Proceedings of the 8th International Conference on Intellectual ...

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Giedrius Jucevičius form for own purposes (e.g. incorporate into s<strong>of</strong>tware that is later taken to <strong>the</strong> market). However, in a well-crafted business model, <strong>the</strong> benefits <strong>of</strong> knowledge partnership outweigh <strong>the</strong> possible free rider effects because innovators retain o<strong>the</strong>r sources to make pr<strong>of</strong>its. A distinction should be made between private open innovation and open source innovation (Huizingh, 2011). Both can be characterised by <strong>the</strong> open process (i.e. involving multiple outsiders in product development), yet differing in terms <strong>of</strong> outcome, which remains open in <strong>the</strong> case <strong>of</strong> open source innovation (e.g. Linux) and closed in <strong>the</strong> case <strong>of</strong> private open innovation. In <strong>the</strong> latter case, things usually get more complicated. There is always a potential trade-<strong>of</strong>f situation between <strong>the</strong> public participation and private appropriation unless “<strong>the</strong> best <strong>of</strong> two worlds” solution is achieved. Three major models <strong>of</strong> co-creation that have recently emerged in <strong>the</strong> new industrial paradigm <strong>of</strong> peer production can be distinguished (Bauwens, 2009): Commons-centred peer production where community plays <strong>the</strong> key role, is strong enough to sustain its own infrastructure and to cooperate with <strong>the</strong> market players (e.g. Linux open source s<strong>of</strong>tware). The value <strong>of</strong> such knowledge partnerships remains public (e.g. protected by GPL licence). Sharing environment, where <strong>the</strong> platform for knowledge sharing is owned by third party (e.g. company), which monetizes <strong>the</strong> attention space, while <strong>the</strong> community <strong>of</strong> knowledge sharers has indirect influence over <strong>the</strong> platform. The value is appropriated by <strong>the</strong> platform owner and <strong>the</strong> community members (e.g. protected by <strong>the</strong> Creative Commons licence). Crowdsourced environment, where knowledge providers are isolated from each o<strong>the</strong>r, even competing against each o<strong>the</strong>r for <strong>the</strong> benefits (e.g. monetary prize) <strong>of</strong>fered by <strong>the</strong> platform owner. There is no community solidarity and <strong>the</strong> benefits are appropriated by <strong>the</strong> owner <strong>of</strong> <strong>the</strong> platform (e.g. by providing an award for <strong>the</strong> best “crowdsourced” solution) So far <strong>the</strong> discussion was more about <strong>the</strong> incentives and safeguards from <strong>the</strong> perspective <strong>of</strong> <strong>the</strong> lead partner who initiates <strong>the</strong> knowledge sharing. However, any successful knowledge exchange is a twoway process, thus one should also address <strong>the</strong> main incentives behind <strong>the</strong> partner participation in knowledge partnership. Understanding <strong>the</strong> incentives behind <strong>the</strong> involvement <strong>of</strong> network actors will also help envisage <strong>the</strong> appropriate mechanisms <strong>of</strong> control. The research on <strong>the</strong> open innovation has shown that companies perform more inbound than outbound activities, i.e. are more willing to attract <strong>the</strong> external knowledge-related resources than to open up <strong>the</strong>ir own resources to o<strong>the</strong>r stakeholders. Many firms are still largely protective <strong>of</strong> <strong>the</strong>ir own intellectual capital (e.g. fearing to give away <strong>the</strong>ir “golden goose” in <strong>the</strong> innovation market), while <strong>the</strong>ir main concern should be about appropriation <strong>of</strong> pr<strong>of</strong>its from innovation (Huizingh, 2011). One should distinguish between two types <strong>of</strong> methods for capturing value from innovations – formal and informal (Huizingh, 2011). The formal methods rely mainly on <strong>the</strong> legal means <strong>of</strong> protection, such as copyright, trademark or patent protection, which are <strong>of</strong>ten hard to enforce while participating in <strong>the</strong> knowledge partnerships. The informal methods include <strong>the</strong> first mover advantage, <strong>the</strong> lock-in <strong>of</strong> customers, network and tipping effects. There is a bulk <strong>of</strong> research showing that formal methods, such as patents, are not quite useful for capturing <strong>the</strong> commercial value in many industries (except chemicals and pharmaceuticals), while <strong>the</strong> absolute majority <strong>of</strong> patents remain unused by <strong>the</strong>ir owners. The copyright only protects <strong>the</strong> original piece <strong>of</strong> work, but not <strong>the</strong> ideas and concepts, which are very easily leaked into <strong>the</strong> outside world. