Technology and geography in a paradigm shift: the case of Critical & Conflict Materials in ICT

Technology and geography in a paradigm shift: the case of Critical & Conflict Materials in ICT

Show Video

This first paper we have other stuff on on  the general topic is with Andreas Diemer   ex-phd student now a very uh promising researcher  in the University of at the University of   Stockholm. Richard Perkins that is my department  and Axel Gross that is an undergraduate student   in my department so it's a very explorative  study I will let's try to I mean I will try   to to go you know on the general picture more than  on the detail is very descriptive and uh you know   there is no real need to spend time on  details so I would like to have feedback   on the general idea so I will give  a bit of context very short background of   the literature because the problem is that it's  highly multi-disciplinary so   uh we are still digging into various streams  the idea why we are interested in that   very shortly data methodology and then show  you some very preliminary uh descriptive on the   technological side and the geography of technology side. So the context is the fact that the mining   of critical raw materials that includes also  the famous conflict minerals and I will   later undefined precisely and that combination  their use in many you know electrical electronic   advanced electronic products that we know provides  a very important material infrastructure to this   shift between industry 3.0 industry 4.0. However  very little is known on the technological and   geographical networks between the advances of  technology in this case in particular we had   to focus on one and so we selected ICT and that  part of artificial intelligence technologies that   are part of ICT are a subset of ICT and the  demand the technological demand of critical and   conflict materials. This has a number of important  implications for socioeconomic but also  

you know geostrategical consequences in  regions in countries government firms and you know   these resource dependent value chains. One example  just to give you the idea of what I'm talking   about you know the Cobalt demand for lithium-ion  battery is expected to double in three four   years and you see the import exports I mean are  involving some of the most troubled countries in   the world. This is just a snapshot obviously  we could expand far more in this direction.   The background literature okay that has  looked at critical and conflict materials is   really interdisciplinary and by interdisciplinary  I mean not only social sciences okay   but also a natural sciences, so for this work we  had interacted a lot with a group of geologists   in the british geological survey  because we really needed to understand a bit more   uh being you know a poor economic geographer  really doesn't grasp the complexity of in fact   we were also using the wrong terminology  at some point so this help helped us a lot.   So one stream of literature look at social  economic environmental political consequences   sourcing these related minerals or materials.  Another stream of the literature is   characterized as material criticality looks  at the security of the supply precisely at supply   chain disruption in various senses. Very related is  also the literature on material flow analysis that   basically maps stock and flows of minerals their  production-consumption across time and space,   and finally there is also the huge literature  on global production network global value chains   attached flagships in terms of the controller  multinational corporations and their geography   and this obviously has looked at this literature  into the extractive sectors and the backward   forward linkages that global value chains in this  resource-intensive industry can or cannot generate   okay. So this is the background we are still  you know consolidating that. Why this work?  

