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Article
Publication date: 12 March 2024

Anu Mohta and V. Shunmugasundaram

This study aims to assess the risk profile of millennial investors residing in the Delhi NCR region. In addition, the relationship between the risk profile and demographic traits…

Abstract

Purpose

This study aims to assess the risk profile of millennial investors residing in the Delhi NCR region. In addition, the relationship between the risk profile and demographic traits of millennial investors was also analyzed.

Design/methodology/approach

Data was collected using a structured questionnaire segregated into two sections. In the first section, millennials were asked questions on socio-demographic factors, and the second section contained ten Likert-type statements to cover the multidimensionality of financial risk. Factor analysis and one-way ANOVA were used to analyze the primary data collected for this study.

Findings

The findings indicate that the risk profile of millennials is mainly affected by three factors: risk-taking capacity, risk attitude and risk propensity. Except for educational qualification and occupation, all other demographic features, such as age, gender, marital status, income and family size, seem to significantly influence the factors defining millennials' risk profile.

Originality/value

Uncertainty is inherent in any financial decision, and an investor’s willingness to deal with these variations determines their investment risk profile. To make sound financial decisions, it is mandatory to understand one’s risk profile. The awareness of millennials' distinctive risk profile will come in handy to financial stakeholders because they account for one-third of India’s population, and their financial decisions will shape the financial world for the decades to come.

Details

Global Knowledge, Memory and Communication, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9342

Keywords

Article
Publication date: 19 January 2015

Andrea Consiglio and Stavros Zenios

This paper aims to use a risk management approach for re-profiling of sovereign debt. It develops profiles that trade off expected cost of financing alternative debt structures…

1560

Abstract

Purpose

This paper aims to use a risk management approach for re-profiling of sovereign debt. It develops profiles that trade off expected cost of financing alternative debt structures against their risk. The risk profiles are particularly informative for countries facing sovereign debt crisis, as they allow us to identify, with high probability, debt unsustainability. Risk profiles for two eurozone countries with excessive debt, Cyprus and Italy, were developed. In addition, risk profiles were developed for a proposal to impose debt sanctions in the Ukrainian crisis and it was shown that the financial impact could be substantial.

Design/methodology/approach

Using scenario analysis, a risk measure of the sovereign’s debt – Conditional Debt-at-Risk – was developed, and an optimization model was then used to trade off expected cost of debt financing against the Conditional Debt-at-Risk. The model is applied to three diverse settings from current crises.

Findings

The methodology traces informative risk profiles to identify sustainable debt structures. Interesting, although tentative, conclusions are drawn for the countries where the methodology was applied. Cyprus’s debt sustainability hinges on current International Monetary Fund (IMF) projections about gross domestic product growth and small deviations can push debt into unsustainable territory. For Italy, our analysis provides evidence of debt unsustainability. Common assumption of debt by eurozone member states could restore sustainability for Italy. Finally, it is shown how a proposal to impose debt sanctions against Russia for the Ukrainian crisis could have significant financial impact for Ukraine.

Research limitations/implications

Additional work is needed to calibrate the simulation models for each country separately. Nevertheless, the direction of the results is such that more careful calibration will most likely not alter the conclusions but make them stronger instead.

Practical implications

The results provide significant insights for the management of sovereign debt for Cyprus and Italy. They also show the significant positive impact on Ukrainian public finances from debt sanctions. However, the most important practical implication is to show how the proposed methodology provided a decision support tool for restructuring and rescheduling sovereign debt for crisis countries.

Social implications

There is widespread acceptance that debt restructuring has been too little and too late in recent crises failing to re-establish market access in a durable way. How to develop risk profiles for alternative debt structures has been illustrated. Debt profiles that are unsustainable can be identified, with high probability, and alternative structures proposed that restore sustainability. The methodology proposed in this paper is providing a useful tool of analysis. The topic of debt relief is currently debated widely at policy circles by the IMF and the United Nations, and the analysis of this paper provides some insightful input to the debate.

