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The main obstacle of ionic thermo‐electrochemical cells (TECs) in continuous power supply lies in a low heat‐to‐electricity energy conversion efficiency because most TECs work in thermodiffusion mode in which the ions are confined in a liquid/electrolyte media. The introduction of the redox couple onto the electrode surface may overcome the obstacle by resolving the low mass transport rate of ions caused by the redox process occurring near but not on the electrode surface. Herein, the authors demonstrate enhancement of TECs by integrating the redox couple directly onto the electrode surface to maximize the mass transport efficiency. A discontinuous interfacial modification strategy is developed by using a carbon cloth/iron (II/III) phytate as the symmetric electrodes. The gelled electrolyte consisting of a polyacrylamide matrix and phytic acid is shown to promote selective ion diffusion. A synergistic combination consisting of the thermodiffusion effect and redox reactions on the electrode is established in a pre‐treated layout. Such TEC affords a high output voltage of 0.4 V, an excellent instantaneous output power density (20.26 mW m‐2 K‐2) and a record‐high 2 h output energy density (2451 J m‐2) under TH = 30 °C with TC = 15 °C, with an ultrahigh Carnot‐relative efficiency of 1.12%. The continuous output power and Carnot‐relative efficiency of ionic thermo‐electrochemical cells (TECs) can be improved by the utilization of electrodes with redox couples. The introduction of symmetrical electrodes or asymmetric electrodes can demonstrate the universality of electrodes with redox couples for TECs. The application of Grotthuss principle can further improve the performance of TECs.

This research aims to identify the economic and national feasibility of some agricultural activities benefiting from the agricultural initiative's lending funds, as well as to show the impact of the agricultural initiative on these projects in terms of raising social profitability, in the light of the results of the national evaluation criteria addressed in the research. All the studied projects have achieved a net added value at the level of the national economy. The dairy cattle breeding project recorded the lowest net added value of about 914 million dinars (about 745 thousand dollars), and poultry projects achieved the highest added value of about 5 billion ID for the projects of table eggs production 4.9 billion ID for broiler projects, while the relative change in the standard showed that and the broiler production project is one of the most benefited from loan subsidies as the rate of change reached about 25%, while the project of broiler production and poultry hatchery and the project of raising milk cow have negative social return .The initiative's subsidies have increased the social rate of return for these projects to around 24%, 20.5%, and 20%. Agricultural loans from the agricultural initiative raise the national profitability of agricultural projects, which would contribute to the process of agricultural development in Iraq.

This paper compares the minimum divergence estimator of Basu et al. (1998) to a competing minimum divergence estimator which turns out to be equivalent to a method proposed from a different perspective by Windham (1995). Both methods can be applied for any parametric model and contain maximum likelihood as a special case. Efficiencies are compared under model conditions, and robustness properties are studied. Overall the two methods are found to perform quite similarly. Some relatively small advantages of the former method over the latter are identified.

This article introduces a robust hypothesis testing procedure: the Lq-likelihood-ratio-type test (LqRT). By deriving the asymptotic distribution of the test statistic, we demonstrate its robustness analytically and numerically, and investigate the properties of its influence function and breakdown point. A proposed method to select the tuning parameter q offers a good efficiency/robustness trade-off compared with the traditional likelihood ratio test (LRT) and other robust tests. Simulation and a real data analysis provide further evidence of the advantages of the proposed LqRT method. In particular, for the special case of testing the location parameter in the presence of gross error contamination, the LqRT dominates the Wilcoxon-Mann-Whitney test and the sign test at various levels of contamination.

This study explores the efficiency of intellectual capital (ICE) and working capital management (WCME) in the GCC industrial sector and its potential impact on firm performance. The data were gathered from Standard & Poor’s database from 2015 to 2019. This study uses data envelopment analysis (DEA), regression analysis, and robustness tests to accomplish its aims. The results indicate that most firms do not employ their intellectual and working capital investments well and need improvement actions to achieve the best practices. The regression model results reveal that ICE and WCME significantly and positively influence firms’ performance. The results of this study support the resource-based, trade-off, and pecking order theories. The study findings have important implications for many stakeholders; for example, they would be helpful for firm decision-makers in managing their investments in intellectual and working capital to achieve the best practices and improve a firm's performance. In addition, the findings would be helpful for financiers, because high-performance firms are likely to have more reasonable valuations that facilitate debt financing. Moreover, the findings have noteworthy implications for trading procedures as investors aspire to attractive economic returns for their investments in corporations that pasture ICE and WCME issues. Additionally, these findings have important implications for employee job satisfaction and retention by improving IC management.

