2,719 research outputs found

    Conceptualisation of the three-dimensional matrix of collaborative knowledge barriers

    Full text link
    [EN] Nowadays, collaborative knowledge management (CKM) is well accepted as a decisive asset in the field of networked enterprises and supply chains. However, few knowledge management initiatives have been performed successfully because, in most cases, the barriers that hinder the CKM process are unknown and misunderstood. Currently, the research reveals different uni- and bi-dimensional barriers' classifications, however multi-dimensional approaches provide a better view of the complexity in the area of CKM. Therefore, this paper proposes the three-dimensional matrix of collaborative knowledge barriers taking into account: (i) perspectives; (ii) levels and (iii) barriers blocks to provide a reference way to audit the CKM barriers, and thus, in further research, focus on the corrections and adjustments to guarantee the success while implementing a CKM project.Sanchis, R.; Sanchis Gisbert, MR.; Poler, R. (2020). Conceptualisation of the three-dimensional matrix of collaborative knowledge barriers. Sustainability. 12(3):1-25. https://doi.org/10.3390/su12031279S125123Rajabion, L., Sataei Mokhtari, A., Khordehbinan, M. W., Zare, M., & Hassani, A. (2019). The role of knowledge sharing in supply chain success. Journal of Engineering, Design and Technology, 17(6), 1222-1249. doi:10.1108/jedt-03-2019-0052Sanguankaew, P., & Vathanophas Ractham, V. (2019). Bibliometric Review of Research on Knowledge Management and Sustainability, 1994–2018. Sustainability, 11(16), 4388. doi:10.3390/su11164388Zhang, J., Dawes, S. S., & Sarkis, J. (2005). Exploring stakeholders’ expectations of the benefits and barriers of e‐government knowledge sharing. Journal of Enterprise Information Management, 18(5), 548-567. doi:10.1108/17410390510624007Riege, A. (2005). Three‐dozen knowledge‐sharing barriers managers must consider. Journal of Knowledge Management, 9(3), 18-35. doi:10.1108/13673270510602746Yih‐Tong Sun, P., & Scott, J. L. (2005). An investigation of barriers to knowledge transfer. Journal of Knowledge Management, 9(2), 75-90. doi:10.1108/13673270510590236Solli-Sæther, H., Karlsen, J. T., & van Oorschot, K. (2015). Strategic and Cultural Misalignment: Knowledge Sharing Barriers in Project Networks. Project Management Journal, 46(3), 49-60. doi:10.1002/pmj.21501Kukko, M. (2013). Knowledge sharing barriers in organic growth: A case study from a software company. The Journal of High Technology Management Research, 24(1), 18-29. doi:10.1016/j.hitech.2013.02.006Mazorodze, A. H., & Buckley, S. (2019). Knowledge management in knowledge-intensive organisations: Understanding its benefits, processes, infrastructure and barriers. SA Journal of Information Management, 21(1). doi:10.4102/sajim.v21i1.990Vuori, V., Helander, N., & Mäenpää, S. (2018). Network level knowledge sharing: Leveraging Riege’s model of knowledge barriers. Knowledge Management Research & Practice, 17(3), 253-263. doi:10.1080/14778238.2018.1557999Bacon, E., Williams, M. D., & Davies, G. (2020). Coopetition in innovation ecosystems: A comparative analysis of knowledge transfer configurations. Journal of Business Research, 115, 307-316. doi:10.1016/j.jbusres.2019.11.005General Perspectives on Knowledge Management: Fostering a Research Agenda. (2001). Journal of Management Information Systems, 18(1), 5-21. doi:10.1080/07421222.2001.11045672Gupta, S., & Bostrom, R. (2006). Using peer-to-peer technology for collaborative knowledge management: concepts, frameworks and research issues. Knowledge Management Research & Practice, 4(3), 