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Economic incentives, government regulations, and customer perspective on environmental consciousness (EC) are driving more and more companies into product recovery business, which forms the basis for a reverse supply chain. A reverse supply chain consists a series of activities that involves retrieving used products from consumers and remanufacturing (closed-loop) or recycling (open-loop) them to recover their leftover market value. Much work has been done in the areas of designing forward and reverse supply chains; however, not many models deal with the transshipment of products in multiperiods. Linear physical programming (LPP) is a newly developed method whose most significant advantage is that it allows a decision-maker to express his/her preferences for values of criteria for decision-making in terms of ranges of different degrees of desirability but not in traditional form of weights as in techniques such as analytic hierarchy process, which is criticized for its unbalanced scale of judgment and failure to precisely handle the inherent uncertainty and vagueness in carrying out pair-wise comparisons. In this chapter, two multiperiod models are proposed for a remanufacturing system, which is an element of a Reverse Supply Chain (RSC), and illustrated with numerical examples. The first model is solved using mixed integer linear programming (MILP), while the second model is solved using linear physical programming. The proposed models deliver the optimal transportation quantities of remanufactured products for N-periods within the reverse supply chain.

The purpose of this study is to examine whether the relationship between asset quality and profitability is linear or nonlinear, using a global dataset containing 2,943 banks from advanced and emerging economies.

The authors use the U-shape test to investigate the existence of a nonlinear relationship between asset quality and profitability. In addition, the dynamic panel generalised method of moments (GMM) and quantile regression are used to examine the nonlinear effect of profitability on nonperforming loans (NPLs).

After controlling for macroeconomic and bank internal factors, the authors find empirical evidence supporting the existence of a nonlinear relationship in the form of a U-shape. This is also confirmed through the three-stage U test procedure. After distinguishing between advanced and emerging economies, the authors also find that, in advanced markets, the credit policy responds more rapidly to changes in credit market conditions than in emerging markets, providing insights into credit market dynamics.

Further research can check the robustness of this study’s findings in different markets and investigate the existence of nonlinearity in other bank variables.

In a nutshell, the results demonstrate potential implications for policymakers who need to carefully monitor banks' lending behaviour to ensure that banks do not lower lending standards. In addition, banking regulators and supervisors should consider the possible nonlinear relationship in their risk assessments and macrostress tests. Further, these results are important for bank managers, who should monitor the performance of their loan portfolios to ensure that their credit officers do not lower credit standards. Likewise, for banks located in an emerging economy, investing in human capital and advanced technologies can enable them to respond more effectively to changes in the credit market.

To the best of the authors' knowledge, this study is considered the first to provide empirical evidence for the nonlinear relationship between asset quality and profitability.

This study aims to empirically investigate the impact of oil prices, political instability and changes in stability on the bank diversification of the two types of banking systems in the Middle East and North African (MENA) countries.

The study uses bank diversification, stability measurement of probability of default and Zscore by adopting the generalised method of moment for the data between 2007 and 2021. The authors estimate short- and long-run dynamic panel analysis and a robustness test.

The findings reveal that Islamic banks are slightly lower in diversification and stability than conventional peers in the region. Diversification increases with a positive increase in GDP growth, law and order, political stability, bank size, asset quality, oil price, return on equity, profitability and change in banking asset-based stability. The authors found consistency in the two stability measurements in both short- and long-run situations.

Despite the change in banking stability and economic growth and oil prices improved diversification, banks in the region are not diversifying during the crisis period and political instability. Therefore, policymakers should improve mechanisms to monitor the crisis and political unrest to avoid the systemic risk that adversely affects the system through macro-financial linkages in the region.

This study uses change dual stability measurements and oil prices to predict MENA region bank diversification. The authors extended the banking literature by estimating the relationship between crisis periods, political and banking stability, oil prices and other institutional indicators of banking diversification. This study uncovers the effect of the global crisis period on banking diversification and the impact of banking stability changes and validates the models through robustness tests.

The purpose of this study is to critically evaluate how conventional and Islamic banks trade off risk, efficiency and financial performance in their business models, to investigate how patterns of risk and efficiency vary between conventional and Islamic banks and to critically evaluate how the profitability of conventional and Islamic banks varies following the financial crisis.

This study uses univariate and multivariate statistical techniques by investigating 12 Islamic banks and 34 conventional banks operating in the Gulf Cooperation Council (GCC) region has been studied over the period 2011–2018.

The results suggest that Islamic and conventional banks differ not in the levels of efficiency, risk and profitability, but rather in how risk and efficiency influence banks’ financial performance. Islamic banks are found to be less influenced by the adverse effects of credit risk, which is consistent with the risk-sharing nature of Islamic financing. However, the results only hold for return on assets (ROA) and return on equity (ROE) while the net interest margin is observed to be negatively influenced by credit risk. Lower cost-income efficiency is also found to boost ROA and ROE of Islamic banks which could be attributed to a larger share of non-interest revenues due to Sharīʿah-compliance.

