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Article
Publication date: 22 April 2024

Ghada Karaki, Rami A. Hawileh and M.Z. Naser

This study examines the effect of temperature-dependent material models for normal-strength (NSC) and high-strength concrete (HSC) on the thermal analysis of reinforced concrete…

Abstract

Purpose

This study examines the effect of temperature-dependent material models for normal-strength (NSC) and high-strength concrete (HSC) on the thermal analysis of reinforced concrete (RC) walls.

Design/methodology/approach

The study performs an one-at-a-time (OAT) sensitivity analysis to assess the impact of variables defining the constitutive and parametric fire models on the wall's thermal response. Moreover, it extends the sensitivity analysis to a variance-based analysis to assess the effect of constitutive model type, fire model type and constitutive model uncertainty on the RC wall's thermal response variance. The study determines the wall’s thermal behaviour reliability considering the different constitutive models and their uncertainty.

Findings

It is found that the impact of the variability in concrete’s conductivity is determined by its temperature-dependent model, which differs for NSC and HSC. Therefore, more testing and improving material modelling are needed. Furthermore, the heating rate of the fire scenario is the dominant factor in deciding fire-resistance performance because it is a causal factor for spalling in HSC walls. And finally the reliability of wall's performance decreased sharply for HSC walls due to the expected spalling of the concrete and loss of cross-section integrity.

Originality/value

Limited studies in the current open literature quantified the impact of constitutive models on the behaviour of RC walls. No studies have examined the effect of material models' uncertainty on wall’s response reliability under fire. Furthermore, the study's results contribute to the ongoing attempts to shape performance-based structural fire engineering.

Details

Journal of Structural Fire Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-2317

Keywords

Article
Publication date: 28 June 2024

Partha Protim Das and Shankar Chakraborty

Grey relational analysis (GRA) has already proved itself as an efficient tool for multi-objective optimization of many of the machining processes. In GRA, the distinguishing…

Abstract

Purpose

Grey relational analysis (GRA) has already proved itself as an efficient tool for multi-objective optimization of many of the machining processes. In GRA, the distinguishing coefficient (ξ) plays an important role in identifying the optimal parametric combinations of the machining processes and almost all the past researchers have considered its value as 0.5. In this paper, based on past experimental data, the application of GRA is extended to dynamic GRA (DGRA) to optimize two electrochemical machining (ECM) processes.

Design/methodology/approach

Instead of a static distinguishing coefficient, this paper considers dynamic distinguishing coefficient for each of the responses for both the ECM processes under consideration. Based on these coefficients, the application of DGRA leads to determination of the dynamic grey relational grade (DGRG) and grey relational standard deviation (GRSD), helping in initial ranking of the alternative experimental trials. Considering the ranks obtained by DGRG and GRSD, a composite rank in terms of rank product score is obtained, aiding in final rankings of the experimental trials for both the ECM processes.

Findings

In the first example, the maximum material removal rate (MRR) would be obtained at an optimal combination of ECM parameters as electrolyte concentration = 2 mol/l, voltage = 16V and current = 4A, while another parametric intermix as electrolyte concentration = 2 mol/l, voltage = 14V and current = 2A would result in minimum radial overcut and delamination. For the second example, an optimal combination of ECM parameters as electrode temperature = 30°C, voltage = 12V, duty cycle = 90% and electrolyte concentration = 15 g/l would simultaneously maximize MRR and minimize surface roughness and conicity.

Originality/value

In this paper, two ECM operations are optimized using a newly developed but yet to be popular multi-objective optimization tool in the form of the DGRA technique. For both the examples, the derived rankings of the ECM experiments exactly match with those obtained by the past researchers. Thus, DGRA can be effectively adopted to solve parametric optimization problems in any of the machining processes.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 18 March 2024

Prosun Mandal, Srinjoy Chatterjee and Shankar Chakraborty

In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an…

Abstract

Purpose

In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode.

Design/methodology/approach

This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool.

Findings

It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm3/min and 0.001034 g/min, respectively.

Originality/value

Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 11 June 2024

Riya Bindra, Amrendra Pandey, Pooja Misra and Jagdish Shettigar

It is generally believed that business spending on capital expenditure tends to decrease as interest rates rise, and vice versa, this is not always the case. The previous…

Abstract

Purpose

It is generally believed that business spending on capital expenditure tends to decrease as interest rates rise, and vice versa, this is not always the case. The previous literature produces inconclusive results vis-à-vis the interest rate and investment nexus. This study analyzes the responsiveness of investment to changes in high and low levels of interest rates in India through a quantile-based, non-parametric method utilizing annual data from 1980 to 2022.

