project management
Roya Soltani; Ali Nobakhti
Abstract
In this paper, a recommender system based on a multilayer feedforward artificial neural network (ANN) trained by the Levenberg–Marquardt backpropagation algorithm, optimized using a genetic algorithm (GA) to fine-tune both network structure and weights, is proposed to predict competency and recommend ...
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In this paper, a recommender system based on a multilayer feedforward artificial neural network (ANN) trained by the Levenberg–Marquardt backpropagation algorithm, optimized using a genetic algorithm (GA) to fine-tune both network structure and weights, is proposed to predict competency and recommend project managers in project-oriented organizations. The system considers both hard and soft skills, which are essential for sustainable development. The performance of the proposed system was evaluated by a case study within the Iranian construction industry, utilizing the experience of 80 senior managers and experts from the Ministry of Roads and Urban Development of Iran. The results demonstrate the high accuracy of the proposed system in identifying competent project managers. To validate the system, its performance was compared with existing methods in the literature, showing superior accuracy in terms of MSE and RMSE metrics.
Introduction
In today’s dynamic business environment, projects operate within a VUCA context—characterized by volatility, uncertainty, complexity, and ambiguity—that significantly influences managerial decision-making and project outcomes. Rapid technological advancements, economic fluctuations, the complex nature of stakeholder interactions, and resource constraints have made project management an increasingly challenging undertaking. Consequently, the competence of project managers to address a wide range of human resource, technical, and economic challenges, along with their ability to build effective communication and collaboration networks, is a crucial determinant of project success (Omoush, 2020). To ensure successful project delivery, project managers must demonstrate a sound understanding of environmental dynamics and make informed, adaptive decisions that integrate both hard and soft managerial skills—skills that are now more critical than ever for achieving sustainable development. Such abilities reflect the professional competence and strategic agility required for timely and effective decision-making (Karki & Hadikusumo, 2023).
Selecting competent project managers through a data-driven recommender system that matches the desired managerial skills can substantially enhance the effectiveness of project-based organizations. Such a system can transform the manager selection process from subjective judgments to evidence-based decision-making. This approach not only improves the precision of identifying qualified managers but also contributes to better human resource allocation, reduced managerial risk, and enhanced overall project performance. Ultimately, adopting a data-driven recommender framework enables project-based organizations to strengthen their managerial capabilities and achieve a sustainable competitive advantage.
Research Questions
How can a smart recommender system be designed—by integrating ANN and GA—to accurately identify competent project managers in project-based organizations?
To what extent can optimizing the parameters of an ANN using a GA enhance the accuracy of the recommender system?
Literature review
In the literature, various data-driven methods have been developed using machine learning approaches to enhance decision-making, resolve conflicts, and improve project performance, productivity, safety, and workflow in the field of project management. A comprehensive review of the literature reveals that existing predictive models in project management have predominantly focused on forecasting various project outcomes such as quality (Najafi Zangeneh et al., 2020; Fan, 2025), infrastructure costs (Soltanian et al., 2023; Dan, 2024; Chen, 2024; Effat, 2025; Al-Gahtani et al., 2025), dispute occurrences and litigation outcomes (Ayhan et al., 2021), delays (Awada et al., 2021), and construction crew productivity (Sadatnya et al., 2023) through the application of diverse classification algorithms (see Table 1). Despite these advances, the literature lacks studies that aim to develop a predictive model capable of accurately assessing project manager competency using a hybrid framework that combines ANN with metaheuristics. Employing such an approach could provide a robust mechanism for identifying competent project managers and, consequently, enhance the likelihood of successful project delivery in complex and dynamic construction environments.
However, in the literature, the combination of ANN with metaheuristics has been employed to improve prediction accuracy across various domains. These domains include stock market forecasting (Sharma et al., 2022), electricity consumption demand prediction (Azadeh et al., 2007), and patient mortality prediction (Dybowski et al., 1996) (see Table 2).
Methodology
The steps of the proposed recommender system for identifying competent project managers are as follows:
Data preparation: First, a database comprising data related to competency is established and quantified based on the experience of 80 senior managers and specialists. Subsequently, data cleaning is performed, and records with missing values, outliers, or inconsistencies are removed from the database. Finally, 70% of the data is randomly selected for training and 30% for testing.
