Project Decisions Research Articles

Multi-criteria analysis of low impact development practices: a case study in the Tan Hoa - Lo Gom basin, Ho Chi Minh city, Vietnam

Abstract Urban flooding poses a significant challenge for cities globally. In recent years, Low Impact Development (LID) has been recognized as an effective and sustainable solution for managing urban floods. This study employs the EPA-Storm Water Management Model (EPA-SWMM), social surveys, and multi-criteria analysis (MCA) to assess the effectiveness of LID practices from environmental, social, and economic sustainability perspectives. Results demonstrated that implementing LID techniques such as rain gardens, infiltration trenches, permeable pavements, and their combinations in the Tan Hoa - Lo Gom basin can reduce the average total runoff volume by 8.77% to 30.80% under the current land use-land cover and the design hyetograph with a 3-hour duration and a 5-year return period. Moreover, there is a reduction of approximately 7.42% to 30.59% in the average total runoff volume for the design hyetograph with a 3-hour duration and a 5-year return period, aiming to assess the climate change impact. Additionally, sociological and economic aspects are integrated to comprehensively assess each LID practice through MCA via the Analytical Hierarchy Process (AHP) method. Overall, the analysis results indicated that the scenarios involving the application of rain gardens, infiltration trenches, and their combinations are more effective than other scenarios. These findings will provide valuable insights for decision-making and planning of other LID projects in Ho Chi Minh City (HCMC) to mitigate urban flooding, particularly in light of the escalating challenges posed by urbanization and climate change.

A spherical fuzzy objective weighting framework for factors affecting bidding decisions for construction projects: A case study of Taiwan

In response to the intensely competitive bidding environment in Taiwan's construction industry, this study innovates with a spherical fuzzy extension of the modified CRITIC method (SFmCRITIC), a pioneering approach crafted to refine the decision-making process. The research centers on the pivotal role of accurately weighting various significant factors, such as financial stability, market insight, and specialized expertise, to optimize bid success rates. The SFmCRITIC method stands out by quantitatively incorporating the uncertainty and subjectivity typically encountered in bid evaluation. The findings from this methodological application demonstrate a clear hierarchy of influencing factors, offering a nuanced view of strategic priorities for construction firms. This hierarchical understanding not only aids firms in targeted resource distribution and strategic development but also holds promise for adaptation in diverse industry contexts beyond Taiwan, potentially revolutionizing bidding strategies at a global scale.

An improved capacitance-resistance model for analysing hydrogen production with geothermal energy utilisation

The integration of geothermal and hydrogen energy through advanced predictive modeling not only enhances energy production efficiency but also contributes significantly to the global transition towards renewable energy sources. This study commences with the establishment of a geothermal hydrogen production model using Aspen Plus, incorporating physical constraints, derived from the Capacitance Resistance Model (CRM) model. Refinements to Long Short-Term Memory (LSTM) neural networks based on historical data and CRM constraints tailor them for geothermal reforming-based hydrogen production. Production analysis indicates that the hybrid CRM-LSTM model adeptly predicts heat and hydrogen production, improving system performance. The approach demonstrates superior accuracy, with hydrogen production predictions deviating by less than 2%. The comparison highlights the hybrid model’s advantage in handling nonlinear characteristics but it also shows the hybrid model requires longer training times. Sensitivity analysis reveals significant implications for investment decisions, with CRM predicting a 26-year cost recovery period under standard conditions, potentially underestimating actual outcomes by over eight months. Such discrepancies underscore the importance of accurate predictive models in guiding investment decisions for sustainable energy projects. This model contributes to achieving sustainable development goals by integrating geothermal and hydrogen energy, advancing the transition towards renewable and environmentally friendly energy sources.

