Writing, Proofreading and Editing in Information Theory

[EN] Information is a physical entity amenable to be described by an abstract theory. The concepts associated with the creation and post-processing of the information have not, however, been mathematically established, despite being broadly used in many fields of knowledge. Here, inspired by how information is managed in biomolecular systems, we introduce writing, entailing any bit string generation, and revision, as comprising proofreading and editing, in information chains. Our formalism expands the thermodynamic analysis of stochastic chains made up of material subunits to abstract strings of symbols. We introduce a non-Markovian treatment of operational rules over the symbols of the chain that parallels the physical interactions responsible for memory effects in material chains. Our theory underlies any communication system, ranging from human languages and computer science to gene evolution.This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO, Grant MAT2015-71806-R). IMDEANanociencia acknowledges support from the 'Severo Ochoa' Programme for Centres of Excellence in R&D (MINECO, Grant SEV-2016-0686). These funds covered the costs to publish in open access.Arias-Gonzalez, JR. (2018). Writing, Proofreading and Editing in Information Theory. Entropy. 20(5):1-10. https://doi.org/10.3390/e20050368S11020

"China's Entry into the WTO: ICT Sectors, Innovation, Growth and Distribution"

During the debate about PRC's entry into the WTO, it was assumed by the proponents of joining the WTO that the export-led growth will continue and under WTO regime it will also lead to the modernization of the economy along the lines of the other newly industrialized economies(NIEs) of Asia. If examined rigorously, such an assumption can be seen to entail the goal of creating further technological capabilities. In particular, China seems to be firmly committed to the creation of a largely self-sustaining innovation system as part of a knowledge-based economy of the future . Such innovation systems, called positive feedback loop innovation systems or POLIS have been created by advanced countries, and NIEs such as South Korea and Taiwan are proceeding to create these as well. Can China do the same? And will China's entry into the WTO help or hinder such efforts? Using an economy wide model it is found thatThe entry into WTO can create an opportunity for technological learning and new technology imports. The challenge is to learn quickly and develop domestic capability before costs become too high. Thus, subsidizing domestic ICT firms can become an even more attractive strategic trade and technology policy. However, developing an interactive sustainable innovation system with virtuous positive feedbacks will require strategic complementarity between capital expenditures such as R&D and human resources.Therefore, upgrading education and training and developing ICT infrastructure quickly become urgent policy objectives. Also, precompetitive support of innovation needs to be separated from the actual development and marketing. In this area, clear guidelines and incentives for both the state and non-state enterprises will be necessary. A well-defined competition policy is a sine qua non for this purpose. In the Chinese case, openness can lead to increased competition under a rules-based trading regime. The challenge will be to build competitive world class ICT firms in such an environment. Even as competitive policies are pursued along with further structural reforms in China, the fact that such policies are to be pursued in an environment of incomplete information and other market imperfections mean that excess capacity, and consequently, unemployment may persist for sometime. Therefore, the role for appropriate macroeconomic policies to pursue the goal of reducing excess capacity without creating inflationary pressures need to be considered carefully.

KNOWNET: Exploring Interactive Knowledge Networking across Insurance Supply Chains