This work is concerned with testing the population mean vector of nonnormal high-dimensional multivariate data. Several tests for high-dimensional mean vector, based on modifying the classical Hotelling T ² test, have been proposed in the literature. Despite their usefulness, they tend to have unsatisfactory power performance for heavy-tailed multivariate data, which frequently arise in genomics and quantitative finance. This article proposes a novel high-dimensional nonparametric test for the population mean vector for a general class of multivariate distributions. With the aid of new tools in modern probability theory, we proved that the limiting null distribution of the proposed test is normal under mild conditions when p is substantially larger than n . We further study the local power of the proposed test and compare its relative efficiency with a modified Hotelling T ² test for high-dimensional data. An interesting finding is that the newly proposed test can have even more substantial power gain with large p than the traditional nonparametric multivariate test does with finite fixed p . We study the finite sample performance of the proposed test via Monte Carlo simulations. We further illustrate its application by an empirical analysis of a genomics dataset. Supplementary materials for this article are available online.

PurposeUsing data on 51 firms traded in the Egyptian Exchange from 2014 to 2016, this paper aimed to assess the efficiency of corporate governance (CG) and intellectual capital (IC) practices and to explore their influence on the probability of a firm's financial distress.Design/methodology/approachThe relative efficiency of CG and IC practices has been measured under the Malmquist data envelopment analysis model. A modified Z-score model was applied to assess firms' financial distress.FindingsThe Wilcoxon signed-rank test revealed almost insignificant evidence regarding the improvement of CG and IC efficiency over the study period. The efficiency score of CG practices had no impact on the likelihood of financial distress. However, the efficiency score of IC negatively affected the probability of financial distress.Research limitations/implicationsThe integration of data envelopment analysis with Tobit regression was required for identifying the significant drivers of efficient CG and IC.Practical implicationsThe findings shed light on the role of CG and IC in alleviating the degree of financial distress in Egypt as an emerging market, especially the need to raise firms' compliance with the Egyptian CG code from a voluntary to mandatory status.Originality/valueThis study, using Malmquist data envelopment analysis, is among the first attempts to assess the relative efficiency of CG and IC practices and their effects on financial distress.

In this paper the relative efficiency of the forest sector of 28 EU/EFTA countries during the period 2010–2015 is assessed using Data Envelopment Analysis (DEA). Three non-discretionary inputs (persons employed, forest available for wood supply and initial growing stock) are considered. The outputs are roundwood production, gross value added and final growing stock. The proposed DEA model not only computes efficiency scores but also improvement targets. The countries with the lowest efficiency scores during the period under study are Greece, Bulgaria and Italy. In the second stage, a fractional regression model is fitted and the factors that have an influence on the estimated efficiency are identified. The factors that have an influence are GDP and belonging to the NORTH Europe and CENTRAL-WEST Europe regions. Quantitative estimates of the partial effects of these factors are provided. The results can contribute in providing guidance towards the best practice in roundwood production.

This paper offers a novel approach to formulate efficient ratio estimator of the population variance using a transformed auxiliary variable. The impact of transformation on auxiliary information has also been discussed. It is observed that incorporating a transformed auxiliary variable result in a high gain in efficiency. Theoretical properties of the newly developed estimators have been derived. The empirical and simulation studies show that the suggested estimators outperformed the existing estimators.

We use a novel three-stage network data envelopment analysis (DEA) model (based on production, intermediation, and revenue generation operations) with bootstrapping to evaluate the performance of 14 of the largest Canadian credit unions for the period 2007–2017 and the impact of various events on this performance. For each analysis, we contrast the results of the network DEA with those of a black box DEA. We show that the former provides more insightful information regarding the sources of the inefficiencies. We first found that while overall, the credit unions showed high-efficiency ratios, there is room for improvement, especially for the production sub-process. Moreover, the efficiency of individual credit unions is not consistent across the three different stages. Through the years 2007–2017, the credit union system exhibits a relatively sharp decline in its efficiency, mainly due to managerial issues at the revenue generation stage. Our analyses show that the various stages of Canadian credit union operations have been affected by the 2007–2009 financial crisis, the low policy interest rates that occurred in the following years, and the fact that in Canada, the federal government has eliminated the discount on the federal tax rate. The credit unions can improve their performance at the different stages by exploring Fintech Solutions to reduce their operating costs, seeking a better mix of loans and securities investments, and improving their interest and saving rate settings.