Application Of Leagile Theory In Construction Industry To Improve Value-creating Activities

PurposeThe present research aims to investigate how lean project management (LPM) and agile project management (APM) affect project performance outcomes in the construction sector in Jordan. This study focuses on six key project performance outcomes, namely cost, time, quality, client satisfaction, innovation and responsiveness.Design/methodology/approachThe present study employed a quantitative approach to achieve the research objectives. Accordingly, a multi-item survey questionnaire was prepared to gather data from 392 project managers from construction companies in Jordan. The study’s model showed acceptable levels regarding reliability, validity, fit indices and discriminant validity. In order to test the hypotheses of this study, path analysis was employed using Amos 24.0 software.FindingsLPM demonstrated a remarkably high positive impact on cost performance. It also positively affected quality performance and client satisfaction. However, LPM insignificantly affected time, innovation and responsiveness performance measures. On the other hand, APM showed a notably high positive impact on innovation and responsiveness. The findings also revealed that APM positively impacted quality performance and client satisfaction. In addition, APM negatively impacted cost performance and insignificantly impacted time performance.Originality/valueThis study is one of the first comprehensive studies to empirically examine the impact of both LPM and APM on various project performance outcomes in the construction industry in the context of a developing country. It reveals some similarities and differences between LPM and APM with regard to their impacts on project management outcomes. The findings are expected to guide managers in selecting the appropriate project management approach based on the desired performance outcomes. Accordingly, it offers important implications for project managers in construction companies.

Among many fallouts of the global pandemic, firms’ supply chains have been severely impacted at the global scale. Such global impact can be mainly attributed to companies’ current heavy focus on lean manufacturing, resulting in a lack of preparedness and flexibility, and therefore weakening their supply chain links. At the same time, firms face severe financial distress and constraints if their investments in future risks turn out to be of no value. Facing such dilemmas, many firms are unsure of how to appropriately configure lean and risk management at their operational and supply chain levels. This study aims to understand the various configurations of lean manufacturing and supply chain risk management. Also, this study pays attention to buffer capacity associated with lean and risk management. In a dataset collected from 198 US companies, cluster analyses discover the manufacturers’ configurations of the varying emphases on lean management and supply chain management. Our results indicate that firms achieve the highest levels of buffer capacity and firm performance if they implement lean practices and risk management at a higher level than others.

The article identifies the main challenges in supply chain management in 2023. Factors influencing the choice and application of Lean / Agile methodology were also analyzed, their differences were outlined, and a Lean / Agile matrix was constructed, which can be used in supply chain management depending on the characteristics of supply and demand. It is reasoned that as a result, it will enable organizations to optimize operations, reduce costs, improve quality and increase customer satisfaction in a dynamic and competitive business environment. It is also important to understand how lean thinking and the agility method can strengthen and optimize the efforts of business structures in the field of digital transformation. The future of logistics is expected to be shaped by various trends and developments. The key aspects that can determine the future of logistics and the specifics of supply chain management are characterized. The main of them are: automation and robotics; artificial intelligence and machine learning; Internet of Things (IoT); sustainable business practices and green logistics; blockchain technology; customer orientation. The expediency of future implementation of a combined (hybrid) supply chain management methodology ("LEAGILE strategy"), which is a combination of both lean and agile supply chain management, is asserted. Speaking of synergy, combining Lean and Agile methodologies in supply chains can lead to the best results by leveraging the strengths of both approaches. Lean focuses on eliminating waste and increasing efficiency, while Agile emphasizes flexibility and the ability to respond to customer demands. By integrating these two approaches, organizations can achieve a balance between cost reduction and customer satisfaction. Some ways to combine Lean and Agile in supply chains for best results are outlined: 1. Demand-driven manufacturing; 2. Cross-functional collaboration; 3. Continuous improvement; 4. Partnership with suppliers; 5. Technology integration; 6. Flexibility in production; 7. Customer-oriented approach. It is worth implementing a situational approach to choosing a supply chain management methodology in conditions of uncertainty, taking into account the nature of demand, the product life cycle, marketing goals, etc.

