Mitigation proposal for the enhancement of enterprise resilience against supply disruptions

[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

Enterprise Resilience Assessment A Quantitative Approach

[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

A review of approaches and tools for collaborative networks simulation

Collaborative networks (CN) are characterised by being complex systems, highlighting the need of considering simulation approaches to support the resolution of CN models. Simulation approaches are seen as a supporting tool to analyse the formal model of a supply network. Three relevant simulation approaches are identified for its application in the context of CN models: Discrete Events Simulation, System Dynamics and Agent Based Simulation. Each simulation approach is briefly described and compared with each other, according to a group of relevant features, with the main aim of aiding the modellers in the task of selecting the most appropriate simulation approach to address the modelling process in the context of CN. Besides, a group of commercial and academic tools are listed for each simulation approach.Andres, B.; Poler, R. (2016). A review of approaches and tools for collaborative networks simulation. Brazilian Journal of Operations and Production Management. 13(3):232-242. doi:10.14488/BJOPM.2016.v13.n3.a1S23224213

Storyboard tools for university and education research projects

[EN] This paper is focused on the presentation of storyboard and storytelling open source online tools, for its application in the university context and in the education research projects. The main aim of this paper is to provide an open source tool to support (i) university teachers, using storyboard tools as a novel educational resource to include in their master and practice classes, allowing them to structure concepts or explain methodologies through images that have attached short descriptions; (ii) university students, as future industrial engineers, employing storyboard tools for structuring the decision-making process, by taking into account all the actors that are affected in the decision process; (iii) education research projects, adopting storyboard as a tool to aid the creative writing through matching creative images with keywords to capture the essence of the research project.The research leading to these results has received funding from European Community's H2020 Programme (H2020/2014-2020) under grant agreement no 636909, "Cloud Collaborative Manufacturing Networks (C2NET)".Andres, B.; Poler, R. (2017). Storyboard tools for university and education research projects. INTED proceedings (Online). 220-227. https://doi.org/10.21125/inted.2017.0173S22022

A decision support system for the collaborative selection of strategies in enterprise networks

Collaborative networks (CN) consist of autonomous and heterogeneous partners, and each defines its own objectives and formulates its own strategies, which are selected and activated to achieve these objectives. The heterogeneity that characterises network partners could lead to contradictions appearing among the strategies formulated in each CN enterprise. Consequently, the strategies formulated in one enterprise could negatively influence the achievement of the objectives defined in other enterprises of the same network. These contradictions lead to strategies misalignments, which worsens the network performance. In order to deal with these misalignments, a DSS is proposed to support the process of selecting the strategies among all those formulated, with the aim of achieving higher alignment levels. The proposed DSS considers the impacts that each strategy formulated in each enterprise has on the performance of the objectives defined by each network partner. This allows enterprises to select a set of aligned strategies. The selection of proper strategies to be activated in each enterprise strongly influences the CN's performance level, and higher levels of network adaptability, agility and competitiveness are achieved. The proposed DSS is validated under real conditions in a food industry network. The DSS is evaluated by emulating real collaborative conditions and is compared with the equivalent non-collaborative decision making perspective used for selecting strategies. The results demonstrate that the collaborative approach outperforms the performance level of the non-collaborative one and is more effective for handling the robustness and the long-term operation of the CN.Andres, B.; Poler, R. (2016). A decision support system for the collaborative selection of strategies in enterprise networks. Decision Support Systems. 91:113-123. doi:10.1016/j.dss.2016.08.005S1131239

An Information Management Conceptual Approach for the Strategies Alignment Collaborative Process