our concern is really innovation so what is an old idea that I had in mind actually   because somebody an old you know friend at SPRUE that is not there any longer we were   talking about it a long time ago  we were thinking oh you know invention of two   new technologies that are somehow implicated  that rely on this uh critical materials   so we focus on innovation we we look at patterns  okay is a patent based analysis but this   allows us to explore the relationship between  technological change and technological demand   for some of these elements natural elements.  And also shed light at the same time on the   geography of this demand and how this overlaps  or not with the with the geography of the supply   of these resources. This is an exploratory study  that tries to give a preliminary answer to the   following question to what extent the ICT-based  paradigm relies on technologies that are related   to these materials, how this intensity of critical  and conflict materials change over time in   ICT and what is the organizational national  subnational geography of in this you know   inventive activities or better the ownership of  of this inventive activities within the field   of ICT and how this compares with the geography of the supply. So the methodology these are the main   steps very very quickly. Okay we use a tax mining  okay natural language processing on USPTO data  

using the full descriptive text of all  patterns granted between 1976 and 2017.   Then try to limit our selection of both what we  mean by ICT AI and, on the other hand, conflict   and critical materials and we carry out a  very simple analysis of absolute relative   frequencies of keywords appearance for each  of the very detailed technological classes.   Obviously, these frequencies, are as I said, absolute  relative but we believe that the evidence we   have some validation also of this methodology  rough at the moment. But somehow comforting   evidence shows that these patterns might be  an effective way to directly capture this   relationship obviously this is a very descriptive  paper we don't claim causality we are just talking   about association and then we also extend the  analysis of path to patent citations because   patents in ICT AI obviously realize on other  patents that are from other technologies   that might be intensive or related to conflict  and critical materials that and that is an   indirect relationship across technologies  and then we carry out a very simple micro   level analysis of patent acini and looking at this  geolocalization to explore the geography of the   technological demand compared to that of supply  so critical and conflict material definition   in this paper we selected the four officially  officially defined as conflict minerals that is   the famous 3TG - Tin, Tungsten, Tantalum and Gold  this is what the the regulation of the world   level defined as uh conflict minerals cobalt is  not officially considered conflict minerals but   we selected it for a very similar  characteristic to the 3TG and   lithium same story for some characteristics  of also concentration of the supply across   the world and relationship with human rights  abuses exploitation and of of human rights in   general. So these are the six selected then what  we did is also to validate this yeah this oops  

i don't know why it's jumping we try to validate  this uh approach of keywords because because   obviously we have a problem of false positives  right because there might be that some patterns   actually the inventor you know report the fact  that he or she is looking at a way to substitute   this materials and therefore we investigate to  what extent let's say global trends in keywords   appearance predict global production okay of each  of these materials between the 70s and 1917 2017   so you can see then this is we run a regression  and you know this these charts gives you the the   the linear fit between let's say the the  the logs of production uh and the keyword uh   occurrence for the for the for this period and you  can see that i mean the the match is quite good   it's comforting our idea that this method is  capturing something that is very very aligned   i mean you can see that our measure seems to fit  the production data quite well okay with the with   the um with the exception maybe of tungsten that  is not so aligned but generally speaking data on   production of this each of this material comfort  that we are not picking up totally a random   phenomenon for the ICT an ICT related artificial  intelligence we follow the methodology that is   there first starting with the wipo definition  then using oecd classification and then   identifying AI patents in ICT following  two quite well-known approaches in order to   focus our analysis to all ICT and distinguishing  within ICT that part of ICT that is also is ai   so uh generally speaking these are just you know  a charts that show you that particularly since   the end of the 90s there is a surge in patenting  activity particularly related to the classes that   covers obviously uh communication information  technologies and this shift towards uh um   towards uh more and more i mean electronic  intensive kind of invention and innovation   activities now you can see on the other  charts that by selecting the first the top   uh the top classes excluding the big section of c  which is metallurgy and obviously is intrinsically   more related to the minerals okay and so we  can see that the the most the highest related   to these minerals and materials are in fact all  classes that are within ICT so um this is just   to show you again i have a hundred of these these  are the relative frequency of selected keywords   by IPC4 class so detailed technological  class and you can see by technology these   are supposed to be the top 40s obviously