IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i5p3896-d1075438.html
   My bibliography  Save this article

The Role of Cognitive Absorption in Recommender System Reuse

Author

Listed:
  • Nirmal Acharya

    (Australian International Institute of Higher Education, Unit 2 & 3, 15 Anderson Street, Fortitude Valley, QLD 4006, Australia
    School of Business, University of Southern Queensland, Toowoomba, QLD 4350, Australia)

  • Anne-Marie Sassenberg

    (School of Business, University of Southern Queensland, Toowoomba, QLD 4350, Australia)

  • Jeffrey Soar

    (School of Business, University of Southern Queensland, Toowoomba, QLD 4350, Australia)

Abstract

E-commerce is the trade of services and goods via electronic means such as the Internet. It is critical in today’s business and user experience. Most current e-commerce websites employ various technologies such as recommender systems to provide customers with personalised recommendations. Taking this as a cue, this study investigates the effect of cognitive absorption to estimate the holistic experience of recommender systems on shoppers’ intentions to reuse recommender systems. Data collected from 366 online shoppers were analysed using structural equation modelling to test the proposed hypotheses. The findings highlight that cognitive absorption directly and indirectly affects shoppers’ behavioural intentions to reuse recommender systems. The results also exposed the moderating effect of gender on shoppers’ behavioural intentions to reuse recommender systems. An importance-performance map analysis was also conducted to identify significant areas of improvement for e-vendors. This study contributes to advancing existing knowledge relevant to shoppers’ behavioural intentions to reuse recommender systems. The study also provides e-vendor managers with insights into online shoppers’ decision making.