Neural network architecture design: A feedforward multilayer ANN is designed based on the number of hidden layers (i.e., 1, 2, or 3) and the number of neurons per layer (i.e., 2, 4, or 8). The network is trained using the Levenberg–Marquardt algorithm. After training and testing, the optimal network structure is selected based on MSE and RMSE metrics.
Optimization of neural network weights using genetic algorithm: The weights of the designed ANN are optimized using a GA to improve the network’s predictive performance.
Training and testing the ANN-GA recommender system: The ANN optimized by the GA is first trained and then tested. The performance of the proposed ANN-GA recommender system in identifying competent project managers is evaluated based on the MSE and RMSE criteria.
Results
The ANN model with a three-hidden-layer architecture and 2 neurons per layer demonstrated the best performance in terms of MSE and RMSE, with values of 0.351 and 0.593, respectively. This indicates that the designed network effectively predicts project manager competency. To further enhance prediction accuracy, the network weights were optimized using a GA. The resulting ANN-GA recommender system achieved an MSE of 0.094 and an RMSE of 0.307, showing significantly higher accuracy in identifying competent project managers compared to the non-optimized network (MSE = 0.351, RMSE = 0.593). These findings highlight the effectiveness of combining ANN with GA for data-driven competency assessment.
To validate the proposed recommender system for identifying competent project managers, its prediction error was compared with the algorithms reported by Karki and Hadikusumo (2023). As shown in Table 12, the proposed system demonstrates superior accuracy, highlighting its effectiveness over existing methods.
Discussion
Effective project management in the construction industry, a complex and high-risk sector, requires managers capable of making informed decisions under VUCA conditions. Instead of subjective judgments, experiential biases, and unstructured evaluations, the proposed recommender system can help project-based companies use data-driven, intelligent tools to identify more competent managers, improving project productivity while significantly reducing costs associated with poor managerial decisions. Additionally, the proposed system can serve as a decision-support tool for hiring new project managers or promoting existing ones by analyzing past performance and predicting their potential success in future projects.
Conclusion
The proposed recommender system integrates an ANN with a GA to identify and select competent project managers with high accuracy. Leveraging historical data and uncovering hidden patterns, the optimized ANN accurately predicts managerial competencies based on defined criteria. Validation against existing approaches demonstrates that the GA significantly enhances predictive accuracy, highlighting the system’s potential to improve managerial selection and project outcomes in practice.
project management
Mohammad Amin Dorosti; Farhad Saiedi; Saied Yousefi
Abstract
Abstract
Qualified contractors are the main pillar of sustainable construction projects and the technical arm of project implementation, playing a significant role in achieving sustainable development (economic, social, and environmental) goals. Evaluating competence and selecting the best contractor ...
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Abstract
Qualified contractors are the main pillar of sustainable construction projects and the technical arm of project implementation, playing a significant role in achieving sustainable development (economic, social, and environmental) goals. Evaluating competence and selecting the best contractor are among the concerns of employer companies when outsourcing the implementation of such projects. In this regard, company managers and policymakers need criteria to evaluate qualified contractors. The current study aims to identify the evaluation criteria for competence and to select contractors for sustainable construction projects from the perspective of employer companies. This study is applied in terms of purpose and qualitative in terms of data type. In this study, the construction industry in Kish Island is examined, and an expert panel comprising project managers and experts from employer companies is formed, and sampling was carried out non-randomly and purposefully. After surveying 12 experts through semi-structured interviews, the content of the interviews was coded and analyzed using the thematic analysis approach based on the six-step model of Braun and Clarke (2006) with an inductive approach. A total of 73 codes with a frequency of 979 repetitions were counted in 12 sub-themes and 3 main themes. The results showed that, unlike traditional approaches to evaluating candidate contractors in tender meetings, carrying out this process in sustainable construction projects requires a comprehensive approach by the decision-makers of the employer companies and their simultaneous attention to 12 key criteria that are categorized into three economic, social, and environmental dimensions.