[EN] This paper proposes an information management approach to deal with the strategies alignment collaborative process. Much attention has been given to the information management in collaborative networks (CNs), resulting in a wide variety of information management approaches and frameworks. The treatment, estimation, and collection of data are key issues that still need to be addressed, due to the complexity associated with the information exchange and the need to build trust relationships within the CN. In order to address this literature gap, this paper presents an approach to manage information in the specific collaborative process of strategies alignment. The approach is composed of a methodology, that enables to identify the roles participating in the application of the collaborative process, select the collaborative application context, determine the level of collaboration to be applied, and estimate and gather the data required to feed the strategies alignment process. The proposed information management approach bridges the conceptual model of strategies alignment process, with its application in real-world CNs.This work has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 872548 "Fostering DIHs for Embedding Interoperability in Cyber-Physical Systems of European SMEs" (DIH4CPS) (http://dih4cps.eu/).Andres, B.; Poler, R. (2020). An Information Management Conceptual Approach for the Strategies Alignment Collaborative Process. Sustainability. 12(10):1-22. https://doi.org/10.3390/su12103959S1221210Camarinha-Matos, L. M., & Afsarmanesh, H. (2005). Collaborative networks: a new scientific discipline. Journal of Intelligent Manufacturing, 16(4-5), 439-452. doi:10.1007/s10845-005-1656-3Cheikhrouhou, N., Pouly, M., & Madinabeitia, G. (2013). Trust categories and their impacts on information exchange processes in vertical collaborative networked organisations. International Journal of Computer Integrated Manufacturing, 26(1-2), 87-100. doi:10.1080/0951192x.2012.681913Andres, B., & Poler, R. (2016). A decision support system for the collaborative selection of strategies in enterprise networks. Decision Support Systems, 91, 113-123. doi:10.1016/j.dss.2016.08.005Blome, C., Paulraj, A., & Schuetz, K. (2014). Supply chain collaboration and sustainability: a profile deviation analysis. International Journal of Operations & Production Management, 34(5), 639-663. doi:10.1108/ijopm-11-2012-0515Soosay, C. A., & Hyland, P. (2015). A decade of supply chain collaboration and directions for future research. Supply Chain Management: An International Journal, 20(6), 613-630. doi:10.1108/scm-06-2015-0217Chen, L., Zhao, X., Tang, O., Price, L., Zhang, S., & Zhu, W. (2017). Supply chain collaboration for sustainability: A literature review and future research agenda. International Journal of Production Economics, 194, 73-87. doi:10.1016/j.ijpe.2017.04.005Transforming Our World: The 2030 Agenda for Sustainable Development https://sustainabledevelopment.un.org/post2015/transformingourworldFonseca, L. M., Domingues, J. P., & Dima, A. M. (2020). Mapping the Sustainable Development Goals Relationships. Sustainability, 12(8), 3359. doi:10.3390/su12083359Horan, D. (2019). A New Approach to Partnerships for SDG Transformations. Sustainability, 11(18), 4947. doi:10.3390/su11184947Andres, B., & Marcucci, G. (2020). A Strategies Alignment Approach to Manage Disruptive Events in Collaborative Networks. Sustainability, 12(7), 2641. doi:10.3390/su12072641Andres, B., & Blanes, V. J. (2020). A Negotiation Approach to Support the Strategies Alignment Process in Collaborative Networks. Sustainability, 12(7), 2766. doi:10.3390/su12072766Provan, K. G., & Kenis, P. (2007). Modes of Network Governance: Structure, Management, and Effectiveness. Journal of Public Administration Research and Theory, 18(2), 229-252. doi:10.1093/jopart/mum015Pilbeam, C., Alvarez, G., & Wilson, H. (2012). The governance of supply networks: a systematic literature review. Supply Chain Management: An International Journal, 17(4), 358-376. doi:10.1108/13598541211246512Alemany, M. M. E., Alarcón, F., Lario, F.-C., & Boj, J. J. (2011). An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning. Computers in Industry, 62(5), 519-540. doi:10.1016/j.compind.2011.02.002Schneeweiss, C. (2003). Distributed decision making in supply chain management. International Journal of Production Economics, 84(1), 71-83. doi:10.1016/s0925-5273(02)00381-xAlemany, M. M. E., Boj, J. J., Mula, J., & Lario, F.-C. (2009). Mathematical programming model for centralised master planning in ceramic tile supply chains. International Journal of Production Research, 48(17), 5053-5074. doi:10.1080/00207540903055701Saiz, J. J. A., Rodriguez, R. R., Bas, A. O., & Verdecho, M. J. (2010). An information architecture for a performance management framework by collaborating SMEs. Computers in Industry, 61(7), 676-685. doi:10.1016/j.compind.2010.03.012Andrés, B., & Poler, R. (2013). Relevant problems in collaborative processes of non-hierarchical manufacturing networks. Journal of Industrial Engineering and Management, 6(3). doi:10.3926/jiem.552Mula, J., Poler, R., & Garcia, J. P. (2006). MRP with flexible constraints: A fuzzy mathematical programming approach. Fuzzy Sets and Systems, 157(1), 74-97. doi:10.1016/j.fss.2005.05.045Campuzano, F., Mula, J., & Peidro, D. (2010). Fuzzy estimations and system dynamics for improving supply chains. Fuzzy Sets and Systems, 161(11), 1530-1542. doi:10.1016/j.fss.2009.12.002Mula, J., Peidro, D., & Poler, R. (2014). Optimization Models for Supply Chain Production Planning Under Fuzziness. Studies in Fuzziness and Soft Computing, 397-422. doi:10.1007/978-3-642-53939-8_17Da Piedade Francisco, R., Azevedo, A., & Almeida, A. (2012). Alignment prediction in collaborative networks. Journal of Manufacturing Technology Management, 23(8), 1038-1056. doi:10.1108/17410381211276862Savastano, M., Amendola, C., Bellini, F., & D’Ascenzo, F. (2019). Contextual Impacts on Industrial Processes Brought by the Digital Transformation of Manufacturing: A Systematic Review. Sustainability, 11(3), 891. doi:10.3390/su1103089