Design/methodology/approach

This study uses Quantile-on-quantile (QQ) technique proposed by Sim and Zhou (2015) to examine the impact of interest rate quantiles on quantiles of investment. In addition, long-term association and the direction of causality are estimated through the Cho et al. (2015) test of quantile cointegration and the Jeong et al. (2012) Granger causality in quantile (GCQ) test, respectively.

Findings

The empirical evidence validates that the linkage between investments and interest rate is not consistently negative and varies from quantile to quantile. The study finds a negative impact at median quantiles and a positive impact at extreme higher quantiles. Conversely, the impact at lower quantiles is negligible, which is also observed from quantile cointegration, indicating the presence of a statistically significant association above the median quantiles. Additionally, the study finds one interesting finding that there exists unidirectional causality from investment to interest rates in India rather than other way around.

Research limitations/implications

The study provides significant implications for policymakers as it suggests that during extreme economic conditions, the effectiveness of traditional monetary policy tools to boost capital formation is restricted. Policymakers may consider alternative measures to stimulate investment during these time periods. The study additionally posits that the neoclassical theory of investment may not be readily applicable in emerging economies in its unaltered state, mostly due to the lack of well-developed financial markets.

Originality/value

There is a limited literature available on non-linear linkage between interest rates and investment. The present study adds to the existing knowledge by investigating how investment responds differently to fluctuations in interest rates, while incorporating the complete distribution of both the variables.

Details

Journal of Economic Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 11 December 2023

Mohammad Hosein Madihi, Ali Akbar Shirzadi Javid and Farnad Nasirzadeh

In traditional Bayesian belief networks (BBNs), a large amount of data are required to complete network parameters, which makes it impractical. In addition, no systematic method…

Abstract

Purpose

In traditional Bayesian belief networks (BBNs), a large amount of data are required to complete network parameters, which makes it impractical. In addition, no systematic method has been used to create the structure of the BBN. The aims of this study are to: (1) decrease the number of questions and time and effort required for completing the parameters of the BBN and (2) present a simple and apprehensible method for creating the BBN structure based on the expert knowledge.

Design/methodology/approach

In this study, by combining the decision-making trial and evaluation laboratory (DEMATEL), interpretive structural modeling (ISM) and BBN, a model is introduced that can form the project risk network and analyze the impact of risk factors on project cost quantitatively based on the expert knowledge. The ranked node method (RNM) is then used to complete the parametric part of the BBN using the same data obtained from the experts to analyze DEMATEL.

Findings

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively.

Research limitations/implications

Compared to the traditional BBN, the proposed method will significantly reduce the time and effort required to elicit network parameters and makes it easy to create a BBN structure. The results obtained from the implementation of the model on a mass housing project showed that considering the identified risk factors, the cost overruns relating to material, equipment, workforce and overhead cost were 37.6, 39.5, 42 and 40.1%, respectively. The obtained results are based on a single case study project and may not be readily generalizable.

Originality/value

The presented framework makes the BBN more practical for quantitatively assessing the impact of risk on project costs. This helps to manage financial issues, which is one of the main reasons for project bankruptcy.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Open Access
Article
Publication date: 25 September 2023

Wassim Ben Ayed and Rim Ben Hassen

This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the…

Abstract

Purpose

This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.

Design/methodology/approach

This research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).

Findings

The main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.

Research limitations/implications

Since the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.

Practical implications

The results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.

Originality/value

Previous studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.

Details

PSU Research Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2399-1747

Keywords

Article
Publication date: 7 June 2024

Jamilu Iliyasu, Suleiman O Mamman and Attahir Babaji Abubakar

This paper aims to examine the impact of United States (US) financial sanctions on the international dominance of the US dollar.

Abstract

Purpose

This paper aims to examine the impact of United States (US) financial sanctions on the international dominance of the US dollar.

Design/methodology/approach

The survival analysis technique, which incorporates survival and hazard probabilities to determine the probability of central banks' reserve recalibration, is adopted for analysis.

Findings

The result shows that the probability of central banks recalibrating the dollar share of their official reserve currencies would increase by 60% for every ten additional financial sanctions by the United States. This could imply that more sanctions might have unintended consequences on the international reserve currency dominance of the US dollar.

