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The main goal of this study is to examine the relationships between determinants of safety performance of construction sites. To achieve this goal, 168 observable variables and 16 latent dimensions that affect safety performance of construction sites were collected through extensive literature reviews, expert opinions, and face-to-face interviews. A questionnaire form was developed and administered to construction professionals as a data-collection tool about the observable variables and latent dimensions. A total of 180 responses were achieved through data collection. Relationships between observable variables and latent dimensions of the safety performance of construction sites were studied and a multidimensional safety performance model was proposed. The proposed multidimensional safety performance model was supported by structural equation modeling (SEM) analysis. Moreover, 16 latent dimensions with respect to their relative weights and recommendations for construction safety professionals are provided to improve the safety performance of construction sites. [ABSTRACT FROM AUTHOR]

Construction sector has a great potential to reduce total energy consumption through the techniques applied in sustainable projects. All over the world, policy makers have already realized the potential and begun setting some governmental goals. Since new regulations for achieving sustainability have been recently set to change the conventionally practiced administrative patterns in construction sector, the number of claims related to sustainability features of the construction projects has been growing ever since. Construction contracts are playing a critical role in preventing these types of legal and administrative risks that can lead to claims. As a result, these changes have caused a need for some alterations in industry's contractual practices. Since the alterations are new to the field, one can, however, find only a limited number of researches on studying and analyzing the possible regulatory risks associated with green projects and their consequent probable legal claims. As a result, the present research intends to fill this gap in the literature, not only by identifying such risk factors which may lead to claims in sustainable construction, but also by assessing the criticality of each factor on the basis of the opinions of industry professionals and analyzing these factors with the relative importance index method. The findings of this study aim to increase the level of awareness of construction professionals about such probable risks. By revealing the possible legal risks of sustainable projects, the study shall also assist various parties of a contract in drafting particular conditions accordingly, in order to prevent probable future claims. [ABSTRACT FROM AUTHOR]

It is highly probable to encounter disputes in construction projects and construction disputes are detrimental as they may lead to cost overruns and delays. Knowing the compensation with some certainty can avoid parties from extending inconclusive claims. Decision support systems can be helpful to understand the aspect of the compensation, if any compensation can be acquired. Within this context, the primary objective of this research is to predict the associated compensations in construction disputes by using machine learning (ML) techniques on past project data so that in new projects, decision support can be provided with some certainty via forecasts on the aspect of the compensation. To do this, a conceptual model identifying the attributes affecting compensations was established based on an extensive literature review. Using these attributes, data from real-world dispute cases were collected. Insignificant attributes were eliminated via Chi-square tests to establish a simpler classification model, which was experimented via alternative single and ensemble ML techniques. The Naïve Bayes (NB) classifier generated the highest average classification accuracy as 80.61% when One-vs-All (OvA) decomposition technique was utilized. The conceptual model can guide construction professionals during dispute management decisionmaking and the promising results indicate that the classification model has the potential to identify compensations. This study can be used to mitigate disputes by preventing parties from resorting to unpleasant and inconclusive resolution processes. [ABSTRACT FROM AUTHOR]

The major challenges of project risk assessment may be attributed to the knowledge requirements for determining the level of uncertainty and the development of complex models to predict project outcomes. The duration-cost influence network is an adequate model that can be used for activity-based risk modeling. In this study, a scenario analysis feature is added to this model and a Web-based tool is developed that can be used to calculate risk-adjusted duration and cost, considering the risks affecting cost and duration of individual activities. Monte Carlo simulation is used to create scenarios, and the output of these scenarios is calculated by using the cost-duration influence system that simulates the vulnerability of the project to the identified risk factors. The Web-based tool can be used by decision makers during the preplanning stage of construction projects to estimate the cost and duration implications of various risk occurrence scenarios, determine contingencies, and prepare risk-management plans. [ABSTRACT FROM AUTHOR]

The aim of strategic group analysis is to determine whether clusters of firms that have a similar strategic position exist within an industry or not. Findings of strategic group analysis may further be used to investigate the performance implications of strategic group membership. The objective of this paper is to identify the possible strategic groups that could exist within the Turkish construction industry by using a theoretical framework applicable for the construction industry and alternative statistical cluster analysis techniques. The achieved results pinpoint the existence of three clusters and significant differences between the performances of firms in each cluster. All of the firms in the strategic group that have the highest average performance utilize a quality differentiation strategy and have the necessary resources and capabilities that give them the opportunity to differentiate their services from others. Also, they use a systematic approach and have a collaborative environment for strategic decision making. Findings of strategic group analysis can be used by professionals to understand the current strategic position of a firm within the competitive environment and formulate strategies to shift to a better performing cluster. [ABSTRACT FROM AUTHOR]

Abstract: The bid mark-up estimation is an unstructured decision problem that is usually solved by intuition. The aim of this paper is to present a decision support tool so that bid mark-up values may be estimated in a more systematic way. For this purpose, various factors that may affect the level of risk, opportunity and competition in a project option have been identified. Using the 95 cases obtained from the Turkish contractors working in international markets, a case-based reasoning model (CBR) has been developed to estimate the risk, opportunity and competition ratings. These ratings are further converted to risk and profit mark-up values by using linear utility functions constructed according to the boundary values which were identified by the respondents considering worst, average and best scenarios. The applicability of the model has been demonstrated on a real case study. [Copyright &y& Elsevier]

