37 research outputs found

    Challenges and Barriers to Establishing Infrastructure Asset Management: A Comparative Study between Libya and the United States

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    [EN] Purpose - The increased need for, and maintenance of, infrastructure creates challenges for all agencies that manage infrastructure assets. To assist with these challenges, agencies implement asset management systems. The purpose of this paper is to investigate and compare the importance of barriers faced by agencies establishing transportation asset management systems in the USA and Libya to contrast a case of a developed and developing country. Design/methodology/approach - A literature review identified 28 potential barriers for implementing an asset management system. Practitioners who participate in decision-making processes in each country were asked to rate the importance of each barrier in an online survey questionnaire. Descriptive statistics, Kendall Concordance W., and Mann-Whitney are used to analyze the collected data. Findings - Through an analysis of 61 completed questionnaires, 14 barriers were identified as important by both the US and Libyan practitioners. A total of 11 additional barriers, primarily in the areas of political and regulatory obstacles, were determined to be important only for Libya. These 11 barriers provide reasonable insights into asset management systems' barriers for developing countries. Practical implications - The list of barriers identified from this research will assist decision makers to address and overcome these barriers when implementing asset management systems in their specific organizational and country conditions. Originality/value - The research identified standard barriers to implementing asset management systems and identified barriers that were specific to the country context, such as political and regulatory barriers in Libya. When viewed with the asset management literature, the results show broad applicability of some asset management barriers and the need to contextualize to country context (e.g. developing countries) for other barriers.Beitelmal, W.; Molenaar, KR.; Javernick-Will, A.; Pellicer, E. (2017). Challenges and Barriers to Establishing Infrastructure Asset Management: A Comparative Study between Libya and the United States. Engineering Construction & Architectural Management. 24(6):1184-1202. doi:10.1108/ECAM-12-2015-0200S11841202246Acerete, B., Shaoul, J., & Stafford, A. (2009). Taking its toll: The private financing of roads in Spain. Public Money & Management, 29(1), 19-26. doi:10.1080/09540960802617327Alkilani, S., & Jupp, J. (2013). Paving the Road for Sustainable Construction in Developing Countries: A Study of the Jordanian Construction Industry. 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    A Comparison of Qualifications Based-Selection and Best Value Procurement for Construction Manager/General Contractor Highway Construction

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    Faster project delivery and the infusion of contractor knowledge into design are the primary drivers for choosing construction manager/general contractor (CM/GC) project delivery. This paper focuses on the use of qualifications-based (QBS) and best-value (BV) procurement approaches, how and why agencies use each, and their associated opportunities and obstacles. Data for this study were obtained from a majority of federally funded CM/GC projects completed between 2005 to 2015. The findings are that BV and QBS projects characteristics and performance have no statistically significant difference. The choice of BV or QBS coincides with the agency’s CM/GC stage of organizational development and influences of non-agency stakeholders on the CM/GC process. When agencies and the local industry are new to CM/GC, they were found to use BV as it is closer to the traditional procurement culture and it is perceived to result in a fair market project price. Alternatively, agencies and local industry partners with an established history of using CM/GC were found to choose QBS. The low level of design at the time of procurement, means that assumptions relating to risk, production rates, materials sources, etc. may be too preliminary to secure a reliable price. The use of BV procurement was found to pose a risk to innovation and increase negotiation efforts. Qualitative trends from the project data, interviews and literature point to agencies using QBS for the majority of CM/GC project and BV on CM/GC projects with lesser complexity or more highly developed designs at the time of selection

    Investigating Project Bundling Practices for Transportation Construction Projects

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    Project Bundling is an innovative contract procurement strategy that is being widely used in bridge and highway projects to save project delivery time and costs. The guidebook developed by FHWA on project bundling also provides a wealth of information on project bundling. However, the guidebook is primarily focused on the project bundling practices that STAs adopted for bridge projects. Thus, a knowledge gap in project bundling for roadway projects (such as added travel lanes, resurfacing, intersection improvement, interchange work, shoulder rehabilitation and repair, etc.), might exist