we have  also frequency by uh each of these materials or   absolute because some can obviously uh include  more than one keyword so more than one material   mineral material so anyway you can see that  there are and this i mean at the top are all   ICT technologies so what we ask very  simple in a very simple way to look at   if ICT is different from all other technology  in the use in reliance on this specific keyword   we run very very simple uh uh you know we examine  basically if there is a statistical significant   difference between ICT the blue line and all  the other technology green and then we also   look at AI technologies that are within ICT  separately okay so you can see that uh basically   you know dividing up the calculating conditional  means of relative frequently dividing uh broken   down this conditional means in an interval of five  years also to look at the how this relation   changed over time and the ninety percent interval  confidence a confidence interval can can tell you   you know in order to to compare across groups and  within the groups and what we we get is in fact   that ICT seems to be a substantial significantly  different from all uh all the other technologies   and that is not dependent on the subset of ai  within ict okay use keywords more intensely   and they use keywords more intensely over time  than any other technology and particularly this   relationship is stronger since the uh 2000 uh this  is okay this is another way this is the citation   analysis uh this is a a a chart that refers  only we in the subsequent analysis of citation   we focus on the most recent period so 2000  2017. what here is reported is just that   this is backward citation from ICT to  other technologies and what the graph   seems to suggest is basically that the the the  subclasses with higher centralities that are those   in blue actually use uh critical and conflict  material more intensely and therefore it would   seems that ICT technologies when citing non-ICT  patents prefer technologies that are intensive   according to our definition in critical and  conflict materials so for the citation analysis   what we do is i mean we follow that the classical  methodology of uh whole Jaffe and Trajtenberg   for taking into account the fact that over time  all patents stand obviously to cite more prior   art so more and so we basically uh demean citation  rates we wait for for uh for the average number of   citation by class so this is really very very uh  well-known stuff but what what is is interesting   to see is that uh uh the the the this is the  marginal effect of at least one keyword free   frequency on the citation rate and what we see  is that the higher the relative frequency of critical and conflict mineral keyword appearance  in technology the more likely is this technology   to be uh cited by the aggregate ICT technologies  now this relationship grows quite strongly uh up   to the 2005 but then tend to diminish to uh uh  2015 but remaining positive okay well for the   other technologies obviously this relationship is  is not positive although you can see that tends   to be insignificant at least but um in more  recent times so um geographical uh geographical   uh is uh uh what what's the time i'm losing a bit  track of the okay um the geographical analysis the   for the geographical analysis obviously we want  to look uh for the moment we have looked at   the patentastini so we want to just because we  were interested in knowing who owns the technology   more than who invents the technologies that is  a subsequent step that we might want to explore   later on and so uh there is obviously no surprise  in in seeing that these are the top 25 but in the   whole list we we see the big tech okay so the many  familiar electronics and so big tech primarily   located in japan japan is the country more more  present followed by the us and south korea so   the usual suspect okay Samsung IBM Canon Micron  Sony uh even Apple is there actually and uh few   chemical a pharmaceutical giant you can see here i  don't because if I don't have a Dupont for example   Bristol and Miles and there is also Pfizer there  these are the big pharmacan pharma that   as we know are the most uh as also i remember for  from my corridor and mentor John Cantwell are those   that diversify more technologically speaking over  very long period of time so they are active in   technologies that are not necessarily related  to their production lines now um geographical   analysis here is by country we we have a problem  of significance of data uh recording in the case   of taiwan and then china so there is a i mean  the series starts to be uh reliable from late 90s   but what we can see is that from here south korea  japan and taiwan are those picking up the most   particularly in the last couple of decades more  interestingly is to look at to repeat the same   exercise we did for uh the technologies but by big  areas okay using the united nation macro region   americas asia and europe now these are is  the same exercise okay conditional means   broken uh by introverts of five years over time  to capture this relationship and we can see that   i mean the three areas started from a comparable  level in 1975 and then you can see that the   americas okay became even significantly different  from the other areas although interestingly while   europe was going down and this obviously  reflects somehow also specialization behind   what what has grown particularly since the 2000  is asia and you can in ict and ai intersection   technologies and you can see that asia is although  is not significantly different from the americas   but is on the trend let's say to become so so then  we started to look at the specific geography of   all this right and these are simple maps okay the maps using ArcMap or whatever   software