scholarly journals Person - job fi t and the work commitment of IT Personnel

2016 ◽  
Vol 26 (2) ◽  
pp. 218 ◽  
Author(s):  
Therasa C. ◽  
C. Vijayabanu
Keyword(s):  
Regression Analysis ◽  
Principal Component ◽  
Attrition Rate ◽  
P Value ◽  
Work Commitment ◽  
Key Factors ◽  
Coeffi Cients ◽  
Work Autonomy ◽  
Major Factors ◽  
The Impact

Introduction: There have been given a much higher importance to employee commitment and retention since India is experiencing the highest attrition rate globally Economic Times, 2015. Hence, considering the factors of Person-job fi t to interpret the impact towards work commitment is very well essential, especially in the current scenario. Work Commitment is a vital element in any organization which has outstanding impact on productivity and functioning and hence it is very much vital to have a committed workforce which is necessary in this competitive environment and tight labour market. In the same way, there is considerable amount of evidence that if P-J fi t is high then it will have a direct impact on organization commitment also. Person-job fi t is the compatibility between person’s competency and abilities and the requirements of the job Zheng et al.2. If there exists a mismatch between person-job fi t then the consequences might result in poor work commitment, low job satisfaction and extremely lower involvement in the job. Objective: This study analyzed the key factors that contribute to Person- job compatibility among IT workers and also analyzed the relationship and impact of Person- job compatibility towards work commitment. Methods: Exploratory Factor Analysis (EFA) was used to fi lter the key factors initially, followed by a linear regression technique to determine the impact of Person- job compatibility factors in work commitment on a sample of 300 employees. EFA used Principal Component analysis for extraction and Promax for rotation. Finally regression analysis was carried out to predict the work commitment through statistically significant person-job compatibility variables. Results: The impact of person-job compatibility on work commitment was studied through regression analysis and it imply that for every unit increase in HR Policy, a 0.52 (unstandardised coeffi cients) increase in work commitment is predicted and it has been turned out as a most impacting variable to predict work commitment. The coeffi cients for Relationship (B =.330, sig =.000), HR Policies (B =.519, sig =.000), Pay and Benefi ts (B =.386, sig =.000) and Employee Growth (B =.290, sig =.001) were statistically significant, since its p-value is .000 which is smaller than .05. The coeffi cients for Work Autonomy (B =.154, sig = .081) was not statistically signifi cant, since its p-value is 0.081 which is greater than.05. Conclusion: The major factors responsible for creating work commitment among IT employees are Relationship, HR Policies and strategies, Pay and benefi ts, Work autonomy and Employee growth. The most contributing regressors which accounts for creating work commitment are HR policies, Pay and benefi ts, Employee growth and work autonomy.

scholarly journals Assessing the Impact of Relationship Length in the SMEs and Bank Association

2017 ◽  
Vol 9 (5) ◽  
pp. 17 ◽  
Author(s):  
Mark Ojeme
Keyword(s):  
Regression Analysis ◽  
Principal Component ◽  
Building Blocks ◽  
Relationship Building ◽  
Internal Reliability ◽  
Relationship Length ◽  
Relationship Context ◽  
Short And Long Term ◽  
The Impact

Despite the importance of satisfaction, loyalty and relationship length in the literature, there is very little evidence of studies within the Nigerian Business to Business (B2B) Relationship terrain. This paper seeks to investigate the effect of relationship length on SMEs association with their banks in Nigeria. Measurement Items were adapted from various scale sets presented in existing studies were combined to investigate the B2B relationship context. Data were collected from 221 SMEs via a self-administered questionnaire completed either by the SME owner or senior manager with responsibility for relationship with their bank, providing 199 usable records. Principal Component Exploratory Analysis (PCA) was used to determine the underlying data structure, with subsequent deployment of Cronbach’s alpha as a post-hoc assessment of the internal reliability of the retained factors. Subsequently, regression analysis was employed to determine the impact of satisfaction on loyalty in a short and long term relationship contexts. The analysis presented suggests that the SMEs’ had evidence of been satisfied with their bank, however, the regression analysis for both short and long term relationship length were both significant in impacting their loyalty towards their bank. The originality of this paper lies in the investigation of a B2B relationship involving SMEs and banks within a relationship context that hitherto was unknown and the validation of relevant relationship building blocks. 

