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1 – 10 of over 6000Rishabh Rathore, Jitesh J. Thakkar and Jitendra Kumar Jha
The food supply chain is exposed to severe environmental and social issues with serious economic consequences. The identification and assessment of risk involved in the food…
Abstract
Purpose
The food supply chain is exposed to severe environmental and social issues with serious economic consequences. The identification and assessment of risk involved in the food supply chain can help to overcome these challenges. In response, the purpose of this paper is to develop a risk assessment framework for a typical food supply chain.
Design/methodology/approach
An integrated methodology of grey analytical hierarchy process and grey technique for order preference by similarity to the ideal solution is proposed for developing a comprehensive risk index. The opinion of the experts is used to illustrate an application of the proposed methodology for the risk assessment of the food supply chain in India.
Findings
Valuable insights and recommendations are drawn from the results, which are helpful to the practitioners working at strategic and tactical levels in the food supply chain for minimising the supply chain disruptions.
Research limitations/implications
The risk quantification for the case organisation is primarily based on inputs collected from the experts working for Indian food supply chain, and so the generalisation of the results is limited to the context of developing countries. However, the generalisability of the proposed risk quantification methodology and key insights developed in the food supply chain will assist practitioners in policy making.
Practical implications
The risk priorities established by this research would enable an implementation of systematic risk mitigation strategies and deployment of necessary resources for leveraging the efficiency of food supply chain.
Originality/value
Specifically, this research has delivered a risk quantification framework and strengthened the inquiry of risk management for the food supply chain.
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Haris Doukas, Alexandros Flamos, Charikleia Karakosta, Maria Flouri and John Psarras
Greece is a net importer of oil and gas and is among the most vulnerable countries of the European Union (EU) on energy supply disruptions. Furthermore, is considered a…
Abstract
Purpose
Greece is a net importer of oil and gas and is among the most vulnerable countries of the European Union (EU) on energy supply disruptions. Furthermore, is considered a “crossroad” of existing and forthcoming infrastructure for importing energy to the EU. The purpose of this paper is the presentation of the web tool that implements the developed methodology for the quantification of socio‐economic risks of oil and gas corridors. The tool is applied to the main present and future oil and gas corridors to Greece, and the related outcomes are discussed.
Design/methodology/approach
A structured and coherent review on the future and present oil and natural gas (NG) corridors to Greece was elaborated, based on desk analysis and collection of the related data from national and international sources. Factor analysis was employed for the quantification of socio‐economic risks of each energy corridor. Particular emphasis was laid on the tool's design, so as to be user‐friendly, combining intuitive menus and navigation throughout the steps of the system.
Findings
The calculation of socio‐economic risks of the main oil and gas corridors to Greece provides operative and measurable concepts for supporting energy‐modelling processes. Indeed, this paper provides useful insights on the factors affecting the smooth energy supply and the reliability of oil and gas supply options to the Greek energy system. Moreover, the presented web tool can be used as a reference point for the researcher working on energy supply risks quantification.
Originality/value
The introduction of the energy corridors perspective in the valuation of supply security is of significant importance, taking into account the constantly increasing energy dependence of EU countries. To the best of the authors' knowledge, a structured and coherent review of the future and present oil and NG corridors to Greece is not present in the international literature. In addition to this, the development of the web tool is a clear contribution towards the quantification of the economic and socio‐political risk analysis and a step forward of the existing studies.
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This paper aims to present the combination of enterprise risk management (ERM) and value-based management as especially suitable methods for companies with a shareholder value…
Abstract
Purpose
This paper aims to present the combination of enterprise risk management (ERM) and value-based management as especially suitable methods for companies with a shareholder value imperative. Among its major benefits, these methods make the contribution of risk management for business decisions more effective.
Design/methodology/approach
Any possible inconsistencies between ERM, generating value because of imperfect capital markets and the CAPM to calculate cost of capital, which assumes perfect markets, must be avoided. Therefore, it is imperative that valuation methods used are based on risk analysis, and thus do not require perfect capital markets.
