In this study a multi-group approach is used
within the structural equations modelling framework,
with the purpose of validating the temporal stability of
the material deprivation measurement model, as well
the impact of the existence of children in the household.
For the purposes of model comparison, the use of the
likelihood ratio test is discussed, when the normal
distribution of the data cannot be assumed and the
robust Satorra-Bentler scaled-corrected chi-square
estimator is used. The statistical package LISREL 8.8 is
used for estimating models.
Modeling selection pressure in XCS for proportionate and tournament selectionkknsastry
In this paper, we derive models of the selection pressure in XCS for proportionate (roulette wheel) selection and tournament selection. We show that these models can explain the empirical results that have been previously presented in the literature. We validate the models on simple problems showing that, (i) when the model assumptions hold, the theory perfectly matches the empirical evidence; (ii) when the model assumptions do not hold, the theory can still provide qualitative explanations of the experimental results.
Modeling XCS in class imbalances: Population size and parameter settingskknsastry
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the effect of the imbalance ratio—ratio between the number of instances of the majority class and the minority class that are sampled to XCS—on population initialization, and on the creation and deletion of classifiers of the minority class. While theoretical models show that, ideally, XCS scales linearly with the imbalance ratio, XCS with standard configuration scales exponentially. The causes that are potentially responsible for this deviation from the ideal scalability are also investigated. Specifically, the inheritance procedure of classifiers’ parameters, mutation, and subsumption are analyzed, and improvements in XCS’s mechanisms are proposed to effectively and efficiently handle imbalanced problems. Once the recommendations are incorporated to XCS, empirical results show that the population size in XCS indeed scales linearly with the imbalance ratio.
Let's get ready to rumble redux: Crossover versus mutation head to head on ex...kknsastry
This paper analyzes the relative advantages between crossover and mutation on a class of deterministic and stochastic additively separable problems with substructures of non-uniform salience. This study assumes that the recombination and mutation operators have the knowledge of the building blocks (BBs) and effectively exchange or search among competing BBs. Facetwise models of convergence time and population sizing have been used to determine the scalability of each algorithm. The analysis shows that for deterministic exponentially-scaled additively separable, problems, the BB-wise mutation is more efficient than crossover yielding a speedup of Θ(<em>l</em> log<em>l</em>), where <em>l</em> is the problem size. For the noisy exponentially-scaled problems, the outcome depends on whether scaling on noise is dominant. When scaling dominates, mutation is more efficient than crossover yielding a speedup of Θ(<em>l</em> log<em>l</em>). On the other hand, when noise dominates, crossover is more efficient than mutation yielding a speedup of Θ(<em>l</em>).
Analyzing probabilistic models in hierarchical BOA on traps and spin glasseskknsastry
The hierarchical Bayesian optimization algorithm (hBOA) can solve nearly decomposable and hierarchical problems of bounded difficulty in a robust and scalable manner by building and sampling probabilistic models of promising solutions. This paper analyzes probabilistic models in hBOA on two common test problems: concatenated traps and 2D Ising spin glasses with periodic boundary conditions. We argue that although Bayesian networks with local structures can encode complex probability distributions, analyzing these models in hBOA is relatively straightforward and the results of such analyses may provide practitioners with useful information about their problems. The results show that the probabilistic models in hBOA closely correspond to the structure of the underlying optimization problem, the models do not change significantly in subsequent iterations of BOA, and creating adequate probabilistic models by hand is not straightforward even with complete knowledge of the optimization problem.
This document discusses the use of STELLA simulation software to model various systems over time. It provides examples of using STELLA to model predator-prey relationships in an oil palm plantation and to predict climate change scenarios. The document also discusses how simulations like STELLA can encourage student interest and engagement in science learning by making experiments interactive, allowing hypothesis testing, and helping students understand real-world systems.
This document outlines a study on the effect of crop diversity on farm household poverty dynamics in Nigeria. It discusses the motivation, objectives, data, estimation strategy, and results. The study uses panel data from Nigeria from 2010-2016 to estimate an endogenous switching model to assess how crop diversity affects poverty transitions and persistence. It analyzes poverty status in the current and previous period, household retention between periods, and the correlations between error terms to account for unobserved heterogeneity. The results will help identify sustainable agricultural practices that can improve welfare and help households withstand climate change impacts.
This document discusses a study that uses a mixed logit model to predict firm financial distress. Mixed logit is an advanced discrete choice modeling technique that relaxes assumptions of standard logit models. It allows for observed and unobserved heterogeneity across firms. The study aims to demonstrate the empirical usefulness of mixed logit in financial distress prediction by comparing its performance to standard logit models. Results and out-of-sample forecasts show mixed logit outperforms standard logit models by significant margins in predicting firm financial distress.