Government Expenditures on Higher Education and Innovativeness

2020 ◽  
pp. 287-316
Author(s):  
Marko Slavković ◽  
Marijana Simić
Keyword(s):  
Higher Education ◽  
Regression Analysis ◽  
Higher Education Funding ◽  
Key Factors ◽  
Education Expenditure ◽  
Knowledge Based ◽  
Current Trends ◽  
Knowledge Based Economy ◽  
Impact Of Higher Education ◽  
The Impact

Current trends such as globalization and the growing importance of intangible assets and a knowledge-based economy makes a significant contribution to highlighting the importance of higher education funding. Classified as one of the key factors determining the level of innovation and competitiveness, both at the micro and macro levels, education and especially higher education have been funded in different ways in different countries. Therefore, the main objective of the research is to determine the impact of higher education expenditure on innovation in Serbia and Slovenia, on the basis of which a comparison of results can be made. Analyzing the data for the period 2007-2016 and based on the results of the regression analysis, we conclude that there is a negative significant impact of the share of the state allocation for higher education on the level of innovation in Serbia, while the results relating to the situation in Slovenia are contrary and indicate a positive significant impact.

Effect of Household Income on Short-Term Outcomes Following Cerebellopontine Angle Tumor Resection

2021 ◽  
Author(s):  
Vincent Huang ◽  
Stephen P. Miranda ◽  
Ryan Dimentberg ◽  
Kaitlyn Shultz ◽  
Scott D. McClintock ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Household Income ◽  
Cerebellopontine Angle ◽  
Univariate Analysis ◽  
Tumor Resection ◽  
Index Admission ◽  
P Value ◽  
Short Term ◽  
Significant Difference ◽  
The Impact

Abstract Objectives The objective of this study is to elucidate the impact of income on short-term outcomes in a cerebellopontine angle (CPA) tumor resection population. Design This is a retrospective regression analysis. Setting This study was done at a single, multihospital, urban academic medical center. Participants Over 6 years (from June 7, 2013, to April 24, 2019), 277 consecutive CPA tumor cases were reviewed. Main Outcome Measures Outcomes studied included readmission, emergency department evaluation, unplanned return to surgery, return to surgery after index admission, and mortality. Univariate analysis was conducted among the entire population with significance set at a p-value <0.05. The population was divided into quartiles based on median household income and univariate analysis conducted between the lowest (quartile 1 [Q1]) and highest (quartile 4 [Q4]) socioeconomic quartiles, with significance set at a p-value <0.05. Stepwise regression was conducted to determine the correlations among study variables and to identify confounding factors. Results Regression analysis of 273 patients demonstrated decreased rates of unplanned reoperation (p = 0.015) and reoperation after index admission (p = 0.035) at 30 days with higher standardized income. Logistic regression between the lowest (Q1) and highest (Q4) socioeconomic quartiles demonstrated decreased unplanned reoperation (p = 0.045) and decreasing but not significant reoperation after index admission (p = 0.15) for Q4 patients. No significant difference was observed for other metrics of morbidity and mortality. Conclusion Higher socioeconomic status is associated with decreased risk of unplanned reoperation following CPA tumor resection.

scholarly journals Statistical Methods in the Usage of Correlation and Regression of the Machine Learning Models

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2489-2491
Keyword(s):  
Machine Learning ◽  
Regression Analysis ◽  
Correlation Analysis ◽  
Statistical Methods ◽  
Predictive Analytics ◽  
Current Work ◽  
P Value ◽  
Start Up ◽  
Significance Levels ◽  
The Impact

The predictive analytics is the most commonly used methodology in the usage of Machine Learning class of algorithms. Based on the values generated at the time of running the algorithm the significance of the model can be estimated. The current work gives a complete focus on P value and the significance levels of the P value in the correlation analysis of the algorithms. Based on the P value the impact of the model can be notified and the interpretation of the results can be done in the efficient way. The other dimension of the work is the usage of statistical functionalities in the regression analysis, most of the researchers are focusing on the shallow usage of regression analysis in the classification of the tasks. The current work explains the complete internals of the regression models available and the usage of the statistical functionalities utilized in the implementation of the corresponding variants of the algorithms. We believe that the current work exclusively helps the upcoming researcher in the areas of regression in the context of the statistical functionalities which are vital in the implementation of the tasks. The outcome of the work is to exploit the correlation analysis with various significance levels and the issues in the processing of the analysis. The another point here is the regression internals with the focus of statistical methods available in the processing of regression variants. The regression analysis involves various types like linear regression, multiple regressions and logistic regression. The current work gives an overview of all these three types of regressions and also the significance of P value in the prediction of outcome. In the examples such as house rate prediction based on the given area, salary of an employee based on the experience level, profit of the start-up companies based on the spending on research, admin marketing and state of the country are best suitable in the explanation of regression.