in order to identify the location   of the most productive assignees and so we we  we tried with different threshold uh in in the   case of us and europe a good one was those assignees  so those firms that have more than 100 patents   and in the case of asia we had to put  more than 500 patents here i report   these maps and you can see that it's interesting  because the geography of this most productive patent holder that are related  to this critical materials   are obviously in in specific locations where in  fact there is this preponderance of multinational   corporation big tech and clusters okay so i mean  it's california uh new york state and and texas   uh in the case of the us in europe you can  see that is mostly north of europe than london   a lot germany and also the netherlands belgium  but very very specific cluster so these firms   obviously interest some location in asia we see  that is obviously a tokyo the top location because   tokyo and osaka actually because osaka also have  uh one i mean it's one of the hubs but followed   by taipei singapore and beijing in china so then  in a subsequent step we are still working on that   this is very rough uh this is firm patenting  versus each side it's just one big map so you   cannot really see anything because it's difficult  to to uh to disentangle all the six minerals but   basically the message that we have in more detail  maps is that you know as expected the technology   is all global north and most not all but most of  the critical and conflict mineral particularly   the conflict actually subset are in the global  south so this is the first snapshot of the idea   and what we can conclude is that there is  evidence although imperfect although we are we are   you know uh um thinking about many possible  ways to think about this association between   ict technological paradigm and this conflict  mineral innovation uh first of all we want to   expanding other sets of technologies that are not  ict but also to refine a bit better this method   in order to clean it for example by uh i mean  there might be patents that are now relying on on   recycling these materials that can be confused  with ours i mean we are aware of a limit a series   of limitations on this however there is this  association and also data validation production   data i i forgot to say that the the the the  mining sites are comes from obviously a different   data set that is is uh based on the us geological  survey um and so um there are there are different   data sources to match also in order to validate  better this methodology um ict is significantly   different from other technologies in terms of  their reference to critical and conflict materials   we see that um there are two sort of forms of  special disparities or two levels of special   special inequality if you want that is the the  expected one between uh uh global south and   global north particularly and and here there is  also the attempt now with with another quarter to   capture better uh uh the some of these critical  or conflict materials because then there are   the rare earths and you know so there are  there is there is scope of of increasing the   the the analysis also from the material point of  view understanding better the material for which i   i as i told you we need support from  colleagues in in in different fields um   and also to explore for example in the  in the in the logic of the value chain   which are those that could in principle create  generate some kind of more positive spillovers   for the local uh for the local extraction  industry locally owned or miners and   then there is the second level of a special  disparity that sees the concentration of this   of this technological demand in some very few  location hotspot of the global north okay that   uh are the the the the the home of the big uh tech  uh and uh and so this connects to another another   you know other other lines of research that look  precisely at the monopoly of the the large tech   and their disruptive uh effects on on you know  on global north but also on global south and so   we we conclude by saying that you know this this  intuition that specific technologies area paradigm   have actually distinctive resource signature okay  it is a relation that is interesting to explore   and that has a lot of important implication  in terms of demand of these resources and   also geography of these resources so um it's  in progress thank you thank you very much thank you very much simona um so  if you want to stop sharing then uh   exactly i was i was trying on the topic yes so  that i can see the people yeah so we can all   also give the floor to uh people  that want to ask questions so   uh john goddard i was asking john do  you want to ask the question yourself you yes thank you hi there sir hey francis you  were getting on to my question towards the end   which was about the the industrial structure of  the supply side and the power structures there   and the companies and how the supply chain  was functioning and the extent to which it was   global north companies that were controlling the  supply chain as well could you elaborate a bit on   on on on that side of your analysis thank you  uh yeah thank you very much that side is not   in our analysis although we are obviously aware  and we are this is part also of of the future   of the research that has to really focus on the  value chain we haven't we are we have started by   focusing on technology okay it's it's a huge topic  so it's uh it's difficult to to but yes uh mining   companies and and the you know geographical origin  of the mining company is is very very important   matters a lot in particular matters because uh  in the last decades there has been a search of   chinese mining companies in particular  the the context of africa or the triangle   