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> informal methods seem to be <strong>of</strong> greater use for capturing <strong>the</strong> ultimate value, especially in <strong>the</strong> open innovation environment. They rely more on <strong>the</strong> social-economic behaviour <strong>of</strong> actors (e.g. building <strong>the</strong> critical mass <strong>of</strong> customers) than on <strong>the</strong> legal provisions and are more suitable in <strong>the</strong> environment <strong>of</strong> knowledge exchange. Never<strong>the</strong>less, one can find a plenty <strong>of</strong> networks and communities <strong>of</strong> knowledgeable stakeholders, which fail to deliver a fully functioning revenue model. The control and commercialization <strong>of</strong> value out <strong>of</strong> open knowledge partnerships in many instances still retains its controversies. 4. Monetary vs. non-monetary incentives <strong>of</strong> knowledge sharing The decision to participate in open collaborations is driven by two sets <strong>of</strong> incentives – monetary and non-monetary. The role <strong>of</strong> monetary and non-monetary incentives depends to a large extent on <strong>the</strong> 268
Giedrius Jucevičius nature <strong>of</strong> partnership, i.e. pr<strong>of</strong>it-seeking vs. non-pr<strong>of</strong>it seeking, private goods vs. public goods, as well as on <strong>the</strong> intrinsic motives <strong>of</strong> <strong>the</strong> parties (e.g. goodwill, pr<strong>of</strong>essional development, reputation, money, etc.). Conventional logic suggests that monetary incentives are more likely to be present in <strong>the</strong> pr<strong>of</strong>itseeking partnerships, whereas non-monetary incentives should prevail in <strong>the</strong> non-pr<strong>of</strong>it seeking communities. However, <strong>the</strong> practice <strong>of</strong> knowledge partnerships is not that simplistic. As far as monetary incentives are concerned, a distinction can be made between direct vs. indirect, or short-term vs. long-term incentives. The direct monetary incentives imply that <strong>the</strong> knowledge provider is motivated by immediate monetary gains from knowledge sharing (e.g. <strong>the</strong> financial prize for providing innovative solution in <strong>the</strong> “idea contest”). The indirect monetary incentives mean that knowledge provider may expect financial returns in o<strong>the</strong>r forms and contexts <strong>of</strong> participation (e.g. receiving potential contracts and job <strong>of</strong>fers from o<strong>the</strong>r participants <strong>of</strong> knowledge partnership). Most limitations <strong>of</strong> monetary incentives are related to <strong>the</strong> intangible nature <strong>of</strong> knowledge (especially, in cases when knowledge is not codified). At least four major problems with monetary incentives can be noticed (Ghosh, 2004): Matching <strong>the</strong> right buyer with <strong>the</strong> right knowledge seller is <strong>of</strong>ten very complicated. The quality <strong>of</strong> knowledge to be received is very hard to evaluate before establishing <strong>the</strong> market relationship. One should also add that this might as well be a problem <strong>of</strong> knowledge recipient, who might fail to appreciate <strong>the</strong> value <strong>of</strong> shared knowledge due to inadequate absorptive capacity. Successful output / pr<strong>of</strong>it may be <strong>the</strong> result <strong>of</strong> different pieces <strong>of</strong> knowledge that belong to different providers so that attributing adequate monetary value to every piece becomes next to impossible. Besides, knowledge may be only a part <strong>of</strong> ultimate success, with o<strong>the</strong>r key “ingredients” - efforts, determination and organization - being as important. Quite <strong>of</strong>ten <strong>the</strong> parties to knowledge exchange have no clear understanding <strong>of</strong> <strong>the</strong> expected outcomes from <strong>the</strong> knowledge sharing, what makes <strong>the</strong> ex ante evaluation <strong>of</strong> knowledge very difficult. Some successful knowledge-intensive business initiatives that are based on monetary incentives, such as Innocentive, manage to escape most <strong>of</strong> <strong>the</strong> above mentioned limitations. It represents a well thought-out business model with successfully balanced structure <strong>of</strong> incentives and value appropriation. InnoCentive acts as an intermediary for crowdsourcing <strong>the</strong> technological solutions, mainly in <strong>the</strong> field <strong>of</strong> chemical engineering, by building and connecting <strong>the</strong> communities <strong>of</strong> problem seekers and problem solvers. It helps problem seekers to formulate <strong>the</strong> problem in a way that is clear to solution providers without disclosing too much “discrete” information about <strong>the</strong> company, as well as takes care <strong>of</strong> <strong>the</strong> intellectual property issues. Innocentive also builds and engages <strong>the</strong> community <strong>of</strong> problem solvers, who get <strong>the</strong> financial reward in case <strong>of</strong> success (next to <strong>the</strong> recognition as talented problem solver). Innocentive revenue is enabled by <strong>the</strong> membership fees and commission from <strong>the</strong> prize that is awarded to <strong>the</strong> successful problem solvers. On <strong>the</strong> o<strong>the</strong>r hand, Innocentive cannot be regarded as a true knowledge partnership because it is more a meeting place <strong>of</strong> providers <strong>of</strong> knowledge-based solutions and providers <strong>of</strong> financial rewards (ra<strong>the</strong>r than <strong>the</strong>ir internal knowledge). Not surprisingly, in such “virtual marketplace” <strong>the</strong>re is not much controversy concerning <strong>the</strong> use <strong>of</strong> monetary incentives, as well as IP protection (i.e. <strong>the</strong> solution seeker fully appropriates <strong>the</strong> IP by paying <strong>the</strong> solution provider <strong>the</strong> agreed financial award). There are many instances when <strong>the</strong> non-monetary incentives seem to be more effective at encouraging knowledge sharing. Nei<strong>the</strong>r individual, nor collective pay-for-performance schemes can be effective at promoting <strong>the</strong> knowledge sharing if <strong>the</strong>y are not supported by “s<strong>of</strong>t” factors, such as organizational loyalties or strong intrinsic values that constitute <strong>the</strong> basis <strong>of</strong> trust (Ghosh, 2004). The “s<strong>of</strong>t”, non-monetary factors may also act as strong deterrents from free riding activities in <strong>the</strong> collective knowledge sharing processes. Although free riding behaviours can be controlled through extrinsic feelings <strong>of</strong> shame by <strong>the</strong> peers, it is more effective to develop <strong>the</strong> intrinsic feeling <strong>of</strong> guilt, which is usually present in groups with strong organizational loyalty (Kandel and Lazaer, 1992). However, such loyalties are more difficult to achieve in <strong>the</strong> open partnerships that may not always possess common goal or identity. 269
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Proceedings <stron
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Contents Paper Title Author(s) Page
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Paper Title Author(s) Page No. Main
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Paper Title Author(s) Page No. Know
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Preface These proceedings represent
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TU Dortmund, Germany, ); Wing Bun L
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William Halal is Prof</stro
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Evgeny Blagov has obtained a specia
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science and mathem
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George Majdalany is a PhD candidate
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Joyce Nesamani Simson is a PhD cand
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Manpower Discipline Based on Knowle
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Peyman Akhavan et al. brains, knowl
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Peyman Akhavan et al. showed that o
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Peyman Akhavan et al. appropriate l
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Peyman Akhavan et al. sources for c
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Attitudes Towards Changes and Organ
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Ruth Alas et al. During the
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Professional inter
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Ruth Alas et al. Table 4: Correlati
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Research was supported by ETF Grant
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Rivadávia Correa Drummond de Alvar
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5. Conclusions Rivadávia Correa Dr
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Toward a Meta-Synthe</stron
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Xiaomi An et al 2.3 Reasons for dev
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Xiaomi An et al PTC works closely w
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Xiaomi An et al The first is an adm
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Xiaomi An et al policy reflections
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Figure 1: Transmission gear Marko A
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Marko Anzelak et al. knowledge basi
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Marko Anzelak et al. 72% recognise
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Marko Anzelak et al. virtually all
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Gabriel Prananingrum Aryanindita an
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Rita Babiliūtė and Kęstutis Kri
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Knowledge Management, Cultural Know
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Leonard Barnett and Edward Carter 2
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Leonard Barnett and Edward Carter p
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Leonard Barnett and Edward Carter p
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Leonard Barnett and Edward Carter d
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Impact of Knowledg
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Bob Barrett shorter product life-cy
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Bob Barrett 6. Concept of</
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Bob Barrett Brown, J.S. and Duguid
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Aurilla Aurelie Bechina and Eli Hus
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Lorne Booker et al. Knowledge is us
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Figure 1: Business Valuation Knowle
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3.4 Practitioner knowledge market L
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4. Implications Lorne Booker et al.
