IDEAS home Printed from https://ideas.repec.org/a/spr/custns/v2y2015i1p91-104.html
   My bibliography  Save this article

Which Modeling Scholars Get Promoted, and How Fast?

Author

Listed:
  • César Zamudio
  • Meg Meng

Abstract

The future of quantitative marketing is defined by its research output as much as by the researchers who produce it. Yet, little is known about the determinants of promotion and time to promotion among quantitative marketing scholars (or “modelers”) as well as whether their early signals of attractiveness in the job market are indicative of future success. In this article, we shed light on these issues by investigating the roles that research productivity, departmental characteristics, demographics, and coauthorship play in determining promotion and time to promotion from assistant to associate professor. We find that early signals of attractiveness do not play an important role in determining modelers’ promotion and time to promotion. Research productivity does, and its effect is moderated by whether modelers are employed in departments that offer Ph.D. programs. We also find that membership in various coauthorship social networks, or “communities”, is a robust predictor of promotion and time to promotion. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • César Zamudio & Meg Meng, 2015. "Which Modeling Scholars Get Promoted, and How Fast?," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 91-104, March.
    • Handle: RePEc:spr:custns:v:2:y:2015:i:1:p:91-104
    DOI: 10.1007/s40547-014-0030-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s40547-014-0030-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s40547-014-0030-z?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Grewal, Rajdeep & Dearden, James A. & Lilien, Gary L., 2008. "The University Rankings Game: Modeling the Competition Among Universities for Ranking," The American Statistician, American Statistical Association, vol. 62, pages 232-237, August.
    2. Jacob Goldenberg & Barak Libai & Eitan Muller & Stefan Stremersch, 2010. "Database Submission—The Evolving Social Network of Marketing Scholars," Marketing Science, INFORMS, vol. 29(3), pages 561-567, 05-06.
    3. Powers, Thomas L. & Swan, John E. & Bos, Theodore & Patton, John Frank, 1998. "Career Research Productivity Patterns of Marketing Academicians," Journal of Business Research, Elsevier, vol. 42(1), pages 75-86, May.
    4. Vikas Mittal & Lawrence Feick & Feisal Murshed, 2008. "Publish and Prosper: The Financial Impact of Publishing by Marketing Faculty," Marketing Science, INFORMS, vol. 27(3), pages 430-442, 05-06.
    5. Yupin Yang & Mengze Shi & Avi Goldfarb, 2009. "Estimating the Value of Brand Alliances in Professional Team Sports," Marketing Science, INFORMS, vol. 28(6), pages 1095-1111, 11-12.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ethan Pew & César Zamudio & Hua (Meg) Meng, 2021. "Beyond perception: the role of gender across marketing scholars’ careers, in reply to Galak and Kahn (2021)," Marketing Letters, Springer, vol. 32(3), pages 313-323, September.

