3 research outputs found

    A Modeling Framework to Assess Strategies Alignment based on Collaborative Network Emotions

    Full text link
    [DE] The Collaborative Networks (CN) discipline has been largely studied in last decades, addressing different problems and proposing solutions for the robust establishment of collaborative processes, within the enterprises willing to collaborate. The main aim of CN research is, therefore, to generate approaches that enable creating effective relationships in the long term, to achieve stable and agile alliances. The concept of alignment among the CN partners has been considered since the beginning of CN research. Nevertheless, novel perspectives of study in CN, such as the consideration of collaborative emotional states, within the CN, have been introduced in recent years. This paper connects the research area of strategies alignment and the CN emotion models. Accordingly, a modelling framework to assess strategies alignment considering the emotional environment within the CN is proposed. The modelling framework allows representing how the enterprises emotions affect in the selection and alignment of formulated enterprises¿ strategiesAndres, B.; Ferrada, F.; Poler, R.; Camarinha-Matos, L. (2018). A Modeling Framework to Assess Strategies Alignment based on Collaborative Network Emotions. IFIP Advances in Information and Communication Technology. 534:349-361. https://doi.org/10.1007/978-3-319-99127-6_30S349361534Camarinha-Matos, L.M.: Collaborative networks in industry and the role of PRO-VE. Int. J. Prod. Manag. Eng. 2(2), 53–57 (2014)Andres, B., Poler, R.: Models, guidelines and tools for the integration of collaborative processes in non-hierarchical manufacturing networks: a review. Int. J. Comput. Integr. Manuf. 2(29), 166–201 (2016)Bititci, U., Martinez, V., Albores, P., Parung, J.: Creating and managing value in collaborative networks. Int. J. Phys. Distrib. Logist. Manag. 34(3/4), 251–268 (2004)Carbo, B.: Align the organization for improved supply chain performance. ASCET Proj. 2, 244–447 (2002)Macedo, P., Camarinha-Matos, L.: Value systems alignment analysis in collaborative networked organizations management. Appl. Sci. 7(12), 123 (2017)Andres, B., Poler, R.: A decision support system for the collaborative selection of strategies in enterprise networks. Decis. Support Syst. 91, 113–123 (2016)Andres, B., Macedo, P., Camarinha-Matos, L.M., Poler, R.: Achieving coherence between strategies and value systems in collaborative networks. In: Camarinha-Matos, L.M., Afsarmanesh, H. (eds.) PRO-VE 2014. IFIP AICT, vol. 434, pp. 261–272. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44745-1_26Ferrada, F., Camarinha-Matos, L.M.: A system dynamics and agent-based approach to model emotions in collaborative networks. In: Camarinha-Matos, L.M., Parreira-Rocha, M., Ramezani, J. (eds.) DoCEIS 2017. IFIP AICT, vol. 499, pp. 29–43. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-56077-9_3Campuzano, F., Mula, J.: Supply Chain Simulation. A System Dynamics Approach for Improving Performance. Springer, London (2011). https://doi.org/10.1007/978-0-85729-719-8Camarinha-Matos, L.M., Afsarmanesh, H.: Collaborative networks: a new scientific discipline. J. Intell. Manuf. 16(4–5), 439–452 (2005)Vicsek, T.: Complexity: the bigger picture. Nature 418(6894), 131 (2002)Sterman, J., Richardson, G., Davidsen, P.: Modelling the estimation of petroleum resources in the United States. Technol. Forecast. Soc. Chang. 33(3), 219–249 (1998)Vlachos, D., Georgiadis, P., Iakovou, E.: A system dynamics model for dynamic capacity planning of remanufacturing in closed-loop supply chains. Comput. Oper. Res. 34(2), 367–394 (2007)Campuzano-Bolarín, F., Mula, J., Peidro, D.: An extension to fuzzy estimations and system dynamics for improving supply chains. Int. J. Prod. Res. 51(10), 3156–3166 (2013)Barton, P., Bryan, S., Robinson, S.: Modelling in the economic evaluation of health care: selecting the appropriate approach. J. Heal. Serv. Res. Policy 9(2), 110–118 (2004)Eldabi, T., Paul, R.J., Young, T.: Simulation modelling in healthcare: reviewing legacies and investigating futures. J. Oper. Res. Soc. Spec. Issue Oper. Res. Heal. 58(2), 262–270 (2007)Andres, B., Poler, R., Camarinha-Matos, L.M., Afsarmanesh, H.: A simulation approach to assess partners selected for a collaborative network. Int. J. Simul. Model. 16(3), 399–411 (2017)Gohari, A., Mirchi, A., Madan, K.: System dynamics evaluation of climate change adaptation strategies for water resources management in central Iran. Water Resour. Manag. 31(5), 1413–1434 (2007)Fishera, D., Norvell, J., Sonka, S., Nelson, M.J.: Understanding technology adoption through system dynamics modeling: implications for agribusiness management. Int. Food Agribus. Manag. Rev. 3, 281–296 (2000)Lyneisa, J.M.: System dynamics for market forecasting and structural analysis. Syst. Dyn. Rev. 16(1), 3–25 (2000)Borshchev, A., Filippov, A.: From system dynamics and discrete event to practical agent based modeling: reasons, techniques, tools. In: The 22nd International Conference of the System Dynamics Society (2004)Ferrada, F.: C-EMO: A Modeling Framework for Collaborative Network Emotions Doctoral dissertation, Nova University of Lisbon, Portugal (2017). https://run.unl.pt/handle/10362/26857Scherer, K.R.: Emotions are emergent processes: they require a dynamic computational architecture. Rev. Philos. Trans. R. Soc. Biol. Sci. 364(1535), 3459–3474 (2009

    Team-taught versus individually taught undergraduate education: A qualitative study of student experiences and preferences

    Get PDF
    Team teaching is becoming more common in undergraduate programmes of study although the relative merits to the more traditional individually taught courses have not been determined for best practice. For this study, 15 final year undergraduate students were interviewed to gain insight into their learning experiences. A thematic analysis of the interview data identified the perceived advantages and disadvantages of each mode of teaching. The advantages of individually taught courses included: Consistency of content delivery and advice, Familiarity with the lecturer’s teaching style and better Continuity of the subject content. The disadvantage of individually taught modules included Missing knowledge, compared to a team approach. Advantages of team taught modules included: Greater insight into a topic delivered by multiple team members. Disadvantages included: Content overlap, Conflicting messages relating to assessment, team members not taking Ownership of their roles and responsibilities and a belief that overall Team failure is worse than individual failure to deliver a module well. The results revealed that individually taught modules were generally preferred to team taught modules. A set of best practice recommendations are proposed to address the challenges when delivering team-taught teaching and become more student focused
    corecore