فهرست مطالب سیامک حاجی یخچالی

One of the main concerns of project based organizations in construction projects is to manage multiple projects in a portfolio simultaneously. Construction Portfolio management determines the best time and condition of starting and selling each project according to the financial need of the stakeholders. This paper aims to optimize the cash flow in construction portfolios considering market indices using meta-heuristic algorithms from the organization’s point of view. In this research, a model was presented to simulate the conditions of the project portfolio and was optimized using genetic algorithm (GA) and particle swarm optimization (PSO). The inflation rate of construction and real estate during recession and expansion was considered to make the situation more real as well. To evaluate the model, a portfolio including five real selected projects in advance by an organization is optimized by the model. The results showed that the model and the optimization algorithms used in the model had an effective role in the arrangement and balancing of the portfolio. Moreover, conditions of the organization such as cash flow and market indices such as project construction inflation and real estate inflation during periods of recession and boom were also considered, which is almost impossible in traditional project portfolio management. Both algorithms came up with the same solution which showed that the result is valid, but the performance of the particle swarm optimization algorithm was better than the genetic algorithm in terms of program execution speed and speed of the final result. In comparison to an expert decision on balancing the portfolio, the algorithms found the solution with 33% better objective function values.

Delays in construction projects increase project implementation costs. Identifying factors causing delays in these projects and preventing their occurrence are major concerns for many construction project managers. Many studies have been conducted about the main effective factors causing delays in construction projects in different regions. The results achieved in these studies indicate effective factors vary according to the prevailing conditions of the specified type of the construction projects in the region. Identifying and preventing delays in specific types of construction projects from occurring in each region requires dedicated research efforts. Meanwhile, residential building projects constitute a major portion of construction projects in the populated cities. Delays in residential building projects can increase the project's costs and the housing price, which has a major share in the family expenses in Iran. Mashhad is the second largest city in the country with a large housing market. However, research efforts addressing residential building project delays in the city are still missing. In response to this need, current research was conducted to investigate the delay in the residential building projects in the city. Main factors causing delays in these projects were identified, and recommendations to avoid delays from happening or to mitigate their negative impacts were made. To do so, first, a comprehensive literature review was conducted to identify different possible effective factors on construction project delays. Then, a questionnaire-based survey was conducted on different stakeholders of residential building projects to evaluate impacts of effective factors. The survey results indicated project delay is a major concern in the residential building projects in the city. The client's financial problems, contractor's financial problems, and high inflation were identified as main factors with major impacts on the project delay. Proper financial management by the client and comprehensive understanding from supply and demand in the housing market before commencing the project are among recommendations to reduce negative impacts of project delays in these projects.

Nowadays, with significant growth in the number of organizations, they seek to increase their competitive advantages as much as possible. One of the effective approaches is knowledge management, through which organizations try to re-exploit the experiences and knowledge created in their previous projects. Today, many projects are carried out by forces from other nationalities, in which each participating organization operates within complex national, organizational, and informal contexts. So, knowledge is transferred between geographically dispersed individuals and organizations, and across cultural and national boundaries. Given these conditions, knowledge management processes, especially the transfer and acquisition of knowledge, are critical. The purpose of the present study is to design a conceptual framework of the contextual factors affecting the knowledge transfer in transnational projects using a meta-synthesis Firstly, this study would combine previous researches in the field of knowledge transfer. These factors are determined using the open coding method to propose a conceptual framework. Secondly, hypotheses are defined based on obtained factors, and then we would examine the hypotheses and identify the relationship between independent variables and the dependent variable. The statistical population of the present study includes companies involved in the upstream industry in the realm of petroleum. The data are gathered using a questionnaire. This paper focuses on those types of factors which affect knowledge transfer, from both theoretical and empirical viewpoints. We provided an integrative conceptual framework to evaluate and organize the literature on effective contextual factors on knowledge transfer. The obtained results revealed that cultural distance, knowledge distance and language had the most significant influence on the knowledge transfer. Besides, we provided effective solutions for the organizations to improve their knowledge transfer process

Despite the potential threats to the environment, the oil industry plays a positive role in society. Knowledge transfer not only plays a significant role in knowledge process, but also helps the oil and gas industry to reduce their environmental impact with improvement in their operational efficiency. Sharing of knowledge, information, and practices across cultural and national boundaries has become a means to address critical global problems. This paper explores oil and gas industry projects and identifies the critical organizational factors that affect knowledge transfer and influence their performance. The paper concludes with a conceptual model that accounts for the relationships among these factors that can guide further research in understanding knowledge and information transfer across national and cultural boundaries.

