Integrating risk management's best practices to estimate deep excavation projects’ time and cost

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gholamreza Heravi ◽  
Amir Hosein Taherkhani ◽  
Soroush Sobhkhiz ◽  
Ali Hassandokht Mashhadi ◽  
Rouzbeh Zahiri-Hashemi
Keyword(s):  
Risk Analysis ◽  
Best Practices ◽  
Fault Tree Analysis ◽  
Time Estimation ◽  
Bayesian Belief Networks ◽  
Risk Identification ◽  
Estimation Methods ◽  
Deep Excavation ◽  
Content Type ◽  
Response Planning

PurposeThis study provides an integrated risk-based cost and time estimation approach for deep excavation projects. The purpose is to identify the best practices in recent advances of excavation risk analysis (RA) and integrate them with traditional cost and time estimation methods.Design/methodology/approachThe implemented best practices in this research are as follows: (1) fault-tree analysis (FTA) for risk identification (RI); (2) Bayesian belief networks (BBNs), fuzzy comprehensive analysis and Monte Carlo simulation (MCS) for risk analysis; and (3) sensitivity analysis and root-cause analysis (RCA) for risk response planning (RRP). The proposed approach is applied in an actual deep excavation project in Tehran, Iran.FindingsThe results show that the framework proposes a practical approach for integrating the risk management (RM) best practices in the domain of excavation projects with traditional cost and time estimation approaches. The proposed approach can consider the interrelationships between risk events and identify their root causes. Further, the approach engages different stakeholders in the process of RM, which is beneficial for determining risk owners and responsibilities.Originality/valueThis research contributes to the project management body of knowledge by integrating recent RM best practices in deep excavation projects for probabilistic estimation of project time and cost.

Quantitative modeling and analysis of supply chain risks using Bayesian theory

2014 ◽  
Vol 25 (5) ◽  
pp. 631-654 ◽  
Author(s):  
Fazleena Badurdeen ◽  
Mohannad Shuaib ◽  
Ken Wijekoon ◽  
Adam Brown ◽  
William Faulkner ◽  
...  
Keyword(s):  
Risk Management ◽  
Management Practices ◽  
Back Propagation ◽  
Bayesian Belief Networks ◽  
Risk Identification ◽  
Bayesian Theory ◽  
Risk Modeling ◽  
Content Type ◽  
Modeling And Analysis ◽  
Qualitative Approaches

Purpose – Globally expanding supply chains (SCs) have grown in complexity increasing the nature and magnitude of risks companies are exposed to. Effective methods to identify, model and analyze these risks are needed. Risk events often influence each other and rarely act independently. The SC risk management practices currently used are mostly qualitative in nature and are unable to fully capture this interdependent influence of risks. The purpose of this paper is to present a methodology and tool developed for multi-tier SC risk modeling and analysis. Design/methodology/approach – SC risk taxonomy is developed to identify and document all potential risks in SCs and a risk network map that captures the interdependencies between risks is presented. A Bayesian Theory-based approach, that is capable of analyzing the conditional relationships between events, is used to develop the methodology to assess the influence of risks on SC performance Findings – Application of the methodology to an industry case study for validation reveals the usefulness of the Bayesian Theory-based approach and the tool developed. Back propagation to identify root causes and sensitivity of risk events in multi-tier SCs is discussed. Practical implications – SC risk management has grown in significance over the past decade. However, the methods used to model and analyze these risks by practitioners is still limited to basic qualitative approaches that cannot account for the interdependent effect of risk events. The method presented in this paper and the tool developed demonstrates the potential of using Bayesian Belief Networks to comprehensively model and study the effects or SC risks. The taxonomy presented will also be very useful for managers as a reference guide to begin risk identification. Originality/value – The taxonomy developed presents a comprehensive compilation of SC risks at organizational, industry, and external levels. A generic, customizable software tool developed to apply the Bayesian approach permits capturing risks and the influence of their interdependence to quantitatively model and analyze SC risks, which is lacking.

