Pub Date : 2024-04-02DOI: 10.11648/j.sjams.20241202.11
Naveenganesh Muralidharan, Thatsinee Johnson, Leyla Rose, Mark Davis
The Food and Drug Administration’s 2011 Process Validation Guidance and International Council for Harmonization Quality Guidelines recommend continued process verification (CPV) as a mandatory requirement for pharmaceutical, biopharmaceutical, and other regulated industries. As a part of product life cycle management, after process characterization in stage 1 and process qualification and validation in stage-2, CPV is performed as stage-3 validation during commercial manufacturing. CPV ensures that the process continues to remain within a validated state. CPV requires the collection and analysis of data related to critical quality attributes, critical material attributes, and critical process parameters on a minimum basis. Data is then used to elucidate process control regarding the capability to meet predefined specifications and stability via statistical process control (SPC) tools. In SPC, the control charts and Nelson rules are commonly used throughout the industry to monitor and trend data to ensure that a process remains in control. However, basic control charts are susceptible to false alarms and nuisance alarms. Therefore, it is imperative to understand the assumptions behind control charts and the inherent false alarm rates for different Nelson rules. In this article, the authors have detailed the assumptions behind the usage of control charts, the rate of false alarms for different Nelson rules, the impact of skewness and kurtosis of a data distribution on the false alarm rate, and methods for optimizing control chart design by reducing false alarm rates and nuisance signals.
{"title":"CPV Monitoring - Optimization of Control Chart Design by Reducing the False Alarm Rate and Nuisance Signal","authors":"Naveenganesh Muralidharan, Thatsinee Johnson, Leyla Rose, Mark Davis","doi":"10.11648/j.sjams.20241202.11","DOIUrl":"https://doi.org/10.11648/j.sjams.20241202.11","url":null,"abstract":"The Food and Drug Administration’s 2011 Process Validation Guidance and International Council for Harmonization Quality Guidelines recommend continued process verification (CPV) as a mandatory requirement for pharmaceutical, biopharmaceutical, and other regulated industries. As a part of product life cycle management, after process characterization in stage 1 and process qualification and validation in stage-2, CPV is performed as stage-3 validation during commercial manufacturing. CPV ensures that the process continues to remain within a validated state. CPV requires the collection and analysis of data related to critical quality attributes, critical material attributes, and critical process parameters on a minimum basis. Data is then used to elucidate process control regarding the capability to meet predefined specifications and stability via statistical process control (SPC) tools. In SPC, the control charts and Nelson rules are commonly used throughout the industry to monitor and trend data to ensure that a process remains in control. However, basic control charts are susceptible to false alarms and nuisance alarms. Therefore, it is imperative to understand the assumptions behind control charts and the inherent false alarm rates for different Nelson rules. In this article, the authors have detailed the assumptions behind the usage of control charts, the rate of false alarms for different Nelson rules, the impact of skewness and kurtosis of a data distribution on the false alarm rate, and methods for optimizing control chart design by reducing false alarm rates and nuisance signals.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"82 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140755392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-02DOI: 10.11648/j.sjams.20241201.12
Rukia Fwamba, Isaac Chepkwony, W. Fwamba
Partial Differential Equations are used in smoothening of images. Under partial differential equations an image is termed as a function; f(x, y), XÎR2. The pixel flux is referred to as an edge stopping function since it ensures that diffusion occurs within the image region but zero at the boundaries; ux(0, y, t) = ux(p, y, t) = uy(x, 0, t) = uy(x, q, t). Nonlinear PDEs tend to adjust the quality of the image, thus giving images desirable outlooks. In the digital world there is need for images to be smoothened for broadcast purposes, medical display of internal organs i.e MRI (Magnetic Resonance Imaging), study of the galaxy, CCTV (Closed Circuit Television) among others. This model inputs optimization in the smoothening of images. The solutions of the diffusion equations were obtained using iterative algorithms i.e. Alternating Direction Implicit (ADI) method, Two-point Explicit Group Successive Over-Relaxation (2-EGSOR) and a successive implementation of these two approaches. These schemes were executed in MATLAB (Matrix Laboratory) subject to an initial condition of a noisy images characterized by pepper noise, Gaussian noise, Brownian noise, Poisson noise etc. As the algorithms were implemented in MATLAB, the smoothing effect reduced at places with possibilities of being boundaries, the parameters Cv (pixel flux), Cf (coefficient of the forcing term), b (the threshold parameter) alongside time t were estimated through optimization. Parameter b maintained the highest value, while Cv exhibited the lowest value implying that diffusion of pixels within the various images i.e. CCTV, MRI & Galaxy was limited to enhance smoothening. On the other hand the threshold parameter (b) took an escalated value across the images translating to a high level of the force responsible for smoothening.