Suggested Citation

  • Nirmal Acharya & Anne-Marie Sassenberg & Jeffrey Soar, 2023. "The Role of Cognitive Absorption in Recommender System Reuse," Sustainability, MDPI, vol. 15(5), pages 1-23, February.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:3896-:d:1075438
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/5/3896/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/5/3896/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiaojing Sheng & Jianzhi Li & Mohammad Ali Zolfagharian, 2014. "Consumer initial acceptance and continued use of recommendation agents: literature review and proposed conceptual framework," International Journal of Electronic Marketing and Retailing, Inderscience Enterprises Ltd, vol. 6(2), pages 112-127.
    2. Marios Koufaris, 2002. "Applying the Technology Acceptance Model and Flow Theory to Online Consumer Behavior," Information Systems Research, INFORMS, vol. 13(2), pages 205-223, June.
    3. Nanda Kumar & Izak Benbasat, 2006. "Research Note: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites," Information Systems Research, INFORMS, vol. 17(4), pages 425-439, December.
    4. Mahnke, R. & Benlian, Alexander & Hess, Thomas, 2015. "A Grounded Theory of Online Shopping Flow," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 72630, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. D. Veena Parboteeah & Joseph S. Valacich & John D. Wells, 2009. "The Influence of Website Characteristics on a Consumer's Urge to Buy Impulsively," Information Systems Research, INFORMS, vol. 20(1), pages 60-78, March.
    6. Xiaolin Lin & Mauricio Featherman & Stoney L. Brooks & Nick Hajli, 2019. "Exploring Gender Differences in Online Consumer Purchase Decision Making: An Online Product Presentation Perspective," Information Systems Frontiers, Springer, vol. 21(5), pages 1187-1201, October.
    7. Dash, Ganesh & Paul, Justin, 2021. "CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    8. Sarstedt, Marko & Hair, Joseph F. & Cheah, Jun-Hwa & Becker, Jan-Michael & Ringle, Christian M., 2019. "How to specify, estimate, and validate higher-order constructs in PLS-SEM," Australasian marketing journal, Elsevier, vol. 27(3), pages 197-211.
    9. Ali Abumalloh, Rabab & Ibrahim, Othman & Nilashi, Mehrbakhsh, 2020. "Loyalty of young female Arabic customers towards recommendation agents: A new model for B2C E-commerce," Technology in Society, Elsevier, vol. 61(C).
    10. Boas, Taylor C. & Christenson, Dino P. & Glick, David M., 2020. "Recruiting large online samples in the United States and India: Facebook, Mechanical Turk, and Qualtrics," Political Science Research and Methods, Cambridge University Press, vol. 8(2), pages 232-250, April.
    11. Xinshu Zhao & John G. Lynch & Qimei Chen, 2010. "Reconsidering Baron and Kenny: Myths and Truths about Mediation Analysis," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(2), pages 197-206, August.
    12. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sriram Thirumalai & Kingshuk K. Sinha, 2013. "To Personalize or Not to Personalize Online Purchase Interactions: Implications of Self-Selection by Retailers," Information Systems Research, INFORMS, vol. 24(3), pages 683-708, September.
    2. Hu, Xi & Huang, Qian & Zhong, Xuepan & Davison, Robert M. & Zhao, Dingtao, 2016. "The influence of peer characteristics and technical features of a social shopping website on a consumer’s purchase intention," International Journal of Information Management, Elsevier, vol. 36(6), pages 1218-1230.
    3. Shabnam H. A. Zanjani & George R. Milne & Elizabeth G. Miller, 2016. "Procrastinators’ online experience and purchase behavior," Journal of the Academy of Marketing Science, Springer, vol. 44(5), pages 568-585, September.
    4. Aboubaker Ettis, Saïd, 2017. "Examining the relationships between online store atmospheric color, flow experience and consumer behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 37(C), pages 43-55.
    5. Zhang, Hong & Zhao, Ling & Gupta, Sumeet, 2018. "The role of online product recommendations on customer decision making and loyalty in social shopping communities," International Journal of Information Management, Elsevier, vol. 38(1), pages 150-166.
    6. Fang, Jiaming & Zhao, Zhirong & Wen, Chao & Wang, Ruping, 2017. "Design and performance attributes driving mobile travel application engagement," International Journal of Information Management, Elsevier, vol. 37(4), pages 269-283.
    7. Un-Kon Lee, 2021. "The Effect of Confirmation of Nation Brand Image in International Tourism Advertisement on Travel Intention of Foreign Tourists: The Case of Korean ITA for Chinese Tourists," SAGE Open, , vol. 11(1), pages 21582440209, January.
    8. Tibert Verhagen & Daniel Bloemers, 2018. "Exploring the cognitive and affective bases of online purchase intentions: a hierarchical test across product types," Electronic Commerce Research, Springer, vol. 18(3), pages 537-561, September.
    9. Thanh Tung Ha & Thanh Chuong Nguyen & Sy Sua Tu & Minh Hieu Nguyen, 2023. "Investigation of Influential Factors of Intention to Adopt Electric Vehicles for Motorcyclists in Vietnam," Sustainability, MDPI, vol. 15(11), pages 1-16, May.
    10. Wu, Ing-Long & Chen, Kuei-Wan & Chiu, Mai-Lun, 2016. "Defining key drivers of online impulse purchasing: A perspective of both impulse shoppers and system users," International Journal of Information Management, Elsevier, vol. 36(3), pages 284-296.
    11. Barney Tan & Cheng Yi & Hock C. Chan, 2015. "Research Note—Deliberation Without Attention: The Latent Benefits of Distracting Website Features for Online Purchase Decisions," Information Systems Research, INFORMS, vol. 26(2), pages 437-455, June.
    12. Zafar, Abaid Ullah & Shahzad, Mohsin & Ashfaq, Muhammad & Shahzad, Khuram, 2023. "Forecasting impulsive consumers driven by macro-influencers posts: Intervention of followers' flow state and perceived informativeness," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    13. Mwesiumo, Deodat & Halpern, Nigel & Budd, Thomas & Suau-Sanchez, Pere & Bråthen, Svein, 2021. "An exploratory and confirmatory composite analysis of a scale for measuring privacy concerns," Journal of Business Research, Elsevier, vol. 136(C), pages 63-75.
    14. Xitong Li & Jörn Grahl & Oliver Hinz, 2022. "How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment," Information Systems Research, INFORMS, vol. 33(2), pages 620-637, June.
    15. Arnold Kamis & Tziporah Stern & Daniel M. Ladik, 2010. "A flow-based model of web site intentions when users customize products in business-to-consumer electronic commerce," Information Systems Frontiers, Springer, vol. 12(2), pages 157-168, April.
    16. Malik Ishtiaq Ahmed & Raza Muhammad Ali & Hadi Noor Ul & Khan Mahwish J. & Hameed Farhina, 2023. "Social commerce constructs and purchase intention on social commerce sites: investigating the role of affective and cognitive attitudes in managing digital marketing challenges," Management & Marketing, Sciendo, vol. 18(s1), pages 474-495, December.
    17. Thomas Friedrich & Sebastian Schlauderer & Sven Overhage, 2021. "Some things are just better rich: how social commerce feature richness affects consumers’ buying intention via social factors," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(1), pages 159-180, March.
    18. Ammarn Sodawan & Robert Li-Wei Hsu, 2022. "Halal-Friendly Attributes and Muslims’ Visit Intention: Exploring the Roles of Perceived Value and Destination Trust," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    19. Pathak, Kanishka & Prakash, Gyan, 2023. "Exploring the role of augmented reality in purchase intention: Through flow and immersive experience," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    20. Gao, Lingling & Bai, Xuesong, 2014. "Online consumer behaviour and its relationship to website atmospheric induced flow: Insights into online travel agencies in China," Journal of Retailing and Consumer Services, Elsevier, vol. 21(4), pages 653-665.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:3896-:d:1075438. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.