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This study aims to identify and assess the significant risks in Yemen oil and gas construction projects based on their risk rating (impact and probability) by using probability–impact matrix (PIM).

In total, 51 risk factors that might affect construction projects in the oil and gas sector are defined through a detailed literature review and expert judgment. The risk factors were tabulated in a questionnaire form, which was sent to a total of 400 participants asking their contribution in identifying the risk matrix for the risk factors in terms of impact and probability of occurrence during the project life cycle. Five zones were used in the matrix according to the degree of risk factor’s severity on the success of the project. These zones are light green, dark green, yellow, light red and dark red.

The PIM analysis for risk factors found that five factors are located in the dark red zone, as top risks factors have a very high impact and very high probability of occurring; 40 factors are located in the light red zone; six factors are located in the yellow zone; and no factors are located in the green zone (light and dark), which is considered an indication of the importance of risk factors under study and their impact on the success of construction projects in the oil and gas sector. Moreover, the factors under feasibility study and design and resources and material; are the most categories effect on project success.

The research was limited to the oil and gas construction projects in Yemen.

Practically, this study highlights the top risk factors in oil and gas construction projects, which might cause an adverse effect on project success in Yemen. Classification and ranking of these factors by using the risk matrix provide the basis for risk response planning to enhance the chances of project success.

This paper identifies the matrix for risk factors affecting the success of construction projects in the oil and gas industry in Yemen. There is a significant contribution expected from this research, especially for companies operating in the oil and gas sector and other organizations that plan to invest in this field, in addition to expected benefits for the Yemeni Government and researchers because of lack of research in this area.

Traditional risk assessment (RA) methodologies cannot model vagueness in risk and cannot prioritize corrective-preventive measures (CPMs) by considering effectiveness of those on risk types (RTs). These cannot combine and reflect accurately different subjective opinions and cannot be used in a linguistic manner. Risk factors (RFs) are assumed to have the same importance and interrelations between RFs are not considered. This study aims to overcome these disadvantages by combining fuzzy logic with multi-criteria decision-making in a dynamic manner.

This study proposes a novel three-stage fuzzy risk matrix-based RA integrating fuzzy decision-making trial and evaluation laboratory (F-DEMATEL) and fuzzy multi-attributive border approximation area comparison (F-MABAC). At the first stage, importance weights of RFs are computed by F-DEMATEL. At the second stage, risk degrees of RTs are computed via using fuzzy risk matrix. At the third stage, CPMs are ranked by F-MABAC. Finally, a numerical example for RA in a warehouse is given.

Results show that developing instructions for material loading or unloading is the most important CPM and severity is the most important RF for the warehouse.

This study has originality in terms of having fuzzy dynamic structure. At first, RFs are assumed to be criteria sets then, RTs are assumed to be criteria set considering their risk degrees to rank CPMs in a fuzzy manner. Risk degrees of RTs are used for weights of RTs and effectiveness of CPMs are used for performance values of CPMs.

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.

A Mamdani fuzzy logic inference system is coupled with a traditional, categorical risk assessment framework to understand a facilities’ consequence of failure and its effect on an organization’s strategic objectives. Model performance is evaluated using the US Air Force’s facility portfolio, which has been previously assessed, treating facility replicability and interruptability as minimization objectives. The fuzzy logic inference system is built to account for these objectives, but as proof of ease-of-adaptation, facility dependency is added as an additional risk assessment criterion.

Results of the fuzzy logic-based approach show a high degree of consistency with the traditional approach, though the value of the information provided by the framework developed here is considerably higher, as it creates a continuous set of facility prioritizations that are unbiased. The fuzzy logic framework is likely suitable for implementation by diverse, spatially distributed organizations in which decision-makers seek to balance risk assessment complexity with an output value.

This paper fills the identified need for portfolio management strategies that focus on prioritizing projects by risk to organizational operations or objectives.

The purpose of this paper is to present a comprehensive framework for quality-related performance measures linked to supply chain risk (SCR) by analyzing and framing them into a hierarchical structure.

In this paper, quality-related performance measures (QM) are identified on the basis of literature survey and expert opinion. The quality measures are formulated as hierarchy structure and fuzzy AHP as a multi attribute decision-making tool is applied to judge the viable candidates.

Based on a fuzzy AHP approach, a revised risk matrix with a continuous scale was proposed to assess the QMs’ classes. The result classifies the QMs in different categories (extreme, high, medium and low). Based on this result, some management implications and suggestions are proposed.

The present work proposes an assessment methodology for quality-related performance measures linked to SCR. The revised risk matrix with continuous scale for risk assessment in this field is a novel approach. This study contributes to the supply chain management and quality management literature, and provides suggestions for managers to adopt different strategies for different risk classes.