Introduction
The construction industry plays a vital role in enhancing the quality of life and supporting national growth, yet it is also among the largest contributors to environmental degradation through high greenhouse gas emissions and waste generation. Consequently, the transition toward sustainable construction practices has become imperative to mitigate negative environmental impacts. Sustainable construction emphasizes the use of recyclable materials, energy efficiency, waste minimization, and environmental protection, while also attracting increasing attention from governments, scholars, and leading companies as a strategic business priority. In Iran, and particularly in Kish Island, adopting modern construction methods, engaging qualified professionals, leveraging advanced technologies, and reducing bureaucratic inefficiencies have become critical concerns for stakeholders. Within this context, the selection of competent contractors is pivotal, as their capabilities directly influence project outcomes in terms of quality, cost, and timely delivery. However, existing evaluation processes in the country have predominantly focused on traditional economic indicators, neglecting social and environmental dimensions of sustainability. International studies highlight that the absence of comprehensive criteria for contractor assessment often leads to cost overruns, delays, and reduced quality. Therefore, conducting a field-based study to explore and define the dimensions and criteria of contractor competence in sustainable construction projects on Kish Island addresses a critical research gap.
Research Background
The selection of competent contractors is a critical factor in the success of construction projects and has been examined from multiple perspectives in the literature. The concept of “organizational competence” in project management refers to an organization’s ability to integrate resources, processes, and culture in alignment with its mission and strategy, which plays a pivotal role in achieving sustainable development goals. Recent international studies have highlighted that contractors are crucial in attaining sustainability objectives and mitigating environmental and social risks, making transparent and multi-criteria evaluation essential. To this end, numerous studies have considered technical, financial, managerial, safety, past performance, and bid price criteria; however, reliance solely on the “lowest bid” remains a significant weakness in tendering systems. Domestic research indicates that, although ranking systems and prequalification assessments partially improve contractor selection, sustainability criteria are still largely neglected. Evidence from international studies in Egypt, India, Jordan, and China underscores the necessity of integrating environmental, social, and economic indicators alongside traditional criteria, whereas in Iran, final selection often remains price-driven. This gap motivates the present study to identify and comprehensively analyze the competency criteria for contractors in sustainable construction projects on Kish Island, aiming to provide a localized framework that enhances the competitiveness of domestic construction firms and facilitates their entry into international markets.
Method
The present study is applied in nature, qualitative in terms of data type and analytical approach, and falls within the descriptive-survey category regarding data collection. The content analysis of the interviews was conducted using an inductive thematic coding approach. The analysis followed Braun and Clarke’s (2006) six-step framework, including familiarization with the data, generation of initial codes, theme extraction, review of sub-themes, definition and naming of main themes, and reporting. The study population consisted of 12 project managers and experts from client companies active in the construction industry on Kish Island, purposefully selected through non-probabilistic sampling. Semi-structured interviews were conducted between winter 2023 and summer 2024. Data validity was ensured through systematic data recording, increasing participant diversity, iterative data review, and oversight by external experts and faculty members.
Results and Discussion
Through open coding and content analysis of 12 interviews with experts, a total of 73 codes with 979 occurrences were identified, organized into 12 sub-themes and 3 main themes. The findings showed that the most important criteria for contractor competence and selection in these types of projects are structured around three primary categories, including economic, social, and environmental, which constitute the main themes and serve as the foundational pillars of sustainable development. The findings indicate that a comprehensive evaluation of these three dimensions facilitates the selection of competent contractors, reduces operational risks, enhances construction quality, and increases transparency and accountability. From an operational perspective, sustainability competency criteria contribute to the optimization of costs and resources, improvement of operational efficiency, utilization of standard equipment, and reduction of material wastage. Moreover, selecting contractors in accordance with these criteria ensures the implementation of sustainable construction projects, taking into account the specific geographical and environmental conditions of Kish Island, while fulfilling sustainability requirements such as carbon footprint reduction and ecosystem preservation. Overall, the integration of economic, social, and environmental dimensions provides a practical and actionable framework for project managers’ decision-making, enhancing the competitiveness of construction companies and promoting the sustainable performance of projects.