The oil industry holds a major potential of hazards for the environment, and may impact it at different levels. Despite its potential threats to the environment, the oil industry plays a positive role in society as well. It is still necessary to find ways to conciliate industry development, especially active organizations in this industry, with environmental protection. Organizations have the most essential effects in forming and directing the behavior of their staffs. Advances in modern societies have led to more consideration of knowledge management by organizations. Knowledge transfer plays a significant role in knowledge process. Besides, it helps the oil and gas industries to improve their operational efficiency and so reduce their environmental impact. There are various effective factors in knowledge transfer. These factors are generally related to individuals, organizations, and technology. Based on previous studies (Mei et al., 2007; Hassandoust et al., 2001; Wickramasinghe & Widyaratne, 2012), the effective factors can be divided into two main categories named content and context. Though in the literature that are many studies which have been focused on the different factors affecting knowledge transfer, limited studies have examined the organizational factors, and there are still many challenges to understanding the essential organizational factors which affect the knowledge transfer procedure in an industrial organization, company or group. This paper focuses on this type of factors, which affects knowledge transfer, from both theoretical and empirical viewpoints. We provide an integrative conceptual framework for organizing the literature on effective organizational factors for knowledge transfer. Most top ten effective factors are identified from the questionnaires filled out by 137 experts from Iranian oil and gas companies. The obtained results reveal that organizational culture, organizational relationships and reward system have the most significant influence on the knowledge transfer. Besides, we provided effective solutions for the organizations to improve their knowledge transfer process. Our findings can help practitioners develop a more focused approach in dealing with the most significant factors.

Regarding the lack of theoretical point of views, complete and better frameworks is essential to summery and conduct all organizational factors which are most effective in a knowledge transfer process. In this research, it would be realized by answering the following research question.
Research Question: What are the most important organizational factors in knowledge transfer within projects?
The paper develops a conceptual framework for the analysis of knowledge flow transfers in projects. Based on this theoretical framework, the paper proposes research hypotheses and builds a causal model that links the constructs of the model. The organizational factors regarding knowledge transfer in general are summed up from literature and then the issue is studied by conducting a survey in companies. Participants of the study included well-known and successful oil and gas companies. Using in-depth data from Iranian oil and Gas Company, we study the role of organizational factors in knowledge transfer.

Based on a systematic investigation of effective factors in knowledge transfer currently available in the literature, a common frame of reference for knowledge transfer development is developed. This frame of reference consists of thirteen organizational factors. Besides, it will provide a good departure point for future work in knowledge transfer, both academically and practically. These factor including organizational structures, reward system, leadership characteristic, organizational culture, organization commitment, motivation, management support, strategy, organization relationship, training, opportunities to share, control mechanism and team orientation. These factors have investigated in oil and gas projects and it has been identified that 11 items of mentioned factors are effective on transferring knowledge and there is a direct relationship between them. Organizations should attempt to maximize the effect of these factors in order to increase knowledge transfer rate.
Organizational culture has been identified as the most important factor in knowledge transfer. All organizations have personalities as people do and characteristics such as flexibility, innovation, and more. In order to more success, an organization should implement the knowledge orientation culture, such that providing knowledge becomes institutionalized. The second identified priority is the organizational relationship. In order to succeed in knowledge transferring, organizations should create this motivation in their employees. Cash, non-cash, and organizational position lead to better performance of employees in knowledge transfer. Organizations can achieve the best response from their employees by proper defining their reward system. Among the factors studied, it was found that training and team orientations would not have a significant effect on the knowledge transfer in the projects. In addition, despite the positive effects of team works, this factor will not be lonely a motivator for more knowledge transfer. Organizations, with Strengthening and planning on effective organizational factors in knowledge transfer, can prepare the workplace so that knowledge transfer and sharing can be greatly increased.

Organizations have essential effects in forming and directing the behavior of their staffs. Today, most behaviors of the staffs have an organizational origin. This paper aims to identify the most effective organizational factors in knowledge transfer process in order to reduce environmental hazards in oil and gas projects. we developed a conceptual model and hypotheses to verify the role of organizational factors in knowledge transfer. The results reveal that organizational culture, organizational relationships, and reward system have the most significant influence on the knowledge transfer.

The aim of this paper is to propose a new approach to assess the aggregated impact of risks on the completion cost of a construction project. Such an aggregated impact includes the main impacts of risks as well as the impacts of interactions caused by dependencies among them. In this study, Monte Carlo simulation and Bayesian Networks methods are combined to present a framework to assess the aggregated impact of risks on a construction project’s completion cost. Project risk assessment, regardless of the interactions between them, leads to prioritization of risks and does not provide any indicator to assess the aggregated effect of risks on the entire project. Achieving a nearly accurate estimate of the project completion time or cost requires consideration of the probabilities and effects of the risks, as well as the interdependencies among them simultaneously. The integrated model presented in this paper, in addition to providing a framework to evaluate the direct impact of risks on activities or work packages of a construction project, is able to assess the sensitivity of the project completion cost to the occurrence of the risks by considering the probabilities, effects and interdependencies.According to the results of the sensitivity analysis, the probabilities of “shortage of resources”, “inefficiency in project financing” and “poor design” are the main causes of delay in a gas refinery construction project.

