Comparative Study of Idea Generation between Traditional Value Management Workshops and GDSS-Supported Workshops

Value management (VM) has been widely used to meet challenges arising from the construction industry. However, it has also encountered some problems such as passive participation in VM workshops and a lack of time and information to complete all tasks in the workshops. A group decision support system (GDSS), entitled interactive value management system (IVMS), has been developed by the writers to overcome these problems. This paper starts with an introduction to GDSS and a critical review of technologies used in the process of idea generation in VM workshops. This is followed by findings of a laboratory experiment designed to compare the productivity of traditional brainstorming and brainstorming with IVMS support in VM workshops. The results of the experiment showed that IVMS has a positive influence on idea generation in VM workshops. Finally, the implications of the study and directions for future research are discussed.     

Pedagogy of Teaching Value Management in Postgraduate Construction and Property Program

As value management (VM) has been increasingly applied to enhance value in public construction projects, the core subject entitled “Value Management for Construction and Property” is being offered to postgraduate students in the Department of Building and Real Estate at the Hong Kong Polytechnic University. Under the new outcome-based curriculum, the learning outcomes, pedagogy of teaching VM, and activities of the VM workshops for the subject are described in this paper. The results of a questionnaire survey of the students’ feedback on the performance of the workshops for the academic year 2007–2008 are presented and discussed. Students believed that value management workshops are essential in the curriculum. They expressed that it was a valuable experience to participate in the VM workshop which enabled them to have a better understanding of the subject. Some improvement is also recommended for future organization and management of workshops based on the lessons learned in these workshops.     

Improving group decisions by better pooling information: A comparative advantage of group decision support systems.

This study compared a group decision support system (GDSS) with face-to-face (FTF) group discussion on characteristics of information exchange and decision quality. Participants given conflicting information tended to share more of their unique data and engaged in more critical argumentation when using the GDSS than when meeting FTF. Conversely, when information was consistent among members, there were no such differences between FTF and GDSS groups. The GDSS groups significantly outperformed the FTF groups in agreeing on the superior hidden profile candidate, especially when there was a lack of prediscussion consensus. Individual-level analyses revealed that members of GDSS groups that did not have a prediscussion consensus tended to experience stronger preference shifts toward the group's consensus decision. (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.     

Object-Oriented Evolutionary Fuzzy Neural Inference System for Construction Management

Problems in construction management are complex, full of uncertainty, and vary with environment. Fuzzy logic, neural networks, and genetic algorithms (GAs) have been successfully applied in construction management to solve various kinds of problems. Considering the characteristics and merits of each method, this paper combines the above three techniques to develop an Evolutionary Fuzzy Neural Inference Model (EFNIM). Integrating these three methods, the EFNIM uses GAs to simultaneously search for the fittest membership functions with the minimum fuzzy neural network (FNN) structure and optimum parameters of FNN. Thus, the best adaptation mode is automatically identified. Furthermore, this research work integrates the EFNIM with an object-oriented (OO) computer technique to develop an OO Evolutionary Fuzzy Neural Inference System for solving construction management problems. Simulations are conducted to demonstrate the application potential of the EFNIS. This system could be used as a multifarious intelligent decision support system for decision-making to solve manifold construction management problems.     

Effects of leadership style and anonymity on group potency and effectiveness in a group decision support system environment.

A longitudinal laboratory experiment was conducted to evaluate the effects of leadership style (transactional vs transformational) and anonymity level (identified vs anonymous) on group potency and effectiveness of 36 undergraduate student work groups performing a creativity task using a Group Decision Support System (GDSS). GDSS are interactive networks of computers for generating solutions to unstructured problems. Results indicated that GDSS anonymity amplified the positive effect of transformational leadership on group potency relative to transactional leadership in the group writing session of the task. GDSS anonymity also increased the effect of transformational leadership relative to transactional leadership on group effectiveness. Implications for practice and future research are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Action Research as a Proactive Research Method for Construction Engineering and Management