187-196. doi:10.1057/palgrave.kmrp.8500103Bosua, R., & Scheepers, R. (2007). Towards a model to explain knowledge sharing in complex organizational environments. Knowledge Management Research & Practice, 5(2), 93-109. doi:10.1057/palgrave.kmrp.8500131Brandt, D., & Hartmann, E. (1999). Editorial: Research topics and strategies in sociotechnical systems. Human Factors and Ergonomics in Manufacturing, 9(3), 241-243. doi:10.1002/(sici)1520-6564(199922)9:33.0.co;2-bKim, S., & Lee, H. (2006). The Impact of Organizational Context and Information Technology on Employee Knowledge-Sharing Capabilities. Public Administration Review, 66(3), 370-385. doi:10.1111/j.1540-6210.2006.00595.xArgote, L., Beckman, S. L., & Epple, D. (1990). The Persistence and Transfer of Learning in Industrial Settings. Management Science, 36(2), 140-154. doi:10.1287/mnsc.36.2.140Gupta, N., Ho, V., Pollack, J. M., & Lai, L. (2016). A multilevel perspective of interpersonal trust: Individual, dyadic, and cross-level predictors of performance. Journal of Organizational Behavior, 37(8), 1271-1292. doi:10.1002/job.2104Gray, B., & Wood, D. J. (1991). Collaborative Alliances: Moving from Practice to Theory. The Journal of Applied Behavioral Science, 27(1), 3-22. doi:10.1177/0021886391271001Roberts, N. C., & Bradley, R. T. (1991). Stakeholder Collaboration and Innovation: A Study of Public Policy Initiation at the State Level. The Journal of Applied Behavioral Science, 27(2), 209-227. doi:10.1177/0021886391272004Scheff, J., & Kotler, P. (1996). Crisis in the Arts: The Marketing Response. California Management Review, 39(1), 28-52. doi:10.2307/41165875Gulati, R., & Gargiulo, M. (1999). Where Do Interorganizational Networks Come From? American Journal of Sociology, 104(5), 1439-1493. doi:10.1086/210179Maitlo, A., Ameen, N., Peikari, H. R., & Shah, M. (2019). Preventing identity theft. Information Technology & People, 32(5), 1184-1214. doi:10.1108/itp-05-2018-0255Bolloju, N., Khalifa, M., & Turban, E. (2002). Integrating knowledge management into enterprise environments for the next generation decision support. Decision Support Systems, 33(2), 163-176. doi:10.1016/s0167-9236(01)00142-7Hanisch, B., Lindner, F., Mueller, A., & Wald, A. (2009). Knowledge management in project environments. Journal of Knowledge Management, 13(4), 148-160. doi:10.1108/13673270910971897Yew Wong, K., & Aspinwall, E. (2004). Characterizing knowledge management in the small business environment. Journal of Knowledge Management, 8(3), 44-61. doi:10.1108/13673270410541033Knowledge Acquisition and Sharing for Requirement Engineeringhttps://cordis.europa.eu/project/id/28916Practical Tools and Methods for Corporate Knowledge Management—Sharing and Capitalising Engineering Know-How in the Concurrent Enterprisehttps://cordis.europa.eu/project/id/IST-1999-12685Szulanski, G. (1996). Exploring internal stickiness: Impediments to the transfer of best practice within the firm. Strategic Management Journal, 17(S2), 27-43. doi:10.1002/smj.4250171105Wehn, U., & Almomani, A. (2019). Incentives and barriers for participation in community-based environmental monitoring and information systems: A critical analysis and integration of the literature. Environmental Science & Policy, 101, 341-357. doi:10.1016/j.envsci.2019.09.002Schiavone, F., & Simoni, M. (2011). An experience‐based view of co‐opetition in R&D networks. European Journal of Innovation Management, 14(2), 136-154. doi:10.1108/14601061111124867Li, Y., Liu, Y., & Liu, H. (2010). Co-opetition, distributor’s entrepreneurial orientation and manufacturer’s knowledge acquisition: Evidence from China. Journal of Operations Management, 29(1-2), 