偏微分方程用于平滑图像。在偏微分方程中，图像被称为函数；f(x, y), XÎR2。像素通量被称为边缘停止函数，因为它确保扩散发生在图像区域内，而在边界为零；ux(0, y, t) = ux(p, y, t) = uy(x, 0, t) = uy(x, q, t)。非线性 PDE 往往会调整图像的质量，从而使图像呈现出理想的外观。在数字世界中，需要对图像进行平滑处理，以用于广播目的、内部器官的医学显示（即 MRI（磁共振成像））、星系研究、闭路电视（CCTV）等。该模型为图像平滑化提供了优化方案。利用迭代算法，即交替方向隐含法（ADI）、两点显式组连续超松弛法（2-EGSOR）以及这两种方法的连续实施，获得了扩散方程的解。这些方案是在 MATLAB（矩阵实验室）中执行的，初始条件是以胡椒噪声、高斯噪声、布朗噪声、泊松噪声等为特征的噪声图像。由于算法在 MATLAB 中执行，平滑效果在有可能成为边界的地方有所降低，参数 Cv（像素通量）、Cf（强制项系数）、b（阈值参数）和时间 t 都是通过优化估算出来的。参数 b 保持最高值，而 Cv 显示最低值，这意味着 CCTV、MRI 和 Galaxy 等不同图像中像素的扩散受到限制，从而增强了平滑化效果。另一方面，阈值参数（b）在所有图像中的值都在上升，这意味着平滑化的作用力很大。
{"title":"Optimization of the Non-Linear Diffussion Equations","authors":"Rukia Fwamba, Isaac Chepkwony, W. Fwamba","doi":"10.11648/j.sjams.20241201.12","DOIUrl":"https://doi.org/10.11648/j.sjams.20241201.12","url":null,"abstract":"Partial Differential Equations are used in smoothening of images. Under partial differential equations an image is termed as a function; f(x, y), XÎR<sup>2</sup>. The pixel flux is referred to as an edge stopping function since it ensures that diffusion occurs within the image region but zero at the boundaries; u<sub>x</sub>(0, y, t) = u<sub>x</sub>(p, y, t) = u<sub>y</sub>(x, 0, t) = u<sub>y</sub>(x, q, t). Nonlinear PDEs tend to adjust the quality of the image, thus giving images desirable outlooks. In the digital world there is need for images to be smoothened for broadcast purposes, medical display of internal organs i.e MRI (Magnetic Resonance Imaging), study of the galaxy, CCTV (Closed Circuit Television) among others. This model inputs optimization in the smoothening of images. The solutions of the diffusion equations were obtained using iterative algorithms i.e. Alternating Direction Implicit (ADI) method, Two-point Explicit Group Successive Over-Relaxation (2-EGSOR) and a successive implementation of these two approaches. These schemes were executed in MATLAB (Matrix Laboratory) subject to an initial condition of a noisy images characterized by pepper noise, Gaussian noise, Brownian noise, Poisson noise etc. As the algorithms were implemented in MATLAB, the smoothing effect reduced at places with possibilities of being boundaries, the parameters C<sub>v</sub> (pixel flux), C<sub>f</sub> (coefficient of the forcing term), b (the threshold parameter) alongside time t were estimated through optimization. Parameter b maintained the highest value, while C<sub>v</sub> exhibited the lowest value implying that diffusion of pixels within the various images i.e. CCTV, MRI & Galaxy was limited to enhance smoothening. On the other hand the threshold parameter (b) took an escalated value across the images translating to a high level of the force responsible for smoothening.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"18 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140753960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-21DOI: 10.11648/j.sjams.20231103.12
Awogbemi, Clement Adeyeye, Koyejo Samuel Olusegun, Olowu Abiodun Rafiu
{"title":"On Different Extraction Methods of Factor Analysis","authors":"Awogbemi, Clement Adeyeye, Koyejo Samuel Olusegun, Olowu Abiodun Rafiu","doi":"10.11648/j.sjams.20231103.12","DOIUrl":"https://doi.org/10.11648/j.sjams.20231103.12","url":null,"abstract":"","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"11-12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139253558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-16DOI: 10.11648/j.sjams.20231103.11
El Hadji Abdoulaye Thiam, Papa Moussa Niang
{"title":"Improvement of the Raabe-Duhamel Convergence Criterion Generalized","authors":"El Hadji Abdoulaye Thiam, Papa Moussa Niang","doi":"10.11648/j.sjams.20231103.11","DOIUrl":"https://doi.org/10.11648/j.sjams.20231103.11","url":null,"abstract":"","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"104 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139266750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-15DOI: 10.11648/j.sjams.20231102.11
Maruf Ariyo Raheem, Regina Domingo Mbeke, Elisha John Inyang