Where prioritization and selection process of large-scale construction projects is concerned, governments should consider various quantitative and qualitative criteria when choosing the best project alternative. The traditional benefit–cost (BC) analysis has some drawbacks in terms of analyzing qualitative attributes that cannot be easily expressed in monetary terms. To eliminate this limitation, multicriteria decision-making techniques are proposed for the solution of project prioritization problems. In this paper, an analytic network process (ANP) model is developed to demonstrate how the project selection process can be carried out by considering both quantitative and qualitative factors, as well as their interrelations. The decision network is grouped under four subnetworks, namely benefits, costs, opportunities, and risks. The selected alternatives are real highway projects that are in the investment agenda of the Turkish government. Using the proposed network model, four investment alternatives are assessed by a team of experts and achieved results demonstrate that the ranking of project alternatives may significantly change when the ANP model is used instead of the classical B/C approach. [ABSTRACT FROM AUTHOR]

Risk assessment of international projects is a complicated task because of the sensitivity of project success related to country specific risks as well as project risks. Decision makers face the difficulty of weighing project opportunities against risks and determining attractiveness of projects while giving bidding decisions. The aim of this paper is to propose a methodology for risk and opportunity assessment of international projects. The proposed model uses an analytic hierarchy process for calculation of risk and opportunity ratings. A risk breakdown structure, specific to international construction projects, is proposed as well as a list of factors that affect the ability of construction companies to manage risk. An application of the proposed methodology is demonstrated by using real data supplied by a construction company that is experienced in international markets. Ranking of project options is made according to the opportunity and risk ratings that are calculated by using the proposed methodology based on the judgments of company professionals. [ABSTRACT FROM AUTHOR]

A conceptual framework has been developed to investigate value innovations within construction companies. A visual metaphor has been defined to model the innovation system where the elements of the model are objectives, strategies, environmental barriers/drivers, and organizational factors. The major idea is that none of the elements of the model alone can explain the innovative capability, and elements as well as their interrelations should be considered concurrently to investigate how the innovation system works in construction companies. An application of the framework has been demonstrated by 11 cases taken from the Turkish construction industry. General findings of the research have been reported as well as specific company examples that demonstrate the major mechanisms of the innovation system. The research findings have revealed that environmental factors can have both hindering and supporting impacts on the innovation system, depending on other elements of the framework. The type of innovations is strongly related to company targets, strategies, strengths/weaknesses, and environmental factors. Moreover, matching of appropriate strategies with organizational properties leads to an increase in innovative capacity. [ABSTRACT FROM AUTHOR]

In Turkey, achievement of acceptable levels of quality in the construction sector has long been a problem. Great expenditures of time, money, and resources are wasted each year due to inefficient or nonexistent quality levels prevailing in the industry. The situation is even worse in the case of mass housing projects addressing to low and middle income groups. It is the purpose of this paper to identify the type of deviations resulting in rework in mass housing projects, since construction firms can only increase their profit margins by paying more attention to the deviation types. More importantly, firms can improve their images in the sector and thus, can take new projects. To achieve the objective mentioned above, data have been derived from 400 cases by means of a questionnaire containing 108 questions, and results of this survey were evaluated by several statistical techniques. It is concluded that households are not completely satisfied from the quality of products and/or services delivered within their housing units. In future studies, the causes and costs of the rework should be researched for better understanding the results together with the remedial measures being implemented. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Bidding for international construction projects is a critical decision for companies that aim to position themselves in the global construction market. Determination of attractive projects and markets where the competitive advantage of a company is high requires extensive environmental scanning, forecasting, and learning from the experience of competitors in international markets. In this paper, a neuronet model has been developed as a decision support tool that can classify international projects with respect to attractiveness and competitiveness based on the experiences of Turkish contractors in overseas markets. The model can be used to guide decision makers on which type of data should be collected during international business development and further help them to prepare priority lists during strategic planning. Information derived from the model demonstrates that the most important factors that increase attractiveness of an international project are availability of funds, market volume, economic prosperity, contract type, and country risk rating. Similarly, level of competition, attitude of host government, existence of strict quality requirements, country risk rating, and cultural/religious similarities are the most important factors that affect competitiveness of Turkish contractors in international markets. [ABSTRACT FROM AUTHOR]

