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Abstract
The green technology transfer is complex for construction firms. A solution is to analyze it as a social network since, if I identify the different relationships between the actors in the construction sector, it is possible to test the technology adaptation capacity of these actors. The aim was to test the transfer of green technology between international construction companies that dedicated to building social or accessible housing. For this, two countries with the capacity to transfer green technology (United Kingdom and the United States) and two countries with less technology capacity and with the potential to adapt to these technologies (Brazil and Colombia) identified, then 5 construction firms selected for each country with which an analysis of networks (degree, intensity, proximity, and density) and then simulation carried out. As a result, the technology transfer capacity of Latin America companies to accept and adapt technologies from companies in industrialized countries identified, and it hoped to develop indicators of measurement of the technology transfer that allows a better understanding of the complexity of Social Housing.
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References
Abbasian-Hosseini, S. A., Liu, M., & Hsiang, S. M. (2015). Social network analysis for construction specialty trade interference and work plan reliability. Proceedings of IGLC 23 - 23rd Annual Conference of the International Group for Lean Construction: Global Knowledge - Global Solutions, 2015-January (919), 143–152. Recuperado de http://iglc.net/Papers/Details/1223
Alarcón, D. M., Alarcón, I. M., & Alarcón, L. F. (2013). Social network analysis: A diagnostic tool for information flow in the AEC industry. 21st Annual Conference of the International Group for Lean Construction 2013, IGLC 2013, 196–205. Recuperado de http://iglc.net/Papers/Details/864
Alsema, E. A., Anink, D., Meijer, A., Straub, A., & Donze, G. (2016). Integration of Energy and Material Performance of Buildings: I=E+M. Energy Procedia, 96(October), 517–528. Doi: https://doi.org/10.1016/j.egypro.2016.09.094
Asadi, E., Silva, M. G. Da, Antunes, C. H., Dias, L., & Glicksman, L. (2014). Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application. Energy and Buildings, 81, 444–456. Doi: https://doi.org/10.1016/j.enbuild.2014.06.009
Borgatti, S.P., Everett, M.G., & Johnson, J.C. (2013). Analyzing Social Networks. Sage Publications.
Carlucci, S., Lobaccaro, G., Li, Y., Catto Lucchino, E., & Ramaci, R. (2016). The effect of spatial and temporal randomness of stochastically generated occupancy schedules on the energy performance of a multiresidential building. Energy and Buildings, 127, 279–300. Doi: https://doi.org/10.1016/j.enbuild.2016.05.023
Castillo, T., Alarcón, L. F., & Pellicer, E. (2018). Influence of Organizational Characteristics on Construction Project Performance Using Corporate Social Networks. Journal of Management in Engineering, 34(4). Doi: https://doi.org/10.1061/(ASCE)ME.1943-5479.0000612
Gelesz, A., & Reith, A. (2015). Climate-based performance evaluation of double skin facades by building energy modelling in Central Europe. Energy Procedia, 78, 555–560. Doi: https://doi.org/10.1016/j.egypro.2015.11.735
Huang, I. B., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends. Science of the Total Environment, 409(19), 3578–3594. Doi: https://doi.org/10.1016/j.scitotenv.2011.06.022
Kim, M. J., Oh, M. W., & Kim, J. T. (2013). A method for evaluating the performance of green buildings with a focus on user experience. Energy and Buildings, 66, 203–210. Doi: https://doi.org/10.1016/j.enbuild.2013.07.049