[EN] Social media has become an extremely powerful phenomenon with millions of users who post status updates, blog, links and pictures on social networking sites such as Facebook, LinkedIn, and Twitter. However, social networking has so far spread mainly among consumers. Businesses are only now beginning to acknowledge the benefits of using social media to enhance employee and supplier collaboration to support new ideas and innovation through knowledge sharing across functions and organizational boundaries. Many businesses are still trying to understand the various implications of integrating internal communication systems with social media tools and private collaboration and networking platforms. Indeed, a current issue in organizations today is to explore the value of social media mechanisms across a range of functions within their organizations and across their supply chains. .The KNOWNET project (an EC funded Marie Curie IAPP) seeks to assess the value of social networking for knowledge exchange across Insurance supply chains. A key objective of the project being to develop and build a web based interactive environment - a Supplier Social Network or SSN, to support and facilitate exchange of good ideas, insights, knowledge, innovations etc across a diverse group of suppliers within a multi level supply chain within the Insurance sector.The KNOWNET project is a 4 year project funded by the FP7 EC Industry-Academia Partnerships and Pathways (IAPP) - Marie Curie Actions.Grant, S. (2014). KNOWNET: Exploring Interactive Knowledge Networking across Insurance Supply Chains. International Journal of Production Management and Engineering. 2(1):7-14. https://doi.org/10.4995/ijpme.2014.1866SWORD71421Ardichvili, A., Page, V., & Wentling, T. (2003). Motivation and barriers to participation in virtual knowledge‐sharing communities of practice. Journal of Knowledge Management, 7(1), 64-77. doi:10.1108/13673270310463626Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca, G. (2009). Network Analysis in the Social Sciences. Science, 323(5916), 892-895. doi:10.1126/science.1165821Boschma, R. A., & ter Wal, A. L. J. (2007). Knowledge Networks and Innovative Performance in an Industrial District: The Case of a Footwear District in the South of Italy. Industry & Innovation, 14(2), 177-199. doi:10.1080/13662710701253441BERNARDES, E. S. (2010). THE EFFECT OF SUPPLY MANAGEMENT ON ASPECTS OF SOCIAL CAPITAL AND THE IMPACT ON PERFORMANCE: A SOCIAL NETWORK PERSPECTIVE. Journal of Supply Chain Management, 46(1), 45-55. doi:10.1111/j.1745-493x.2009.03185.xBollinger, A. S., & Smith, R. D. (2001). Managing organizational knowledge as a strategic asset. Journal of Knowledge Management, 5(1), 8-18. doi:10.1108/13673270110384365Bredl K, Grob A, Hunniger J and Fleischer J(2012)'the Avartar as a Knowledge worker; How immersive 3D virtual environments may foster knowledge acquisition' Electronic Journal of Knowledge Management vol 10 issue 1 pp15-25Capó‐Vicedo, J., Mula, J., & Capó, J. (2011). A social network‐based organizational model for improving knowledge management in supply chains. Supply Chain Management: An International Journal, 16(4), 284-293. doi:10.1108/13598541111139099Carter, C. R., Ellram, L. M., & Tate, W. (2007). THE USE OF SOCIAL NETWORK ANALYSIS IN LOGISTICS RESEARCH. Journal of Business Logistics, 28(1), 137-168. doi:10.1002/j.2158-1592.2007.tb00235.xChesborough H (2003)'Open Innovation: The new imperative for creating and profiting from technology, Harvard Business School Press Cambridge MA.CHOI, T. Y., & WU, Z. (2009). TRIADS IN SUPPLY NETWORKS: THEORIZING BUYER-SUPPLIER-SUPPLIER RELATIONSHIPS. Journal of Supply Chain Management, 45(1), 8-25. doi:10.1111/j.1745-493x.2009.03151.xChungsuk R, Kim Y, Abhijit C & Raghav R(2005)'knowledge acquisition via three learning process in enterprise information portals: Learning by Investment, learning by doing and learning from others' MIS Quarterly june 2005 vol 29 issue 2 pp245-278Chiu C, Hsu M; Wang E (2006)' Understanding knowledge sharing in virtual communities: an integration of socisl capital and social cognitive theories' Decision support systems 42Ciborra, C. U., & Patriotta, G. (1998). Groupware and teamwork in R&D: limits to learning and innovation. R&D Management, 28(1), 43-52. doi:10.1111/1467-9310.00080Dede, C. (2009). Immersive Interfaces for Engagement and Learning. Science, 323(5910), 66-69. doi:10.1126/science.1167311Duan, W. (2009). Special issue on online communities and social network: An editorial introduction. Decision Support Systems, 47(3), 167-168. doi:10.1016/j.dss.2009.02.010Edwards, T., Battisti, G., & Neely, A. (2004). Value creation and the UK economy: a review of strategic options. International Journal of Management Reviews, 5-6(3-4), 191-213. doi:10.1111/j.1460-8545.2004.00103.xGanley, D., & Lampe, C. (2009). The ties that bind: Social network principles in online communities. Decision Support Systems, 47(3), 266-274. doi:10.1016/j.dss.2009.02.013Giannakis, M. (2008). Facilitating learning and knowledge transfer through supplier development. Supply Chain Management: An International Journal, 13(1), 62-72. doi:10.1108/13598540810850328Gilbert, M., & Cordey-Hayes, M. (1996). Understanding the process of knowledge transfer to achieve successful technological innovation. Technovation, 16(6), 301-312. doi:10.1016/0166-4972(96)00012-0Khan, A., & Khan, R. (2012). Embracing new media in Fiji: the way forward for social network marketing and communication strategies. Strategic Direction, 28(4), 3-5. doi:10.1108/02580541211212754Kotabe, M., Martin, X., & Domoto, H. (2003). Gaining from vertical partnerships: knowledge transfer, relationship duration, and supplier performance improvement in the U.S. and Japanese automotive industries. Strategic Management Journal, 24(4), 293-316. doi:10.1002/smj.297Mangold, W. G., & Faulds, D. J. (2009). Social media: The new hybrid element of the promotion mix. Business Horizons, 52(4), 357-365. doi:10.1016/j.bushor.2009.03.002Mayer, A. (2009). Online social networks in economics. Decision Support Systems, 47(3), 169-184. doi:10.1016/j.dss.2009.02.009McLure Wasko, M., & Faraj, S. (2000). «It is what one does»: why people participate and help others in electronic communities of practice. The Journal of Strategic Information Systems, 9(2-3), 155-173. doi:10.1016/s0963-8687(00)00045-7Nonaka, I., & Konno, N. (1998). The Concept of «Ba»: Building a Foundation for Knowledge Creation. California Management Review, 40(3), 40-54. doi:10.2307/41165942Newell, S., and Swan, J. (2000) Trust and Inter-organizational Networking. Human Relations. Vol.53 No.10, 1287-1328.Ozkul, A., & Barut, M. (2009). Measuring supply chain relationships: a social network approach. International Journal of Integrated Supply Management, 5(1), 38. doi:10.1504/ijism.2009.026204S Wheeler (2007)in Moore, M. G. (1972) Learner autonomy: the second dimension of independent learning. Conver-gence, 5 (2) 76-88Seufert, A., von Krogh, G., & Bach, A. (1999). Towards knowledge networking. Journal of Knowledge Management, 3(3), 180-190. doi:10.1108/13673279910288608Swan, J., Newell, S., Scarbrough, H., & Hislop, D. (1999). Knowledge management and innovation: networks and networking. Journal of Knowledge Management, 3(4), 262-275. doi:10.1108/13673279910304014Tsai, K.-H. (2009). Collaborative networks and product innovation performance: Toward a contingency perspective. Research Policy, 38(5), 765-778. doi:10.1016/j.respol.2008.12.012Walter, J., Lechner, C., & Kellermanns, F. W. (2007). Knowledge transfer between and within alliance partners: Private versus collective benefits of social capital. Journal of Business Research, 60(7), 698-710. doi:10.1016/j.jbusres.2007.01.026Wu C (2008)Knowledge creation in a supply chain' Supply Chain management: An international Journal, Vol 13, no 3 pp241-250Yang, S. J. H., & Chen, I. Y. L. (2008). A social network-based system for supporting interactive collaboration in knowledge sharing over peer-to-peer network. International Journal of Human-Computer Studies, 66(1), 36-50. doi:10.1016/j.ijhcs.2007.08.005Teece D J (2000) Strategies for managing knowledge assets: the role of firm structure and industrial context, Long range planning, 2000 – ElsevierCummings, J. L., & Teng, B.-S. (2003). Transferring R&D knowledge: the key factors affecting knowledge transfer success. Journal of Engineering and Technology Management, 20(1-2), 39-68. doi:10.1016/s0923-4748(03)00004-3Chatti M and M Jarke (2007) 'The future of e-learning: a shift to knowledge networking and social software' Interna-tional Journal of Knowledge and Learning Vol 3 Nos 4/5 2007Selnes, F., & Sallis, J. (2003). Promoting Relationship Learning. Journal of Marketing, 67(3), 80-95. doi:10.1509/jmkg.67.3.80.1865

