scholarly journals Influence of E-Procurement on the Performance of State Corporations in Kenya

2021 ◽  
Vol 7 (6) ◽  
pp. 45-51
Author(s):  
Munaku D. Mwangi ◽  
Wycliffe N. Arani
Keyword(s):  
Regression Model ◽  
Sample Size ◽  
Content Validity ◽  
Response Rate ◽  
Primary Data ◽  
Validity And Reliability ◽  
Rural Roads ◽  
Descriptive Research ◽  
Simple Regression Model ◽  
Simple Regression

The purpose of study is to investigate the influence of e-procurement on the performance of state corporations in Kenya. Descriptive research design is adopted with the use of questionnaire as tool for primary data collected. The data yielded a response rate of 95.2 percent from a sample size of 62 used, which were drawn mainly from senior procurement managers of Kenya Rural Roads Authority (KeRRA). The data collected was statistically analysed to test content validity and reliability. In addition, a simple regression model was used conducted to test relationship between e-procurement and the performance of state corporations in Kenya. From the findings it was found out that e-procurement has transformed all routine purchasing transactions within KeRRA. However, it was established that e-procurement does not reduce the costs of acquiring materials and freeing up KeRRA resources. It was also noted that e-procurement positively increases the performance of state corporations.

scholarly journals Influence of E-Procurement on the Performance of State Corporations in Kenya

2021 ◽  
Vol 6 (6) ◽  
pp. 31-36
Author(s):  
Munaku D. Mwangi ◽  
Wycliffe N. Arani
Keyword(s):  
Regression Model ◽  
Sample Size ◽  
Content Validity ◽  
Response Rate ◽  
Primary Data ◽  
Validity And Reliability ◽  
Rural Roads ◽  
Descriptive Research ◽  
Simple Regression Model ◽  
Simple Regression

The purpose of study is to investigate the influence of e-procurement on the performance of state corporations in Kenya. Descriptive research design is adopted with the use of questionnaire as tool for primary data collected. The data yielded a response rate of 95.2 percent from a sample size of 62 used, which were drawn mainly from senior procurement managers of Kenya Rural Roads Authority (KeRRA). The data collected was statistically analysed to test content validity and reliability. In addition, a simple regression model was used conducted to test relationship between e-procurement and the performance of state corporations in Kenya. From the findings it was found out that e-procurement has transformed all routine purchasing transactions within KeRRA. However, it was established that e-procurement does not reduce the costs of acquiring materials and freeing up KeRRA resources. It was also noted that e-procurement positively increases the performance of state corporations.

scholarly journals Fine-Scale Mapping of Quantitative Trait Loci Using Historical Recombinations

Genetics ◽  
1997 ◽  
Vol 145 (4) ◽  
pp. 1201-1218
Author(s):  
Momiao Xiong ◽  
Sun-Wei Guo
Keyword(s):  
Qtl Mapping ◽  
Regression Model ◽  
Sample Size ◽  
Multiple Regression ◽  
Regression Models ◽  
Fine Scale ◽  
Simple Regression Model ◽  
Multiple Regression Models ◽  
Qtl Map ◽  
Simple Regression

With increasing popularity of QTL mapping in economically important animals and experimental species, the need for statistical methodology for fine-scale QTL mapping becomes increasingly urgent. The ability to disentangle several linked QTL depends on the number of recombination events. An obvious approach to increase the recombination events is to increase sample size, but this approach is often constrained by resources. Moreover, increasing the sample size beyond a certain point will not further reduce the length of confidence interval for QTL map locations. The alternative approach is to use historical recombinations. We use analytical methods to examine the properties of fine QTL mapping using historical recombinations that are accumulated through repeated intercrossing from an F2 population. We demonstrate that, using the historical recombinations, both simple and multiple regression models can reduce significantly the lengths of support intervals for estimated QTL map locations and the variances of estimated QTL map locations. We also demonstrate that, while the simple regression model using historical recombinations does not reduce the variances of the estimated additive and dominant effects, the multiple regression model does. We further determine the power and threshold values for both the simple and multiple regression models. In addition, we calculate the Kullback-Leibler distance and Fisher information for the simple regression model, in the hope to further understand the advantages and disadvantages of using historical recombinations relative to F2 data.