Agile methodology is a type of project management process, mainly used for software development, where demands and solutions evolve through the collaborative effort of self-functional teams and their customers. During the past few decades, fundamental changes have taken place in project development, planning, and execution. This has taken from with embracing new techniques such as various agile project management, instead of using the traditional waterfall project management. . It is mainly suitable for complex project, where there is delay in construction projects & final deliverable in advance. Construction delays are a common phenomenon in civil engineering projects. There are many reasons to delay in construction as pre-design, design and execution phase. It leads to time overrun in the construction work. Completion of construction projects on time seems to be challenging tasks in large-scale construction. It has been observed that about 90% of government infrastructure projects fail to achieve on time completion in India. Time is a major factor in construction and on time completion will bring about many benefits to the client, contractor and the society. This thesis paper will discuss and finding out the reasons for delay in two different construction project and apply agile management methodology where the delay is identified in this construction works. Also will prove the scope of agile management in construction industry in future.

The essential requirements for sanctioning Energy Sector projects have always been conceptual planning, Front-End Engineering Design (FEED) and feasibility studies. Traditional EPC projects start with a planning phase, a design phase, a construction phase, a testing phase, and a turnover to the user phase followed by project closeout. Such projects are usually delivered through water fall management approach. Large EPC projects have more elaborate models with multiple stage gates and bid phases, but the commonality is the sequential nature, with user input happening primarily in the planning and or design phase. During construction phase again there is a sequential work plan with defined project schedule defining activities with regards to trade or geographic areas. Large construction projects are usually implemented through multiple sub-contractors under a general contractor, with a separate designer and a separate owner, and in some cases separate end users (tenants), with complex contracting methodology (ies) in place. As the era of "easy hydrocarbons" is approaching its end, mega-projects are becoming a norm in petroleum sector despite high CAPEX and having long lead times for reaching commercial operations. This is so because unconventional oil and gas like shale gas, Oil sands, FLNG, Ultra-deep water reservoirs require implemetation of state-of-the-art technologies and resource in lesser known project site conditions. FID for such project has traditionally been based on conceptual planning, Front-End Engineering Design (FEED) and feasibility studies. These preliminary steps also help in defining a rigid process (Stage Gate Process "SGP") to follow during subsequent project progress related to EPC activities. SGP outlines activities to be completed in every stage of the project and progress into subsequent stage is authorized only with the approval of a committee / individual called "Gatekeeper". This study discusses application of SGP, having shared Gatekeeper from project stakeholders, together with Agile project management methods, SCRUM to be specific, for developing successful strategies for project EPC phase. As oil and gas industry is moving to megaprojects with innovative reserves recovery ideas, the sector is experiencing increased utility of Agile project-management methods. The entire innovation process has great potential in reducing project development time frame and increasing the success rate of Greenfield or Brownfield projects. This study outlines how Agile method, such as Scrum, can be used as a structured innovative methodology with milestones and decision points (similar to Stage-Gate), and benefits for project stakeholders. This study is carried out as follows: One (01) Green Field project is selected for investigation related to successful EPC management through possible use of Scrum (Agile Methodology)One (01) IT Project is selected for investigations related to successful implementation of Agile management during planning, development and delivery phase.Responsibilities of Project Owner as well as Project Director (Single Point Accountable individual) will be identified for successful implementation of Agile methodology.The study will investigate the availability of know-how and actual utilization of combination of SGP and Srum (Agile methodology) by Project Director / Owner during project execution.The study will identify and quantify the risks involved and benefits achieved in using combination of SGP and Scrum project management strategy. This study indicates that Project Owner as well as Project Director are responsible to identify which component of the EPC project is to be handled through waterfall management and which component is to be managed through Agile. The paper provided two case studies of the use of agile tools and methodologies for IT related projects (which are true candidate for Agile) and EPC project which is different from software or information technology. The very beneficial results and outcomes from the case studies provided proven examples of the success of the application. It is recommended that not all of the principles of agile fit into every EPC project management requirement and need to be evaluated for use for each project and additionally management should make investments in non-core training for their personnel. Mega projects in oil and gas sector are prone to change in requirements during EPC stage. As such Agile project-management method i.e. SCRUM can be used in the innovation process and has a great potential to reduce development time and increase the success rate of new projects. The article briefly outlines how an Agile method, such as Scrum, can be used within a structured innovation process with milestones and decision points, such as Stage-Gate. For mega projects in oil and gas sector a combination of waterfall and scrum methods can be used for managing components of the project.