128-142. doi:10.1016/j.jom.2010.07.006McGaughey, S. L., Liesch, P. W., & Poulson, D. (2000). An unconventional approach to intellectual property protection: the case of an Australian firm transferring shipbuilding technologies to China. Journal of World Business, 35(1), 1-20. doi:10.1016/s1090-9516(99)00031-0Ilvonen, I., & Vuori, V. (2013). Risks and benefits of knowledge sharing in co-opetitive knowledge networks. International Journal of Networking and Virtual Organisations, 13(3), 209. doi:10.1504/ijnvo.2013.063049Martinez-Noya, A., Garcia-Canal, E., & Guillen, M. F. (2012). R&D Outsourcing and the Effectiveness of Intangible Investments: Is Proprietary Core Knowledge Walking out of the Door? Journal of Management Studies, 50(1), 67-91. doi:10.1111/j.1467-6486.2012.01086.xROSEN, B., FURST, S., & BLACKBURN, R. (2007). Overcoming Barriers to Knowledge Sharing in Virtual Teams. Organizational Dynamics, 36(3), 259-273. doi:10.1016/j.orgdyn.2007.04.007Hislop, D. (2005). The effect of network size on intra-network knowledge processes. Knowledge Management Research & Practice, 3(4), 244-252. doi:10.1057/palgrave.kmrp.8500073Abou-Zeid, E.-S. (2005). A culturally aware model of inter-organizational knowledge transfer. Knowledge Management Research & Practice, 3(3), 146-155. doi:10.1057/palgrave.kmrp.8500064Balle, A. R., Steffen, M. O., Curado, C., & Oliveira, M. (2019). Interorganizational knowledge sharing in a science and technology park: the use of knowledge sharing mechanisms. Journal of Knowledge Management, 23(10), 2016-2038. doi:10.1108/jkm-05-2018-0328Baccarini, D., Salm, G., & Love, P. E. D. (2004). Management of risks in information technology projects. Industrial Management & Data Systems, 104(4), 286-295. doi:10.1108/02635570410530702Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A review of enterprise agility: Concepts, frameworks, and attributes. International Journal of Industrial Ergonomics, 37(5), 445-460. doi:10.1016/j.ergon.2007.01.007Peltokorpi, V. (2006). Knowledge sharing in a cross-cultural context: Nordic expatriates in Japan. Knowledge Management Research & Practice, 4(2), 138-148. doi:10.1057/palgrave.kmrp.8500095Solitander, M., & Tidström, A. (2010). Competitive flows of intellectual capital in value creating networks. Journal of Intellectual Capital, 11(1), 23-38. doi:10.1108/14691931011013316Khamseh, H. M., & Jolly, D. (2014). Knowledge transfer in alliances: the moderating role of the alliance type. Knowledge Management Research & Practice, 12(4), 409-420. doi:10.1057/kmrp.2012.63Corallo, A., Lazoi, M., & Secundo, G. (2012). Inter-organizational knowledge integration in Collaborative NPD projects: evidence from the aerospace industry. Knowledge Management Research & Practice, 10(4), 354-367. doi:10.1057/kmrp.2012.25Salvetat, D., Géraudel, M., & d’ Armagnac, S. (2013). Inter-organizational knowledge management in a coopetitive context in the aeronautic and space industry. Knowledge Management Research & Practice, 11(3), 265-277. doi:10.1057/kmrp.2012.6Baba, M. L., Gluesing, J., Ratner, H., & Wagner, K. H. (2004). The contexts of knowing: natural history of a globally distributed team. Journal of Organizational Behavior, 25(5), 547-587. doi:10.1002/job.259Korbi, F. B., & Chouki, M. (2017). Knowledge transfer in international asymmetric alliances: the key role of translation, artifacts, and proximity. Journal of Knowledge Management, 21(5), 1272-1291. doi:10.1108/jkm-11-2016-0501Faerman, S. R., McCaffrey, D. P., & Slyke, D. M. V. (2001). Understanding Interorganizational Cooperation: Public-Private Collaboration in Regulating Financial Market Innovation. Organization Science, 12(3), 