The construction industry is overwhelmed by an increasing number and severity of disputes. The primary objective of this research is to predict the occurrence of disputes by utilizing machine learning (ML) techniques on empirical data. For this reason, variables affecting dispute occurrence were identified from the literature, and a conceptual model was developed to depict the common factors. Based on the conceptual model, a questionnaire was designed to collect empirical data from experts. Chi-square tests were conducted to reveal the associations between input variables and dispute occurrence. Alternative classification techniques were tested, and support vector machine (SVM) classifiers achieved the best average accuracy (90.46%). Ensemble classifiers combining the tested classification techniques were developed for enhanced prediction performance. Experimental results showed that the best ensemble classifier, obtained from the majority voting technique, can achieve 91.11% average accuracy. Based on Chi-square tests, the most influential factors on dispute occurrence were found as variations and unexpected events in projects. Other important predictors were all related to the skills of the parties involved. This study contributes to the construction dispute domain in three ways: (1) by proposing a conceptual model that combined the diverse efforts in the literature for identifying variables affecting dispute occurrence; (2) by highlighting the influential factors, such as response rate and communication skills, as indicators for potential disputes; and (3) by providing an empirical ML-based model with enhanced prediction capabilities that can function as an early-warning mechanism for decision-makers. [ABSTRACT FROM AUTHOR]

In the globalized business world, construction companies start to seek new opportunities to invest on an international basis in order to gain profit. Therefore, construction companies have to conduct not only national projects but also international projects to be competitive. However, although these international projects can be profitable, the construction companies face many challenges in the management of these projects due to the country-specific problems and conditions. This can lead to variation in the management of similar projects conducted in different countries. In particular, cost estimation in different countries is a challenging task for construction companies. Therefore, in order to provide insights about construction cost in different countries, different organizations publish construction cost indices. However, some criticisms related to the reliability and usability of these indices are stated. In this study, a new concept, called a cost map, is proposed by developing a framework based on twelve macro level parameters. The cost map is applied to 37 European countries. The data related to these parameters are collected using different databases. European countries are clustered by using a self-organizing map. As a result of this study, the cost map is determined as a reliable and convenient tool for a cost comparison. [ABSTRACT FROM AUTHOR]

During the feasibility study of BOT (Build-Operate-Transfer) hydropower investments, the selling price of energy is the most critical parameter that impacts the net present value (NPV) estimated by the investors. Investors usually consider the price of energy guaranteed by the government during their feasibility studies which is the worst case scenario. However, it is apparent that negotiations that take place between investor and broker determine the price of energy which is affected by various sources of uncertainty associated with the energy demand and country conditions. The objective of this study was to make a realistic estimate of the investor's selling price by modeling the negotiation process between investor and broker using a multi-agent system (MAS). Thus, the factors affecting the negotiation process were identified, a negotiation protocol between the parties was set up, negotiation scenarios were determined, and modelled by using a MAS. The model was tested on a hydropower investment in Turkey and generated more realistic results compared to the current practice. Investors and brokers may benefit from this study because it considers the potential changes in the market as well as the negotiating postures of parties under different scenarios. [ABSTRACT FROM AUTHOR]

Many factors, such as unforeseeable events, managerial and financial problems of contractors, insufficient technical capacity of site teams of contractors or Consultants, and so on, may lead to delays in construction projects. Proper analysis of compensability and quantum of a delay event is of prime importance. Any delay analysis application can be considered as a result of the combination of contract documents, scheduler, record-keeping mechanism at the site, communication among project participants, delay analyst, and delay analysis methodology. The main purposes of this study are to identify the shortcomings frequently encountered in the implementation of delay analysis applications in all stages of a construction project, to address the responsible element, and to propose a set of rules to overcome these shortcomings and obtain accurate and reliable results. For this purpose, 17 shortcomings were identified. Moreover, an integrated approach is developed which is composed of a set of rules solving all of the identified shortcomings, and a flowchart guiding the parties from scratch until the end of the project. This study is unique in its nature as it encompasses all stages of a construction project that contribute to a delay analysis application. [ABSTRACT FROM AUTHOR]

Energy demand has been increasing, but traditional sources of energy are depletable. New investments are needed in renewable energy production. Hydroelectric power plants are often considered a feasible renewable source of energy and are often organized as a public private partnerships (PPP). However, risk factors stemming from the macro environment as well as project conditions should be considered in performing feasibility studies. The objective of this study was to develop a method that can be used to predict the profitability of hydropower investments considering the relevant risk factors. To that end, a cash flow that represents the construction and operation period is set up, the risk factors involved in such projects are identified, the impacts of these risk factors on the cash flow parameters are assessed, and Monte Carlo simulation is performed to estimate the net present value (NPV) of a hydropower investment. The proposed method was tested in a hydropower investment located in Turkey and generated credible results that could be of great benefit to potential investors operating in similar conditions. The primary contribution of this research is the creation of a method that allows investors to assess the profitability of a hydropower investment by using a stochastic approach. [ABSTRACT FROM PUBLISHER]

Performance of the construction projects have been criticized for many years due to their low productivity rates and cost overruns as well as significant delays. Increasing number of dissatisfied customers compel practitioners to reform conventional practices of construction management. Lean construction has emerged as a result of these efforts in the industry. However, there are limited number of studies that demonstrate the practical benefits of lean construction applications. The aim of this paper is to untangle practical applications of lean construction and to reveal their benefits. A methodology was developed to compare the lean and non-lean scenarios of a residential building project by means of Monte Carlo simulation. Simulation models were generated through regular meetings held with construction planning experts. Research findings demonstrate that application of lean construction principles have a potential to improve the performance of projects by reducing both the total project duration and its expected variation. In addition, the study revealed that utilization of practical lean construction principles may result in a considerable amount of time reduction in wall construction and plastering activities of residential building projects. Although the findings of this study cannot be generalized, they are expected to encourage practitioners to adopt lean construction principles. [ABSTRACT FROM PUBLISHER]