A hybrid approach for risk-informed decision-making in supply chain projects

A hybrid approach for risk-informed decision-making in supply chain projects

Investment decision analysis of shipping desulfurization project based on a fuzzy real option approach

ABSTRACT This study addresses shipping companies’ compliance with the International Maritime Organization’s 2020 sulfur emission limits, providing guidance for investment decisions in desulfurization projects. The paper uses a novel RCFM model, integrating real option theory (R), shipping cycle theory (C), fuzzy set theory (F), and Monte Carlo simulation (M). Key findings are: (1) During high oil price volatility, traditional binary tree models show computational distortions corrected by Monte Carlo simulation, whereas in lower volatility, the fuzzy binary tree model offers reliable investment intervals. (2) Investment in desulfurization depends on remaining vessel life and fuel price differences. For example, during the recovery period, for vessels with a remaining life of less than 5 years, investing in a desulfurizer is profitable if the fuel price difference exceeds $550/t and using low-sulfur fuel is advisable if below $400/t. For vessels of remaining life of 5-9 years, invest in a desulfurizer if the difference exceeds $500/t and use low-sulfur fuel if below $300/t. For over 9 years, invest in a desulfurizer if the difference exceeds $450/t and use low-sulfur fuel if below $200/t.

Methods of wind energy harnessing: A state-of-the-art and bibliometric analysis

Wind energy is one of the most promising alternatives for obtaining a sustainable electricity generation model with low greenhouse gas emissions. The maturity of this technology, coupled with its low investment costs and good performance, makes it highly interesting for countries to develop projects within this field. However, its high operation intermittency caused by the natural behavior of wind requires preliminary research on the technical conditions (Installation, Capacity, Environmental, Legal, Administrative, Logistics) of the geographical area wherein the wind energy project is planned. This paper provides an overview of the state-of-the-art research studies on the potential of wind energy within a territory. This review describes current methodological alternatives for assessing wind energy generation projects and potential energy studies in different geographical areas globally. Therefore, a bibliometric analysis is included, examining the scientific research trends in the field of wind energy in addition to the different technologies and innovations that have contributed to the viability of a greater wind energy generation project. Finally, the study discusses the technical restriction criteria faced by any such project. This paper also seeks to become a point of reference for future reviews and decision-making in wind projects.

Evaluating Stakeholders’ Decisions in A Blockchain-Based Recycling Construction Waste Project: A Hybrid Evolutionary Game and System Dynamics Approach

To promote efficient construction waste recycling and reuse, a novel waste management approach based on blockchain technology was introduced to the industry. However, adopting blockchain platforms in construction waste recycling and reuse may impact the behavioral strategies of stakeholders and impede the prediction of the specific impacts of stakeholders’ decisions. Accordingly, this study addresses two primary questions: (1) What are the collaborative framework and the behavioral evolution trends of multiple stakeholders within the context of blockchain? (2) How can the behavioral strategies of multiple stakeholders be systematically coordinated to achieve efficient construction waste recycling and reuse driven by blockchain? To answer these questions, a tripartite game model combined with system dynamics was constructed. In this model, we aimed to elucidate the internal organizational framework, analyze the dynamic evolution process, and assess the influence of decisions made by multiple stakeholders at the individual level. It also offers corresponding policy recommendations for efficient construction waste recycling and reuse driven by blockchain at the system level. This study offers three innovations. First, it considers the decision-making of multiple stakeholders as an interdependent and coevolutionary process to overcome the defects of analyzing only one type of participant. Second, in contrast to the static analysis method, it employs a dynamic system approach to deeply analyze the evolving structures of blockchain-based projects. Third, it provides a theoretical framework for the practical implementation of blockchain-driven platforms in managing construction waste recycling and reuse, thus fostering effective policy development and management practices. This framework aims to promote sustainable development in construction waste recycling and reuse projects in China as well as globally.