Originality/value

To the best of the authors’ knowledge, this study may be a novel attempt to use survival analysis to examine the impact of financial sanctions on the US dollar’s international reserve currency dominance.

Details

Journal of Financial Economic Policy, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-6385

Keywords

Article
Publication date: 19 February 2024

Tchai Tavor

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Abstract

Purpose

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Design/methodology/approach

Employing a multifaceted approach, the study combines parametric and nonparametric tests, robustness checks, and regression analysis to assess the impact of Airbnb’s announcements on emerging economy stock markets.

Findings

Airbnb’s announcements affect emerging economies' stock markets with a distinct pattern of cumulative abnormal returns (CAR): negative before the announcement and positive afterward. Informed investors strategically leverage this opportunity through short selling before the announcement and acquiring positions following it. Regression analysis validates these trends, revealing that stock index returns and inbound tourism affect CAR before announcements, while GDP growth influences CAR afterward. Announcements pertaining to emerging economies exert a more pronounced impact on stock indices compared to city-specific announcements, with COVID-19 period announcements demonstrating greater significance in abnormal returns than non-COVID-19 period announcements.

Originality/value

This study advances existing literature through a comprehensive range of statistical tests, differentiation between emerging countries and cities, introduction of five macroeconomic variables, and reliance on credible primary Airbnb data. It highlights the potential for investors to leverage Airbnb announcements in emerging markets for stock market profits, emphasizing the need for adaptive investment strategies considering broader macroeconomic factors.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 16 May 2024

Vincenzo Fasone, Giulio Pedrini and Mariano Puglisi

This paper applies an original construct of “subjective risk intelligence (SRI)” to the small business context. By leveraging on its multidimensionality, it aims to shed light on…

Abstract

Purpose

This paper applies an original construct of “subjective risk intelligence (SRI)” to the small business context. By leveraging on its multidimensionality, it aims to shed light on the existing ambiguities in the analysis of the relationship between the entrepreneurial attitude towards risk evaluation and firms’ financial stability.

Design/methodology/approach

The empirical investigation refers to the Italian context, where an ad hoc survey has been administered to a sample of small businesses. Based on both a linear and a semiparametric regression, results show a significant relationship between SRI and firm’s financial structure, and that such relationship is basically nonlinear.

Findings

Evidence shows that entrepreneurs with a high level of risk intelligence run highly leveraged firms. Moreover, in the light of the non-linearity of such relationship, higher levels of risk intelligence are associated with a greater capacity of the entrepreneur to govern the financial balance of the enterprise only up to a certain threshold. Over this threshold, risk intelligence generates overconfidence leading the entrepreneur to a reckless behaviour in taking financial risks.

Originality/value

From a theoretical point of view, the paper contributes to the literature by shedding lights on the complexity of the relationship between risk intelligence and small businesses. From a policy point of view, findings suggest that, to train new entrepreneurs, the educational system aims should focus on the development of two specific “soft skills”: the ability to manage emotions and the ability to glimpse opportunities even in uncertain situations.

Details

International Journal of Entrepreneurial Behavior & Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2554

Keywords

Open Access
Article
Publication date: 24 July 2024

Zhenhua Qin and Xiao-Lin Li

This paper explores whether fintech paves the way for the transition to carbon neutrality in the context of China’s climate policy uncertainty (CCPU) and the influence of the…

73

Abstract

Purpose

This paper explores whether fintech paves the way for the transition to carbon neutrality in the context of China’s climate policy uncertainty (CCPU) and the influence of the ocean carbon sink market.

Design/methodology/approach

We apply a novel wavelet analysis technique to investigate the time-frequency dependence between the CCPU index, the CSI (China Securities Index) Fintech Theme Index (CFTI) and the Carbon Neutral Concept Index (CNCI).

Findings

The empirical results show that CCPU and CFTI have a detrimental effect on CNCI in high-frequency bands. Furthermore, in low-frequency domains, the development of CFTI can effectively promote the realization of carbon neutrality.

Practical implications

Our findings show that information from the CCPU and CFTI can be utilized to forecast the movement of CNCI. Therefore, the government should strike a balance between fintech development and environmental regulation and, hence, promote the use of renewable energy to reduce carbon emissions, facilitating the orderly and regular development of the ocean carbon sink market.

Originality/value

The development of high-quality fintech and positive climate policy reforms are crucial for achieving carbon neutrality targets and promoting the growth of the marine carbon sink market.

Details

Marine Economics and Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2516-158X

Keywords

1 – 10 of 325