The importance of fit between an organization's implementation of project management (PM), and its business level strategy is emphasized in the literature. However, there are a limited number of studies investigating the relationship between business level strategy and implementation of PM in the construction industry. This paper aligns one of the business strategies, namely differentiation, with the PM process. A framework representing differentiation in the construction industry is proposed in this study. Structural equation modelling (SEM) is used to validate the relationship between differentiation and the PM process. The results show that a relationship between differentiation strategy and PM exists. The two types of differentiation are revealed, namely “product variety and speed-related differentiation” (PSD) and “quality and image-related differentiation” (QID). The companies trying to differentiate based on PSD should focus on cost, time and quality management. Change management and project planning are identified as important drivers of differentiation based on PSD. On the other hand, the companies trying to differentiate on QID should consider health, safety and environmental issues as well as quality. Companies should also manage their resources effectively to support the PM process that in turn leads to successful differentiation. Companies can utilize the research findings as a guideline while formulating their differentiation strategies. [ABSTRACT FROM AUTHOR]

Abstract: Effective risk assessment and management is critical for success in international construction projects. This paper proposes a knowledge-based risk mapping tool for systematically assessing risk-related variables that may lead to cost overrun in international markets. The tool uses an ontology that relates risk and vulnerability to cost overrun [1] and a novel risk-vulnerability assessment methodology [2] to estimate potential risk paths that may emerge in international construction projects. The tool has been developed in collaboration with an industrial partner, a construction management company that gives risk management consultancy services to Turkish contractors working in international markets. The tool has been designed by using the previous projects of the partner firm as test cases and preferences of company professionals are taken into account while determining the functions of the tool. As the reliability and usability of the tool significantly depend on the subjective evaluations of users about level of vulnerability and magnitude of potential risk events, a lessons learned database has been incorporated into the tool so that decision-makers may refer to risk event histories of previous projects to make estimations about forthcoming projects. In order to evaluate the usability of the tool, a usability test has been conducted by eight construction experts. Usability test results demonstrated that the tool can be utilized for prediction of probable risk paths and their impact on cost. Results of a case study, a building project in Serbia, have also been reported in this paper to demonstrate the functions and the performance of the tool. Although the usability and reliability test results are satisfactory, the tool should be seen as an initial platform which should be improved by increasing its “intelligence” by high quality and enough number of risk event histories, and also customized according to user preferences as well as company policies. [Copyright &y& Elsevier]

Investments in renewable energy resources have become inevitable due to increasing energy demand and energy prices, diminishing non-renewable energy resources, and the outgrowth of carbon footprints. Photovoltaic (PV) systems offer high solar energy potential in sustainable energy production whereas their high initial costs necessitate critical strategic valuation of investments. Valuation with conventional methods has been challenging due to existence of uncertainties such as fluctuating PV panel prices, changing meteorological conditions with certain effects on power generation, and governmental policies on energy market regulations. This study aims to propose a real options approach to valuation of residential rooftop PV system investments considering these uncertainties and demonstrate benefits of this approach with an application on the residential PV investment decisions in Turkey. The proposed method, Real Options Valuation (ROV) with Least-Squares Monte Carlo Simulation (LSMC) considers the deferral option of the investor by utilizing stochastic simulations, the discounted cash flow method, linear regression, and backward dynamic programming and thus evaluates the effects of uncertainties on financial attractiveness of residential PV investments. The case study findings proved that ROV with LSMC having a 7-years deferral option supported the investment decision with realizable cost-effective options while "NPV method" resulted in an infeasible investment. Scenario analysis was also conducted to explore policy options that can be used to promote solar energy investments in Turkey. This study has a potential to have practical contributions for investors as well as implications for policy-makers. [Display omitted] • Considering strategic value of flexibility for investment time with deferral option. • Handling uncertainties using stochastic simulations. • ROV method can prevent faulty rejection of investments with classical methods. [ABSTRACT FROM AUTHOR]

Multiagent systems (MASs) consist of several autonomous entities, called agents, that interact with each other to either fulfill their own interests (competition) or reach a common goal (cooperation). In MASs, negotiation is the key form of interaction that enables groups of agents to arrive at a mutual agreement regarding some belief, goal, or plan. The aim of this study is to develop a MAS that simulates the negotiation process between parties (mainly contractor and client) about risk allocation and sharing of cost overruns in construction projects. The MAS was developed using three different negotiation protocols: time-dependent concession, Zeuthen's strategy, and Zeuthen's strategy with Bayesian learning. Sensitivity analysis was carried out to test the effect of reservation value, first-offer value, and negotiation protocol on the settlement amounts. The model was also tested on three hypothetical cases. Results show that it is mainly the reservation value that determines the settlement amount of the negotiation. The developed system can be used by decision makers to understand how the risks and associated costs are shared between parties under different scenarios. [ABSTRACT FROM AUTHOR]

