Application of fuzzy TOPSIS framework for selecting complex project in a case company

Purpose This study aims to propose a method known as the fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) for complex project selection in organizations. To fulfill study objectives, the factors responsible for making a project complex are collected through literature review, which is then analyzed by fuzzy TOPSIS, based on three decision-makers’ opinions. Design/methodology/approach The selection of complex projects is a multi-criteria decision-making (MCDM) process for global organizations. Traditional procedures for selecting complex projects are not adequate due to the limitations of linguistic assessment. To crossover such limitation, this study proposes the fuzzy MCDM method to select complex projects in organizations. Findings A large-scale engine manufacturing company, engaged in the energy business, is studied to validate the suitability of the fuzzy TOPSIS method and rank eight projects of the case company based on project complexity. Out of these eight projects, the closeness coefficient of the most complex project is found to be 0.817 and that of the least complex project is found to be 0.274. Finally, study outcomes are concluded in the conclusion section, along with study limitations and future works. Research limitations/implications The outcomes from this research may not be generalized sufficiently due to the subjectivity of the interviewers. The study outcomes support project managers to optimize their project selection processes, especially to select complex projects. The presented methodology can be used extensively used by the project planners/managers to find the driving factors related to project complexity. Originality/value The presented study deliberately explained how complex projects in an organization could be select efficiently. This selection methodology supports top management to maintain their proposed projects with optimum resource allocations and maximum productivity.© 2021, Ahm Shamsuzzoha, Sujan Piya and Mohammad Shamsuzzaman. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at http://creativecommons.org/licences/by/4.0/legalcodefi=vertaisarvioitu|en=peerReviewed

A decision support system for demolition safety risk assessment

Demolition can be defined as dismantling, razing, destroying or wrecking of any building or structure or any part thereof. Demolition work involves many of the hazards associated with construction. However, demolition also involves additional hazards due to unknown factors which makes demolition work particularly dangerous. In order to make the demolition project safer, everyone at a demolition site must be fully aware of the hazards they may encounter and the safety precautions that they must take to protect themselves and their employees. Safety risk assessment is a planning tool that can be used to improve safety performance at demolition site. In the absence of a special tool for demolition safety risk assessment, a prototype Decision Support System (DSS) based on failure mode and effect analysis that enables decision makers to systematically and semi-quantitatively identify, analyze and evaluate safety risks factors in demolition project has been developed. The prototype is named Hybrid Demolition Safety Risk Assessor (HDSRA). It has three modules; (i) safety risk identification, (ii) safety risk analysis and (iii) safety risk evaluation. Module one aids the decision makers to identify thirty-seven safety risks that is developed by reviewing safety literatures and forming consensus among Delphi panel of experts. In addition, the module introduces seven immediate causes that trigger occurrence of those thirty-seven safety risks. The second module comprised a hybrid decision making model based on Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) that relatively estimates likelihood of thirty-seven safety risks with respect to seven immediate causes. The third module evaluates and prioritizes the safety risks by using two ranking methods; Analytic Hierarchy Process (AHP) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The HDSRA prototype is then developed by integrating module 1, 2 and 3 and evaluated by a group of demolition experts. HDSRA acts as information source that can be used by demolition contractors to identify safety risks in a systematic way. Therefore, possibility of raising error during risk identification process in the implementation of demolition work is reduced. Decision support system that is produced by the HDSRA prototype, proactively proposes action that should be taken by demolition safety experts to control risks at workplace. And finally, HDSRA can be also used as a training tool to raise safety awareness among demolition workers

Factors affecting delays in rail transportation projects using Analytic Network Process: the case of Iran

Delays in the implementation and commissioning of rail transportation projects can cause economic dam-ages to project stakeholders and the cities linked by such rail networks. Hence, the current study aims toinvestigate the key delay factors and provides salient recommendations. In this study, multi-criteria deci-sion-making–the Analytic Network Process (ANP) and the DEMATEL (Decision Making trial and evalu-ation laboratory) method was employed to help decision-makers in prioritizing these delay factors andevaluating their interactions, respectively. A Delphi approach was used to validate the study’s findings viaexpert questionnaire surveys–based on a rail transportation development project for the MobarakehSteel Complex (MSC). The study’s findings revealed the management factors as the most important delayfactors, followed closely by the financial, design, and implementation factors. Other potent issues includethe existence of numerous decision-making stations, lack of central role, and sufficient authority for theproject managers are responsible for project delays. Overall, the results show that resolving problemswith the‘management’domain can significantly avoid or alleviate the extent of delays in rail transporta-tion development projects. The study’s findings and recommendations can serve as a policy and consulta-tive instrument for the relevant stakeholders in the railway industry

Multi-criteria decision-making prototype for the 4th construction revolution implementation readiness using intellectual capital perspective