Open innovation: past, present and future trends

[EN] Purpose The purpose of this paper is to provide interested parties with the means of grasping how the literature on open innovation has evolved over the course of time. In this way, the authors furthermore contribute towards a better understanding, scaling and positioning of this field of research. Design/methodology/approach This study applies a combination of bibliometric techniques, such as citations, co-citations and social network analysis in order to map the scientific domain of open innovation. Currently, bibliometric analysis represents a methodology in effect on a global scale to evaluate the existing state of fields of research (Mutschke et al., 2011). This spans the application of quantitative and statistical analysis to publications such as articles and their respective citations and serving to evaluate the performance of research through returning data on all of the activities ongoing in a scientific field with summaries of these data generating a broad perspective on the research activities and impacts, especially as regards the researchers, journals, countries and universities (Hawkins, 1977; Osareh, 1996; Thomsom Reuters, 2008). Findings This research aims to map and analyse the intellectual knowledge held on open innovation. To this end, the authors carried out a bibliometric study with recourse to co-citations. Based on cluster and factorial analyses, it is possible identify and classify the several theoretical perspectives on open innovation across six areas: open innovation concept, open innovation and networks, open innovation and knowledge, open Innovation, and innovation spillovers, open innovation management and open innovation and technology.JoAo J. Ferreira and Cristina I. Fernandes acknowledge the financial support from NECE - Research Unit in Business Sciences funded by the Multiannual Funding Programme of R&D Centres of FCT - Fundacao para a Ciencia e a Tecnologia (Project UID/GES/04630/2013).Fernandes, C.; Ferreira, J.; Peris-Ortiz, M. (2019). Open innovation: past, present and future trends. Journal of Organizational Change Management. 32(5):578-602. https://doi.org/10.1108/JOCM-09-2018-0257S578602325Ahn, J. M., Minshall, T., & Mortara, L. (2017). Understanding the human side of openness: the fit between open innovation modes and CEO characteristics. R&D Management, 47(5), 727-740. doi:10.1111/radm.12264Alexy, O., George, G., & Salter, A. J. (2013). Cui Bono? The Selective Revealing of Knowledge and Its Implications for Innovative Activity. Academy of Management Review, 38(2), 270-291. doi:10.5465/amr.2011.0193Baldwin, C., & von Hippel, E. (2011). Modeling a Paradigm Shift: From Producer Innovation to User and Open Collaborative Innovation. Organization Science, 22(6), 1399-1417. doi:10.1287/orsc.1100.0618Ballell, L., Bates, R. H., Young, R. J., Alvarez-Gomez, D., Alvarez-Ruiz, E., Barroso, V., … Cammack, N. (2013). Fueling Open-Source Drug Discovery: 177 Small-Molecule Leads against Tuberculosis. ChemMedChem, 8(2), 313-321. doi:10.1002/cmdc.201200428Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), 99-120. doi:10.1177/014920639101700108Belussi, F., Sammarra, A., & Sedita, S. R. (2010). Learning at the boundaries in an «Open Regional Innovation System»: A focus on firms’ innovation strategies in the Emilia Romagna life science industry. Research Policy, 39(6), 710-721. doi:10.1016/j.respol.2010.01.014Berchicci, L. (2013). Towards an open R&D system: Internal R&D investment, external knowledge acquisition and innovative performance. Research Policy, 42(1), 117-127. doi:10.1016/j.respol.2012.04.017Berkhout, G., Hartmann, D., & Trott, P. (2010). Connecting technological capabilities with market needs using a cyclic innovation model. R&D Management, 40(5), 474-490. doi:10.1111/j.1467-9310.2010.00618.xBerthon, P., Ewing, M. T., & Napoli, J. (2008). Brand Management in Small to Medium-Sized Enterprises*. Journal of Small Business Management, 46(1), 27-45. doi:10.1111/j.1540-627x.2007.00229.xBianchi, M., Campodall’Orto, S., Frattini, F., & Vercesi, P. (2010). Enabling open innovation in small- and medium-sized enterprises: how to find alternative applications for your technologies. R&D Management, 40(4), 414-431. doi:10.1111/j.1467-9310.2010.00613.xChen, J., Chen, Y., & Vanhaverbeke, W. (2011). The influence of scope, depth, and orientation of external technology sources on the innovative performance of Chinese firms. Technovation, 31(8), 362-373. doi:10.1016/j.technovation.2011.03.002Cheng, C.-F., Lai, M.-K., & Wu, W.