Abstract: Strategic group analysis comprises of clustering of firms within an industry according to their similarities with respect to a set of strategic dimensions and investigating the performance implications of strategic group membership. One of the challenges of strategic group analysis is the selection of the clustering method. In this study, the results of the strategic group analysis of Turkish contractors are presented to compare the performances of traditional cluster analysis techniques, self-organizing maps (SOM) and fuzzy C-means method (FCM) for strategic grouping. Findings reveal that traditional cluster analysis methods cannot disclose the overlapping strategic group structure and position of companies within the same strategic group. It is concluded that SOM and FCM can reveal the typology of the strategic groups better than traditional cluster analysis and they are more likely to provide useful information about the real strategic group structure. [Copyright &y& Elsevier]

In this study, an analytic network process (ANP), which can handle the interrelations between risk related factors, is proposed as a reliable technique for measuring the level of risk associated with international construction projects. Within this context, ANP is used to derive the relative priorities of risk factors as an input to a decision support tool, which can be utilized during bidding decisions. The decision support tool may help a decision maker to estimate the level of risk so that alternative projects may be ranked with respect to their risk levels and appropriate contingency values may be defined after a bid decision is given. The tool has a database in which risk information of the rated projects can be stored for future use. The reliability of the tool was tested on eight real cases and satisfactory results were achieved in estimating the risk level. [ABSTRACT FROM AUTHOR]

Abstract: One of the most important phases in the construction industry (CI) is the bidding process. During the bidding process, selecting the most appropriate sub-contractors (SCs) for the relevant sub-works is highly critical for the overall project performance. In order to select the most appropriate SCs for the project and prepare the most realistic and accurate bid proposal, general contractors (GCs) have to know all financial, technical and general information about these SCs. Within this context, GCs should consider several factors in the selection process. These factors may include the quality of production, efficiency, employment of qualified members, reputation of the company, accessibility to the company, completion of the work on time etc. This paper proposes a web-based sub-contractor evaluation system called WEBSES by which the SCs can be evaluated based on a combined criterion. It enables GCs to select the most appropriate SCs for their relevant sub-works, speed up the selection process and gain time and cost savings during the bidding process. [Copyright &y& Elsevier]

Strategic collaborations such as joint ventures (JVs) have become an important way of exploiting business opportunities for construction companies. However, such entities are difficult to manage due to their composite structures, which entail diverse organizational cultures, styles, and objectives. Therefore, measurement of JV performance has been an interesting research topic although there is no consensus on the definition, measures, and variables of performance yet. Considering the inherent complexities of the construction projects, only an adequate combination of criteria allows assessing the international construction joint venture (ICJV) performance. Within this study, an analytic network process model is developed to examine the links between the determinants of performance and to observe the influences of these factors on the ICJV performance. As a result, interpartner relations, structural factors and interpartner fit are found to be the most important determinants of ICJV success. Effectiveness of conflict resolution and control mechanisms contribute significantly to ICJV performance. Cultural fit is the most important fit that should be attained between the partners. The performance of the model is tested on eight real construction projects and satisfactory results are obtained. [ABSTRACT FROM AUTHOR]

This paper presents a quantitative methodology to determine financial impacts of the risk factors during the bidding stages of international construction projects. Project and country data of 26 construction projects from 21 countries were collected for evaluation of the international risk factors. The factors impacting cost contingency were identified using correlation and regression analysis techniques. The results indicated that four factors had major contributions for explaining the variations in the contingency levels. A regression model including the significant factors was developed to support bidding contingency decisions. The methodology presented provides a robust and practical statistical approach for determination of contingency by focusing on important risk factors. Details regarding model development and validation are presented along with a discussion on study limitations. [ABSTRACT FROM AUTHOR]

To increase the quality of decision making in construction companies, organizational memory should be enhanced and utilized effectively. Experiences of other companies should constitute an important part of organizational memory so that a construction company may have the chance to learn from the experiences of others and modify its behavior in the light of acquired knowledge. Within this study, a case-based reasoning (CBR) decision support tool is constructed to demonstrate how experiences of competitors in international markets may be used by contractors, to support international market selection decisions. 215 cases from the Turkish construction industry have been used to build the model, namely CBR-INT. The reliability of CBR-INT in predicting potential profitability of international projects and the level of competitiveness of Turkish contractors is around 90%. Moreover, CBR-INT has proven to be an effective tool for practitioners due to its high explanation capability and ease of use. Using the conceptual framework of CBR-INT, different CBR models can also be constructed for other countries. [ABSTRACT FROM AUTHOR]

Disputes, frequently encountered in construction projects, can substantially affect project success, necessitating a clear understanding of how and why disputes occur. Previous studies on disputes mostly yielded exhaustive lists or hierarchies of possible causes of disputes, which can hardly be used to understand how these causes come together to form a dispute. To address this gap, this study provides an alternative approach to understand the underlying causes of disputes, and their relationship within a specific context, using causal map analysis. This study is conducted using causal mapping approach to understand dispute emergence patterns in practice. Initially, a causal map of construction disputes is developed based on literature. The map is altered and verified through an expert workshop, considering projects contracted through FIDIC Yellow Book. The causal representation of the dispute emergence patterns highlights the importance of pre-construction studies, people factor, and contract terms. It is revealed that significant causes are either result of a chain of preceding factors or are triggers for further ones. This finding reinforces that the occurrence of disputes does not only depend on individual causes; rather, these causes combine with a series of other factors for a dispute to occur. [ABSTRACT FROM AUTHOR]