Roberto Baldacci (“ An Exact Algorithm for the Pickup and Delivery Problem with Time Windows ”) is a researcher in operations research at the Department of Electronics, Computer Science, and Systems (DEIS) of the University of Bologna, Italy. His major research interests are in the areas of transportation planning, logistics and distribution, and the solution of vehicle routing and scheduling problems over street networks. His research activities are in the theory and applications of mathematical programming including the design of new heuristic and exact methods for solving routing and location problems. Enrico Bartolini (“ An Exact Algorithm for the Pickup and Delivery Problem with Time Windows ”) holds a postdoctoral position at the University of Bologna. His research activity concerns the study and development of heuristic and exact algorithms for solving combinatorial optimization problems with applications in logistics and distribution systems, in particular network design problems and some generalizations of the vehicle routing problem. Saif Benjaafar (“ Optimal Control of an Assembly System with Multiple Stages and Multiple Demand Classes ”) is professor of industrial and systems engineering at the University of Minnesota, where he is also founding and current director of the Industrial & Systems Engineering Program, director of the Center for Supply Chain Research, and a faculty scholar with the Center for Transportation Studies. He was a Distinguished Senior Visiting Scientist at Honeywell Laboratories and a visiting professor at universities in France, Belgium, Hong Kong, China, and Singapore. His research is in the areas of supply chain management, service and manufacturing operations, and production and inventory systems, with a current focus on sustainability and environmental modeling. He serves on the editorial board of several journals including Manufacturing & Service Operations Management, Production and Operations Management, Naval Research Logistics, and IIE Transactions. He is a Fellow of the Institute of Industrial Engineers (IIE). Dimitris Bertsimas (“ Performance Analysis of Queueing Networks via Robust Optimization ”) is the Boeing Professor of Operations Research and codirector of the Operations Research Center at the Massachusetts Institute of Technology. This research is part of his work in the last decade on robust optimization for optimization and performance analysis of stochastic systems. Atul Bhandari (“ Revenue Management with Bargaining ”) is manager of the Algorithms Team at SmartOps. He supervises the design and development of enterprise inventory optimization algorithms, supervises modeling and analysis support for sales and implementation efforts, and leads educational sessions. He earned a Ph.D. in operations research from the Carnegie Mellon University Tepper School of Business. Sushil Bikhchandani (“ An Ascending Vickrey Auction for Selling Bases of a Matroid ”) is professor of decisions, operations, and technology management at the Anderson School of Management at the University of California, Los Angeles. He is interested in the economics of incentives and its application to auctions, market institutions, and social learning. J. Paul Brooks (“ Support Vector Machines with the Ramp Loss and the Hard Margin Loss ”) is an assistant professor of operations research in the Department of Statistical Sciences and Operations Research and a fellow of the Center for Study of Biological Complexity, Virginia Commonwealth University. He is currently secretary/treasurer of the INFORMS Section on Data Mining. His research interests include the design of optimization-based algorithms for data mining and their application to biomedical data. He is also interested in applications of optimization to models of cellular metabolism and network design problems. Sungyong Choi (“ A Multiproduct Risk-Averse Newsvendor with Law-Invariant Coherent Measures of Risk ”) is an instructor in the Department of Management Science and Information Systems at Rutgers University. Dr. Choi's research interests are in the area of stochastic modeling and its application in supply chain management. Milind Dawande (“ Production Planning with Patterns: A Problem from Processed Food Manufacturing ” and “ Quantifying the Impact of Layout on Productivity: An Analysis from Robotic-Cell Manufacturing ”) is professor and area coordinator of operations management at the School of Management, University of Texas at Dallas. His research interests are in discrete optimization problems in manufacturing and operations. His papers have appeared in a number of research outlets, including Operations Research, Management Science, Manufacturing & Service Operations Management, and the INFORMS Journal on Computing. Mehmet Demirci (“ Production Planning with Patterns: A Problem from Processed Food Manufacturing ”) is a supply chain sales engineer at SmartOps. He holds a Ph.D. degree in industrial engineering from the University of Pittsburgh. His research interests include inventory optimization, operations management, large-scale combinatorial optimization, and operations research applications in health care. Sven de Vries (“ An Ascending Vickrey Auction for Selling Bases of a Matroid ”) is a professor of operations research in the Department of Mathematics at the Universität Trier. His research interests include combinatorial optimization and auctions. Xiaowei Ding (“ A Top-Down Approach to Multiname Credit ”) is an associate at Morgan Stanley's Commodity Trading Group. Mohsen ElHafsi (“ Optimal Control of an Assembly System with Multiple Stages and Multiple Demand Classes ”) is a professor at the Anderson Graduate School of Management at the University of California, Riverside, where he also serves as associate dean and graduate advisor. He holds Ph.D. and M.Sc. degrees from the Industrial and Systems Engineering Department at the University of Florida and was the Honor Graduate. He received the Qualified Engineer degree, with honors, from the Ecole Nationale d'Ingénieurs de Tunis, Tunisia. His area of research includes operations and supply chain management, manufacturing and service operations, and production and inventory systems. Amr Farahat (“ A Comparison of Bertrand and Cournot Profits in Oligopolies with Differentiated Products ”) is an assistant professor at the Johnson Graduate School of Management at Cornell University. He obtained his doctoral degree in operations research from the Massachusetts Institute of Technology. His current research focuses on differentiated product pricing, inventory management, and competition. He is interested in problems at the interface of operations management, economics, and marketing. Vivek F. Farias (“ The Irrevocable Multiarmed Bandit Problem ”) is the Robert N. Noyce Career Development Assistant Professor of Management at the Sloan School of Management and the Operations Research Center at the Massachusetts Institute of Technology. His research focuses on revenue management, dynamic optimization, and the analysis of complex stochastic systems. The paper in this issue is part of the author's research in the context of dynamic optimization. David Gamarnik (“ Performance Analysis of Queueing Networks via Robust Optimization ”) is an associate professor of operations research at the Sloan School of Management of the Massachusetts Institute of Technology. His research interests include applied probability and stochastic processes, theory of random combinatorial structures and algorithms, and various applications. He currently serves as an associate editor of Annals of Applied Probability, Operations Research, Mathematics of Operations Research, and queueing systems journals. Srinagesh Gavirneni (“ Production Planning with Patterns: A Problem from Processed Food Manufacturing ”) is an assistant professor of operations management in the Johnson Graduate School of Management at Cornell University. His research interests are in the areas of supply chain management, inventory control, production scheduling, simulation, and optimization. His papers have appeared in Management Science, Manufacturing & Service Operations Management, Operations Research, European Journal of Operational Research, Operations Research Letters, IIE Transactions, and Interfaces. Previously he was an assistant professor in the Kelley School of Business at Indiana University, the chief algorithm design engineer of SmartOps, a software architect at Maxager Technology Inc., and a research scientist with Schlumberger. His undergraduate degree from IIT-Madras is in mechanical engineering, and he received an M.Sc. from Iowa State University and a Ph.D. from Carnegie Mellon University. Kay Giesecke (“ A Top-Down Approach to Multiname Credit ”) is assistant professor of management science and engineering at Stanford University. His research and teaching interests are in financial engineering. Lisa R. Goldberg (“ A Top-Down Approach to Multiname Credit ”) is executive director of analytic initiatives at MSCI Barra with responsibility for developing and prototyping financial risk and valuation models. Randolph W. Hall (“ Discounted Robust Stochastic Games and an Application to Queueing Control ”) is vice president of research, and professor of industrial and systems engineering, at the University of Southern California. After receiving a Ph.D. in civil engineering from the University of California, Berkeley, he has held research and faculty positions at General Motors, the University of California, Berkeley, and the University of Southern California, including dir

