Product Brokering Efficiency as a mediator of Online Product Recommendation and Customer Loyalty

https://doi.org/10.22146/jpsi.64138

Felisa Lilian(1), Honey Wahyuni Sugiharto Elgeka(2*), V Heru Hariyanto(3)

(1) Faculty Of Psychology, Universitas Surabaya
(2) Faculty Of Psychology, Universitas Surabaya
(3) Faculty Of Psychology, Universitas Surabaya
(*) Corresponding Author

Abstract


Marketing strategies in e-commerce have a main goal, that is to pursue customer loyalty. Sociolla is an e-commerce company that sells cosmetic products and has a recommendation feature to make it easier for customers during the shopping process. These recommendations can trigger customer satisfaction and generate loyalty. The purpose of this study was to examine the correlation between online product recommendation and customer loyalty with product brokering efficiency as a mediator. 179 Sociolla customers were recruited in this study using convenience sampling. The data were analyzed using the SPSS-Process Hayes model 4. Results showed that perceived decision quality acts as a mediator in the relationship between enablers and customer loyalty (β = .20, [ .13; .27]). It can be concluded that recommendations that are comprehensive, clear, and meet the customer needs will make it easier for customers to make purchasing decisions, which ultimately leads the customers to form loyalty toward the products.

Keywords


customer loyalty; online product recommendations; product brokering efficiency.

Full Text:

PDF


References

Cenfetelli, RT, & Schwarz, A. (2011). Identifying and testing the inhibitors of technology usage intentions. Information Systems Research, 22 (4), 808–823. https://doi.org/10.1287/isre.1100.0295

Craig, AW, Loureiro, YK, Wood, S., & Vendemia, JMC (2012). Suspicious minds: Exploring neural processes during exposure to deceptive advertising. Journal of Marketing Research, 49 (3), 361–372. https://doi.org/10.1509/jmr.09.0007

Darke, PR, & Ritchie, RJB (2007). The defensive consumer: Advertising deception, defensive processing, and distrust. Journal of Marketing Research, 44 (1), 114–127. https://doi.org/10.1509/jmkr.44.1.114

Fang, YH (2012). Does online interactivity matter? Exploring the role of interactivity strategies in consumer decision making. Computers in Human Behavior, 28 (5), 1790–1804. https://doi.org/10.1016/j.chb.2012.04.019

Graham, L. (2020). Advantages of shopping online at Sociolla. Retrieved from: http://www.fermeloiedor.com/keuntungan-berjual-online-di-sociolla/ on August 24, 2021

Hess, T., Fuller, M., & Campbell, D. (2009). Designing interfaces with social presence: Using vividness and extraversion to create social recommendation agents. Journal of the Association for Information Systems, 10 (12), 889–919. https://doi.org/10.17705/1jais.00216

Iprice. (2021). Indonesia e-commerce map. Retrieved from: https://iprice.co.id/insights/mapofecommerce/ on August 24, 2021

Jacoby, J., Speller, DE, & Kohn, CA (1974). Brand choice behavior as a function of information load. Journal of Marketing Research, 11 (1), 63. https://doi.org/10.2307/3150994

Jiang, Z., & Benbasat, I. (2007a). Investigating the influence of the functional mechanisms of online product presentations. Information Systems Research, 18 (4), 454–470. https://doi.org/10.1287/isre.1070.0124

Jiang, Z., & Benbasat, I. (2007b). The effects of presentation formats and task complexity on online consumers' product understanding. MIS Quarterly: Management Information Systems, 31 (3), 475–500. https://doi.org/10.2307/25148804

Lee, BK, & Lee, WN (2004). The effect of information overload on consumer choice quality in an online environment. Psychology and Marketing, 21 (3), 159–183. https://doi.org/10.1002/mar.20000

Liang, TP, Lai, HJ, & Ku, YIC (2006). Personalized content recommendation and user satisfaction: Theoretical synthesis and empirical findings. Journal of Management Information Systems, 23 (3), 45–70. https://doi.org/10.2753/MIS0742-1222230303

