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1 – 10 of over 75000Farman 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 is to…
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.
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David M. Herold, Sara Saberi, Mahtab Kouhizadeh and Simon Wilde
In response, the purpose of this paper is to provide theoretical frameworks about the organizational uncertainty behind what and when to adopt blockchain technology and their…
Abstract
Purpose
In response, the purpose of this paper is to provide theoretical frameworks about the organizational uncertainty behind what and when to adopt blockchain technology and their implications on transaction costs. The immature nature and the absence of standards in blockchain technology lead to uncertainty in government organizations concerning the adoption (“what to adopt”) and the identification of the right time (“when to start”).
Design/methodology/approach
Using transaction cost theory and path dependency theory, this paper proposes two frameworks: to assess transaction cost risks and opportunities costs; and to depict four different types of transaction costs outcomes regarding blockchain adoption.
Findings
This paper identifies various theoretical concepts that influence blockchain adoption and combine the two critical constructs of “bounded rationality” and the “lock-in effect” to categorize the multiple transaction costs outcomes for blockchain adoption.
Research limitations/implications
Although existing research in blockchain highlights mainly the potential benefits of blockchain applications, only a little attention has been given to frameworks that categorize potential transaction costs outcomes under uncertainty, in particular from organizational theorists.
Originality/value
Both frameworks advance the understanding of the decision-making behind blockchain adoption and synthesize the current literature to offer conceptual clarity regarding the varied implications and outcomes linked to the uncertainty regarding transactions costs stemming from blockchain technology.
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John Ahmet Erkoyuncu, Rajkumar Roy, Essam Shehab and Elmar Kutsch
In the light of challenges experienced in cost estimation at the bidding stage of complex engineering services in the defence industry (e.g. contracting for availability), the…
Abstract
Purpose
In the light of challenges experienced in cost estimation at the bidding stage of complex engineering services in the defence industry (e.g. contracting for availability), the purpose of this paper is to present a framework to manage the influence of uncertainty on cost estimates.
Design/methodology/approach
The research applied the Soft Systems Methodology and benefitted from interaction with four major organisations in the defence industry through document sharing, semi-structured interviews, workshops, and case studies.
Findings
The framework is composed of seven stages to plan, identify, prioritise, classify, and manage cost uncertainties. Through the validation of three case studies some of the key benefits of the framework were realised in project planning, uncertainty visualisation, and capability management.
Research limitations/implications
The research has been applied in the defence sector in the UK and focuses on the bidding stage. Further research needs to be applied to confirm that the findings are applicable across industries and across the life cycle.
Originality/value
The paper builds on the theory behind risk and uncertainty management and proposes an innovative framework that avoids the assumption of “perfect” knowledge by raising questions about the validity of the input data.
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Olav Torp, Ingemund Jordanger, Ole Jonny Klakegg and Yvonne C.B. Bjerke
The purpose of the paper is 1) to address the importance of contingency at the right level when defining project control baseline, including cost reserves / “room to manoeuvre”…
Abstract
Purpose
The purpose of the paper is 1) to address the importance of contingency at the right level when defining project control baseline, including cost reserves / “room to manoeuvre” and 2) present proactive uncertainty management as a regime to ensure cost effective management of project reserves and contribute to project success.
Design/Methodology/Approach
The paper is a combination of literature study and quantitative research on how contingency develops during the lifetime of a case project. The investigation into the case project includes document study into quantitative material from the case project. The combination of empirical material and theory makes the discussion robust.
Findings
Unrealistic low cost uncertainty will lead to unrealistic low contingency. The case study from a Norwegian mega project shows a contingency of 15 per cent in addition to expected costs. The case study shows that by continuous opportunity management and risk reduction, the needs for management reserves are systematically reduced and the contingency is controlled.
Research Limitations/Implications
This research is limited to one case study. A higher number of cases are necessary to generalise the findings. However, the authors would claim that the systematic mapping of need for management reserve towards the project contingency, and a continuous uncertainty management system will help to obtain cost effective management. The findings from the case study could be applied on similar cases.
Practical Implications
The case study shows a way of setting contingencies and managing contingencies through systematic uncertainty management.
Originality/Value
Improved management of project provisions will increase the value of future projects.