This study was conducted with the aim of investigating the implementation of agile project management methodologies in the construction industry in the United States. The research utilized a review of literature methodology to examine the benefits, challenges, and success factors associated with adopting agile practices in construction projects. By analyzing past studies and scholarly publications, a comprehensive understanding of the topic was achieved. The study highlighted several key benefits of agile project management in the construction industry. These benefits included improved adaptability to changing project requirements, increased client satisfaction through enhanced collaboration and continuous feedback, and greater project transparency and visibility. Additionally, agile methodologies were found to foster more effective risk management and improved project delivery timelines. Challenges encountered during the implementation of agile practices in the construction industry were also identified. These challenges encompassed resistance to change, inadequate stakeholder buy-in, difficulties in integrating Agile with traditional construction practices, and the need for skilled agile practitioners. Understanding these challenges can assist project managers and stakeholders in developing strategies to mitigate potential obstacles. By synthesizing the existing literature, this research provides valuable insights into the implementation of Agile project management in the United States construction industry. The findings contribute to a deeper understanding of the benefits, challenges, and success factors associated with agile practices, enabling construction professionals to make informed decisions and adopt effective strategies when implementing agile methodologies in their projects. Keywords: Agile project management, Implementation, Construction industry, Benefits, challenges, success factors, United States.