scholarly journals DETERMINANTS OF MANAGEMENT ACCOUNTING PRACTICES BY MANUFACTURING FIRMS

2021 ◽  
pp. 55-61
Author(s):  
Joseph Adu-Gyamfi ◽  
Prof Kong Yusheng ◽  
Abraham Lincoln Ayisi ◽  
Wilson Elorm Pekyi
Keyword(s):  
Regression Analysis ◽  
Production Technology ◽  
Firm Size ◽  
Management Accounting ◽  
Manufacturing Firms ◽  
Improve Performance ◽  
Competition Level ◽  
Major Factors ◽  
Advanced Production ◽  
The Impact

The impact of the management accounting practices on manufacturing firms in the developing countries cannot be overlook. Management accounting practices adopts and put to practice by these firms has always yielded result, but before management accounting practices are adopted by these firms there are factors that determine their adoption. This paper purposely looks into factors that determine the adoption of management accounting practices by manufacturing firms in Ghana. Various literatures has brought to light that that both internal and external environmental factor such firm size, market rivalry (competition), level of qualification of accounting staff and advanced production technology as the major factors that affect MAPs adoption and want to make analysis with Ghanaian manufacturing firms does these factors affect their choice of MAPs This study gathered Data from 200 manufacturing firms in Ghana through questionnaires and regression analysis were done using SPSS to determine the impact these factors have on the adoption of MAPs by these manufacturing firms in Ghana. The study identified determinants such as, firm size, market rivalry (competition), level of qualification of accounting staff and advanced production technology has a positive significant impact on the adoption of management accounting practices by manufacturing firms in Ghana. The study recommends that it is important for organizations to identify the best MAPs which can be include in the firms operations to improve performance and longevity of the organization KEYWORDS: Ghana, Management accounting practices, firm size, market rivalry (competition), qualification of accounting staff and advanced production technology

scholarly journals Multiple correlation-regression analysis of the impact of major factors on oil production

2021 ◽  
Vol 258 ◽  
pp. 12013
Author(s):  
Klara Gabdrakhmanova ◽  
Gulnara Izmailova ◽  
Lilia Samigullina ◽  
Muhammad Majidov
Keyword(s):  
Regression Analysis ◽  
Oil Recovery ◽  
Oil Companies ◽  
Correlation And Regression Analysis ◽  
Direct Measurements ◽  
Major Factors ◽  
Relationship Of ◽  
The Impact ◽  
The Relationship ◽  
Relevant Factors

This article discusses the multiple regression analysis techniques to determine the effectiveness of the factors used. The study examines the various relationships between the elements. It is important to identify which factor will be the most important when selecting wells to determine the amount of oil recovery. Nowadays, the most important problem in the fields of Tatarstan and Bashkortostan is the depletion of deposits. To maintain the profitability of mining companies, therefore, the issue of preparing new reserves remains relevant. This process involves high costs and risks. For a more reliable picture, it is crucial to determine the most relevant factors. The use of the triad of studies proposed by the authors makes it possible to more reliably determine the effectiveness of oil companies. The initial data are direct measurements and methods of mathematical statistics that allow more accurate predictions. Statistical analysis made it possible to identify the parameters on which the effectiveness of the factors depends. In domestic practice, the assessment of resources and reserves of hydrocarbons is usually made by deterministic methods, while abroad the statistical method is used. When studying the relationships between objects, the analyst should be interested not only in the presence and quantitative assessment of the relations but also in the form and relationship of the effective and factor characteristics, its analytical expression. Correlation and regression analysis help to solve these problems. Correlation analysis aims to measure the tightness of the relationship between the varying variables and to evaluate the factors that have the greatest impact on the resulting trait. Regression analysis is designed to select the form of the relationship, to determine the calculated values of the dependent variable (the effective feature) [1]. For the factor analysis, we used data on the oil industry published in the annual statistical collections of Rosstat, as well as specialized periodicals for ten years.