Conclusison
Based on the findings of the study, it can be concluded that contractors who demonstrate strong performance across the twelve identified criteria in the economic, social, and environmental dimensions have a greater capacity to achieve the sustainable development objectives of construction projects. Design-build contracts further enhance this capacity by fostering team integration, efficient communication, and innovative solutions, and by selecting contractors based on maximum value rather than the lowest price. The economic evaluation of contractors should focus on financial credibility, resource management, and cost optimization while maintaining service quality. The social evaluation should encompass human resource management, social capital, professional ethics, and stakeholder engagement. The environmental evaluation should assess contractors’ capability and experience in implementing sustainable processes, waste and energy management, and environmental training. Complementary measures include the development of multidimensional evaluation systems, creation of a contractor performance database, and interdisciplinary assessments. The study’s limitations include difficulties in accessing experts and the restricted generalizability of the results beyond Kish Island. Future research could develop the current study by applying advanced quantitative methods under uncertainty and establishing mechanisms for continuous monitoring and performance evaluation of contractors.
project management
mohammad forozandeh; Amirali Foukerdi; majid salamati
Abstract
Navigating the complexities of modern financial markets requires a comprehensive understanding of the future of venture capital fund management. This involves innovative design and the adoption of new methodologies for managing knowledge-based projects. A promising strategy is the establishment of a ...
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Navigating the complexities of modern financial markets requires a comprehensive understanding of the future of venture capital fund management. This involves innovative design and the adoption of new methodologies for managing knowledge-based projects. A promising strategy is the establishment of a Project Management Office (PMO). This article aims to develop a robust implementation framework for the PMO, enhancing the management of knowledge-based projects, improving the investment ecosystem, and fostering strategic partnerships with co-investors. The study assesses the current maturity within a fund, evaluating related processes and infrastructures from the stakeholders' viewpoints. Data were gathered through interviews with five experts and analyzed using the Organizational Project Management Maturity Model. The results indicate that creating an effective PMO framework necessitates a thorough situational analysis, maturity assessment, and identification of improvement starting points, structured into four key steps: team preparation, current state assessment, maturity level identification, and action planning to achieve organizational objectives.IntroductionIn contemporary finance, investment funds are tasked with establishing and managing diverse portfolios aimed at profit generation. Fund management involves a systematic approach, encompassing several phases from the initial evaluation of proposals to the execution of investment contracts, followed by ongoing management and exit strategies. The development of effective mechanisms throughout these processes is crucial, as they are regarded as key success factors that can enhance the fund's financial capital and credibility within the investment ecosystem. The implementation of a structured system for planning, monitoring, and controlling investments is vital. Typically, this is facilitated by a Project Management Office (PMO), which acts as a dynamic management framework to achieve the strategic objectives of the fund. The PMO oversees the definition, implementation, supervision, and control of projects at various organizational levels, thereby maximizing coordination and efficiency among units and enhancing the effectiveness of achieving organizational goals.National economic growth and development hinge on the successful execution of projects and the support of diverse business sectors. In the context of Iran's economy, empowering knowledge-based enterprises has emerged as a strategic response to economic challenges. National policies, including those outlined in Article 44 of the Constitution and various development plans, emphasize the knowledge-based economy as a priority area. However, the advancement of such businesses faces significant barriers, including limited financial resources, inadequate market knowledge, insufficient governmental support for technology transfer, and challenges related to branding and market expansion (Gholami et al., 2018).The purpose of this paper is to present a Project Management Office framework in a venture capital fund. For this purpose, the maturity level of the organization and the current project management processes examined in the fund under study are assessed, and superior solutions are presented to increase the maturity level of project management processes. This framework is designed based on the primary and secondary functions of the Project Management Office in the venture fund. In this regard, first, by reviewing the research background in the two areas of venture capital funds and Project Management Offices, the general and specialized functions, implementation processes, prominent models used, and their adaptation for use in the investment industry are investigated. Then, the steps of using the Project Management Office in an applied case are followed and implemented.MethodsThe present study is in the field of applied research from the perspective of the objective and follows a case study method. The research uses the opinions and views of experts and, therefore, from the perspective of type, is considered