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Lei Guo, Huimin Li, Peng Li and Chengyi Zhang
The purpose of this paper is to find how those uncertainty factors influence transaction costs generated and to identify ways to minimize the transaction costs borne by the…
Abstract
Purpose
The purpose of this paper is to find how those uncertainty factors influence transaction costs generated and to identify ways to minimize the transaction costs borne by the construction owner.
Design/methodology/approach
The literature indicates that there is no consensus on a standard definition of transaction costs in the construction industry. A detailed literature review of research work on transaction costs in construction is conducted in order to identify the determinants of transaction costs in construction projects. A structural equation model is tested on data collected by means of a survey administered to construction owners.
Findings
The findings indicate that the transaction costs borne by the owner can be minimized if the owner minimizes the uncertainties inherent in the construction project by making sure the engineering design is as complete as possible before bids are sought from contractors; harmonious relationships between project participants; fair risk allocation; have experience in similar type projects; and contractor selection practices that routinely detect irregular behavior.
Research limitations/implications
The data used in this research are primarily based on the experiences of public owners and the markets in which they operate; a larger representation of private owners could make the conclusions more general. Another limitation of the study is that it relies on a survey of opinions rather than actual records of costs and other hard data.
Practical implications
No empirical study has ever been conducted of transaction-related issues in the construction industry because of the lack of a common understanding of transaction cost. This paper provides the groundwork for such a study.
Originality/value
This paper attempts to reconcile the many determinants of transaction costs in construction projects under uncertainty considered by different researchers in a multitude of research studies.
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The paper seeks to develop an analytical theory of project investment.
Abstract
Purpose
The paper seeks to develop an analytical theory of project investment.
Design/methodology/approach
The authors derive a partial differential equation that the variable cost of a project should satisfy, determine a proper initial condition through a thought experiment, and solve the equation.
Findings
A formula of variable cost as an analytical function of fixed cost, uncertainty of the environment and the duration of a project is obtained.
Practical implications
The analytical formula enables systematic comparison of returns of different investment under different market conditions to be made. This refines the insights from real option theory in many ways. Since all production systems need fixed investment to lower variable costs, by providing an analytical theory about the relation among fixed costs, variable costs and uncertainty, this theory contributes a new foundation to investment theory and other different fields.
Originality/value
An analytical theory of project investment about the relation among fixed costs, variable costs, uncertainty of the environment and the duration of a project, which is the core concern in most business decisions, does not exist in the current literature.
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Salma Mokdadi and Zied Saadaoui
This paper aims to study the impact of geopolitical uncertainty on corporate cost of debt and the moderating role of information asymmetry between creditors and borrowing firms.
Abstract
Purpose
This paper aims to study the impact of geopolitical uncertainty on corporate cost of debt and the moderating role of information asymmetry between creditors and borrowing firms.
Design/methodology/approach
This study uses 5,223 firm-quarter observations on German-listed firms spanning 2010:Q1–2021:Q4. This study regresses the cost of debt financing on the geopolitical risk, accounting quality and other control variables. Information asymmetry is measured using the performance-matched Jones-model discretionary accrual and the stock bid-ask spread. It uses interaction terms to check if information asymmetry moderates the impact of geopolitical uncertainty on the cost of debts and control for the moderating role of business risk. For the sake of robustness check, it uses long-term cost of debt and bond spread as alternative dependent variables. In addition, this study executes instrumental variables regression and propension score matching to control for potential endogeneity problems.
Findings
Estimation results show that geopolitical uncertainty exerts a positive impact on the cost of debt. This impact is found to be more important on the cost of long-term debts. Information asymmetry is found to exacerbate the positive impact of geopolitical risk on the cost of debt. These results are robust to the change of the dependent variable and to the mitigation of potential endogeneity. At high levels of information asymmetry, this impact is more important for firms belonging to “Transportation”, “Automobiles and auto parts”, “Chemicals”, “Industrial and commercial services”, “Software and IT services” and “Industrial goods” business sectors.
Research limitations/implications
Geopolitical uncertainty should be seriously considered when setting strategies for corporate financial management in Germany and similar economies that are directly exposed to geopolitical risks. Corporate managers should design a comprehensive set of corporate policies to improve their transparency and accountability during increasing uncertainty. Policymakers are required to implement innovative monetary and fiscal policies that take into consideration the heterogeneous impact of geopolitical uncertainty and information transparency in order to contain their incidence on German business sectors.
