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This study aims to investigate the relationship between stock markets, environmental, social and governance (ESG) factors and Shariah-compliant in an integrated framework.

The authors employ the multivariate factor stochastic volatility (mvFSV) framework to extract the volatility of the different sectoral indices. Based on this evidence, the authors employ the quantile vector autoregressive (QVAR) approach to examine the dynamic spillover connectedness among the aforementioned indices.

The study emphasizes the following major findings: (1) significant time-varying spillover connectedness across quantiles, (2) bidirectional and asymmetric spillover effect among the ESG index and the other sectoral indices, (3) the strength of spillover connectedness is time-varying across quantiles, (4) based on the perspective of portfolio optimization, ESG market is a significant strong forecasting contributor to conventional and Shariah-compliant markets, (5) overall, the findings point out serious quantile pass-through effect among ESG index and the other sectoral indices during the COVID-19 health crisis.

This study extends the previous literature in the following ways. First, to the best of the researchers’ knowledge, none of the existing studies have investigated the relationship between stock markets, ESG factors and Shariah-compliant in an integrated framework. Second, this study extends the previous scholarships by applying the mvFSV. Third, the authors propose a new rolling version to estimate dynamic spillovers, namely the rolling-window quantile VAR method. This approach provides a great advantage in computing the dynamics of return and variance spillover between variables in terms not only of the overall factor but also of the net (pairwise) aspect.

Commercial banks face several risks, including credit, liquidity, operational and disruptive risks. In addition to these risks that are challenging for banks to control and manage, crises and disasters can exert substantially more destructive shocks. These shocks can exacerbate internal risks and cause severe damage to the bank's performance, leading banks to bankruptcy and closure. This study aims to facilitate achieving resilient banking policies through a model-based assessment of business continuity management (BCM) policies.

By applying a system dynamics (SD) methodology, a systemic model that includes a causal structure of the banking business is presented. To build a simulation model, data are collected from a commercial bank in Iran. By presenting the simulation model of the bank's business, the consequences of some given crises on the bank's performance are tested, and the effectiveness of risk and crisis management policies is evaluated. Vensim Personal Learning Edition (PLE) software is used to construct the simulation model.

Results indicate that the current BCM policies do not show appropriate resilience in the face of various crises. Commercial banks cannot create sustainable value for the banks' shareholders despite the possibility of profitability, as the shareholders lack adequate resilience and soundness. These commercial banks do not have the appropriate resilience for the next pandemic after coronavirus disease 2019 (COVID-19). Moreover, the robustness of the current banking business model is very fragile for the banking run crisis.

A forward-looking view of resilient banking can be obtained by combining liquidity coverage, stable funding, capital adequacy and insights from stress tests. Resilient banking requires a balanced combination of robustness, soundness and profitability.

The present study is a combination of bank business management, risk and resilience management and SD simulation. This approach can analyze and simulate the dynamics of bank resilience. Additionally, present of a decision support system (DSS) to analyze and simulate the outcomes of different crisis management policies and solutions is an innovative approach to developing effective and resilient banking policies.

In many manufacturing systems, machines are subject to preventive maintenance. This paper aims to schedule the operations of jobs and preventive maintenance tasks in such a way that the completion time of jobs and preventive maintenance tasks is minimized.

An heuristic approach based on artificial immune algorithm is proposed for solving the multiple‐route job shop‐scheduling problem subject to fixed periodic and age‐dependent preventive maintenance tasks. Under fixed periodic assumption, the time between two consecutive preventive maintenance tasks is assumed constant. Under age‐dependent assumption, a preventive maintenance task is triggered if the machine operates for a certain amount of time. The goal is to schedule the jobs and preventive maintenance task subject to makespan minimization.

In addition to presenting mathematical formulation for the multiple‐route job shop‐scheduling problem, this paper proposes a novel approach by which one can tackle the complexity that is raised in scheduling and sequencing the jobs and the preventive maintenance simultaneously and obtain the required schedule in reasonable time.

Integrating preventive maintenance tasks into the scheduling procedure is vital in many manufacturing systems. Using the proposed approach, one can obtain a schedule that defines the production route through which each part is processed, the time each operation must be started, and when preventive maintenance must be carried out on each machine. This, in turn, results in overall manufacturing cost reduction.

Using the approach proposed in this paper, good solutions, if not optimal, can be obtained for scheduling jobs and preventive maintenance task in one of the most complicated job shop configurations, namely, multiple‐route job shop. Thus, the approach can dominate all other simpler configurations.

During the last decade, intellectual capital (IC) has been widely considered as a critical tool to deliver successful business in an intensive knowledge environment. The main goal of this paper is therefore to develop and prioritize human capital indicators as an important component of IC in knowledge-based industries.

Based on an extensive literature review, a valid and reliable questionnaire was designed. In order to gather data, it was sent out to 108 participants from academia and universities who were well qualified in pharmaceutical practice. Besides statistical analysis, the authors also used fuzzy TOPSIS technique as a MADM model in order to extract prioritization of indicators.