descriptive survey research. The elements of the research method are presented in several steps. In this study, the self-assessment method based on the OPM3 cycle was used. Due to the need for decision-making, resource allocation, and review and modification of business goals and strategies, this study includes only the first to third steps of implementation; the follow-up of the next steps falls outside the scope of this research. One of the important assumptions of this research was the need to focus the study on the scope of project management and portfolio management, excluding the scope of program management from the research domain.In the first step, a comprehensive analysis of the current environmental situation of the organization, including human skills, capital, and tools available to the organization, was conducted. The output of this step is to determine the requirements and framework for the implementation of the Project Management Office in the organization and to develop an improvement plan in the third step of implementation.Discussion and resultsIn this paper, Bamdad Capital Management Company's venture fund was considered as the spatial domain of the research. This company began its activity in 2019 with the participation of Bahman Entrepreneurship Development Company (a subsidiary of Barakat Knowledge-Based Holding), with the aim of investing in, leading, and financing various projects. The company invests in health, energy, metal and mining industries, agriculture, and food. Currently, Bamdad Capital Management is responsible for leading and managing three investment funds, one of which is the 200-billion-toman venture fund for the development of entrepreneurship. This fund has so far invested in 12 projects over a seven-year period.The results show the overall maturity status of the organization by project and portfolio domains. Due to the heterogeneity of expert opinions, the percentage of maturity and immaturity of the processes has been calculated using the weighted average of "yes" and "no" answers given by the five experts. Also, in the standardization stage, no superior solution proposed by the OPM3 standard has been fully and continuously implemented in the project management processes (project scope) of the studied company.ConclusionIn the studied fund, the processes of risk, cost, and time management (with a maturity of more than 50%) have been considered by managers from the very beginning. Examining how much time (investment) and the amount of risk of a project can achieve the expected goals has led to an increase in maturity in the processes related to risk management, cost management, and time management compared to other areas. However, the organization has not yet reached full maturity in these areas. In addition to these knowledge areas that show the highest level of maturity in the organization, increasing the maturity of other areas—especially communication management and stakeholder knowledge (with maturity less than 20%), which relates to how to communicate and interact with various stakeholders, especially investors and entrepreneurs—should be seriously considered in planning for organizational improvement. Other knowledge areas such as scope management, integration, logistics, quality, and human resources (with maturity between 20% and 50%) also require tailored improvement plans. The best solutions for each field should be identified and implemented to elevate maturity levels. The results of this research can be compared with similar studies in other industries to identify influential components. Future researchers can use models and simulations to investigate the impact of effective components and characteristics on this research topic. Moreover, future research can explore the influence of external factors such as economic and political changes on venture capital funds.
project management
Ali Namazian; Somayeh Behboodian
Abstract
Projects, during their execution, face various risks that can impact the achievement of project objectives. Therefore, the need for extensive project risk management is widely recognized. In a systematic risk management process, after risk evaluation, risk analysts are confronted with the risk response ...
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Projects, during their execution, face various risks that can impact the achievement of project objectives. Therefore, the need for extensive project risk management is widely recognized. In a systematic risk management process, after risk evaluation, risk analysts are confronted with the risk response phase, where they decide on the actions to be taken regarding identified risks. Hence, designing and implementing a structured approach to manage and mitigate risks will yield beneficial outcomes for successful completion within the desired budget, time, and quality. In conducted studies, a comprehensive approach that integrates the time and cost implications of risks and response strategies has been lacking. In this article, an optimization model of zero-one programming has been employed to select the most suitable risk response strategies for the project. In the developed framework, the modeling of the impact of risks on the time and cost of activities, as well as the effect of implementing risk response strategies on reducing the undesirable time and cost implications of risks, has been utilized to select optimal strategies. Finally, to evaluate the efficiency of the model, an industrial case study was utilized, which confirmed the favorable performance of this framework.IntroductionEvery project throughout its lifespan faces opportunities and risks. Risks are uncertain outcomes or consequences of activities or decisions. Therefore, in the project planning process, it is necessary to identify potential risks and then consider appropriate strategies to deal with various risks. In this article, a mathematical programming model is used to evaluate and analyze project risks and to select project risk