• Login
    View Item 
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Dissertations
    • View Item
    •   Home
    • UA Graduate and Undergraduate Research
    • UA Theses and Dissertations
    • Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UA Campus RepositoryCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournalThis CollectionTitleAuthorsIssue DateSubmit DateSubjectsPublisherJournal

    My Account

    LoginRegister

    About

    AboutUA Faculty PublicationsUA DissertationsUA Master's ThesesUA Honors ThesesUA PressUA YearbooksUA CatalogsUA Libraries

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    When Personalization Backfires

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    azu_etd_17808_sip1_m.pdf
    Size:
    3.317Mb
    Format:
    PDF
    Download
    Author
    Yi, John Jongsei
    Issue Date
    2020
    Keywords
    Identity threat
    Personalization
    Self
    Advisor
    Warren, Caleb
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Technological advances have enabled firms to track information about individual consumers and offer personalized recommendations, products, and services to those consumers. Intuitively, individual-level personalization should better serve the unique needs of each consumer (Arora et al. 2008; Franke, Schreier, and Kaiser 2010; Pine 2011), thereby increasing consumer loyalty and firm profitability. I illustrate a problem with technologies that enable personalization: personalized products, services, and experiences (hereafter, “products”) can threaten the self by highlighting aspects of a consumer’s identity that they may not like. Receiving a personalized product heightens consumers’ awareness of their past behavior, which increases the accessibility of the identity related to this behavior. But consumers may not always like or aspire to have the identity that a personalized product activates. Being associated with undesirable identities can pose a threat to the self, and consequently, consumers attempt to avoid products and behaviors that are linked to these negative identities (White and Argo 2009). We, therefore, hypothesize that personalized products will backfire when the personalization activates a feared identity, causing consumers to avoid using the product. Our findings contribute to theory on personalization (Arora et al., 2008) and associated concepts such as mass customization and one-to-one marketing (Franke et al. 2010; Pine 2011) and also work on identity-related consumption (White and Argo 2009; White, Argo, and Sengupta 2012; White and Dahl 2007), showing personalized products can highlight a feared identity, which risks repelling consumers.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Management
    Degree Grantor
    University of Arizona
    Collections
    Dissertations

    entitlement

     
    The University of Arizona Libraries | 1510 E. University Blvd. | Tucson, AZ 85721-0055
    Tel 520-621-6442 | repository@u.library.arizona.edu
    DSpace software copyright © 2002-2017  DuraSpace
    Quick Guide | Contact Us | Send Feedback
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.