Search results

1 – 10 of over 71000
To view the access options for this content please click here
Article
Publication date: 22 June 2010

Ole Jonny Klakegg, Olav Torp and Kjell Austeng

The purpose of this paper is to describe the transfer of experiences to improve the basis for overcoming the dilemma of trying to achieve analyses and systems that are…

Abstract

Purpose

The purpose of this paper is to describe the transfer of experiences to improve the basis for overcoming the dilemma of trying to achieve analyses and systems that are both good and simple. The quality of decisions relating to projects depends on how well the assumed basis for the project actually fit the reality of the situation in which the consequences occur. Good value and cost estimations support good decisions about projects insofar as the assumptions on which they are based mirror the reality, and the decision makers can understand the analysis.

Design/methodology/approach

The paper uses a longitudinal case study and qualitative analysis. Data relating to a large number of cases have become available to the authors through many years of research and consulting activities. Through joint experience and discussion the patterns are analysed. This paper is descriptive with respect to the challenges and empirical examples. The analysis itself ends with a rather normative conclusion.

Findings

There is a dilemma embedded in the processes used to analyse uncertainty and risks associated with projects. On the one hand, an important task is to reduce the complexity of a given situation to render the issues sufficiently simple for them to be understood and assessed. On the other hand, the models and assumptions upon which an analysis is based have to be sufficiently precise and detailed in order to make sense. The same dilemma is found when considering actions to address risks and uncertainties, as well as in designing management systems. It is concluded that the dilemma is real. Solutions have to be found among both good and simple options.

Research limitations/implications

The paper does not answer questions on “how to” and does not dig deep into theoretical perspectives on the current dilemma. More research to understand all aspects of the issue is needed.

Practical implications

Uncertainty analysis and management systems have to be good (precise enough) and at the same time simple (practical). There is no value unless it is used. Practical examples in the paper are intended to help practitioners identify alternative options.

Originality/value

The dilemma of good and simple has not been explicitly addressed before in light of practical experience and theory. The value added is increased awareness of an important problem in analytical processes.

Details

International Journal of Managing Projects in Business, vol. 3 no. 3
Type: Research Article
ISSN: 1753-8378

Keywords

To view the access options for this content please click here
Article
Publication date: 13 August 2019

Hui Lü, Kun Yang, Wen-bin Shangguan, Hui Yin and DJ Yu

The purpose of this paper is to propose a unified optimization design method and apply it to handle the brake squeal instability involving various uncertainties in a…

Abstract

Purpose

The purpose of this paper is to propose a unified optimization design method and apply it to handle the brake squeal instability involving various uncertainties in a unified framework.

Design/methodology/approach

Fuzzy random variables are taken as equivalent variables of conventional uncertain variables, and a unified response analysis method is first derived based on level-cut technique, Taylor expansion and central difference scheme. Next, a unified reliability analysis method is developed by integrating the unified response analysis and fuzzy possibility theory. Finally, based on the unified reliability analysis method, a unified reliability-based optimization model is established, which is capable of optimizing uncertain responses in a unified way for different uncertainty cases.

Findings

The proposed method is extended to perform squeal instability analysis and optimization involving various uncertainties. Numerical examples under eight uncertainty cases are provided and the results demonstrate the effectiveness of the proposed method.

Originality/value

Most of the existing methods of uncertainty analysis and optimization are merely effective in tackling one uncertainty case. The proposed method is able to handle the uncertain problems involving various types of uncertainties in a unified way.

Details

Engineering Computations, vol. 37 no. 1
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Article
Publication date: 1 March 2006

Jan Emblemsvåg and Lars Endre Kjølstad

The article sets out to discuss and present a solution to the fact that various qualitative risk analyses of the same problem can reach significantly different conclusions.

Abstract

Purpose

The article sets out to discuss and present a solution to the fact that various qualitative risk analyses of the same problem can reach significantly different conclusions.

Design/methodology/approach

By reviewing a common risk analysis approach and identifying where the possible problems arise, the authors propose ways to overcome the problems based on what they have found in the literature in general.

Findings

There are ways to greatly reduce the problems, but this requires a risk analysis approach in which information quality and consistency are the subject of greater focus.

Research limitations/implications

The definitions used, Monte Carlo methods and the analytical hierarchy process are well tested in countless applications. Hence, the authors believe that this work possesses no major limitations.

Practical implications

The approach has only been applied to theoretical situations; real‐life situations are needed to address possible practical limitations.