    Determining Contingencies in the Management of Construction Projects

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    [EN] This research describes the managerial approaches that contractors follow to determine different types of contingencies in construction project management. Two large Spanish general contractors were selected for an in-depth analysis. Interviews and surveys were conducted with six additional companies to explore the external validity of the findings. Managers constrain time and cost buffers through project objectives, applying heuristics to determine inventory buffers. The management of capacity buffers is entrusted to subcontractors. The contractors take advantage of scope and quality buffers to meet project objectives but rarely share these buffers with the owner, unless the owner is an internal client.Ortiz-González, JI.; Pellicer, E.; Molenaar, KR. (2019). Determining Contingencies in the Management of Construction Projects. Project Management Journal. 50(2):226-242. https://doi.org/10.1177/8756972819827389S226242502Adafin, J., Wilkinson, S., Rotimi, J. O. 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Journal of Construction Engineering and Management, 135(3), 135-145. doi:10.1061/(asce)0733-9364(2009)135:3(135)De la Cruz, M. P., del Caño, A., & de la Cruz, E. (2006). Downside Risks in Construction Projects Developed by the Civil Service: The Case of Spain. Journal of Construction Engineering and Management, 132(8), 844-852. doi:10.1061/(asce)0733-9364(2006)132:8(844)Ford, D. N. (2002). Achieving Multiple Project Objectives through Contingency Management. Journal of Construction Engineering and Management, 128(1), 30-39. doi:10.1061/(asce)0733-9364(2002)128:1(30)González, V., Alarcón, L. F., & Molenaar, K. (2009). Multiobjective design of Work-In-Process buffer for scheduling repetitive building projects. Automation in Construction, 18(2), 95-108. doi:10.1016/j.autcon.2008.05.005Guest, G., Bunce, A., & Johnson, L. (2006). How Many Interviews Are Enough? Field Methods, 18(1), 59-82. doi:10.1177/1525822x05279903Günhan, S., & Arditi, D. (2007). Budgeting Owner’s Construction Contingency. Journal of Construction Engineering and Management, 133(7), 492-497. doi:10.1061/(asce)0733-9364(2007)133:7(492)Hällgren, M., & Wilson, T. L. (2008). The nature and management of crises in construction projects: Projects-as-practice observations. International Journal of Project Management, 26(8), 830-838. doi:10.1016/j.ijproman.2007.10.005Harbuck R. H. (2004). Competitive bidding for highway construction projects (pp. ES91–ES94). Morgantown, WV: AACE International Transactions.HORMAN, M., & KENLEY, R. (1998). Process Dynamics: Identifying a Strategy for the Deployment of Buffers in Building Projects. International Journal of Logistics Research and Applications, 1(3), 221-237. doi:10.1080/13675569808962049Horman, M. J., & Thomas, H. R. (2005). Role of Inventory Buffers in Construction Labor Performance. Journal of Construction Engineering and Management, 131(7), 834-843. doi:10.1061/(asce)0733-9364(2005)131:7(834)Howell, G., Laufer, A., & Ballard, G. (1993). Interaction between Subcycles: One Key to Improved Methods. Journal of Construction Engineering and Management, 119(4), 714-728. doi:10.1061/(asce)0733-9364(1993)119:4(714)Howell, G., Laufer, A., & Ballard, G. (1993). Uncertainty and project objectives. Project Appraisal, 8(1), 37-43. doi:10.1080/02688867.1993.9726884Idrus, A., Fadhil Nuruddin, M., & Rohman, M. A. (2011). Development of project cost contingency estimation model using risk analysis and fuzzy expert system. Expert Systems with Applications, 38(3), 1501-1508. doi:10.1016/j.eswa.2010.07.061Laryea, S., & Hughes, W. (2011). Risk and Price in the Bidding Process of Contractors. Journal of Construction Engineering and Management, 137(4), 248-258. doi:10.1061/(asce)co.1943-7862.0000293Leach, L. (2003). Schedule and Cost Buffer Sizing: How to Account for the Bias between Project Performance and Your Model. Project Management Journal, 34(2), 34-47. doi:10.1177/875697280303400205Lee, S., Peña-Mora, F., & Park, M. (2006). Reliability and Stability Buffering Approach: Focusing on the Issues of Errors and Changes in Concurrent Design and Construction Projects. Journal of Construction Engineering and Management, 132(5), 452-464. doi:10.1061/(asce)0733-9364(2006)132:5(452)Oviedo-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.1943-7862.0000811Pellicer, E., Sanz, M. A., Esmaeili, B., & Molenaar, K. R. (2016). Exploration of Team Integration in Spanish Multifamily Residential Building Construction. Journal of Management in Engineering, 32(5), 05016012. doi:10.1061/(asce)me.1943-5479.0000438Pellicer, E., & Victory, R. (2006). IMPLEMENTATION OF PROJECT MANAGEMENT PRINCIPLES IN SPANISH RESIDENTIAL DEVELOPMENTS. International Journal of Strategic Property Management, 10(4), 233-248. doi:10.3846/1648715x.2006.9637555Rooke, J., Seymour, D., & Fellows, R. (2004). Planning for claims: an ethnography of industry culture. Construction Management and Economics, 22(6), 655-662. doi:10.1080/014461904200026324Slauson N. P. (2005). The effectiveness of the construction contract (pp. PM121–PM127). Morgantown, WV: AACE International Transactions.Tah, J. H. M., Thorpe, A., & McCaffer, R. (1993). Contractor project risks contingency allocation using linguistic approximation. Computing Systems in Engineering, 4(2-3), 281-293. doi:10.1016/0956-0521(93)90052-xTaylor, J. E., Dossick, C. S., & Garvin, M. (2011). Meeting the Burden of Proof with Case-Study Research. Journal of Construction Engineering and Management, 137(4), 303-311. doi:10.1061/(asce)co.1943-7862.0000283Thal, A. E., Cook, J. J., & White, E. D. (2010). 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    Modelo de aprendizaje para la selección de un proyecto diseño-construcción (llave en mano) en el sector público A learning model for design-build project selection in the public sector