responses. This model considers the probabilistic nature of risk events and develops an index for evaluating the time and cost impacts of risks, as well as response strategies. The proposed approach can be used to select the best combination of risk response strategies that have the most impact on the time and cost of implementing activities, resulting in completing the project with minimum time and cost.Literature ReviewDifferent models have been developed for project risk management to enhance success in development projects. These approaches utilize various structures and tools to quantitatively or qualitatively model the selection of risk response strategies for the project. In recent years, due to unexpected events such as financial crises, significant delays have occurred in projects worldwide (Motaleb, 2021). Thus, researchers have attempted to propose various methods to mitigate the effects of risks in recent years.In the Zonal-based approach, two selected criteria based on risks are plotted on the horizontal and vertical axes, respectively. The two chosen criteria are the weighted probability of immediate project risk and external project risk, and the controllability and specificity of the risks related to the project. Based on the different values of these two criteria, a two-dimensional chart consisting of multiple regions is formed. Different strategies are placed in the corresponding regions. Therefore, suitable strategies can be selected based on the regions formed by the coordinates of the two criterion values.In the Trade-off-based approach, in order to identify the selected risk for formulating response strategies, exchanges are conducted considering the project's goals, requirements, and managers' mental settings among risk-related criteria such as cost, success probability, percentage of work losses, duration, quality, etc. Then, desirable strategies can be selected from the options based on the efficiency frontier rule.The approach based on WBS is considered a risk management and project management method. This choice aligns the risk response strategy with the work activities based on WBS analysis of the project. (Guan et al., 2023) developed an integrated approach based on an optimization model and fault tree analysis for budget allocation in response to risk from safety and prevention perspectives.The optimization approach involves creating a mathematical model to solve the problem of selecting risk response strategies. In general, the objective function aims to minimize the cost of implementing strategies, and the constraints include combinations of strategies, an acceptable level of risk loss, budget for implementing strategies, etc.MethodologyIn this study, a set of work activities is considered, and for each work activity, there may be associated risks that can have an impact. Then, risk response strategies are modeled to determine the most desirable strategy. The zero-one programming technique is used to solve the model. By solving the model, strategies are selected that maximize the estimated impact of risk response after implementation and minimize the cost of implementation. In the proposed model, a set of actions is selected in a way that satisfies the system constraints and optimizes the corresponding objective function. The objective function can be related to time or cost, and the goal of the model is to minimize project completion time or project cost. The model constraints are related to time and cost. The time constraint means that selected strategies should not exceed the specified time frame for their execution and impact on time. The cost constraint means that selected strategies should not exceed the budget and predefined cost in terms of their cost and impact on cost. ResultsThe model presented in this study has an objective function and nine constraints. The purpose of this model is to determine strategies that minimize project completion delay and help achieve and improve project goals. Due to the structure of the modeling, including the objective function and problem constraints, the complexity of the model will change polynomially based on the number of risks, response strategies, and project activities. If simulation-based approaches are used to solve the model, considering the binary nature of project risks and replacing it with the expected value, the complexity of the solution approach will be exponential. Therefore, using the logic of expected value to calculate the duration of activities and project completion time will accelerate the solution process.Discussion and conclusionsIn a systematic project risk management process, after assessing the risks, the implementation of project risk response strategies takes place. The conducted research has generally provided general solutions, and there is no comprehensive model for evaluating project risk reduction measures. In this article, a mathematical optimization model has been developed by considering the risks and response strategies as independent variables for each work activity. Essentially, based on the potential risks that may occur for each work activity, strategies are chosen to minimize project completion delay and reduce the incurred costs, ultimately achieving the project's completion with the least delay and cost. Implementing risk response strategies to mitigate the time and cost impacts of risks requires time and investment. Therefore, selecting these strategies will be justifiable when the time and cost benefits derived from their implementation are greater than the time and cost spent.
project management
ali mohaghar; Fatemeh Saghafi; Ebrahim Teimoury; Jalil Heidary Dahooie; Abdolkarim sabaee
Abstract
The application of supply chain management within the construction industry presents significant challenges due to the transient nature of construction projects, high levels of customization, low repeatability of activities, absence of a production line, and interdependent relationships among activities. ...