An investment decision framework for offshore CCUS project under interval-valued fermatean fuzzy environment

ABSTRACT Carbon Capture, Utilization and Storage (CCUS) is an indispensable technology for achieving a net-zero emission society. The offshore CCUS project is still in its infancy. To promote its sustainable development, developing a comprehensive framework for investment decision-making is very crucial. First, a comprehensive evaluation criteria system is established. Second, in order to characterize the ambiguity and uncertainty of information in the process of making decisions, the interval-valued fermatean fuzzy set (IVFFS) is introduced, and the extended variance method of IVFFS is proposed to systematically calculate the weights of experts. Then, the power weighted average (PWA) operator based similarity measure of IVFFSs is developed to aggregate different expert information. Meanwhile, the fuzzy-weighted zero-inconsistency (FWZIC) method and the method based on the removal effects of criteria (MEREC) are used to determine the criteria weights. In addition, considering the interactions between the criteria, we introduce the Hamacher operator into the measurement of alternatives and ranking according to the compromise solution (MARCOS) method to select the optimal alternative in the interval-valued fermatean fuzzy (IVFF) environment. The suggested framework is then used to analyse a case study. After that, sensitivity and comparative analyses are conducted to confirm its robustness and viability. This study creates a practical investment framework for offshore CCUS projects, identifies a number of investment-sensitive criteria and provides management insights. The proposed framework expands the methods and applications in the field of decision-making and provides a scientific approach for investment decision-making in offshore CCUS projects, which can be a useful reference for managers.

The tortoise in the urban development network: How social relations affect decision-making speed in a road expansion project in Kristiansand, Norway

ABSTRACT Why do urban development projects take a long time to complete? This question is of paramount importance, both practically and academically. Practically, understanding the reasons for delays in these projects can help improve project efficiency, reduce costs, and enhance stakeholder satisfaction. Academically, the study contributes to the field of urbanization by applying social network analysis (SNA) to explore the interactions and relationships among decision-makers in urban development projects. This study draws upon original data from a road extension project in Kristiansand to illustrate and explain why the implementation of large development projects suffers from convoluted and slow decision-making processes after an overall agreement on project aims and goals has been established. This study draws on a sample of 33 actors who participated in the decisions concerning the project. I collected the data through a combination of interviews and document reviews and subsequently analyzed them using social network structural metrics and visualization techniques. The results show that the actors are connected in less dense, more centralized, and clustered networks with subgroups and low reciprocity which have hampered efficient communication, resulting in delays. The findings imply that the pattern of relationships among decision-making actors can affect the amount of time taken to reach conclusions in urban development initiatives.

Life Cycle Assessment of Single-Story Low-Income Housing: A Brazilian Case Study

This study aims to assess the environmental impacts of different construction systems employed in a single-story low-income housing development utilizing Life Cycle Assessment (LCA). The LCA was applied to the roof, wall, coating, and floor systems, considering the initial and recurring impacts from extraction to material replacement. Data were quantified using the CML 2001 method with OpenLCA 1.9 software. The analyzed impact categories are the potential for the depletion of abiotic resources—non-fossil (ADP); potential for the depletion of abiotic resources—fossil (ADP f); soil and water acidification potential (AP); eutrophication potential (EP); global warming potential—100 (GWP); stratospheric ozone layer depletion potential (ODP); and photochemical oxidation potential (POCP). The results highlight the impacts related to the maintenance and replacement of materials as the most significant, with walls being the system with the highest concentration of impacts, presenting the highest results among five of the seven categories. In the GWP category, the wall system resulted in 42% of total impacts (initial + recurring impacts). These findings show that the selection and definition of construction materials in the design phase can either mitigate or exacerbate environmental burdens. Therefore, this research contribution lies in pinpointing the environmental impacts of each construction system of low-income housing to support architects and engineers in addressing environmental impacts when making project decisions.

Research on optimal investment decision of distribution network projects under the construction of the new power system

Abstract This article establishes a ranking model of distribution network projects to make optimal investment decisions. The project optimization ranking model consists of the LCC model and the project comprehensive evaluation model. When constructing the evaluation model of distribution network projects, the evaluation index system is first set, and then the weight allocation for each index is calculated based on the G1-antientropy weight comprehensive integrated weighting method, so as to calculate the comprehensive benefit of the unit cost of a project for optimal sorting. Taking a distribution network planning project in Sichuan Province as an example, the empirical analysis is conducted, and the ranking results are obtained by using the above optimization ranking model for distribution network projects depending on the comprehensive benefit index of unit cost of the project A-E, which confirms the reasonability and practicability of the decision-making system and realizes the optimization of investment decisions for distribution network projects.