372-388. doi:10.1287/orsc.12.3.372.10099Jaworski, B. J. (1988). Toward a Theory of Marketing Control: Environmental Context, Control Types, and Consequences. Journal of Marketing, 52(3), 23-39. doi:10.1177/002224298805200303Cooke-Davies, T. (2002). The «real» success factors on projects. International Journal of Project Management, 20(3), 185-190. doi:10.1016/s0263-7863(01)00067-9Santos, V. R., Soares, A. L., & Carvalho, J. Á. (2012). Knowledge Sharing Barriers in Complex Research and Development Projects: an Exploratory Study on the Perceptions of Project Managers. Knowledge and Process Management, 19(1), 27-38. doi:10.1002/kpm.1379Tiwari, S. R. (2015). Knowledge Integration in Government-Industry Project Network. Knowledge and Process Management, 22(1), 11-21. doi:10.1002/kpm.1460Mariotti, F. (2007). Learning to share knowledge in the Italian motorsport industry. Knowledge and Process Management, 14(2), 81-94. doi:10.1002/kpm.275Ardichvili, A. (2008). Learning and Knowledge Sharing in Virtual Communities of Practice: Motivators, Barriers, and Enablers. Advances in Developing Human Resources, 10(4), 541-554. doi:10.1177/1523422308319536Levy, M., Loebbecke, C., & Powell, P. (2003). SMEs, co-opetition and knowledge sharing: the role of information systems. European Journal of Information Systems, 12(1), 3-17. doi:10.1057/palgrave.ejis.3000439Gabelica, C., Bossche, P. V. den, Segers, M., & Gijselaers, W. (2012). Feedback, a powerful lever in teams: A review. Educational Research Review, 7(2), 123-144. doi:10.1016/j.edurev.2011.11.003Zakaria, N., Amelinckx, A., & Wilemon, D. (2004). Working Together Apart? Building a Knowledge-Sharing Culture for Global Virtual Teams. Creativity and Innovation Management, 13(1), 15-29. doi:10.1111/j.1467-8691.2004.00290.xKatz, R., & Allen, T. J. (1982). Investigating the Not Invented Here (NIH) syndrome: A look at the performance, tenure, and communication patterns of 50 R & D Project Groups. R&D Management, 12(1), 7-20. doi:10.1111/j.1467-9310.1982.tb00478.xGupta, A. K., & Govindarajan, V. (2000). Knowledge flows within multinational corporations. Strategic Management Journal, 21(4), 473-496. doi:10.1002/(sici)1097-0266(200004)21:43.0.co;2-iBarkema, H. G., & Vermeulen, F. (1997). What Differences in the Cultural Backgrounds of Partners Are Detrimental for International Joint Ventures? Journal of International Business Studies, 28(4), 845-864. doi:10.1057/palgrave.jibs.8490122Sanchis, R., & Poler, R. (2019). Enterprise Resilience Assessment—A Quantitative Approach. Sustainability, 11(16), 4327. doi:10.3390/su11164327Vaara, E., Sarala, R., Stahl, G. K., & Björkman, I. (2010). The Impact of Organizational and National Cultural Differences on Social Conflict and Knowledge Transfer in International Acquisitions. Journal of Management Studies, 49(1), 1-27. doi:10.1111/j.1467-6486.2010.00975.xRichards, D., Busch, P., & Venkitachalam, K. (2007). Ethnicity-based cultural differences in implicit managerial knowledge usage in three Australian organizations. Knowledge Management Research & Practice, 5(3), 173-185. doi:10.1057/palgrave.kmrp.8500145Seely Brown, J., & Duguid, P. (s. f.). Structure and Spontaneity: Knowledge and Organization. Managing Industrial Knowledge: Creation, Transfer and Utilization, 44-67. doi:10.4135/9781446217573.n3Nonaka, I., & Konno, N. (1998). The Concept of «Ba»: Building a Foundation for Knowledge Creation. California Management Review, 40(3), 40-54. doi:10.2307/41165942Bocquet, R., & Mothe, C. (2010). Knowledge governance within clusters: the case of small firms. Knowledge Management Research & Practice, 8(3), 229-239. doi:10.1057/kmrp.2010.14Janssens, M., Lambert, J., & Steyaert, C. (2004). Developing