Originality/value
Despite its relevance to corporate financing conditions, little is known about the impact of geopolitical uncertainty on the cost of debt financing. To the best of the authors’ knowledge, there is still no empirical evidence on how information asymmetry between creditors and borrowing firms shapes the impact of geopolitical uncertainty on the cost of debt. This paper tries to fill this gap by interacting two measures of information asymmetry with geopolitical uncertainty. In contrast with previous studies, this study shows that the impact of geopolitical uncertainty on the cost of debt is non-linear and heterogeneous. The results show that the impact of geopolitical uncertainty does not exert the same impact on the cost of debt instruments with different maturities. This impact is found to be heterogeneous across business sectors and to depend on the level of information asymmetry.
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Seyed Jafar Sadjadi, Zahra Ziaei and Mir Saman Pishvaee
This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability…
Abstract
Purpose
This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability of vaccines, wastages in storage, limited capacity and different priorities for demands.
Design/methodology/approach
This study presents a mixed-integer linear programming (MILP) model and using a robust counterpart approach for coping with uncertainties of model.
Findings
The presented robust model in comparison with the deterministic model has a better performance and is more reliable for network design of vaccine supply chain.
Originality/value
This study considers uncertainty in the network design of vaccine supply chain for the first time in the vaccine context It presents an MILP model where strategic decisions for each echelon and tactical decisions among different echelons of supply chain are determined. Further, it models the difference between high- and low-priority demands for vaccine.
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Liwei Ju, Zhe Yin, Qingqing Zhou, Li Liu, Yushu Pan and Zhongfu Tan
This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose a low-carbon economic scheduling optimization model for GVPP considering carbon…
Abstract
Purpose
This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose a low-carbon economic scheduling optimization model for GVPP considering carbon emission trading.
Design/methodology/approach
In view of the strong uncertainty of wind power and photovoltaic power generation in GVPP, the information gap decision theory (IGDT) is used to measure the uncertainty tolerance threshold under different expected target deviations of the decision-makers. To verify the feasibility and effectiveness of the proposed model, nine-node energy hub was selected as the simulation system.
Findings
GVPP can coordinate and optimize the output of electricity-to-gas and gas turbines according to the difference in gas and electricity prices in the electricity market and the natural gas market at different times. The IGDT method can be used to describe the impact of wind and solar uncertainty in GVPP. Carbon emission rights trading can increase the operating space of power to gas (P2G) and reduce the operating cost of GVPP.
Research limitations/implications
This study considers the electrical conversion and spatio-temporal calming characteristics of P2G, integrates it with VPP into GVPP and uses the IGDT method to describe the impact of wind and solar uncertainty and then proposes a GVPP near-zero carbon random scheduling optimization model based on IGDT.
Originality/value
This study designed a novel structure of the GVPP integrating P2G, gas storage device into the VPP and proposed a basic near-zero carbon scheduling optimization model for GVPP under the optimization goal of minimizing operating costs. At last, this study constructed a stochastic scheduling optimization model for GVPP.
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Melanie E. Kreye, Linda B. Newnes and Yee Mey Goh
– The purpose of this paper is to explore the information that manufacturing companies have available when competitively bidding for service contracts.
Abstract
Purpose
The purpose of this paper is to explore the information that manufacturing companies have available when competitively bidding for service contracts.
Design/methodology/approach
A semi-structured interview study was undertaken with industrialists in various sectors, which are currently facing the issue of servitisation.
Findings
One of the main findings was that, despite the novelty of the process, the decision makers at the competitive bidding stage have an understanding of the involved uncertainties. In particular, the uncertainty arising from the customer as the user of the product and evaluator of the competitive bids in addition to the uncertainty connected to the competitors were identified as the main influences on the pricing decision.
Research limitations/implications
The research implications show the influences and considerations during the decision-making process at the competitive bidding stage for service contracts. These include the customer and the competitors.
Practical implications
Shortcomings in the current industrial practice were identified such as the approaches used to communicate the cost estimate for the service contract. The approaches currently used contradict research findings in the area of communicating uncertainty information, which means that further research is to be done to identify optimal approaches to displaying the uncertainty connected to the communicated information.
Originality/value
This paper offers a basis for research to understand the challenges industry faces when competitively bidding for service contracts. This can be used to develop novel approaches in supporting the decision maker such as a model that presents the probability of winning in comparison to the probability of making a profit.
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