IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v38y2019i6p913-917.html
   My bibliography  Save this article

Editorial: An Update on the Frontiers Section

Author

Listed:
  • K. Sudhir

    (Yale School of Management, Yale University, New Haven, Connecticut 06520)

Abstract

Frontiers is a new section positioned as a prestigious subbrand under the Marketing Science umbrella. Its purpose is to encourage and nurture timely research with potentially high impact in quantitative marketing with a differentiated format and review process. In this issue, we publish the first set of three papers in Frontiers. This editorial describes (i) the papers and how they fit the goals of Frontiers and (ii) the minor changes in the Frontiers’ review process to improve efficiency and consistency for both authors and the journal.

Suggested Citation

  • K. Sudhir, 2019. "Editorial: An Update on the Frontiers Section," Marketing Science, INFORMS, vol. 38(6), pages 913-917, November.
    • Handle: RePEc:inm:ormksc:v:38:y:2019:i:6:p:913-917
    DOI: 10.1287/mksc.2019.1199
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/mksc.2019.1199
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.2019.1199?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. Nico Neumann & Catherine E. Tucker & Timothy Whitfield, 2019. "Frontiers: How Effective Is Third-Party Consumer Profiling? Evidence from Field Studies," Marketing Science, INFORMS, vol. 38(6), pages 918-926, November.
    2. Pengyuan Wang & Guiyang Xiong & Jian Yang, 2019. "Frontiers: Asymmetric Effects of Recreational Cannabis Legalization," Marketing Science, INFORMS, vol. 38(6), pages 927-936, November.
    3. K. Sudhir, 2016. "Editorial—The Exploration-Exploitation Tradeoff and Efficiency in Knowledge Production," Marketing Science, INFORMS, vol. 35(1), pages 1-9, January.
    4. Xueming Luo & Siliang Tong & Zheng Fang & Zhe Qu, 2019. "Frontiers: Machines vs. Humans: The Impact of Artificial Intelligence Chatbot Disclosure on Customer Purchases," Marketing Science, INFORMS, vol. 38(6), pages 937-947, November.
    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. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    2. Tinglong Dai & Sridhar Tayur, 2022. "Designing AI‐augmented healthcare delivery systems for physician buy‐in and patient acceptance," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4443-4451, December.
    3. Muhammad Nur Firdaus Nasir & Iqbal Jaapar & Walid Muhmmad Syafrien Effendi & Fadly Mohamed Sharif & Khairulwafi Mamat & Nurul Farhana Nasir, 2024. "Exploring the Role of Artificial Intelligence in the Design Industry: Client Satisfaction through Enhancing Quality while Preserving Human Creativity," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(3s), pages 4538-4543, October.
    4. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    5. Katharina Klein & Luis F. Martinez, 2023. "The impact of anthropomorphism on customer satisfaction in chatbot commerce: an experimental study in the food sector," Electronic Commerce Research, Springer, vol. 23(4), pages 2789-2825, December.
    6. Siliang Tong & Nan Jia & Xueming Luo & Zheng Fang, 2021. "The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1600-1631, September.
    7. Xin (Shane) Wang & Neil Bendle & Yinjie Pan, 2024. "Beyond text: Marketing strategy in a world turned upside down," Journal of the Academy of Marketing Science, Springer, vol. 52(4), pages 939-954, July.
    8. Asim Ansari & Yang Li & Jonathan Z. Zhang, 2018. "Probabilistic Topic Model for Hybrid Recommender Systems: A Stochastic Variational Bayesian Approach," Marketing Science, INFORMS, vol. 37(6), pages 987-1008, November.
    9. Li, Tian-Ge & Zhang, Chu-Bing & Chang, Ying & Zheng, Wei, 2024. "The impact of AI identity disclosure on consumer unethical behavior: A social judgment perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    10. Baabdullah, Abdullah M. & Alalwan, Ali Abdallah & Algharabat, Raed S. & Metri, Bhimaraya & Rana, Nripendra P., 2022. "Virtual agents and flow experience: An empirical examination of AI-powered chatbots," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    11. Rathore, Bhawana & Sengupta, Pooja & Biswas, Baidyanath & Kumar, Ajay, 2024. "Predicting the price of taxicabs using Artificial Intelligence: A hybrid approach based on clustering and ordinal regression models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    12. K. Sudhir, 2018. "Editorial—Introducing A New Section— Marketing Science: Frontiers," Marketing Science, INFORMS, vol. 37(1), pages 1-4, January.
    13. Ulrich Gnewuch & Stefan Morana & Oliver Hinz & Ralf Kellner & Alexander Maedche, 2024. "More Than a Bot? The Impact of Disclosing Human Involvement on Customer Interactions with Hybrid Service Agents," Information Systems Research, INFORMS, vol. 35(3), pages 936-955, September.
    14. Carlson, Keith & Kopalle, Praveen K. & Riddell, Allen & Rockmore, Daniel & Vana, Prasad, 2023. "Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 54-74.
    15. Jana Holthöwer & Jenny Doorn, 2023. "Robots do not judge: service robots can alleviate embarrassment in service encounters," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 767-784, July.
    16. Affeldt, P. & Argentesi, E. & Filistrucchi, Lapo, 2021. "Estimating Demand with Multi-Homing in Two-Sided Markets," Other publications TiSEM 1317bf39-d02e-4f61-a34f-e, Tilburg University, School of Economics and Management.
    17. Justina Sidlauskiene & Yannick Joye & Vilte Auruskeviciene, 2023. "AI-based chatbots in conversational commerce and their effects on product and price perceptions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-21, December.
    18. Kamoonpuri, Sana Zehra & Sengar, Anita, 2023. "Hi, May AI help you? An analysis of the barriers impeding the implementation and use of artificial intelligence-enabled virtual assistants in retail," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    19. Pappas, Alec & Fumagalli, Elena & Rouziou, Maria & Bolander, Willy, 2023. "More than Machines: The Role of the Future Retail Salesperson in Enhancing the Customer Experience," Journal of Retailing, Elsevier, vol. 99(4), pages 518-531.
    20. Bradlow, Eric T. & Gangwar, Manish & Kopalle, Praveen & Voleti, Sudhir, 2017. "The Role of Big Data and Predictive Analytics in Retailing," Journal of Retailing, Elsevier, vol. 93(1), pages 79-95.

    More about this item

    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:inm:ormksc:v:38:y:2019:i:6:p:913-917. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.