Originality/value

The paper illustrates the importance of distinguishing between “uncertainty”, “risk” and “capabilities” and the associated implications. It also shows how this can be done in a logically consistent way using the analytical hierarchy process so that the problem of inconsistency is reduced, and how the analysis can be used to systematically improve itself. The proposed risk analysis is a novel approach that has, to the authors' knowledge, never been thought of before.

Details

Management Decision, vol. 44 no. 3
Type: Research Article
ISSN: 0025-1747

Keywords

To view the access options for this content please click here
Article
Publication date: 26 February 2019

Shahab Shoar, Farnad Nasirzadeh and Hamid Reza Zarandi

The purpose of this paper is to present a fault tree (FT)-based approach for quantitative risk analysis in the construction industry that can take into account both…

Abstract

Purpose

The purpose of this paper is to present a fault tree (FT)-based approach for quantitative risk analysis in the construction industry that can take into account both objective and subjective uncertainties.

Design/methodology/approach

In this research, the identified basic events (BEs) are first categorized based on the availability of historical data into probabilistic and possibilistic. The probabilistic and possibilistic events are represented by probability distributions and fuzzy numbers, respectively. Hybrid uncertainty analysis is then performed through a combination of Monte Carlo simulation and fuzzy set theory. The probability of occurrence of the top event is finally calculated using the proposed FT-based hybrid uncertainty analysis method.

Findings

The efficiency of the proposed method is demonstrated by implementing in a real steel structure project. A quantitative risk assessment is performed for weld cracks, taking into account of both types of uncertainties. An importance analysis is finally performed to evaluate the contribution of each BE to the probability of occurrence of weld cracks and adopt appropriate response strategies.

Research limitations/implications

In this research, the impact of objective (aleatory) dependence between the occurrences of different BEs and subjective (epistemic) dependence between estimates of the epistemically uncertain probabilities of some BEs are not considered. Moreover, there exist limitations to the application of fuzzy set rules, which were used for aggregating experts’ opinions and ranking purposes of the BEs in the FT model. These limitations can be investigated through further research.

Originality/value

It is believed that the proposed hybrid uncertainty analysis method presents a robust and powerful tool for quantitative risk analysis, as both types of uncertainties are taken into account appropriately.

To view the access options for this content please click here
Article
Publication date: 24 September 2019

Farman Afzal, Shao Yunfei, Mubasher Nazir and Saad Mahmood Bhatti

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper…

Abstract

Purpose

In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.

Design/methodology/approach

This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.

Findings

The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.

Research limitations/implications

This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.

Practical implications

These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.

Originality/value

This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.

Details

International Journal of Managing Projects in Business, vol. 14 no. 2
Type: Research Article
ISSN: 1753-8378

Keywords

To view the access options for this content please click here
Article
Publication date: 18 July 2008

Elizabeth Atherton, Nick French and Laura Gabrielli

Real estate development appraisal is a quantification of future expectations. The appraisal model relies upon the valuer/developer having an understanding of the future in…

Abstract

Purpose

Real estate development appraisal is a quantification of future expectations. The appraisal model relies upon the valuer/developer having an understanding of the future in terms of the future marketability of the completed development and the future cost of development. In some cases the developer has some degree of control over the possible variation in the variables. However, other variables are totally dependent upon the vagaries of the market at the completion date. To try to address the risk of a different outcome to the one expected the developer will often carry out a sensitivity analysis on the development. This paper aims to look at the processes for so doing and the role of the decision maker in the analysis.

Design/methodology/approach

Traditional sensitivity analysis has generally only looked at the best and worst scenarios and has focused on the anticipated or expected outcomes. This does not take into account uncertainty and the range of outcomes that can happen. A fuller analysis should include examination of the uncertainties in each of the components of the appraisal and account for the appropriate distributions of the variables. This requires a standardised approach and the use of a generic forecasting software package.

Findings

There are numerous risks involved in the development of real estate. By allowing the decision maker to contribute to the assessment of these risks, the analysis provides the decision maker with a greater understanding of the critical variables and their impact upon the viability of the final scheme.

Originality/value

This analysis shows that developers can get a better understanding of the upside and downside risks associated with their project.

Details

Journal of European Real Estate Research, vol. 1 no. 2
Type: Research Article
ISSN: 1753-9269

Keywords

To view the access options for this content please click here
Article
Publication date: 30 April 2020

Lei Wang, Chuang Xiong and Qinghe Shi

Considering that uncertain factors widely exist in engineering practice, an adaptive collocation method (ACM) is developed for the structural fuzzy uncertainty analysis.