Academic research in applied disciplines such as construction engineering and management (CEM) has the dual mission of simultaneously contributing to the solution of practical problems and creating theoretical and conceptual knowledge. To do so, appropriate research approaches are needed. However, extant literature in the field has paid little attention to this issue and research methods used have been almost entirely either quantitative surveys or case studies. In this paper, action research (AR) is proposed as an answer to this knowledge gap. AR aims at building and testing theory within the context of solving an immediate practical problem in a real setting. The paper describes the underlying philosophy and application procedure of AR and highlights its strengths and weaknesses. Then, the applicability of the method to CEM is illustrated through a case study of improving access to information to support planning and decision making in a construction owner organization through designing and implementing a data warehouse. The findings indicate that AR is a reliable, structured, and rigorous research approach that is very useful for conducting applied research in construction and enabling academia to influence and improve construction industry practices. It can also effectively help to improve collaboration between academic researchers and industry practitioners in research and development projects.     

RFID+4D CAD for Progress Management of Structural Steel Works in High-Rise Buildings

This research presents a strategy and information system to manage the logistics and progress control of structural steel works under the integrated environment of radio frequency identification and four-dimensional computer-aided design (4D CAD). Considering the characteristics of the manufacturing and erection processes of structural steel works in high-rise building construction from a practical point of view, this research has developed a strategy to support successful application of these two state-of-the-art technologies and has developed an information system to support the logistics and progress management based on this strategy. The results of this research have been validated and verified through real-world applications in two high-rise building construction projects considering realistic constraints. Time study has been conducted to verify the efficiency of the proposed information system. In addition, lessons learned and issues identified through these real-world applications are described and discussed in this paper.     

Critical Success Factors for Value Management Studies in Construction

Value management (VM) studies often face pressure caused by limited time and resources. The identification of key factors for value management success enables appropriate allocation of the limited time and resources in order to achieve better output. Most of the related past work only identified critical success factors for value management studies in general. This paper seeks to distinguish these factors according to their degrees of importance in relation to success. A questionnaire survey was conducted to gather views from experts with experience in value management practice. The findings of the survey reveal the relative importance of the nominated success factors. Two factors that had not been highlighted by previous research are identified as having a significant influence on the success of VM studies. In order to explore the underlying construction among the identified critical success factors (CSFs), factor analysis was adopted to investigate the cluster of the relationship. The results indicate that the success of VM studies requires a combined effort from all parties involved.     

Integrated Decision Support System for Optimal Renewal Planning of Sewer Networks

Municipalities are under increasing pressure to adopt proactive and optimized renewal strategies to reduce the risks, life-cycle costs, and resources needed to maintain acceptable performance and service levels of their infrastructure assets. A new integrated approach for optimal renewal planning of municipal infrastructure systems has been developed. This paper discusses the application of the proposed approach to implement a GIS-based decision support system (DSS) to support the renewal planning of sewer networks. Condition rating, risk assessment, and prioritization techniques are described. A procedure for identifying and selecting the most suitable renewal technologies is also presented. A genetic algorithm-based multiobjective optimization technique is used to find a Pareto front of feasible solutions, each comprising a set of sewers to be renewed each year, along with the associated costs and expected benefits in terms of condition improvement and risk reduction. The paper also presents an example application of the prototype DSS on the sewer network in Regina, Canada.     

The eyes have it: Minority influence in face-to-face and computer-mediated group discussion.

