IDEAS home Printed from https://ideas.repec.org/a/vrs/poicbe/v17y2023i1p1103-1118n15.html
   My bibliography  Save this article

Suspiciousness and Fast and Slow Thinking Impact on Trust in Recommender Systems

Author

Listed:
  • Rad Dana

    (Aurel Vlaicu University of Arad, Arad, Romania)

  • Cuc Lavinia Denisia

    (Aurel Vlaicu University of Arad, Arad, Romania)

  • Lile Ramona

    (Aurel Vlaicu University of Arad, Arad, Romania)

  • Cuc Paul Nichita

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Pantea Mioara Florina

    (Aurel Vlaicu University of Arad, Arad, Romania)

  • Anta Darius

    (Adlai E. Stevenson High School in Lincolnshire, Illinois, USA)

Abstract

By offering consumers more proactive and individualized information services, recommender systems have proven to be a significant answer to the problem of information overload. And collaborative filtering approaches have proven to be an important component of many such recommender systems, allowing for the development of high-quality recommendations by harnessing the preferences of communities of similar users. In this study, we argue that individual personality traits may play an essential role in ensuring general end-user confidence in recommender systems. Individual elements to be examined include social suspiciousness as a personality feature and Daniel Kahneman’s fast and slow thinking styles, which distinguish between two modes of thought: System 1 is rapid, instinctual, and emotive, while System 2 is slower, more deliberate, and more rational. Due to a lack of explanation or inaccurate recommendation results, users may not trust current recommender systems, which poses a significant challenge for those systems. As such, having a trustworthy recommender system is essential. Three different trust-aware recommender system types are analyzed systematically in this study: robust systems that filter misleading information such as spam and fake news; social aware conscious systems that benefit from users’ social connections; and explainable systems that offer justifications for recommended products. On a sample size of 487 Romanian respondents, in an online survey, we have analyzed the impact of individual factors on the trustworthiness of the three types of recommender systems. Results show that fast thinking fully mediates the relationship between social suspiciousness and trust in all three types of recommender systems.

