Online Search and In-Store Purchase Webrooming: The Mediating Role of Perceived Risk and the Moderating Role of Product Type
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This paper explores webrooming intention determinants by analyzing the contributions of online trust, perceived risk, and need to touch in an integrated omnichannel context. In particular, it investigates the mediating effect of the perceived risk and the moderating effect of the type of product (high-touch products versus low-touch products). A stratified random sampling strategy was used to collect data on 900 consumers in Jordan, Saudi Arabia, and Palestine to increase the representativeness. The partial least squares structural equation modeling (PLS-SEM) was used to test the proposed model. The results show that online trust has a significant negative impact on perceived risk and a positive impact on webrooming intention. Perceived risk, in its turn, positively affects webrooming intention strongly and mediates the connection between online trust and webrooming behavior partially. Also, need for touch proves to be a strong predictor of the webrooming intention, which confirms the role of sensory motivation in the decision-making process in the omnichannel. The product type moderating effect was, however, not supported. Multi-group analysis also reveals that the structural relations are similar in the three countries. The paper is important to the literature on omnichannel retailing because it offers a risk-based account of webrooming behavior and shows that trust is a twofold phenomenon, acting as both a direct and indirect motivation. It also has some practical implications to the retailer in the sense that it highlights the need to incorporate online trust-building tools with the in-store experience in order to improve consumer decision-making.
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Alrawad, M., Lutfi, A., Alyatama, S., Al Khattab, A., Alsoboa, S. S., Almaiah, M. A., Ramadan, M. H., Arafa, H. M., Ahmed, N. A., & Alsyouf, A. (2023). Assessing customers perception of online shopping risks: A structural equation modeling–based multigroup analysis. Journal of Retailing and Consumer Services, 71, 103188. https://doi.org/10.1016/j.jretconser.2022.103188
Alsulaimani, M. M. (2024). Factors affecting consumer intention to use e-grocery shopping in Saudi Arabia. International Journal of E-Business Research (IJEBR), 20(1), 1–17.
Arora, S., & Sahney, S. (2019). Examining consumers’ webrooming behavior: An integrated approach. Marketing Intelligence & Planning, 37(3), 339–354. https://doi.org/10.1108/MIP-05-2018-0152
Aw, E. C.-X. (2020). Understanding consumers’ paths to webrooming: A complexity approach. Journal of Retailing and Consumer Services, 53, 101991. https://doi.org/10.1016/j.jretconser.2019.101991
Barann, B., Hermann, A., Heuchert, M., & Becker, J. (2022). Can't touch this? Conceptualizing the customer touchpoint in the context of omni-channel retailing. Journal of Retailing and Consumer Services, 65, 102269. https://doi.org/10.1016/j.jretconser.2020.102269
Chang, Y. P., & Li, J. (2022). Seamless experience in the context of omnichannel shopping: scale development and empirical validation. Journal of Retailing and Consumer Services, 64, 102800. https://doi.org/10.1016/j.jretconser.2021.102800
Chen, P., Hitt, L. M., Hong, Y., & Wu, S. (2021). Measuring Product Type and Purchase Uncertainty with Online Product Ratings: A Theoretical Model and Empirical Application. Information Systems Research, 32(4), 1470–1489. https://doi.org/10.1287/isre.2021.1041
Cui, X., Xie, Q., Zhu, J., Shareef, M. A., Goraya, M. A. S., & Akram, M. S. (2022). Understanding the omnichannel customer journey: The effect of online and offline channel interactivity on consumer value co-creation behavior. Journal of Retailing and Consumer Services, 65, 102869. https://doi.org/10.1016/j.jretconser.2021.102869
Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3
Firmanshah, M. I., Abdullah, N., & Fariduddin, M. N. (2023). The relationship of school students’ environmental knowledge, attitude, behavior, and awareness toward the environment: A systematic review. International Journal of Academic Research in Progressive Education and Development, 12(1), 432–449. http://dx.doi.org/10.6007/IJARPED/v12-i1/15707
Flavián, C., Gurrea, R., & Orús, C. (2019). Feeling Confident and Smart with Webrooming: Understanding the Consumer’s Path to Satisfaction. Journal of Interactive Marketing, 47(1), 1–15. https://doi.org/10.1016/j.intmar.2019.02.002
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business Research, 56(11), 867–875. https://doi.org/10.1016/S0148-2963(01)00273-9
Gasparin, I., Panina, E., Becker, L., Yrjölä, M., Jaakkola, E., & Pizzutti, C. (2022). Challenging the" integration imperative": A customer perspective on omnichannel journeys. Journal of Retailing and Consumer Services, 64, 102829. https://doi.org/10.1016/j.jretconser.2021.102829
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 51–90. https://doi.org/10.2307/30036519
Gensler, S., Verhoef, P. C., & Böhm, M. (2012). Understanding consumers’ multichannel choices across the different stages of the buying process. Marketing Letters, 23(4), 987–1003. https://doi.org/10.1007/s11002-012-9199-9
Goraya, M. A. S., Zhu, J., Akram, M. S., Shareef, M. A., Malik, A., & Bhatti, Z. A. (2022). The impact of channel integration on consumers’ channel preferences: Do showrooming and webrooming behaviors matter? Journal of Retailing and Consumer Services, 65, 102130. https://doi.org/10.1016/j.jretconser.2020.102130
