Finding Differences among Construction Companies Management Practices and Their Relation to Project Performance

[EN] The performance of construction companies is linked to the performance of their projects because their financial success and the satisfaction of their clients depends on it. However, most studies of construction companies' performance consider mainly the corporate aspects but not the performance they achieve in their projects as a result of their management practices. A key issue is determining the differences among management practices used by construction companies that provide them with a competitive advantage, which was the purpose of this study. To achieve this goal, nine construction companies were selected for participation in this collaborative benchmarking study, and the management practices that differentiate the investigated construction companies were determined. The results highlight the relevance of the management of information and communication and the importance of lean management practices as the tools for analysis and planning or to improve processes. Construction companies' managers should consider these differentiating elements as a path to achieve competitive advantage.Castillo, T.; Alarcón, LF.; Pellicer, E. (2018). Finding Differences among Construction Companies Management Practices and Their Relation to Project Performance. Journal of Management in Engineering. 34(3):1-13. doi:10.1061/(ASCE)ME.1943-5479.0000606S11334

Understanding Interactions between Design Team Members of Construction Projects Using Social Network Analysis

[EN] Social network analysis (SNA) has not been used to study design project teams in which the full interactions have become more complex (formal and informal) because the team members are from different companies and there is no colocation. This work proposes a method to understand the interactions in the design teams of construction projects using SNA metrics and the sociograms generated within temporary organizations. This study includes three stages: (1) a literature review of the dimensions of interactions within work teams and the application of SNA to the architecture, engineering, and construction (AEC) industry; (2) a proposal of an interaction network method for construction project design teams; and (3) an analysis of a pilot project. Interaction networks were defined in two categories: general interactions and commitment management. For each network, metric indicators were defined for the analysis. The pilot project showed high levels of consistency among team responses. The proposed method allows an analysis of the entire work team and of each individual team member. The method also makes it possible to analyze the work team from a global perspective by carrying out a joint analysis of two or more networks.The authors would like to acknowledge the help and support provided by GEPUC and GEPRO SpA., which provided access to data collection for this study. In addition, the authors acknowledge financial support from FONDECYT (1181648) and the Pontificia Universidad Catolica de Chile. Rodrigo Herrera acknowledges financial support for Ph.D. studies from VRI of PUC and CONICYT-PCHA/National Doctorate/2018-21180884.Herrera, RF.; Mourgues, C.; Alarcón, LF.; Pellicer, E. (2020). Understanding Interactions between Design Team Members of Construction Projects Using Social Network Analysis. Journal of Construction Engineering and Management. 146(6):1-13. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001841S1131466Alarcón D. M. I. M. Alarcón and L. F. Alarcón. 2013. “Social network analysis: A diagnostic tool for information flow in the AEC industry.” In Proc. 21st Annual Conf. of the Int. Group for Lean Construction 2013 947–956. Fortaleza Brazil: International Group for Lean Construction.Alarcón, L. F., Ashley, D. B., de Hanily, A. S., Molenaar, K. R., & Ungo, R. (2011). Risk Planning and Management for the Panama Canal Expansion Program. Journal of Construction Engineering and Management, 137(10), 762-771. doi:10.1061/(asce)co.1943-7862.0000317Al Hattab, M., & Hamzeh, F. (2015). Using social network theory and simulation to compare traditional versus BIM–lean practice for design error management. Automation in Construction, 52, 59-69. doi:10.1016/j.autcon.2015.02.014Austin, R. B., Pishdad-Bozorgi, P., & de la Garza, J. M. (2016). Identifying and Prioritizing Best Practices to Achieve Flash Track Projects. Journal of Construction Engineering and Management, 142(2), 04015077. doi:10.1061/(asce)co.1943-7862.0001061Baiden, B. K., Price, A. D. F., & Dainty, A. R. J. (2006). The extent of team integration within construction projects. International Journal of Project Management, 24(1), 13-23. doi:10.1016/j.ijproman.2005.05.001Cash, P., Dekoninck, E. A., & Ahmed-Kristensen, S. (2017). Supporting the development of shared understanding in distributed design teams. Journal of Engineering Design, 28(3), 147-170. doi:10.1080/09544828.2016.1274719Castillo, 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), 04018013. doi:10.1061/(asce)me.1943-5479.0000612Castillo, T., Alarcón, L. F., & Salvatierra, J. L. (2018). Effects of Last Planner System Practices on Social Networks and the Performance of Construction Projects. Journal of Construction Engineering and Management, 144(3), 04017120. doi:10.1061/(asce)co.1943-7862.0001443Craft, R. C., & Leake, C. (2002). The Pareto principle in organizational decision making. Management Decision, 40(8), 729-733. doi:10.1108/00251740210437699Dainty, A. R. J., Briscoe, G. H., & Millett, S. J. (2001). Subcontractor perspectives on supply chain alliances. Construction Management and Economics, 19(8), 841-848. doi:10.1080/01446190110089727Dave B. S. Kubler K. Främling and L. Koskela. 2014. “Addressing information flow in lean production management and control in construction.” In Proc. 22nd Annual Conf. of the Int. Group for Lean Construction 581–592. Oslo Norway: International Group for Lean Construction.Flores J. J. C. Ruiz D. Alarcón L. F. Alarcón J. L. Salvatierra and I. Alarcón. 2014. “Improving connectivity and information flow in lean organizations—Towards an evidence-based methodology.” In Proc. 22nd Annual Conf. of the Int. Group for Lean Construction 2014 1109–1120. Oslo Norway: International Group for Lean Construction.Herrera R. F. C. Mourgues and L. F. Alarcón. 