DESIGN OF THE ARCHITECTURE OF THE AUTOMATED SYSTEM FOR CREATING THE ACCOMPANYING DOCUMENTATION OF THE EDUCATIONAL PROCESS

Background. The architecture of the automated system is the main source of quality of software and software-hardware systems. It determines how quickly and efficiently a developer is able to analyze, understand, test, extend, and maintain an automated system. Changes in the system architecture have a high cost due to its complexity and the possibility of destruction during expansion. At present, most of the knowledge and information about the design decisions on which the architecture is based are implicitly embedded in it, which leads to problems during the development process, in particular, during the programmatic implementation of its structural elements. It is determined that, despite the long way that the evolution of systems architecture has passed, today there are very few objective, repeatable and empirically based methodologies and tools for the design and analysis of architecture. As a rule, software architects are programmers who have decades of experience in software development practice. Given their experience, they clearly understand that errors in the architecture design are the root causes of lower-level problems that manifest in the software code. Most often, a programmer feels when the architecture of his project is of low quality, because there are a large number of technical flaws, the number of which only increases with time. But most projects continue to be implemented, which leads to a decrease in the quality of the finished automated system. Objective. The purpose of this work is to design and document the software architecture of the automated system for creating the accompanying documentation of the educational process in order to take the first step towards understanding the relationships and the impact of the adopted project decisions on the code base. Conclusions. To achieve the goal, a class of multi-level architectures was chosen, among which the three-level architecture is the most common. Features of implementation of open and closed three-level architectures are considered. On the basis of the MVC architectural template, an architectural project of an automated system for creating accompanying documentation of the educational process has been developed. The main subsystems and data elements are documented.

Are public transit investments based on accurate forecasts? An analysis of the improving trend of transit ridership forecasts in the United States

Historically, forecasts of travel demand on public transit infrastructures have been found to be optimistically biased. However, there has been a lack of data available for statistically significant analysis of factors affecting the accuracy. This paper analyzes the overall trend of transit ridership forecast accuracy in the US and contextualizes it with ridership trends based on the largest yet database of 164 large-scale transit infrastructure projects in the US. We find that transit ridership is about 24.6 % lower than forecast on average with about 70 % of the projects over-predicting ridership. Forecast accuracy varies by mode, service area characteristics, familiarity with transit, ramp up period, and time span. The accuracy has been getting better over the years, particularly after 2000 with the introduction of new analytical and evaluation tools as part of the Capital Investment Grants program. Projects that have been forecasted since 2000 have average ridership about 22 % lower than forecast, compared to about 52 % lower from pre-2000. The steadily improving accuracy, however, is offset by the unexpected decline in transit ridership since 2012. Advent of ride-hailing services and improved socio-economic trends that support auto-oriented cities have prompted this decline in ridership and have affected their forecasts as well. Despite the improving trend, we find that there remains substantial deviation in the outcomes from their forecasts. This points to the need of better scrutiny of model inputs and specifications and how they interact with the built environment to unearth the underlying reasons for inaccuracy. Planners and policymakers may make use of our results to advocate for considering the uncertainty around forecasts for any project and funding decision.