-Y. (2010). Exploring the impact of innovation strategy on R&D employees’ job satisfaction: A mathematical model and empirical research. Technovation, 30(7-8), 459-470. doi:10.1016/j.technovation.2010.03.006Chesbrough, H. and Bogers, M. (2014), “Explicating open innovation: clarifying an emerging paradigm for understanding innovation”, in Chesbrough, H., Vanhaverbeke, W. and West, J. (Eds), New Frontiers in Open Innovation, Oxford University Press, Oxford, pp. 3-28.Chesbrough, H. (2012). Open Innovation: Where We’ve Been and Where We’re Going. Research-Technology Management, 55(4), 20-27. doi:10.5437/08956308x5504085Chesbrough, H. W., & Appleyard, M. M. (2007). Open Innovation and Strategy. California Management Review, 50(1), 57-76. doi:10.2307/41166416Chiaroni, D., Chiesa, V., & Frattini, F. (2011). The Open Innovation Journey: How firms dynamically implement the emerging innovation management paradigm. Technovation, 31(1), 34-43. doi:10.1016/j.technovation.2009.08.007Christensen, J. F., Olesen, M. H., & Kjær, J. S. (2005). The industrial dynamics of Open Innovation—Evidence from the transformation of consumer electronics. Research Policy, 34(10), 1533-1549. doi:10.1016/j.respol.2005.07.002Cooke, P. (2005). Regionally asymmetric knowledge capabilities and open innovation. Research Policy, 34(8), 1128-1149. doi:10.1016/j.respol.2004.12.005Cooper, R. G. (2008). Perspective: The Stage-Gate®Idea-to-Launch Process—Update, What’s New, and NexGen Systems. Journal of Product Innovation Management, 25(3), 213-232. doi:10.1111/j.1540-5885.2008.00296.xDahlander, L., & Gann, D. M. (2010). How open is innovation? Research Policy, 39(6), 699-709. doi:10.1016/j.respol.2010.01.013Dahlander, L., O’Mahony, S., & Gann, D. M. (2014). One foot in, one foot out: how does individuals’ external search breadth affect innovation outcomes? Strategic Management Journal, 37(2), 280-302. doi:10.1002/smj.2342Di Gangi, P. M., & Wasko, M. (2009). Steal my idea! Organizational adoption of user innovations from a user innovation community: A case study of Dell IdeaStorm. Decision Support Systems, 48(1), 303-312. doi:10.1016/j.dss.2009.04.004Dodgson, M., Gann, D., & Salter, A. (2006). The role of technology in the shift towards open innovation: the case of Procter & Gamble. R and D Management, 36(3), 333-346. doi:10.1111/j.1467-9310.2006.00429.xDoloreux, D., & Melançon, Y. (2008). On the dynamics of innovation in Quebec’s coastal maritime industry. Technovation, 28(4), 231-243. doi:10.1016/j.technovation.2007.10.006Drechsler, W., & Natter, M. (2012). Understanding a firm’s openness decisions in innovation. Journal of Business Research, 65(3), 438-445. doi:10.1016/j.jbusres.2011.11.003Chatenier, E. du, Verstegen, J. A. A. M., Biemans, H. J. A., Mulder, M., & Omta, O. S. W. F. (2010). Identification of competencies for professionals in open innovation teams. R&D Management, 40(3), 271-280. doi:10.1111/j.1467-9310.2010.00590.xEbner, W., Leimeister, J. M., & Krcmar, H. (2009). Community engineering for innovations: the ideas competition as a method to nurture a virtual community for innovations. R&D Management, 39(4), 342-356. doi:10.1111/j.1467-9310.2009.00564.xEnkel, E., Gassmann, O., & Chesbrough, H. (2009). Open R&D and open innovation: exploring the phenomenon. R&D Management, 39(4), 311-316. doi:10.1111/j.1467-9310.2009.00570.xFaems, D., De Visser, M., Andries, P., & Van Looy, B. (2010). Technology Alliance Portfolios and Financial Performance: Value-Enhancing and Cost-Increasing Effects of Open Innovation*. Journal of Product Innovation Management, 27(6), 785-796. doi:10.1111/j.1540-5885.2010.00752.xFaraj, S., Jarvenpaa, S. L., & Majchrzak, A. (2011). Knowledge Collaboration in Online Communities. Organization Science, 22(5), 1224-1239. doi:10.1287/orsc.1100.0614Felin, T., & Zenger, T. R. (2014). Closed or open innovation? Problem solving and the governance choice. Research Policy, 43(5), 914-925. doi:10.1016/j.respol.2013.09.006Fetterhoff, T. J., & Voelkel, D. (2006). Managing Open Innovation in Biotechnology. Research-Technology Management, 49(3), 14-18. doi:10.1080/08956308.2006.11657373Franzoni, C., & Sauermann, H. (2014). Crowd science: The organization of scientific research in open collaborative projects. Research Policy, 43(1), 1-20. doi:10.1016/j.respol.2013.07.005Füller, J., Hutter, K., & Faullant, R. (2011). Why co-creation experience matters? Creative experience and its impact on the quantity and quality of creative contributions. R&D Management, 41(3), 259-273. doi:10.1111/j.1467-9310.2011.00640.xFüller, J., Matzler, K., & Hoppe, M. (2008). Brand Community Members as a Source of Innovation. Journal of Product Innovation Management, 25(6), 608-619. doi:10.1111/j.1540-5885.2008.00325.xGarriga, H., von Krogh, G., & Spaeth, S. (2013). How constraints and knowledge impact open innovation. Strategic Management Journal, 34(9), 1134-1144. doi:10.1002/smj.2049Gassmann, O., Enkel, E., & Chesbrough, H. (2010). The future of open innovation. R&D Management, 40(3), 213-221. doi:10.1111/j.1467-9310.2010.00605.xGrönlund, J., Sjödin, D. R., & Frishammar, J. (2010). Open Innovation and the Stage-Gate Process: A Revised Model for New Product Development. California Management Review, 52(3), 106-131. doi:10.1525/cmr.2010.52.3.106Hawkins, D. T. (1977). Unconventional uses of on-line information retrieval systems: On-line bibliometric studies. Journal of the American Society for Information Science, 28(1), 13-18. doi:10.1002/asi.4630280103Henkel, J. (2006). Selective revealing in open innovation processes: The case of embedded Linux. Research Policy, 35(7), 953-969. doi:10.1016/j.respol.2006.04.010Hu, J.