Results of an experiment comparing face-to-face groups with anonymous and identified computer-supported groups challenged theoretical arguments (V. S. Rao & S. L. Jarvenpaa, 1991 ) that computer-based group decision support systems (GDSS) can increase group decision quality by facilitating expression of minority opinions. In groups working on a hidden-profile investment decision task, minority opinion holders expressed their arguments most frequently under anonymous GDSS communication, but the influence of the minority arguments on private opinions and on group decisions was highest under face-to-face communication. These results suggest that the conditions that facilitate the expression of minority arguments may also diminish the influence of those arguments. The implications of these findings for a normative view of social influence, for social presence theory, and for the effects of GDSS on participation rates in group discussion are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Decision Support System for Scheduling Steel Fabrication Projects

One of the most important and difficult problems faced by the steel fabrication industry is the planning and scheduling of shop activities. Competitive pressures force fabricators to disrupt schedules in progress to accommodate frequent requests from key customers for changes in design and/or delivery schedules. Capacity management is a complex problem and is key to proper management of manufacturing/fabrication activities. This paper presents a decision support system for planning and scheduling of steel fabrication projects. Although the immediate application of this approach is steel fabrication, its fundamental heuristic approach can be applied to any construction job shop scheduling exercise. Its main advantage over techniques such as CPM is that it is resource driven; its advantages over simulation techniques are its simplicity and overall schedule development time.     

Knowledge-Enabled Decision Support System for Routing Urban Utilities

This paper presents a Web-based system for supporting the selection of the most suitable routes for buried urban utilities. The aim of the proposed system is to support (not make) decisions through a collaborative semiautomated environment, in which stakeholders can share information and/or study the impacts of different routing alternatives with respect to decision constraints. First, the knowledge relating to route selection for urban utilities is represented through an ontology. The ontology defines the types and attributes of infrastructure products and the surrounding areas. It also defines the impacts of routing options on surrounding areas through a set of decision criteria adopted to evaluate the effectiveness of any route in terms of its potential impacts. A set of constraints are also defined to help represent/study the decision criteria. Second, a GIS-based system has been created to help visualize route data, interact with users, and support the needed discussions among stakeholders. The portal also achieves data interoperability through wrapping existing geospatial data with ontology structures. Finally, a set of reasoners have been created to help quantify/augment some of the constraints. The system is capable of (1)?extracting the attributes of each routing option, (2)?testing the interaction/conflicts between route attributes and the constraints of the surrounding area, (3)?studying the impacts of a route as stipulated in the ontology, (4)?referring users to existing best practices to help enhance routes or address conflicts and, when needed, (5)?develop objective measures for comparing different routes. On the microlevel (street level), route options are evaluated through a “constraint-satisfaction” approach. On the macrolevel (city level), route options are evaluated through a fuzzy inference scoring system. The proposed system focuses on facility life cycle, sustainability, and community impacts. Construction costing, scheduling, labor, and equipment along with other management issues can either be added to the system or, better, analyzed through integrating the system with four-dimensional (4D) modeling tools.     

基于GIS的矿山重大安全隐患决策支持系统探讨

分析矿山重大安全隐患决策支持系统的应用前景,从该系统的总体设计、系统功能结构、数据库建库、系统实现等方面进行探讨,为矿山安全管理信息化设计提供相关参考.     

Dual-Interval Fuzzy Stochastic Programming Method for Long-Term Planning of Municipal Solid Waste Management

In many real-world problems, quality of the available information is generally poor and uncertainties presented as multiple formats may exist in various system components. In this study, a dual-interval fuzzy stochastic programming (DIFSP) method is developed for tackling uncertainties presented as dual intervals and random variables within a multistage context. The developed method is applied to a case study of long-term planning of a municipal solid waste-management system. It has been demonstrated that DIFSP has advantages in addressing the dynamic, interactive, and uncertain characteristics. Moreover, it can reflect dynamics in terms of both waste-flow allocation and facility-capacity expansion through constructing a multilayer scenario tree. With the aid of an interactive algorithm woven with a vertex analysis, solutions for waste-flow allocation and facility-capacity expansion under various uncertainty levels in decision making may be illuminated in support of solid waste-management system planning in urban regions. They can help decision makers to identify desired waste-management policies with minimized system cost and maximized environmental efficiency.     

