Antecedent of Webrooming Behavior

Sekar Yorindasari, Rahab Rahab, Weni Novandari


Webrooming is shopping behavior by viewing products online but the actual purchases are made in offline stores. Increased internet access makes it easier for consumers to find goods according to their needs. However, several factors can influence consumers in deciding webrooming behavior. Webrooming has been explored from the perspective of consumer motivation, such as information seeking. The research approach was adopted as a theoretical foundation, focusing on information processing and uncertainty reduction. Data obtained by 103 respondents, using multiple regression analysis. The results of the analysis show that the variables Need for Touch and Perceived Usefulness of Online Reviews have a positive and significant effect on webrooming behavior, while Online Purchase Risk Perceived has no effect on webrooming behavior. The findings of this study can be used by marketers to study consumer webrooming behavior so that they can formulate appropriate marketing strategies. The limitation of this study is that this study only has a coefficient of determination only 35.7% of the variables used to examine this webrooming behavior. So for future research, it can be investigated further by adding other variables that affect webrooming behavior, and can add a mediating or moderating role.

Keywords: Webrooming behavior; Need for Touch; Online Purchase Risk Perceived; Perceived Usefulness of Online Reviews

Full Text:



Arora, S., Sahney, S., 2019. Examining consumers' webrooming behavior: an integrated approach.

Markets. Intell. plan. 37 (3), 339–354

Aw, EC 2020. Understanding consumers' paths to webrooming: A complexity approach, Journal of Retailing and Consumer Services 53

Aw, et al., 2021. Understanding the role of channel-, consumer-, and product-related factors in determining webrooming intention, Journal of Retailing and Consumer Services 58

Cho S, Workman J. 2011. Gender, fashion innovativeness and opinion leadership, and need for touch: effects on multichannel choice and touch/non-touch preference in clothing shopping. Journal of Fashion Marketing and Management: An International Journal 15(3): 363–382

Chou, SY, Shen, GC, Chiu, HC and Chou, YT (2016), “Multichannel service providers' strategy: understanding customers' switching and free-riding behavior”, Journal of Business Research, Vol. 69 No. 6, pp. 2226-2232.

Dholakia, UM, Kahn, BE, Reeves, R., Rindfleisch, A., Stewart, D., Taylor, E., 2010. Consumer behavior in a multichannel, multimedia retailing environment. J. Interact. Mark. 24(2), 86–95.

Fernandez, NV, P´erez, MJS, V´ azquez-Casielles, R., 2018. Webroomers versus showroomers: are they the same? J. Bus. res. 92, 300–320.

positive reviews and the motivation to touch, Journal of Consumer Behavior

Flavian, C., Gurrea, R., Orús, C., 2019. Feeling confident and smart with webrooming: understanding the consumer's path to satisfaction. J. Interact. Markets. 47, 1–15

Google Consumer Barometer (2015), “The smart shopper: research and purchase behavior (ROPO)”, available at: (accessed December 25, 2016).

Hall, A., Towers, N., & Shaw, DR (2017). Understanding how millennial shoppers decide what to buy: Digitally connected unseen journeys. International Journal of Retail & Distribution Management, 45(5), 498–517.

Kahneman, D., Tversky, A., 1979. Prospect theory: an analysis of decision under risk.

Econometrica 47 (2), 229–263.

Karimi, S., Wang, F., 2017. Online review helpfulness: impact of reviewer profile image. Decis.

Support System. 96, 39–48.

Kim, H., Karpova, E., 2010. Consumer attitudes toward fashion counterfeits: application of the theory of planned behavior. Cloth. Text. res. J. 28(2), 79–94.

Lester, DH, Forman, AM, Loyd, D., 2006. Internet shopping and buying behavior of college students. serv. Markets. Q. 27(2), 123–138.

Peck, J., & Childers, TL (2003). Individual differences in haptic information processing: The “Need for Touch” scale. Journal of Consumer Research, 30(3), 430–442.

Pires, G., Stanton, J., Eckford, A., 2004. Influences on the perceived risk of purchasing online. J. Consum. Behav. 4 (2), 118–131.

Reid, LF, Ross, HF, Vignali, G., 2016. An exploration of the relationship between product selection criteria and engagement with 'show-rooming' and 'web-rooming' in the consumer's decision-making process. int. J. Bus. Glob. 17(3), 364–383.

Sahney, S., Ghosh, K. and Shrivastava, A. (2013), “Conceptualizing consumer 'trust' in online buying behavior: an empirical inquiry and model development in Indian context”, Journal of Asia Business Studies, Vol. 7 No. 3, pp. 278-298.

Santos, S., & Gonçalves, HM (2019). Multichannel consumer behaviors in the mobile environment: Using fsQCA and discriminant analysis to understand webrooming motivations. Journal of Business Research, 101, 757–766.

Tormala, ZL, Rucker, DD, Seger, CR, 2008. When increased confidence yields increased thought: A confidence-matching hypothesis. Journal of Experimental Social Psychology 44 (1), 141–147.

Wang, YM, Lin, HH, Tai, WC, Fan, YL, 2016. Understanding multi-channel research shoppers: an analysis of Internet and physical channels. inf. syst. E-Bus. Manag. 14(2), 389–413.

Yrjola, M., Spence, MT, Saarij€ arvi, H., 2018. Omni-channel retailing: propositions, examples and solutions. int. Rev. Retail Distribution. consumption. res. 28(3), 259–276.

Zhang, KZ, Zhao, SJ, Cheung, CM, Lee, MK, 2014. Examining the influence of online reviews on consumers' decision-making: a heuristic–systematic model. Decis. Support System. 67,


  • There are currently no refbacks.