Electricity Infrastructure Technical Security

2020 ◽  
pp. 1-30
Author(s):  
Martin Hromada ◽  
David Rehak ◽  
Neil Walker
Keyword(s):  
Complex System ◽  
Risk Assessment ◽  
Risk Management ◽  
Risk Analysis ◽  
Best Practices ◽  
Risk Identification ◽  
Security Measures ◽  
Identification Methods ◽  
General Energy ◽  
Electricity Infrastructure

In general, energy infrastructure is a basic but very complex system of elements, interconnections, functional inputs and outputs, which creates the need to break down subsystems, systems, and infrastructure areas. The aim of this chapter is therefore to discuss the possible implementation of approaches to risk assessment and risk management in relation to the application of technical security measures. This chapter of the book will therefore discuss risk analysis methods where the transition from general approaches to risk analysis, through risk identification methods and procedures and the assessment of major industrial and technological risks, to specific risk analysis methodologies for electricity infrastructures, will be presented. An important part of the chapter is also the introduction of practical approaches and methodologies that are accepted as “best practices” in connection with ensuring the technical security of electricity infrastructures.

scholarly journals Research and Application of Critical Failure Paths Identification Method for Dam Risk Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Kun He ◽  
Liang Pei ◽  
Xiang Lu ◽  
Jiankang Chen ◽  
Zhenyu Wu
Keyword(s):  
Risk Analysis ◽  
Analytic Hierarchy Process ◽  
Fault Tree Analysis ◽  
Risk Identification ◽  
Analytic Hierarchy ◽  
Identification Method ◽  
Failure Path ◽  
And Control ◽  
The Impact ◽  
Hierarchy Process

Dam is an important part of the national infrastructure, and its safety has been widely concerned. Risk identification of dams plays a significant role in risk assessment and control. Finding out some critical failure paths through adopting timely measures can help reduce the risk occurrence probability effectively. This paper develops an identification method based on the credibility and the interval analytic hierarchy process (IAHP) methods, namely, consistency and difference-based interval analytic hierarchy process (CDB-IAHP) method, to identify the critical failure paths of dams exactly considering the dynamic cognition degree of decision-makers. Based on the fault tree analysis (FTA) method, the framework and analysis for critical failure paths identification of a gravity dam and an Earth-rockfill dam are conducted and made. The results show that the critical failure paths obtained by the proposed method are in line with the statistical data, and the importance of disaster causing factors has some difference with the traditional method. Additionally, some engineering and nonengineering measures are suggested to reduce the impact of potential failure paths. The applications demonstrate that the proposed method shows good applicability for risk analysis and critical failure path mining of dams.

A risk analysis model for mining accidents using a fuzzy approach based on fault tree analysis

2018 ◽  
Vol 31 (4) ◽  
pp. 577-594 ◽  
Author(s):  
Fatma Yasli ◽  
Bersam Bolat
Keyword(s):  
Risk Analysis ◽  
Management Strategies ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Fuzzy Approach ◽  
Analysis Model ◽  
Basis Risk ◽  
Tree Analysis ◽  
Content Type ◽  
Essential Components

