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Where Should I Send It? Optimizing the Submission Decision Process

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  • Santiago Salinas
  • Stephan B Munch

Abstract

How do scientists decide where to submit manuscripts? Many factors influence this decision, including prestige, acceptance probability, turnaround time, target audience, fit, and impact factor. Here, we present a framework for evaluating where to submit a manuscript based on the theory of Markov decision processes. We derive two models, one in which an author is trying to optimally maximize citations and another in which that goal is balanced by either minimizing the number of resubmissions or the total time in review. We parameterize the models with data on acceptance probability, submission-to-decision times, and impact factors for 61 ecology journals. We find that submission sequences beginning with Ecology Letters, Ecological Monographs, or PLOS ONE could be optimal depending on the importance given to time to acceptance or number of resubmissions. This analysis provides some guidance on where to submit a manuscript given the individual-specific values assigned to these disparate objectives.

Suggested Citation

  • Santiago Salinas & Stephan B Munch, 2015. "Where Should I Send It? Optimizing the Submission Decision Process," PLOS ONE, Public Library of Science, vol. 10(1), pages 1-11, January.
    • Handle: RePEc:plo:pone00:0115451
    DOI: 10.1371/journal.pone.0115451
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    1. David Adam, 2002. "The counting house," Nature, Nature, vol. 415(6873), pages 726-729, February.
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    1. Paul Sebo & Jean Pascal Fournier & Claire Ragot & Pierre-Henri Gorioux & François R. Herrmann & Hubert Maisonneuve, 2019. "Factors associated with publication speed in general medical journals: a retrospective study of bibliometric data," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1037-1058, May.
    2. Tony E Wong & Vivek Srikrishnan & David Hadka & Klaus Keller, 2017. "A multi-objective decision-making approach to the journal submission problem," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-19, June.
    3. Zeynep Didem Unutmaz Durmuşoğlu & Alptekin Durmuşoğlu, 2021. "A TOPSIS model for understanding the authors choice of journal selection," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 521-543, January.
    4. Aderemi Oluyinka Adewumi & Peter Ayokunle Popoola, 2018. "A multi-objective particle swarm optimization for the submission decision process," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 98-110, February.
    5. Robert Finger & Nils Droste & Bartosz Bartkowski & Frederic Ang, 2022. "A note on performance indicators for agricultural economic journals," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(2), pages 614-620, June.
    6. Sergey Kolesnikov & Eriko Fukumoto & Barry Bozeman, 2018. "Researchers’ risk-smoothing publication strategies: Is productivity the enemy of impact?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1995-2017, September.

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