Although complexity and risk are inherent characteristics of megaconstruction projects, existing project management approaches fail to incorporate complexity-based thinking into risk management. Complexity is usually considered as the source of risk events, along with uncertainty. However, prevailing risk management practices are oriented toward only handling the uncertainty. The lack of integration between the complexity and other risk-related concepts leads to unrealistic project risk assessments and the formulation of imperfect management strategies. The aim of this research is to explore the relationship between complexity and risk in detail and propose an integrated risk assessment approach. For this purpose, a mixed-methods research approach was adopted to collect data via semistructured interviews and survey questions. Data obtained from 11 megaconstruction projects carried out by Turkish contractors were analyzed in two ways. Quantitative findings served to verify the relationship between complexity and risk in numerical terms, whereas qualitative findings were utilized to develop a framework that explains the nature of this relationship. The conceptual framework represents the links between complexity and risk in megaconstruction projects, together with uncertainty and management strategies. The existence of causal relations between these concepts may constitute a significant challenge during the risk assessment. Therefore, an integrated risk assessment process (IRAP) was proposed so that megaproject practitioners could develop better risk management plans. The findings of this research were based on megaconstruction projects, but they may also apply to other types of projects. [ABSTRACT FROM AUTHOR]

Investigation of market entry strategies is critical for the success of international contractors. Establishing partnerships is among the most effective vehicles of operating in international markets. The major objective of this paper is to analyze the partnership behavior of contractors in overseas projects. In this respect, social network analysis (SNA) was used to better understand the collaborative project networks in different markets and for projects of differing sizes. A database was developed based on the collaborative international construction projects where Turkish firms and their non-Turkish partners were involved. A total of 449 projects carried out in 46 countries were used for the analysis. The findings of the study suggest that contractors adopt different strategies depending on the market and project characteristics. The majority of the companies tend to remain in the same markets; they keep working with the same partners or choose local partners; and engage with multiple partners in more complex projects. This study is expected to help contractors reflect on their internationalization decisions and devise appropriate strategies to establish project networks. [ABSTRACT FROM AUTHOR]

Risk, complexity, and uncertainty are inherent components of megaprojects due to their unique features. However, existing project management practices lack a structured synthesis of these concepts, which leads to unrealistic risk assessments, ineffective management strategies, and poor project performance. In order to fill this gap, this research aims to develop a holistic risk quantification approach incorporating risk-related concepts. For this purpose, a conceptual risk assessment process developed for mega construction projects was operationalized with an Analytic Network Process (ANP) model. The weights of the risk sources in the ANP model were determined by the domain experts through a two-round Delphi study. With the purpose of improving the efficiency and reliability of the knowledge elicitation process, the Delphi study was supported by an interactive data collection tool capable of ANP calculations. The resulting model helped to prioritize the risk sources in mega construction projects. The validity of the findings was tested through the data of 11 mega construction projects. Validation studies revealed the potential of the ANP-based model in quantifying the project risks. Hence, the novel approach proposed in this study is expected to contribute both to the literature by unveiling the interactions between risk-related concepts and to the practitioners by assisting them in assessing the project risks more realistically. Although the risk quantification model has been developed for mega construction projects, it can also be implemented in other project-based industries with minor modifications. [ABSTRACT FROM AUTHOR]

In case of an emergency in a building, first responders need to know current blockages in the building (e.g., blocked passageways and exits) and safe evacuating paths so that the occupants can be guided to the unblocked exits and safe paths toward those exits. To automatically determine blockage levels at buildings, a system that fuses data from multiple sensors and video camera was proposed. A prototype was developed and tested on an experimental model of a pilot building's hallway. A series of damage tests were conducted on the hallway model and recorded by the sensors and the video camera. Individual performances of sensors and video camera were evaluated, and a decision tree method was used to fuse sensor and video camera data for estimating the level of blockage in the hallway for different damage combinations applied on building components. The results demonstrated the technical feasibility of the proposed system and the findings of the decision tree highlight that by using less number of sensors, a cost-effective configuration can be achieved. The estimated blockage information can be used to create a topological map of the damaged building, indicating safe paths toward available unblocked exits. [ABSTRACT FROM AUTHOR]

International construction projects generally involve participants from different cultural backgrounds. In this type of projects, national culture can significantly influence knowledge sharing between individuals. This research contributes to the literature by providing a deeper understanding of cultural issues that influence knowledge sharing in international construction projects. The research was carried out in three international construction joint ventures located in Qatar, Libya, and Bulgaria. A mixed method design was used to better understand the research problem and strengthen the findings. The findings are interpreted through the cultural dimensions of Hofstede and Hall. Based on the analysis, language and communication difficulties, trust, motivation, and personal relationships were found as the critical barriers to successful knowledge sharing in multicultural project teams. Findings from this study can help managers to better understand the role of national culture in knowledge sharing in the context of improving project performance. [ABSTRACT FROM AUTHOR]