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The application of supply chain management within the construction industry presents significant challenges due to the transient nature of construction projects, high levels of customization, low repeatability of activities, absence of a production line, and interdependent relationships among activities. Construction supply chains are intricate systems, where the final performance results from numerous decisions made across multiple independent companies. Interactions among supply chain stakeholders and the unique characteristics of each project create complex phenomena with multiple interconnected elements and variables. The Viable System Model (VSM), rooted in organizational cybernetics, provides a structured approach to addressing complex and unstructured problems. This structured approach allows analysts to gain in-depth insights into the functional issues of the existing system and understand how to modify the system design to adapt to internal and external disruptions.MethodologyDespite the extensive capabilities of the Viable System Model as a diagnostic tool for assessing organizational structure and achieving viability, a systematic and distinct methodology for its application is lacking. Researchers in VSM often do not employ a specific methodology for systems analysis. In this study, we propose a methodology for applying the VSM as a diagnostic tool for organizations, derived from a review of theoretical foundations and practical requirements of VSM. Building on Jackson's methodology outlined in his book "System Thinking, Creative Holism for Managers," we have developed a methodology by integrating Jackson's approach with case study research. This methodology includes stages such as designing a diagnostic framework, selecting case studies, identifying systems, conducting system diagnosis, and validating the model. We applied this methodology to diagnose the supply chain of an Iranian petrochemical construction project, resulting in the development of a viable system model. The validity of the research methodology and findings was confirmed through expert participation and the application of multiple qualitative criteria.ResultsFollowing the selection of a case study and the identification of systems, we investigated the existence and function of five subsystems and communication channels within the focal system using a case study approach to gather information and develop the viable system model. Data was collected through semi-structured interviews conducted at various managerial and technical levels within a prominent project-oriented company in Iran's petrochemical industry. These interviews lasted between 45 and 60 minutes each. Data collection methods also included observation and document examination. The research involved a semi-structured interview with 18 individuals to explore complications within each of the five systems. Subsequently, the collected data was adapted to the model's requirements, and findings were extracted through intra-case analysis and coding. This process led to model development and the identification of weaknesses within the construction supply chain from the perspective of the five systems and communication channels, with a focus on achieving viability.ConclusionsThe developed model highlights weaknesses and bottlenecks within the focal system, shedding light on the most significant issues. A critical issue identified in the case study is the evident lack of coherence within System 4 and System 5. The results reveal that the incoherence of System 5, divided between parts of the company at level 0 and the parent company at a higher recursion level outside the focal system, results in defects within the communication channels related to this system, including C14 (Connection of System 4 with System 5), C9 (Algedonic channel), and C16 (Connection of System 5 with the homeostatic loop of Systems 3 and 4). Additionally, System 4, which is jointly managed by a segment of the company and the project management consultant, leads to disruptions in channels related to this system, particularly C13 (Homeostatic loop between Systems 3 and 4), C14 (Communication between System 4 and System 5), and C15 (Homeostat of System 4 with the future environment). Concerning common errors, the dominant error is E5, attributed to the lack of coherence between Systems 4 and 5 and the weak performance of System 2. This error largely stems from inconsistencies between the two operational units responsible for the engineering phase and the construction and installation phase. To achieve viability within the focal system, several measures should be taken, including the establishment of centralized Systems 4 and 5 within the company and strengthening communication channels with incomplete or insufficient capacity. These channels include the connection between System 4 and System 5 (C14), the Algedonic channel (C9), the connection of System 5 with the homeostatic loop of Systems 3 and 4 (C16), the homeostatic loop of System 3 and System 4 (C13), and the homeostat of System 4 with the future environment (C15). A crucial homeostatic link involves the communication and interaction between System 3 and System 4 (C13) to establish dynamic communication between the current project environment and its future. However, the interaction between these two systems is currently conflicting and misaligned due to the lack of coherence within System 4 and differences in functionality between System 3's perspective on the current state and System 4's perspective on the future state. Balancing the emphasis on System 4 and the future with the daily operations of the supply chain's operational units within System 1 is essential to avoid supply chain disruptions or inefficiencies. The lack of coherence within System 4 also affects the performance of other systems, particularly System 5, as well as the stability of System 4 in relation to the future environment. Inadequate information about the future environment can hinder informed decision-making within the system. By addressing these points within the model, the construction project's supply chain can move toward viability and better adapt to changes in the project environment. This research represents one of the limited studies in the implementation of VSM within the construction project environment.
project management
Yahya Dorfeshan; Seyed Meysam Mousavi; Behnam Vahdani
Abstract
Critical path method is one of the most widely used approaches in planning and project control. Time is considered a determinative criterion for the critical path. But it seems necessary to regard other criteria in addition to time. Besides time criterion, effective criteria such as quality, cost, risk ...
