In this research, variation is defined as the time difference between what was planned and what actually happened in terms of task starting times and duration. Variation in construction tasks is important as it can impact productivity performance. Construction projects consist of a large number of interdependent tasks. When the starting time and/or duration of one task varies, it can affect other downstream tasks and result in disruptions to the schedule and/or decreased productivity. The construction process is complex and involves numerous people with different levels of responsibility, which makes identifying the root causes of the variation difficult. A nationwide survey was administered to workers, foremen, and project managers to identify the most prevalent causes and magnitude of both starting time and task duration variation. Fifty individual causes of variation were divided into eight categories: prerequisite work, detailed design/working method, labor force, tools and equipment, material and components, work/job site conditions, management/supervision/information flow, and weather or external conditions. This research examined the similarities and differences in perceptions between craft workers, foremen, and project managers in terms of starting time and task duration variation. The top eight causes of starting time variation and top nine causes of task duration variation were identified. The research also quantitatively analyzed the underlying structure of the causes of variation using factor analysis. This was done by grouping the 50 individual causes into nine orthogonal factors that represent the underlying structure of the affecting causes. The findings will help construction project managers and field managers focus on the root causes of variation during planning in order to develop effective strategies to reduce variation and improve project productivity performance.

Construction project managers are often faced with the challenge of managing a complex construction process consisting of multiple trades working on a large number of interdependent tasks. A social network is a pattern of ties that exist between different entities (i.e., people, organizations, countries). There is an underlying social network of trades that exists with a construction project and recognizing it can help a management team succeed in this challenging environment. A $50 million project involving 43 trades was studied over a 28-week period. Pajek, a social network analysis program, was used to generate a series of 14 social networks for the trades involved. Both degree and eigenvector centrality were analyzed to reflect the distribution of relationships through the network and to identify the key trades. This research is useful to project managers and is significant as it outlines and illustrates a method of identifying the underlying network and associated key trades of a construction project based on spatial proximity. While this research is based upon an individual case study, the apsects of this research are repeatable. The methods presented in this paper will enable others to develop a social network that is tailored for a specific aspect of a project, ranging from contract development teams to the individual trades using a critical path method (CPM) schedule.

Different types of flow variation and how they affect construction project performance have been studied by previous researchers. One aspect that has not been well researched is how work flow variation and labor productivity are related in construction practice. To study that issue, 134 weeks of project production data were collected and analyzed to explore this relationship. Labor productivity was found to be positively correlated with Percent Plan Complete (PPC), a measure of work flow variation. The relationship between productivity and the ratio of total task completion to planned tasks, weekly workload, weekly work output, and weekly work hours was also studied, and no significant correlation was found. The results suggest that productivity is not improved by completing as many tasks as possible regardless of the plan, nor from increasing workload, work output, or the number of work hours expended. In contrast, productivity does improve when work flow is made more predictable. These findings can help project managers focus on actual drivers of productivity. It can also help consulting companies pinpoint responsibility for productivity losses in claims.

In construction, the most relevant systems used for project management (PM) and project production management (PPM) in the planning and control phases are critical path method (CPM), last planner system (LPS), and location-based techniques (LB). Studies have addressed these systems, mostly in isolated fashions. This study aims to compare and contrast their use in terms of PM and PPM and clarify industry benefits in order to eliminate potential misunderstandings about their use. A survey was administered to construction professionals in Brazil, China, Finland, and the United States. No single system addresses all needs of PM and PPM. CPM is the dominant system when considering the following characteristics: primary industry types, type of organization, size of organization, professional position within the organization, and area of work. Contributions to knowledge include that CPM is a contract requirement with perceived benefits associated with critical path analysis; LB and LPS have perceived benefits regarding continuous flow and use of resources, treatment of interferences, and improving production control. All systems were found to have a similar level of benefits for management of contracts, delay and change, and evaluation of the root causes of delays. The industry can benefit from aligning project scheduling methods with project needs.

Effective construction project planning relies on addressing constraints related to materials, labor, equipment, and others. Planning meetings are typical venues for stakeholders to identify, communicate, and remove constraints. However, a critical gap exists in lacking an automated approach to identify, classify, analyze, and track constraint discussions during onsite planning meetings. Therefore, this research aims to 1. develop a natural language processing model to classify constraints in meeting discussions; 2. uncover the discussion patterns of managers and foremen regarding various constraints; and 3. extract the root causes for constraints, evaluate their impacts, and prepare managers to develop practical solutions for constraint removal. This research collected meeting transcripts from 94 onsite planning meetings of a building project, spanning 263,836 words. Next, this research leveraged a general pretrained transformer (GPT) to segment discussion dialogs into topics. A Bidirectional Encoder Representations from Transformers (BERT)-based model was developed to categorize constraint types for each topic. The constraint patterns among meeting attendees were assessed. Furthermore, a GPT-based tool was devised to track root causes, impacts, and solutions for various constraints. Test results revealed an 8.8% improvement in constraint classification accuracy compared with the traditional classification model. An occupational characteristic in constraint discussion was observed in that the management team tended to balance their focus on various constraints, while foremen concentrated on more practical issues. This research contributes to the body of knowledge by leveraging language models to analyze construction planning meetings. The findings facilitate project managers in establishing constraint logs for diagnosing and prognosticating planning issues.