Управління стійким розвитком підприємств агропродовольчої сфери в контексті інноватики персоналу та трансферу знань

The article is devoted to managing the sustainable development of agro-food enterprises in the context of personnel innovation and knowledge transfer. Based on the research, it was proposed that the factors influencing the sustainable development of agro-food enterprises be arranged. The purpose of the study was to study the management of sustainable development of agro-food enterprises in the context of personnel innovation and knowledge transfer. The transition to a modernization development model is possible because the state reduces funding (primarily from budget funds) to the full extent of its vulnerable sectors of the economy, especially the extractive industries and industrial production. The primary funding should be directed to the creation of innovative products that ensure the increase in the competitiveness of the Ukrainian economy and the development of high-tech production (ensuring the formation of innovative clusters of the economy thanks to the definition of “growth points” that allow for more effective dissemination of innovations); establishing the transparency of investment decision-making and budgetary financing of innovative projects, ensuring their reasonableness and expediency; active fight against corruption and the introduction of effective public control over the execution of state orders when conducting competitions (tenders) for investment projects. The characteristics of factors affecting socio-economic development should be considered in more detail within the following groups: international, environmental, financial and economic, demographic, socio-cultural and, political and legal factors. Factors of indirect influence have the same effect on all economic entities in the same strategic group. Therefore, their influence on the competitiveness of economic entities in the agro-food sector cannot be considered decisive. Management decisions made with the help of feedback may significantly reflect the factors of indirect influence on the management of the sustainable development of agro-food enterprises in the context of personnel innovation and knowledge transfer, which is the subject of further research. Keywords: management, sustainable development, enterprises, agro-food sector, innovation, personnel, knowledge transfer, innovation management, personnel management.

Optimal site selection of electrochemical energy storage station based on a novel grey multi-criteria decision-making framework

A scientific and reasonable siting decision is the key to ensure the smooth operation and positive results of the project. In this paper, a grey multi-criteria decision-making (MCDM) method is proposed and applied to the siting of electrochemical energy storage station (EESS) projects. First, this paper constructs an criteria system consisting of 5 criteria and 22 sub-criteria. Second, considering the uncertainty and hesitation of decision makers (DMs), grey numbers are used to describe the evaluation information of DMs, and further decision information is mined through secondary evaluation based on the initial evaluation. Third, considering the unique situation of the EESS with many criteria, equal importance and interdependence among criteria, the improved best-worst method (IBWM) expands the scope of application to make the decision-making process more realistic. Fourth, in order to reduce the loss of information, the grey entropy method and the probability-based WISP method are proposed. Finally, the validity and feasibility of the method is verified through case studies. The results show that P2 is the optimal choice. This work has important theoretical significance and practical application value, and provides a reference basis for early decision-making of the EESS project.

THE METHOD OF RANKING EFFECTIVE PROJECT SOLUTIONS IN CONDITIONS OF INCOMPLETE CERTAINTY

The subject of research in the article is the process of ranking options in support systems for project decision-making under conditions of incomplete certainty. The goal of the work is to increase the efficiency of technologies for automated design of complex systems due to the development of a combined method of ranking effective options for building objects in conditions of incomplete certainty of input data. The following tasks are solved in the article: analysis of the current state of the problem of ranking options in support systems for project decision-making; decomposition of problems of system optimization of complex design objects and support of project decision-making; development of a variant ranking method that combines the procedures of lexicographic optimization and cardinal ordering in conditions of incomplete certainty of input data. The following methods are used: systems theory, utility theory, optimization, operations research, interval and fuzzy mathematics. Results. According to the results of the analysis of the problem of supporting project decision-making, the existence of the problem of correctly reducing subsets of effective options for ranking, taking into account factors that are difficult to formalize and the experience of the decision-maker (DM), was established. Decomposition of the problems of system optimization of complex design objects and support for project decision-making was carried out. For the case of ordinalistic presentation of preferences between local criteria, an estimate of the size of the rational reduction of subsets of optimal and suboptimal options for each of the indicators is proposed. Its use allows for one approach to obtain a subset of effective variants of a given capacity for analysis and final selection of the DM. A method of transforming the ordinalistic presentation of preferences between local criteria to their quantitative presentation in the form of weighting coefficients is proposed. Conclusions. The developed methods expand the methodological foundations of the automation of processes supporting the adoption of multi-criteria project decisions. They make it possible to correctly reduce the set of effective alternatives in conditions of incomplete certainty of the input data for the final choice, taking into account factors that are difficult to formalize, knowledge and experience of ODA. The practical use of the obtained results will allow to reduce the time and capacity complexity of the procedures for supporting project decision-making, and due to the use of the technology of selection of subsets of effective options with intervally specified characteristics - to guarantee the quality of project decisions and to provide a more complete assessment of them.

