IDEAS home Printed from https://ideas.repec.org/h/spr/prbchp/978-981-19-0357-1_14.html
   My bibliography  Save this book chapter

The Influential Role of Trust in Understanding Online Product Recommendation System

In: Future of Work and Business in Covid-19 Era

Author

Listed:
  • Priyadarsini Patnaik

    (Birla Global University)

  • Biswajeet Patnaik

    (KIIT University)

Abstract

Artificial intelligence-driven online product recommender (OPR) system is integrated with technology to interact and engage with actual and potential customers. So, marketers must understand how the consumer’s form their purchase intentions and their buying behaviour while they get recommendations from online product recommenders. Despite having greater access to information, customers still avoid online shopping and are reluctant to use online product recommendations due to a lack of trust. So, developing and maintaining a trust mechanism towards online product recommenders is very essential for success in digital commerce and to maintain long-lasting ties with online buyers. This study is aimed at exploring the impact of trust in online product recommender systems. In this study, survey data was analysed and a research model was proposed based on the hypothesis. The findings revealed that trust is the most significant element in online shopping, and if trust on OPR is higher, the purchase intention is also higher. The study provides guidance towards measuring the effectiveness of online product recommenders which will help marketers and researchers to understand the significant influence of trust on OPR.

Suggested Citation

  • Priyadarsini Patnaik & Biswajeet Patnaik, 2022. "The Influential Role of Trust in Understanding Online Product Recommendation System," Springer Proceedings in Business and Economics, in: Rabi Narayan Subudhi & Sumita Mishra & Abu Saleh & Dariush Khezrimotlagh (ed.), Future of Work and Business in Covid-19 Era, pages 155-170, Springer.
    • Handle: RePEc:spr:prbchp:978-981-19-0357-1_14
    DOI: 10.1007/978-981-19-0357-1_14
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    AI; OPR; Purchase intention; Trust;
    All these keywords.

    Statistics

    Access and download statistics

    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:spr:prbchp:978-981-19-0357-1_14. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.