2018. “Assessment of lean practices performance and social networks in Chilean airport projects.” In Proc. 26th Annual Conf. of the Int. Group for Lean Construction 2018 603–613. Chennai India: International Group for Lean Construction.Hickethier G. I. D. Tommelein and B. Lostuvali. 2013. “Social network analysis of information flow in an IPD-project design organization.” In Proc. 21st Annual Conf. of the Int. Group for Lean Construction 2013 319–328. Fortaleza Brazil: International Group for Lean Construction.Hoppe, B., & Reinelt, C. (2010). Social network analysis and the evaluation of leadership networks. The Leadership Quarterly, 21(4), 600-619. doi:10.1016/j.leaqua.2010.06.004Karp, N. C., Hauer, K. E., & Sheu, L. (2019). Trusted to Learn: a Qualitative Study of Clerkship Students’ Perspectives on Trust in the Clinical Learning Environment. Journal of General Internal Medicine, 34(5), 662-668. doi:10.1007/s11606-019-04883-1Kereri, J. O., & Harper, C. M. (2019). Social Networks and Construction Teams: Literature Review. Journal of Construction Engineering and Management, 145(4), 03119001. doi:10.1061/(asce)co.1943-7862.0001628Kleinsmann, M., Deken, F., Dong, A., & Lauche, K. (2012). Development of design collaboration skills. Journal of Engineering Design, 23(7), 485-506. doi:10.1080/09544828.2011.619499Knotten, V., Lædre, O., & Hansen, G. K. (2017). Building design management – key success factors. Architectural Engineering and Design Management, 13(6), 479-493. doi:10.1080/17452007.2017.1345718Long D. and P. Arroyo. 2018. “Language moods and improving project performance.” In Proc. 26th Annual Conf. of the Int. Group for Lean Construction 2018 495–504. Chennai India: International Group for Lean Construction.Love, P. E. D., Irani, Z., Cheng, E., & LI, H. (2002). A model for supporting inter-organizational relations in the supply chain. Engineering Construction and Architectural Management, 9(1), 2-15. doi:10.1046/j.1365-232x.2002.00225.xMedina-Mora R. T. Winograd R. Flores and F. Flores. 1992. “The action workflow approach to workflow management technology.” In Proc. Computer Supported Cooperative Work 92 281–288. New York: Association for Computing Machinery.Ng, S. T., & Tang, Z. (2010). Labour-intensive construction sub-contractors: Their critical success factors. International Journal of Project Management, 28(7), 732-740. doi:10.1016/j.ijproman.2009.11.005Oluwatayo, A. A., & Amole, D. (2013). Ownership, structure, and performance of architectural firms. Frontiers of Architectural Research, 2(1), 94-106. doi:10.1016/j.foar.2012.12.001Oviedo-Haito, R. J., Jiménez, J., Cardoso, F. F., & Pellicer, E. (2014). Survival Factors for Subcontractors in Economic Downturns. Journal of Construction Engineering and Management, 140(3), 04013056. doi:10.1061/(asce)co.1943-7862.0000811Paris, C. R., Salas, E., & Cannon-Bowers, J. A. (2000). Teamwork in multi-person systems: a review and analysis. Ergonomics, 43(8), 1052-1075. doi:10.1080/00140130050084879Phelps A. F. 2012. “Behavioral factors influencing lean information flow in complex projects.” In Proc. 20th Annual Conf. of the Int. Group for Lean Construction 2012. San Diego: International Group for Lean Construction.Priven V. and R. Sacks. 2013. “Social network development in Last Planner System implementations.” In Proc. 21st Annual Conf. of the Int. Group for Lean Construction 2013 474–485. Fortaleza Brazil: International Group for Lean Construction.Pryke, S. (2012). Social Network Analysis in Construction. doi:10.1002/9781118443132Rahmawati Y. C. Utomo N. Anwar N. P. Negoro and C. B. Nurcahyo. 2014. “A framework of knowledge management for successful group decision in design process.” In Proc. 2014 IEEE Conf. on Open Systems 60–65. Subang Malaysia: IEEE.Rojas, M. J., Herrera, R. F., Mourgues, C., Ponz-Tienda, J. L., Alarcón, L. F., & Pellicer, E. (2019). BIM Use Assessment (BUA) Tool for Characterizing the Application Levels of BIM Uses for the Planning and Design of Construction Projects. Advances in Civil Engineering, 2019, 1-9. doi:10.1155/2019/9094254Schöttle A. S. Haghsheno and F. Gehbauer. 2014. “Defining cooperation and collaboration in the context of lean construction.” In Proc. 22nd Annual Conf. of the Int. Group for Lean Construction 1269–1280. Oslo Norway: International Group for Lean Construction.Schröpfer, V. L. M., Tah, J., & Kurul, E. (2017). Mapping the knowledge flow in sustainable construction project teams using social network analysis. Engineering, Construction and Architectural Management, 24(2), 229-259. doi:10.1108/ecam-08-2015-0124Scott, J. (2017). Social Network Analysis. doi:10.4135/9781529716597Searle, J. R. (1969). Speech Acts. doi:10.1017/cbo9781139173438Segarra L. R. F. Herrera L. F. Alarcón and E. Pellicer. 2017. “Knowledge management and information flow through social networks analysis in Chilean architecture firms.” In Proc. 25th Annual Conf. of the Int. Group for Lean Construction 413–420. Heraklion Greece: International Group for Lean Construction.Sonnenwald, D. H. (1996). Communication roles that support collaboration during the design process. Design Studies, 17(3), 277-301. doi:10.1016/0142-694x(96)00002-6Svalestuen F. K. Frøystad F. Drevland S. Ahmad J. Lohne and O. Lædre. 2015. “Key elements to an effective building design team.” In Proc. Int. Conf. on Project Management 838–843. Sapporo Japan: Elsevier.Sydow, J., & Braun, T. (2018). Projects as temporary organizations: An agenda for further theorizing the interorganizational dimension. International Journal of Project Management, 36(1), 4-11. doi:10.1016/j.ijproman.2017.04.012Turner, J. R., & Müller, R. (2003). On the nature of the project as a temporary organization. International Journal of Project Management, 21(1), 1-8. doi:10.1016/s0263-7863(02)00020-0Valentine, M. A., Nembhard, I. M., & Edmondson, A. C. (2015). Measuring Teamwork in Health Care Settings. Medical Care, 53(4), e16-e30. doi:10.1097/mlr.0b013e31827feef6Wesz, J. G. B., Formoso, C. T., & Tzortzopoulos, P. (2018). Planning and controlling design in engineered-to-order prefabricated building systems. Engineering, Construction and Architectural Management, 25(2), 134-152. doi:10.1108/ecam-02-2016-0045Wong, P. S. P., Demertjis, M., Hardie, M., & Lo, C. yiu. (2014). The effect of unlearning on organisational learning behaviour and performance in construction contracting organisations. International Journal of Project Organisation and Management, 6(3), 197. doi:10.1504/ijpom.2014.065256Zhang, L., & Ashuri, B. (2018). BIM log mining: Discovering social networks. Automation in Construction, 91, 31-43. doi:10.1016/j.autcon.2018.03.00