the the lithium triangle in in latin america  so that is something that we will try to attach   to this research and actually there is already  work done on that and therefore we will try to   connect if anyone is is actually has anything  on that we will be very very interested in   we cannot cover everything in this respect but  is a very crucial point thank you thank you hey lisa do you want to ask yes thank  you um nice to see you simona hi lisa   um you look really well thank you so much and  also i really enjoy your talk i have to say   absolutely fascinating something that uh  sometimes is forgotten what happens at the   very very very beginning of a value chain and i  was just wondering because i really have no idea   what kind of innovation are done on these in  relation to this ccm is that about mining is   about processing um i just could not visualize  what type of innovation would be patented in   relation to these mineralism another question that  i have if i may is is there any chance that some   of these innovation so these patterns on on cmm  so ccm can they can can they also be applied to   other industries like i'm thinking for example  automotive i'm thinking about i mean although   autos are becoming more and more digital uh enable  but still did you check or do you think is worth   checking whether the ccm patents might actually  be used in other sectors thank you very very   interesting presentation thank you thank you thank  you lisa thank you very much um uh yeah it's uh   it's a very wide use and it's related to precisely  batteries so we are now exploring precisely   uh i mean with the with the with the geo geology  friends they have a lot of industry let's say   connections for uh uh with the with the automotive  industry okay precisely because he's one of   the big user so consider here we are looking at  technologies not at industries but it's obviously   one link to be done as as john was suggesting  also you know this industry structure story okay   uh these are minerals i mean the cobalt is  crucial for miniaturization of electronic   electronic components okay so every single  mobile laptop has a cobalt inside okay   so a macroelectronic circuit so it is a very  wide range so we look we we had to select ict   technologies but i mean the the use of these  technologies at the industry level is wide okay so   i'm talking about ict technologies not necessarily  ict industries the user of the technology so   i mean it's uh it's uh um it's a very very  wide use because monetarization cannot happen   without some of these materials okay and then  the more you expand into other of this i mean for   example the rare earth the more you find specific  technologies that are specific to some industries   but ict being a you know as we know general  purpose eu it's used by a huge number of of   industries automotive is one big user okay so uh  this is again something that we we will uh we will   uh do also because by look as you know better than  me shifting to value chains you need industries   so uh it's it's a bit problematic because for  example it would be very interesting to and we   started to look at export imports of this critical  material which in some cases is very distorted   because just to give you an example the cobalt  that comes from the democratic republic of congo   is actually smogged through rwanda and so there  is a whole gray gray to not called dark area there   that you know it's uh it's difficult it  needs more thinking how to to capture there is work for everybody anyway here so join in i thank you very much thank you simona that  was very thought provoking it's a bit outside   my research area but it's it's really interesting  i think it will be really i have three types of   three kind of comments i think the first  would be really interesting to see what   size of economic activity depends on these  materials and i mean now it will be approaching   100 i think indirectly at least for sure  but it would be really interesting to   see if there is some sort of indication of  what we are talking about what is enabled   by these materials the second is i'm not familiar  with the data from the ustpo but my understanding   limited is that you it's the most expensive  patent office to register with and it's also   kind of necessary if you're doing business in  the us so you may have some self-selection in the   geography between america's asia and europe and  what you'll be observing probably is like the the   european and the asian are the the real tigers of  these countries that that register there probably   and the final thing is it will be very interesting  to to see if you can observe in the data   at what level of demand or price  or geopolitical reasons we have   episodes that create substitute  technologies so technologies that do   not use cobalt anymore because cobalt becomes  more expensive or is owned by a country that   another country doesn't work want to work  with et cetera but these are all nothing a bit   too simple no no no no you you touch upon a very  important point i mean size of the activity as   i said okay i mean this is the first step in this  research and so we had to start with something and   we started with technology uspto you are right  we are very well aware of the the bias however   think about something first of all us pto has  been the one that gives you more solid data   back on time okay so it really covers from the  70s onwards and therefore to look at the trend   is very very important it is also true  that this kind of technological development   is as our data set shows very clearly mostly  done by big tech and big tech wherever they are   they patent in all of these data sets now we can  at some point replicate once we are more uh you   know into the we can replicate with the you know  the european patent