Face Gear Width Prediction Using the DOE Method

2008 ◽  
Vol 130 (10) ◽  
Author(s):  
Michèle Guingand ◽  
Didier Remond ◽  
Jean-Pierre de Vaujany
Keyword(s):  
Regression Model ◽  
Simple Formula ◽  
Design Parameters ◽  
Face Gear ◽  
Main Design ◽  
Gear Design ◽  
Simple Regression Model ◽  
Numerical Tool ◽  
Influential Parameters ◽  
Simple Regression

This paper deals with face gear design. The goal is to propose a simple formula for predicting the width of the wheel as a function of the main design parameters. A specific software was used to achieve this goal. This numerical tool is able to simulate the geometry and the quasistatic loaded behavior of a face gear. The statistical method used for analyzing the influence of data is described: The design of experiments leads to a simple regression model taking into account the influential parameters and their couplings. In the last part of this paper, the results of the formulas are compared to those of the software and an optimal design is proposed based on the regression model.

scholarly journals PENGARUH TATA KELOLA PEMERINTAH DAERAH TERHADAPTRANSPARANSI PENGELOLAAN KEUANGAN DAERAH: BUKTI EMPIRIS PADA PEMERINTAH PROVINSI DI INDONESIA

2017 ◽  
Vol 21 (3) ◽  
pp. 448
Author(s):  
Syamsul Syamsul ◽  
Irwan Taufiq Ritonga
Keyword(s):  
Corporate Governance ◽  
Regression Model ◽  
Financial Management ◽  
Local Governments ◽  
Environmental Governance ◽  
Local Governance ◽  
Government Officials ◽  
Simple Regression Model ◽  
Simple Regression

This study developed a research Beekes and Brown (2006) who found that corporate governance makes companies more informative (more transparent). This study aims to prove whether the same results were also found in environmental governance in Indonesia. The theory is used to achieve the goal of this research is the theory of agency. This research was conducted in 32 local governments in Indonesia. Based on a simple regression model, this study shows that local governance affects positively the transparency of local financial management. Such findings reinforce previous research. The findings of this study provide a useful contribution to government officials (executive and legislative), in demonstrating the important role of local governance in encouraging the transparency of local financial management. In addition, the findings of this study can be used as the basis for further research related to the topic of local governance and transparency of local financial management.

PENGARUH LABEL HALAL TERHADAP KEPUTUSAN MASYARAKAT MEMBELI PRODUK MAKANAN DAN MINUMAN (Studi Kasus Lingkungan VI Kelurahan Nangka Binjai Utara)

2020 ◽  
Vol 5 (2) ◽  
pp. 354
Author(s):  
Raja Sakti Putra Harahap
Keyword(s):  
Regression Model ◽  
Quantitative Method ◽  
Statistical Tests ◽  
A Value ◽  
Regression Formula ◽  
Simple Regression Model ◽  
Food And Beverage ◽  
R Value ◽  
Positive Effect ◽  
Simple Regression

This study aims to determine how the effect of the halal label on people’s decisions to buy food and beverage products. The method used is a quantitative method with a simple regression model and using statistical tests with the help of IBM SPSS Statistics 22 for windows. The sample in this study is the neighborhood community VI Nangka Village as many as 70 respondents. The results showed that the calculated r value was 0,79, so it could be saidthat there was s relationship or correlation between the variables X (Halal Label) with the variable Y ( The decision to buy food and beverage products). Then the t value < t table, which has a value of 0,657 < 1,668. Then  is accepted and  is rejected, which means that partially (X) variable does not have a significant effect on variable (Y), where the results of the hypothesis are accepted and proven after being calculated using a simple regression formula, namely Y = 34,7 + 0,67X.  By having a regression coefficoent of 0,675%, so the halal label has a positive effect on decisions to buy food and beverage products.

scholarly journals An Evaluation of Alternative Multiple Testing Methods for Finance Applications*

2020 ◽  
Vol 10 (2) ◽  
pp. 199-248 ◽  
Author(s):  
Campbell R Harvey ◽  
Yan Liu ◽  
Alessio Saretto
Keyword(s):  
Regression Model ◽  
Multiple Testing ◽  
Empirical Finance ◽  
Relative Performance ◽  
Testing Methods ◽  
Multiple Tests ◽  
High Profile ◽  
Simple Regression Model ◽  
Testing Environments ◽  
Simple Regression

Abstract In almost every area of empirical finance, researchers confront multiple tests. One high-profile example is the identification of outperforming investment managers, many of whom beat their benchmarks purely by luck. Multiple testing methods are designed to control for luck. Factor selection is another glaring case in which multiple tests are performed, but numerous other applications do not receive as much attention. One important example is a simple regression model testing five variables. In this case, because five variables are tried, a t-statistic of 2.0 is not enough to establish significance. Our paper provides a guide to various multiple testing methods and details a number of applications. We provide simulation evidence on the relative performance of different methods across a variety of testing environments. The goal of our paper is to provide a menu that researchers can choose from to improve inference in financial economics. (JEL G0, G1, G3, G5, M4, C1)

Sign in / Sign up

Export Citation Format

Share Document