Analyzing the Association between Lean Design Management Practices and BIM Uses in the Design of Construction Projects

[EN] There is a beneficial effect when integrating Building Information Modeling (BIM) with lean practices to identify and reduce waste in the construction industry. According to experts, it is possible to improve the design process through waste reduction by implementing lean practices and BIM. An unexplored perspective on these synergies concerns the relationship between the specific uses of BIM and lean practices. Therefore, this study analyzed the relationships between Lean Design Management (LDM) practices and BIM uses in the planning and design phases of the infrastructure lifecycle. To achieve this objective, the research was organized into three stages: (1) the explanation of LDM practices and BIM uses; (2) the characterization of sample projects and data collection strategies; and (3) data exploration, including reliability analysis, descriptive statistics, association analysis, and a causal analysis of LDM practices and BIM uses. The analysis of the relationship between LDM practices and BIM uses generated empirical evidence of the implementation of BIM uses and lean management practices at the design phase. LDM practices from the categories planning and control and problem-solving and decision-making were more related to BIM uses than LDM practices from the category stakeholder management. Additionally, it was concluded that if a project applies a higher proportion of BIM uses, it will tend to apply a higher proportion of LDM practices; however, this relationship is not as clear in the other way around.The authors acknowledge the help and support provided by GEPUC, which provided access to data collection for this study. In addition, the authors acknowledge financial support from FONDECYT (1181648) and the Pontificia Universidad Católica de Chile. Rodrigo Herrera acknowledges financial support for Ph.D. studies from Vicerrectoría de Investigación (VRI) of Pontificia Universidad Católica de Chile (PUC) and CONICYT-PCHA/National Doctorate/2018 -21180884.Herrera, RF.; Mourgues, C.; Alarcón, LF.; Pellicer, E. (2021). Analyzing the Association between Lean Design Management Practices and BIM Uses in the Design of Construction Projects. Journal of Construction Engineering and Management. 147(4):1-11. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002014S1111474Akoglu, H. (2018). User’s guide to correlation coefficients. Turkish Journal of Emergency Medicine, 18(3), 91-93. doi:10.1016/j.tjem.2018.08.001Al Hattab, M., & Hamzeh, F. (2015). Using social network theory and simulation to compare traditional versus BIM–lean practice for design error management. Automation in Construction, 52, 59-69. doi:10.1016/j.autcon.2015.02.014Arayici, Y., Coates, P., Koskela, L., Kagioglou, M., Usher, C., & O’Reilly, K. (2011). Technology adoption in the BIM implementation for lean architectural practice. Automation in Construction, 20(2), 189-195. doi:10.1016/j.autcon.2010.09.016Arroyo, P., Fuenzalida, C., Albert, A., & Hallowell, M. R. (2016). Collaborating in decision making of sustainable building design: An experimental study comparing CBA and WRC methods. Energy and Buildings, 128, 132-142. doi:10.1016/j.enbuild.2016.05.079Bloom, N., & Van Reenen, J. (2007). Measuring and Explaining Management Practices Across Firms and Countries. The Quarterly Journal of Economics, 122(4), 1351-1408. doi:10.1162/qjec.2007.122.4.1351Bloom, N., & Van Reenen, J. (2010). New Approaches to Surveying Organizations. American Economic Review, 100(2), 105-109. doi:10.1257/aer.100.2.105Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2008). BIM Handbook. doi:10.1002/9780470261309El. Reifi, M. H., & Emmitt, S. (2013). Perceptions of lean design management. Architectural Engineering and Design Management, 9(3), 195-208. doi:10.1080/17452007.2013.802979Fakhimi A. H. J. Majrouhi Sardroud and S. Azhar. 2016. “How can Lean IPD and BIM work together?” In Proc. 33rd Int. Symp. on Automation and Robotics in Construction (ISARC) 1–8. Auburn AL: International Symposium on Automation and Robotics in Construction.Formoso C. T. P. Tzotzopoulos M. S. Jobim and R. Liedtke. 1998. “Developing a protocol for managing the design process in the building industry.” In Proc. 6th Annual Conf. of the Int. Group for Lean Construction. Guarujá Brazil: International Group for Lean Construction.Gambatese, J. A., Pestana, C., & Lee, H. W. (2017). Alignment between Lean Principles and Practices and Worker Safety Behavior. Journal of Construction Engineering and Management, 143(1), 04016083. doi:10.1061/(asce)co.1943-7862.0001209Gerber D. J. B. Becerik-Gerber and A. Kunz. 2010. “Building information modeling and Lean Construction: Technology methodology and advances from practices.” In Proc. 18th Annual Conf. of the Int. Group for Lean Construction 1–11. Haifa Israel: International Group for Lean Construction.Gu, N., & London, K. (2010). Understanding and facilitating BIM adoption in the AEC industry. Automation in Construction, 19(8), 988-999. doi:10.1016/j.autcon.2010.09.002Koskela L. 2000. “An exploration towards a production theory and its application to construction.” Ph.D. thesis Dept. of Technology Technical Research Centre of Finland.Koskela L. G. Ballard and V. P. Tanhuanpää. 1997. “Towards lean design management.” In Proc. 5th Annual Conf. of the Int. Group for Lean Construction 1997 1–13. Gold Coast Australia: International Group for Lean Construction.Liu, Y., van Nederveen, S., & Hertogh, M. (2017). Understanding effects of BIM on collaborative design and construction: An empirical study in China. International Journal of Project Management, 35(4), 686-698. doi:10.1016/j.ijproman.2016.06.007Matta G. R. F. Herrera C. Baladrón Z. Giménez and L. F. Alarcón. 2018. “Using BIM-based sheets as a visual management tool for on-site instructions: A case study.” In Vol. 1 of Proc. 26th Annual Conf. of the Int. Group for Lean Construction: Evolving Lean Construction Towards Mature Production Management Across Cultures and Frontiers 144–154.Mesa, H. A., Molenaar, K. R., & Alarcón, L. F. (2016). Exploring performance of the integrated project delivery process on complex building projects. International Journal of Project Management, 34(7), 1089-1101. doi:10.1016/j.ijproman.2016.05.007Mok, K. Y., Shen, G. Q., & Yang, J. (2015). Stakeholder management studies in mega construction projects: A review and future directions. International Journal of Project Management, 33(2), 446-457. doi:10.1016/j.ijproman.2014.08.007Molwus, J. J., Erdogan, B., & Ogunlana, S. (2017). Using structural equation modelling (SEM) to understand the relationships among critical success factors (CSFs) for stakeholder management in construction. Engineering, Construction and Architectural Management, 24(3), 426-450. doi:10.1108/ecam-10-2015-0161Munthe-Kaas T. S. H. Hjelmbrekke and J. Lohne. 2015. “Lean design versus traditional design approach.” In Proc. 23th Annual Conf. Int. Group for Lean Construction 578–588. Perth Australia: International Group for Lean Construction.Nascimento, D., Caiado, R., Tortorella, G., Ivson, P., & Meiriño, M. (2018). Digital Obeya Room: exploring the synergies between BIM and lean for visual construction management. Innovative Infrastructure Solutions, 3(1). doi:10.1007/s41062-017-0125-0Olatunji, O. A. (2011). Modelling the costs of corporate implementation of building information modelling. Journal of Financial Management of Property and Construction, 16(3), 211-231. doi:10.1108/13664381111179206Porwal, A., & Hewage, K. N. (2013). Building Information Modeling (BIM) partnering framework for public construction projects. Automation in Construction, 31, 204-214. doi:10.1016/j.autcon.2012.12.004Ragin, C. C. (2006). Set Relations in Social Research: Evaluating Their Consistency and Coverage. Political Analysis, 14(3), 291-310. doi:10.1093/pan/mpj019Sacks R. R. Barak B. Belaciano and U. Gurevich. 2011. “Field tests of the KanBIM lean production management system.” In Proc. 19th Annual Conf. of the Int. Group for Lean Construction 1–12. Lima Perú: International Group for Lean Construction.Sacks, R., Koskela, L., Dave, B. A., & Owen, R. (2010). Interaction of Lean and Building Information Modeling in Construction. Journal of Construction Engineering and Management, 136(9), 968-980. doi:10.1061/(asce)co.1943-7862.0000203Schimanski C. P. G. P. Monizza C. Marcher and D. T. Matt. 2019. “Conceptual foundations for a new lean BIM-based production system in construction.” In Proc. 27th Annual Conf. of the Int. Group for Lean Construction 877–888. Dublin Ireland: International Group for Lean Construction.Schneider, C. Q., & Wagemann, C. (2012). Set-Theoretic Methods for the Social Sciences. doi:10.1017/cbo9781139004244Succar B. 2016. “211in model uses list.” Accessed March 1 2020. https://bimexcellence.org/wp-content/uploads/211in-Model-Uses-Table.pdf.Succar, B., Sher, W., & Williams, A. (2012). Measuring BIM performance: Five metrics. Architectural Engineering and Design Management, 8(2), 120-142. doi:10.1080/17452007.2012.659506Tsai, M.-H., Mom, M., & Hsieh, S.-H. (2014). Developing critical success factors for the assessment of BIM technology adoption: part I. Methodology and survey. Journal of the Chinese Institute of Engineers, 37(7), 845-858. doi:10.1080/02533839.2014.88881