Decision-making in teamworks: sticky notes tool for degree

[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

[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

Methodology to Identify SMEs Needs of Internationalised and Collaborative Networks

This paper provides a methodology to support researchers in the identification of SMEs needs encountered when establishing collaborative processes within non-hierarchical manufacturing networks. Furthermore, the methodology also determines the needs when non-hierarchical networks internationalise their processes and operations to overcome globalisation and competitive environments. The major goal of this study is to provide a methodology to enable researchers to underline factors of SMEs integration with particular emphasis on the internationalisation of operations and the establishment of collaborative processes with networked partners. The provided methodology is the first step to develop a future empirical study to explore the findings of the literature review applied to SMEs and to identify the enterprises needs appeared when internationalised and collaborative processes are established in nonhierarchical networks.Andrés, B.; Poler, R. (2013). Methodology to Identify SMEs Needs of Internationalised and Collaborative Networks. IFIP Advances in information and communication technology. 398:463-470. doi:10.1007/978-3-642-40361-3_59S463470398Camarinha-Matos, L., Afsarmanesh, H., Galeano, N., Molina, A.: Collaborative networked organisations – Concepts and practice in manufacturing enterprises. Computers & Industrial Engineering 57(1), 46–60 (2008)Corti, D., Egaña, M.M., Errasti, A.: Challenges for off-shored operations: findings from a comparative multi-case study analysis of Italian and Spanish companies. In: Proceedings 16th Annual EurOMA Conference (2009)Mediavilla, M., Errasti, A., Domingo, R.: Framework for assessing the current strategic factory role and deploying an upgrading roadmap. An empirical study within a global operations network. Dirección y Organización 46, 5–15 (2012)Martínez, S., Errasti, A., Santos, J., Mediavilla, M.: Framework for improving the design and configuration process of a global production and logistic network. In: Emmanouilidis, C., Taishch, M., Kiritsis, D. (eds.) APMS 2012, Part II. IFIP AICT, vol. 398, pp. 471–478. Springer, Heidelberg (2013)Andrés, B., Poler, R.: Análisis de los Procesos Colaborativos en Redes de Empresas No-Jerárquicas. In: Ros, L., Fuente, V., Hontoria, E., Soler, D., Morales, C., Bogataj, M. (eds.) Ingeniería Industrial: Redes Innovadoras. XV Congreso de Ingeniería de Organización, CIO 2011 Libro de Actas, Cartagena, Spain, September 7-9, pp. 369–373 (2011)Andrés, B., Poler, R.: Relevant Problems in Collaborative Processes of Non-Hierarchical Manufacturing Networks. In: Prado, J.C., García, J., Comesaña, J.A., Fernández, A.J. (eds.) 6th International Conference on Industrial Engineering and Industrial Management, Vigo, Spain, July 18-20, pp. 90–97 (2012)Alfaro, J.J., Rodríguez, R., Ortiz, A., Verdecho, M.J.: An information architecture for a performance management framework by collaborating SMEs. Computers in Industry 61(7), 676–685 (2010)Ferdows, K.: Making the most of foreign factories. Harvard Business Review, 73–88 (March-April 1997)Flaherty, T.: Coordinating International Manufacturing and Technology. In: Porter, M. (ed.). Harvard Business School Press (1986)McGee, J., Thomas, H., Wilson, D.: Strategy: Analysis and Practice. McGraw-Hill, New York (2005

Team Building Dynamics: An Application to MBA Students

[EN] This paper introduces the concept of team building dynamics for teaching management of high performance teams. A set of methodologies for application, using team building dynamics is proposed and described, by considering also all the steps to follow by the students in order to properly carry out each team building dynamic. Examples of applications in practical classes devoted to MBA students are presented. Finally, a discussion about how the proposed team building dynamics can facilitate compact teamwork is described. The importance of future MBA students, to know the main skills of a good manager, is one of the objectives to achieve in the university education process.Andres, B.; Sanchis, R.; Poler, R. (2018). Team Building Dynamics: An Application to MBA Students. INTED proceedings (Online). 7017-7025. doi:10.21125/inted.2018.1643S7017702