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook. Springer International Publishing. https://doi.org/10.1007/978-3-030-80519-7
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027
Heitz-Spahn, S. (2013). Cross-channel free-riding consumer behavior in a multichannel environment: An investigation of shopping motives, sociodemographics and product categories. Journal of Retailing and Consumer Services, 20(6), 570–578. https://doi.org/10.1016/j.jretconser.2013.07.006
Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382
Herhausen, D., Binder, J., Schoegel, M., & Herrmann, A. (2015). Integrating bricks with clicks: Retailer-level and channel-level outcomes of online–offline channel integration. Journal of Retailing, 91(2), 309–325. https://doi.org/10.1016/j.jretai.2014.12.009
Huang, P., Lurie, N. H., & Mitra, S. (2009). Searching for Experience on the Web: An Empirical Examination of Consumer Behavior for Search and Experience Goods. Journal of Marketing, 73(2), 55–69. https://doi.org/10.1509/jmkg.73.2.55
Huré, E., Picot-Coupey, K., & Ackermann, C.-L. (2017). Understanding omni-channel shopping value: A mixed-method study. Journal of Retailing and Consumer Services, 39, 314–330. https://doi.org/10.1016/j.jretconser.2017.08.011
Jadil, Y., Rana, N. P., & Dwivedi, Y. K. (2022). Understanding the drivers of online trust and intention to buy on a website: An emerging market perspective. http://qspace.qu.edu.qa/handle/10576/58381
Jarvenpaa, S. L., Tractinsky, N., & Vitale, M. (2000). Consumer trust in an Internet store. Information Technology and Management, 1(1–2), 45–71. https://doi.org/10.1023/A:1019104520776
Kleinlercher, K., Linzmajer, M., Verhoef, P. C., & Rudolph, T. (2020). Antecedents of Webrooming in Omnichannel Retailing. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.606798
Lavuri, R., & Thaichon, P. (2025). Webrooming in the Luxury Market: Role of Consumer Traits, Channel-Related Factors and Shopping Motivations. Australasian Marketing Journal, 14413582251333808. https://doi.org/10.1177/14413582251333808
Lim, X. J., Cheah, J. H., Dwivedi, Y. K., & Richard, J. E. (2022). Does retail type matter? Consumer responses to channel integration in omni-channel retailing. Journal of Retailing and Consumer Services, 67, 102992. https://doi.org/10.1016/j.jretconser.2022.102992
Masoud, E. Y. (2013). The effect of perceived risk on online shopping in Jordan. European Journal of Business and Management, 5(6), 76–87.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and Validating Trust Measures for e-Commerce: An Integrative Typology. Information Systems Research, 13(3), 334–359. https://doi.org/10.1287/isre.13.3.334.81
Nawi, N. C., Al Mamun, A., Hamsani, N. H. B., & Muhayiddin, M. N. bin. (2019). Effect of consumer demographics and risk factors on online purchase behaviour in Malaysia. Societies, 9(1), 10. https://doi.org/10.3390/soc9010010
Nelson, P. (1970). Information and Consumer Behavior. Journal of Political Economy, 78(2), 311–329. https://doi.org/10.1086/259630
Nelson, P. (1974). Advertising as Information. Journal of Political Economy, 82(4), 729–754. https://doi.org/10.1086/260231
Peck, J., & Childers, T. L. (2003). Individual Differences in Haptic Information Processing: The “Need for Touch” Scale. Journal of Consumer Research, 30(3), 430–442. https://doi.org/10.1086/378619
Phamthi, V. A., Nagy, Á., & Ngo, T. M. (2024). The influence of perceived risk on purchase intention in e‐commerce—Systematic review and research agenda. International Journal of Consumer Studies, 48(4), e13067. https://doi.org/10.1111/ijcs.13067
Quach, S., Barari, M., Moudrý, D. V., & Quach, K. (2022). Service integration in omnichannel retailing and its impact on customer experience. Journal of Retailing and Consumer Services, 65, 102267. https://doi.org/10.1016/j.jretconser.2020.102267
Rouibah, K., Lowry, P. B., & Hwang, Y. (2016). The effects of perceived enjoyment and perceived risks on trust formation and intentions to use online payment systems: New perspectives from an Arab country. Electronic Commerce Research and Applications, 19, 33–43. https://doi.org/10.1016/j.elerap.2016.07.001
Santos, S., & Gonçalves, H. M. (2019). Multichannel consumer behaviors in the mobile environment: Using fsQCA and discriminant analysis to understand webrooming motivations. Journal of Business Research, 101, 757–766. https://doi.org/10.1016/j.jbusres.2018.12.069
Shankar, A., & Jain, S. (2021). Factors affecting luxury consumers’ webrooming intention: a moderated-mediation approach. Journal of Retailing and Consumer Services, 58, 102306. https://doi.org/10.1016/j.jretconser.2020.102306
Sharma, N., & Fatima, J. K. (2024). Influence of perceived value on omnichannel usage: Mediating and moderating roles of the omnichannel shopping habit. Journal of Retailing and Consumer Services, 77, 103627. https://doi.org/10.1016/j.jretconser.2023.103627
Stone, R. N., & Grønhaug, K. (1993). Perceived risk: Further considerations for the marketing discipline. European Journal of Marketing, 27(3), 39–50. https://doi.org/10.1108/03090569310026637
Yadav, R., Giri, A., Chakrabarty, D., & Alzeiby, E. A. (2024). Understanding the consumers webrooming in retailing industry: An application of uses and gratification and uncertainty reduction theory. Technological Forecasting and Social Change, 206, 123509. https://doi.org/10.1016/j.techfore.2024.123509