Comparing Team Interactions in Traditional and BIM-Lean Design Management

[EN] There is qualitative evidence showing that design teams that use BIM-lean management have a higher level of interaction than design teams that do not use this management approach. However, there is no quantitative empirical evidence of this higher level of interaction. Therefore, the objective of this paper is to present quantitative empirical evidence of the differences among the various types of interactions of a design team. Two case studies were analyzed, and their design management was assessed from a lean BIM perspective while their team interactions were assessed using social network analysis (SNA). To achieve the aim of this paper, four steps were performed: (1) case study selection; (2) description of the design management of the projects from the lean design management and BIM perspectives; (3) assessment of design team interaction; and (4) comparison using SNA. The results show that the project that applied BIM-lean management exhibited higher levels of interactions among its design team members than the traditional team; transparent, orderly, and standardized information flows; a collaborative, trusting, and learning environment; and commitment management. None of these interaction elements were visible in the project that did not apply BIM-lean management. It is suggested that an analysis be performed on a representative sample of projects in the future so that conclusive statistical inferences could be made.This research was funded by Fondecyt Regular, grant number 1210769 and ANID, grant number CONICYT-PCHA/National Doctorate/2018-21180884. The APC was paid by the Pontificia Universidad Católica de Valparaíso.Herrera, RF.; Mourgues, C.; Alarcón, LF.; Pellicer, E. (2021). Comparing Team Interactions in Traditional and BIM-Lean Design Management. Buildings. 11(10):1-25. https://doi.org/10.3390/buildings11100447S125111

Modelación multidimensional: un mecanismo de mejora para la gestión de proyectos de construcción

Multidimensional modeling is the digital, visual, automated representation of the different parts of a project, using commercially available software or a single computational tool. A dimension is any variable that a professional needs to know and analyze in order to manage a construction project, which can be used during the entire life cycle of the project, from design to operation. The modeled dimensions were surface area, space, time, building sequence and execution strategy, cubage and quantity, cost, safety, and history of activities. Performance indicators were used to evaluate the use of the proposed modeling method as a tool to improve project management. The method of trial and error using three cases (construction projects in Chile) was used to validate and to evaluate that method. The use of multidimensional modeling made the processes of planning, control, and coordination of the studied project cases easier and more transparent. It resulted in higher availability, consistency, accessibility, reliability of information, reduction of uncertainty for professionals and workers in general in terms of project scope and performance, faster and better decision-making, and better understanding and communication among project participants.La Modelación Multidimensional es la representación digital, visual y automatizada de las diversas dimensiones de un proyecto, utilizando software comercialmente disponibles o una herramienta computacional única. Una “dimensión” es cualquier variable que el profesional necesita conocer y analizar para gestionar un proyecto de construcción, y puede ser utilizada durante todo el ciclo de vida del proyecto, desde el diseño hasta la operación. Las dimensiones modeladas fueron superficie, espacio, tiempo, secuencia constructiva y estrategia de ejecución, cubicación y cantidad, costo, seguridad, e historial de desempeño de actividades. Se utilizaron indicadores de desempeño para evaluar el uso de la modelación propuesta como un mecanismo de mejora en la gestión de proyectos. La validación y evaluación de la modelación multidimensional se llevó a cabo con el método prueba-error utilizando tres casos de estudio (proyectos de edificación chilenos). El uso de la modelación multidimensional simplificó e hizo más transparente los procesos de planificación, control y coordinación de los proyectos en estudio durante su ejecución. Esto se reflejó en el incremento de la disponibilidad, consistencia, facilidad de acceso y confiabilidad de la información del proyecto, en la reducción de la incertidumbre que tuvieron los profesionales y trabajadores en general respecto al alcance y desempeño del proyecto, en el aumento de la velocidad y calidad del proceso de toma de decisiones, y en la mejora del entendimiento y la comunicación entre los participantes del proyecto.La Modelación Multidimensional es la representación digital, visual y automatizada de las diversas dimensiones de un proyecto, utilizando software comercialmente disponibles o una herramienta computacional única. Una “dimensión” es cualquier variable que el profesional necesita conocer y analizar para gestionar un proyecto de construcción, y puede ser utilizada durante todo el ciclo de vida del proyecto, desde el diseño hasta la operación. Las dimensiones modeladas fueron superficie, espacio, tiempo, secuencia constructiva y estrategia de ejecución, cubicación y cantidad, costo, seguridad, e historial de desempeño de actividades. Se utilizaron indicadores de desempeño para evaluar el uso de la modelación propuesta como un mecanismo de mejora en la gestión de proyectos. La validación y evaluación de la modelación multidimensional se llevó a cabo con el método prueba-error utilizando tres casos de estudio (proyectos de edificación chilenos). El uso de la modelación multidimensional simplificó e hizo más transparente los procesos de planificación, control y coordinación de los proyectos en estudio durante su ejecución. Esto se reflejó en el incremento de la disponibilidad, consistencia, facilidad de acceso y confiabilidad de la información del proyecto, en la reducción de la incertidumbre que tuvieron los profesionales y trabajadores en general respecto al alcance y desempeño del proyecto, en el aumento de la velocidad y calidad del proceso de toma de decisiones, y en la mejora del entendimiento y la comunicación entre los participantes del proyecto