Fuzzy Logic Approach to Identify Deprivation Index in Peninsular MalaysiajournalBEEI
Deprivation indices are similar to inequalities index or index of disadvantageous. It was built to measure the basic necessities in a specific study area or region. There were many indices that have been constructed in the previous study. However, since these indices had depended mostly on two factors; socio-economic conditions and geography of the study area, thus different result would be generated in different areas. The objective of this study is to construct the new index based on above factors in Peninsular Malaysia by using a fuzzy logic approach. This study employed twelve variables from different facilities condition that was obtained from Malaysia 2000’s census report. These variables were considered as input parameters in the fuzzy logic system. Data turned into linguistic variables and shaped into rules in the form of IF-ELSE conditions. After that, the centroid of area method is applied to acquire the final deprivation index for a specific district in Peninsular Malaysia. The result showed that less developed states generated lower index for examples Kelantan and Kedah while more developed states generated a higher index for examples Selangor and W.P. Kuala Lumpur.
Modeling selection pressure in XCS for proportionate and tournament selectionkknsastry
In this paper, we derive models of the selection pressure in XCS for proportionate (roulette wheel) selection and tournament selection. We show that these models can explain the empirical results that have been previously presented in the literature. We validate the models on simple problems showing that, (i) when the model assumptions hold, the theory perfectly matches the empirical evidence; (ii) when the model assumptions do not hold, the theory can still provide qualitative explanations of the experimental results.
Modeling XCS in class imbalances: Population size and parameter settingskknsastry
This paper analyzes the scalability of the population size required in XCS to maintain niches that are infrequently activated. Facetwise models have been developed to predict the effect of the imbalance ratio—ratio between the number of instances of the majority class and the minority class that are sampled to XCS—on population initialization, and on the creation and deletion of classifiers of the minority class. While theoretical models show that, ideally, XCS scales linearly with the imbalance ratio, XCS with standard configuration scales exponentially. The causes that are potentially responsible for this deviation from the ideal scalability are also investigated. Specifically, the inheritance procedure of classifiers’ parameters, mutation, and subsumption are analyzed, and improvements in XCS’s mechanisms are proposed to effectively and efficiently handle imbalanced problems. Once the recommendations are incorporated to XCS, empirical results show that the population size in XCS indeed scales linearly with the imbalance ratio.
Let's get ready to rumble redux: Crossover versus mutation head to head on ex...kknsastry
This paper analyzes the relative advantages between crossover and mutation on a class of deterministic and stochastic additively separable problems with substructures of non-uniform salience. This study assumes that the recombination and mutation operators have the knowledge of the building blocks (BBs) and effectively exchange or search among competing BBs. Facetwise models of convergence time and population sizing have been used to determine the scalability of each algorithm. The analysis shows that for deterministic exponentially-scaled additively separable, problems, the BB-wise mutation is more efficient than crossover yielding a speedup of Θ(<em>l</em> log<em>l</em>), where <em>l</em> is the problem size. For the noisy exponentially-scaled problems, the outcome depends on whether scaling on noise is dominant. When scaling dominates, mutation is more efficient than crossover yielding a speedup of Θ(<em>l</em> log<em>l</em>). On the other hand, when noise dominates, crossover is more efficient than mutation yielding a speedup of Θ(<em>l</em>).
Analyzing probabilistic models in hierarchical BOA on traps and spin glasseskknsastry
The hierarchical Bayesian optimization algorithm (hBOA) can solve nearly decomposable and hierarchical problems of bounded difficulty in a robust and scalable manner by building and sampling probabilistic models of promising solutions. This paper analyzes probabilistic models in hBOA on two common test problems: concatenated traps and 2D Ising spin glasses with periodic boundary conditions. We argue that although Bayesian networks with local structures can encode complex probability distributions, analyzing these models in hBOA is relatively straightforward and the results of such analyses may provide practitioners with useful information about their problems. The results show that the probabilistic models in hBOA closely correspond to the structure of the underlying optimization problem, the models do not change significantly in subsequent iterations of BOA, and creating adequate probabilistic models by hand is not straightforward even with complete knowledge of the optimization problem.
This document discusses the use of STELLA simulation software to model various systems over time. It provides examples of using STELLA to model predator-prey relationships in an oil palm plantation and to predict climate change scenarios. The document also discusses how simulations like STELLA can encourage student interest and engagement in science learning by making experiments interactive, allowing hypothesis testing, and helping students understand real-world systems.
This document outlines a study on the effect of crop diversity on farm household poverty dynamics in Nigeria. It discusses the motivation, objectives, data, estimation strategy, and results. The study uses panel data from Nigeria from 2010-2016 to estimate an endogenous switching model to assess how crop diversity affects poverty transitions and persistence. It analyzes poverty status in the current and previous period, household retention between periods, and the correlations between error terms to account for unobserved heterogeneity. The results will help identify sustainable agricultural practices that can improve welfare and help households withstand climate change impacts.
This document discusses a study that uses a mixed logit model to predict firm financial distress. Mixed logit is an advanced discrete choice modeling technique that relaxes assumptions of standard logit models. It allows for observed and unobserved heterogeneity across firms. The study aims to demonstrate the empirical usefulness of mixed logit in financial distress prediction by comparing its performance to standard logit models. Results and out-of-sample forecasts show mixed logit outperforms standard logit models by significant margins in predicting firm financial distress.