office but one actually one   interesting thing that is emerged by presenting  this work has been also to look at the chinese   patent data because chinese are very very big  in this and therefore it might be that the   number of smaller player appears so now i have a  chinese student that is looking into that because   obviously you know natural language processing  in chinese is beyond the the competences that   the research team has for the moment so that  is important but you are right i mean we   it's it's also in the paper this note on  the uspto that might be slightly biased and substitute technologies that is actually what is  in the conclusion uh critically uh highlighted   as one of the final objective of this research is  to look at the looking at this level of technology   over time if we can capture something that  departs and therefore that starts substituting   technologies that uh not only technically  substitute but technology that recycle better and   you know there is a potential for some kind of  prediction based on on this we have to refine a   little bit more and then the method in order then  to be able maybe to pick up something that is a   bit more let's say positive and cheerful because  here the story at the end of the day is not well i don't i don't see any more person um  wanted to ask any question but i have some   some comments uh so as uh lisa another say i  think it was very very interesting i think it's a   it's a noble way of always to think about  something that many other researchers have   have been looking at the past you know with all  the um pharmaceutical patterns history and things   like that in a more kind of novel and actual way  um because uh i think nowadays uh big firms are so   much concerned about also all the social corporate  responsibility uh i'm i'm also thinking that um   the social impact of those uh value chains if  you want uh it's something uh worth to explore   in particular because you're talking about those  countries and where those patterns have created   value you know to whom has benefited also thinking  about maybe ownership and corporate governance   you were talking about how chinese  companies are exploiting those kind of   mineral mines in using sometimes children so  i think that that there is a huge scope in   in thinking about the the social implications  of of all of these value chains but um that on   the on the on the origin uh maybe of this mineral  side on the other side i think that there is also   a new literature on on the value of patterns and  also thinking not only on the quantities but also   uh different patterns generate a different  value added and also they have different type   of value in where they are used so um i think it's  linked with what lisa was saying if they are here   some of them they might be more key enabled  technologies other might be more specific uh so   therefore maybe the use of one mineral or another  might have a different purpose as the final   value of that particular pattern um so um yeah i  think browning hall is doing a lot on the value of   patterns comparing to the quantity of patterns so  there are some papers on that um i think somebody   in the chat thank you raquel thank you very much  these are all very important considerations in   fact you saw in my very compacted one slide on the  literature there is already huge literature that   looks at this minerals and you know the link  with the corporate social responsibility now   i mean i i have my my own uh uh reservation let's  say on the on the on the tail of corporate social   responsibility okay because it's it's it's been  in the sense it's been a way also to shift to the   private business firm the the task of ensuring  that everything is okay and it's been there you   know also in the last let's say 20 years has  become very big but i see other colleagues like   elisa giuliani working a lot on that i know very  well her work actually this research has been   presented for the first time in a workshop  organized by me and elisa on the dark side of the   the the innovation of innovation at the  german last year and i mean you know   the work the serious work done on this shows that  a lot is actually window dressing okay so um i   i feel and i mean i'm not qualified to go into  that but i feel that there is seriously the need   to regulate this in a solid way i know that a  lot of work is is is being carried out at the   european commission level on this for example and  in the united states of america regard regulatory   bodies there is there are connection between  these two areas in this respect and i see things   moving more on that than telling firms  be good also because think about some   of these critical areas now the the democratic  republic of congo is estimated although this again   is you you you check different sources and you  see different estimates but to produce between   35 and 60 percent of the cobalt in the world now  talking about corporate social responsibility   in firms that are located there right i mean just  two days ago the italian ambassador was killed in   there okay under the the the eye of everybody  so i'm i'm not sure that is the way to go   something can be done to strengthen that in  certain contexts but i i am a bit uh uh skeptical   uh on on on the on the real solution leaning  on on on the corporate social responsibility   uh the value of patented is an excellent  suggestion uh because i believe that it's   very relevant in this so browning hall i  will i will check that is a very very good   suggestion and i saw so that john was mentioning  a sustainable development goal we we are in fact   trying to align with that literature too i have  another phd student who is actually focusing   on on sdg uh particularly  relative to africa focusing   to link this topic with sdg because  