: Modelling volatility asset returns is a well-researched concept in financial statistics, given its significance to investment analysts, economists, risk-averse investors, policymakers and other relevant stakeholders to underpin the market and the general economic performance and resilience to shocks, domestically and internationally. Thus, this study fits an appropriate ARCH/GARCH family model to daily stock returns volatility of each of the selected five most traded assets of the oil and gas marketing companies on the Nigerian stock exchange (NSE), using daily closing prices from January 1, 2005, to December 31, 2020. First-order symmetric and asymmetric volatility models with the Normal, Student’s t, Skewed Student’s t and generalized error distributions (GED) were fitted to select the best model with the most appropriate error distribution using appropriate model selection criteri EGARCH (1,1) with GEDs was found to be the best-fitted models based on the Akaike Information Criterion (AIC). The results indicated the presence of a leverage effect in the series and how the volatility reacts to good news as against bad news implying that positive shock has a higher impact on the returns of the respective companies. Based on the findings it is recommended that, for enhanced precision, GARCH family models with appropriate error distribution be applied in underpinning assets volatility, which in turn would help to better understand the nature of inherent shocks characterizing asset volatility of the respective companies. With such knowledge, appropriate investment decisions are made to guide risk-averse investors in their investments.
{"title":"Volatility Modelling of Stock Returns of Selected Nigerian Oil and Gas Companies","authors":"Maruf Ariyo Raheem, Regina Domingo Mbeke, Elisha John Inyang","doi":"10.11648/j.sjams.20231102.11","DOIUrl":"https://doi.org/10.11648/j.sjams.20231102.11","url":null,"abstract":": Modelling volatility asset returns is a well-researched concept in financial statistics, given its significance to investment analysts, economists, risk-averse investors, policymakers and other relevant stakeholders to underpin the market and the general economic performance and resilience to shocks, domestically and internationally. Thus, this study fits an appropriate ARCH/GARCH family model to daily stock returns volatility of each of the selected five most traded assets of the oil and gas marketing companies on the Nigerian stock exchange (NSE), using daily closing prices from January 1, 2005, to December 31, 2020. First-order symmetric and asymmetric volatility models with the Normal, Student’s t, Skewed Student’s t and generalized error distributions (GED) were fitted to select the best model with the most appropriate error distribution using appropriate model selection criteri EGARCH (1,1) with GEDs was found to be the best-fitted models based on the Akaike Information Criterion (AIC). The results indicated the presence of a leverage effect in the series and how the volatility reacts to good news as against bad news implying that positive shock has a higher impact on the returns of the respective companies. Based on the findings it is recommended that, for enhanced precision, GARCH family models with appropriate error distribution be applied in underpinning assets volatility, which in turn would help to better understand the nature of inherent shocks characterizing asset volatility of the respective companies. With such knowledge, appropriate investment decisions are made to guide risk-averse investors in their investments.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116949574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-09DOI: 10.11648/j.sjams.20231101.12
John Socrates Kekenusa, Sendy Beatrix Rondonuwu, Marline Sofiana Paendong
{"title":"Determination of the Utilization and Effort Level of Mackerel Scad (<i>Decapterus spp</i>) in the North Bolaangmongondow Waters North Sulawesi","authors":"John Socrates Kekenusa, Sendy Beatrix Rondonuwu, Marline Sofiana Paendong","doi":"10.11648/j.sjams.20231101.12","DOIUrl":"https://doi.org/10.11648/j.sjams.20231101.12","url":null,"abstract":"","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139370442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-13DOI: 10.11648/j.sjams.20231101.11