Fuzzy Logic Approach to Identify Deprivation Index in Peninsular MalaysiajournalBEEI
Deprivation indices are similar to inequalities index or index of disadvantageous. It was built to measure the basic necessities in a specific study area or region. There were many indices that have been constructed in the previous study. However, since these indices had depended mostly on two factors; socio-economic conditions and geography of the study area, thus different result would be generated in different areas. The objective of this study is to construct the new index based on above factors in Peninsular Malaysia by using a fuzzy logic approach. This study employed twelve variables from different facilities condition that was obtained from Malaysia 2000’s census report. These variables were considered as input parameters in the fuzzy logic system. Data turned into linguistic variables and shaped into rules in the form of IF-ELSE conditions. After that, the centroid of area method is applied to acquire the final deprivation index for a specific district in Peninsular Malaysia. The result showed that less developed states generated lower index for examples Kelantan and Kedah while more developed states generated a higher index for examples Selangor and W.P. Kuala Lumpur.
Investigations of certain estimators for modeling panel data under violations...Alexander Decker
This document investigates the efficiency of four methods for estimating panel data models (pooling, first differencing, between, and feasible generalized least squares) when the assumptions of homoscedasticity, no autocorrelation, and no collinearity are jointly violated. Monte Carlo simulations were conducted under varying conditions of heteroscedasticity, autocorrelation, collinearity, sample size, and time periods. The results showed that in small samples, the feasible generalized least squares estimator is most efficient when heteroscedasticity is severe, regardless of autocorrelation and collinearity levels. However, when heteroscedasticity is low to moderate with moderate autocorrelation, first differencing and feasible generalized least squares
Application of Semiparametric Non-Linear Model on Panel Data with Very Small ...IOSRJM
-This research work investigated the behaviour of a new semiparametric non-linear (SPNL) model on
a set of panel data with very small time point (T = 1). The SPNL model incorporates the relationship between
individual independent variable and unobserved heterogeneity variable. Five different estimation techniques
namely; Least Square (LS), Generalized Method of Moments (GMM), Continuously Updating (CU), Empirical
Likelihood (EL) and Exponential Tilting (ET) Estimators were employed for the estimation; for the purpose of
modelling the metrical response variable non-linearly on a set of independent variables. The performances of
these estimators on the SPNL model were examined for different parameters in the model using the Least
Square Error (LSE), Mean Absolute Error (MAE) and Median Absolute Error (MedAE) criteria at the lowest
time point (T = 1). The results showed that the ET estimator which provided the least errors of estimation is
relatively more efficient for the proposed model than any of the other estimators considered. It is therefore
recommended that the ET estimator should be employed to estimate the SPNL model for panel data with very
small time point.
1) This study analyzes spatial effects and conditional convergence theory at the parish level in mainland Portugal from 1991-2001.
2) Statistical analysis shows some positive spatial autocorrelation of product growth, with high-high autocorrelation in coastal parishes and low-low autocorrelation in inland parishes.
3) Estimates using OLS and maximum likelihood methods indicate that when spatial spillover effects are considered, there are indications that spatial factors condition convergence of parish productivity over this period.
Multiple Linear Regression Applications in Real Estate Pricinginventionjournals
In this paper, we attempt to predict the price of a real estate individual homes sold in North West Indiana based on the individual homes sold in 2014. The data/information is collected from realtor.com. The purpose of this paper is to predict the price of individual homes sold based on multiple regression model and also utilize SAS forecasting model and software. We also determine the factors influencing housing prices and to what extent they affect the price. Independent variables such square footage, number of bathrooms, and whether there is a finished basement,. and whether there is brick front or not and the type of home: Colonial, Cotemporary or Tudor. How much does each type of home (Colonial, Contemporary, Tudor) add to the price of the real estate
Multiple Linear Regression Applications in Real Estate Pricinginventionjournals
This document describes using multiple linear regression to predict real estate prices. House price data from 480 homes sold in Indiana in 2014 is used. Independent variables like size, number of bedrooms/bathrooms, and whether there is a basement are considered. Correlations between variables are examined. An initial regression model is developed using all potential predictors. The best fitting model is found to use only homeowner association (HOA) fees as a predictor, with the equation Price=312638+17.854Hoa.
This document discusses using machine learning algorithms to predict household poverty levels. The goals are to build classification models to predict a household's poverty level as either "poor" or "non-poor" based on household attributes. Linear regression is proposed as the modeling algorithm. The document outlines collecting and preprocessing a household dataset, feature selection, model training and evaluation using metrics like MSE, RMSE and R-squared. References are provided on related work applying machine learning to poverty prediction using household surveys and satellite imagery.