<p><strong>Green Supply Chain Management (GSCM) is considered to be an effective management tool, aiming to integrate environmental sustainability thinking into the various stages of the construction supply chain. This is in relation to its ability to substantially reduce greenhouse emissions, energy consumption, pollution, waste, and other drivers of negative environmental impacts across the entire construction supply chain management phases. Despite the implementation of GSCM practices as a means to reduce negative environmental footprints, climate change continues to occur with a steady rise in greenhouse gas emissions per year that are associated with the built environment. Moreover, recent reports from the United Nations (UN) indicate that the global construction industry is still far from achieving its decarbonization goals by 2050, despite the integration of various sustainability practices, including sustainable technologies, policies, and solutions. This, therefore, reinforces that green or sustainability is no longer enough to eliminate the current negative impacts of construction activities on our built environment.</strong></p><p>To address these challenges, there is a need for a paradigm shift from a green to a proactive approach called regenerative thinking that focuses not only on reducing negative environmental footprints but also aims to restore and renew our ecosystems, communities, and the built environment in general. The shift from a green to a regenerative paradigm in construction brings about a comprehensive change in how construction projects are conceived, designed, and executed. By embracing this shift, the construction industry has the potential to redefine its impact, demonstrating that it can not only construct functional spaces but also actively contribute to the regeneration of the built environment.</p><p>Despite the numerous benefits associated with shifting from green to a regenerative paradigm in construction, there exists a deficiency in research that has been able to address how the various GSCM practices used in the construction industry can move beyond limiting negative environmental impact or achieving sustainability alone. Against this backdrop, this research aims to establish a robust approach that integrates regenerative principles into the current GSCM practices used in the construction industry in an attempt to develop and facilitate the adoption of a novel, regenerative supply chain management (RSCM). To achieve this aim, the research begins with an assessment of the current GSCM practices and their limitations across various stages of the construction supply chain through a systematic literature review. It then proceeds to explore enhancements for each stage and their associated limitations, drawing from regenerative principles that acknowledge the interconnectedness of human actions with nature. This integration resulted in the development of a preliminary conceptual RSCM model which was further validated using a multi-phase approach. Further investigation leads to the formulation of performance evaluation criteria tailored to the regenerative approach, which then informs the development of a systematic model assigning priorities to the validated RSCM practices. To complement the overall research objective, an automated RSCM decision support system (RSCM-DSS) was developed and further validated to facilitate informed decision-making and practical implementation of the RSCM practices developed in this study. A variety of data collection techniques, including literature review, real-life case studies, and experts identified through purposeful and snowballing sampling techniques, among others were employed in this study. Data were analysed via descriptive statistics, Fuzzy Analytical Hierarchy Process (FAHP), Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS), among others.</p><p>This research offers significant theoretical, practical, and policy implications. Theoretically, it advances green and sustainable thinking in construction by integrating regenerative principles throughout the supply chain management phases, developing a comprehensive model that emphasises interconnectedness. Practically, the research offers refined performance evaluation criteria for monitoring regenerative initiatives and stresses stakeholder collaboration for better outcomes. On the policy front, the findings enable policymaking for restoration-focused regulations, potentially integrating regenerative principles into standards such as the construction contract documents. In essence, this research seeks to reshape paradigms, guide practices, and influence policies, ultimately steering the construction sector towards a more regenerative and holistic approach.</p>