Purpose Risk analysis is a critical investigation field for many sectors and organizations to maintain the information management reliable. Since mining is one of the riskiest sectors for both workers and management, comprehensive risk analysis should be carried out. The purpose of this paper is to explore comprehensively the undesired events that may occur during a particular process with their main reasons and to perform a risk analysis for these events, by developing a risk analysis methodology. For performing risk analysis, discovering and defining the potential accidents and incidents including their root causes are important contributions of the study as distinct from the related literature. The fuzzy approach is used substantially to obtain the important inferences about the hazardous process by identifying the critical risk points in the processes. In the scope of the study, the proposed methodology is applied to an underground chrome mine and obtaining significant findings of mining risky operations is targeted. Design/methodology/approach Fault tree analysis and fuzzy approach are used for performing the risk analysis. When determining the probability and the consequences of the events which are essential components for the risk analysis, expressions of the heterogeneous expert group are considered by means of the linguistic terms. Fault tree analysis and fuzzy approach present a quiet convenience solution together to specify the possible accidents and incidents in the particular process and determine the values for the basis risk components. Findings This study primarily presents a methodology for a comprehensive risk analysis. By implementing the proposed methodology to the underground loading and conveying processes of a chrome mine, 28 different undesired events that may occur during the processes are specified. By performing risk analysis for these events, it is established that the employee’s physical constraint while working with the shovel in the fore area, the falling of materials on employees from the chute and the scaling bar injuries are the riskiest undesired events in the underground loading and conveying process of the mine. Practical implications The proposed methodology provides a confidential and comprehensive method for risk analysis of the undesired events in a particular process. The capability of fault tree analysis for specifying the undesired events systematically and the applicability of fuzzy approach for converting the experts’ linguistic expressions to the mathematical values provide a significant advantage and convenience for the risk analysis. Originality/value The major contribution of this paper is to develop a methodology for the risk analysis of a variety of mining accidents and incidents. The proposed methodology can be applied to many production processes to investigate the dangerous operations comprehensively and find out the efficient management strategies. Before performing the risk analysis, determining the all possible accidents and incidents in the particular process using the fault tree analysis provides the effectiveness and the originality of the study. Also, using the fuzzy logic to find out the consequences of the events with experts’ linguistic expressions provides an efficient method for performing risk analysis.

Risks of water and wastewater PPP projects: an investors’ perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Omid Amiri ◽  
Amir Ayazi ◽  
Mahmoud Rahimi ◽  
Garshasb Khazaeni
Keyword(s):  
Risk Factors ◽  
Public Sector ◽  
Risk Score ◽  
Fault Tree Analysis ◽  
Risk Identification ◽  
Point Of View ◽  
Financial Resources ◽  
Constructive Approach ◽  
Content Type ◽  
Water And Wastewater

Purpose Water and wastewater (WW) projects are gaining attention in Iran because of shortages of water resources. However, these projects are lengthy and they are accompanied by numerous risks, such as lack of sufficient financial resources. Public–private partnerships (PPPs) are taken into account as a constructive approach to deal with the problem of insufficient government funds and they are increasingly being implemented to construct the required infrastructures in different countries. Although WW projects in PPPs can reduce the government’s debt, investors are still uncertain about this approach. Hence, this study aims to identify and evaluate the risk of all parties involved in WW-PPP projects, from the viewpoint of investor. Design/methodology/approach First, the risk factors which are involved in WW projects are identified by interviewing experts and reviewing the literature by means of fault tree analysis (FTA) tool. Second, the probability and effects of the risky factors which are related to specific event are evaluated and analyzed by hybridization of interval fuzzy Type-2 sets (IT2FS) and risk score formulation. Finally, some solutions are proposed to deal with the most challenging risks. Findings Six gate events, namely, risks which are related to investors such as investor’s consultant-related risks, risky conditions from engineering, procurement, and construction (EPC) contractors’ point of view, risk factors which public sector takes into account, public sector’s consultant-related risks which public sector’s consultant consider challenging and external factors were defined according to the literature. From FTA tool and by interviewing the experts, 94 basic events were identified. Finally, from hybridization of IT2FSs and risk score formulation, top five risks are determined as “Difficulty of injecting financial resources into the project,” “Fluctuation in inflation rate,” “Poor decision-making process” in public sector, “Difficulty of importing the equipment which are required for the project (such as pumps, grain catchers, garbage collectors, etc.) from other countries” and “Impact of risky conditions in other projects on operation of PPP project.” Originality/value In the absence of a constructive approach for risk identification and a reliable model for evaluating the identified risks in PPP projects, this research project is one of the first research studies which used FTA for identifying risks and hybridization of IT2FSs and risk score formulation for evaluating the risks.