BIM Use Assessment (BUA) Tool for Characterizing the Application Levels of BIM Uses for the Planning and Design of Construction Projects

[EN] The evaluation of BIM capabilities and repeatability enables a company or project to identify its current status and how to improve continuously; this evaluation can be performed with BIM maturity models. However, these maturity models can measure the BIM state but not specifically the application of BIM uses. Likewise, in interorganizational project teams with a diversity of factors from various companies, it is possible to evaluate the capacity at a specified time with specified factors, but it is not possible to evaluate the repeatability unless the client always works with the same project teams. Therefore, despite the existence of various BIM uses in the literature, there is no instrument to evaluate the level of implementation of them in construction projects. This research proposes a BIM Use Assessment (BUA) tool for characterizing the levels of application of the BIM uses in the planning and design phases of building projects. The research methodology was organized into three stages: (1) identification, selection, and definition of BIM uses; (2) proposal of the BUA tool for characterizing the level of BIM use application; and (3) validation of the BUA tool. The tool was validated using 25 construction projects, where high reliability and concordance were observed; hence, the BUA tool complies with the consistency and concordance analysis for assessing uses in the design and planning phases of construction projects. The assessment will enable self-diagnosis, stakeholder qualification/selection, and industry benchmarking.This work was supported by FONDECYT (1181648 to Alarcón L. F. and Mourgues C.) and CONICYT, Chile (PCHA/National Doctorate/2018-21180884 to Herrera R. F.).Rojas, MJ.; Herrera, RF.; Mourgues, C.; Ponz-Tienda, JL.; Alarcón, LF.; Pellicer, E. (2019). BIM Use Assessment (BUA) Tool for Characterizing the Application Levels of BIM Uses for the Planning and Design of Construction Projects. Advances in Civil Engineering. 2019:1-9. https://doi.org/10.1155/2019/9094254S192019Azhar, S. (2011). Building Information Modeling (BIM): Trends, Benefits, Risks, and Challenges for the AEC Industry. Leadership and Management in Engineering, 11(3), 241-252. doi:10.1061/(asce)lm.1943-5630.0000127Succar, B., Sher, W., & Williams, A. (2012). Measuring BIM performance: Five metrics. Architectural Engineering and Design Management, 8(2), 120-142. doi:10.1080/17452007.2012.659506Sydow, J., & Braun, T. (2018). Projects as temporary organizations: An agenda for further theorizing the interorganizational dimension. International Journal of Project Management, 36(1), 4-11. doi:10.1016/j.ijproman.2017.04.012McHugh, M. L. (2012). Interrater reliability: the kappa statistic. Biochemia Medica, 276-282. doi:10.11613/bm.2012.03

