General-Purpose Situational Simulation Environment for Construction Education

The traditional construction education model based on precise well-defined problems and formal definitions is not satisfactorily fulfilling its mission of educating the decision makers of tomorrow. This realization has moved several researchers to explore alternatives where problem solving is carried out in conjunction with the environment, and concepts are embedded in the context promoting learning within the nexus of the activity. Several efforts have been undertaken to develop these environments resulting in a variety of special-purpose situational simulations. However, special-purpose situational simulations exhibit inherent limitations related to their application breadth, flexibility, and promotion of collaborations. These limitations cannot be resolved within the framework of special-purpose learning environments. A general-purpose environment is required to overcome these shortcomings and take full advantage of the situational learning paradigm. This paper describes the conceptual framework and pilot implementation of such an environment called the Virtual Coach.     

Interval Temporal Logic in General-Purpose Situational Simulations

The need for contextually rich educational environments in construction engineering and management calls for the development of situational simulations. Situational simulations emulate real processes and provide temporally dynamic clinical exercises that expose participants to rapidly unfolding events and the pressures of decision making. A survey of simulations of construction management processes and construction operations shows that commonly used discrete event simulation paradigms are unsuitable for representing actions and events in interactive general purpose situational simulations for the construction domain. Instead, this paper argues that a definition of the situational environment using the semantics of constraint satisfaction and an interval representation of time is more appropriate for representing activities, events, actions, and situations relevant to the construction domain. This paper also illustrates how this new paradigm facilitates the implementation of a reasoning mechanism that can be used by a software agent to perceive present actions and predict the future evolution of a simulated environment.     

Multi-Agent Framework for General-Purpose Situational Simulations in the Construction Management Domain

The need for contextually rich education environments in construction management suggests the development of a general-purpose situational simulation framework that can be used by independent developers to build effective training environments. Design and implementation of such a framework involves an understanding of the reasoning processes underlying the construction management domain. These reasoning processes can be isolated using a conceptual classification of problems in the construction management domain into constraint satisfaction and planning. Such a classification allows us to distribute the different reasoning processes to autonomous agents that comprise the foundations of a multi-agent framework for building general-purpose situational simulations. The Virtual Coach is an implementation of the proposed framework. Experimental results from preliminary studies have shown the efficacy of the Virtual Coach as an educational tool.     

Poisson Model of Construction Incident Occurrence

Construction incidents are essentially random events because they have a probabilistic component that causes their occurrence to be indeterministic. Thus, as with most random events, one of the best ways to understand and analyze construction incidents is to apply statistical methods and tools. Consequently, this paper presents a statistical framework based on the modified loss causation model (MLCM). Even though the MLCM has been used for the framework, the approach can be readily adapted for other incident causation models. The MLCM is separated into two basic components: random and systematic. The random component is represented by a probability density function (PDF), which has parameters influenced by the systematic component of the MLCM, while the systematic component is represented by the situational variables and quality of the safety management system. In particular, this paper proposes that the PDF can be represented by the Poisson distribution. Besides being a convenient and simple distribution that can be easily used in applications, the Poisson distribution had been used in various industries to model random failures or incidents. The differences in contexts and the undesirable effects of adopting an unrepresentative distribution will require formal analysis to determine the suitability of the Poisson distribution in modeling the random component of construction incident occurrence. Incident records for 14 major projects were used in the analysis. Hypothesis testing using the chi-square goodness-of-fit and dispersion tests shows that the incident occurrences can be modeled as a Poisson process characterized by some mean arrival rate. The paper also presents some applications of the proposed Poisson model to improve construction safety management, focusing on two specific concepts: the Bayesian approach and the partitioned Poisson.     

Managing Construction Projects Using the Advanced Programmatic Risk Analysis and Management Model

Risk management is an important part of construction management, yet the risk-based decision support tools available to construction managers fail to adequately address risks relating to cost, schedule, and quality together in a coherent framework. This paper demonstrates the usefulness of the Advanced Programmatic Risk Analysis and Management Model (APRAM) originally developed for the aerospace industry, for managing schedule, cost, and quality risks in the construction industry. The usefulness of APRAM for construction projects is demonstrated by implementing APRAM for an example based on an actual building construction project and comparing the results with other risk analysis techniques. The results show that APRAM simultaneously addresses cost, schedule, and quality risk together in a coherent, probabilistic framework that provides the information needed to support decision making in allocating scarce project resources.     