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Critical path method is one of the most widely used approaches in planning and project control. Time is considered a determinative criterion for the critical path. But it seems necessary to regard other criteria in addition to time. Besides time criterion, effective criteria such as quality, cost, risk and safety are considered in this paper. Then, the developed problem is solved as a multi-attribute decision making problem by a new extension of MULTIMOORA method. Moreover, type-2 fuzzy sets are utilized for considering uncertainties. Type-2 fuzzy sets are more flexible and capable than type-1 fuzzy sets in reflecting uncertainties. Eventually, SWARA method is developed for determining the weights of efficient criteria such as time, cost, quality, risk and safety under type-2 fuzzy environment. Finally, an applied example has been solved to illustrate the calculations and the ability of the proposed approach. Based on the example, it is clear that the longest path in terms of time criterion is not a critical path, and other influential criteria are involved in determining the critical path. IntroductionToday, in the competitive business environment, project management, planning, scheduling, and project control hold significant importance. One of the widely used and common methods in the field of project planning and control is undoubtedly the Critical Path Method (CPM). In the Critical Path Method, activity durations are predetermined. However, in the real world, many projects and activities are executed for the first time and have considerable uncertainties. Therefore, obtaining an accurate estimate of the time and resources required for activities is challenging. However, considering a single criterion, such as time, will not yield fruitful results, and other influential parameters such as risk should also be taken into account. For example, a path that carries a high level of risk may not be the critical path at present, but it may become critical in the future due to the high risk involved. For this reason, this research explores other influential criteria besides time and considers them in determining the critical path.Materials and MethodsIn this study, the problem under investigation is the determination of the critical path while considering other influential criteria in addition to the time criterion. To achieve this, multiple criteria decision-making methods are used to consider criteria such as time, cost, quality, risk, and safety in determining the critical path. Furthermore, to account for the uncertainties of the real world and incorporate expert opinions, type-2 fuzzy sets are utilized. It should be noted that the MULTIMOORA method is employed for ranking the critical paths, while the SWARA method is used to determine the weights of the influential criteria in determining the critical path. Both methods have been extended and developed in a type-2 fuzzy environment.Discussion and Results Initially, the proposed method is solved considering only the time criterion. As observed, the critical path has changed, indicating the importance of other criteria in determining the critical path. Then, the proposed method is solved considering pairwise combinations of the criteria, where the time criterion is treated as a fixed criterion due to its high importance. In fact, the problem is solved considering time and cost, time and risk, time and quality, and time and risk. By increasing or decreasing each criterion, the critical path changes, demonstrating the significance of all criteria in determining the project's critical path. To determine the critical path, it is necessary to consider all criteria together. These variations in the criteria and the resulting change in the critical path clearly indicate the importance and influence of other criteria in determining the critical path.ConclusionIn this article, an extension of the MULTIMOORA multi-criteria decision-making method is presented in the reference section. Additionally, Type-2 fuzzy numbers, which offer more flexibility and better representation of uncertainties compared to Type-1 fuzzy numbers, are utilized. The MULTIMOORA multi-criteria decision-making method is developed to incorporate these Type-2 fuzzy numbers. The opinions of three experts are used numerically for the time and cost criteria and linguistically as linguistic variables for the quality, risk, and safety criteria. Ultimately, the weights of the influential criteria of time, cost, risk, quality, and safety are determined using the developed SWARA method under Type-2 fuzzy environment. Finally, the most critical path is determined by considering not only the time criterion but also the influential criteria of cost, quality, risk, and safety. Based on the conducted research, a set of criteria including time, cost, quality, risk, and safety are used in this article, and additional criteria can also be added to this set.