The analysis indicates that there is little difference between academic and university respondents. Furthermore, the fuzzy TOPSIS results show that participants have high concerns especially about knowledge and skills of managers and employees.

The findings offer valuable insights in evaluating the state of human capital state as a key component of IC in knowledge- based industry.

There is an immediate need that the policy makers and corporate managers wake up to the need and start to measure and disclose the intangible assets of firms. Intellectual capital measurement is also of primary interest for top executives of pharmaceutical firms in Iran.

This is an initial and pioneering study to develop a valid tool to evaluate IC in the Iranian pharmaceutical industry. The present study provides a new aspect of performance measurement for research-based industries in emerging economies and would be a good topic for further research.

This paper aims to evaluate the risk‐adjusted performance of the management styles of Malaysian mutual funds using nine modified performance evaluation measures generated by the maximum drawdown risk measure (M‐DRM) based on the modern portfolio theory. The purpose is to report the findings in a manner which is realizable by the average investors and portfolio managers.

This paper evaluates the performance of more than 400 Malaysian mutual funds using risk‐adjusted returns over the two sub‐periods of 2000‐2005 and 2006‐2011. The M‐DRM, as a different measure from downside risk, is applied to improve nine risk‐adjusted performance measures of Sortino, Treynor, M‐squared, Jensen's alpha, information ratio (IR), MSR, upside partial ration (UPR), FPI, and leverage factor. It proposes a new single‐factor model to test the maximum drawdown beta and alpha in the M‐DRM framework.

The evidence clearly indicates that the replacement framework in terms of MDB, the maximum drawdown beta, and the maximum drawdown CAPM can be replaced by the conventional frameworks in terms of MVB, beta, and the CAPM and also MSB, downside beta, and D‐CAPM for modifying nine performance evaluation measures from the management styles of Malaysian mutual funds.

The research evidence reported in this paper can be applied as input in the process of decision making by small and average investors and portfolio managers who are seeking the possibility of participating in the global stock market through mutual funds.

This paper is the first study to estimate a new regression model in the M‐DRM framework to evaluate the performance of Malaysian mutual funds. In addition, it proposes nine modified performance evaluation measures in the M‐DRM framework for the first time.

This paper aims to evaluate the risk‐adjusted performance of Malaysian mutual funds using optimized drawdown risk measures (ODRMs) based on modern portfolio theory, and to represent the results in a manner which is easily understood by average investors and portfolio managers.

This study evaluates the performance of 70 Malaysian mutual funds using risk‐adjusted returns during 2000‐2011. The ODRM is primarily calculated by 70 linear programming models, consequently seven new optimized risk‐adjusted performance measures including Sharpe, Treynor, M‐squared, Jensen's alpha, information ratio (IR), MSR, and FPI are proposed to evaluate these funds.

The results of this study have several implications. First, the ODRM can be an alternative risk measure to optimize the selection of mutual funds. Second, it proposes new seven optimized performance measures of Sharpe, Treynor, M‐square, Jensen's alpha, IR, MSR, and FPI. These measures help fund managers to evaluate the performance of Malaysian mutual funds optimally. Third, No‐Islamic funds have the upper performance than Islamic funds based on the results of optimized measures and robustness tests. Fourth, the majority of surveying funds over‐perform the benchmark indexes.

The research evidence reported by this study can be utilized as input in the process of decision making by small and average investors and portfolio managers who are seeking the possibility of participating in Malaysian stock market by mutual funds.

This paper is the first study that optimizes the drawdown risk measure to evaluate the performance of Malaysian mutual funds and propose seven optimized measures, Sharpe, Treynor, M‐Square, Jensen's alpha, IR, MSR, and FPI.

The aim of this research was to investigate the use of aqueous extracts of nettle plant (NE) as a green corrosion inhibitor of mild steel in hydrochloric acid solution.

The inhibition efficiency was investigated by weight loss measurements, potentiodynamic polarizations, electrochemical impedance spectroscopy, SEM observations and EDX analysis.

The inhibition efficiency increased with an increase in concentration of NE up to a critical concentration of 1.5×10−3 g · cm−3 where the highest inhibition efficiency of 97 percent was obtained. The adsorption of the inhibitor was spontaneous (reflected by the negative value of ΔG_ads0), supported the mechanism of physical adsorption and obeyed to the Langmuir adsorption isotherm. The inhibition action of the extracts was independent on the storage time; it could be conserved without any specific conditions of time and temperature.

The anticorrosion effect can be better understood when the active compound in the extracts is identified and what is the inhibition efficiency of one component in the presence of another in the mixture (synergetic or antagonist effects).

Nettle is a healthy plant, without particular toxicity that can find possible applications as environmentally friendly inhibitor of mild steel used as materials in food industry.

Aqueous nettle extracts were studied for the first time as corrosion inhibitor and its anticorrosion effect was proven by standard methods.