-L., & Hsu, Y.-H. (2008). The more interactive, the more innovative? A case study of South Korean cellular phone manufacturers. Technovation, 28(1-2), 75-87. doi:10.1016/j.technovation.2007.07.010Hua, S. Y., & Wemmerlov, U. (2006). Product Change Intensity, Product Advantage, and Market Performance: An Empirical Investigation of the PC Industry. Journal of Product Innovation Management, 23(4), 316-329. doi:10.1111/j.1540-5885.2006.00204.xHuizingh, E. K. R. E. (2011). Open innovation: State of the art and future perspectives. Technovation, 31(1), 2-9. doi:10.1016/j.technovation.2010.10.002Hurley, R. F., & Hult, G. T. M. (1998). Innovation, Market Orientation, and Organizational Learning: An Integration and Empirical Examination. Journal of Marketing, 62(3), 42-54. doi:10.1177/002224299806200303Hurmelinna, P., Kyläheiko, K., & Jauhiainen, T. (2007). The Janus face of the appropriability regime in the protection of innovations: Theoretical re-appraisal and empirical analysis. Technovation, 27(3), 133-144. doi:10.1016/j.technovation.2005.09.011Hutter, K., Hautz, J., Füller, J., Mueller, J., & Matzler, K. (2011). Communitition: The Tension between Competition and Collaboration in Community-Based Design Contests. Creativity and Innovation Management, 20(1), 3-21. doi:10.1111/j.1467-8691.2011.00589.xHwang, A.-S. (2004). Integrating Technology, Marketing and Management Innovation. Research-Technology Management, 47(4), 27-31. doi:10.1080/08956308.2004.11671638Ili, S., Albers, A., & Miller, S. (2010). Open innovation in the automotive industry. R&D Management, 40(3), 246-255. doi:10.1111/j.1467-9310.2010.00595.xJacobides, M. G., & Billinger, S. (2006). Designing the Boundaries of the Firm: From «Make, Buy, or Ally» to the Dynamic Benefits of Vertical Architecture. Organization Science, 17(2), 249-261. doi:10.1287/orsc.1050.0167Jeppesen, L. B., & Lakhani, K. R. (2010). Marginality and Problem-Solving Effectiveness in Broadcast Search. Organization Science, 21(5), 1016-1033. doi:10.1287/orsc.1090.0491Kaminski, P. C., de Oliveira, A. C., & Lopes, T. M. (2008). Knowledge transfer in product development processes: A case study in small and medium enterprises (SMEs) of the metal-mechanic sector from São Paulo, Brazil. Technovation, 28(1-2), 29-36. doi:10.1016/j.technovation.2007.07.001Keupp, M. M., & Gassmann, O. (2009). Determinants and archetype users of open innovation. R&D Management, 39(4), 331-341. doi:10.1111/j.1467-9310.2009.00563.xKirschbaum, R. (2005). Open Innovation In Practice. Research-Technology Management, 48(4), 24-28. doi:10.1080/08956308.2005.11657321Kline, S.J. and Rosenberg, N. (1986), “An overview of innovation”, in Laudau, R. and Rosenberg, N. (Eds), The Positive Sum Strategy: Harnessing Technology for Economic Growth, National Academy Press, Washington, DC, pp. 275-306.Koc, T., & Ceylan, C. (2007). Factors impacting the innovative capacity in large-scale companies. Technovation, 27(3), 105-114. doi:10.1016/j.technovation.2005.10.002Laursen, K., & Salter, A. J. (2014). The paradox of openness: Appropriability, external search and collaboration. Research Policy, 43(5), 867-878. doi:10.1016/j.respol.2013.10.004Lee, S., Park, G., Yoon, B., & Park, J. (2010). Open innovation in SMEs—An intermediated network model. Research Policy, 39(2), 290-300. doi:10.1016/j.respol.2009.12.009Leimeister, J. M., Huber, M., Bretschneider, U., & Krcmar, H. (2009). Leveraging Crowdsourcing: Activation-Supporting Components for IT-Based Ideas Competition. Journal of Management Information Systems, 26(1), 197-224. doi:10.2753/mis0742-1222260108Lemon, M., & Sahota, P. S. (2004). Organizational culture as a knowledge repository for increased innovative capacity. Technovation, 24(6), 483-498. doi:10.1016/s0166-4972(02)00102-5Li, Y.-R. (2009). The technological roadmap of Cisco’s business ecosystem. Technovation, 29(5), 379-386. doi:10.1016/j.technovation.2009.01.007Lichtenthaler, U. (2007). The Drivers of Technology Licensing: An Industry Comparison. California Management Review, 49(4), 67-89. doi:10.2307/41166406Lichtenthaler, U. (2008). Open Innovation in Practice: An Analysis of Strategic Approaches to Technology Transactions. IEEE Transactions on Engineering Management, 55(1), 148-157. doi:10.1109/tem.2007.912932Lichtenthaler, U. (2009). Outbound open innovation and its effect on firm performance: examining environmental influences. R&D Management, 39(4), 317-330. doi:10.1111/j.1467-9310.2009.00561.xLichtenthaler, U., & Ernst, H. (2006). Attitudes to externally organising knowledge management tasks: a review, reconsideration and extension of the NIH syndrome. R and D Management, 36(4), 367-386. doi:10.1111/j.1467-9310.2006.00443.xLichtenthaler, U., & Ernst, H. (2007). External technology commercialization in large firms: results of a quantitative benchmarking study. R&D Management, 37(5), 383-397. doi:10.1111/j.1467-9310.2007.00487.xLichtenthaler, U., & Ernst, H. (2009). Opening