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Blockchain technology, a key feature of the fourth industrial revolution, is receiving widespread attention and exploration around the world. Taking the coronavirus pandemic as an example, the purpose of this study to examine the application of blockchain technology from the perspective of epidemic prevention and control.

Exploring multiple case studies in the Chinese context at various stages of deployment, this study documents a framework about how some of the major challenges associated with COVID-19 can be alleviated by leveraging blockchain technology.

The case studies and framework presented herein show that utilization of blockchain acts as an enabler to facilitate the containment of several COVID-19 challenges. These challenges include the following: complications associated with medical data sharing; breaches of patients' data privacy; absence of real-time monitoring tools; counterfeit medical products and non-credible suppliers; fallacious insurance claims; overly long insurance claim processes; misappropriations of funds; and misinformation, rumors and fake news.

Blockchain is ushering in a new era of innovation that will lay the foundation for a new paradigm in health care. As there are currently insufficient studies pertaining to real-life case studies of blockchain and COVID-19 interaction, this study adds to the literature on the role of blockchain technology in epidemic control and prevention.

The purpose of this paper is to examine pro-poor urban asset adaptation to climate variability and change. It constructs a conceptual framework that explores the appropriate asset adaptation strategies for extreme poor households as well as the process of supporting these households and groups in accumulating these assets.

Qualitative data are obtained from life histories, key informant interviews (KIIs) and focus-group discussions (FGDs). These data are collected, coded and themed.

This research identifies that households among the urban extreme poor do their best to adapt to perceived climate changes; however, in the absence of savings, and access to credit and insurance, they are forced to adopt adverse coping strategies. Individual adaptation practices yield minimal results and are short lived and even harmful because the urban extreme poor are excluded from formal policies and institutions as they lack formal rights and entitlements. For the poorest, the process of facilitating and maintaining patron–client relationships is a central coping strategy. Social policy approaches are found to be effective in facilitating asset adaptation for the urban extreme poor because they contribute to greater resilience to climate change.

This study analyses the empirical evidence through the lens of a pro-poor asset-adaptation framework. It shows that the asset-transfer approach is an effective in building household-adaptation strategies. Equally important is the capacity to participate in and influence the institutions from which these people have previously been excluded.

The purpose of this study is to evaluate the effect of blockchain technology on firms’ operational efficiency in the context of China.

The authors use panel data for blockchain-based companies listed on stock exchanges in China (Shanghai, Shenzhen and Hong Kong) between 2014 and 2018. The operational efficiency of firms that deploy blockchain technology is evaluated using ordinary least squares and system generalized method of moments estimation.

Results suggest that companies’ current year performance exceeds the previous year performance because of blockchain deployment in firms’ operations. Firms with higher financial leverage and return on assets reap more benefits from blockchain. Larger and older firms benefit less from blockchain implementation. Stochastic frontier estimation suggests that, on average, firms attain a 57.76 per cent technical efficiency level, or, put differently, they operate 42.24 per cent below their maximum level of potential output.

Blockchain can benefit firms in terms of consensus, security and trust, spurring the evolution of a new form of organizational dynamics. This study explores the theory of transactional cost analysis under blockchain technology. In addition, this study hypothesizes and empirically demonstrates the significant impacts of blockchain technology on corporations’ operational efficiency, using audited, externally reported financial data. Industry professionals can reap benefits from this research by noticing the magnitude of changes in firms’ financial parameters attributable to blockchain adoption.

Zakat, one of the fundamental pillars of Islam, holds the potential to significantly contribute to fiscal consolidation, particularly in developing nations. However, the national-level potential of Zakat often remains unexplored. This study aims to explore the potential of national-level Zakat and the opportunity to integrate it into the fiscal framework.

This study estimates Zakat’s potential on national financial and economic components. The components include bank deposits, shares and securities, pensions (provident fund), industrial production and trade services, mining resources, Ushr on agro-crops and forestry, Ushr on livestock, Ushr on fishery, gross domestic product (GDP), national budget and national revenue. The study gathers data, ranging from FY2000 to FY2018, on national economic sectors from reliable secondary sources. The net value (NV) of each indicator is calculated as NV = TV − LA, where NV is the wage-adjusted net value after deducting the living adjustment (LA) value from the sectoral total. The proposed LA value, approximately 20%, is suggested to be deducted from the total sectoral value of each sector (excluding specific industries with preadjusted wages), equating to the Nisab value.

It is estimated that the aggregate potential of Zakat in Bangladesh was US$9,749m in FY2018, compared to US$809m in FY2000, revealing the value is 3.77% of GDP and 21% of the national fiscal budget. In FY2018, the service sector was the largest contributor (30%), followed by bank deposits (23%). Pension funds made minimal contributions, whereas shares and bonds, as well as the manufacturing sector, each made a 10% contribution to the estimated Zakat potential. Zakat on agriculture output accounted for 15% of the total. The aggregate potential Zakat in FY2018 was 12% higher than that in FY2000.