Value Analysis Model to Support the Building Design Process

[EN] The architecture, engineering, and construction industry requires methods that link the capture of customer requirements with the continuous measurement of the value generated and the identification of value losses in the design process. A value analysis model (VAM) is proposed to measure the value creation expected by customers and to identify value losses through indexes. As points of reference, the model takes the Kano model and target costing, which is used in the building project design process. The VAM was developed under the design science research methodology, which focuses on solving practical problems by producing outputs by iteration. The resulting VAM allowed the measurement and analysis of value through desired, potential, and generated value indexes, value loss identification, and percentages of value fulfillment concerning the design stage. The VAM permits the comparison of different projects, visualization of the evolution of value generation, and identification of value losses to be eradicated. The VAM encourages constant feedback and has potential to deliver higher value, as it enables the determination of parameters that add value for different stakeholders and informs designers where to direct resources and efforts to enhance vital variables and not trivial variablesThis research was funded by CONICYT grant number PCHA/National Doctorate/2016-21160571 for the postgraduate studies of Zulay Giménez and by FONDECYT (1181648).Giménez, Z.; Mourgues, C.; Alarcón, LF.; Mesa, H.; Pellicer, E. (2020). Value Analysis Model to Support the Building Design Process. Sustainability. 12(10):1-24. https://doi.org/10.3390/su12104224S1241210Gunby, M., Damnjanovic, I., Anderson, S., Joyce, J., & Nuccio, J. (2013). Identifying, Communicating, and Responding to Project Value Interests. Journal of Management in Engineering, 29(1), 50-59. doi:10.1061/(asce)me.1943-5479.0000116Chaos Report. Project Smart UK. United Kingdomhttps://www.projectsmart.co.uk/white-papers/chaos-report.pdfDíaz, H., Alarcón, L. F., Mourgues, C., & García, S. (2017). Multidisciplinary Design Optimization through process integration in the AEC industry: Strategies and challenges. Automation in Construction, 73, 102-119. doi:10.1016/j.autcon.2016.09.007Bustos Chocomeli, Ó. H. (s. f.). Factores latentes de la desviación de presupuestos en proyectos de arquitectura. Un análisis empírico. doi:10.4995/thesis/10251/48558Knotten, V., Svalestuen, F., Hansen, G. K., & Lædre, O. (2015). Design Management in the Building Process - A Review of Current Literature. Procedia Economics and Finance, 21, 120-127. doi:10.1016/s2212-5671(15)00158-6Kamara, J. M., Anumba, C. J., & Evbuomwan, N. F. O. (2000). Process model for client requirements processing in construction. Business Process Management Journal, 6(3), 251-279. doi:10.1108/14637150010325462Kumar, V., & Whitney, P. (2007). Daily life, not markets: customer-centered design. Journal of Business Strategy, 28(4), 46-58. doi:10.1108/02756660710760944Love, P. E. D., Lopez, R., & Edwards, D. J. (2013). Reviewing the past to learn in the future: making sense of design errors and failures in construction. Structure and Infrastructure Engineering, 9(7), 675-688. doi:10.1080/15732479.2011.605369Holmström, J., Ketokivi, M., & Hameri, A.-P. (2009). Bridging Practice and Theory: A Design Science Approach. Decision Sciences, 40(1), 65-87. doi:10.1111/j.1540-5915.2008.00221.xPeffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems, 24(3), 45-77. doi:10.2753/mis0742-1222240302Huang, J. (2017). Application of Kano Model in Requirements Analysis of Y Company’s Consulting Project. American Journal of Industrial and Business Management, 07(07), 910-918. doi:10.4236/ajibm.2017.77064Rachwan, R., Abotaleb, I., & Elgazouli, M. (2016). The Influence of Value Engineering and Sustainability Considerations on the Project Value. Procedia Environmental Sciences, 34, 431-438. doi:10.1016/j.proenv.2016.04.038Eskerod, P., & Ang, K. (2017). Stakeholder Value Constructs in Megaprojects: A Long-Term Assessment Case Study. Project Management Journal, 48(6), 60-75. doi:10.1177/875697281704800606Bolar, A. A., Tesfamariam, S., & Sadiq, R. (2017). Framework for prioritizing infrastructure user expectations using Quality Function Deployment (QFD). International Journal of Sustainable Built Environment, 6(1), 16-29. doi:10.1016/j.ijsbe.2017.02.002Gallarza, M. G., Arteaga-Moreno, F., Servera-Francés, D., & Fayos-Gardó, T. (2016). Participar como voluntario en eventos especiales: comparación entre el valor esperado y percibido. Innovar, 26(59), 47-60. doi:10.15446/innovar.v26n59.54322Kowaltowski, D. C. C. K., & Granja, A. D. (2011). The concept of desired value as a stimulus for change in social housing in Brazil. Habitat International, 35(3), 