The fourth industrial revolution, so-called Industry 4.0 has transformed the decision-making process by increasing the use of information and digitisation technologies, which resulted in improving the performance and structuring the management process to the industry. Thus, in recent years, the implementation level of information and digitisation technologies in the construction industry, termed as ‘Construction 4.0 (CR4.0)’, has increased rapidly. However, the construction industry has been unable to translate its acquired knowledge into actionable, transformational and strategic goals towards CR4.0. CR4.0 has changed the nature of competitive resources by reshaping the structure and way construction firms work. Construction firms face various technological, human, and process-related challenges. The starting point for this research was based on exploring the potentials in reskilling and upskilling knowledge through the development of Intellectual Capital (IC) of the construction firms. As a result, based on the Resource-based View theory, CR4.0 implementation process has been approached as a knowledge-based innovation which occurred with the development of three IC capitals: Human Capital (HC), Relationship Capital (RC) and Structure Capital (SC ). Hence, this research aims to develop a Multi-Criteria Decision-Making (MCDM) prototype, used to support decision-making in CR4.0 readiness, named as the 'Construction Firm's Industry 4.0 Readiness MCDM (ConFIRM)’. The first objective is to identify the critical criteria of IC that may affect the CR4.0 implementation readiness. The process involved Systematic Literature review and semi-structured interviews. The second objective is to investigate the significant level of IC affecting CR4.0 implementation readiness through Analytical Hierarchy Process (AHP) technique. The third objective is to derive the weightage of criteria and sub-criteria of ConFIRM through Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP). The fourth objective is to develop a prototype called as ConFIRM that comprising of 3 main criteria, 16 sub-criteria and 92 super sub-criteria according to their significance weightage in achieving CR4.0 implementation readiness. The MCDM results indicated HC (37%) to be the most critical CR4.0 main criteria, followed by SC (34%), and RC (29%) respectively. The HC represented the cumulative tacit knowledge within the organisation, and it would be the main generator of intangibles. For the sub-criteria level, the results indicated that “Management Capital (12%)” has been considered the most critical CR4.0 sub-criteria. The second most critical sub-criteria would be the “Experience Capital (10%)”, followed by “Process Capital (8%)”. On the other hand, the “Sustainable Capital (2%)” was the least critical sub-criteria. Then, the weightages were formulated into automated MCDM prototype, where the scores were calculated using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), indicating the CR4.0 implementation readiness. As for the fourth objective, ConFIRM was adopted in real case studies and evaluated based on the judgement of five experts to determine its applicability and validity in evaluating CR4.0 readiness of contracting firms in Malaysia. In the case studies, the experts recognised the performance and effectiveness of ConFIRM as the novel method for CR4.0 readiness evaluation. ConFIRM would be able to add value to the development of CR4.0 strategies by identifying the corrective/preventive actions needed, based on the readiness assessment, before the start of the implementation process

A FRAMEWORK FOR STRATEGIC PROJECT ANALYSIS AND PRIORITIZATION

Projects that support the long-term strategic intent and alignment are considered strategic projects. Therefore, these projects must consider their alignment with the organization’s current strategy and focus on the risk, organizational capability, resources availability, political influence, and socio-cultural factors. Quantitative and qualitative methods prioritize the projects; however, they are usually suitable for specific industries. Although prioritization models are used in the private sector, the same in the public sector is not widely seen in the literature. The lack of models in the public sector has happened because of the projects’ social implications, the value perception of different projects in the public sector, and potentially differing value perceptions attached to the types of projects in different decision-making environments in the public sector. The thesis proposes a generic framework to develop a priority list of the available basket of projects and decide on projects for the next undertaking. The focus of the thesis is on public projects. The analysis in the framework considers the critical factors for prioritization obtained from the literature clustered through the agglomerative text clustering technique. In the proposed framework, 13 critical clusters are identified and weighted using the Criteria Importance Through Intercriteria Correlation (CRITIC) method to develop their ranking using the Technique for Order of Preference Similarity Ideal Solution (TOPSIS) method. In addition, the proposed framework uses vector weighting to prioritize projects across industries. The applicability of the framework is demonstrated through Qatar’s real estate and transportation projects. The outcome obtained from the framework is compared with those obtained through the experts using the System Usability Scale (SUS). The comparison shows that the framework provides good predictability of the projects for implementation

Anticipating Environmental Burdens in Research and Innovation Projects. Application to the Case of Active and Healthy Ageing

[EN] In this paper; for research and innovation projects without environmental goals; a procedure is proposed to operationalize the anticipation and reflexivity of environmental concerns in the initial phases. By using the expert knowledge of specialists; we have first conducted a study to identify the general environmental topics relevant in any kind of research and innovation project not addressing the environment. In a second phase; a strategy is proposed to rank order the topics in terms of environmental relevance by means of the Analytic Hierarchy Process. To illustrate it; the case of Information and Communication Technologies for Active and Healthy Ageing is used because of its increasing importance; and because normal environmental targets are not considered. Results show that; in this case; the most relevant topic to be considered is the primary energy consumption by sources; followed by hazardous solid waste and consumption of non-renewable and scarce materials. According to the experts; these should be the main issues to be considered regarding the environmental sustainability of the outputs of such research and innovation projects. In conclusion; this paper contributes to a better understanding of how to promote a wider integration of environmental sustainability in research and innovation when environmental goals are not initially included.This work was funded by Spanish Agencia Estatal de Investigacion under grants [CSO2016-76828-R and BES-2017-081141]; and the Generalitat Valenciana under grant [AICO/2018/270].Monsonís-Payá, I.; Gómez-Navarro, T.; García-Melón, M. (2020). Anticipating Environmental Burdens in Research and Innovation Projects. Application to the Case of Active and Healthy Ageing. International Journal of Environmental research and Public Health (Online). 17(10):1-21. https://doi.org/10.3390/ijerph17103600S1211710Steffen, W., Grinevald, J., Crutzen, P., & McNeill, J. (2011). 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Key performance indicators selection through an analytic network process model for tooling and die industry