it's obviously very very important but as i said i mean wha what was a bit the um  you know the the spirit is this is a big topic   not we're not going to go into all the directions  because we don't have the competences to do that   okay there is all the the the the other side of  the story is in in the in the exploitation of   these minerals by local populations okay and that  could could be really a very important source of   local economic development and you know there  you need also other tools other methodologies   so it's it's really very open and it's just i  wanted to flag if anyone thinks about doing this   please let me know because we need in chronic then  there is rampant clay i don't know if you know him   and he does a lot on social impact assessment  he has uh also uh every year winter and summer   schools on social impact assessment with uh  practitioners and so uh and they do a lot of work   on africa different type of plantations and  exploitation so i think this is probably one   of the friends i can recommend you to go um i can  introduce you to him and and the wife that also   has a company on social impact assessment um yeah  so um yeah fascinating uh i think that uh we are   right on time i think uh so  if there is no more questions   um who can i ask a question yeah absolutely  yes please thank you so much for simula's talk   um i noticed you have a geographical analysis  and also you have the temporal analysis   about the change over time i just wondered  whether you have considered it would be um   any classroom pattern if you look at by the  country boundary um in terms of the way the   patent um emergence across the time because  i would imagine even though you mentioned   they are clustered in amsterdam and also some  major cities in major countries but i mean the   emergence of this patent ib actually occurred have  any patent based on one country or the randomly   appearance in different places mainly because of  a company um i wonder whether that's one aspect   that you have looked into and on the other  hand you mentioned you'll be interested in   explore the patent in china i thought i can  offer you a thought about my experience with   chinese patent um so basically the patent  system in china and they were designed   um in a different way in as incentive as uk system  and u.s system i remember like researcher told me   well they have to pay themselves to get patent and  also as a way of being examined by the government   and university as a way to get promoted so  i guess in from that perspective patent has   not only been as economic incentive for  a researcher but also they have their own   willingness to patent it so i would imagine that  would have an impact that could possibly lead to certain um i wouldn't know how to explain  that but i would think they are kitten   for a different reason and just thought on  that thank you no thank you very very much what you see about the location of obviously  i mean we start with the big firms or we start   with the big the big players okay because what we  we didn't know we didn't know but i mean really   the big majority is very very important that is  all very concentrated at the organizational level   and uh it's interesting because as you know  patents do not register only firms okay there   can be other organizations and um actually the  only non private owner non-business owner big is   the board of university of california that appears  in the the top 500 okay interestingly enough   so i mean you know we will go to and now i showed  you the maps with the threshold because otherwise   also in order to present the map you don't see  anything so it's also a choice a bit dictated   by visualization but we have to go much further  with the geographical analysis this was really   a preliminary story uh the chinese patents  i i know uh the very big difference so using   chinese patents won't obviously allow any  comparison with other patent sources okay while   tasers was saying epo data can give you a  bit different picture and they can be roughly   compared to your spto capturing chinese data  and is not it's not in that direction i know   i know here that we have a big problem of  quality in fact however it's interesting   because guess what looking at this preliminary uh  the big patent owner in this uh in this critical   and uh materials are not business firms  are universities in the case of china   so interesting yeah to to see yeah you  will see at some point i mean we can we can   also get in contact with this i would love to  follow up thank you so much um i also remember you   used to write about the structural agglomeration  do you think you might go into it and explore the   different kind of different type of agglomeration  type driven by transaction code or that kind of   structure to examine a little bit about it  there are different directions right i mean   it's it's it's a big job so we'll we'll i  have to find also some money for it because   you know is israel is rather uh is rather  labor intensive let's put it this way   so well thank you very much simona i think  everybody enjoyed very much your presentation   so it looks very very very promising so i think  i think we are all of us we are thinking in what   is coming next so uh keep working on that thank  you thank you so much thank you all for uh for a   very very nice exchange and as said if any of you  is doing something related because it's part of   a big puzzle and it would be really nice to share  thank you really very much it was a pleasure   and thank you very much all for uh joining  us today uh in two weeks time we will have   uh kevin morgan also uh giving a seminar so  um we look forward for the next seminar as   well um have a nice day and see you  soon bye bye bye bye thank you all

2021-03-04 22:52

Show Video

Other news