Nnaemeka Martin Eze, Chimeremeze Davidson Sibigem, Oluchukwu Chukwuemeka Asogwa, Chinonso Michael Eze, Samson Offorma Ugwu, Felix Obi Ohanuba
{"title":"On Statistical Analysis of Eight Sexually Transmitted Diseases Using Categorical Analysis of Variance: A Case Study of the University of Nigeria Teaching Hospital","authors":"Nnaemeka Martin Eze, Chimeremeze Davidson Sibigem, Oluchukwu Chukwuemeka Asogwa, Chinonso Michael Eze, Samson Offorma Ugwu, Felix Obi Ohanuba","doi":"10.11648/j.sjams.20231101.11","DOIUrl":"https://doi.org/10.11648/j.sjams.20231101.11","url":null,"abstract":"","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124625652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-29DOI: 10.11648/J.SJAMS.20210905.11
Zeine Sid Elemine, I. Faye, Alassane Sy, D. Seck
In this paper, we are concerned with the the internal control of an elliptic singularly perturbed degenerated parabolic equation. This parabolic equation models sand transport problem near the coast in areas subjected to the tide. We study first the null controllability result of the parabolic equation modeling sand transport equation.The limit problem obtained by homogenization problem is also considered. We use distributed and bounded controls supported on a small open set of the initial domain. We prove the null controllability of the system at any time by using observability inequality for both problem. For this purpose, a specific carleman estimate for the solutions of degenerate adjoint limit problem is also proved.
{"title":"Carleman Estimate for a Singulary Perturbed Degenerated Parabolic Equation","authors":"Zeine Sid Elemine, I. Faye, Alassane Sy, D. Seck","doi":"10.11648/J.SJAMS.20210905.11","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20210905.11","url":null,"abstract":"In this paper, we are concerned with the the internal control of an elliptic singularly perturbed degenerated parabolic equation. This parabolic equation models sand transport problem near the coast in areas subjected to the tide. We study first the null controllability result of the parabolic equation modeling sand transport equation.The limit problem obtained by homogenization problem is also considered. We use distributed and bounded controls supported on a small open set of the initial domain. We prove the null controllability of the system at any time by using observability inequality for both problem. For this purpose, a specific carleman estimate for the solutions of degenerate adjoint limit problem is also proved.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133554961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-26DOI: 10.11648/J.SJAMS.20210904.12
E. Yehia
For modeling count data, the Poisson regression model is widely used in which the response variable takes non-negative integer values. However, the presence of strong correlation between the explanatory variables causes the problem of multicollinearity. Due to multicollinearity, the variance of the maximum likelihood estimator (MLE) will be inflated causing the parameters estimation to become unstable. Multicollinearity can be tackled by using biased estimators such as the ridge estimator in order to minimize the estimated variance of the regression coefficients. An alternative approach is to specify exact linear restrictions on the parameters in addition to regression model. In this paper, the restricted Poisson ridge regression estimator (RPRRE) is suggested to handle multicollinearity in Poisson regression model with exact linear restrictions on the parameters. In addition, the conditions of superiority of the suggested estimator in comparison to some existing estimators are discussed based on the mean squared error (MSE) matrix criterion. Moreover, a simulation study and a real data application are provided to illustrate the theoretical results. The results indicate that the suggested estimator, RPRRE, outperforms the other existing estimators in terms of scalar mean squared error (SMSE). Therefore, it is recommended to use the RPRRE for the Poisson regression model when the problem of multicollinearity is present.