An Analysis of Poverty in Italy through a fuzzy regression modelBeniamino Murgante
An Analysis of Poverty in Italy through a fuzzy regression model
Paola Perchinunno, Francesco Campobasso, Annarita Fanizzi, Silvestro Montrone - Department of Statistical Science, University of Bari
What Causes Economic Growth? A Breakdown of The Solow Growth ModelJaredBilberry1
The document summarizes an empirical study examining the Solow growth model and the augmented Solow model developed by Mankiw, Romer and Weil. The study uses data from 1960-1985 for non-oil producing countries to test the relationship between GDP per capita in 1985 and variables for investment, population growth, and secondary education. Descriptive statistics show average GDP increased from 1960 to 1985 while population and investment levels also rose. Correlation analysis found GDP correlated positively with investment and education, but negatively with population growth, supporting the models' predictions.
1. The document provides an introduction to regression models and panel data, outlining key concepts such as the definition of panel data, benefits of using panel data including controlling for individual heterogeneity, and limitations of panel data including problems with data collection.
2. Panel data involves observing the same cross-section of individuals, countries, firms etc. over multiple time periods, allowing analysis of both time and individual variability.
3. Using panel data offers advantages over cross-sectional or time series data alone, such as better accounting for unobserved heterogeneity and enabling analysis of dynamic adjustments over time.
Global demographic trends and future carbon emissions o neill et al_pnas_2010...Adnan Ahmed
This document summarizes a study that analyzed the implications of future demographic trends on global carbon emissions through 2100. Using an energy-economic model called PET, the study found that:
1) Slowing population growth could provide 16-29% of the emissions reductions suggested to avoid dangerous climate change by 2050.
2) Aging populations can substantially reduce emissions in some regions by up to 20% due to lower labor participation rates, while urbanization can increase emissions over 25% from higher productivity.
3) At a global level, the effects of changes in population composition like aging and urbanization are offsetting, but urbanization is a dominant driver of increased emissions in developing countries like China and India.
Application Of Ordinal Logistic Regression In The Study Of Students PerformanceMartha Brown
This document discusses a study that used ordinal logistic regression to analyze factors influencing students' academic performance. The study examined mode of entry, age, department, and sex using data from graduated students at University of Ilorin. The results found that sex was not a determining factor, and there was an equal chance for males and females to graduate with first class honors. Younger students performed better than older ones. Students admitted through direct entry had the highest odds of graduating with first class honors, as these students tended to be more educationally mature.
Hierarchy of Needs and Dynamics of Consumer BehaviorPavel Luksha
Pavel. Luksha. Presentation at the European Association of Evolutionary Political Economists meeting 2004, discussing simulation model of hierarchically organized consumer choice
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document presents a sequential probit model analysis of infant mortality in Nigeria using 2003 Nigeria Demographic and Health Survey data. The analysis examined factors affecting an infant's survival (stage 1) and age at death (stage 2). For stage 1, results showed infant mortality was positively affected by birth order and breastfeeding duration, and negatively affected by mother's education, number of total children born, and place of delivery. For stage 2, only place of delivery significantly affected infant's age at death. The error terms between stages were found to be significantly correlated.
Income and price elasticity of demand quantify the responsiveness of markets to changes in income and in prices, respectively. Under the assumptions of utility maximization and preference independence (additive preferences), mathematical relationships between income elasticity values and the uncompensated own and cross price elasticity of demand are here derived using the differential approach to demand analysis. Key parameters are: the elasticity of the marginal utility of income, and the average budget share. The proposed method can be used to forecast the direct and indirect impact of price changes and of financial instruments of policy using available estimates of the income elasticity of demand.
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0151390
This document discusses spatial data analysis of productivity convergence across regions in Portugal based on convergence theories and spatial econometrics. It analyzes productivity data for different sectors in Portuguese regions using Moran's I statistics, finding positive spatial autocorrelation in productivity for agriculture, services, industry, and total sectors. The document also reviews theories of absolute and conditional convergence and studies examining spatial effects on productivity convergence. It proposes using spatial econometric models and specification tests to analyze conditional productivity convergence across Portuguese regions from 1995 to 2002 while controlling for spatial effects.
This document presents a spatial model analyzing productivity convergence across regions in Portugal from 1995 to 2002. It builds a model using cross-section estimation methods to examine the influence of spatial effects and human capital on conditional productivity convergence across economic sectors in mainland Portugal's NUTS III regions. The results indicate that productivity convergence was greatest in industry and was conditioned by human capital, particularly higher education levels. Spatial spillover effects and spatial autocorrelation did not significantly impact productivity convergence across regions and sectors in the period studied.
This document discusses a regression model to predict soybean crop prices in the US based on various factors from 1995 to 2005. It analyzes factors like temperature, precipitation, crop yield, population, food supply, crude oil prices, and export/import quantities. The regression model explains over 90% of the variation in crop prices based on just four key factors, showing a strong relationship between observed and predicted values.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Total Ionization Cross Sections due to Electron Impact of Ammonia from Thresh...Dr. Amarjeet Singh
In the present paper, we have employed modified Khare-BEB method [Atoms, (2019)] to evaluate total ionization cross sections by the electron impact for ammonia in energy range from the ionization threshold to 10 MeV. The theoretical ionization cross sections have been compared to the available previous theoretical and experimental results. The collision parameters dipole matrix squared M_j^2 and CRP also have been calculated. The present calculations were found in remarkable agreement with the available experimental results.