Abstract

Purpose

Considering that uncertain factors widely exist in engineering practice, an adaptive collocation method (ACM) is developed for the structural fuzzy uncertainty analysis.

Design/methodology/approach

ACM arranges points in the axis of the membership adaptively. Through the adaptive collocation procedure, ACM can arrange more points in the axis of the membership where the membership function changes sharply and fewer points in the axis of the membership where the membership function changes slowly. At each point arranged in the axis of the membership, the level-cut strategy is used to obtain the cut-level interval of the uncertain variables; besides, the vertex method and the Chebyshev interval uncertainty analysis method are used to conduct the cut-level interval uncertainty analysis.

Findings

The proposed ACM has a high accuracy without too much additional computational efforts.

Originality/value

A novel ACM is developed for the structural fuzzy uncertainty analysis.

Details

Engineering Computations, vol. 37 no. 9
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Article
Publication date: 3 February 2021

Ming-Lang Tseng, Shiou-Yun Jeng, Chun-Wei Lin and Ming K. Lim

Construction and demolition waste (CDW) continuously causes environmental and social problems. These formidable challenges lead to sustainable issues and are an…

Abstract

Purpose

Construction and demolition waste (CDW) continuously causes environmental and social problems. These formidable challenges lead to sustainable issues and are an increasingly urgent issue worldwide. Prior studies have neglected to link the triple bottom line (TBL) to a reliable estimation or empirical model for estimating CDW production performance and lack empirical sensitivity analysis in profit maximization. This study proposes an attribute analysis to build a cost–benefit analysis (CBA) to obtain profit maximization.

Design/methodology/approach

This study uses fuzzy set theory to develop a cost and benefit analysis (CBA) model to assess the sensitivity analysis in terms of its performance on addressing the environmental, economic and social aspects. The model is used to weigh the sum of benefits such as financial gain and total costs of actions taken to mitigate the negative impacts.

Findings

Based on the sensitivity analysis conducted, the environmental, economic and social mean scales were significantly changed, i.e. increased, and profits increased drastically. The results provide an insight into environmental legislation compliance, environmental investment and environmental impact as the cause attributes for the CDW recycling profit increase. The results prove that sensitivity analysis is viable to infer that a sustainable production performance can achieve more revenue and profit through an adequate selection of attributes regarding the TBL aspects to address the firm's uncertainty problem in multiple criteria analysis.

Originality/value

This study builds a CBA model to maximize profits for recycled CDW material by linking of environmental, economic and societal aspects for recycled CDW assessments. It considers a sustainability structure with criteria based on TBL aspects to assess production performance to realize the Sustainable Development Goals and presents fuzzy set theory and sensitivity analysis to solve the uncertainty problem in the construction industry.

Details

Management of Environmental Quality: An International Journal, vol. 32 no. 3
Type: Research Article
ISSN: 1477-7835

Keywords

To view the access options for this content please click here

Abstract

Details

Flexible Urban Transportation
Type: Book
ISBN: 978-0-08-050656-2

To view the access options for this content please click here
Article
Publication date: 3 February 2012

Joel H. Helquist, Amit Deokar, Jordan J. Cox and Alyssa Walker

The purpose of this paper is to propose virtual process simulation as a technique for identifying and analyzing uncertainty in processes. Uncertainty is composed of both…

Abstract

Purpose

The purpose of this paper is to propose virtual process simulation as a technique for identifying and analyzing uncertainty in processes. Uncertainty is composed of both risks and opportunities.

Design/methodology/approach

Virtual process simulation involves the creation of graphical models representing the process of interest and associated tasks. Graphical models representing the resources (e.g. people, facilities, tools, etc.) are also created. The members of the resources graphical models are assigned to process tasks in all possible combinations. Secondary calculi, representing uncertainty, are imposed upon these models to determine scores. From the scores, changes in process structure or resource allocation can be used to manage uncertainty.

Findings

The example illustrates the benefits of utilizing virtual process simulation in process pre‐planning. Process pre‐planning can be used as part of strategic or operational uncertainty management.

Practical implications

This paper presents an approach to clarify and assess uncertainty in new processes. This modeling technique enables the quantification of measures and metrics to assist in systematic uncertainty analysis. Virtual process simulation affords process designers the ability to more thoroughly examine uncertainty while planning processes.

Originality/value

This research contributes to the study of uncertainty management by promoting a systematic approach that quantifies metrics and measures according to the objectives of a given process.

Details

Business Process Management Journal, vol. 18 no. 1
Type: Research Article
ISSN: 1463-7154

Keywords

1 – 10 of over 71000