Research on Critical Factors Influencing Organizational Resilience of Major Transportation Infrastructure Projects: A Hybrid Fuzzy DEMATEL-ISM-MICMAC Approach

To strengthen major transportation infrastructure projects’ (MTIPs’) organizational resilience and fortify their capacity for crisis management and project risk prevention. In this paper, based on the resilience theory development process, the connotation of organizational resilience of MTIPs is defined, and 20 influencing factors of organizational resilience of MTIPs are extracted from four categories of stability, redundancy, adaptability, and rapidity according to the literature analysis and case study method. The significance, causality, and multilevel recursive order structure of the influencing factors were investigated by the fuzzy DEMATEL-ISM approach, and their driving and dependent characteristics were analyzed through MICMAC. The results indicate that risk warning and prediction, human resources management, inter-organizational synergies, resource reserve situations, organizational leadership, and organizational learning are the crucial factors of organizational resilience in MTIPs. There are three levels and five ranks in the multilevel recursive rank structure of the factors affecting MTIPs’ organizational resilience. Among them, risk warning and prediction, equipment condition and performance, human resources management, and organizational leadership have the deepest impact on organizational resilience in MTIPs. The findings can clarify ideas for subsequent research on organizational resilience in this area and inform project decision-makers in developing strategies for optimizing organizational resilience.

NUMERICAL SIMULATION OF THE SPATIAL MODEL OF THE DAMAGED NINE-STORY BUILDING FOR STRENGTH AND RIGIDITY ASSESSMENT BASED ON SURVEY RESULTS

The paper presents the main ideas and possibilities of creating a complex spatial numerical model, research and analysis of the stress-strain state, strength and stiffness of a damaged nine-story building with the help of our own software, using the modified method of straight lines, and the calculation software complex LIRA from the action of a complex load based on the results of an engineering survey by experimental methods. The created complex model of the building based on BIM technologies is used for further adoption of optimal project decisions and significantly accelerates project work. The results of a numerical study of a complex spatial model and conclusions about the strength characteristics of structures and the building as a whole significantly expand the possibilities in making project decisions and creating promising developments based on them.

Extending CityGML with public input – social ADE

PurposeThis paper aims to enrich the 3D urban models with data contributed by citizens to support data-driven decision-making in urban infrastructure projects. We introduced a new application domain extension to CityGML (social – input ADE) to enable citizens to store, classify and exchange comments generated by citizens regarding infrastructure elements. The main goal of social – input ADE is to add citizens’ feedback as semantic objects to the CityGML model.Design/methodology/approachFirstly, we identified the key functionalities of the suggested ADE and how to integrate them with existing 3D urban models. Next, we developed a high-level conceptual design outlining the main components and interactions within the social-input ADE. Then we proposed a package diagram for the social – input ADE to illustrate the organization of model elements and their dependencies. We also provide a detailed discussion of the functionality of different modules in the social-input ADE.FindingsAs a result of this research, it has seen that informative streams of information are generated via mining the stored data. The proposed ADE links the information of the built environment to the knowledge of end-users and enables an endless number of socially driven innovative solutions.Originality/valueThis work aims to provide a digital platform for aggregating, organizing and filtering the distributed end-users’ inputs and integrating them within the city’s digital twins to enhance city models. To create a data standard for integrating attributes of city physical elements and end-users’ social information and inputs in the same digital ecosystem, the open data model CityGML has been used.

Cultural Influences on Problem Solving and Decision-Making in Student Projects: A Comparative Study between Indonesia and Germany

Cultural Influences on Problem Solving and Decision-Making in Student Projects: A Comparative Study between Indonesia and Germany