up the innovation process: the role of technology aggressiveness. R&D Management, 39(1), 38-54. doi:10.1111/j.1467-9310.2008.00522.xLichtenthaler, U., & Lichtenthaler, E. (2009). A Capability-Based Framework for Open Innovation: Complementing Absorptive Capacity. Journal of Management Studies, 46(8), 1315-1338. doi:10.1111/j.1467-6486.2009.00854.xLove, J. H., Roper, S., & Bryson, J. R. (2011). Openness, knowledge, innovation and growth in UK business services. Research Policy, 40(10), 1438-1452. doi:10.1016/j.respol.2011.05.016Majchrzak, A., & Malhotra, A. (2013). Towards an information systems perspective and research agenda on crowdsourcing for innovation. The Journal of Strategic Information Systems, 22(4), 257-268. doi:10.1016/j.jsis.2013.07.004Mention, A.-L. (2011). Co-operation and co-opetition as open innovation practices in the service sector: Which influence on innovation novelty? Technovation, 31(1), 44-53. doi:10.1016/j.technovation.2010.08.002Mutschke, P., Mayr, P., Schaer, P., & Sure, Y. (2011). Science models as value-added services for scholarly information systems. Scientometrics, 89(1), 349-364. doi:10.1007/s11192-011-0430-xParida, V., Westerberg, M., & Frishammar, J. (2012). Inbound Open Innovation Activities in High-Tech SMEs: The Impact on Innovation Performance. Journal of Small Business Management, 50(2), 283-309. doi:10.1111/j.1540-627x.2012.00354.xPiller, F. T., & Walcher, D. (2006). Toolkits for idea competitions: a novel method to integrate users in new product development. R and D Management, 36(3), 307-318. doi:10.1111/j.1467-9310.2006.00432.xRampersad, G., Quester, P., & Troshani, I. (2010). Managing innovation networks: Exploratory evidence from ICT, biotechnology and nanotechnology networks. Industrial Marketing Management, 39(5), 793-805. doi:10.1016/j.indmarman.2009.07.002Roberts, P. W., & Amit, R. (2003). The Dynamics of Innovative Activity and Competitive Advantage: The Case of Australian Retail Banking, 1981 to 1995. Organization Science, 14(2), 107-122. doi:10.1287/orsc.14.2.107.14990Rohrbeck, R., Hölzle, K., & Gemünden, H. G. (2009). Opening up for competitive advantage - How Deutsche Telekom creates an open innovation ecosystem. R&D Management, 39(4), 420-430. doi:10.1111/j.1467-9310.2009.00568.xRost, K. (2011). The strength of strong ties in the creation of innovation. Research Policy, 40(4), 588-604. doi:10.1016/j.respol.2010.12.001Salter, A., Criscuolo, P., & Ter Wal, A. L. J. (2014). Coping with Open Innovation: Responding to the Challenges of External Engagement in R&D. California Management Review, 56(2), 77-94. doi:10.1525/cmr.2014.56.2.77Salter, A., Wal, A. L. J., Criscuolo, P., & Alexy, O. (2014). Open for Ideation: Individual‐Level Openness and Idea Generation in R&D. Journal of Product Innovation Management, 32(4), 488-504. doi:10.1111/jpim.12214Small, H. (1973). Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24(4), 265-269. doi:10.1002/asi.4630240406Souitaris, V. (2002). Technological trajectories as moderators of firm-level determinants of innovation. Research Policy, 31(6), 877-898. doi:10.1016/s0048-7333(01)00154-8Spithoven, A., Clarysse, B., & Knockaert, M. (2010). Building absorptive capacity to organise inbound open innovation in traditional industries. Technovation, 30(2), 130-141. doi:10.1016/j.technovation.2009.08.004Spithoven, A., Vanhaverbeke, W., & Roijakkers, N. (2012). Open innovation practices in SMEs and large enterprises. Small Business Economics, 41(3), 537-562. doi:10.1007/s11187-012-9453-9Stang, P. E., Ryan, P. B., Racoosin, J. A., Overhage, J. M., Hartzema, A. G., Reich, C., … Woodcock, J. (2010). Advancing the Science for Active Surveillance: Rationale and Design for the Observational Medical Outcomes Partnership. Annals of Internal Medicine, 153(9), 600. doi:10.7326/0003-4819-153-9-201011020-00010Terwiesch, C., & Xu, Y. (2008). Innovation Contests, Open Innovation, and Multiagent Problem Solving. Management Science, 54(9), 1529-1543. doi:10.1287/mnsc.1080.0884Thomsom Reuters (2008), “Using bibliometrics: a guide to evaluating research performance with citation data”, available at: http://ip-science.thomsonreuters.com/m/pdfs/325133_thomson.pdf(accessed 30 December 2018).Vrande, V. V. de, Vanhaverbeke, W., & Gassmann, O. (2010). Broadening the scope of open innovation: past research, current state and future directions. International Journal of Technology Management, 52(3/4), 221. doi:10.1504/ijtm.2010.035974Von Hippel, E., & von Krogh, G. (2006). Free revealing and the private-collective model for innovation incentives. R and D Management, 36(3), 295-306. doi:10.1111/j.1467-9310.2006.00435.xVon Krogh, G. (2012). How does social software change knowledge management? Toward a strategic research agenda. The Journal of Strategic Information Systems, 21(2), 154-164. doi:10.1016/j.jsis.2012.04.003Yu, D., & Hang, C. C. (2010). A Reflective Review of Disruptive Innovation Theory. International Journal of Management Reviews, 12(4), 435-452. doi:10.1111/j.1468-2370.2009.00272.

