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i'm here with Wharton management professor Tyler rye and doctoral student Adam caster who are here to talk about
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their paper cognitive neighborhoods in the valuation of innovation across national analysis welcome thank you
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thanks so tell us about your paper yeah so in a nutshell this paper is trying to
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understand exactly how classification systems which differ across countries how that affects outcomes animation in
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particular trying to understand how the classification system affects how patent
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examiner's search for prior art and how they find sort of what might be relevant
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or not relevant so what are some of the key takeaways of your paper so the key takeaways are that it's really important
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to understand how the classification system affects the way that an innovators innovation is going to be is
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going to be viewed and seen so if it's a sign to a certain class it's a class
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that is much more central and much more related to other technology classes it's
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going to be much more likely to be picked up by others when they're doing future examination search by not only
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patent examiner's but also inventors so it's going to much more likely we cited
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and probably much more likely to be more highly valued so that's an important key
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takeaway yeah absolutely you know something that's interesting to keep in mind when we're looking at patents and
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classification and the valuation of intellectual property is there's an assumption that the number of citations
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that a patent gets in future innovation is a reflection of its value and what Adams done really nicely in this paper
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is show that it's not just a reflection of the quality of the patent that's
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driving its valuation but it really is where it gets slotted into the classification system so examiner's like
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all of us use heuristics and shortcuts to think about what's related in what
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isn't and what we've done in the paper is actually modeled this out and shown
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the structural characteristics of the different patent classes in terms of how they relate to each other based on how
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examiners are searching and the big takeaway is that the same piece of intellectual property if it's in a class
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a patent class that is in the neighborhood of many examiners are more likely to then cite
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it in future patent searches and this is going to affect its valuation so irrespective of quality its examiner's
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it's their cognition and it's the properties of the categorization system
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that really seemed to be driving valuation in an important way as well as perceptions of what is a breakthrough
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technology versus what isn't and in to add on to that another important aspect
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that we find is that we're looking at cross different patent systems so we're
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looking at the US Japan and Germany and you can see that there is structural differences in the classification
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systems across these different patenting jurisdictions and that this itself you know just even looking at the exact same
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innovation being applied for in these different systems kind of very different outcomes purely based off of or at least
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in a strong part due to the fact that the way that the technology is classified is different and so this
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isn't really important for for practitioners to sort of be aware of and also just in terms of better
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understanding exactly not only evaluation itself but is how I was mentioning what might be breakthrough
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what might not be breakthrough what's the best way to ensure that something might be a breakthrough is going to be
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seen by the most people going forward so what conclusions have any surprised you
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so I think for me personally I expected that for technology classes that were very central so we're very related other
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technology classes I thought there'd be a downside in the sense that if it's
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highly related it might distract it might detract attention away from that focal class so if you think about a
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patent examiner inventor who has a technology and they're looking back if it's if the technology class itself that
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they're originally searching it is very broad they might leave as much time to
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search directly in that in that primary class so I was really expecting there to
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be sort of a negative effect as well at least in terms of saying that while it's
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going to it's going to say it's going to basically push attention further
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outwards and I thought there might be a negative effect what was rising to us is
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that we didn't find that at all in fact what we do find that most of the you
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know the difference in terms of what technologies get cited more often than not comes from citations from outside
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the class there was actually no negative effect within the class itself which I think for me was was
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surprising I thought there'd be some some negative associated with with sort
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of being more central yeah and for me my my big takeaway is uh you know a little
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less complicated in your uh which I agree absolutely everything you've just said but it surprised me that the same
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piece of intellectual property applied for in different systems is valued so differently you know you'd expect that
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there is some sort of underlying quality that's reflected in the valuation of
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intellectual property and the degree to which it's picked up and built on and
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what we found is that I mean this is true to a certain extent but depending on the properties of the classification
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system this changes in really quite dramatic ways and it you know it really speaks to the cultural creation of
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innovation and innovation outcomes what are some of the practical implications of your findings yeah so I think that
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the first important thing to note especially is is sort of practitioners to understand the differences across
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these systems now I think admittedly some the research might be one step away from you know really being able to
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explain exactly how should patent applicants really proceed in terms of trying to maximize value so first I
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think a first step in an area for future researchers to understand exactly how much agency they have in terms of what
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classes are assigned certainly there is at least indicators that the USPTO for instance has a very strong hand and sort