Risk identification and modeling for blockchain-enabled container shipping

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Son Nguyen ◽  
Peggy Shu-Ling Chen ◽  
Yuquan Du
Keyword(s):  
Design Methodology ◽  
Directed Acyclic Graph ◽  
Risk Identification ◽  
Container Shipping ◽  
Content Type ◽  
Acyclic Graph ◽  
Operational Risks ◽  
Systems Security ◽  
Event Risk ◽  
Potential Risks

PurposeAlthough being considered for adoption by stakeholders in container shipping, application of blockchain is hindered by different factors. This paper investigates the potential operational risks of blockchain-integrated container shipping systems as one of such barriers.Design/methodology/approachLiterature review is employed as the method of risk identification. Scientific articles, special institutional reports and publications of blockchain solution providers were included in an inclusive qualitative analysis. A directed acyclic graph (DAG) was constructed and analyzed based on network topological metrics.FindingsTwenty-eight potential risks and 47 connections were identified in three groups of initiative, transitional and sequel. The DAG analysis results reflect a relatively well-connected network of identified hazardous events (HEs), suggesting the pervasiveness of information risks and various multiple-event risk scenarios. The criticality of the connected systems' security and information accuracy are also indicated.Originality/valueThis paper indicates the changes of container shipping operational risk in the process of blockchain integration by using updated data. It creates awareness of the emerging risks, provides their insights and establishes the basis for further research.

scholarly journals A Fusion Algorithm for Estimating Time-Independent/-Dependent Parameters and States

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4068
Author(s):  
Zheshuo Zhang ◽  
Jie Zhang ◽  
Jiawen Dai ◽  
Bangji Zhang ◽  
Hengmin Qi
Keyword(s):  
Unscented Kalman Filter ◽  
Time Estimation ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Fusion Algorithm ◽  
State Variable ◽  
Current Estimation ◽  
Real Time Estimation ◽  
And Control ◽  
Independent Parameters

Vehicle parameters are essential for dynamic analysis and control systems. One problem of the current estimation algorithm for vehicles’ parameters is that: real-time estimation methods only identify parts of vehicle parameters, whereas other parameters such as suspension damping coefficients and suspension and tire stiffnesses are assumed to be known in advance by means of an inertial parameter measurement device (IPMD). In this study, a fusion algorithm is proposed for identifying comprehensive vehicle parameters without the help of an IPMD, and vehicle parameters are divided into time-independent parameters (TIPs) and time-dependent parameters (TDPs) based on whether they change over time. TIPs are identified by a hybrid-mass state-variable (HMSV). A dual unscented Kalman filter (DUKF) is applied to update both TDPs and online states. The experiment is conducted on a real two-axle vehicle and the test data are used to estimate both TIPs and TDPs to validate the accuracy of the proposed algorithm. Numerical simulations are performed to further investigate the algorithm’s performance in terms of sprung mass variation, model error because of linearization and various road conditions. The results from both the experiment and simulation show that the proposed algorithm can estimate TIPs as well as update TDPs and online states with high accuracy and quick convergence, and no requirement of road information.

Identifying the best practices in green operations strategy of hospitals

2019 ◽  
Vol 26 (4) ◽  
pp. 1106-1131 ◽  
Author(s):  
Yazan Khalid Abed-Allah Migdadi ◽  
Abeer Ahmad Omari
Keyword(s):  
Best Practices ◽  
Waste Management ◽  
Electrical Power ◽  
Global Reporting Initiative ◽  
Operations Strategy ◽  
Content Type ◽  
Hazardous Waste Management ◽  
The World ◽  
Sustainability Reports ◽  
Two Stages

Purpose The purpose of this paper is to identify the best practices in the green operations strategy of hospitals. Design/methodology/approach A total of 25 cases from all over the world were investigated. The source of data was the annual sustainability reports that were retrieved from Global Reporting Initiative (GRI) database. The present research adopted the benchmarking method and the quantitative content analysis of sustainability reports. Then, the indicative models of best practices were developed by using two analysis approaches; within cluster analysis and across clusters analysis. Findings This study found four major taxonomies of green operation strategy in hospitals. The significant strategic groups were resources/waste management; electrical power management; non-hazardous waste management; and emissions/resources management. Indicative models for the relationship between actions and key green performance indicators were developed in the two stages of the analysis. Originality/value The best practices of green operations strategies in hospitals have not so far been investigated. Countries around the world should obey the new regulations for their environmental footprint; if they do, it will exert pressure on all sectors and organizations at all levels to take immediate steps to measure and improve their environmental performance.