435-446. doi:10.1016/j.habitatint.2010.12.002Tucker, J. R., Pearce, A. R., Bruce, R. D., McCoy, A. P., & Mills, T. H. (2012). The perceived value of green professional credentials to credential holders in the US building design and construction community. Construction Management and Economics, 30(11), 963-979. doi:10.1080/01446193.2012.728710Lee, B. D., & Paredis, C. J. J. (2014). A Conceptual Framework for Value-driven Design and Systems Engineering. Procedia CIRP, 21, 10-17. doi:10.1016/j.procir.2014.06.147Kamara, J. M., Anumba, C. J., & Evbuomwan, N. F. O. (2000). Establishing and processing client requirements-a key aspect of concurrent engineering in construction. Engineering Construction and Architectural Management, 7(1), 15-28. doi:10.1046/j.1365-232x.2000.00129.xDrevland, F., & Tillmann, P. A. (2018). Value for Whom? 26th Annual Conference of the International Group for Lean Construction. doi:10.24928/2018/0533Rybkowski, Z. K., Shepley, M. M., & Ballard, H. G. (2012). Target Value Design: Applications to Newborn Intensive Care Units. HERD: Health Environments Research & Design Journal, 5(4), 5-22. doi:10.1177/193758671200500402Yin, Y., Qin, S., & Holland, R. (2011). Development of a design performance measurement matrix for improving collaborative design during a design process. International Journal of Productivity and Performance Management, 60(2), 152-184. doi:10.1108/17410401111101485Volkova, T., & Jākobsone, I. (2016). Design thinking as a business tool to ensure continuous value generation. Intellectual Economics, 10(1), 63-69. doi:10.1016/j.intele.2016.06.003Westcott, M., Sato, S., Mrazek, D., Wallace, R., Vanka, S., Bilson, C., & Hardin, D. (2013). The DMI Design Value Scorecard: A New Design Measurement and Management Model. Design Management Review, 24(4), 10-16. doi:10.1111/drev.10257Heikkilä, V. T., Paasivaara, M., Lasssenius, C., Damian, D., & Engblom, C. (2017). Managing the requirements flow from strategy to release in large-scale agile development: a case study at Ericsson. Empirical Software Engineering, 22(6), 2892-2936. doi:10.1007/s10664-016-9491-zFARÍAS, P., & FISTROVIC, B. (2016). LAS PREFERENCIAS DEL CONSUMIDOR USANDO EL MÉTODO DE MÁXIMAS DIFERENCIAS. Revista de Administração de Empresas, 56(2), 138-151. doi:10.1590/s0034-759020160202Amini, P., Falk, B., & Schmitt, R. (2016). A Framework for Value-optimized Design of Product Features. Procedia CIRP, 57, 386-391. doi:10.1016/j.procir.2016.11.067Menezes, A. C., Cripps, A., Bouchlaghem, D., & Buswell, R. (2012). Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap. Applied Energy, 97, 355-364. doi:10.1016/j.apenergy.2011.11.075Zimina, D., Ballard, G., & Pasquire, C. (2012). Target value design: using collaboration and a lean approach to reduce construction cost. Construction Management and Economics, 30(5), 383-398. doi:10.1080/01446193.2012.676658Borgianni, Y. (2018). Verifying dynamic Kano’s model to support new product/service development. Journal of Industrial Engineering and Management, 11(3), 569. doi:10.3926/jiem.2591Pandolfo, A., Rojas, J. W., Kurek, J., Pandolfo, L., Lublo, R., Guimaráes, J., & Reinehr, R. (2008). Aplicación del modelo de evaluación de proyectos habitacionales para la medición de la satisfacción de las necesidades del usuario. Revista ingeniería de construcción, 23(1). doi:10.4067/s0718-50732008000100005Haddadi, A., Johansen, A., & Andersen, B. (2016). A Conceptual Framework to Enhance Value Creation in Construction Projects. Procedia Computer Science, 100, 565-573. doi:10.1016/j.procs.2016.09.196Lin, G., & Shen, Q. (2007). Measuring the Performance of Value Management Studies in Construction: Critical Review. Journal of Management in Engineering, 23(1), 2-9. doi:10.1061/(asce)0742-597x(2007)23:1(2)Witell, L., Löfgren, M., & Dahlgaard, J. J. (2013). Theory of attractive quality and the Kano methodology – the past, the present, and the future. Total Quality Management & Business Excellence, 24(11-12), 1241-1252. doi:10.1080/14783363.2013.791117Rischmoller, L., Alarcón, L. F., & Koskela, L. (2006). Improving Value Generation in the Design Process of Industrial Projects Using CAVT. Journal of Management in Engineering, 22(2), 52-60. doi:10.1061/(asce)0742-597x(2006)22:2(52)Tauriainen, M., Marttinen, P., Dave, B., & Koskela, L. (2016). The Effects of BIM and Lean Construction on Design Management Practices. Procedia Engineering, 164, 567-574. doi:10.1016/j.proeng.2016.11.659Song, J., Migliaccio, G. C., Wang, G., & Lu, H. (2017). Exploring the Influence of System Quality, Information Quality, and External Service on BIM User Satisfaction. Journal of Management in Engineering, 33(6), 04017036. doi:10.1061/(asce)me.1943-5479.0000549Matzler, K., Hinterhuber, H. H., Bailom, F., & Sauerwein, E. (1996). How to delight your customers. Journal of Product & Brand Management, 5(2), 6-18. doi:10.1108/1061042961011946