language strategies for international companies: the contribution of translation studies. Journal of World Business, 39(4), 414-430. doi:10.1016/j.jwb.2004.08.006Aga, D. A., Noorderhaven, N., & Vallejo, B. (2016). Transformational leadership and project success: The mediating role of team-building. International Journal of Project Management, 34(5), 806-818. doi:10.1016/j.ijproman.2016.02.012Panahi, S., Watson, J., & Partridge, H. (2015). Information encountering on social media and tacit knowledge sharing. Journal of Information Science, 42(4), 539-550. doi:10.1177/0165551515598883Bisbal, J., Lawless, D., Bing Wu, & Grimson, J. (1999). Legacy information systems: issues and directions. IEEE Software, 16(5), 103-111. doi:10.1109/52.795108Holsapple, C. W., & Joshi, K. D. (2002). Knowledge Management: A Threefold Framework. The Information Society, 18(1), 47-64. doi:10.1080/01972240252818225Lee, M. R., & Chen, T. T. (2012). Revealing research themes and trends in knowledge management: From 1995 to 2010. Knowledge-Based Systems, 28, 47-58. doi:10.1016/j.knosys.2011.11.016Sieber, J. E. (1988). Data sharing: Defining problems and seeking solutions. Law and Human Behavior, 12(2), 199-206. doi:10.1007/bf01073128Pauleen, D. J., & Wang, W. Y. C. (2017). Does big data mean big knowledge? KM perspectives on big data and analytics. Journal of Knowledge Management, 21(1), 1-6. doi:10.1108/jkm-08-2016-033

    Enterprise Resilience Assessment A Quantitative Approach

    Full text link
    [EN] Enterprise resilience is a key capacity to guarantee enterprises¿ long-term continuity. This paper proposes a quantitative approach to enhance enterprise resilience by selecting optimal preventive actions to be activated to cushion the impact of disruptive events and to improve preparedness capability, one of the pillars of the enterprise resilience capacity. The proposed algorithms combine the dynamic programming approach with attenuation formulas to model real improvements when a combined set of preventive actions is activated for the same disruptive event. A numerical example is presented that shows remarkable reductions in the expected annual cost due to potential disruptive events.Sanchis, R.; Poler, R. (2019). Enterprise Resilience Assessment A Quantitative Approach. Sustainability. 11(16):1-13. https://doi.org/10.3390/su11164327S1131116Baghersad, M., & Zobel, C. W. (2015). Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors. International Journal of Production Economics, 168, 71-80. doi:10.1016/j.ijpe.2015.06.011Cagliano, A. C., De Marco, A., Grimaldi, S., & Rafele, C. (2012). An integrated approach to supply chain risk analysis. Journal of Risk Research, 15(7), 817-840. doi:10.1080/13669877.2012.666757Vanpoucke, E., Boyer, K. K., & Vereecke, A. (2009). Supply chain information flow strategies: an empirical taxonomy. International Journal of Operations & Production Management, 29(12), 1213-1241. doi:10.1108/01443570911005974Chaudhuri, A., Boer, H., & Taran, Y. (2018). Supply chain integration, risk management and manufacturing flexibility. International Journal of Operations & Production Management, 38(3), 690-712. doi:10.1108/ijopm-08-2015-0508Oliva, F. L. (2016). A maturity model for enterprise risk management. International Journal of Production Economics, 173, 66-79. doi:10.1016/j.ijpe.2015.12.007Hendry, L. C., Stevenson, M., MacBryde, J., Ball, P., Sayed, M., & Liu, L. (2019). Local food supply chain resilience to constitutional change: the Brexit effect. International Journal of Operations & Production Management, 39(3), 429-453. doi:10.1108/ijopm-03-2018-0184Prior, T., & Hagmann, J. (2013). Measuring resilience: methodological and political challenges of a trend security concept. Journal of Risk Research, 17(3), 281-298. doi:10.1080/13669877.2013.808686Holling, C. S. (1973). Resilience and Stability of Ecological Systems. Annual Review of Ecology and Systematics, 4(1), 1-23. doi:10.1146/annurev.es.04.110173.000245Haimes, Y. Y. (2009). On the Definition of Resilience in Systems. Risk Analysis, 29(4), 498-501. doi:10.1111/j.1539-6924.2009.01216.xDoorn, N. (2015). Resilience indicators: opportunities for including distributive justice concerns in disaster management. Journal of Risk Research, 20(6), 711-731. doi:10.1080/13669877.2015.1100662Scholz, R. W., Blumer, Y. B., & Brand, F. S. (2012). Risk, vulnerability, robustness, and resilience from a decision-theoretic perspective. Journal of Risk Research, 15(3), 313-330. doi:10.1080/13669877.2011.634522Reyes Levalle, R., & Nof, S. Y. (2015). Resilience by teaming in supply network formation and re-configuration. International Journal of Production Economics, 160, 80-93. doi:10.1016/j.ijpe.2014.09.036Kamalahmadi, M., & Parast, M. M. (2016). A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research. International Journal of Production Economics, 171, 116-133. doi:10.1016/j.ijpe.2015.10.023Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124-143. doi:10.1108/09574090910954873Comfort, L. K., Sungu, Y., Johnson, D., & Dunn, M. (2001). Complex Systems in Crisis: Anticipation and Resilience in Dynamic Environments. Journal of Contingencies and Crisis Management, 9(3), 144-158. doi:10.1111/1468-5973.00164Ayyub, B. M. (2013). Systems Resilience for Multihazard Environments: Definition, Metrics, and Valuation for Decision Making. Risk Analysis, 34(2), 340-355. doi:10.1111/risa.12093Cox Jr., L. A. T. (2012). Community Resilience and Decision Theory Challenges for Catastrophic Events. Risk Analysis, 32(11), 1919-1934. doi:10.1111/j.1539-6924.2012.01881.xSchmitt, A. J., & Singh, M. (2012). A quantitative analysis of disruption risk in a multi-echelon supply chain. International Journal of Production Economics, 139(1), 22-32. doi:10.1016/j.ijpe.2012.01.004Dabhilkar, M., Birkie, S. E., & Kaulio, M. (2016). Supply-side resilience as practice bundles: a critical incident study. International Journal of Operations & Production Management, 36(8), 948-970. doi:10.1108/ijopm-12-2014-0614Dormady, N., Roa-Henriquez, A., & Rose, A. (2019). Economic resilience of the firm: A production theory approach. International Journal of Production Economics, 208, 446-460. doi:10.1016/j.ijpe.2018.07.017Polyviou, M., Croxton, K. L., & Knemeyer, A. M. (2019). Resilience of medium-sized firms to supply chain disruptions: the role of internal social capital. International Journal of Operations & Production Management, 40(1), 68-91. doi:10.1108/ijopm-09-2017-0530The Ripple Effect—How Manufacturing and Retail Executives View the Growing Challenge of Supply Chain Risk www2.deloitte.com/us/en/pages/operations/articles/supply-chain-risk-ripple-effect.htmlRisk Ranking 2013–2015 http://www.ey.com/GL/en/Services/Advisory/Business-Pulse--top-10-risks-and-opportunitiesGlobal Risk Management Survey—Executive Summary www.aon.com/2017-global-risk-management-survey/pdfs/2017-Aon-Global-Risk-Management-Survey-Full-Report-062617.pdfThe State of Enterprise Resilience Survey 2016/2017 www.controlrisks.com/our-thinking/insights/reports/the-state-of-enterprise-resilience-survey-2016-201720th CEO Survey www.pwc.com/gx/en/ceo-survey/2017/pwc-ceo-20th-survey-report-2017.pdfBCI Supply Chain Resilience Report 2018 www.thebci.org/uploads/assets/uploaded/c50072bf-df5c-4c98-a5e1876aafb15bd0.pdfThe global risks report 2019 