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Item type:Publication, A new approach for ranking efficient DMUs with data envelopment analysis(Emerald, 2020-07-02)Purpose: Classical models of data envelopment analysis (DEA) calculate the efficiency of decision-making units do not differentiate between efficient units. The purpose of this paper is to present a new method for ranking efficient units and compare it with the other methods presented in this field. Design/methodology/approach: In this paper, a new method is presented for ranking efficient units. To validate the proposed method, a real case, which was studied by Li et al. (2016) is examined and the rankings of the efficient units are compared with four other methods including the Andersen and Petersen’s super-efficiency, game theory and the concept of Shapley value and the technique for order of preference by similarity to ideal solution methods. Findings: The results show that there is a high correlation between the rankings of efficient units obtained by the new proposed method and the other methods such as Andersen and Petersen’s super-efficiency, game theory and Shapley value methods. Originality/value: The problem of ranking efficient units with the DEA method is an important issue for researchers. Extensive studies have been proposed to provide methods for ranking efficient units. This paper proposes a simple and fast method for ranking efficient units that achieves better results. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Trading off time-cost-quality in construction project scheduling problems with fuzzy SWARA-TOPSIS approach(MDPI, 2021-09-01)The increasing number of construction projects together with the limited resources of organizations led to tough competition for achieving project goals. Time, cost, and quality have been known as the project iron triangle. Project managers attempt to allocate the appropriate resources and make the best decisions for accomplishing projects with the shortest durations, lowest costs, and the highest quality. No study has examined the time–cost–quality trade-off problem with decision-making approaches. In this study, the fuzzy multi-criteria decision-making (MCDM) methods are exploited to choose the best mode for performing each activity. For this purpose, the SWARA method is applied to determine the importance weights of time, cost, and quality. In addition, the TOPSIS (Technique for the Order Preference by Similarity to Ideal Solution) technique is used to rank and select the best activity execution modes. The proposed model is implemented on two medium- and large-size construction projects to evaluate its efficiency. Several execution modes with fuzzy duration, cost, and quality are considered for each project activity. Finally, sensitivity analysis is conducted taking three different conditions into account: the shortest duration of the execution modes, the lowest cost of the execution modes, and the highest quality of execution modes for each activity. The solution of each trade-off is compared with the solution obtained from the fuzzy SWARA–TOPSIS method. The schedule is developed according to the best execution mode for each project activity. The obtained results in two different construction projects show significant improvements in the overall project objectives so that the projects can be completed in fewer durations and costs along with higher quality. Because of the higher importance of cost, the cost of each activity is closer to the lowest cost. The activity duration is also closer to the most likely duration, and quality is closer to the high-quality level. The application of this approach can create new opportunities for research and knowledge development in the field of construction project scheduling. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluating efficiency in construction projects with the TOPSIS model and NDEA method considering environmental effects and undesirable data(Springer Science+Business Media, 2021-05-30)Today, project stakeholders seek to reduce the total costs and durations of projects while increasing their quality levels. Also, the governments have paid more attention to the environmental effects of projects. This study tackles the time–cost–quality-environmental effects trade-off project scheduling problem. Various activity execution modes are evaluated using the network data envelopment analysis (NDEA) method to select the best modes in order to mitigate the environmental impacts, along with reducing the duration and cost of project implementation and enhancing the overall quality of the project. The method of ideal and anti-ideal virtual units is applied to rank the efficient execution modes. In addition, the TOPSIS method is utilized to rank the different execution modes of each activity. Finally, the results of two methods are compared. The findings show that the selection of an efficient execution mode for each activity leads to a trade-off between the four project objectives including time, cost, quality, environmental impacts. The shortest project duration and the lowest total project cost were obtained using the NDEA-Nuo method, the highest quality level was gained by the NDEA-INP method, and the minimum environmental impacts of the entire project were attained by the TOPSIS method. Also, the lowest amount of resource consumption was obtained using the TOPSIS method, so that the daily consumption amount of each resource was less than the other two methods. As a result, the project management team can apply either the NDEA or TOPSIS method based on the organizational policy. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Investigating the environmental impacts of construction projects in time-cost trade-off project scheduling problems with CoCoSo multi-criteria decision-making method(Multidisciplinary Digital Publishing Institute (MDPI), 2021-10-01)Currently, construction projects have a significant share in environmental pollution. Usually, the employers and managers of construction projects pay attention to the project implementation with the shortest duration and the lowest cost, whereas less attention is paid to the environmental effects of the implementation of projects. Sustainable development requires the planning and implementation of construction projects, taking environmental impacts, along with other factors, into account. Few studies have investigated the balancing time, cost, and environmental effects. Although the selection of an execution method for the project activity requires the use of decision-making methods, these methods have not been used in the project scheduling problems. This study seeks to simultaneously minimize the project time, cost, and environmental impacts. The of this study is to evaluate the environmental impact of project activities in three physical, biological, and social aspects throughout the construction projects, and to attempt to minimize them as measurable values. In this paper, the environmental effects of an urban water supply construction project as a real case study are assessed in different activity execution modes by the Leopold matrix and the best execution mode of each project activity is selected using the CoCoSo (combined compromise solution) multi-criteria decision-making method, considering the time–cost-environmental impact trade-off. The CoCoSo method is employed because of its high flexibility compared to other multi-criteria decision-making methods. The results of this study will direct managers and stake-holders of construction projects to pay more attention to the environmental effects of construction project activities, together with the other conventional project goals and objectives, such as the time and cost. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessing employees’ job motivation using BWM method and fuzzy goal programming: A case study of a petrochemical company(Emerald Publishing, 2022-09-23)Recognizing the factors affecting employees’ job motivation is one of the necessities that can improve people’s performance and increase their effectiveness. This study aims to determine the factors affecting job motivation and to examine effective strategies to increase motivation through identifying internal and external factors. Design/methodology/approach: In this descriptive study, the statistical population was the employees of the largest petrochemical company in Iran. The questionnaire was randomly distributed to the organization’s employees and managers based on Herzberg’s motivation-hygiene theory. To analyze the obtained data, first, the best and the worst factors were identified using SPSS software and then were ranked using best–worst method (BWM). Findings: The results demonstrated that the highest rank among the motivational factors of employees is related to working environment conditions and the lowest rank is related to career advancement and development indicator. In the second stage, the best strategies for motivational factors were determined using the fuzzy goal programming method. The findings showed that 12 out of the 17 proposed solutions have the highest motivation among employees, the implementation of which can increase employee productivity in the petrochemical company under study. Originality/value: Further to the best of the authors’ knowledge, job motivation factors in the petrochemical industry have never been examined and ranked by using the BWM method so far. Also, the goal programming approach has never been applied to determine strategies for increasing job motivation and ultimately productivity. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Application of fuzzy BWM-CoCoSo to time-cost-environmental impact trade-off construction project scheduling problem(Springer Science+Business Media, 2022-04-05)The economic growth and the development of construction industry in several countries have had detrimental impacts on environment and natural ecosystems. Therefore, environmental impact assessment studies of construction projects have received more attention from governments and organizations. In other words, minimizing environmental impacts have been taken into consideration along with other common project goals. This study aims to identify and evaluate the environmental impacts of construction projects and ultimately determine the most favorable implementation modes of activities so that each project activity is executed with the least possible cost, duration, and environmental effects. The environmental consequences of projects are identified in three biological, physicochemical, and socioeconomic environments. Also, the positive and negative environmental impacts are assessed using the Leopold matrix method. Then, the importance weights of the project objectives including cost, time, negative environmental impacts, and positive environmental impacts are calculated using the fuzzy BWM method. Finally, the various modes of executing each activity are prioritized and ranked by using the fuzzy CoCoSo technique regarding the weighted objectives. The activity execution mode with the highest ranking indicates the best possible implementation mode of that given activity according to cost, time and positive environmental impacts as well as negative environmental impacts. The proposed method is implemented in a remote rural water supply construction project for efficiency evaluation. This study directs project managers to identify and assess the environmental consequences and impacts of construction projects in addition to considering the other two common project objectives. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Identifying and prioritizing service compensation factors influencing nurses’ motivation: Application of hybrid fuzzy DEMATEL-BWM method(Springer Science+Business Media, 2022-12-17)Human resources are a key source of sustainable competitive advantage and are considered as one of the substantial factors for an organization’s success. No organization can survive without its human resources. Understanding employees’ needs, desires, and satisfaction is essential. Organizational managers consider financial and non-financial compensation for employees’ service. There is a need for a practical look at the field of nursing service compensation, especially in the healthcare system. In this study, the factors affecting nursing service compensation in the selected private hospitals in Iran were initially identified and confirmed using the exploratory and confirmatory factor analyses. The three major factors are empowerment components, organizational components, and financial components. Then, the driver factors (causes) and dependent factors (effects) in the nursing service compensation system were investigated and their relationships were determined using the fuzzy DEMATEL technique. Finally, these factors were ranked using the best–worst (BWM) method. The results of BWM indicate that financial components gained the top-ranked, followed by organizational components, and empowerment components. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Towards sustainable project scheduling with reducing environmental pollution of projects: fuzzy multi-objective programming approach to a case study of Eastern Iran(Springer Science+Business Media, 2022-05-09)Implementation of projects with an acceptable quality level in the minimum cost and time has always been the ultimate goal of managers and decision-makers in the construction industry. On the other hand, the construction industry is responsible for creating various environmental problems. Therefore, reducing the environmental destructive effects of project implementation is of utmost importance. The aim of this paper is to consider the environmental pollution along with the project iron triangle of cost, time, and quality in the scheduling of the construction projects. A multi-objective multi-mode resource-constraint project scheduling model is presented considering the generalized precedence constraints between project activities as well as the limitation of renewable resources and non-renewable resources. In this study, the environmental effects of construction projects as well as the three conflicting goals of cost (budget), time (duration), and quality are taken into account. Also, the limitations of renewable and non-renewable resources as well as the generalized activity precedence relationships are incorporated into the proposed model. The proposed model was implemented on a rural water supply project including 25 activities and was solved using the fuzzy goal programming approach with GAMS software. Different combinations of activity modes were presented along with the start time of each activity considering four objective functions. The results showed that this project would be completed in 190 days, at the cost of $15,394, with the quality level of 0.835, and environmental effects of 0.372, which are between the optimal and worst objective functions values. In addition, the sensitivity analysis indicates the high efficiency of the proposed model and its capability in assisting project managers and planners. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A robust bi-objective optimization model for resource levelling project scheduling problem with discounted cash flows(Springer Verlag, 2022-06-01)Due to limited financial resources and high costs of infrastructure projects, project stakeholders seek to gain maximum profits with optimal resource utilization as well as cost and time minimization. Therefore, this study presents a multi-mode resource-constrained project scheduling model considering the uncertain parameters of cost and time together with the goals of maximizing the net present value and minimizing resource usage fluctuation. Also, the assumptions related to the real-world projects regarding multi-mode activities, limitation of renewable resources, and the deadline of project are incorporated into the proposed model. Moreover, a robust scheduling method is presented to better deal with the inherent uncertainties of projects regarding cost and time. The model is solved with the exact method named lexicographic goal programming (LGP). Due to the NP-hardness of the problem, two metaheuristic algorithms named Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) are applied to solve various medium and large size problems. The obtained results indicate the high efficiency of the two metaheuristic algorithms in solving the problem and the better performance of the MOPSO algorithm compared with NSGA-II in terms of five indices. Furthermore, the model is implemented in an offshore equipment installation phase of a wellhead platform project. Finally, the sensitivity analysis of the proposed robust model is performed considering different conservation levels, and the results are evaluated by Monte Carlo simulation with three normal, uniform and triangular distributions. The findings demonstrate that the robustness of the model against the variations of uncertain parameters. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A step-by-step hybrid approach based on multi-criteria decision-making methods and a bi-objective optimization model to project risk management(Regional Association for Security and crisis management, 2024-01-01)Project success and achieving project objectives and goals highly depend on effective and thorough risk management implementation. This study provides a comprehensive and practical methodology for project risk management. In this paper, firstly, the risks were collected by analyzing the historical documents and literature. Then, the collected risks were screened using brainstorming and categorized into five groups. Subsequently, a questionnaire was made and the identified risks were validated using the Fuzzy Delphi technique. Also, the relationships between risks were determined using the Interpretive Structural Modelling (ISM) method. Moreover, the weights of the criteria used to rank the risks were calculated through the Fuzzy Best-Worst Method. Subsequently, the major risks were determined using the fuzzy WASPAS method. Furthermore, a novel bi-objective mathematical programming model was developed and solved using the Augmented Epsilon-Constraint (AEC) method to choose the optimal risk response strategies for each critical risk. The results demonstrated that the proposed framework is effective in dealing with construction project risks.