The aim is to study jump liquidity risk and its impact on risk measures: value at risk (VaR) and conditional VaR (CVaR).
Abstract
Purpose
The aim is to study jump liquidity risk and its impact on risk measures: value at risk (VaR) and conditional VaR (CVaR).
Design/methodology/approach
The liquidity discount factor is modelled with mean revision jump diffusion processes and the liquidity risk is integrated in the framework of VaR and CVaR.
Findings
The standard VaR, CVaR, and the liquidity adjusted VaR can seriously underestimate the potential loss over a short holding period for rare jump liquidity events. A better risk measure is the liquidity adjusted CVaR which gives a more realistic loss estimation in the presence of the liquidity risk. An efficient Monte Carlo method is also suggested to find approximate VaR and CVaR of all percentiles with one set of samples from the loss distribution, which applies to portfolios of securities as well as single securities.
Originality/value
The paper offers plausible stochastic processes to model liquidity risk.
Details
Keywords
Fazli Haleem, Sami Farooq, Brian Vejrum Wæhrens and Harry Boer
Many factors have been identified that may drive a firm’s decision to offshore production activities. The actual performance effects of offshoring, however, depend on the extent…
Abstract
Purpose
Many factors have been identified that may drive a firm’s decision to offshore production activities. The actual performance effects of offshoring, however, depend on the extent to which these drivers are realized. Furthermore, the question is how risk management helps mitigating the risk involved in offshoring ventures, thus leading to better performance outcomes. The purpose of this study is to investigate the extent to which realized offshoring drivers and risk management mediate the relationship between offshoring experience and firm performance.
Design/methodology/approach
Data from the Global Operations Networks project, a cross-sectional survey administered in Denmark and Sweden, are used to test two hypotheses on the mediating role of realized offshoring drivers and risk management in the relationship between offshoring experience and firm performance. AMOS version 23 is used to perform the analyses.
Findings
The results demonstrate that realized offshoring drivers fully mediate the relationship between offshoring experience and firm performance. However, risk management does not mediate the relationship between offshoring experience and firm performance.
Originality/value
This study develops new theory on, and managerial insight into, the mediating role of realized offshoring drivers and risk management in the relationship between offshoring experience and firm performance.
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Soora Rasouli and Harry Timmermans
This chapter reviews models of decision-making and choice under conditions of certainty. It allows readers to position the contribution of the other chapters in this book in the…
Abstract
Purpose
This chapter reviews models of decision-making and choice under conditions of certainty. It allows readers to position the contribution of the other chapters in this book in the historical development of the topic area.
Theory
Bounded rationality is defined in terms of a strategy to simplify the decision-making process. Based on this definition, different models are reviewed. These models have assumed that individuals simplify the decision-making process by considering a subset of attributes, and/or a subset of choice alternatives and/or by disregarding small differences between attribute differences.
Findings
A body of empirical evidence has accumulated showing that under some circumstances the principle of bounded rationality better explains observed choices than the principle of utility maximization. Differences in predictive performance with utility-maximizing models are however small.
Originality and value
The chapter provides a detailed account of the different models, based on the principle of bounded rationality, that have been suggested over the years in travel behaviour analysis. The potential relevance of these models is articulated, model specifications are discussed and a selection of empirical evidence is presented. Aspects of an agenda of future research are identified.
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Ziyu Liao, Bai Chen, Tianzuo Chang, Qian Zheng, Keming Liu and Junnan Lv
Supernumerary robotic limbs (SRLs) are a new type of wearable robot, which improve the user’s operating and perceive the user’s environment by extra robotic limbs. There are some…
Abstract
Purpose
Supernumerary robotic limbs (SRLs) are a new type of wearable robot, which improve the user’s operating and perceive the user’s environment by extra robotic limbs. There are some literature reviews about the SRLs’ key technology and development trend, but the design of SRLs has not been fully discussed and summarized. This paper aims to focus on the design of SRLs and provides a comprehensive review of the ontological structure design of SRLs.
Design/methodology/approach
In this paper, the related literature of SRLs is summarized and analyzed by VOSviewer. The structural features of different types of SRLs are extracted, and then discuss the design approach and characteristics of SRLs which are different from typical wearable robots.
Findings
The design concept of SRLs is different from the conventional wearable robots. SRLs have various reconfiguration and installed positions, and it will influence the safety and cooperativeness performance of SRLs.
Originality/value
This paper focuses on discussing the structural design of SRLs by literature review, and this review will help researchers understand the structural features of SRLs and key points of the ontological design of SRLs, which can be used as a reference for designing SRLs.
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Federico Caniato, Des Doran, Rui Sousa and Harry Boer
The purpose of this paper is to identify similarities and differences between qualitative-based and quantitative-based research, and to present recommendations for designing and…
Abstract
Purpose
The purpose of this paper is to identify similarities and differences between qualitative-based and quantitative-based research, and to present recommendations for designing and conducting the research so that the possibilities of publishing it in leading Operations Management (OM) journals are improved.
Design/methodology/approach
The paper takes its outset in contributions made at the 2016 European Operations Management Association Young Scholars Workshop. The theme of the workshop was “Designing and developing research projects in Operations Management – from concept to publication.” Taking the perspectives of the case researcher, the survey researcher and the editor/reviewer, the authors present and discuss the views on and experiences with designing research for publication.
Findings
The authors identify a number of recommendations that researchers should use when designing, conducting, and presenting their research for publication. The recommendations include the need to clearly and concisely establish relevance, account for choice of methodology as well as the operationalization, sampling, analytical, and validation methods used, and demonstrate the contribution of the paper in the discussion section. Furthermore, the authors draw attention to the importance of developing a publication strategy as early as possible. Other important aspects include the title of the paper, keywords selection, and rejection criteria. Finally, the authors stress the importance of “total quality management” in designing and executing OM research.
Originality/value
Going beyond the standard author guidelines found at journal web sites, the authors present a collection of viewpoints, which are based on the authors’ experiences as reviewers, editors, and evaluators of OM research projects and their designs.
Details
Keywords
Ahmed A.M. Abdelkader, Hend Hassan and Marwa Abdelkader
Artificial Intelligence (AI) is permeating many facets of our daily lives, appearing in household appliances, cell phones and popular online apps. AI has the capacity to…
Abstract
Artificial Intelligence (AI) is permeating many facets of our daily lives, appearing in household appliances, cell phones and popular online apps. AI has the capacity to revolutionize teaching and learning processes in higher education institutions. The integration of AI technologies in education can lead to personalized learning experiences, improved educational quality and enhanced learning outcomes. However, the adoption of AI in higher education comes with challenges such as ethical considerations and the need to address equity and inclusion issues to ensure that all students benefit from AI advancements. This chapter considers how AI can be utilized in education, while acknowledging the challenges and finding ways to mitigate them. Useful tools include: Bespoke Learning, Intelligent Tutoring Systems, Grading, Collaborative, Learning Assistance, Research Support and Adaptive Learning. The challenges addressed are: ethical considerations, resistance to change and data security and privacy. In navigating the complexities of integrating AI in higher education, institutions must strike a balance between leveraging the transformative potential of AI technologies and addressing the ethical, social and technical challenges that accompany their implementation. By prioritizing ethical considerations, addressing resistance to change and safeguarding data security and privacy, higher education institutions can harness the benefits of AI to enhance teaching and learning practices, foster innovation and prepare students for success in the digital age.