Project Portfolio Selection is one of the strategic decisions on the level of management in project-oriented organizations; which is one of the most important and effective stages in project portfolio management. In other words, after identification and evaluation of different projects, optimal combination of projects must be selected based on different criteria. Since commonly resources of organizations are less than required resources on projects that are ahead of the organization; so project selection among different project portfolio and decision making about these issues are inevitable in organizations. So durability of organizations depends closely on the way of modeling and used approaches for project selection problem. In previous researches related to project selection problem, generally the problem of project clustering have not deeply been considered while project clustering may allow that projects to reach the highest return. In this article, we will propose a model for clustering, evaluating and selecting projects. At first projects will be clustered in various portfolios by K-MEANS algorithm, then projects of each portfolio will be evaluated and prioritized with analytical network process (ANP). Finally, projects from each portfolio will be selected based on knapsack problem.

Considering the increasing environmental hazards caused by industrial activities, more attention has been paid to the aspects of this issue and the efforts to carry out sustainable activities, which has made it very important to pay attention to environmental issues. The purpose of this research is to find the effective criteria for selecting suppliers of oil and gas products, considering the importance of these suppliers to the environmental hazards resulting from the operation of their products. By studying the past functions and reviewing the lessons, which have been learned from the implemented projects, and taking into account the experts and owners of the executive experience, key points in the supply chain that were directly related to the environmental functions were identified, and the criteria were recognized and combined with two methods of the process of Hierarchical Analysis (AHP) and the preferred method based on similarity to the fuzzy TOPSIS solution and performing paired comparisons to determine the weights of each of the criteria and the comparison of each of the suppliers according to the criteria identified in the end of the main criteria and Effective in identifying the choice of a green supplier. The results of this research can be applied in the models used by decision makers to select contractors, oil suppliers, and gas products, which can play a very important role in greening the supply chain of goods. Introduction It is clear that in the project procedure, after decision-making and design, efficient design can provide satisfactory results regarding to the purposes and hypotheses of the study. However, can modern techniques, methods, accurate design, and prediction of various factors lead to the ultimate goal? Of course the answer is negative, because the mental and physical efforts can lead to efficient results when it is possible to show everything in practice. The accuracy and efficiency of planning should be indicated in practice; otherwise, all of them will lead to failure. Therefore, in addition to accurate planning and design, we should attempt to find a way to measure the results and find a solution to deal with problems and deviations. No system can work and achieve its highest capacity without control. All of us are familiar with chaos and delay, which is resulted to the lack of control in traffic systems. Uncontrolled water or electricity network systems can cause problems or decrease efficiency. If a building system is efficiently designed but progresses without any control, it may lead to delays or replacement. This study aims to utilize theoretical models and methods in practice to achieve new methodology in project progress measurement. Then, important points in this regard are taken into considerations and finally, theoretical foundations of methodology design are presented. The present research intends to examine whether it is possible to combine decision-making methods that can be used to provide green supply suppliers in the supply chain of the Pars Oil and Gas Company with the intention of reducing environmental risks, including reducing environmental pollution. Then, by combining AHP and TOPSIS fuzzy methods, and applying green criteria, it provides a framework for ranking suppliers in the supply chain and selected the most suitable supplier for cooperation in the supply chain. Materials and Method In this research, the indicators and criteria for selecting green suppliers were collected through library studies. In particular, six major indicators were used in this study. Then, by designing a pairwise comparison questionnaire (questionnaire 1), these indicators were compared in two groups. The data from this questionnaire are included in the fuzzy AHP model to become numerical weights for the indices. In the next stage, another questionnaire (questionnaire number 2) is designed in which decision makers or respondents compare the suppliers with regard to the indicators. The data of this questionnaire and the weights obtained by the fuzzy AHP model are included in the fuzzy TOPSIS model, so that the suppliers, at the end, are prioritized according to the green criteria. The problem of choosing green suppliers for solving multiple problems can be solved by multivariable decision analysis methods. In this research, the combination of two methods of AHP and TOPSIS has been used to achieve the answer. Since the data were collected inaccurately, and sometimes qualitatively, the use of definite methods can lead to incorrect results. Therefore, for fuzzy logic, the following methods are combined to obtain accurate results. Conclusion In this research, two methods of fuzzy AHP and TOPSIS, which are fuzzy multi criteria decision-making methods, are used to rank green suppliers that play a key and undeniable role in reducing environmental hazards and sustainable development in the supply chain used. Initially, six sources of green supply choices were identified by studying the literature. The basis of the questionnaire was compilation: comprehensive environmental management, hazardous material management, green innovation, green image, green product and pollution control. After collecting data from the experts, the Fuzzy AHP method was used to determine the significance or weight of the criteria and the green innovation indicator was identified as the most important indicator. Then, the suppliers of the company were ranked by using the fuzzy TOPSIS method. This research with a semantic approach can be the first step in the implementation of the green supply chain in service organizations and other institutions.

In many developed countries sustainability is a big challenge and is one of the very important issues in the field of project management that often has been neglected in project management so far. Project management and sustainability are separately addressed in countless studies but there is an essential need of intersecting above mentioned issues together. In this study, we investigate to introduce a set of indicators and perform a hybrid decision making method to identify and categorize a set of indicators for project portfolio selection and then prioritize proposed factors based on combination of Grounded theory and fuzzy DEMATEL to consider in an uncertain environment. Results in this paper represents that the most important factors are responsibility and cost. Also, responsibility is the most affected one and cost is the most effective ones. Moreover, factors such as risk and waste are effective factors.