A Case Study on Small Town Big Player – Enjay IT Solutions Ltd., BhiladDr. Amarjeet Singh
Adequately trained Manpower is a problem that affects the IT industry as a whole, but it is particularly acute for Enjay IT Solution. Enjay's location in a semi-urban or rural area makes it even more difficult to find a talented employee with the right skills. As the competition for skilled workers grows, it becomes more difficult to attract and keep those workers who have the requisite training and experience.
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Similar to The Likelihood Ratio Test in Structural Equation Models: A Multi-Group Approach to Portuguese Material Deprivation
Investigations of certain estimators for modeling panel data under violations...Alexander Decker
This document investigates the efficiency of four methods for estimating panel data models (pooling, first differencing, between, and feasible generalized least squares) when the assumptions of homoscedasticity, no autocorrelation, and no collinearity are jointly violated. Monte Carlo simulations were conducted under varying conditions of heteroscedasticity, autocorrelation, collinearity, sample size, and time periods. The results showed that in small samples, the feasible generalized least squares estimator is most efficient when heteroscedasticity is severe, regardless of autocorrelation and collinearity levels. However, when heteroscedasticity is low to moderate with moderate autocorrelation, first differencing and feasible generalized least squares
Application of Semiparametric Non-Linear Model on Panel Data with Very Small ...IOSRJM
-This research work investigated the behaviour of a new semiparametric non-linear (SPNL) model on
a set of panel data with very small time point (T = 1). The SPNL model incorporates the relationship between
individual independent variable and unobserved heterogeneity variable. Five different estimation techniques
namely; Least Square (LS), Generalized Method of Moments (GMM), Continuously Updating (CU), Empirical
Likelihood (EL) and Exponential Tilting (ET) Estimators were employed for the estimation; for the purpose of
modelling the metrical response variable non-linearly on a set of independent variables. The performances of
these estimators on the SPNL model were examined for different parameters in the model using the Least
Square Error (LSE), Mean Absolute Error (MAE) and Median Absolute Error (MedAE) criteria at the lowest
time point (T = 1). The results showed that the ET estimator which provided the least errors of estimation is
relatively more efficient for the proposed model than any of the other estimators considered. It is therefore
recommended that the ET estimator should be employed to estimate the SPNL model for panel data with very
small time point.
1) This study analyzes spatial effects and conditional convergence theory at the parish level in mainland Portugal from 1991-2001.
2) Statistical analysis shows some positive spatial autocorrelation of product growth, with high-high autocorrelation in coastal parishes and low-low autocorrelation in inland parishes.
3) Estimates using OLS and maximum likelihood methods indicate that when spatial spillover effects are considered, there are indications that spatial factors condition convergence of parish productivity over this period.
Multiple Linear Regression Applications in Real Estate Pricinginventionjournals
In this paper, we attempt to predict the price of a real estate individual homes sold in North West Indiana based on the individual homes sold in 2014. The data/information is collected from realtor.com. The purpose of this paper is to predict the price of individual homes sold based on multiple regression model and also utilize SAS forecasting model and software. We also determine the factors influencing housing prices and to what extent they affect the price. Independent variables such square footage, number of bathrooms, and whether there is a finished basement,. and whether there is brick front or not and the type of home: Colonial, Cotemporary or Tudor. How much does each type of home (Colonial, Contemporary, Tudor) add to the price of the real estate
Multiple Linear Regression Applications in Real Estate Pricinginventionjournals
This document describes using multiple linear regression to predict real estate prices. House price data from 480 homes sold in Indiana in 2014 is used. Independent variables like size, number of bedrooms/bathrooms, and whether there is a basement are considered. Correlations between variables are examined. An initial regression model is developed using all potential predictors. The best fitting model is found to use only homeowner association (HOA) fees as a predictor, with the equation Price=312638+17.854Hoa.
This document discusses using machine learning algorithms to predict household poverty levels. The goals are to build classification models to predict a household's poverty level as either "poor" or "non-poor" based on household attributes. Linear regression is proposed as the modeling algorithm. The document outlines collecting and preprocessing a household dataset, feature selection, model training and evaluation using metrics like MSE, RMSE and R-squared. References are provided on related work applying machine learning to poverty prediction using household surveys and satellite imagery.
An Analysis of Poverty in Italy through a fuzzy regression modelBeniamino Murgante
An Analysis of Poverty in Italy through a fuzzy regression model
Paola Perchinunno, Francesco Campobasso, Annarita Fanizzi, Silvestro Montrone - Department of Statistical Science, University of Bari
What Causes Economic Growth? A Breakdown of The Solow Growth ModelJaredBilberry1
The document summarizes an empirical study examining the Solow growth model and the augmented Solow model developed by Mankiw, Romer and Weil. The study uses data from 1960-1985 for non-oil producing countries to test the relationship between GDP per capita in 1985 and variables for investment, population growth, and secondary education. Descriptive statistics show average GDP increased from 1960 to 1985 while population and investment levels also rose. Correlation analysis found GDP correlated positively with investment and education, but negatively with population growth, supporting the models' predictions.
