Search results

1 – 10 of over 1000
Article
Publication date: 13 January 2022

Zeinab Rahimi Rise and Mohammad Mahdi Ershadi

This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts…

Abstract

Purpose

This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts of infectious diseases in comparison with predicted gross domestic product (GDP) in future years could be beneficial for this aim along with predicted social impacts of infectious diseases in countries.

Design/methodology/approach

The proposed uncertain SEIAR (susceptible, exposed, infectious, asymptomatic and removed) model evaluates the impacts of variables on different trends using scenario base analysis. This model considers different subsystems including healthcare systems, transportation, contacts and capacities of food and pharmaceutical networks for sensitivity analysis. Besides, an adaptive neuro-fuzzy inference system (ANFIS) is designed to predict the GDP of countries and determine the economic impacts of infectious diseases. These proposed models can predict the future socioeconomic trends of infectious diseases in each country based on the available information to guide the decisions of government planners and policymakers.

Findings

The proposed uncertain SEIAR model predicts social impacts according to uncertain parameters and different coefficients appropriate to the scenarios. It analyzes the sensitivity and the effects of various parameters. A case study is designed in this paper about COVID-19 in a country. Its results show that the effect of transportation on COVID-19 is most sensitive and the contacts have a significant effect on infection. Besides, the future annual costs of COVID-19 are evaluated in different situations. Private transportation, contact behaviors and public transportation have significant impacts on infection, especially in the determined case study, due to its circumstance. Therefore, it is necessary to consider changes in society using flexible behaviors and laws based on the latest status in facing the COVID-19 epidemic.

Practical implications

The proposed methods can be applied to conduct infectious diseases impacts analysis.

Originality/value

In this paper, a proposed uncertain SEIAR system dynamics model, related sensitivity analysis and ANFIS model are utilized to support different programs regarding policymaking and economic issues to face infectious diseases. The results could support the analysis of sensitivities, policies and economic activities.

Highlights:

  • A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

  • Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

  • Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

  • An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

  • A real case study is considered to evaluate the performances of the proposed models.

A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

A real case study is considered to evaluate the performances of the proposed models.

Details

Journal of Economic and Administrative Sciences, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1026-4116

Keywords

Open Access
Article
Publication date: 14 February 2024

Chao Lu and Xiaohai Xin

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address…

Abstract

Purpose

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

Design/methodology/approach

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

Findings

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

Research limitations/implications

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

Originality/value

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

Details

Asia Pacific Journal of Innovation and Entrepreneurship, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2071-1395

Keywords

Article
Publication date: 12 December 2023

T.M. Jeyashree and P.R. Kannan Rajkumar

This study focused on identifying critical factors governing the fire response of prestressed hollow-core slabs. The hollow-core slabs used as flooring units can be subjected to…

Abstract

Purpose

This study focused on identifying critical factors governing the fire response of prestressed hollow-core slabs. The hollow-core slabs used as flooring units can be subjected to elevated temperatures during a fire. The fire response of prestressed hollow-core slabs is required to develop slabs with greater fire endurance. The present study aims to determine the extent to which the hollow-core slab can sustain load during a fire without undergoing progressive collapse under extreme fire and heating scenarios.

Design/methodology/approach

A finite element model was generated to predict the fire response of prestressed hollow core slabs under elevated temperatures. The accuracy of the model was predicted by examining thermal and structural responses through coupled temperature displacement analysis. A sensitivity analysis was performed to study the effects of concrete properties on prediction of system response. A parametric study was conducted by varying the thickness of the slab, fire and heating scenarios.

Findings

Thermal conductivity and specific heat of concrete were determined as sensitive parameters. The thickness of the slab was identified as a critical factor at a higher load level. Asymmetric heating of the slab resulted in higher fire resistance compared with symmetric heating.

Originality/value

This is the first study focused on studying the effect of modeling uncertainties on the system response by sensitivity analysis under elevated temperatures. The developed model with a parametric study helps in identifying critical factors for design purposes.

Details

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

Keywords

Article
Publication date: 26 February 2024

Muddassar Malik

This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and…

Abstract

Purpose

This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and regulatory adjustments (RAs) in Organization for Economic Cooperation and Development public commercial banks.

Design/methodology/approach

Using principal component analysis (PCA) and regression models, the research analyzes a representative data set of these banks.

Findings

A significant negative correlation between risk governance characteristics and RAs is found. Sensitivity analysis on the regulatory Tier 1 capital ratio and the total capital ratio indicates mixed outcomes, suggesting a complex relationship that warrants further exploration.

