WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 65Citation - Scopus: 81Assessing Coordination Performance Based on Centrality in an E-Mail Communication Network(American Society of Civil Engineers (ASCE), 2015) Doğan, Sevgi Zeynep; Arditi, David; Doğan, Sevgi Zeynep; Erbaşaranoğlu, Bengi; 02.02. Department of Architecture; 02. Faculty of Architecture; 01. Izmir Institute of TechnologyBuilding design and construction require the collective effort of diverse project participants. The coordination performance of these project participants is important for effective management and needs to be assessed periodically. However, there is no uncomplicated quantitative way to measure coordination. Measuring coordination is cumbersome and time-consuming particularly during the project execution phase. This study proposes an easy procedure for monitoring the coordinative performance of project participants. The degree, betweenness, and closeness centrality measures of the project participants in a wayfinding signage project at a major airport construction project are calculated using social network analysis on the e-mail communication network between the participants. A centrality index is defined for each firm based on the average of these three centrality measures. The firm's coordination score is also calculated based on content analysis of the sent and received e-mails between the participants. The coordination scores are found to be highly correlated with the centrality indices. To define the coordinative role of a firm, its centrality index could therefore be measured easily using a simple software and only the number and direction of e-mails exchanged betweenArticle Citation - WoS: 6Citation - Scopus: 13Critical Success Factors of Partnering in the Building Design Process(Middle East Technical University, 2015) Doğan, Sevgi Zeynep; Kılıç Çalğıcı, Pınar; Doğan, Sevgi Zeynep; Günaydın, Hüseyin Murat; 02.02. Department of Architecture; 02. Faculty of Architecture; 01. Izmir Institute of TechnologyThe construction industry is vertically fragmented because of the inherent nature of construction projects, which require planning, design, letting, construction, and operation in distinct phases (Fellows and Liu, 2012; Fong and Lung, 2007). The construction industry is also horizontally fragmented because of the general tendency of participants to work independently in all phases of the project (Fellows and Liu, 2012; Saram and Ahmed, 2001). Given the increasing number of construction projects in the current global environment, geographical fragmentation is caused by project participants that are frequently geographically separated. The construction industry is also temporally fragmented, as the phases of construction projects diverge over an estimated time period (Luck, 1996). According to Evbuomwan and Anumba (1998), the fragmentation in the industry results in costly engineering changes and design iterations, time and cost increases, poor communication between project participants, neglect of the application of sustainability principles throughout the life cycle of the building, and inadequate coordination and integration of the various participants. The root cause of much of these problems encountered in the management of building projects can be traced back to the design phase.Article Citation - WoS: 66Citation - Scopus: 76Using Decision Trees for Determining Attribute Weights in a Case-Based Model of Early Cost Prediction(American Society of Civil Engineers (ASCE), 2008) Doğan, Sevgi Zeynep; Arditi, David; Doğan, Sevgi Zeynep; Günaydın, Hüsnü Murat; 02.02. Department of Architecture; 02. Faculty of Architecture; 01. Izmir Institute of TechnologyThis paper compares the performance of three different decision-tree-based methods of assigning attribute weights to be used in a case-based reasoning (CBR) prediction model. The generation of the attribute weights is performed by considering the presence, absence, and the positions of the attributes in the decision tree. This process and the development of the CBR simulation model are described in the paper. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of residential building projects. The CBR results indicate that the attribute weights generated by taking into account the information gain of all the attributes performed better than the attribute weights generated by considering only the appearance of attributes in the tree. The study is of benefit primarily to researchers, as it compares the impact of attribute weights generated by three different methods and, hence, highlights the fact that the prediction rate of models such as CBR largely depends on the data associated with the parameters used in the model.Article Citation - WoS: 87Citation - Scopus: 100Determining Attribute Weights in a Cbr Model for Early Cost Prediction of Structural Systems(American Society of Civil Engineers (ASCE), 2006) Doğan, Sevgi Zeynep; Günaydın, Hüsnü Murat; Günaydın, Hüsnü Murat; Doğan, Sevgi Zeynep; 02.02. Department of Architecture; 02. Faculty of Architecture; 01. Izmir Institute of TechnologyThis paper compares the performance of three optimization techniques, namely feature counting, gradient descent, and genetic algorithms (GA) in generating attribute weights that were used in a spreadsheet-based case based reasoning (CBR) prediction model. The generation of the attribute weights by using the three optimization techniques and the development of the procedure used in the CBR model are described in this paper in detail. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of 29 residential building projects. The results indicated that GA-augmented CBR performed better than CBR used in association with the other two optimization techniques. The study is of benefit primarily to researchers as it compares the impact attribute weights generated by three different optimization techniques on the performance of a CBR prediction tool.