Toward Value-Based Healthcare through Interactive Process Mining in Emergency Rooms: The Stroke Case

[EN] The application of Value-based Healthcare requires not only the identification of key processes in the clinical domain but also an adequate analysis of the value chain delivered to the patient. Data Science and Big Data approaches are technologies that enable the creation of accurate systems that model reality. However, classical Data Mining techniques are presented by professionals as black boxes. This evokes a lack of trust in those techniques in the medical domain. Process Mining technologies are human-understandable Data Science tools that can fill this gap to support the application of Value-Based Healthcare in real domains. The aim of this paper is to perform an analysis of the ways in which Process Mining techniques can support health professionals in the application of Value-Based Technologies. For this purpose, we explored these techniques by analyzing emergency processes and applying the critical timing of Stroke treatment and a Question-Driven methodology. To demonstrate the possibilities of Process Mining in the characterization of the emergency process, we used a real log with 9046 emergency episodes from 2145 stroke patients that occurred from January 2010 to June 2017. Our results demonstrate how Process Mining technology can highlight the differences between the flow of stroke patients compared with that of other patients in an emergency. Further, we show that support for health professionals can be provided by improving their understanding of these techniques and enhancing the quality of care.This research was funded by Hospital General de Valencia thanks to the LOPEZ TRIGO 2017 AWARD and by the CONICYT grant REDI 170136 Project. The APC was funded by the APE/2019/007 (D.O.G.V. 8355/06.08.2018 Annex XIII).Ibáñez Sánchez, G.; Fernández Llatas, C.; Martinez-Millana, A.; Celda, A.; Mandingorra, J.; Aparici-Tortajada, L.; Valero Ramon, Z.... (2019). Toward Value-Based Healthcare through Interactive Process Mining in Emergency Rooms: The Stroke Case. International Journal of Environmental research and Public Health. 16(10):1-22. https://doi.org/10.3390/ijerph16101783S1221610Berwick, D. M., Nolan, T. W., & Whittington, J. (2008). The Triple Aim: Care, Health, And Cost. Health Affairs, 27(3), 759-769. doi:10.1377/hlthaff.27.3.759Porter, M. E. (2010). What Is Value in Health Care? New England Journal of Medicine, 363(26), 2477-2481. doi:10.1056/nejmp1011024Mamlin, B. W., & Tierney, W. M. (2016). The Promise of Information and Communication Technology in Healthcare: Extracting Value From the Chaos. The American Journal of the Medical Sciences, 351(1), 59-68. doi:10.1016/j.amjms.2015.10.015Murdoch, T. B., & Detsky, A. S. (2013). The Inevitable Application of Big Data to Health Care. JAMA, 309(13), 1351. doi:10.1001/jama.2013.393Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients. Health Affairs, 33(7), 1123-1131. doi:10.1377/hlthaff.2014.0041Fernández-Llatas, C., Meneu, T., Traver, V., & Benedi, J.-M. (2013). Applying Evidence-Based Medicine in Telehealth: An Interactive Pattern Recognition Approximation. International Journal of Environmental Research and Public Health, 10(11), 5671-5682. doi:10.3390/ijerph10115671Rojas, E., Sepúlveda, M., Munoz-Gama, J., Capurro, D., Traver, V., & Fernandez-Llatas, C. (2017). Question-Driven Methodology for Analyzing Emergency Room Processes Using Process Mining. Applied Sciences, 7(3), 302. doi:10.3390/app7030302Sackett, D. L., Rosenberg, W. M. C., Gray, J. A. M., Haynes, R. B., & Richardson, W. S. (1996). Evidence based medicine: what it is and what it isn’t. BMJ, 312(7023), 71-72. doi:10.1136/bmj.312.7023.71Is Evidence-Based Medicine Patient-Centered and Is Patient-Centered Care Evidence-Based? (2006). Health Services Research, 41(1), 1-8. doi:10.1111/j.1475-6773.2006.00504.xGoldberger, J. J., & Buxton, A. E. (2013). Personalized Medicine vs Guideline-Based Medicine. JAMA, 309(24), 2559. doi:10.1001/jama.2013.6629Kelly, M. P., Heath, I., Howick, J., & Greenhalgh, T. (2015). The importance of values in evidence-based medicine. BMC Medical Ethics, 16(1). doi:10.1186/s12910-015-0063-3Gonzalez-Ferrer, A., Seara, G., Cháfer, J., & Mayol, J. (2018). Generating Big Data Sets from Knowledge-based Decision Support Systems to Pursue Value-based Healthcare. International Journal of Interactive Multimedia and Artificial Intelligence, 4(7), 42. doi:10.9781/ijimai.2017.03.006Lazer, D., Kennedy, R., King, G., & Vespignani, A. (2014). The Parable of Google Flu: Traps in Big Data Analysis. Science, 343(6176), 1203-1205. doi:10.1126/science.1248506Rojas, E., Munoz-Gama, J., Sepúlveda, M., & Capurro, D. (2016). Process mining in healthcare: A literature review. Journal of Biomedical Informatics, 61, 224-236. doi:10.1016/j.jbi.2016.04.007Fernandez-Llatas, C., Lizondo, A., Monton, E., Benedi, J.-M., & Traver, V. (2015). Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems. Sensors, 15(12), 29821-29840. doi:10.3390/s151229769Baker, K., Dunwoodie, E., Jones, R. G., Newsham, A., Johnson, O., Price, C. P., … Hall, G. (2017). Process mining routinely collected electronic health records to define real-life clinical pathways during chemotherapy. International Journal of Medical Informatics, 103, 32-41. doi:10.1016/j.ijmedinf.2017.03.011Rebuge, Á., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99-116. doi:10.1016/j.is.2011.01.003Partington, A., Wynn, M., Suriadi, S., Ouyang, C., & Karnon, J. (2015). Process Mining for Clinical Processes. ACM Transactions on Management Information Systems, 5(4), 1-18. doi:10.1145/2629446Storm-Versloot, M. N., Ubbink, D. T., Kappelhof, J., & Luitse, J. S. K. (2011). Comparison of an Informally Structured Triage System, the Emergency Severity Index, and the Manchester Triage System to Distinguish Patient Priority in the Emergency Department. Academic Emergency Medicine, 18(8), 822-829. doi:10.1111/j.1553-2712.2011.01122.xFeigin, V. L., Roth, G. A., Naghavi, M., Parmar, P., Krishnamurthi, R., Chugh, S., … Forouzanfar, M. H. (2016). Global burden of stroke and risk factors in 188 countries, during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. The Lancet Neurology, 15(9), 913-924. doi:10.1016/s1474-4422(16)30073-4Howard, G., & Goff, D. C. (2012). Population shifts and the future of stroke: forecasts of the future burden of stroke. Annals of the New York Academy of Sciences, 1268(1), 14-20. doi:10.1111/j.1749-6632.2012.06665.xGustavsson, A., Svensson, M., Jacobi, F., Allgulander, C., Alonso, J., Beghi, E., … Olesen, J. (2011). Cost of disorders of the brain in Europe 2010. European Neuropsychopharmacology, 21(10), 718-779. doi:10.1016/j.euroneuro.2011.08.008Alberts, M. J. (2000). Recommendations for the Establishment of Primary Stroke Centers. JAMA, 283(23), 3102. doi:10.1001/jama.283.23.3102Conca, T., Saint-Pierre, C., Herskovic, V., Sepúlveda, M., Capurro, D., Prieto, F., & Fernandez-Llatas, C. (2018). Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care: Analysis Using Process Mining. Journal of Medical Internet Research, 20(4), e127. doi:10.2196/jmir.8884Chavalarias, D., Wallach, J. D., Li, A. H. T., & Ioannidis, J. P. A. (2016). Evolution of ReportingPValues in the Biomedical Literature, 1990-2015. JAMA, 315(11), 1141. doi:10.1001/jama.2016.195