www.weforum.org/reports/the-global-risks-report-2019Madni, A. M., & Jackson, S. (2009). Towards a Conceptual Framework for Resilience Engineering. IEEE Systems Journal, 3(2), 181-191. doi:10.1109/jsyst.2009.2017397Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). ENSURING SUPPLY CHAIN RESILIENCE: DEVELOPMENT OF A CONCEPTUAL FRAMEWORK. Journal of Business Logistics, 31(1), 1-21. doi:10.1002/j.2158-1592.2010.tb00125.xBellman, R. (1954). The theory of dynamic programming. Bulletin of the American Mathematical Society, 60(6), 503-516. doi:10.1090/s0002-9904-1954-09848-8Cord, J. (1964). A Method for Allocating Funds to Investment Projects when Returns are Subject to Uncertainty. Management Science, 10(2), 335-341. doi:10.1287/mnsc.10.2.335Weingartner, H. M. (1966). Capital Budgeting of Interrelated Projects: Survey and Synthesis. Management Science, 12(7), 485-516. doi:10.1287/mnsc.12.7.485Weingartner, H. M., & Ness, D. N. (1967). Methods for the Solution of the Multidimensional 0/1 Knapsack Problem. Operations Research, 15(1), 83-103. doi:10.1287/opre.15.1.83Nemhauser, G. L., & Ullmann, Z. (1969). Discrete Dynamic Programming and Capital Allocation. Management Science, 15(9), 494-505. doi:10.1287/mnsc.15.9.494Boyer, V., Baz, D. E., & Elkihel, M. (2010). Solution of multidimensional knapsack problems via cooperation of dynamic programming and branch and bound. European J. of Industrial Engineering, 4(4), 434. doi:10.1504/ejie.2010.035653Skiena, S. S. (1999). Who is interested in algorithms and why? ACM SIGACT News, 30(3), 65-74. doi:10.1145/333623.333627Chou, T.-C., & Talalay, P. (1983). Analysis of combined drug effects: a new look at a very old problem. Trends in Pharmacological Sciences, 4, 450-454. doi:10.1016/0165-6147(83)90490-xChou, T.-C., & Talalay, P. (1984). Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors. Advances in Enzyme Regulation, 22, 27-55. doi:10.1016/0065-2571(84)90007-4Belen’kii, M. S., & Schinazi, R. F. (1994). Multiple drug effect analysis with confidence interval. Antiviral Research, 25(1), 1-11. doi:10.1016/0166-3542(94)90089-2Glossary of Terms and Symbols Used in Pharmacology. Pharmacology and Experimental Therapeutics Department at Boston University School of Medicine http://www.bumc.bu.edu/busm-pm/academics/resources/glossary/Foucquier, J., & Guedj, M. (2015). Analysis of drug combinations: current methodological landscape. Pharmacology Research & Perspectives, 3(3), e00149. doi:10.1002/prp2.149Tallarida, R. J. (2011). Quantitative Methods for Assessing Drug Synergism. Genes & Cancer, 2(11), 1003-1008. doi:10.1177/194760191244057

    Mitigation proposal for the enhancement of enterprise resilience against supply disruptions

    Full text link
    [EN] The current context is characterised by growing uncertainty, insecurities and risks. To overcome this situation, enterprises need to be resilient enough to guarantee its business continuity. This research is focused on the preparedness capacity, one of the three constituent capacities of enterprise resilience. To be prepared for the unexpected, it is necessary to identify, the most critical disruptive events companies face from a supply side and propose mitigation actions to provide companies with a set of alternatives to support the enhancement of the preparedness capacity of enterprise resilience. This research offers valuable information about both aspects; an analysis of the most worrisome supply disruptive events and a proposal of preventive actions as mitigation policies.Sanchis, R.; Poler, R. (2019). Mitigation proposal for the enhancement of enterprise resilience against supply disruptions. IFAC-PapersOnLine. 52(13):2833-2838. https://doi.org/10.1016/j.ifacol.2019.11.638S28332838521