Suggested Citation

  • Rad Dana & Cuc Lavinia Denisia & Lile Ramona & Cuc Paul Nichita & Pantea Mioara Florina & Anta Darius, 2023. "Suspiciousness and Fast and Slow Thinking Impact on Trust in Recommender Systems," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 1103-1118, July.
    • Handle: RePEc:vrs:poicbe:v:17:y:2023:i:1:p:1103-1118:n:15
    DOI: 10.2478/picbe-2023-0099
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/picbe-2023-0099
    Download Restriction: no
    File URL: https://libkey.io/10.2478/picbe-2023-0099?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lindsay P. Schwartz & Steven R. Hursh, 2022. "A behavioral economic analysis of smartwatches using internet‐based hypothetical demand," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2729-2736, October.
    2. Ioan RADU & Cleopatra SENDROIU & Mihai Ludovic DEMETER & Florin CAZACU, 2018. "Possible Future Applications of the Blockchain Technology," PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ECONOMICS AND SOCIAL SCIENCES, Bucharest University of Economic Studies, Romania, vol. 1(1), pages 245-251, April.
    3. OGREAN Claudia & HERCIU Mihaela, 2020. "Digital Transformation Of Centru Region – Romania. Needs Assessment," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 15(2), pages 270-281, August.
    4. Vasile Dinu, 2021. "Artificial Intelligence in Wholesale and Retail," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 1-5, February.
    5. Samson, Alain & Voyer, Benjamin G., 2012. "Two minds, three ways: dual system and dual process models in consumer psychology," LSE Research Online Documents on Economics 47252, London School of Economics and Political Science, LSE Library.
    6. Alain Samson & Benjamin G. Voyer, 2012. "Two minds, three ways: dual system and dual process models in consumer psychology," AMS Review, Springer;Academy of Marketing Science, vol. 2(2), pages 48-71, December.
    7. Camelia Grădinaru & Daniel-Rareș Obadă & Ioan-Alexandru Grădinaru & Dan-Cristian Dabija, 2022. "Enhancing Sustainable Cosmetics Brand Purchase: A Comprehensive Approach Based on the SOR Model and the Triple Bottom Line," Sustainability, MDPI, vol. 14(21), pages 1-22, October.
    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. Erlandsson, Arvid & Västfjäll, Daniel & Sundfelt, Oskar & Slovic, Paul, 2016. "Argument-inconsistency in charity appeals: Statistical information about the scope of the problem decrease helping toward a single identified victim but not helping toward many non-identified victims ," Journal of Economic Psychology, Elsevier, vol. 56(C), pages 126-140.
    2. Janotta, Frederica & Hogreve, Jens, 2024. "Ready for take-off? The dual role of affective and cognitive evaluations in the adoption of Urban Air Mobility services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 185(C).
    3. Samson, Alain & Voyer, Benjamin G., 2014. "Emergency purchasing situations: Implications for consumer decision-making," Journal of Economic Psychology, Elsevier, vol. 44(C), pages 21-33.
    4. Marion Garaus, 2020. "The influence of media multitasking on advertising effectiveness," AMS Review, Springer;Academy of Marketing Science, vol. 10(3), pages 244-259, December.
    5. Haase, Janina & Wiedmann, Klaus-Peter, 2020. "The implicit sensory association test (ISAT): A measurement approach for sensory perception," Journal of Business Research, Elsevier, vol. 109(C), pages 236-245.
    6. Mattavelli, Simone & Perugini, Marco & Richetin, Juliette, 2015. "When the Brand Refers to Me, I Prefer Going Green," 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy 202709, European Association of Agricultural Economists.
    7. Eisenbeiss, Maik & Wilken, Robert & Skiera, Bernd & Cornelissen, Markus, 2015. "What makes deal-of-the-day promotions really effective? The interplay of discount and time constraint with product type," International Journal of Research in Marketing, Elsevier, vol. 32(4), pages 387-397.
    8. Jebarajakirthy, Charles & Das, Manish & Shah, Dhara & Shankar, Amit, 2021. "Deciphering in-store-online switching in multi-channel retailing context: Role of affective commitment to purchase situation," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    9. Capelli, Sonia & Thomas, Fanny, 2021. "To look tasty, let's show the ingredients! Effects of ingredient images on implicit tasty–healthy associations for packaged products," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    10. Panzone, Luca & Hilton, Denis & Sale, Laura & Cohen, Doron, 2016. "Socio-demographics, implicit attitudes, explicit attitudes, and sustainable consumption in supermarket shopping," Journal of Economic Psychology, Elsevier, vol. 55(C), pages 77-95.
    11. Liu, Yanfeng & Cai, Lanhui & Ma, Fei & Wang, Xueqin, 2023. "Revenge buying after the lockdown: Based on the SOR framework and TPB model," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    12. Richetin, Juliette & Mattavelli, Simone & Perugini, Marco, 2016. "Increasing implicit and explicit attitudes toward an organic food brand by referencing to oneself," Journal of Economic Psychology, Elsevier, vol. 55(C), pages 96-108.
    13. P. Münchhalfen & R. Gaschler, 2021. "Attention Distribution of Current Key Investor Documents: Standardization as a Long-Term Goal of the PRIIP Regulation," Journal of Consumer Policy, Springer, vol. 44(1), pages 73-94, March.
    14. Victoria L. Crittenden & Robert A. Peterson, 2012. "The AMS review: year 2," AMS Review, Springer;Academy of Marketing Science, vol. 2(2), pages 45-47, December.
    15. Rutsaert, Pieter & Donovan, Jason & Murphy, Mike & Hoffmann, Vivian, 2024. "Farmer decision making for hybrid maize seed purchases: Effects of brand loyalty, price discounts and product information," Agricultural Systems, Elsevier, vol. 218(C).
    16. Simon Kloker & Tim Straub & Christof Weinhardt, 2019. "Moderators for Partition Dependence in Prediction Markets," Group Decision and Negotiation, Springer, vol. 28(4), pages 723-756, August.
    17. Sang Cheol Park & Munkh-Erdene Tserendulam & Sung Yul Ryoo, 2021. "The Two Minds of Non-Work-Related Computing in the Workplace," SAGE Open, , vol. 11(3), pages 21582440211, September.
    18. Wei He & Chenyuan Jin, 2024. "A study on the influence of the characteristics of key opinion leaders on consumers’ purchase intention in live streaming commerce: based on dual-systems theory," Electronic Commerce Research, Springer, vol. 24(2), pages 1235-1265, June.
    19. Yam B. Limbu & A. F. M. Jalal Ahamed, 2023. "What Influences Green Cosmetics Purchase Intention and Behavior? A Systematic Review and Future Research Agenda," Sustainability, MDPI, vol. 15(15), pages 1-15, August.
    20. Prabaharan M & M Selvalakshmi & R Christina Jeya Nithilia, 2024. "The Role of Digital Touchpoints in Car Purchasing - An Empirical Research Concerning the Indian Market," Post-Print hal-04668727, HAL.

    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:vrs:poicbe:v:17:y:2023:i:1:p:1103-1118:n:15. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.