Aviation has multi-cultural business environment in all aspects as operational and management. Managing aviation requires high awareness on human factor risk which includes organizational behavior-related topics. The greatest risk to an enterprise’s ability to achieve its strategic goals and objectives is the human factor. Both organizational behavior and corporate culture behavior with social psychology are the most vital aspects of management and strategy in terms of human resources. Related risks, including organizational behavior and culture, have the potential to directly impact on both business performance and corporate sustainability. Therefore, in this paper, the most prominent risks were determined in accordance with social psychology, and after identification of human factor-based risks, these have prioritized and prepared risk mapping with fresh approach. For this reason, this study aims to develop risk mapping model for human factors that takes into account interrelations among risk factors three dimensional based new approach. This approach includes both identification of human factor based risks, prioritization them and setting risk mapping according to corporate based qualifications via tailoring risk list. Developed risk map in this paper will help to manage corporate risks to achieve improved performance and sustainability.

This new organizational behavior- and culture-focused risk mapping model developed in this study has the potential to make significant contribution to the management of the human factor for modern management and strategy. In enterprise risk management system, risk mapping is both strong and effective strategic methodology to manage ergonomics issue with strategic approach. Human factor is both determinative and also strategic element to both continuity and performance of business operations with safely and sound. In view of management and strategy, vitally, the human factor determines the outcome in both every business and every decision-making.

It is assumed that, if managers manage human risk you may get advantages to achieving corporate strategies in timely manner. Aviation is sensitive sector for its ingredients: airports, airlines, air traffic management, aircraft maintenance, pilotage and ground handling. Aim of this paper is to present risk management approach to optimize human performance while minimizing both failures and errors by aircraft maintenance technician (AMT). This model may apply all human factors in other departments of aviation such as pilots and traffic controllers. AMT is key component of aircraft maintenance. Thus, errors made by AMTs will cause aircraft accidents or incidents or near miss incidents. In this study, new taxonomy model for human risk factors in aircraft maintenance organizations has been designed, and also new qualitative risk assessment as three dimensions is carried out by considering the factors affecting the AMT’s error obtained from extensive literature review and expert opinions in the field of aviation. Human error risks are first categorized into two main groups and sub three groups and then prioritized using the risk matrix via triple dimension as probability, severity and interrelations ratio between risks.

Risk mapping is established to decide which risk management option they will apply for managers when they will look at this map. Managers may use risk map to both identify their managerial priorities and share sources to managing risks, and make decisions on risk handling options. This new model may be a useful new tool to manage ergonomic human factor-based risks in developing strategy in aviation business management. In addition, this paper will contribute to department of management and strategy and related literature.

This study has originality via new modeling of risk matrix. In this study, dimension of risk analysis has been improved as three dimensions. This study has new approach and new assessment of risk with likelihood (probability), impact (severity) and interrelations ratio. This new model may be a useful new tool to both assess and prioritize mapping of ergonomic-based risks in business management. In addition, this research will contribute to aviation management and strategy literature and also enterprise risk management literature.

This paper aims to develop a process for prioritizing project risks that integrates the decision-maker's risk attitude, uncertainty about risks both in terms of the associated probability and impact ratings, and correlations across risk assessments.

This paper adopts a Monte Carlo Simulation-based approach to capture the uncertainty associated with project risks. Risks are prioritized based on their relative expected utility values. The proposed process is operationalized through a real application in the construction industry.

The proposed process helped in identifying low-probability, high-impact risks that were overlooked in the conventional risk matrix-based prioritization scheme. While considering the expected risk exposure of individual risks, none of the risks were located in the high-risk exposure zone; however, the proposed Monte Carlo Simulation-based approach revealed risks with a high probability of occurrence in the high-risk exposure zone. Using the expected utility-based approach alone in prioritizing risks may lead to ignoring few critical risks, which can only be captured through a rigorous simulation-based approach.

Monte Carlo Simulation has been used to aggregate the risk matrix-based data and disaggregate and map the resulting risk profiles with underlying distributions. The proposed process supported risk prioritization based on the decision-maker's risk attitude and identified low-probability, high-impact risks and high-probability, high-impact risks.

Supply chain (SC) environment is surrounded by risk variables. This issue is regarded as an emerging and strategic problem which must be resolved by SC executives. The ability to measuring green supplier’s performance and affecting risk variables to demonstrating effective suppliers list has a potential contribution to be investigated. This paper aims to develop a decision-making model to assess green suppliers under legislation and risk factors. This leads to fewer disruptions in managing the SC and its impact to further improvement. It also presents research concepts forming a new approach for identification, prediction and understating relationship of supply risk.