Research limitations/implications

The study’s limited sample size calls for further research to confirm findings and explore risk governance’s impact on banks’ capital structures.

Practical implications

Enhanced risk governance could reduce RAs, influencing banking policy.

Social implications

The study advocates for improved banking regulatory practices, potentially increasing sector stability and public trust.

Originality/value

This study contributes to understanding risk governance’s role in regulatory compliance, offering insights for policymaking in banking.

Details

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

Keywords

Article
Publication date: 2 November 2022

Ashis Mitra

The present study aims to demonstrate the application of newly developed combinative distance-based assessment (CODAS) approach for grading and selection of Tossa jute fibres…

Abstract

Purpose

The present study aims to demonstrate the application of newly developed combinative distance-based assessment (CODAS) approach for grading and selection of Tossa jute fibres, which possesses some unique features uncommon to other variants of multi-criteria decision-making (MCDM) method.

Design/methodology/approach

The CODAS method was used in this study to rank/grade ten candidate lots of Tossa fibres on the basis of six apposite jute fibre properties, namely, fibre defect, root content, fineness, strength, colour and density. These six fibre properties were considered as the six decision criteria, here, and they were assigned weights as determined previously by an earlier researcher using analytic hierarchy process. The grading of jute fibres was done based on a comprehensive single index known as the assessment scores (Hi), in descending order of magnitude.

Findings

Among the 10 Tossa jute lots, T2 was ranked 1 (top grade) because of the highest assessment score of 6.887, followed by T1 with Rank 2 (assessment score 1.830). Because of the least assessment score of −2.795, the candidate lot T4 was considered as the worst, and hence ranked 10. The overall ranking pattern given by the CODAS method was similar to the TOPSIS approach done by Ghosh and Das (2013). This study was supported by various sensitivity analyses to judge the efficacy of the present approach. No occurrence of rank reversal during the sensitivity analyses obviously corroborates the robustness and stability of the CODAS method.

Practical implications

Jute pricing is fixed solely by the quality for which grading of fibre is prerequisite. The traditional “Hand and Eye” method or Bureau of Indian Standards (BIS) system for jute grading is basically subjective assessment and need domain expertise. MCDM is reported as the most viable solution which gives due importance to the fibre parameters while grading the fibres based on a single index. The present study demonstrates the maiden application of CODAS to address the fibre grading problems for jute industries. This approach can also be extended to solve other decision problems of textile industry, in general.

Originality/value

CODAS is a recently developed exponent of MCDM. Uniqueness of the present study lies in the fact that this is the first ever application of CODAS in the domain of textile industry, in general, and jute industry, in particular. CODAS approach is very simple involving a few simple mathematical equations yet a potent tool of decision-making. This method possesses some features uncommon in other variants of MCDM. Moreover, the efficacy of CODAS method is investigated through various sensitivity analyses, which has been ignored in the earlier approaches.

Details

Research Journal of Textile and Apparel, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1560-6074

Keywords

Article
Publication date: 6 June 2023

Charilaos Mertzanis, Nejla Ellili, Hazem Marashdeh and Haitham Nobanee

The study examines the effects of corporate governance and countrywide institutions and risk factors on corporate liquidity.

Abstract

Purpose

The study examines the effects of corporate governance and countrywide institutions and risk factors on corporate liquidity.

Design/methodology/approach

Using firm-level data, the authors analyze the effect of corporate governance and various economic, regulatory and social institutions on the liquidity of firms operating in the Middle East and North Africa (MENA) region. The authors use fixed-effects, firm-specific and country-level controls, disaggregated analysis, sensitivity and endogeneity analysis to test the robustness of the estimates.

Findings

The corporate governance characteristics of firms influence in diverse ways their liquidity decisions. The independence and diversity of the board and institutional ownership are especially strong predictors. The effect also depends on the size of the firm and the degree of economic development and exhibits time sensitivity and nonlinearity. Enforcement institutions and risk factors play a strong role.

Originality/value

The analysis contributes to the literature by using a large sample of countries and firms over a larger period, distinguishing between poorer and richer countries and using sensitivity and endogeneity analysis. The analysis considers explicitly the role of regulatory and enforcement conditions, social structures and religious beliefs.

Details

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

Keywords

Article
Publication date: 21 February 2024

Nehal Elshaboury, Tarek Zayed and Eslam Mohammed Abdelkader

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective…

Abstract

Purpose

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

Design/methodology/approach

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Findings

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

Originality/value

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.