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    El método primario de ejecución de proyectos en el sector público en los Estados Unidos (U.S.), tradicionalmente ha sido la ejecución diseño-licitación-construcción. El sector público históricamente ha separado los contratos de diseño y construcción. En la década de los 90, el sector público norteamericano comenzó a experimentar con la ejecución de proyectos diseño-construcción (llave en mano), que combina el diseño y la construcción en un solo contrato. En 1997 se estableció un sistema de apoyo a la toma de decisiones, con el fin de entregar un modelo se selección formal para la ejecución de proyectos en el sector público. El modelo apoya a los propietarios del sector público a determinar cuáles son los proyectos adecuados para la ejecución diseño-construcción (llave en mano). Este modelo inicial por naturaleza era estático y estaba basado en un análisis de regresión de 104 proyectos. El análisis produjo un modelo predictivo con cinco criterios de rendimiento: satisfacción general, carga administrativa, cumplimiento de expectativas, variación del programa, y variación del presupuesto. Desde 1997, el número de proyectos diseño-construcción ha aumentado dramáticamente y los métodos diseño-construcción del sector público han evolucionado. El modelo original puede ser mejorado con nuevos datos y una estructura que se traduce en un modelo adaptativo, mientras la industria continúa evolucionando. Este documento presenta una aplicación formal y el uso de capacidades para complementar el modelo estático original. Este modelo se ajusta a parámetros y funciones a través del empleo de inteligencia artificial, como principal motor de conocimiento. Este enfoque puede ser adaptado a muchas aplicaciones de apoyo a la toma de decisiones en la industria del diseño y construcción.The primary method of public sector project delivery in the United States (U.S.) has traditionally been design-bid-build delivery. The public sector has historically separated design and construction contracts. In the 1990s, the U.S. public sector began to experiment with design-build project delivery, which combines design and construction in one contract. In 1997, a decision support system was developed to provide a formal selection model for public sector design-build projects. The model supports public owners in determining which projects are appropriate for design-build delivery. This initial model was static in nature and was based on a regression analysis of 104 projects. The analysis resulted in a predictive model with five performance criteria: overall satisfaction; administrative burden; conformance to expectations; schedule variance; and budget variance. Since 1997, the number of design-build projects has increased dramatically and public sector design-build methods have evolved. The original model can be improved with new data and a new framework to provide for an adaptive model as the industry continues to evolve. This paper presents a formalized application and use of learning capabilities to supplement the original static model. This model adjusts parameters and functions using artificial intelligence as the main knowledge engine. This approach can be adapted to many applications of decision support in the design and construction industry