Analysis and Design of Mobile Collaborative Applications Using Contextual Elements

Collaborative mobile applications support users on the move in order to perform a collaborative task. One of the challenges when designing such applications is to consider the context where they will execute. Contextualized applications are easy to adopt by the users; unfortunately the design of contextualized tools is not evident. This paper presents a framework of contextual elements to be considered during the conception, analysis and design phases of a mobile collaborative application. This framework supports developers to identify non-functional requirements and part of the architectural design in order to get contextualized applications. The use of this framework is complementary to any structured software process. A framework use example is also presented as an illustration of its applicability

Influence of the experience of the project manager and the foreman on project management's success in the context of LPS implementation

[EN] Production planning is a key element for success in building project management. Last Planner System (LPS) has emerged as an alternative proactive management method through the commitment of the different stakeholders involved in the project; however, further research is required to determine the factors that can affect the success of LPS implementation. This research aims to analyze how the implementation of LPS and the construction management experience of the project manager and the construction site foreman individually influence project management's success, getting minimum time and cost deviations. In this work, newly built single-family house projects were analyzed. Quantitative and qualitative analyses, based on the Mann-Whitney U test and qualitative comparative analysis method, respectively, were performed to constrain both the individual and combined effects of LPS, the project foreman, and the project manager in terms of cost and time deviation as measures of project management success. The results highlight that LPS implementation is significant in terms of time deviation and combined LPS implementation and the foreman's experience in construction management are sufficient to maintain time deviations below 10%. However, among the studied variables, only the foreman's experience is a required condition to maintain cost deviations under 10%. Overall, this study may help construction organizations to improve their managerial practices at construction sites. (c) 2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).Funding for open access charge: CRUE-Universitat Politecnica de Valencia.Montalbán-Domingo, L.; Casas-Rico, JE.; Alarcón, LF.; Pellicer, E. (2024). Influence of the experience of the project manager and the foreman on project management's success in the context of LPS implementation. Ain Shams Engineering Journal. 15(1). https://doi.org/10.1016/j.asej.2023.10232415

Importance of Noncost Criteria Weighing in Best-Value Design–Build US Highway ProjectsE DESIGN-BUILD U.S. HIGHWAY PROJECT

United States highway agencies use best-value procurement with a fixed price to select design-builders.&nbsp; This method enables public agencies to choose the best proposer by assessing several factors in addition to price. Theoretically, considering cost and non-cost factors in the selection enhances the probability of selecting the proposer that provides the best value for each dollar spent.&nbsp; However, bidding results from the last 15 years show that 80% of best-value procurements are awarded the proposer with the lowest bid.&nbsp; The selection seems thus to be biased towards price. This research explores the balance between cost and non-cost components in best-value procurement by identifying how weights and scores influence the selection. The goal of this analysis is to determine the ranges of weights that better balance cost and non-cost factors in the weighted criteria best-value procurement. This study characterized a first-of-a-kind dataset of 882 non-cost scores and 1,158 cost scores from 347 best-value highway projects. The study applied simulation to the weighted criteria award algorithm to explore the balance between cost and non-cost factors and derive recommendations about how to make non-cost factors more influential. The results show that weight of cost higher or equal to 57% will result in a lowest price selection. Highways agencies should be aware of how weights and scores impact the best-value selection so that they can align these elements with their selection objectives.</p