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    MARKETING MESSAGES, SEQUENTIAL EFFECTS, AND OPTIMAL DISCLOSURE

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    Name:
    Chen_temple_0225E_15445.pdf
    Embargo:
    2025-08-24
    Size:
    45.03Mb
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    Genre
    Thesis/Dissertation
    Date
    2023-08
    Author
    Chen, Han
    Advisor
    Srivastava, Joydeep
    Wang, Yang
    Committee member
    Kumar, Subodha
    Wattal, Sunil
    Department
    Business Administration/Marketing
    Subject
    Marketing
    Operations research
    Behavioral sciences
    Advertising
    Marketing mix
    Marketing models and analytics
    Price promotion
    Pricing
    Product recommendation
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/8984
    
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    DOI
    http://dx.doi.org/10.34944/dspace/8948
    Abstract
    Effects of marketing mix tools, such as price promotions and digital advertising, are dynamic and long-term. Yet marketing literature has mainly focused on their immediate and short-term effects. Marketing Mix changes consumers' state, such as expectations and beliefs, and the changed state affects consumers' subsequent behaviors and responses to marketing stimuli and treatment, which may cause unintended consequences and generate important marketing opportunities as well. In Essay 1, we uncover the perils of tensile discounts (e.g., maximum discounts such as "up to 60% off") by examining their effects on store visits and purchases. Through a series of studies and using a multi-method approach including empirical data analysis, quasi-field experiment, numerical simulations, and controlled lab studies, we find that despite the initial efficacy in shaping consumer discount expectations and stimulating store visits, a maximum discount (vs. a minimum discount such as "starting at 20% off" or a range discount such as "20% off to 60% off") could reduce consumer purchases in many conditions. There is thus a need to balance the outcomes of the two stages and choose the optimal tensile discount under different discount distributions to maximize store sales. In Essay 2, we investigate how digital platforms leverage curation source (algorithm or human) advertising to promote depth or breadth selling and best sequence these two types of advertising to further improve advertising effects. Through a survey study and a field experiment, we find that consumers have a lay belief about the competitive advantages of algorithms and humans that algorithms (humans) generate personalized (novel) recommendations, and importantly, they consider and purchase products similar (new) to their previous preferences when receiving such advertising. Moreover, the complementarity between depth and breadth selling can be best leveraged in sequential advertising by the initial breadth selling amplifying the subsequent depth selling effectiveness. Thus, a carefully-sequenced hybrid advertising can help cultivate consumers’ ever-renewing interests and consumption.
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