Lim, KH, Benbasat, I., & Ward, LM (2000). The role of multimedia in changing first impression bias. Information Systems Research, 11 (2), 115–136. https://doi.org/10.1287/isre.11.2.115.11776

Markopoulos, PM, & Clemons, EK (2013). Reducing buyers' uncertainty about taste-related product attributes. Journal of Management Information Systems, 30 (2), 269–299. https://doi.org/10.2753/MIS0742-1222300210

Mavlanova, T., Benbunan-Fich, R., & Lang, G. (2016). The role of external and internal signals in E-commerce. Decision Support Systems, 87, 59–68. https://doi.org/10.1016/j.dss.2016.04.009

Olbrich, R., & Holsing, C. (2011). Modeling consumer purchasing behavior in social shopping communities with clickstream data. International Journal of Electronic Commerce, 16 (2), 15–40. https://doi.org/10.2753/JEC1086-4415160202

Park, DH, & Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement. Electronic Commerce Research and Applications, 7 (4), 386–398. https://doi.org/10.1016/j.elerap.2007.11.004

Pratminingsih, SA, Lipuringtyas, C., & Rimenta, T. (2013). Factors Influencing Customer Loyalty Toward Online Shopping. International Journal of Trade, Economics, and Finance, 4 (3), 104–110. https://doi.org/10.7763/ijtef.2013.v4.268

Ratchford, BT (2001). The economics of consumer knowledge. Journal of Consumer Research, 27 (4), 397–411. https://doi.org/10.1086/319617

Srinivasan, SS, Anderson, R., & Ponnavolu, K. (2002). Customer loyalty in e-commerce: An exploration of its antecedents and consequences. Journal of Retailing, 78 (1), 41–50. https://doi.org/10.1016/S0022-4359(01)00065-3

Tam, KY, & Ho, SY (2005). Web personalization as a persuasion strategy: An elaboration likelihood model perspective. Information Systems Research, 16 (3), 271–291. https://doi.org/10.1287/isre.1050.0058

Tam, KY, & Ho, SY (2006). Understanding the impact of web personalization on user information processing and decision outcomes. MS Quarterly, 30 (4), 865–890.

Wang, W., Qiu, L., Kim, D., & Benbasat, I. (2016). Effects of rational and social appeals of online recommendation agents on cognition- and affect-based trust. Decision Support Systems, 86, 48–60. https://doi.org/10.1016/j.dss.2016.03.007

Xu, J., Benbasat, I., & Cenfetelli, RT (2014). The nature and consequences of trade-off transparency in the context of recommendation agents. MIS Quarterly: Management Information Systems, 38 (2), 379–406. https://doi.org/10.25300/MISQ/2014/38.2.03

Zhang, H., Zhao, L., & Gupta, S. (2018). The role of online product recommendations on customer decision-making and loyalty in social shopping communities. International Journal of Information Management, 38 (1), 150–166. https://doi.org/10.1016/j.ijinfomgt.2017.07.006

Zhang, T., Agarwal, R., & Jr., HCL (2011). The value of it-enabled retailer learning: Personalized product recommendations and customer store loyalty in electronic markets. MIS Quarterly, 35 (4), 859–881.



DOI: https://doi.org/10.22146/jpsi.64138

Article Metrics

Abstract views : 3074 | views : 2086

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2021 Jurnal Psikologi

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 

Recent Issues

Buku 1 Buku 1 Buku 1 Buku 1 
Vol 51 Issue 1 (2024)
Page 1-119		 Vol 50 Issue 3 (2023)
Page 219-332		 Vol 50 Issue 2 (2023)
Page 125-218		 Vol 50 Issue 1 (2023)
Page 1-124		 

 

 

Published by Faculty of Psychology, Universitas Gadjah Mada, Indonesia Building D-6th, Floor No. D-606. Jl. Sosio Humaniora No. 1, Bulaksumur Yogyakarta, 55281
Email: jurnalpsikologi@ugm.ac.id
Phone/whatsApp: +6281125210175

Web Analytics Made Easy - StatCounter View My Stats