Although the construction industry is critical for sustainability goals due to the high amount of waste it generates, its waste management performance is still not at the desired level. One of the main reasons for this can be attributed to the lack of enough knowledge of construction companies on the sources/reasons of waste and amount of waste. The major aim of this study was to develop a knowledge-based tool for capturing, storing, and disseminating waste-related knowledge for prefabricated steel construction projects. The developed tool can be used for waste estimation, monitoring, and minimization of all materials used during different phases of prefabricated steel structure projects based on the data captured from current and previous projects. One advantage of the tool is the integration of all processes of waste management, which have been usually considered independently in previous studies. Moreover, being a knowledge-based tool, it can increase awareness and learning ability of companies about waste and its management. Finally, although the process model of the tool is generic and can operate in alternative domains, the tool is applicable for only prefabricated steel projects. It is believed that the process model and the tool presented in this paper can be further customized for different project types and considering different company needs. • The process model for material waste management in prefabricated steel structure projects is developed. • A knowledge-based material waste management tool is developed as a web-based tool. • The tool integrates three material waste management mechanisms, namely waste estimation, waste monitoring, and waste analyzing. • A similarity assessment method was used to estimate material waste and monitor material waste management performance. • The tool is validated by five professionals from three construction companies. [ABSTRACT FROM AUTHOR]

Economic globalization is increasingly affecting both the construction industry and academia. It is changing the traditional roles of civil engineers and construction managers. Cross-cultural collaboration and communication skills, multinational team management skills, the ability to overcome the social challenges of geographically distributed teams, and familiarity with construction materials, standards, and methods of foreign countries are vital for modern construction professionals. However, the traditional skills and education style of engineers and construction managers do not equip them to successfully deal with such issues. This paper describes the experiences of a university course International Collaborative Construction Management that was developed to educate the next generation of civil engineers to be more internationally savvy. Throughout the three years that the course has been conducted to date, students in Turkey, the United States, Israel, and Brazil were grouped in multinational teams. They collaborated to develop construction schedules, cost estimates, risk assessment plans and response strategies and to prepare bid documents for actual construction projects. Within the context of this course, students were introduced to the different challenges of cross-cultural collaboration and improved their technical/managerial skills through direct involvement in hands-on experiences. [ABSTRACT FROM AUTHOR]

Risk management is about identifying risks, assessing their impacts, and developing mitigation strategies to ensure project success. The difference between the expected and actual project outcomes is usually attributed to risk events and how they are managed throughout the project. Although there are several reference frameworks that explain how risks can be managed in construction projects, a major bottleneck is the lack of a common vocabulary for risk-related concepts. Poor definition of risk and patterns of risk propagation in a project decrease the reliability of risk models that are constructed to simulate project outcomes under different risk occurrence scenarios. This study aims to extend previous studies in risk management by presenting an ontology for relating risk-related concepts to cost overrun. The major idea is that cost overrun depends on causal relations between various risk sources (namely, risk paths) and sources of vulnerability that interfere with these paths. Ontology is used to develop a database system that represents risk event histories of international construction projects and to construct a model for estimation of cost overrun. It will form the basis of a multiagent system that can be used to simulate the negotiation process among project participants about sharing of costs considering the risk allocation clauses in the contract, sources of vulnerability, and causal relations between risk events and their impacts. The ontology is constructed by interaction with Turkish contractors working in international markets and extensive literature review on risk-related concepts. The validation test results provide evidence that the ontology is fairly effective to help Turkish contractors to assess cost overrun by considering sources of vulnerability and risk in international construction projects. [ABSTRACT FROM AUTHOR]

Measuring the performance of joint ventures has been an important research topic for a few decades. No consensus on an appropriate definition and measurement of performance of international joint ventures (IJVs) has yet emerged, and the validity of the underlying measures is still questionable. In this study, the construct validity of measures that define IJV performance in construction is evaluated using data obtained through a questionnaire survey. A second-order performance construct is proposed, which is measured by means of project performance, partner performance, performance of IJV management, and perceived satisfaction with IJV. The validity of the performance measures is evaluated by means of tests that assess content validity, reliability, and convergent and discriminant validity. The findings reveal that all proposed indicators are valid measures of IJV performance and that they correspond to different dimensions of performance. This research is expected to trigger further work on developing a multidimensional performance measure for IJVs in construction. In addition, the findings can help practitioners reflect on how they operate and measure the success of their IJVs. [ABSTRACT FROM AUTHOR]