    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. Surendra Rajiv & Junhong Chu & Zhiying Jiang, 2015. "Publication, Citation, Career Development, and Recent Trends: Empirical Evidence for Quantitative Marketing Researchers," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 71-90, March.
    2. Stijn M. J. van Osselaer & Sarah Lim, 2019. "Research productivity of faculty at 30 leading marketing departments," Marketing Letters, Springer, vol. 30(2), pages 121-137, June.
    3. Michael Lewis & Yeujun Yoon, 2018. "An Empirical Examination of the Development and Impact of Star Power in Major League Baseball," Journal of Sports Economics, , vol. 19(2), pages 155-187, February.
    4. Eelco Kappe & Ashley Stadler Blank & Wayne S. DeSarbo, 2014. "A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions," Management Science, INFORMS, vol. 60(6), pages 1489-1510, June.
    5. Rosenzweig, Stav & Grinstein, Amir & Ofek, Elie, 2016. "Social network utilization and the impact of academic research in marketing," International Journal of Research in Marketing, Elsevier, vol. 33(4), pages 818-839.
    6. Scott D. Grimshaw & Jeffrey S. Larson, 2021. "Effect of Star Power on NBA All-Star Game TV Audience," Journal of Sports Economics, , vol. 22(2), pages 139-163, February.
    7. Naidoo, Vik & Hollebeek, Linda D., 2016. "Higher education brand alliances: Investigating consumers' dual-degree purchase intentions," Journal of Business Research, Elsevier, vol. 69(8), pages 3113-3121.
    8. Soledad Moya & Diego Prior & Gonzalo Rodriguez-Pérez, 2014. "Research Patterns in the Spanish Accounting Academia," Investigaciones de Economía de la Educación volume 9, in: Adela García Aracil & Isabel Neira Gómez (ed.), Investigaciones de Economía de la Educación 9, edition 1, volume 9, chapter 30, pages 567-583, Asociación de Economía de la Educación.
    9. Ralf van der Lans & Bram Van den Bergh & Evelien Dieleman, 2014. "Partner Selection in Brand Alliances: An Empirical Investigation of the Drivers of Brand Fit," Marketing Science, INFORMS, vol. 33(4), pages 551-566, July.
    10. Cho, Yung-Jan & Fu, Pei-Wen & Wu, Chi-Cheng, 2017. "Popular Research Topics in Marketing Journals, 1995–2014," Journal of Interactive Marketing, Elsevier, vol. 40(C), pages 52-72.
    11. Brigida Blasi & Sandra Romagnosi & Andrea Bonaccorsi, 2018. "Universities as celebrities? How the media select information from a large research assessment exercise," Science and Public Policy, Oxford University Press, vol. 45(4), pages 503-514.
    12. Jeongeun Kim, 2018. "The Functions and Dysfunctions of College Rankings: An Analysis of Institutional Expenditure," Research in Higher Education, Springer;Association for Institutional Research, vol. 59(1), pages 54-87, February.
    13. Ellen Hazelkorn, 2011. "Measuring World-class Excellence and the Global Obsession with Rankings," Chapters, in: Roger King & Simon Marginson & Rajani Naidoo (ed.), Handbook on Globalization and Higher Education, chapter 29, Edward Elgar Publishing.
    14. Stremersch, S. & Camacho, N.M.A. & Vanneste, S. & Verniers, I.W.J., 2014. "Unraveling Scientific Impact," ERIM Report Series Research in Management ERS-2014-014-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    15. Olivier Chatain & Denisa Mindruta, 2017. "Estimating Value Creation from Revealed Preferences: Application to Value-based Strategies," Strategic Management Journal, Wiley Blackwell, vol. 38(10), pages 1964-1985, October.
    16. Hauke A. Wetzel & Stefan Hattula & Maik Hammerschmidt & Harald J. Heerde, 2018. "Building and leveraging sports brands: evidence from 50 years of German professional soccer," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 591-611, July.
    17. Matt Andrews & Peter Harrington, 2016. "Off Pitch: Football’s Financial Integrity Weaknesses, and How to Strengthen them," CID Working Papers 311, Center for International Development at Harvard University.
    18. Ferrara, Gerardo & Kim, Jun Sung & Koo, Bonsoo & Liu, Zijun, 2021. "Counterparty choice in the UK credit default swap market: An empirical matching approach," Economic Modelling, Elsevier, vol. 94(C), pages 58-74.
    19. Paulo Reis Mourao, 2016. "Soccer transfers, team efficiency and the sports cycle in the most valued European soccer leagues – have European soccer teams been efficient in trading players?," Applied Economics, Taylor & Francis Journals, vol. 48(56), pages 5513-5524, December.
    20. Jeremy T. Fox & David H. Hsu & Chenyu Yang, 2012. "Unobserved Heterogeneity in Matching Games with an Application to Venture Capital," NBER Working Papers 18168, National Bureau of Economic Research, Inc.

    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:spr:custns:v:2:y:2015:i:1:p:91-104. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.