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This study aims to investigate the effects of ball–material ratio on the properties of mixed powders and Cu-Bi self-lubricating alloy materials.

Cu-Bi mixed powder was ball milled at different ball–material ratios, and the preparation of Cu-Bi alloy materials was achieved through powder metallurgy technology. Scanning electron microscopy, X-ray diffraction and Raman spectroscopy were conducted to study the microstructure and phase composition of the mixed powder. The apparent density and flow characteristics of mixed powders were investigated using a Hall flowmeter. Tests on the crushing strength, impact toughness and tribological properties of self-lubricating alloy materials were conducted using a universal electronic testing machine, 300 J pendulum impact testing machine and M200 ring-block tribometer, respectively.

With the increase in ball–material ratio, the spherical copper matrix particles in the mixed powder became lamellar, the mechanical properties of the material gradually reduced, the friction coefficient of the material first decreased and then stabilized and the wear rate decreased initially and then increased. The increase in the ball–material ratio resulted in the fine network distribution of the Bi phase in the copper alloy matrix, which benefitted its enrichment on the worn surface for the formation a lubricating film and improvement of the material’s tribological performance. However, a large ball–material ratio can excessively weaken the mechanical properties of the material and reduce its wear resistance.

The effects of ball–material ratio on Cu-Bi mixed powder and material properties were clarified. This work provides a reference for the mechanical alloying process and its engineering applications.

Microribbon with meander type based on giant magnetoimpedance (GMI) effect has become a research hot spot due to their higher sensitivity and spatial resolution. The purpose of this paper is to further optimize the line spacing to improve the performance of meanders for sensor application.

The model of GMI effect of microribbon with meander type is established. The effect of line spacing (Ls) on GMI behavior in meanders is analyzed systematically.

Comparison of theory and experiment indicates that decreasing the line spacing increases the negative mutual inductance and a consequent increase in the GMI effect. The maximum value of the GMI ratio increases from 69% to 91.8% (simulation results) and 16.9% to 51.4% (experimental results) when the line spacing is reduced from 400 to 50 µm. The contribution of line spacing versus line width to the GMI ratio of microribbon with meander type was contrasted. This behavior of the GMI ratio is dominated by the overall negative contribution of the mutual inductance.

This paper explores the effect of line spacing on the GMI ratio of meander type by comparing the simulation results with the experimental results. The superior line spacing is found in the identical sensing area. The findings will contribute to the design of high-performance micropatterned ribbon with meander-type GMI sensors and the establishment of a ribbon-based magnetic-sensitive biosensing system.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.

The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.

The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.

The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.

The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.

The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.

The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.

This paper aims to investigate the impact of corporate dividend policy on the capital structure in the Korean stock market. To distinctly discern the voluntariness of changes in corporate dividend policy, we analyze companies that, following a substantial increase, do not reduce dividends for the subsequent two years or, after a significant decrease, do not raise dividends for the following two years. Our empirical findings indicate that companies that increase dividends experience a significant decrease in both book and market leverage, even after controlling for variables such as target leverage ratios. This result suggests that a large increase in dividends can effectively reduce information asymmetry, leading to a lower cost of equity. On the contrary, after a decrease in dividends, both book leverage and market leverage significantly increase, revealing a symmetric relationship between dividend policy and capital structure. In conclusion, large dividend increases in Korean companies not only reduce information asymmetry but also lower the cost of equity capital, resulting in observable changes in the leverage ratio.

Using the next-day and next-week returns of stocks in the Korean market, we examine the association of option volume ratios – i.e. the option-to-stock (O/S) ratio, which is the total volume of put options and call options scaled by total underlying equity volume, and the put-call (P/C) ratio, which is the put volume scaled by total put and call volume – with future returns. We find that O/S ratios are positively related to future returns, but P/C ratios have no significant association with returns. We calculate individual, institutional, and foreign investors’ option ratios to determine which ratios are significantly related to future returns and find that, for all investors, higher O/S ratios predict higher future returns. The predictability of P/C depends on the investors: institutional and individual investors’ P/C ratios are not related to returns, but foreign P/C predicts negative next-day returns. For net-buying O/S ratios, institutional net-buying put-to-stock ratios consistently predict negative future returns. Institutions’ buying and selling put ratios also predict returns. In short, institutional put-to-share ratios predict future returns when we use various option ratios, but individual option ratios do not.

The challenge of predicting changes in aggregate income and stock prices is one that has occupied the research agendas of economists. This paper aims to use the consumption–income ratio and the dividend–price ratio to predict future income and stock prices.

To examine the stability of the consumption–income ratio and the dividend–price ratio, the authors run a two-variable, two-lag reduced-form VAR in the vein of Cochrane (1994), using a lag of each respective ratio as exogenous to the VAR. Additionally, the authors estimate an AR(4) model for income and prices.

The consumption–income ratio and the dividend–price ratio remain key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. The dividend–price ratio does not significantly predict future price growth. Consumption and dividend shocks have lasting impacts on income and prices.

The consumption–income ratio and the dividend–price ratio are still key to understanding future movements in income and stock prices. The consumption–income ratio significantly predicts future income in the USA, and aggregate income is easier to predict than consumption in the VAR model. However, the dividend–price ratio does not significantly predict future price growth, a change from previous research from the 1990s, despite the increasing complexity of stock markets. Consumption and dividend shocks have lasting impacts on income and prices and appear to be significant drivers in both the short- and long-run variance in income and prices.

Why Ratios? The need for ratios rests upon the fact that absolute figures by themselves tell one very little about the performance of an organisation. The fact that a company made £1 million pre‐tax profit in its last financial year is no indication of its performance. If it had to deploy £1,000 millions of funds to achieve that profit then its performance was abysmally low. If it only employed £2 millions its performance was very good. In one sense then ratio analysis is concerned with expressing relationships between inputs and outputs, such as the capital required to support an activity and the profit earned from that activity; the sales achieved per square foot of sales space occupied; the cost per ton‐mile of delivering goods; and the way in which these different aspects relate to each other and to overall performance. In another sense they are concerned with relationships between aspects of a business which are crucial for its success, e.g. the relationship between short‐term assets and short term liabilities because it reflects the ability of the business to meet its obligations to creditors.

The application of factor analysis to the area of financial ratio analysis was pioneered by Pinches, Mingo, and Caruthers (1973) in a study of U.S. industrial firms. During the last two decades numerous studies have applied the technique as a means of eliminating redundancy among financial ratios and/or reducing the number of ratios selected as a basis for further investigation to a limited but crucial subset. It is observed that all studies reported were on the manufacturing and retailing sectors. The international commercial airline sector was chosen as the subject of the present research in an attempt to study the factor groupings in a sector whose financial characteristics differ from manufacturing or retailing. Results show that factor categorization reflects the sector's financial characteristics. The study also draws conclusions on some observed differences between the empirical and theoretical ratio classification observed in the literature. The study lends support to the conclusion that factor analysis provides a useful means by which to develop and test the theoretical structure and grouping of financial ratios.

This paper seeks to model and evaluate the comparative operating efficiency of banks using a non‐parametric methodology known as the data envelopment analysis (DEA). The paper adopts a modified version of DEA in which no inputs are specified. The only variables considered are the financial ratios. The results obtained suggest that the majority of banks investigated are fairly inefficient over the period 1991‐94. In addition to calculating efficiency scores for all banks in the sample, the study results revealed the composite reference set and their shadow prices, major determinants of banks’ relative performance, and the target financial ratios.