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of affecting what the eventual primary classification is going to be which is what we're looking at but also when
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applicants file for a patent application there they're required to include a
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class when in their first application so i think it's it's clear that the you
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know the class is important what the next step is to understand exactly how much agency and what can Apple can't do
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in order to ensure that their application their applications are going to be funneled into the classes that
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they want it and be seen by the the proper examiner's so what sets your research apart I think you kind of
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touched on that could you explain a little bit more yeah absolutely so theoretically there is a large
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difference in terms of the way that classification understanding its use as a heuristic has been used and so this
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context is very different because we're trying to understand search and particularly sir
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for innovation so generally generally the research is focused on consumers looking for specific products which is a
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slightly different context one where they already have in their mind a certain type of product they're going to
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look for and so the dynamics are very different when you're thinking about technology on the other hand especially
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in this paper we're looking at nanotechnology which for a large part of the period that we're studying is a very
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nascent area is to understand exactly how do people make sense of these new technologies and in particular when
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they're when they're searching trying to understand that it's related where where
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might this new you know piece of this new innovation or adventure and fit into the sort of broader sense and where my
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in have might one frame it in order to best take advantage of of the you know the institution in terms of its
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classification or aspects or become really important I think this is something that's that sort of missed and
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more broadly we have a much more fluid view of the way that these classification systems work so
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theoretically most of the research is sort of focused on how these classifications are sort of fixed in
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time and all individuals really have this sort of the same premonition or the same sort of cognitive schema of what
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these classification systems look like whereas whereas we're taking much more
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fluid look and trying to look at how a new technology class know technology is starting to become you know sort of more
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mainstream and sort of how that affects the innovations over time yeah and I the
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only thing I'd add to that is I think that one of the unique things about this
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work that we're doing is instead of looking at individual categories or individual classifications which is the
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traditional approach in the academic literature we're really highlighting the
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influence of the properties of the classification system and so we're taking a level of analysis from here and
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expanding it out to the broader topography of categories and how they relate to each other now this leads to
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some different questions and this is part of you know the basis for you know want to undertake this research in the
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first place because the traditional prediction is that if you want to be understood and you want to be valued you
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have to fit neatly within a particular category and so this applies very generally to technologies to people to
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organizations and there's a large literature that's looked at this but what hasn't really been looked at is
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how the embeddedness of the category that you're in in a broader system of classification effects outcomes for you
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as a technology a person and organization whatever it is and that's really the piece that we're bringing to
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bear in this research showing that yes it's important what category you're in
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but really what's driving the effects especially when valuation is based on being on the radar of lots of other
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things is where this class sits in the broader system what lessons are in your research applicable to venture
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capitalists inventors and businesses are there any yeah I think so just as Tyler
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was mentioning oftentimes we think of it being necessary to sort of fit into a single category have a very very salient
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identity that fits into a single category and that that is important to degree but especially for I think in
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particular new innovations new technologies is in order to get garner widespread attention you actually want
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to sort of sometimes appear more broad so in particular it might not be a bad thing I think we're showing that's not a
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bad thing to actually fall into multiple different classes because that's going
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to garner more intention so I think fundamentally speaking it's important of
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a sealing identity at the same time I think our research is really going the direction of showing that actually
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there's a lot of benefits to sort of spanning multiple different classes product headers etc because that might
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garner more attention which ultimately my benefit producers themselves and venture capitalist in terms of thinking
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about who they should invest in and the other thing that I'd add to that is to
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the extent that venture capitalists or other audiences are looking at patent citations as a way to value startups IP
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or even an established company's intellectual property you know they might be picking up some misleading
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stuff here so doing close to diligence is probably still very important especially when you're thinking about
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something like nanotechnology that really is global in its scope and revolutionary and its potential unless
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you're actually getting under the hood and understanding the nuts and bolts of
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what this technology is doing what its potential is in the real world you might be missing stuff if you're just looking
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at things like you know the traditional measures of forward citations it's picked up by a lot of other
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innovations this must be important or it's picked up by lots of diverse innovations so this must be a
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breakthrough so what we're showing is you know there's a piece to that that's
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true but if you're relying just on that you're probably missing a big chunk of
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what's actually driving quality in this field you