INFORMS Open Forum

  • 1.  Innovative versus Incremental Research

    Posted 08-01-2016 11:49

    Innovative versus Incremental Research

    Authors (including myself) often receive comments from reviewers that their papers have incremental value, Knowing breakthroughs in any academic field are rare events, I often wonder if papers with incremental value are publishable especially when the measure of incremental value is somewhat subjective. Should we (as a research community) advocate incremental research?  

    We aspire to conduct innovative research. However, without incremental research, we cannot build a body of knowledge so that we can truly advance our understanding about a certain topic. For example, the “bullwhip” paper by Lee et al. (1997) has stimulated thousands of research papers that enable us to understand the information sharing from the perspective of different supply chain partners. In a similar vein, the “return policy” by Pasternack (1985) has generated thousands of research papers that focused on different variants of supply contracts.  (The reader is referred to Lariviere (2015) for an insightful perspective about research on supply chain contracts.) Therefore, innovative research and incremental research are symbiotic: one cannot survive without the other. If we agree with this logic, then incremental research can be valuable too! 

    Is incremental research publishable? I have this question in my mind for a long time, but I did not have a clear answer until after I attended a short speech delivered by Professor Wally Hopp of University of Michigan (the former Editor-in-Chief of Management Science) during a conference in 2015.  Professor Hopp commented that, when he was managing Management Science, the acceptance “bar” for modelling and analysis rigor was lower for innovative research, but it was higher for incremental research.  He opined that, for an innovative new problem, it is generally too much to expect an author to probe all of the issues of interest or to definitively demonstrate that the proposed methodology is the best available. But, after a topic area has been studied for a while and the contours of the problem have been defined, it is reasonable to expect authors to produce studies that are more complete in their scope and rigorous in their analysis.

    Everyone in the audience agreed with Wally’s remarks, but I wonder how one should set the bar for incremental research.  In my mind, we should measure the “value” of incremental research in relation to what is already known in the literature.  In other words, instead of judging on its  δ,  let us measure incremental research based on its value V, where and  K is the existing knowledge. By advocating both innovative and incremental research, all of us can create knowledge of high value.

    References

    Lariviere MA 2015. Supply Chain Contracting: Doughnuts to Bubbles. Manufacturing & Service Operations Management. http://dx.doi.org/10.1287/msom.2015.0567

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    Christopher Tang
    Professor
    University of California-Los Angeles
    Los Angeles CA
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  • 2.  RE: Innovative versus Incremental Research

    Posted 08-02-2016 10:28

    Thanks for this thoughtful piece Dr. Tang. I agree with you completely. 

    As a practitioner, I'm looking for the best solution, not the most innovative or the newest. So I don't care if a paper merely moves the ball further down the field. That is progress! In fact, making improvements can be just as hard, if not harder, than coming up with the original idea, which may have many issues left on the table (ah, those darned details!).

    When I find an idea I think might be helpful, it's very useful to see a citation trail of incremental improvements. That tells me the idea is perceived to have value, since so many folks are devoting their valuable research time to these improvements. Plus, each improvement likely points out a flaw/weakness in the original formulation.

    So, I second Dr. Tang's call for evaluating on value, not information content. I also liked his previous article on making research more relevant. 

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    Michael Beyer PE,CAP
    Data Scientist