    Management of time and cost contingencies in construction projects: a contractor perspective

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    The management of threats and opportunities plays a key-role in enhancing project performance. However, there is a gap in literature concerning how general contractors manage threats and opportunities in construction projects, in particular in the use of time and cost contingencies. This research partially addresses this gap through a case study of two large Spanish construction companies. The research presented two key factors determining how the contractors analyzed manage time and cost contingencies: project objectives and existing mistrust among the contractor’s team members. The research also found that managers use time and cost contingencies not only to manage threats, but also as tools for managing opportunities, thereby providing insight into a previously undescribed form of contingency: the negative contingency. The research results enable a better understanding of the actual behavior of general contractors, which contributes to paving the way for developing enhanced methods for contingencies management

    The influence of P3s on design flexibility and downstream design feedback in the Presidio Parkway

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    Public-Private Partnerships (P3s) offer the opportunity to improve integration among project stakeholders throughout a project’s life cycle. Stakeholder integration, in turn, can enhance design decision-making process by focusing on the project’s life cycle cost. The objective of this paper is to compare and contrast design decision-making in a P3 and design-bid-build (DBB) process to explore if life cycle considerations are better optimized under a P3 delivery method. To do this, we analyzed a project that included both P3 and DBB project delivery strategies—the Presidio Parkway. We collected data through 16 open-ended, semi-structured interviews with key project participants. We analyzed the data for design decision-making processes and found mixed evidence supporting the proposition that life cycle considerations can be better optimized under a P3 delivery method. Specifically, we found that the ability of the P3 contractor to influence project outcomes depends on the timing of the integration of the designer in a P3 and the degree of design criteria and flexibility allowed. In the case study analyzed, the P3 designer was able to influence downstream life cycle considerations, such as the operations and maintenance of the project; however, given the degree of definition of the design and the timing of integration of the P3 designer, it was not possible to influence the upstream design decisions. These findings allow researchers to better understand how P3s are being integrated from a design perspective and allow the public sector to realize how the timing and degree of definition of the design in P3s influences a concessionaire’s ability to make life cycle design choices.Non UBCUnreviewedFacultyOthe

    Decision Support System for Selection of Project Delivery Method in Transit

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    A decision support system was developed to help transit agencies evaluate and choose the most appropriate project delivery method for their capital projects. The system considers the traditional design–bid–build, construction manager-at-risk, design–build, and design–build–operate–maintain delivery methods. A set of 24 pertinent issues that can affect the choice of project delivery method are identified and described. The described decision support system consists of two distinct tiers. The first tier is a qualitative assessment in which the decision maker evaluates the effectiveness of each delivery method for dealing with the relevant pertinent issues. This tier will help agencies determine if there is a dominant or obvious choice of project delivery method. If at the end of this stage a clear choice is not evident, the user will move to the second tier, where a weighted matrix is used to score competing alternatives. The system will also provide a structure for documenting the project delivery decision in the form of a project delivery decision report. A validation process for the system is described, and a brief example is provided to show the application of the decision support system
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