Sustainability principles should be incorporated into all decision-making stages for residential construction projects to ensure maximum revenue while maintaining essential residential building services. This study identifies and analyzes the critical success factors (CSFs) necessary for implementing agile project management (APM) in residential construction projects. Data were collected from 120 professionals in the Nigerian construction industry through questionnaire surveys to understand the implementation of APM. The CSFs were obtained from previous research and analyzed within the specific context of the Nigerian construction industry through questionnaire surveys. The CSFs were grouped into two main categories using exploratory factor analysis: dynamic project optimization and agile project foundations. The model for the CSFs was developed using partial least squares structural equation modeling. The study found that the dynamic project optimization element had the most significant impact on the model, highlighting its importance as a key CSF in APM implementation. These results support the adoption of APM within Nigeria’s construction industry as stakeholders and professionals seek effective strategies to reduce costs and improve sustainability.

In the construction industry supply chain management (SCM) is a vital tool in controlling business processes in a defined and a systematic way to improve quality, time management and increase profit. Effective supply chain management has become a potentially valuable method of securing and improving competitive advantage and organizational performance since competition no longer between organizations, but between global organizations and among supply chains. This paper aims to investigate the impact of supply chain management practices on competitive advantage and organizational performance in the construction industry, Sri Lanka, due to the lack of application of supply chain management practices to determine the organizational performance in the competitive environment. Further, this study focuses five SCM practices: strategic supplier partnership, customer relationship, level of information sharing, quality of information sharing, and postponement to investigate what supply chain management is, how it works in increase competitive advantage and what are its dynamics. Six hypotheses were developed based on the constructed conceptual framework derived from the supply chain management literature. The data were collected over the survey technique by randomly administering structured questionnaires from 198 respondents of construction management teams and different sub-contractors. First Multiple regression analysis was performed to explore the impact of five supply chain management practices on competitive advantage and organizational performance in the construction industry and the analysis was carried out the factor analysis to explore the significance of supply chain management dimensions. The results of the regression analysis indicated that all SCM variables have a positive impact on competitive advantages and organizational performance of the construction industry in Sri Lanka. Moreover, it suggested that the strategic supplier partnership was the most significant SCM variable which determines the competitive advantage and level of information sharing variable was the less significant variable towards competitive advantage. The results of this study provide new insights to the construction companies to better understand the significant role that SCM variables play in respect to the competitive advantages and organizational performance in Sri Lanka. The study has outlined to examine the five SCM variables in construction industry. Hence future study can be outlined to further examine the impact of SCM on competitive advantages in other industries. Moreover, the future study can be outlined to further examine the impact of SCM variables in different dimensions especially including customer perspective in respect to human variables. Besides, this study was based on the limited large scale construction companies operated in Sri Lanka and ignore the small and medium scale supermarkets.
 Keywords: Supply chain management practices, Competitive advantage, Organizational performance

Largely taken for granted within the UK construction sector has been a view that supply chain management theory is robust, relevant and reliable. As such it has formed a substantial aspect of previous and contemporary policy and government funded research. Despite this, the general view of its development and diffusion over the last 15 years within the construction industry has been problematic. Coincidentally, prevailing debates within the supply chain management academic community point to the lack of unified theory, models of diffusion and strong connections to organization theory. Using Straussian grounded theory, iterations between data and organization theory provided a fresh perspective on the development and diffusion of supply chain management in construction. This inductive research provided contextually rich explanations for development and diffusion that explicitly connected with and drew upon robust, relevant and reliable theories of institutions, innovation diffusion, triads, quasifirms and mechanisms of organizational governance. These explanations challenge the simplistic assumption that chains and networks of organizations are holistically managed and controlled by any single organization or institution in the construction industry. The debate therefore shifts away from proselytizing supply chain management towards research that explores the rigour, relevance and reliability of supply chain management assumptions in construction. The gap between industry practice and policy is exposed and the question is posed: to what extent policy and practice do, or should, constitute a recursive relationship.

