01578nas a2200541   4500008004100000245006500041210006200106260001200168300000800180490000600188653002600194653002400220653002600244653002000270653003300290653002400323653001800347653002500365653004200390653002100432653002600453653002200479653002500501653002700526653002900553653001900582653001700601653001500618653001500633653003200648653000900680653001700689653001500706653002200721653002600743653001500769653002400784653002500808653001800833653002000851653002000871653002500891653001300916653002700929100001800956700002300974856003900997       2019                        eng d00aEditorial: Celebrating Innovation in Florence (October 2019)0 aEditorial Celebrating Innovation in Florence October 2019  c10/2019  a3-40 v910abehavioural economics10abehavioural science10abibliometric analysis10abusiness models10aBuyer-Supplier Relationships10achoice architecture10acollaboration10aconsumer-to-business10aContent creator-based business models10acontent creators10acreativity management10adigital platforms10adigital technologies10adigital transformation10aDigital user involvement10adigitalization10adigitization10adisruption10ae-commerce10ahuman-centered data economy10aIIoT10aIndustry 4.010ainnovation10ainnovation policy10aintellectual commerce10aLiving lab10amission-led science10amultisided platforms10apersonal data10aresearch impact10asocial commerce10aSupplier Integration10ataxonomy10auser-generated content1 aTanev, Stoyan1 aSandstrom, Gregory  uhttp://159.203.47.210/article/127002038nas a2200265   4500008004100000022001400041245004800055210004600103260004200149300001000191490000600201520128700207653002601494653002401520653002401544653002201568653002401590653002101614100002001635700002101655700002101676700001701697700002001714856003801734       2019                        eng d  a1927-032100aGiving Science Innovation Systems a 'Nudge'0 aGiving Science Innovation Systems a Nudge  aOttawabTalent First Networkc10/2019  a51-610 v93 aIn this article we consider the role that contextual factors play in science innovation systems &ndash; that is, the choice architecture, that influences the orientation and outcomes of publicly-funded research. More specifically, we examine how choice architects, particularly policymakers and funding administrators, can affect the decision-making behaviour of researchers. The context for today&rsquo;s science innovation systems continues to shift as governments seek solutions to the world&rsquo;s &ldquo;grand societal challenges&rdquo;, such as climate change and ageing populations, in addition to greater and more demonstrable impact from funded research. This means that the assumptions of &ldquo;basic research [being] performed without thought of practical ends&rdquo; (Bush, 1945) that have shaped such projects, actually run counter to the growing expectations of greater commercialisation and use of multidisciplinary mission-led approaches. We argue that a closer examination of the choice architecture for publicly-funded research is required to understand and address how these potentially conflicting objectives may be pursued most productively through interventions that could form the basis of a novel, behaviourally-based toolkit for science innovation policy.10abehavioural economics10abehavioural science10achoice architecture10ainnovation policy10amission-led science10aresearch impact.1 ade Jong, Kirsty1 aDaellenbach, Urs1 aDavenport, Sally1 aHaar, Jarrod1 aLeitch, Shirley  uhttps://timreview.ca/article/127502080nas a2200205   4500008004100000022001400041245009400055210006900149260004200218300001000260490000600270520145000276653000901726653002101735653002201756653002301778653001501801100002101816856003701837       2018                        eng d  a1927-032100aFrom Organizations to Organizational Fields: The Evolution of Civic Innovation Ecosystems0 aFrom Organizations to Organizational Fields The Evolution of Civ  aOttawabTalent First Networkc06/2018  a34-470 v83 aContemporary approaches to urban technology emphasize local “innovation ecosystems”. Two organizational models – living labs and innovation integrators – are commonly used as hubs to broker these ecosystems. Curiously, both coexist in some cities, allowing a comparison of their impact and an analysis of their development over time and in context. The case studies presented in this article suggest that our analytical frameworks for technology policy may fall short, in that they contemplate only the organizations themselves – the living labs or innovation integrators. The dynamics observed in each city are well articulated, however, in the sociotechnical systems literature. The hub can be understood as a “niche”, which fosters radical innovations and new processes. As these prototypes are increasingly deployed and accepted, there is a regime shift, ultimately creating an experimentalist culture that fills the role previously held by the hub. This conclusion is neither a challenge to ecosystem theory nor a critique of innovation policy and its implementation. Rather, I suggest that we must extend these theoretical frameworks, drawing on sociotechnical systems literature to better account for institutions and for systems change as we design policy for urban technology. This article therefore makes a contribution by using a sociotechnical systems lens to explain the evolution of local urban innovation ecosystems.10acity10acivic technology10ainnovation policy10ainnovation systems10aLiving lab1 aClaudel, Matthew  uhttp://timreview.ca/article/1163