1. The document provides an introduction to regression models and panel data, outlining key concepts such as the definition of panel data, benefits of using panel data including controlling for individual heterogeneity, and limitations of panel data including problems with data collection.
2. Panel data involves observing the same cross-section of individuals, countries, firms etc. over multiple time periods, allowing analysis of both time and individual variability.
3. Using panel data offers advantages over cross-sectional or time series data alone, such as better accounting for unobserved heterogeneity and enabling analysis of dynamic adjustments over time.
Global demographic trends and future carbon emissions o neill et al_pnas_2010...Adnan Ahmed
This document summarizes a study that analyzed the implications of future demographic trends on global carbon emissions through 2100. Using an energy-economic model called PET, the study found that:
1) Slowing population growth could provide 16-29% of the emissions reductions suggested to avoid dangerous climate change by 2050.
2) Aging populations can substantially reduce emissions in some regions by up to 20% due to lower labor participation rates, while urbanization can increase emissions over 25% from higher productivity.
3) At a global level, the effects of changes in population composition like aging and urbanization are offsetting, but urbanization is a dominant driver of increased emissions in developing countries like China and India.
Application Of Ordinal Logistic Regression In The Study Of Students PerformanceMartha Brown
This document discusses a study that used ordinal logistic regression to analyze factors influencing students' academic performance. The study examined mode of entry, age, department, and sex using data from graduated students at University of Ilorin. The results found that sex was not a determining factor, and there was an equal chance for males and females to graduate with first class honors. Younger students performed better than older ones. Students admitted through direct entry had the highest odds of graduating with first class honors, as these students tended to be more educationally mature.
Hierarchy of Needs and Dynamics of Consumer BehaviorPavel Luksha
Pavel. Luksha. Presentation at the European Association of Evolutionary Political Economists meeting 2004, discussing simulation model of hierarchically organized consumer choice
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document presents a sequential probit model analysis of infant mortality in Nigeria using 2003 Nigeria Demographic and Health Survey data. The analysis examined factors affecting an infant's survival (stage 1) and age at death (stage 2). For stage 1, results showed infant mortality was positively affected by birth order and breastfeeding duration, and negatively affected by mother's education, number of total children born, and place of delivery. For stage 2, only place of delivery significantly affected infant's age at death. The error terms between stages were found to be significantly correlated.
Income and price elasticity of demand quantify the responsiveness of markets to changes in income and in prices, respectively. Under the assumptions of utility maximization and preference independence (additive preferences), mathematical relationships between income elasticity values and the uncompensated own and cross price elasticity of demand are here derived using the differential approach to demand analysis. Key parameters are: the elasticity of the marginal utility of income, and the average budget share. The proposed method can be used to forecast the direct and indirect impact of price changes and of financial instruments of policy using available estimates of the income elasticity of demand.
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0151390
This document discusses spatial data analysis of productivity convergence across regions in Portugal based on convergence theories and spatial econometrics. It analyzes productivity data for different sectors in Portuguese regions using Moran's I statistics, finding positive spatial autocorrelation in productivity for agriculture, services, industry, and total sectors. The document also reviews theories of absolute and conditional convergence and studies examining spatial effects on productivity convergence. It proposes using spatial econometric models and specification tests to analyze conditional productivity convergence across Portuguese regions from 1995 to 2002 while controlling for spatial effects.
This document presents a spatial model analyzing productivity convergence across regions in Portugal from 1995 to 2002. It builds a model using cross-section estimation methods to examine the influence of spatial effects and human capital on conditional productivity convergence across economic sectors in mainland Portugal's NUTS III regions. The results indicate that productivity convergence was greatest in industry and was conditioned by human capital, particularly higher education levels. Spatial spillover effects and spatial autocorrelation did not significantly impact productivity convergence across regions and sectors in the period studied.
This document discusses a regression model to predict soybean crop prices in the US based on various factors from 1995 to 2005. It analyzes factors like temperature, precipitation, crop yield, population, food supply, crude oil prices, and export/import quantities. The regression model explains over 90% of the variation in crop prices based on just four key factors, showing a strong relationship between observed and predicted values.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
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Total Ionization Cross Sections due to Electron Impact of Ammonia from Thresh...Dr. Amarjeet Singh
In the present paper, we have employed modified Khare-BEB method [Atoms, (2019)] to evaluate total ionization cross sections by the electron impact for ammonia in energy range from the ionization threshold to 10 MeV. The theoretical ionization cross sections have been compared to the available previous theoretical and experimental results. The collision parameters dipole matrix squared M_j^2 and CRP also have been calculated. The present calculations were found in remarkable agreement with the available experimental results.
