Wine Online: Search Costs Affect Competition on Price, Quality, and Distribution. Marketing Science, 19(1), 83–103. https://www.jstor.org/stable/193260
McCole, P., Ramsey, E., & Williams, J. (2010). Trust considerations on attitudes towards online purchasing: The moderating effect of privacy and security concerns. Journal of Business Research, 63(9), 1018–1024. https://doi.org/10.1016/j.jbusres.2009.02.025
Mehta, R. (2020). Gender-based differences in consumer decision-making styles: Implications for marketers. DECISION, 47(3), 319–329. https://doi.org/10.1007/s40622-020-00252-8
Meyers-Levy, J., & Maheswaran, D. (1991). Exploring Differences in Males’ and Females’ Processing Strategies. Journal of Consumer Research, 18(1), 63–70. https://doi.org/10.1086/209241
Molinillo, S., Aguilar-Illescas, R., Anaya-Sánchez, R., & Liébana-Cabanillas, F. (2021). Social commerce website design, perceived value and loyalty behavior intentions: The moderating roles of gender, age and frequency of use. Journal of Retailing and Consumer Services, 63, 102404. https://doi.org/10.1016/j.jretconser.2020.102404
Murray, K. B. (1991). A Test of Services Marketing Theory: Consumer Information Acquisition Activities. Journal of Marketing, 55(1), 10–25. https://doi.org/10.2307/1252200
Ngueutsa, R., & Kouabenan, D. R. (2017). Fatalistic beliefs, risk perception and traffic safe behaviors. European Review of Applied Psychology, 67(6), 307–316. https://doi.org/10.1016/j.erap.2017.10.001
Nissen, A., & Krampe, C. (2021). Why he buys it and she doesn’t – Exploring self-reported and neural gender differences in the perception of eCommerce websites. Computers in Human Behavior, 121, 106809. https://doi.org/10.1016/j.chb.2021.106809
Park, C., & Lee, T. M. (2009). Information direction, website reputation and eWOM effect: A moderating role of product type. Journal of Business Research, 62(1), 61–67. https://doi.org/10.1016/j.jbusres.2007.11.017
Pradhan, B., Kishore, K., & Gokhale, N. (2023). Social media influencers and consumer engagement: A review and future research agenda. International Journal of Consumer Studies, 47(6), 2106–2130. https://doi.org/10.1111/ijcs.12901
Richard, M.-O. (2005). Modeling the impact of internet atmospherics on surfer behavior. Journal of Business Research, 58(12), 1632–1642. https://doi.org/10.1016/j.jbusres.2004.07.009
Senecal, S., & Nantel, J. (2004). The Influence of Online Product Recommendations on Consumers’Online Choices. Journal of Retailing, 159–169. https://doi.org/10.1016/j.jretai.2004.04.001
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory of consumption values. Journal of Business Research, 22(2), 159–170. https://doi.org/10.1016/0148-2963(91)90050-8
Singh, S., & Jang, S. (2022). Search, purchase, and satisfaction in a multiple-channel environment: How have mobile devices changed consumer behaviors? Journal of Retailing and Consumer Services, 65, 102200. https://doi.org/10.1016/j.jretconser.2020.102200
Smith, D., Menon, S., & Sivakumar, K. (2005). Online peer and editorial recommendations, trust, and choice in virtual markets. Journal of Interactive Marketing, 19(3), 15–37. https://doi.org/10.1002/dir.20041
Sramova, B., & Pavelka, J. (2019). Gender differences and wellbeing values in adolescent online shopping. International Journal of Retail & Distribution Management, 47(6), 623–642. https://doi.org/10.1108/IJRDM-08-2017-0173
Steckel, J. H., Winer, R. S., Bucklin, R. E., Dellaert, B. G. C., Drèze, X., Häubl, G., Jap, S. D., Little, J. D. C., Meyvis, T., Montgomery, A. L., & Rangaswamy, A. (2005). Choice in Interactive Environments. Marketing Letters, 16(3), 309–320. https://doi.org/10.1007/s11002-005-5894-0
Sun, J., Song, S., House, D., & Kwon, M. (2019). Role of gender differences on individuals’ responses to electronic word-of-mouth in social interactions. Applied Economics, 51(28), 3001–3014. https://doi.org/10.1080/00036846.2018.1564015
Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0
Szymanski, D. M., & Hise, R. T. (2000). E-satisfaction: An initial examination. Journal of Retailing, 76(3), 309–322. https://doi.org/10.1016/S0022-4359(00)00035-X
Toh, R. S., Raven, P., & DeKay, F. (2011). Selling rooms: Hotels vs. third-party websites. Cornell Hospitality Quarterly, 52(2), 181–189. Scopus. https://doi.org/10.1177/1938965511400409
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Ward, M. R., & Lee, M. J. (2000). Internet shopping, consumer search and product branding. Journal of Product & Brand Management, 9(1), 6–20. https://doi.org/10.1108/10610420010316302
Yang, K., & Lee, H. (2010). Gender differences in using mobile data services: Utilitarian and hedonic value approaches. Journal of Research in Interactive Marketing, 4(2), 142–156. https://doi.org/10.1108/17505931011051678
Zauberman, G. (2003). The Intertemporal Dynamics of Consumer Lock-In (SSRN Scholarly Paper 401460). https://doi.org/10.2139/ssrn.401460
Zayer, L. T., & Coleman, P. (2012). Male Consumers’ Motivations for online information Search and Shopping Behavior. In Online Consumer Behavior. Routledge.
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