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The authors’ conclusions are based on mathematical derivations that are supported by computer simulations and three worked examples in applications of economics and finance. Finally, the authors provide a link to a computer program so that researchers can perform the analyses easily.

Based on a parameter estimation goal, the present work is concerned with determining the minimum sample size researchers should collect so their sample medians can be trusted as good estimates of corresponding population medians. The authors derive two solutions, using a normal approximation and an exact method.

The exact method provides more accurate answers than the normal approximation method. The authors show that the minimum sample size necessary for estimating the median using the exact method is substantially smaller than that using the normal approximation method. Therefore, researchers can use the exact method to enjoy a sample size savings.

In this paper, the a priori procedure is extended for estimating the population median under the skew normal settings. The mathematical derivation and with computer simulations of the exact method by using sample median to estimate the population median is new and a link to a free and user-friendly computer program is provided so researchers can make their own calculations.

The authors derive the necessary mathematics, provide computer simulations, provide links to free and user-friendly computer programs, and analyze real data sets.

Cohen's d, which indexes the difference in means in standard deviation units, is the most popular effect size measure in the social sciences and economics. Not surprisingly, researchers have developed statistical procedures for estimating sample sizes needed to have a desirable probability of rejecting the null hypothesis given assumed values for Cohen's d, or for estimating sample sizes needed to have a desirable probability of obtaining a confidence interval of a specified width. However, for researchers interested in using the sample Cohen's d to estimate the population value, these are insufficient. Therefore, it would be useful to have a procedure for obtaining sample sizes needed to be confident that the sample. Cohen's d to be obtained is close to the population parameter the researcher wishes to estimate, an expansion of the a priori procedure (APP). The authors derive the necessary mathematics, provide computer simulations and links to free and user-friendly computer programs, and analyze real data sets for illustration of our main results.

In this paper, the authors answered the following two questions: The precision question: How close do I want my sample Cohen's d to be to the population value? The confidence question: What probability do I want to have of being within the specified distance?

To the best of the authors’ knowledge, this is the first paper for estimating Cohen's effect size, using the APP method. It is convenient for researchers and practitioners to use the online computing packages.

This paper describes the organic geochemical characteristics and their roles on barium enrichment in the No. 2 Coal from Huanglong Jurassic Coalfield, China. A total of 18 bench samples were taken from Huangling Mine 2. The average content of barium (3701 mg/kg) was about 23 times higher than that of common world coals. Terrestrial higher plants were the main coal-forming parent material. Relying on the parameters of OEP, Pr/Ph and so on, there is little correlation between organic geochemical characteristics and barium enrichment. Therefore, organic material has little influence on the process of coal-forming and the enrichment of barium.

This paper takes Chinese A-share listed companies from 2007 to 2021 as research samples to investigate the influence of supplier concentration on debt maturity structure and its mechanism. It further analyzes whether the relationship between the two is different in the case of different monetary policies, collateral assets, and total debt. The research conclusion is of practical significance for enterprises to construct a balanced debt maturity structure and prevent financial risks.

This paper adopts the empirical research method. The data came from the CSMAR database, which eliminated ST and *ST and companies with missing data, resulting in a sample of 20,328. Stata16 was used for statistical analysis.

There is an inverted U-shaped relationship between supplier concentration and debt maturity structure, and market position and trade credit play an intermediary role. In the case of tight monetary policy, fewer collateral assets, and higher total debt, the inverse U-shaped relationship is more significant.

This paper examines the relationship between supplier concentration and debt maturity structure from a non-linear perspective for the first time, providing theoretical support for enterprises to form a reasonable debt structure, and deepening the theoretical cognition of the relationship between supplier concentration and corporate debt maturity structure.

This paper aims to investigate the law and logic mechanism of management control matching pattern and company strategy aggressiveness under different strategies by textual analysis, based on the empirical data of Chinese A-share listed companies during the period from 2010 to 2018. Additional analyses further investigate the moderating effect of environmental uncertainty and R&D intensity on the relationship between management control matching type and strategy aggressiveness. The conclusion can help relevant departments to develop management control theory and method system with Chinese characteristics and provide theoretical reference for the matching mode of dual control.

This paper uses the text analysis method. The main explanatory variables are analyzed using the computer SQL Server database software through the relevant text of the board of directors report in the company annual report. Other financial data came from the CSMAR database, excluding ST and PT and companies with missing data, and 16,902 samples were finally obtained. This paper conducted statistical analysis through Stata12.