scholarly journals PENGARUH KEPUASAN WAJIB PAJAK, PENEGAKAN SANKSI PAJAK DAN KEADILAN DISTRIBUTIF TERHADAP KEPATUHAN WAJIB PAJAK DI KOTA PONTIANAK

2018 ◽  
Vol 8 (1) ◽  
pp. 001
Author(s):  
JOKO SUSENO ◽  
SANI SANI
Keyword(s):  
Regression Analysis ◽  
Distributive Justice ◽  
Multiple Regression Analysis ◽  
Significant Influence ◽  
P Value ◽  
Service Company ◽  
Service Companies ◽  
The Impact ◽  
Construction Services ◽  
Analyze Data

The aims of study are analyzing the impact of satisfaction from the taxpayers, tax sanction enforcement and distributive justice on taxpayer compliance, especially taxpayer of construction service companies. Data has been collected by closed questionnaire with Likert scale between 1 and 5. From the statement, it can know the level of taxpayer compliance as the respondent to the problem determined by the way of providing value to answers result from the respondents. Multiple regression analysis has been used to analyze data. Based on the research, it shows that taxpayer satisfaction variable can be proved by having a positive and significant influence on taxpayer compliance especially taxpayer of construction service company by coefficient result β = 0,383 with p-value equal to 0,0095 smaller than α= 0,05 , variables Enforcement of tax sanctions has been proven by having a positive and significant impact on taxpayer compliance, especially Construction Services Company coefficient β = 0.943 with p-value of 0.014 smaller than α = 0.05. And distributive justice variable has positive and significant influence on taxpayer compliance especially Construction Service Company with result of coefficient β = 0,749 with p-value equal to = 0,0185 smaller than α = 0, 05

scholarly journals Capital Structure Modelling and Analysis of its Impact on Business Performance

2017 ◽  
Vol 8 (2) ◽  
pp. 19-36 ◽  
Author(s):  
Jarmila Horváthová ◽  
Martina Mokrišová
Keyword(s):  
Principal Component Analysis ◽  
Regression Analysis ◽  
Capital Structure ◽  
Public Interest ◽  
Business Performance ◽  
Principal Component ◽  
Structure Model ◽  
Independent Variables ◽  
The Impact ◽  
The Capital Structure

The aim of the paper was to investigate the impact of company's capital structure on its performance. To achieve the goal, the data of Slovak businesses were used. An input analysis of the capital structure of the selected sector was carried out in order to generalize and elaborate conclusions aimed at the capital structure of the businesses analysed. Selected indicators of capital structure were calculated to analyse the relationships between these indicators and business performance. The results of the correlation analysis were complemented by examining the impact of selected independent variables on business performance applying regression analysis and Principal Component Analysis. Based on the findings, capital structure model was formulated to quantify the impact of changes in capital structure on business performance. The contribution of the paper is the identification of capital structure indicators that affect business performance as well as the construction of capital structure model. The article as well as the research, which is the basis for paper elaboration, is the result of professional public interest focused on finding whether the capital structure is the determinant of business performance.

scholarly journals Low-carbon Development of Urban Logistics Based on Principal Component Analysis —A Case Study of Lanzhou City

2016 ◽  
Vol 8 (1) ◽  
pp. 73 ◽  
Author(s):  
Huifang Bai ◽  
Kedong Tan ◽  
Kaishun Huang ◽  
Qian Guo
Keyword(s):  
Principal Component Analysis ◽  
Carbon Emission ◽  
Principal Component ◽  
Component Analysis ◽  
Low Carbon ◽  
Key Factors ◽  
Low Carbon Economy ◽  
Lanzhou City ◽  
The Impact

The Low-carbon economy is a sustainable economic model advocated by many countries all over the world. Urban logistics, as an important source of urban environmental pollution, is in an urgent demand for the development. This paper takes Lanzhou City as the research object to find out the key factors of urban logistics carbon emissions through the construction of carbon emission index system, the principal component analysis of the impact indicators from 2005 to 2014. And by evaluating the carbon emission level of logistics in Lanzhou City, it provides the corresponding solutions for the low carbon logistics development in Lanzhou City.

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