Competency-Based Model for Predicting Construction Project Managers’ Performance

Using behavioral competencies to influence human resource management decisions is gaining popularity in business organizations. This study identifies the core competencies associated with the construction management role and, further, develops a predictive model to inform human resource selection and development decisions within large construction organizations. A range of construction managers took part in behavioral event interviews where staff were asked to recount critical management incidents, decisions, and actions from which their key competencies could be identified. By delineating the sample according to their levels of performance measured against a range of role-specific performance criteria, the competencies defining superior management performance could be determined. These were then used to construct a logistic regression model from which a project manager’s performance can be predicated. The validated results reveal that “self-control” and “team leadership” are the most predictive behaviors of effective project management performance within the framework of the model. The paper explores the potential role and application of the framework to underpin human resource management decision making with regards to recruitment, performance management, succession planning, and resource allocation.     

Scoring Approach to Construction Bond Underwriting

This paper introduces a conceptual scoring-based contractor evaluation system to address the problems created by the subjective nature of surety underwriting process. The methodology presented in this paper provides the surety underwriters with an objective tool for estimating the probability that the evaluated contractor would perform in a satisfactory manner with respect to the main decision factors considered in the bond underwriting process. The proposed model could be used by decision makers to prescreen contractors and make underwriting decisions. The paper first discusses the construction bond underwriting process and provides a brief introduction to the scoring technique as the modeling environment used in this paper. Then, the three steps included in the development of the proposed scoring system are presented in detail followed by an example demonstrating the application of the final product.     

Stochastic Time–Cost Optimization Model Incorporating Fuzzy Sets Theory and Nonreplaceable Front

In a real construction project, the duration and cost of each activity could change dynamically as a result of many uncertain variables, such as weather, resource availability, productivity, etc. Managers/planners must take these uncertainties into account and provide an optimal balance of time and cost based on their own experience and knowledge. In this paper, fuzzy sets theory is applied to model the managers’ behavior in predicting time and cost pertinent to a specific option within an activity. Genetic algorithms are used as a searching mechanism to establish the optimal time–cost profiles under different risk levels. In addition, the nonreplaceable front concept is proposed to assist managers in recognizing promising solutions from numerous candidates on the Pareto front. Economic analysis skills, such as the utility theory and opportunity cost, are integrated into the new model to mimic the decision making process of human experts. A simple case study is used for testing the new model developed. In comparison with the previous models, the new model provides managers with greater flexibility to analyze their decisions in a more realistic manner. The results also indicate that greater robustness may be achieved by taking some risks. This research is relevant to both industry practitioners and researchers. By incorporating the concept of fuzzy sets, managers can represent the range of possible time–cost values as well as their associated degree of belief. The model presented in this paper can, therefore, support decision makers in analyzing their time–cost optimization decision in a more flexible and realistic manner. Many novel ideas have also been incorporated in this paper to benefit the research community. Examples of these include the use of fuzzy sets theory, nonreplaceable front concept, utility theory, opportunity cost, etc. With suitable modifications, these concepts can be applied to model to other similar optimization problems in construction.     

Decision Support System for Residential Land Development Site Selection Process

An important phase within the overall residential land development process is preliminary project planning, which is a highly coordinated effort involving a number of decisions that are made by a variety of individuals. One critical decision faced by the project owner and the development team, during the preliminary planning phase, is the initial selection of the most appropriate site for a proposed conceptual development plan. The scope of this paper deals with (1) formulating a model for the preliminary planning phase of residential site selection; and (2) developing an associated decision support system that can assist the decision makers during this phase of the project. The analytical hierarchy process was the decision making theory used in the site selection decision support system. Analytical hierarchy process uses a hierarchical structure comprising both quantitative and qualitative factors that are based on factual data and the knowledge and experience of the decision makers.     

Mobile Ad Hoc Network-Enabled Collaboration Framework Supporting Civil Engineering Emergency Response Operations

This paper presents an information-technology-based collaboration framework that facilitates disaster response operations. The collaboration framework incorporates a web collaboration service, radio frequency identification (RFID) tags, a building blackbox system (BBS), a geo-database, and a geographic information system (GIS). Through the integration of these technologies, the framework provides a collaboration medium for first responders, including civil engineers, to cohesively respond to disasters. Access to critical building information, such as construction documents, through the BBS supports assessments of building integrity during disaster response. Building assessment information is stored on RFID tags, which are accessible to first responders through digital devices via a wireless ad hoc network. With on-site assessment information shown on a digital map, decision makers locate, collect, and distribute critical resources through the GIS to first responders. In addition, the decision makers at distributed locations evaluate the incident through discussion sessions, hosted by the web collaboration environment, for integrated decision making. Test-bed simulations for the framework have been carried out with encouraging results at the training ground of the Illinois Fire Service Institute.     