Kontu, K., Rinne, S., Olkkonen, V., Lahdelma, R., & Salminen, P. (2015). Multicriteria evaluation of heating choices for a new sustainable residential area. Energy and Buildings, 93(x), 169–179. Doi: https://doi.org/10.1016/j.enbuild.2015.02.003
Liu, Y., Guo, X., & Hu, F. (2014). Cost-benefit analysis on green building energy efficiency technology application: A case in China. Energy and Buildings, 82, 37–46. Doi: https://doi.org/10.1016/j.enbuild.2014.07.008
Lopes, R. A., Chambel, A., Neves, J., Aelenei, D., & Martins, J. (2016). A Literature Review of Methodologies Used to Assess the Energy Flexibility of Buildings. Energy Procedia, 91, 1053–1058. Doi: https://doi.org/10.1016/j.egypro.2016.06.274
Ma, H., Zhou, W., Lu, X., Ding, Z., & Cao, Y. (2016). Application of Low Cost Active and Passive Energy Saving Technologies in an Ultra-low Energy Consumption Building. Energy Procedia, 88, 807–813. Doi: https://doi.org/10.1016/j.egypro.2016.06.132
Marques, S. B., Bissoli-Dalvi, M., & Alvarez, C. E. de. (2018). Políticas públicas em prol da sustentabilidade na construção civil em municípios brasileiros. urbe. Revista Brasileira de Gestão Urbana, 10(Suppl. 1), 186-196. Epub July 30, 2018. Doi: https://dx.doi.org/10.1590/2175-3369.010.supl1.ao10
McKinsey Global Institute. (2017). Reinventing Construction: A Route to Higher Productivity. McKinsey & Company, (February), 20. Doi: https://doi.org/10.1080/19320248.2010.527275
Moschetti, R., & Brattebø, H. (2016). Sustainable business models for deep energy retrofitting of buildings: state-of-the-art and methodological approach. Energy Procedia, 96(1876), 435–445. Doi: https://doi.org/10.1016/j.egypro.2016.09.174
Niknam, M., & Karshenas, S. (2015). Sustainable Design of Buildings using Semantic BIM and Semantic Web Services. Procedia Engineering, 118, 909–917. Doi: https://doi.org/10.1016/j.proeng.2015.08.530
Panchal, S., Dincer, I., & Agelin-Chaab, M. (2016). Analysis and evaluation of a new renewable energy based integrated system for residential applications. Energy and Buildings, 128, 900–910. https://doi.org/10.1016/j.enbuild.2016.07.038
Park, H., & Han, S. H. (2012). Impact of inter-firm collaboration networks in international construction projects: A longitudinal study. In Construction Research Congress 2012: Construction Challenges in a Flat World (pp. 1460–1470). Construction Management and Information Laboratory, Dept. of Civil and Environmental Engineering, Yonsei University, Seoul, South Korea. Doi: https://doi.org/10.1061/9780784412329.147
Pisello, A. L., Castaldo, V. L., Taylor, J. E., & Cotana, F. (2016). The impact of natural ventilation on building energy requirement at inter-building scale. Energy and Buildings, 127, 870–883. Doi: https://doi.org/10.1016/j.enbuild.2016.06.023
Salcido, J. C., Abdul, A., & Issa, R. R. A. (2016). From simulation to monitoring: Evaluating the potential of mixed-mode ventilation (MMV) systems for integrating natural ventilation in office buildings through a comprehensive literature review. Energy & Buildings, 127, 1008–1018. Doi: https://doi.org/10.1016/j.enbuild.2016.06.054
Sartori, I., Napolitano, A., & Voss, K. (2012). Net zero energy buildings: A consistent definition framework. Energy and Buildings, 48, 220–232. Doi: https://doi.org/10.1016/j.enbuild.2012.01.032
Zabalza Bribián, I., Valero Capilla, A., & Aranda Usón, A. (2011). Life cycle assessment of building materials: Comparative analysis of energy and environmental impacts and evaluation of the eco-efficiency improvement potential. Building and Environment, 46(5), 1133–1140. Doi: https://doi.org/10.1016/j.buildenv.2010.12.002
Zucker, G., Judex, F., Blöchle, M., Köstl, M., Widl, E., Hauer, S., … Zeilinger, J. (2016). A new method for optimizing operation of large neighborhoods of buildings using thermal simulation. Energy and Buildings, 125, 153–160. Doi: https://doi.org/10.1016/j.enbuild.2016.04.081