This paper shows that the matching pattern between formal and informal control is divided into three types. They have different impacts on strategy aggressiveness. Specifically, consistent matching type II significantly positively influences the aggressiveness of offensive strategy. Consistent matching type I significantly positively influences the aggressiveness of defensive strategy. Complementary matching type I significantly positively influences the aggressiveness of analytical strategy. Additional analyses find that compared with non-high-tech companies, high-tech companies have more significant influence on the relationship between management control matching pattern and company strategic aggressiveness. And compared with other two “strategy-control” matching patterns, both environmental uncertainty and product innovation have more significant influence on the relationship between consistent matching II and offensive strategy aggressiveness.

To the best of the authors’ knowledge, this paper divides the formal and informal control matching patterns of management control into three categories for the first time. It examines the relationship between the formal and informal control matching of management accounting and the degree of strategy aggressiveness. The conclusion provides new empirical evidence to promote the effective implementation of development strategies for companies. It can help relevant departments to develop management control theory and method systems with Chinese characteristics and provide theoretical references for the matching mode of dual control.

The purpose of this paper is to perform an investigative analysis of the distribution of agricultural growth in China and the evolution of the decision mechanism.

The kernel density estimation method was used to investigate the distribution of agricultural growth in China using 1988‐2008 panel data of the 29 provinces on the mainland. A nonparametric income distribution approach was employed to decompose China's agricultural output growth into farmland accumulation, capital deepening, labor‐scale change, technical change, and efficiency change based on stochastic frontier function. A further investigation of the evolution of the decision mechanism for agricultural growth was then performed using counterfactual analysis.

The results of this analysis indicate that: from 1996, the distribution of agricultural output per worker evolved from a unimodal into a bimodal distribution; technical change is the primary impetus to distribution shift; and capital deepening and efficiency change play a dominant role in the deformation of the distribution of agricultural output per worker from a unimodal to a bimodal distribution.

The paper is an original work and its methodology makes a meaningful contribution to understanding China's agricultural growth. That is, the use of income distribution analysis method to analyze agricultural growth does not only allow a more in‐depth understanding of the gap between regional agricultural growth rates, but also makes up for the existing lack of convergence in agricultural growth in China.

This paper aims to propose and demonstrate a novel surface plasmon resonance (SPR)-sensing approach by using the fundamental mode beam based on a graded index multimode fiber (GIF). The proposed SPR sensor has high sensitivity and controllable working dynamic range, which expects to solve the two bottlenecks of fiber SPR sensor, including low sensitivity and the difficulty in multichannel detection.

The low-order mode of the GIF to SPR sense, which keeps the sensitivity advantage of the single-mode fiber SPR sensor, is used. By using this new SPR sensor, the effect of light incident angle and gold film thickness on working dynamic range was studied. According to the study results, the smaller is the incident angle, the larger is the SPR working dynamic range and the longer is the resonance wavelength with a fixed gold film thickness; the larger is the gold film thickness, the longer is the resonance wavelength with a fixed grinding angle. After the parameter optimization, the sensitivity of these two parameter-adjusting methods reach 4,442 and 3031 nm/RIU.

When the grinding angle of the GIF increases, the dynamic range of the resonance wavelength increases and has a redshift, sensitivity increases, and the resonance valley becomes more unobvious with a fixed gold film thickness. Similarly, when gold film thickness increases, the dynamic range of the resonance wavelength increases and has a redshift, sensitivity increases, and the resonance valley becomes more unobvious with a fixed grinding angle. These adjusting performance aforementioned lay the foundation for solving of the fiber-based SPR multichannel detection and increasing of the fiber-based SPR sensor sensitivity, which has a good application value.

This study aimed to adapt existing text-mining techniques and propose a novel topic recognition approach for textual patient reviews.

The authors first transformed multilabel samples for adapting model training forms. Then, an improved method was proposed based on dynamic mixed sampling and transfer learning to improve the learning problem caused by imbalanced samples. Specifically, the training of our model was based on the framework of a convolutional neural network and self-trained Word2Vector on large-scale corpora.

Compared with the SVM and other CNN-based models, the CNN+ DMS + TL model proposed in this study has made significant improvement in F1 score.

The improved methods based on dynamic mixed sampling and transfer learning can adequately manage the learning problem caused by the skewed distribution of samples and achieve the effective and automatic topic recognition of textual patient reviews.

The peer-review history for this article is available at: https://publons.com/publon/10.1108/OIR-01-2021-0059.