International joint ventures (IJVs) have become popular because of their importance as a strategic alternative in global competition. The measurement of the performance of IJVs has been an important research topic for a few decades, however there is no consensus on an appropriate definition and measurement of IJV performance. In this study, a model is proposed to assess IJV performance in construction. The validity of the proposed drivers and measures of performance is investigated and relationships between them are analyzed. The effects of interpartner fit/relations, structural IJV characteristics, host country factors, and project-related factors on IJV performance are examined through a questionnaire survey. IJV performance is defined by a four-dimensional construct that considers the performance of the project, the IJV partners, the IJV organization itself, and the perceptions of the IJV partners. The results point out the significance of the interpartner fit and the quality of partner relations for a successful IJV operation. The findings of the study also suggest that project-related factors have a moderate influence on IJV performance. In a properly designed IJV structure, partners with compatible skills, resources, and cultures are found to maintain good relations and are expected to achieve greater IJV success. [ABSTRACT FROM AUTHOR]

Globalized competition and customer needs forced construction companies to measure their performance beyond the financial measures such as profitability, turnover, etc. As qualitative determinants were added to measurement systems, their investigation and evaluation became a major area of research. In this study, the impact of “resources and capabilities,” “strategic decisions,” “project management competencies,” and “strength of relationships with other parties” on “company performance” was investigated. A questionnaire survey was administered to 73 Turkish contractors and the results of the survey were analyzed using structural equation modeling. The findings indicate that, as expected, resources and capabilities and strategic decisions have an important and direct impact on company performance, whereas project management competencies and strength of relationships with other parties impact company performance only indirectly, through their impact on companies’ resources and capabilities and strategic decisions. [ABSTRACT FROM AUTHOR]

Joint ventures have become popular because of their importance as a strategic alternative in global competition. One of the reasons why international joint ventures (IJVs) are difficult to manage is because the cultural distance between IJV partners has significant impact on alliance performance. Since construction projects are highly sensitive to external risks, the effect of the culture in the location in which the IJV operates is also significant. In this study, the effect of cultural similarity/difference relative to the national and organizational characteristics of partner companies on IJV performance is examined through a questionnaire survey. The impact of the cultural similarity/difference between an IJV partner and the host country is also assessed. The results of the study suggest that differences in organizational culture have a greater impact on IJV performance than differences in national and host country culture. The findings also reveal that similarity between the national cultures of IJV partners has a negative effect on IJV performance. The analysis of the data failed to provide evidence that IJV performance is affected by differences between the culture of the host country and the culture of an IJV partner. [ABSTRACT FROM AUTHOR]

Managing knowledge effectively is critical to the survival and advance of a company, especially in project-based industries such as construction. However, capturing knowledge in construction projects is a tedious task, as knowledge is usually experience based, tacit, and hard to pass on to others. In this study, a survey was carried out among eight leading Turkish construction contractors that are operating within the international construction market. The specific objectives of this survey are to find out how the tacit and explicit knowledge are captured, stored, shared, and used in forthcoming projects, as well as major drivers and barriers for knowledge management. Based on the survey, it was determined that most of these firms do not have a knowledge management strategy and a systematic way of capturing and storing tacit knowledge. A conceptual framework is proposed to formalize the knowledge-capturing process within construction companies. To demonstrate how the conceptual framework can be implemented in practice, a Web-based system, namely, Knowledge Platform for Contractors (KPfC) is presented. It is hypothesized that KPfC can be used to manage both tacit and explicit knowledge effectively in construction projects. [ABSTRACT FROM AUTHOR]

Joint ventures have been an important research topic over the last few decades primarily because of their importance as a strategic alternative in global competition. Due to the inherent complexities of international joint ventures (IJVs), involving a mixture of different managerial systems, attitudes, and business strategies, such entities are very difficult to manage. In this study, the effect of strategic, organizational, and cultural fit between IJV partners and of interpartner relations on IJV performance is examined through a questionnaire survey. IJV performance is measured by means of two constructs: “project performance” and “performance of IJV management.” The results point out the significance of the quality of partner relations for a successful IJV operation. Findings of the study also suggest that the level of organizational fit between the partners has a moderate influence on IJV performance. It was observed that strategic fit between IJV partners affects interpartner relations extensively, which in turn affects IJV performance. IJV partners with compatible technical and managerial skills, financial resources, organizational size, workload, and project experiences are expected to achieve greater IJV success. [ABSTRACT FROM AUTHOR]

Organizational learning has been identified as a core competency for project-based companies with industry specific challenges. In this study, it is hypothesized that a web-based lessons learned management system may help construction companies to manage lessons learned effectively. A lessons learned management process model (LLMPM) was proposed for capturing and transferring knowledge across projects. Expert review meetings with participants from both academia and private sector were carried out to develop LLMPM. The identified requirements were actualized through generation of a web-based IT tool (LinCTool) with abilities of capturing, storing and disseminating lessons learned. Black-box testing was used to verify LinCTool and interviews were conducted with experts as final testing to evaluate its effectiveness and usability. Results show that LinCTool has a potential to enhance organizational learning in companies by assigning multiple users having different responsibilities/roles in the learning process, categorizing lessons learned using a taxonomy and retrieving lessons learned considering project similarities. • A lessons learned management process model (LLMPM) for transferring knowledge. • LinCTool developed as a web-based tool to implement LLMPM. • A taxonomy to categorize lessons learned and their retrieval. • A similarity assessment method to transfer lessons between the projects. • LinCTool validated by four company professionals from three construction companies. [ABSTRACT FROM AUTHOR]