Funding Information: Radu Godina and Pedro Espadinha-Cruz acknowledge Funda??o para a Ci?ncia e a Tecnologia (FCT-MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI).In the last few decades, the fast technological development has caused high competitiveness among companies, encouraging a pursuit for strategies that allow them to gain competitive advantage, such as the monitoring of performance by using key performance indicators (KPIs). However, its selection process is complex since there are several KPIs available to evaluate performance and different relationships between them. To overcome this challenge, the use of a multiple criteria decision-making model (MCDM) was proposed, namely the analytic network process (ANP) through which a reduced number of them are prioritized. To identify which KPIs are suitable for the press cast and die manufacturing industry, a literature review was made, and 58 unique KPIs were identified. Thus, to validate the proposed methodology, a case study was carried out in an automotive press molding industry. With the implementation of the proposed ANP model it was possible to identify 9 KPIs that ensure the correct molding process monitoring, while being aligned with the Balanced Scorecard criteria. The results show that the proposed model is suitable for selecting KPIs for the molding industry.publishersversionpublishe

Improved Methods for Network Screening and Countermeasure Selection for Highway Improvements

Network screening and countermeasure selection are two crucial steps in the highway improvement process. In network screening, potential improvement locations are ranked and prioritized based on a specific method with a set of criteria. The most common practice by transportation agencies has been to use a simple scoring method, which, in general, weighs and scores each criterion and then ranks the locations based on their relative overall scoring. The method does not deal well with criteria that are qualitative in nature, nor does it account for the impacts of correlation among the criteria. The introduction of Analytic Hierarchy Process (AHP) provides agencies with a method to include both quantitative and qualitative criteria. However, it does not address the issue on correlation. This dissertation explores the use of both Analytic Network Process (ANP) and Fuzzy Analytic Network Process (FANP) for their potential capabilities to address both issues. Using urban four-lane divided highways in Florida for bicycle safety improvements, both ANP and FANP were shown to provide more reasonable rankings than AHP, with FANP providing the best results among the methods. After the locations are ranked and prioritized for improvements, the next step is to evaluate the potential countermeasures for improvements at the selected top-ranked locations. In this step, the standard practice has been to use Crash Modification Factors (CMFs) to quantify the potential impacts from implementing specific countermeasures. In this research, CMFs for bicycle crashes on urban facilities in Florida were developed using the Generalized Linear Model approach with a Zero-Inflated Negative Binomial (ZINB) distribution. The CMFs were tested for their spatial and temporal transferability and the results show only limited transferability both spatially and temporally. The CMFs show that, in general, wider lanes, lower speed limits, and presence of vegetation in the median reduce bicycle crashes, while presence of sidewalk and sidewalk barrier increase bicycle crashes. The research further considered bicycle exposure using the bicycle activity data from the Strava smartphone application. It was found that increased bicycle activity reduces bicycle crash probabilities on segments but increases bicycle crash probabilities at signalized intersections. Also, presence of bus stops and use of permissive signal phasing at intersections were found to increase bicycle crash probabilities

An analytic network process model to prioritize supply chain risks in green residential megaprojects

Megaprojects and specifically ‘green’ construction of residential megaprojects can contain significant risks of failure. To design proper risk mitigation strategies, after identifying key risk factors, the next step is to conduct assessments that would facilitate the process of risk element prioritization. Risk assessment comprises the establishment of factor interrelation and discerning the indicators of importance. This research proposes a novel version of an integrated prioritization method and analyzes twelve all-inclusive key supply chain oriented risk factors identified in a previous study. Through a comprehensive literature review three criteria, impact, probability, and manageability are selected. Also, a fourth criterion namely influence rate is included in the model, based on the driving powers that can also be derived from the Interpretive Structural Modeling’s (ISM) assessment. Fundamentally, the calculations hinge on the Analytic Network Process (ANP) method which provides an assessment of the alternatives’ weights based on pairwise comparisons concerning the criteria specified. To enhance the accuracy of the perceptive judgments of the expert panelists, a bell-shaped fuzzy function is used to convert the verbal statements to crisp values. In addition, Row Sensitivity Analysis is administered to check the stability of the results and provide predictive scenarios. To validate the model, a case study, located in Iran, was conducted, where an expert panel consisting of four individuals made the pair-wise comparisons through an ANP questionnaire. Results indicate priority and sensitivity of the alternatives concerning criteria, for the case under study