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Adequately trained Manpower is a problem that affects the IT industry as a whole, but it is particularly acute for Enjay IT Solution. Enjay's location in a semi-urban or rural area makes it even more difficult to find a talented employee with the right skills. As the competition for skilled workers grows, it becomes more difficult to attract and keep those workers who have the requisite training and experience.
Effect of Biopesticide from the Stems of Gossypium Arboreum on Pink Bollworm ...Dr. Amarjeet Singh
Pink bollworm and Lepidoptera development quickly in numbers which is a typical animal group that produces around 100 youthful ones inside certain days or weeks. This assault influences the harvests broadly in the tropical and sub-tropical temperature areas. Thus, to keep up with the yield of harvests the vermin ought to be kept away by utilizing pesticides. The unnecessary measure of the purpose of pesticides influences the dirt, land, and as well as human well-being, and contaminates the climate. Thus, an ozone-accommodating biopesticide is extracted from the stems of the Gossypium arboreum. Thus, the extraction of biopesticide from the stems of Gossypium arboreum demonstrated that the quantity of pink bollworm and Lepidoptera is diminished step by step in the wake of showering the arrangement on the impacted region of the plant because of the presence of the gossypol.
Artificial Intelligence Techniques in E-Commerce: The Possibility of Exploiti...Dr. Amarjeet Singh
This document discusses the potential applications of artificial intelligence techniques in e-commerce in Saudi Arabia. It begins with an introduction to e-commerce and AI, and how AI is being used increasingly in e-commerce applications worldwide. It then reviews literature on how AI can be integrated into e-commerce systems and the various applications of AI in e-commerce. Some key applications discussed include AI assistants, personalized recommendations, demand forecasting, supply chain management, fraud detection and more. The document concludes that Saudi Arabia is well positioned to benefit from using AI to boost its growing e-commerce sector.
Factors Influencing Ownership Pattern and its Impact on Corporate Performance...Dr. Amarjeet Singh
This document summarizes a research study that analyzed the factors influencing ownership patterns of selected Indian companies and the impact of ownership patterns on corporate performance. The study used data from 5 industries over 5 years from 2017 to 2021. Multiple regression, ANOVA, and correlation analyses were conducted. The results found that the percentage of independent directors on the board and the size of the company had a significant impact on Indian promoter holdings. Additionally, non-institutional ownership was found to have a significant impact on corporate performance measures like asset utilization ratio. The study concluded that ownership patterns can influence corporate performance and companies should work to optimize factors like debt-equity ratio and board independence to improve financial outcomes.
An Analytical Study on Ratios Influencing Profitability of Selected Indian Au...Dr. Amarjeet Singh
Every country with a well-developed transportation network has a well-developed economy. The automobile industry is a critical engine of the nation's economic development. The automobile industry has significant backward and forward links with every area of the economy, as well as a strong and progressive multiplier impact. The automotive industry and the auto component industry are both included in the vehicle industry. It includes passenger waggons, light, medium, and heavy commercial vehicles, as well as multi-utility vehicles such as jeeps, three-wheelers, military vehicles, motorcycles, tractors, and auto-components such as engine parts, batteries, drive transmission parts, electrical, suspension and chassis parts, and body and other parts. In the last several years, India's automobile sector has seen incredible growth in sales, production, innovation, and exports. India's car industry has emerged as one of the best in the world, and the auto-ancillary sector is poised to assist the vehicle sector's expansion. Vehicle manufacturers and auto-parts manufacturers account for a significant component of global motorised manufacturing. Vehicle manufacturers from across the world are keeping a close eye on the Indian auto sector in order to assess future demand and establish India as a global manufacturing base. The current research focuses on three automotive behemoths: TATA Motors, MRF, and Mahindra & Mahindra.
A Study on Factors Influencing the Financial Performance Analysis Selected Pr...Dr. Amarjeet Singh
The growth of a country's banking sector has a significant impact on its economic development. The banking sector plays a critical role in determining a country's economic future. A well-planned, structured, efficient, and viable banking system is an essential component of an economy's economic and social infrastructure. In modern society, a strong banking system is required because it meets the financial needs of the modern society. In a country's economy, the banking system plays a crucial role. Because it connects surplus and deficit economic agents, the bank is the most important financial intermediary in the economy. The banking system is regarded as the economy's lifeline. It meets the financial needs of commerce, industry, and agriculture. As a result, the country's development and the banking system are intertwined. They are critical in the mobilisation of savings and the distribution of credit to various sectors of the economy. India's private sector banks play a critical role in the country's economic development. So The financial performance of private sector banks must be evaluated carefully.