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Strategic Thinking Dimensions in Em
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Constantin Bratianu et al. shows <s
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Constantin Bratianu et al. Academy
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Constantin Bratianu et al. cases wi
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Constantin Bratianu et al. Pinker,
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Delio Ignacio Castañeda and Sandra
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Quality in Teacher Education: A Sys
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Rajendra Chetty The mechanism <stro
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Academic leadership Rajendra Chetty
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Rajendra Chetty There must be a re-
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Developing Personal Knowledge Manag
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Thirathep Chonmait
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Thirathep Chonmait
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The Relationship Between Knowledge
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Samuel Kai Wah Chu et al. A knowled
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Samuel Kai Wah Chu et al. negative
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Samuel Kai Wah Chu et al. Questionn
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Samuel Kai Wah Chu et al. few done
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Value Creation Through Collaborativ
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Ridha Derrouiche et al. level for e
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Ridha Derrouiche et al. best, <stro
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Ridha Derrouiche et al. experience
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Ridha Derrouiche et al. Of course,
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Organizational Learning and Transfo
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Irra Chrisyanti Dewi was carried ou
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Irra Chrisyanti Dewi Table 2: Valid
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Irra Chrisyanti Dewi Library is exp
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Knowledge Acquisition and Sharing:
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Ikechukwu Diugwu articulated and st
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Ikechukwu Diugwu establishing setti
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Ikechukwu Diugwu Mentzer, J. T., Mi
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Eva Eckenhofer cou
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Eva Eckenhofer The
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Eva Eckenhofer The
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Eva Eckenhofer Bur
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1.2 Intellectual capital and innova
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3.2.2 Reliability Irene Y.H. Fan an
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Figure 4: latent variable coefficie
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Irene Y.H. Fan and Rongbin W.B. Lee
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Irene Y.H. Fan and Rongbin W.B. Lee
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2.1 Appropriation Ronny Gey From a
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Ronny Gey Table 1: Characterization
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Ronny Gey The developers feel that
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Ronny Gey A first limitation we wer
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Kenneth Grant part of</stro
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Kenneth Grant The diffusion was stu
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Kenneth Grant A detailed computer-s
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Kenneth Grant did not come to <stro
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Kenneth Grant of m
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Michel Grundstein although hundred
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Michel Grundstein Figure 1: DITEK p
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Michel Grundstein 4.1.1 Knowledge i
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Michel Grundstein share. However <s
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6. Conclusions and perspectives Mic
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Intellectual Property Valuation Dec
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Hezlin Harris et al. (Burrone and S
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Hezlin Harris et al. The need for s
Page 239 and 240: Acknowledgements Hezlin Harris et a
Page 241 and 242: Managing an Assessment Process <str
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Page 245 and 246: Shaheed Hartley Table 3: OEQ respon
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Page 251 and 252: Igor Hawryszkiewycz between communi
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Page 257 and 258: Eli Hustad and Aurilla Aurelie Bech
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Page 275 and 276: Organizational Learning in Pr<stron
Page 277 and 278: Brigita Janiunaite et al. learn and
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Page 285 and 286: Brigita Janiunaite et al. learning
Page 287 and 288: Balancing the Ince
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Page 297 and 298: Palmira Juceviciene and Vyda Mozuri
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Page 313 and 314: Robertas Jucevicius Lawton Smith, H
Page 315 and 316: Annukka Jyrämä et al. knowledge c
Page 317 and 318: Annukka Jyrämä et al. Respondents
Page 319 and 320: Annukka Jyrämä et al. various cit
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Page 323 and 324: Managing Information Overload - Tea
Page 325 and 326: Harri Ketamo conceptual structure a
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Page 335 and 336: Le Nguyen Doan Khoi days needed for
Page 337 and 338: Le Nguyen Doan Khoi dosage. Moreove
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Developing Human Capital through Ne
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Eric Kong organisation as individua
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Eric Kong As described by Tosey and
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Eric Kong Craft, A. (2001) "Neuro-l
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Sophie Le Bellu and Benoit Le Blanc
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Results Sophie Le Bellu and Benoit
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Pornpen Lertthasanawong and Nopasit
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2. Literature review Ya-Hui Ling 2.
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Ya-Hui Ling action of</stro
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Intellectual Capital Intellectual C
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Ya-Hui Ling Hitt, M.A., Hoskisson,
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Maksim Maksimovic et al paper prese
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Maksim Maksimovic et al 4. Lean kno
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Maksim Maksimovic et al of<
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Maurizio Massaro and Andrea Moro <s
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Maurizio Massaro and Andrea Moro Pr
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Maurizio Massaro and Andrea Moro hi
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Maurizio Massaro and Andrea Moro Si
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Helen Mitchell and Dennis Viehland
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Figure 1: KMS Framework for collabo
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Mohd Zali Mohd Nor et al. Ano<stron
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Mohd Zali Mohd Nor et al. Table 4:
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Mohd Zali Mohd Nor et al. KQ8 provi
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Maria Cristina Morariu economy and
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Table 1: Literature review summary
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Maria Cristina Morariu ATO = Turnov
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4.2 Correlation analysis Maria Cris
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4.3 Regression analysis Maria Crist
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Table 13: Regression analysis_M6 Mo
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The Arrival of <st
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Bertrand Pauget and Ahmed Dammak Mo
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Bertrand Pauget and Ahmed Dammak no
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Bertrand Pauget and Ahmed Dammak th
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Bertrand Pauget and Ahmed Dammak Sa
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Wannapa Pipattanawong et al. cannot
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Wannapa Pipattanawong et al. 3.2 Do
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Wannapa Pipattanawong et al. Moreov
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The Dark Side of S
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Siwarit Pongsakornrungsilp vans, ro
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Siwarit Pongsakornrungsilp Kreng Ja
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Siwarit Pongsakornrungsilp Lave, J.
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