{"title":"On the Restricted Poisson Ridge Regression Estimator","authors":"E. Yehia","doi":"10.11648/J.SJAMS.20210904.12","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20210904.12","url":null,"abstract":"For modeling count data, the Poisson regression model is widely used in which the response variable takes non-negative integer values. However, the presence of strong correlation between the explanatory variables causes the problem of multicollinearity. Due to multicollinearity, the variance of the maximum likelihood estimator (MLE) will be inflated causing the parameters estimation to become unstable. Multicollinearity can be tackled by using biased estimators such as the ridge estimator in order to minimize the estimated variance of the regression coefficients. An alternative approach is to specify exact linear restrictions on the parameters in addition to regression model. In this paper, the restricted Poisson ridge regression estimator (RPRRE) is suggested to handle multicollinearity in Poisson regression model with exact linear restrictions on the parameters. In addition, the conditions of superiority of the suggested estimator in comparison to some existing estimators are discussed based on the mean squared error (MSE) matrix criterion. Moreover, a simulation study and a real data application are provided to illustrate the theoretical results. The results indicate that the suggested estimator, RPRRE, outperforms the other existing estimators in terms of scalar mean squared error (SMSE). Therefore, it is recommended to use the RPRRE for the Poisson regression model when the problem of multicollinearity is present.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117138308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-07-24DOI: 10.11648/J.SJAMS.20210903.12
Xiangyi Zhu
The characteristics of prospector are to constantly find new market opportunities, carry out technological innovation, and obtain growth opportunities by moving to high value-added fields. Defender often choose a relatively stable market area and take effective actions, such as setting competitive prices or providing high-quality products and services, to actively prevent subsequent competitors from entering this industry. Although different strategic types of enterprises have different business preference, they cannot do without the active cooperation of employees in the process of strategy implementation, because they are the closest to the production and customers. If the incentive mechanism conflicts with employees' interests, employees may respond by leaving. Based on the sample of China's A-share listed companies from 2007 to 2019, this paper uses the fixed effect model to examine the impact of strategy on employee incentive mechanism and turnover rate. The empirical results show that, compared with defender, the pay gap of prospector is higher, and the above phenomenon is more significant in enterprises with lower labor intensity. In addition, prospector will also push up the turnover rate of employees, in which the pay gap plays a mediating role. This conclusion not only enriches the research of strategic theory and compensation contract, but also has some enlightenment for the relevant government departments to develop vocational training to improve employees' skills.
{"title":"Corporate Strategy, Pay Gap and Employee Turnover Rate: Based on Mediation Model","authors":"Xiangyi Zhu","doi":"10.11648/J.SJAMS.20210903.12","DOIUrl":"https://doi.org/10.11648/J.SJAMS.20210903.12","url":null,"abstract":"The characteristics of prospector are to constantly find new market opportunities, carry out technological innovation, and obtain growth opportunities by moving to high value-added fields. Defender often choose a relatively stable market area and take effective actions, such as setting competitive prices or providing high-quality products and services, to actively prevent subsequent competitors from entering this industry. Although different strategic types of enterprises have different business preference, they cannot do without the active cooperation of employees in the process of strategy implementation, because they are the closest to the production and customers. If the incentive mechanism conflicts with employees' interests, employees may respond by leaving. Based on the sample of China's A-share listed companies from 2007 to 2019, this paper uses the fixed effect model to examine the impact of strategy on employee incentive mechanism and turnover rate. The empirical results show that, compared with defender, the pay gap of prospector is higher, and the above phenomenon is more significant in enterprises with lower labor intensity. In addition, prospector will also push up the turnover rate of employees, in which the pay gap plays a mediating role. This conclusion not only enriches the research of strategic theory and compensation contract, but also has some enlightenment for the relevant government departments to develop vocational training to improve employees' skills.","PeriodicalId":422938,"journal":{"name":"Science Journal of Applied Mathematics and Statistics","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123200211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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