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: 27 July 2023

Aicha Gasmi, Marc Heran, Noureddine Elboughdiri, Lioua Kolsi, Djamel Ghernaout, Ahmed Hannachi and Alain Grasmick

The main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.

Abstract

Purpose

The main purpose of this study resides essentially in the development of a new tool to quantify the biomass in the bioreactor operating under steady state conditions.

Design/methodology/approach

Modeling is the most relevant tool for understanding the functioning of some complex processes such as biological wastewater treatment. A steady state model equation of activated sludge model 1 (ASM1) was developed, especially for autotrophic biomass (XBA) and for oxygen uptake rate (OUR). Furthermore, a respirometric measurement, under steady state and endogenous conditions, was used as a new tool for quantifying the viable biomass concentration in the bioreactor.

Findings

The developed steady state equations simplified the sensitivity analysis and allowed the autotrophic biomass (XBA) quantification. Indeed, the XBA concentration was approximately 212 mg COD/L and 454 mgCOD/L for SRT, equal to 20 and 40 d, respectively. Under the steady state condition, monitoring of endogenous OUR permitted biomass quantification in the bioreactor. Comparing XBA obtained by the steady state equation and respirometric tool indicated a percentage deviation of about 3 to 13%. Modeling bioreactor using GPS-X showed an excellent agreement between simulation and experimental measurements concerning the XBA evolution.

Originality/value

These results confirmed the importance of respirometric measurements as a simple and available tool for quantifying biomass.

Details

Arab Gulf Journal of Scientific Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1985-9899

Keywords

Article
Publication date: 9 January 2024

Coky Fauzi Alfi, Maslinawati Mohamad and Khaled Hussainey

This study conducts a meta-analysis to investigate the impact of board diversity, independence and size on carbon emission disclosure.

Abstract

Purpose

This study conducts a meta-analysis to investigate the impact of board diversity, independence and size on carbon emission disclosure.

Design/methodology/approach

The results of 22 empirical investigations on the association between board qualities and carbon emission disclosure are synthesised using a meta-analysis approach. Inclusion and exclusion criteria are established, and search strategies are devised to locate relevant material. Data extraction entails gathering important information such as the names of the authors, variables and correlation coefficients. Fisher's z-transformation is used to compute and synthesise effect sizes and assumptions, sensitivity testing and subgroup analysis are performed to assess the robustness of the findings.

Findings

A substantial association was discovered between board characteristics and carbon emission disclosure. Board independence and gender diversity revealed small to medium-strength positive relationships, whilst board size had a medium-strength positive correlation. The study periods varied from 2011 to 2022, with 2018 having the most studies. However, highly heterogeneous groups were discovered; further subgroup analyses were then carried out to sort out this issue.

Research limitations/implications

Several limitations were recognised due to the limited number of studies and heterogeneity, although subgroup analysis was used to reduce the influence of heterogeneity. To investigate alternate outcomes, more analysis of the heterogeneity level and potential modifications to the model assumptions may be required.

Practical implications

Companies should consider board size, independence and gender diversity when formulating long-term competitive strategies in the climate change movement. These characteristics can aid in bridging information gaps and garnering stakeholder support for carbon-reduction initiatives.

Originality/value

This meta-analysis addresses a gap in the literature by addressing prior studies' conflicting and inconsistent findings on the association between board characteristics and carbon emission disclosure. It employs a rigorous approach and synthesis strategy to provide a thorough and robust understanding of the crucial role of board characteristics in carbon emission disclosure.

Details

Journal of Accounting Literature, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-4607

Keywords

Article
Publication date: 20 October 2023

Abdul Rehman Shaikh

This study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era…

Abstract

Purpose

This study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era. This study also aims to categorize and rank the identified enablers using expert panel input.

Design/methodology/approach

A review of the extant literature was conducted to investigate and identify the factors that contribute to SCR. The relative ranking of the enablers was carried out by a group of industry and academic experts. The expert panel was convened to compare the main categories and each enabler in pairs and to score the enablers using triangular fuzzy numbers.

Findings

This study identified 16 critical SCR enablers. Using the fuzzy analytic hierarchy process (AHP), these enablers were divided into three groups and analyzed. The results show that financial enablers, technology enablers and then social enablers are prioritized when it comes to SCR in emerging markets. The robustness of the ranking of enablers is tested through sensitivity analysis.

Practical implications

The results shall be helpful for policymakers and managers to understand the important enablers and also help allocate resources to important enablers. Managers will be able to formulate strategies to achieve SCR in an uncertain environment.

Originality/value

This is one of the first attempts to identify and rank the enablers of SCR in an emerging economy context.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

1 – 10 of over 1000