Organizational knowledge transfer through creation, mobilization and diffusion: A case analysis of InTouch within Schlumberger

There is a paucity of theory for the effective management of knowledge transfer within large organisations. Practitioners continue to rely upon ‘experimental’ approaches to address the problem. This research attempts to reduce the gap between theory and application, thereby improving conceptual clarity for the transfer of knowledge. The paper, through an in-depth case analysis conducted within Schlumberger, studies the adoption of an intranet-based knowledge management (KM) system (called InTouch) to support, strategically align and transfer knowledge resources. The investigation was undertaken through the adoption of a robust methodological approach (abductive strategy) incorporating the role of technology as an enabler of knowledge management application. Consequently, the study addressed the important question of translating theoretical benefits of KM into practical reality. The research formulates a set of theoretical propositions which are seen as key to the development of an effective knowledge based infrastructure. The findings identify 30 generic attributes that are essential to the creation, mobilisation and diffusion of organisational knowledge. The research makes a significant contribution to identifying a theoretical and empirically based agenda for successful intranet-based KM which will be of benefit to both the academic and practitioner communities. The paper also highlights and proposes important areas for further research

Investigating knowledge management factors affecting Chinese ICT firms performance: An integrated KM framework

This is an Author's Accepted Manuscript of an article published in the Journal of Information Systems Management, 28(1), 19 - 29, 2011, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/10580530.2011.536107.This article sets out to investigate the critical factors of Knowledge Management (KM) which are considered to have an impact on the performance of Chinese information and communication technology (ICT) firms. This study confirms that the cultural environment of an enterprise is central to its success in the context of China. It shows that a collaborated, trusted, and learning environment within ICT firms will have a positive impact on their KM performance

Knowledge Management Practice at a Bulgarian Bank: A Case Study

This paper reports on knowledge management (KM) practices in the customer service and lending departments of one of Bulgaria's top retail banks and investigates how KM processes can be further improved. The Bank's KM activities have been studied using observations, interviews and informal discussions for data collection. Findings were compared and contrasted with existing literature in similar contexts. Although rudiments of knowledge sharing are evident from the KM activities in different departments of the bank, the limitations such as resistance to change of the implemented KM systems are impeding the effectiveness of the knowledge management process. More training and incentives are needed to increase knowledge creation and sharing. Moreover, a clearly articulated KM strategy along with success criteria and commitment and support from senior management is needed. There is a severe lack of knowledge management studies in Bulgarian context in general and Bulgarian banking sector in particular. The authors' findings will potentially help in improving knowledge sharing practice as well as provide a valuable insight into knowledge management related issues in the Bulgarian context. The findings from this research can be useful to companies from Eastern Europe and other regions in improving their knowledge sharing practice