基于GIS的金属矿山通风信息系统研究

根据金属矿山的通风管理现状,提出信息管理与决策支持为一体的设计模式,并引入地理信息系统.文中详述了金属矿山通风信息系统的构成、功能.应用实践表明,该系统可为金属矿山通风及时实现安全、高效、经济的动态管理.     

Decision Support System for Monthly Operation of Hydropower Reservoirs: A Case Study

This paper presents a decision support system for multipurpose reservoir operation. The mathematical models in the system are formulated for monthly operation of hydropower reservoirs. The key components of the system are four main modules: database management, inflow modeling and forecasting, operation management, and real-time operation. Flexibility is the key feature of the system, providing the users with different decision tools and different indices for measuring the performance of each tool. A cost function is developed based on the present value of the total capital cost and the cost of operation and maintenance of the system. This cost function, which is developed based on “reasonable” estimates of water and energy prices, is used to measure the performance of reservoir operation policies. A utility function based on multicriterion decision making (MCDM) that uses an analytical hierarchy process is also developed. The MCDM utility function enables decision makers to incorporate the priority of different objectives in developing optimal operating policies and can be effectively used when the priority of objectives is not clear and the decision-making process relies mainly on the decision maker’s preferences. Both economic and MCDM utility functions are implemented and coupled with deterministic and stochastic optimization models. The decision support system (DSS) is applied to the largest surface water resources system in Iran, namely, the Dez and Karoon river-reservoir system. The results of the case study have shown that the DSS has been able to significantly increase the long-term power generation of the system while satisfying water demands for different purposes.     

Site Layout Planning using Nonstructural Fuzzy Decision Support System

Site layout planning can affect productivity and is crucial to project success. However, as construction is heterogeneous in the nature of its organizations, project designs, time constraints, environmental effects, etc., site layout planning for each project becomes unique. Affected by many uncertainties (variables) and variations, site layout planning is a typical multiobjective problem. To facilitate the decision-making process for these problems, a nonstructural fuzzy decision support system (NSFDSS) is proposed. NSFDSS integrates both experts’ judgment and computer decision modeling, making it suitable for the appraisal of complicated construction problems. The system allows assessments based on pairwise comparisons of alternatives using semantic operators that can provide a reliable assessment result even under the condition of insufficient precise information.     

Modeling the Construction Management Process to Support Situational Simulations

Construction managers are decision makers who administer nontrivial processes. The replacement of highly experienced construction managers and other construction professionals is a laborious process for the industry. This paper introduces a conceptual framework for the construction management practice that serves as the foundation for the development of situational simulations. Situational simulations are temporally dynamic clinical exercises with the objective of exposing participants to rapidly unfolding events and the pressure of decision making. The application of situational simulations provides construction managers and other decision makers the opportunity of experiencing and responding to risky events without endangering the success of real projects, further enhancing their decision-making skills. The construction management conceptual framework includes a process, a product, and an information model. The analysis of a basic mathematical representation of the process model is the focus of this paper.     

Electimize: New Evolutionary Algorithm for Optimization with Application in Construction Engineering

In nonlinear construction optimization problems, the capability of current optimization algorithms to find an optimal solution is usually limited by their inability to evaluate the effects of changing the value of each decision variable on reaching the optimal solution. This paper presents fundamental research aimed at developing a novel evolutionary optimization algorithm, named Electimize, that mimics the behavior of electrons flowing, through electric circuit branches with the least electric resistance. In the proposed algorithm, solutions are represented by electric wires and are evaluated on two levels: a global level, using the objective function, and a local level, evaluating the potential of each generated value for every decision variable. The paper presents (1) the research philosophy and scope, (2) the research methodology, and (3) the development of the algorithm. The proposed algorithm has been validated and applied successfully to an NP-hard cash flow optimization problem. The algorithm was able to find a better optimal solution and identified ten alternative optimal solutions for the same problem. This should prove useful in enhancing the optimization of complex large-scale problems.