Findings
Value-based risk management requires the impact of changes in risk on enterprise value to be calculated and the aggregation of opportunities and risks related to planning to calculate total risk (using Monte Carlo simulation) and valuation techniques that reflect the effects changes in risk, on probability of default, cost of capital and enterprise value (and do not assume perfect capital markets). It is recommended that all relevant risks should be quantified and described using adequate probability distributions derived from the best information.
Practical implications
This approach can help to improve the use of risk analysis in decision-making by improving existing risk-management systems.
Originality/value
This extension of ERM is outlined to provide risk-adequate evaluation methods for business decisions, using Monte Carlo simulation and recently developed methods for risk–fair valuation with incomplete replication in combination with the probability of default. It is shown that quantification of all risk using available information should be accepted for the linking of risk analysis and business decisions.
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Astha Sharma, Dinesh Kumar and Navneet Arora
The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values…
Abstract
Purpose
The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.
Design/methodology/approach
An extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.
Findings
The three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.
Practical implications
The study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.
Originality/value
There is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.
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Pradeep Kumar Tarei, Jitesh J. Thakkar and Barnali Nag
The purpose of this paper is to identify various risk and sub-risk drivers that affect the supply chain (SC) performance and to propose a framework to quantify the overall SC risk…
Abstract
Purpose
The purpose of this paper is to identify various risk and sub-risk drivers that affect the supply chain (SC) performance and to propose a framework to quantify the overall SC risk index by considering the importance of each risk and sub-risk drivers and their mutual interactions.
Design/methodology/approach
A hybrid method based on decision-making trial and evaluation laboratory and analytical network process has been proposed to develop the risk quantification framework. A case study of Indian petroleum supply chain (PSC) has been illustrated to explain the proposed method.
Findings
The results of this study found that transportation/logistics (delivery system), quality of the petroleum products, crude supply, customer’s order and legal/political regulations are the most significant risk drivers of a typical PSC. It is also found that the Indian PSC possesses a risk score of 34 percent.
Research limitations/implications
The quantification of risk in operational measure provides an unblemished representation of the overall SC risk. Unlike the existing financial measure, it takes complex subjective operational effectiveness like product quality, customer satisfaction, etc., into consideration. Identifying the high-prioritized risks helps the decision and policy makers to merely focus on the most prominent risk drivers, and reduce the impact of overall SC risk. Planning a risk mitigation strategy at a given level of risk is however beyond the scope of this research.
Originality/value
The paper develops a risk quantification framework in the context of a PSC.
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Ziyu Jin, John Gambatese, Ding Liu and Vineeth Dharmapalan
The prevention through design (PtD) concept has been widely recognized as one of the most effective approaches to eliminate or reduce construction site hazards. It encourages…
Abstract
Purpose
The prevention through design (PtD) concept has been widely recognized as one of the most effective approaches to eliminate or reduce construction site hazards. It encourages engineers and architects to consider occupational safety and health during the planning and design phases. Nevertheless, the implementation of PtD is often inhibited because designers lack adequate knowledge about construction safety and the construction process, and limited design-for-safety tools and procedures are available for designers to use. The purpose of this paper is to provide designers a tool for assessing construction risks during early phases of multistory building projects at an activity level and on a daily basis in a 4D environment. By using the tool, proactive measures could be taken in the design and planning phase to reduce site hazards.
Design/methodology/approach
The proposed method consists of four steps including risk quantification at a design element level, 4D model integration with risk values, risk assessment, and design alternative selection and model acceptance. A case study was carried out to test and verify the proposed method.
Findings
The proposed tool has the capability to assess the safety risk for an entire multistory project and visualize safety risk in a particular time period, work space and task prior to construction. It benefits designers in conducting risk assessments and selecting design alternatives concerning safety. Contractors could also utilize the visualization and simulation results of the 4D model for site safety planning so that a range of risk mitigation strategies could be implemented during construction.
Originality/value
The study provides an innovative PtD tool targeting designers as primary end-users. The proposed tool helps designers assess construction risks and has potential to incorporate the top levels of the hierarchy of risk controls.