The paper highlights a novel contribution through its nuanced analysis of sector-specific Zakat on macrolevel data and its implications within the fiscal framework. The results suggest that Zakat has substantial potential to impact fiscal dynamics, providing valuable insights for policymakers and stakeholders to recognize the national-level Zakat for development plans such as the five-year plan. The study suggests piloting a central and independent national body to study the feasibility of national-level Zakat collection and its utilization in the fiscal budget. It will help the government reduce the burden of external debt and deficit budget and, instead, will promote revenue collection in collaboration with the National Board of Revenue.

This paper briefly introduces the concept of model selection, reviews recent development in the area of econometric analysis of model selection and addresses some of the crucial issues that are being faced by researchers in their routine research problems. The paper emphasizes on the importance of model selection, particularly the information criteria and penalty functions based model selection procedures which are useful for economists and finance researchers.

The main purpose of this paper is to select the most suitable production model for measuring the production process of some major manufacturing industries in Oman.

This empirical paper looks into an analytical justification to use Cobb‐Douglas (C‐D) production model in order to estimate and test the coefficients of the production inputs for each of the selected manufacturing industries using annual industrial statistical data over the period 1994 through 2007 published by Ministry of Commerce and Industry, Sultanate of Oman.

The results of the paper indicate that for most of the selected industries the C‐D function fits the data very well in terms of labor and capital elasticity, return to scale measurements, standard errors, economy of the industries, high value of R² and reasonably good Durbin‐Watson statistics. The estimated results suggest that the manufacturing industries of Oman generally seem to indicate the case of increasing return to scale. Of the nine industries, seven exhibit increasing return to scale and only the rest two show decreasing return to scale. The paper finds no industry with constant return to scale.

The paper could not consider a good number of manufacturing industries and a long period of time series data in the study because of lack of data availability.

Recently, businessmen as well as industrialists are very much concerned about the theory of firm in order to make correct decisions regarding what items, how much and how to produce them. All these decisions are directly related with the cost considerations and market situations where the firm is to be operated. In this regard, this paper should be helpful in suggesting the most suitable functional form of production process for the major manufacturing industries of developing countries like Oman.

The paper shows originality in substance and makes a unique contribution to the literature on industrial economics in Oman.

The focus of this paper is to develop an econometric model that measures the changes in GDP for the OIC states.

This paper focuses on the development of an econometric model which measures the changes of gross domestic product (GDP) for the members of Organization of Islamic Conference (OIC) countries. In particular, we analyze the growth of GDP in the OIC countries and their implications for expanded marketing opportunities for goods and services. We also discuss some challenges the marketers may face in future if the formation of OIC countries block become an economic identity and set up some sort of confederation.

The problem of multi‐collinearity needs to be solved if the model is not going to change.

The recommended solution is to acquire more data on the countries that were absent from the original sample. This may be hard to obtain due to some countries not having a process for collecting accurate statistics.

Recently, Bhatti and Khan considered various functional forms to see their suitability in terms of efficiency and competency in assessing production process based on agricultural data. This paper reviews some models recently used in the literature and selects the most suitable one for measuring the production process of 21 major manufacturing industries in Bangladesh. In particular, the paper estimates and tests the coefficients of the production inputs for each of the selected manufacturing industries using Bangladesh Bureau of Statistics annual data over the period 1982‐1983 through 1991‐1992.

The purpose of this paper is to present an analytical justification from statistical view point about why Islam has strictly forbidden interest for the humankind.

It is a theoretical paper that looks into analytical views of justification in order to investigate the motivation of prohibiting interest.

The results of the paper suggest that interest has a great negative impact on the society, economy and morality of human beings. Analysis found some solid reasons which proved that interest has been really an evil system for the humankind and society as a whole for all times in the history of civilizations. On the other hand, from the statistical information given in the paper it was found that interest‐free financial institutions have been very successful in terms of their deposit, investment, foreign exchange business, financial stability and popularity as compared to the interest based financial institutions.

The impact of interest‐free financial institutions in development financing and in establishing sustainability of a welfare community remains a potential problem due to our shortage and/or lack of proper knowledge.

It is, therefore, very important to be aware of the exact stance of Islam on interest first. Then more extensive networking and complementary relations are needed among the financial and socio‐economic development goals in accordance with the tenets of the Islamic Shariah.

The paper shows its originality in substance and makes a unique contribution to the literature on systems and ethics.

The purpose of this paper is to generate three types of forecasts, namely, historical, ex‐post and ex‐ante, using the world famous Box‐Jenkins time series models for motor, mash and mung prices in Bangladesh.

The models on the basis of which these forecasts have been computed were selected by six important information criteria such as Akaike's Information Criterion (AIC), Schwarz's Bayesian Information Criterion (BIC), Theil's R², Theil's R², SE(σ) and Mean Absolute Percent Errors (MAPEs). In order to examine the forecasting performance of the selected models, three types of forecast errors were estimated, i.e. root mean square percent errors (RMSPEs), mean percent forecast errors (MPFEs) and Theil's inequality coefficients (TICs).

The estimates suggest that in most cases the forecasting performances of the models in question are quite satisfactory.

The models developed in this paper can be used for policy purposes as far as price forecasts of the commodities are concerned.