Benefits and Barriers of Construction Project Monitoring Using High-Resolution Automated Cameras

A more rapid and widespread use and implementation of technology in construction often fails since its benefits and limitations remain somewhat unclear. Project control is one of the most variable and time consuming task of construction project managers and superintendents and yet continues to be mostly a manual task. Controlling tasks such as tracking and updating project schedules can be assisted through remotely operating technology such as high-resolution cameras that can provide construction management and other users with imaging feeds of job site activities. Although construction cameras have been around for many years, the costs, benefits, and barriers of their use have not been investigated nor quantified in detail. Subsequently, definitions and understanding vary widely, making it difficult for decision makers at the organizational level to decide on the investment in camera technology. This paper reviews the status of high-resolution cameras and their present use in construction. Results of a multiphased survey to industry professionals were collected in order to identify benefits and barriers and develop a cost-benefit model that can be used for implementation technology in construction.     

Prediction of Organizational Effectiveness in Construction Companies

Investigation of literature on organizational effectiveness (OE) reveals that the researchers have been in consensus for the difficulty of defining, modeling, and measuring OE, which is important for attaining high performance. Major focuses of this paper are, therefore, to construct a conceptual framework to model OE, to derive major determinants of OE from this framework, and to measure OE by constructing prediction models based on artificial neural network (ANN) and multiple regression (MR) techniques. Based on the proposed framework that investigates OE from the perspectives of organization and its subsystems, business, and macroenvironments, the most significant variables that determine OE have been collected and used as inputs for the two prediction models, which have been constructed by using the information associated with 116 Turkish construction companies obtained from a designed survey. According to the prediction results and comparative study, ANN slightly outperformed the MR model in terms of errors, correlations between desired versus actual outputs, and relations between input-output parameters. The ANN model is proposed for use as a tool to assess company effectiveness and to guide decision makers about the major determinants of OE to increase firm performance.     

Analysis of Spatial Scenarios Aiding Decision Making for Regional Irrigation Water-Demand Planning

Regional irrigation water-demand planning is utilized to establish appropriate cropping patterns and estimate irrigation water demand. Although optimization methods have been extensively adopted, uncertainties of meteorological conditions and the complexity of spatial contexts make developing explicit and structured decision making extremely difficult. Rather than generating a single optimal solution, decision makers prefer to generate several possible scenarios and compare results. This study proposes a novel spatial scenario-based planning framework, with a database, model base, and scenario-setting modules, to generate flexible spatial planning scenarios for improving irrigation water-demand planning. Possible demand planning scenarios for irrigation managers are discussed. A prototype of the proposed scenario-based framework is implemented on a geographic information system platform to assist in spatial decision making. Demand planning during a drought period for the Chia-Nan irrigation command area, the largest one in Taiwan, is adopted as a case study to demonstrate the proposed framework for spatial scenario analysis.     

Formulating Procurement Selection Criteria through Case-Based Reasoning Approach

An appropriate procurement system is a catalyst to the success of a construction project. In practice, the solutions and outcomes of previous procurement selection decisions could be extremely useful in supporting decision making. As a technique that captures and reuses experiential knowledge, case-based reasoning (CBR) has a high potential for modeling the procurement selection decision within a complex dynamic environment. This paper examines the suitability of CBR approaches for procurement selection. The process involved in procurement selection is examined first. A conceptual framework for case-based procurement selection is proposed. The structure of a prototype model on procurement selection criteria (PSC) formulation is presented in this paper. The model applies the CBR approach to procurement criteria selection irrespective of the variability in the characteristics of the client, project, and external environment.     

Aesthetics, Death, and Landmark Structures: Approach for Values Clarification

The Golden Gate Bridge is an iconic landmark, which has long held the distinction of being the most popular structure in the world to commit suicide. A general process is presented for policy makers’ use to generate conversation and clarify their values in making decisions about public works improvements. This applies particularly well where issues of aesthetics and cost are emotionally and politically charged. The Golden Gate Bridge serves as a case study of how this process can be used. Three design solutions were generated on the basis of architectural concerns and developed in the context of evaluation criteria. A value-based decision analysis approach was taken to determine the preference structure of decision makers involved and to provide a rational framework for further development. Results indicate that existing preferences among decision makers may not be consistent with their public decisions and could be clarified given a more rigorous framework. The do-nothing option is likely to be less preferred to other options given a thorough definition of the acceptance criteria.     