At primal stage, different risk factors that influence green suppliers’ performance are indicated and their relationship is analyzed using decision-making trial and evaluation laboratory (DEMATEL) method. At the same time, failure mode and effect analysis is used to determine risk rating of each supplier. Finally, the evaluation based on distance from average solution (EDAS) method ranks suppliers and several comparisons and analysis are performed to test the stability of the results. The approaches include comparison to technique for order performance by similarity to ideal solution, multi-attributive border approximation area comparison, Vlse Kriterijumska Optimizacija I Kompromisno Resenje and complex proportional assessment methods, followed by analysis of rank reversal, weight sensitivity analysis and effect of dynamic metrics.

A real-time case study on green supplier selection (GSS) problem of a reputed construction company of Spain has been presented to demonstrate the practical aspects of the proposed method. In practice, though organizations are aware of various risks from local and global suppliers, it is difficult to incorporate these risk factors for ranking the suppliers. This real-case application shows the evaluation and incorporation of risk factors into the supplier selection model.

The proposed multi-criteria decision model quantitatively aids managers in selecting green suppliers considering risk factors.

A new model has been developed to present a sound mathematical model for solving GSS problems which considers the interaction between the supplier selection risk factors by proposing an integrated analytical approach for selecting green suppliers strategically consisting of DEMATEL, FMEA and EDAS methods.

The purpose of this paper is to address the limitations of conventional risk matrix based tools such that both positive and negative connotation of uncertainty could be captured within a unified framework that is capable of modeling the direction and strength of causal relationships across uncertainties and prioritizing project uncertainties as both threats and opportunities.

Theoretically grounded in the frameworks of Bayesian belief networks (BBNs) and interpretive structural modeling (ISM), this paper develops a structured process for assessing uncertainties in projects. The proposed process is demonstrated by a real application in the construction industry.

Project uncertainties must be prioritized on the basis of their network-wide propagation impact within a network setting of interacting threats and opportunities. Prioritization schemes neglecting interdependencies across project uncertainties might result in selecting sub-optimal strategies. Selection of strategies should focus on both identifying common cause uncertainty triggers and establishing the strength of interdependency between interconnected uncertainties.

This paper introduces a novel approach that integrates both facets of project uncertainties within a project uncertainty network so that decision makers can prioritize uncertainty factors considering the trade-off between threats and opportunities as well as their interactions. The ISM based development of the network structure helps in identifying common cause uncertainty triggers whereas the modeling of a BBN makes it possible to visualize the propagation impact of uncertainties within a network setting. Further, the proposed approach utilizes risk matrix data for project managers to be able to adopt this approach in practice. The proposed process can be used by practitioners while developing uncertainty management strategies, preparing risk management plans and formulating their contract strategy.

This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.

New product development (NPD) is essential to the survival of companies and surpassing other competitors. A key prerequisite for the success of an NPD project is the timing of new product delivery to the market. The main challenge faced by many project managers is the delay in execution and completion phases due to the complex nature and uncertainty of these projects. Rival companies' cooperation reduces the time spent on an NPD project which is an excellent way to reduce the risk of losing the market, but it increases other risk factors.

Based on the results, the security and confidentiality of innovation, the competitors attracting human resources and the company’s brand credibility factors were ranked higher than other factors and should be predicted and managed before cooperating with competitors.

This paper proposed a new model to assess risk factors in cooperation with rival companies in NPD projects. This model takes into account new parameters, for example, negative and positive risks, negative and positive passable risks and risk-based multi-objective optimization by ratio analysis plus full multiplicative form methodology for the rival companies cooperation in NPD projects. To evaluate the efficiency of the proposed model, a real case of the R&D unit of Iran Khodro Company was studied.

The aim of this study is to identify the risk matrix for factors causing time delay in road construction projects in the West Bank in Palestine from owners' viewpoint.

In total, 43 factors that might cause delays of road construction projects were defined through a detailed literature review. The factors were tabulated in a questionnaire form, which was sent out to a total of 25 public owners asking their contribution in identifying the risk matrix for the 43 factors in terms of impact and probability of occurrence. Three zones were used in the matrix according to the degree of factors' severity on the projects' time delay; they are: green, yellow, and red.

The analysis of 43 factors considered indicates that six factors are located in the green zone, 29 factors are located in the yellow zone, and eight factors are located in the red zone.

The paper identifies the risk matrix for factors affecting time delay in road construction projects in the West Bank in Palestine from the owners' perspective.