Person:
Truong, Huong May

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Huong May
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Truong
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IE University
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IE Business School
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Information Systems and Technology
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2016 - 201912020 - 20221
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    Publication
    Buyers’ Strategic Behavior in B2B Multichannel Auction Markets: When an Online Posted Price Channel Is Incorporated into a Dutch Auction System
    (Institute for Operations Research and Management Sciences, 2022-11-15) Truong, Huong May; Gupta, Alok; Ketter, Wolfgang; van Heck, Eric; https://ror.org/02jjdwm75
    Firms are increasingly adopting different sales channels to reach new potential buyers. Yet, extant research has mainly focused on business-to-customer (B2C) online and offline posted price channels. Business-to-business (B2B) multichannel and, especially, systems with multiple pricing mechanisms are largely underexplored. This paper investigates the strategic behaviors of B2B buyers in a unique system where an online posted price channel is incorporated into a Dutch auction market sequentially. We follow buyers’ purchasing paths and examine conditions under which B2B auction buyers will use the online posted price channel. We incorporate learning and experience and demonstrate how buyers’ behaviors evolve. We investigate an emerging group of buyers who use different price mechanisms and their surplus extraction activities. We further explore how the market flow changes when posted prices are incorporated. Our results, using an extensive data set from the world’s largest flower market, highlight the importance of quantity demand, product diversity, and experience in explaining the choice of the new posted price channel. We find a significantly higher average loss of surplus at the product level for multichannel buyers than for single channel buyers and a reduction in the number of small orders in the auction channel. Subsequently, theoretical and managerial implications for B2B multichannel markets and market design are discussed.
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    Publication
    Integrating learning styles and adaptive e-learning system: Current developments, problems and opportunities
    (Elsevier, 2016-02) Truong, Huong May; European Commissions; https://ror.org/02jjdwm75
    Learning styles which refer to students’ preferred ways to learn can play an important role in adaptive e-learning systems. With the knowledge of different styles, the system can offer valuable advice and instructions to students and teachers to optimise students’ learning process. Moreover, e-leaning system which allows computerised and statistical algorithms opens the opportunity to overcome drawbacks of the traditional detection method that uses mainly questionnaire. These appealing reasons have led to a growing number of researches looking into the integration of learning styles and adaptive learning system. This paper, by reviewing 51 studies, delves deeply into different parts of the integration process. It captures a variety of aspects from learning styles theories selection in e-learning environment, online learning styles predictors, automatic learning styles classification to numerous learning styles applications. The results offer insights into different developments, achievements and open problems in the field. Based on these findings, the paper also provides discussion, recommendations and guidelines for future researches.