From a theoretical point of view, this study helps to understand the risk, efficiency and financial performance of Islamic banks in comparison with conventional banks.

The results of this study can serve bank managers, regulators and shareholders. Policymakers should encourage a more risk-sharing structure of Islamic financing as it brings less adverse effects of credit risk and increases income sustainability for Islamic banks. The present study may help bank managers to improve the financial performance of their firms by controlling risk and efficiency. The study results also have implications for shareholders and depositors of Islamic and conventional banks as they should have a predetermined position about the level of credit risk and efficiency in each banking system.

The foremost contribution is that this is one of the few studies to compare risk, efficiency and financial performance of Islamic and conventional banks in the GCC region. By using the latest data, this paper hopes that the findings will be more relevant than previous studies to the current situation of the banking industry in the region.

Islamic finance is an alternative approach of financial intermediation based on risk-sharing and asset-backed operations, which evolved substantially in recent years in academic research raising the need for quantitative studies to address the intellectual development and scientific performance of this field. This study aims to provide quantitative statistics and comprehensive review of the key influential and intellectual structure of Islamic finance literature.

The authors apply the trending and cutting-edge quali-quantitative approach of bibliometric citation analysis. This study reviews 1,940 English studies and review papers published in scientific journals indexed by the Scopus database from 1983 to 2019. RStudio, VOSviewer and Excel’s software are used to analyze the collected data and apply the bibliometric tests.

The results identify the leading academic authors, journals, institutions and countries with relation to Islamic finance. The authors also propose six main research themes in this field, which are as follows: Islamic finance – fundamentals, growth and legitimacy; customer’s attitude and perception toward Islamic finance; accounting and social reporting of Islamic finance; performance and risk management of Islamic finance; Islamic financial markets; and efficiency of Islamic financial institutions. Lastly, the authors identify research gaps in the existing Islamic finance literature and present 24 future research directions.

The data in this study is confined only to the Scopus database of English papers and reviews. It also considers papers directly related to the field of Islamic finance.

To the best of the authors’ knowledge, this paper is one of the first to address the literature of Islamic finance from a bibliometric aspect. The results of this study along with future research questions will help researchers and practitioners to further explore and stand on firm quantitative bases regarding the scientific development of Islamic finance.

India has the biggest number of active users on social media platforms, particularly Twitter. The purpose of this paper is to examine public sentiment on COVID-19 vaccines and COVID Appropriate Behaviour (CAB) by text mining (topic modeling) and network analysis supported by thematic modeling.

A sample dataset of 115,000 tweets from the Twitter platform was used to examine the perception of the COVID-19 vaccination and CAB from January 2021 to August 2021. The research applied a machine-learning algorithm and network analysis to extract hidden and latent patterns in unstructured data to identify the most prevalent themes. The COVID-19 Vaccine Hesitancy Amplification Model was formulated, which included five key topics based on sample big data from social media.

The identified themes are Social Media Adaptivity, Lack of Knowledge Providing Mechanism, Perception of Vaccine Safety Measures, Health Care Infrastructure Capabilities and Fear of Coronavirus (Coronaphobia). The study implication assists communication strategists and stakeholders design effective communication strategies using digital platforms. The study reveals CAB themes as with Mask Wearing Issues and Employment Issues as relevant themes discussed on digital channels.

The themes extracted in the present study provide a roadmap for policy-makers and communication experts to utilize social media platforms for communicating and understanding the perception of preventive measures of vaccination and CAB. As evidenced by the increased engagement on social media platforms during the COVID-19-induced lockdown, digital platforms are indeed valuable from the communication perspective to be proactive in the event of a similar situation. Moreover, significant themes, including social media adaptivity, absence of knowledge-providing mechanism and perception of safety measures of the vaccine, are the critical parameters leading to an amplified effect on vaccine hesitancy.

The COVID-19 Vaccine Hesitancy Amplification Themes (CVHAT) equips stakeholders and government strategists with a preconfigured paradigm to tackle dedicated communication campaigns and assess digital community behavior during health emergencies COVID-19.

The increased acceptance of vaccines and the following of CAB decrease the advocacy of mutation of the virus and promote the healthy being of the people. As CAB has been mentioned as a preventive strategy against the COVID-19 pandemic, the research preposition promotes communication intervention which helps to mitigate future such pandemics. As developing, economies require effective communication strategies for vaccine acceptance and CAB, this study contributes to filling the gap using a digital environment.

Chan et al. (2020) recommended using social media platforms for public knowledge dissemination. The study observed that the value of a communication strategy is increased when communication happens using highly trusted and accessible channels such as Twitter and Facebook. With the preceding context, the present study is a novel approach to contribute toward digital communication strategies related to vaccination and CAB.