Originality/value

The use of scenario analysis for sovereign debt modeling and the use of an optimization model developed by the authors in previous research provide empirical analysis for three current problems in sovereign debt management. Useful insights are obtained for three important real-world cases for Cyprus, Italy and Ukraine.

Article
Publication date: 14 May 2020

Tariq Al-Shbail

Customs risk management has been widely recognized as a powerful tool to balance between trade facilitation and revenue maximization. However, most customs administrations…

Abstract

Purpose

Customs risk management has been widely recognized as a powerful tool to balance between trade facilitation and revenue maximization. However, most customs administrations worldwide, particularly in developing countries, are suffering from a lack of experience and knowledge to assess their risk management systems for revenue protection (RP). Customs risk management has a very limited legacy in the literature. Academic research is quite scarce and very limited, although its relevance to customs administrations. This paper aims to identify the key risk profiles and indicators that contribute to the protection of customs revenue and investigate the role of these risk profiles and indicators on customs RP using the case of Jordan Customs.

Design/methodology/approach

This study adopts a panel data approach by using the case of Jordan Customs. Data were collected from the risk targeting and selectivity system at Jordan Customs for the year 2019, a total of 600 observations.

Findings

The findings show that all risk targeting criteria except random selectivity (RS) and HS code have a significant positive association with RP. The findings also revealed that RS is an effective tool to prevent traders with fraud and offenses history from a prediction of targeting patterns and to assess the traders’ compliance and make sure their declarations are free from fraud or offenses. Moreover, the findings of this study indicate that customs administrations should adopt alternative programs such as authorized economic operator and post clearance audit as an effective means to measure and improve compliance.

Research limitations/implications

The main contribution of this study lies in proposing a model to assist customs administrations in assessing the performance of risk management systems to protect revenue. This model provides a comprehensive conceptualization and explanations necessary for numerous aspects of risk management projects and it assists to predict the outcomes based on formulated indicators.

Practical implications

This study provides guidelines for risk analysts on how to identify and assess the key risk profiles and indicators that effect on maximizing the detection of revenue leakage and to obtain interpretable and predictable results. In addition, the findings of this study will assist customs administrations in supporting revenue collection, minimizing uncertainty, allocating resources more effectively to target high-risk consignments, while simplifying the procedures for the safe consignments.

Originality/value

This paper is of significant value because it is one of the preliminary studies that empirically identify the risk indicators/profiles that contribute to the protection of revenue and investigate the predictive power of these risk indicators/profiles as a key predictor to protect customs revenue.

Details

Transforming Government: People, Process and Policy, vol. 14 no. 3
Type: Research Article
ISSN: 1750-6166

Keywords

Article
Publication date: 3 June 2014

Archie Lockamy III

As organizations increase their dependence on supply chain networks, they become more susceptible to their suppliers’ disaster risk profiles, as well as other categories of risk

3684

Abstract

Purpose

As organizations increase their dependence on supply chain networks, they become more susceptible to their suppliers’ disaster risk profiles, as well as other categories of risk associated with supply chains. Therefore, it is imperative that supply chain network participants are capable of assessing the disaster risks associated with their supplier base. The purpose of this paper is to assess the supplier disaster risks, which are a key element of external risk in supply chains.

Design/methodology/approach

The study participants are 15 automotive casting suppliers who display a significant degree of disaster risks to a major US automotive company. Bayesian networks are used as a methodology for examining the supplier disaster risk profiles for these participants.

Findings

The results of this study show that Bayesian networks can be effectively used to assist managers in making decisions regarding current and prospective suppliers vis-à-vis their potential revenue impact as illustrated through their corresponding disaster risk profiles.

Research limitations/implications

A limitation to the use of Bayesian networks for modeling disaster risk profiles is the proper identification of risk events and risk categories that can impact a supply chain.

Practical implications

The methodology used in this study can be adopted by managers to assist them in making decisions regarding current or prospective suppliers vis-à-vis their corresponding disaster risk profiles.

Originality/value

As part of a comprehensive supplier risk management program, organizations along with their suppliers can develop specific strategies and tactics to minimize the effects of supply chain disaster risk events.