The understanding of Lean Construction (LC) management philosophy is essential to making effective decisions in construction projects. LC's philosophy focuses on identifying and eliminating process waste while adding value to production. In construction management, timely decisions and instructions can positively impact projects. This paper will examine how lean and digital methodology can positively influence construction management. This research focuses on a digitised Last Planner System® (LPS) that provides a collaborative platform to make informed decisions promptly. Integrating numerous digital platforms, such as an Unmanned Aerial Vehicle (UAV) with 4K camera technology and virtual field walks using 360° images. The synergy between Lean and Building Information Modelling (BIM) has shown that is improves collaboration in design and construction activities. Enhancing the connection by incorporating reality capture with digital LPS and Business Intelligence (BI) tools can improve accountability and increase collaboration by providing the necessary information to make prompt and correct decisions. Focusing on project stakeholders we will examine how digital platforms used with lean philosophy can improve project workflow and the delivery of construction projects effectively and efficiently. The increased transparency provided by interactive digital platforms enhances collaboration and supports project team integration. Lean processes utilising digital tools can reduce the variability and uncertainty of construction projects and improved overall project delivery.

This study examines how Industry 4.0 has been discussed in the construction industry and construction management (CM) research over the past four years using Oesterreich and Teuteberg’s (2016) article as a key marker. The techniques adopted in this paper were Bibliometric analysis. Citation, co-citation, and co-occurrence analyses were applied to the articles published between 2016-2019 in the WoS database. This study concluded that most CM research themes had been impacted by Industry 4.0. Also, CM scholars, journal editors, and decision-makers have expressed significant interest in Industry 4.0. Finally, this research has focused on research themes that have been less examined by scholars and have identified areas for future research on how CM literature may benefit from Industry 4.0. Twenty-one main research themes were identified, a co-occurrence network was constructed and examined. The results indicate that there are a sufficient number of references to Industry 4.0 in the themes of management, smart factory, and digitisation. On the other hand, other themes have received less scholarly attention, such as performance, simulation, and supply chain management. Those less explored themes possibly require additional studies.

Improving Construction Processes Using Lean Management Methodologies – Cost Case Study

Traditional two-dimensional (2D) delivery systems in the construction industry can hinder the way information is communicated between owners, architects, and contractors. This hindrance exists in all phases of a project, from design and construction to the operation and maintenance of the completed facility. Building Information Management (BIM) is an emerging information technology that promotes a collaborative process for the Architectural, Engineering, Construction and Facilities Management (AECFM) industry; it can aid the exchange of information and provide improved project data accessibility to all stakeholders of a construction project. The Naval Facilities Engineering Command (NAVFAC), in conjunction with the facility management (FM) chiefs of the other Department of Defense (DoD) agencies, is committed to adopting the standards and technologies used in the private sector that promote efficient and effective business and construction management practices. The AECFM industry shift to BIM is resonating to the public sector and implementation plans to accommodate the shift are being developed by many public agencies at all levels of government. NAVFAC recognizes the need to develop and adopt BIM technologies in order to keep pace with private sector advances and has drafted a BIM Road Map document (NAVFAC, 2009) to provide BIM implementation guidance to the NAVFAC organizations responsible for providing and maintaining facilities and infrastructure to Supported Commanders. The objective of this thesis is to evaluate the NAVFAC BIM Road Map, analyze BIM tools and processes currently used in the construction industry, and provide recommendations for best practices and improvements to the NAVFAC BIM Road Map. The methodologies used in this research includes three phases: Phase 1- evaluate the current NAVFAC BIM Road Map, Phase 2: Case Study and Phase 3: Develop recommendations to improve BIM Road Map. The outcome of this research effort will be a set of recommendations that ensure that all parties are clearly aware of the opportunities and responsibilities associated with incorporation of BIM into the organizational workflow for naval construction projects.