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Henry Lau, Yung Po Tsang, Dilupa Nakandala and Carman K.M. Lee
In the cold supply chain (SC), effective risk management is regarded as an essential component to address the risky and uncertain SC environment in handling time- and…
Abstract
Purpose
In the cold supply chain (SC), effective risk management is regarded as an essential component to address the risky and uncertain SC environment in handling time- and temperature-sensitive products. However, existing multi-criteria decision-making (MCDM) approaches greatly rely on expert opinions for pairwise comparisons. Despite the fact that machine learning models can be customised to conduct pairwise comparisons, it is difficult for small and medium enterprises (SMEs) to intelligently measure the ratings between risk criteria without sufficiently large datasets. Therefore, this paper aims at developing an enterprise-wide solution to identify and assess cold chain risks.
Design/methodology/approach
A novel federated learning (FL)-enabled multi-criteria risk evaluation system (FMRES) is proposed, which integrates FL and the best–worst method (BWM) to measure firm-level cold chain risks under the suggested risk hierarchical structure. The factors of technologies and equipment, operations, external environment, and personnel and organisation are considered. Furthermore, a case analysis of an e-grocery SC in Australia is conducted to examine the feasibility of the proposed approach.
Findings
Throughout this study, it is found that embedding the FL mechanism into the MCDM process is effective in acquiring knowledge of pairwise comparisons from experts. A trusted federation in a cold chain network is therefore formulated to identify and assess cold SC risks in a systematic manner.
Originality/value
A novel hybridisation between horizontal FL and MCDM process is explored, which enhances the autonomy of the MCDM approaches to evaluate cold chain risks under the structured hierarchy.
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Emille Rocha Bernardino de Almeida Prata, José Benício Paes Chaves, Silvane Guimarães Silva Gomes and Frederico José Vieira Passos
Quantitative metrics should be used as a risk management option whenever possible. This work proposes a framework for the risk quantification and the resulting risk-based design…
Abstract
Purpose
Quantitative metrics should be used as a risk management option whenever possible. This work proposes a framework for the risk quantification and the resulting risk-based design of control charts to monitor quality control points.
Design/methodology/approach
Two quality control models were considered for the risk quantification analysis. Estimated operating characteristic curves, expressing the defect rate (on a ppm basis) as a function of the sample size, process disturbance magnitude and process capacity, were devised to evaluate the maximum rate of defective product of the processes. The proposed framework applicability on monitoring critical control points in Hazard Analysis and Critical Control Point (HACCP) systems was further evaluated by Monte Carlo simulations.
Findings
Results demonstrate that the proposed monitoring systems can be tuned to achieve an admissible failure risk, conveniently expressed as the number of non-conforming items produced per million products, and these risks can be properly communicated. This risk-based approach can be used to validate critical control point monitoring procedures in HACCP plans. The expected rates of non-conforming items sent out to clients estimated through stochastic simulation procedures agree well with theoretical predictions.
Practical implications
The procedures outlined in this study may be used to establish the statistical validity of monitoring systems that uses control charts. The intrinsic risks of these control systems can be assessed and communicated properly in order to demonstrate the effectiveness of quality control procedures to auditing third parties.
Originality/value
This study provides advancements toward practical directives for the implementation of statistical process control in the food industry. The proposed framework allows the assessment and communication of intrinsic failure risks of quality monitoring systems. It may contribute to the establishment of risk-based thinking in the constitution of quality management systems.
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This paper aims to explore the interplay between risk management and control systems in banks, specifically investigating the managerial intentions underlying the design of…
Abstract
Purpose
This paper aims to explore the interplay between risk management and control systems in banks, specifically investigating the managerial intentions underlying the design of management control systems.
Design/methodology/approach
This study is based on 31 interviews with personnel of two banks in a European country.
Findings
The main finding is that belief systems drive the interplay between risk management and control systems in the studied banks. In several instances, belief systems and boundary systems were operating complementarily. Cross-case analyses of the two banks demonstrate that risk management (i.e. the Basel II Accord) replaced established operating procedures for loan origination and portfolio monitoring at the first bank, whereas senior managers suppressed Basel II to maintain established loan origination and portfolio monitoring procedures at the second one.
Originality/value
This is one of very few studies investigating the interplay between risk management and control systems in banks.
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