Details

Industrial Management & Data Systems, vol. 114 no. 5
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 1 June 2002

A. Ireland, D.A. Tomalin, M. Renshaw and K. Rayment

While there is debate about the extent to which patients are harmed when they are cared for in hospital, it is clear that admission as an inpatient is not without risk. This paper…

646

Abstract

While there is debate about the extent to which patients are harmed when they are cared for in hospital, it is clear that admission as an inpatient is not without risk. This paper presents works on the progress to date with identifying what these risks are and quantifying the likelihood and severity of the risk. The clinical risk profiling tool that has been developed as part of this exercise has assisted with the identification and prioritisation of clinical risks and is the first step in risk reduction and elimination.

Details

International Journal of Health Care Quality Assurance, vol. 15 no. 3
Type: Research Article
ISSN: 0952-6862

Keywords

Article
Publication date: 9 March 2012

Archie Lockamy and Kevin McCormack

To counteract the effects of global competition, many organizations have extended their enterprises by forming supply chain networks. However, as organizations increase their…

3033

Abstract

Purpose

To counteract the effects of global competition, many organizations have extended their enterprises by forming supply chain networks. However, as organizations increase their dependence on these networks, they become more vulnerable to their suppliers' risk profiles. The purpose of this paper is to present a methodology for modeling and evaluating risk profiles in supply chains via Bayesian networks.

Design/methodology/approach

Empirical data from 15 casting suppliers to a major US automotive company are analyzed using Bayesian networks. The networks provide a methodological approach for determining a supplier's external, operational, and network risk probability, and the potential revenue impact a supplier can have on the company.

Findings

Bayesian networks can be used to develop supplier risk profiles to determine the risk exposure of a company's revenue stream. The supplier risk profiles can be used to determine those risk events which have the largest potential impact on an organization's revenues, and the highest probability of occurrence.

Research limitations/implications

A limitation to the use of Bayesian networks to model supply chain risks is the proper identification of risk events and risk categories that can impact a supply chain.

Practical implications

The methodology used in this study can be adopted by managers to formulate supply chain risk management strategies and tactics which mitigate overall supply chain risks.

Social implications

The methodology used in this study can be used by organizations to reduce supply chain risks which yield numerous societal benefits.

Originality/value

As part of a comprehensive supplier risk management program, organizations along with their suppliers can develop targeted approaches to minimize the occurrence of supply chain risk events.

Article
Publication date: 24 October 2008

Claudio Giannotti and Gianluca Mattarocci

In real estate industry, managers' choices in portfolio construction impact directly on the performance of real estate fund. Looking at the literature, real estate diversification…

1568

Abstract

Purpose

In real estate industry, managers' choices in portfolio construction impact directly on the performance of real estate fund. Looking at the literature, real estate diversification criteria are related to tenants' characteristics, to endogenous and exogenous risk and to financial choices. The aim of the paper is to study the role of different risk profiles in the investment selection and in the construction of an efficient real estate portfolio.

Design/methodology/approach

The first step is to find out an investment selection model based on the main risk factors. The aim was to check the ability of qualitative criteria (tenant, exogenous, endogenous and financial risks) to identify ex ante the best investment opportunities. The observation of the portfolios' composition on the efficient frontier and the proximity of individual property to the efficient frontier point out which risk factors are more important. The second step is to define a model to construct a portfolio, with non correlated investments, based on the main risk factors. This ability was tested by comparing the classifications made according to quality criteria, which can potentially be used ex ante to construct a diversified portfolio, with the results of cluster analysis. The results from the cluster analysis, free from quality profiles, are therefore considered as the best diversification strategy.

Findings

The results stemming from the use of a real estate database supplied by Fimit SGR (Unicredit banking group) showed that an ex ante study of risk profiles can help to identify those investment opportunities which are more or less near to the efficient frontier, although there is no prevailing criterion to identify a portfolio able to maximise investment diversification benefits. To identify more efficient portfolio is necessary to define an evaluation approach that considers simultaneously different risk profiles of real estate investments.