Meaning in the context of stress and coping.

Although theoretical and empirical work on topics related to meaning and meaning making proliferate, careful evaluation and integration of this area have not been carried out. Toward this end, this article has 3 goals: (a) to elaborate the critical dimensions of meaning as it relates to stressful life events and conditions, (b) to extend the transactional model of stress and coping to include these dimensions, and (c) to provide a framework for understanding current research and directions for future research within this extended model. First, the authors present a framework for understanding diverse conceptual and operational definitions of meaning by distinguishing 2 levels of meaning, termed global meaning and situational meaning. Second, the authors use this framework to review and synthesize the literature on the functions of meaning in the coping process and propose a definition of meaning making that highlights the critical role of reappraisal. The authors specify the roles of attributions throughout the coping process and discuss implications for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Decision Support Tool for Life-Cycle-Based Solid Waste Management

Existing solid waste management (SWM) planning software provides only limited assistance to decision makers struggling to find strategies that address their multifarious concerns. The combinatorial nature (many waste items and many management options) and multiple objectives of the SWM problem severely constrain the effectiveness of a manual search process using these tools. Recognizing this, researchers have proposed several optimization-based search procedures. These methods, however, enjoy limited use due to the substantial expertise required for their application. This paper presents a new computer-based decision support framework that addresses these limitations. The new framework integrates process models that quantify the life-cycle inventory of a range of pollutants and costs for an extensive municipal solid waste system, an optimization search procedure that identifies strategies that meet cost and environmental objectives and site-specific restrictions, and a user-friendly interface that facilitates utilization of these components by practitioners. After describing the software design, the use and value of the tool in typical waste management scenarios is demonstrated through a hypothetical, but realistic, case study in which several alternative SWM strategies are generated and examined.     

Monitoring and Evaluation Scheme using the Multiple-Criteria-Decision-Making Technique: Application to Irrigation Projects

The application of monitoring and evaluation (M&E) systems to assess agricultural projects has received some attention in recent years. These systems provide valuable information for managers and decision makers by analyzing the implementation process, the progress of trends, and the long-term and short-term effectiveness of these projects. An algorithm is developed to monitor and evaluate drip and pressure irrigation projects in Iran. Different indicators are identified and the framework of an integrated evaluation system is demonstrated using an analytical hierarchy process for multiple-criteria-decision making. There is much subjective information that is quantified and normalized in order to remove any bias in evaluators’ assessment of qualitative measures or sensitivity to linguistic expressions. The application of this system to rank projects in different regions (zones) in Iran is also presented in this paper. The results have shown the significant value of such systems in providing information and input for different decision-making levels.     

Simulation of Concrete Batch Plant Production

The decision-making process is a very essential part of any construction operation. Simulation can be used as a tool to assist construction managers in making informed decisions. In this paper, simulation is applied to concrete batching operations to analyze alternative solutions and resource management. Data are collected to define activity durations for the plant. A simulation model is constructed for the plant using the MicroCYCLONE simulation system. Based on sensitivity analysis, management tools are constructed to help the decision maker. These tools are a time-cost-quantity chart, a feasible region analysis, and a contour lines chart. Time-cost-quantity and contour lines charts are used for determining production time, production cost, and resources for a required distance from the plant. The feasible region chart is used for determining the range of alternative solutions that can be taken to minimize production time and cost of the available plant resources, according to the required transportation distance.     

Modeling Weather-Sensitive Construction Activity Using Simulation

This paper proposes a framework for simulating weather-sensitive construction projects that are executed under extreme weather conditions. It applies the framework steps to enable simulating and planning pipeline construction activities under severe cold weather conditions. The uncertainties caused by weather, such as extreme cold, heat, wind, or precipitation, can significantly affect a project’s schedule and produce significant deviations from the baseline schedule. The proposed framework structures a project in the way an engineer would approach it, setting out a breakdown of work activities to quantify weather effects and account for their impact on the project baseline. The proposed weather-sensitive construction simulation framework is employed to determine the effects of weather on the construction process of high-density polyethylene (HDPE) pipe installation. The relevant simulation findings are reported to clarify the impact of extreme weather events on construction projects and to assist in project planning and decision support.