Encouraging millennials to collaborate and learn on the job

2015 ◽  
Vol 14 (4) ◽  
pp. 118-123 ◽  
Author(s):  
Lauren Trees
Keyword(s):  
Knowledge Management ◽  
Best Practices ◽  
Social Networking ◽  
Age Groups ◽  
Lessons Learned ◽  
Retention Rates ◽  
Direct Access ◽  
Content Type ◽  
Business Outcomes ◽  
Wide Range

Purpose – The purpose of this paper is to present enterprise social networking and gamification as two potential tools to help organizations engage Millennial employees in collaboration and learning. Design/methodology/approach – The research provides general descriptions of enterprise social networking and gamification approaches, shares data on adoption of these approaches from APQC’s “2015 Knowledge Management Priorities Data Report” (based on a January 2015 survey of 524 knowledge management professionals) and includes four company examples adapted from APQC’s Connecting People to Content and Transferring and Applying Critical Knowledge best practices studies. The methodology for APQC’s best practices studies involves screening 50 or more organizations with potential best practices in a given research scope area and identifying five or six with proven best practices. APQC then conducts detailed site visits with the selected organizations and publishes case studies based on those site visits. Findings – Enterprise social networking platforms are in place at 50 per cent of organizations, with another 25 per cent planning to implement them by the end of 2015. By providing near-immediate access to information and answers, enterprise social networking helps Millennials learn the ropes at their new workplaces, gives them direct access to more knowledgeable colleagues who can assist and mentor them, and helps them improve their business outcomes by reusing knowledge and lessons learned across projects. Younger workers can also harness the power of social networking to create a sense of belonging and build their reputations in large, dispersed firms, where it is particularly difficult for them to gain visibility. A recent APQC survey indicates that 54 per cent of organizations either currently employ gamification to encourage collaboration or expect to implement it within the next three years. The rush to gamify the enterprise is, at least in part, a reflection of employers’ desire to satisfy Millennials and make them feel connected to a community of co-workers. Although games appeal to a wide range of age groups, Millennials grew up with digital interaction and tend to prefer environments that emphasize teamwork, social learning and frequent feedback – all of which can be delivered through gamification. Originality/value – The value of this paper is to introduce the value of and relationship between enterprise social networking and gamification platforms to human resource (HR) professionals looking to increase engagement and retention rates for Millennial employees.

What drives housing prices, rent and new construction in China

2017 ◽  
Vol 10 (5) ◽  
pp. 662-686
Author(s):  
Dimitrios Staikos ◽  
Wenjun Xue
Keyword(s):  
Real Estate ◽  
Empirical Test ◽  
Housing Prices ◽  
Panel Cointegration ◽  
Real Estate Market ◽  
Estimation Methods ◽  
Content Type ◽  
New Construction ◽  
Using Data ◽  
First Time

Purpose With this paper, the authors aim to investigate the drivers behind three of the most important aspects of the Chinese real estate market, housing prices, housing rent and new construction. At the same time, the authors perform a comprehensive empirical test of the popular 4-quadrant model by Wheaton and DiPasquale. Design/methodology/approach In this paper, the authors utilize panel cointegration estimation methods and data from 35 Chinese metropolitan areas. Findings The results indicate that the 4-quadrant model is well suited to explain the determinants of housing prices. However, the same is not true regarding housing rent and new construction suggesting a more complex theoretical framework may be required for a well-rounded explanation of real estate markets. Originality/value It is the first time that panel data are used to estimate rent and new construction for China. Also, it is the first time a comprehensive test of the Wheaton and DiPasquale 4-quadrant model is performed using data from China.

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