Originality/value

The paper considers the Italian market, a young market for institutional real estate investments characterised by high growing opportunities. The value added of the paper is to study the relationship of different real estate specific risks considered in literature (tenant risk, endogenous and exogenous risk) and financing choices in order to define a more complete model to evaluate real estate portfolios.

Details

Journal of European Real Estate Research, vol. 1 no. 3
Type: Research Article
ISSN: 1753-9269

Keywords

Article
Publication date: 1 December 2004

Michael Mainelli

There is a gap linking organisational risk profiles to real people. Yet people are core to all risk/reward decisions, both at an organisational and a personal level. If an…

1688

Abstract

There is a gap linking organisational risk profiles to real people. Yet people are core to all risk/reward decisions, both at an organisational and a personal level. If an organisation is the aggregate of the decisions made by its people, how can aggregation be carried out sensibly; how can concordance between the organisational risk/reward profile and its people’s be ensured; what tools might help? The paper concludes with suggestions for areas of potentially fruitful research into how personal risk/reward profiles can be assessed and analysed to inform organisational risk/reward decisions.

Details

Journal of Financial Regulation and Compliance, vol. 12 no. 4
Type: Research Article
ISSN: 1358-1988

Keywords

Article
Publication date: 31 May 2011

Archie Lockamy

The purpose of this paper is to provide a methodology for benchmarking supplier risks through the creation of Bayesian networks. The networks are used to determine a supplier's…

1820

Abstract

Purpose

The purpose of this paper is to provide a methodology for benchmarking supplier risks through the creation of Bayesian networks. The networks are used to determine a supplier's external, operational, and network risk probability to assess its potential impact on the buyer organization.

Design/methodology/approach

The research methodology includes the use of a risk assessment model, surveys, data collection from internal and external sources, and the creation of Bayesian networks used to create risk profiles for the study participants.

Findings

It is found that Bayesian networks can be used as an effective benchmarking tool to assist managers in making decisions regarding current and prospective suppliers based upon their potential impact on the buyer organization, as illustrated through their associated risk profiles.

Research limitations/implications

A potential limitation to the use of the methodology presented in the study is the ability to acquire the necessary data from current and potential suppliers needed to construct the Bayesian networks.

Practical implications

The methodology presented in this paper can be used by buyer organizations to benchmark supplier risks in supply chain networks, which may lead to adjustments to existing risk management strategies, policies, and tactics.

Originality/value

This paper provides practitioners with an additional tool for benchmarking supplier risks. Additionally, it provides the foundation for future research studies in the use of Bayesian networks for the examination of supplier risks.

Details

Benchmarking: An International Journal, vol. 18 no. 3
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 20 December 2018

Archie Lockamy III

The global electronic equipment industry has evolved into one of the most innovative technology-based business sectors to transpire in the last three decades. Much of its success…

1374

Abstract

Purpose

The global electronic equipment industry has evolved into one of the most innovative technology-based business sectors to transpire in the last three decades. Much of its success has been attributed to effective supply chain management. The purpose of this paper is to provide an examination of external risk factors associated with the industry’s key suppliers through the creation of Bayesian networks which can be used to benchmark external risks among these suppliers.

Design/methodology/approach

The study sample consists of the suppliers to seven of the leading global electronic equipment companies. Bayesian networks are used as a methodology for examining the supplier external risk profiles of the study sample.

Findings

The results of this study show that Bayesian networks can be effectively used to assist managers in making decisions regarding current and prospective suppliers with respect to their potential impact on supply chains as illustrated through their corresponding external risk profiles.

Research limitations/implications

A limitation to the use of Bayesian networks for modeling external risk profiles is the proper identification of risk events and risk categories that can impact a supply chain.

Practical implications

The methodology used in this study can be adopted by managers to assist them in making decisions regarding current or prospective suppliers vis-à-vis their corresponding external risk profiles.

Originality/value

As part of a comprehensive supplier risk management program, companies along with their suppliers can develop specific strategies and tactics to minimize the effects of supply chain external risk events.

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