    Searching for BcB_c mesons in the ATLAS experiment at LHC

    Get PDF
    We discuss the feasibility of the observation of the signal from BcB_c mesons in the ATLAS experiment of the LHC collider at a luminosity of ${\approx}\ 10^{33}cmcm^{-2}ss^{-1}.Inparticularweaddressthedecaymode. In particular we address the decay mode B_c{\rightarrow}J/\psi \pifollowedbytheleptonicdecay followed by the leptonic decay J/\psi{\rightarrow}\mu^+\mu^-,whichshouldpermitanaccuratemeasurementofthe, which should permit an accurate measurement of the B_cmass.WeperformedaMonteCarlostudyofthesignalandbackgroundconcludingthataprecisionof mass. We performed a Monte Carlo study of the signal and background concluding that a precision of 40MeVforthe MeV for the B_c$ mass could be achieved after one year of running.Comment: Latex,7 pages including 3 uuencoded Postscript figures appended at the end of the latex fil

    Decision-making in teamworks: sticky notes tool for degree

    Full text link
    [EN] This paper is focused on the presentation of an open-source online tool based on the methodology of sticky notes tools to support Industrial Engineering degree students in the practical work of decision-making and in the teamwork's practical sessions. The main aim of this paper is to identify a tool to support students, as future industrial engineers, in the decision-making process through teamwork, in the establishment of strategic policies, and in the process of creating solutions, amongst others. Moreover, three different case study are provided with the main objective of showing the potential of the proposed tool in the scope of decision-making in teamwork's.Andres, B.; Sanchis, R.; Poler, R. (2016). Decision-making in teamworks: sticky notes tool for degree. ICERI Proceedings. 4293-4301. doi:10.21125/iceri.2016.2010S4293430

    Text-To-Speech Applications to Develop Educational Materials

    Full text link
    [EN] There are several ways to develop educational materials and several different types of educational materials depending on the audience, objectives, topics or themes, type of education, among others. One of the most common educational materials developed is the use of presentations slides where to shape the information that the trainer wishes to share. The most used presentation graphics packages are Microsoft PowerPoint, OpenOffice Impress and Apple KeyNote. These systems enable Word processing, outlining, drawing, graphing, and displaying different presentation management tools to design and configure a presentation. This educational material is usually used to be shown during an explanation in a master class or online through an e-learning platform. In the case that the education material is available through an online resource, it is important not only to present the information in a readable manner but: (i) to add the explanation as a spoken sound version in order to give to the receiver more information than the one that is displayed in the slides and (ii) to avoid fatigue due to reading all the information of the slides. Currently, there are different text-to-speech applications that allow to play sound files based on text without the interaction of humans. This paper focuses on these applications, which their main characteristics are and which their benefits and weaknesses are in order to select the most appropriate one to develop the different types of educational materials.Sanchis, R.; Andres, B.; Poler, R. (2018). Text-To-Speech Applications to Develop Educational Materials. INTED proceedings (Online). 6085-6093. doi:10.21125/inted.2018.1436S6085609
    corecore