An Empirical Analysis of Financial Performance of Selected Oil Exploration an...Dr. Amarjeet Singh
After the United States, China, and Japan, India was the world's fourth biggest consumer of oil and petroleum products. The nation is significantly reliant on crude oil imports, the majority of which come from the Middle East. The Indian oil and gas business is one of the country's six main sectors, with important forward links to the rest of the economy. More than two-thirds of the country's overall primary energy demands are met by the oil and gas industry. The industry has played a key role in placing India on the global map. India is now the world's sixth biggest crude oil user and ninth largest crude oil importer. In addition, the country's portion of the worldwide refining market is growing. India's refining industry is now the world's sixth biggest. With plans for Reliance Petroleum Limited to commission another refinery with a capacity of 29 MTPA next 16 to its 33 MTPA refinery in Jamnagar, Gujarat, this position is projected to be enhanced. As a consequence, the Reliance refinery would be the biggest single-site refinery in the world. Based on secondary data gathered from CMIE, the current research examines the ratios influencing the profitability of selected oil exploration and production businesses in India during a 10-year period.
Since 1991, thanks to economic policy liberalization, the Indian economy has entered an era in which Indian businesses can no longer disregard global markets. Prior to the 1990s, the prices of a variety of commodities, metals, and other assets were carefully regulated. Others, which were not rolled, were primarily dependant on regulated input costs. As a result, there was no uncertainty and, as a result, no price fluctuations. However, in 1991, when the process of deregulation began, the prices of most items were deregulated. It has also resulted in the exchange being partially deregulated, easing trade restrictions, lowering interest rates, and making significant advancements in foreign institutional investors' access to the capital markets, as well as establishing market-based government securities pricing, among other things. Furthermore, portfolio and securities price volatility and instability were influenced by market-determined exchange rates and interest rates. As a result, hedging strategies employing a variety of derivatives were exposed to a variety of risks. The Indian capital market will be examined in this study, with a focus on derivatives.
Theoretical Estimation of CO2 Compression and Transport Costs for an hypothet...Dr. Amarjeet Singh
This document discusses theoretical estimates for the costs of compressing and transporting CO2 from a hypothetical carbon capture and storage project at the Saline Joniche Power Plant in Italy. It first provides background on the power plant project from 2008 that proposed converting the site to coal power. It then details the methodology used to size the compression system, estimating power needs for multi-stage compression up to pipeline pressures. Costs are considered for constructing, operating, and maintaining both the compression plant and pipeline to a potential offshore storage site. The aim is to evaluate retrofitting the existing plant with carbon capture and storage as a way to enable continued coal power production consistent with climate goals.
Analytical Mechanics of Magnetic Particles Suspended in Magnetorheological FluidDr. Amarjeet Singh
In this paper, the behavior of MR particles has been systematically investigated within the scope of analytical mechanics. . A magnetorheological fluid belongs to a class of smart materials. In magnetorheological fluids, the motion of magnetic particles is controlled by the action of internal and external forces. This paper presents analytical mechanics for the interaction of system of particles in MR fluid. In this paper, basic principles of Analytical Mechanics are utilized for the construction of equations.
Techno-Economic Aspects of Solid Food Wastes into Bio-ManureDr. Amarjeet Singh
Solid waste is health hazard and cause damage to the environment due to improper handling. Solid waste comprises of Industrial Waste (IW), Hazardous Waste (HW), Municipal Solid Waste (MSW), Electronic waste (E-waste), Bio-Medical Waste (BMW) which depend on their supply & characteristics. Food waste or Bio-waste composting and its role in sustainable development is explained in food waste is a growing area of concern with many costs to our community in terms of waste collection, disposal and greenhouse gases. When rotting food ends up in landfill it turns into methane, a greenhouse gas that is particularly damaging to the environment. Composting is biochemical process in which organic materials are biologically degraded, resulting in the production of organic by products and energy in the form of heat. Heat is trapped within the composting mass, leading to the phenomenon of self-heating. This overall process provide us Bio-Manure.
Crypto-Currencies: Can Investors Rely on them as Investment Avenue?Dr. Amarjeet Singh
The purpose of this study is to examine investors’ perceptions about investing in crypto-currencies. We think that investors trust in crypto-currencies is largely driven by crypto-currency comprehension, trust in government, and transaction speed. This is the first study to examine crypto-currencies from the investor’s perspective. Following that, we discover important antecedents of crypto-currency confidence. Second, we look at the government's role in crypto-currencies. The importance of this study is: first, crypto-currencies have the potential to disrupt the current economic system as the debate is all about impact of decentralization of transactions; thus, further research into how it affects investors trust is essential; and second, access to crypto-currencies. Finally, if Fin-Tech companies or banks want to enter the bitcoin industry may not attract huge advertising costs as well as marketing to soothe clients' concerns about investing in various digital currencies The research sheds light on indecisiveness in the context of marketing aspects adopted by demonstrating investors are aware about the crypto.
Awareness of Disaster Risk Reduction (DRR) among Student of the Catanduanes S...Dr. Amarjeet Singh
The Island Province of Catanduanes is prone to all types of natural hazards that includes torrential and heavy rains, strong winds and surge, flooding and landslide or slope failures as a result of its geographical location and topography. RA 10121 mandates local DRRM bodies to “encourage community, specifically the youth, participation in disaster risk reduction and management activities, such as organizing quick response groups, particularly in identified disaster-prone areas, as well as the inclusion of disaster risk reduction and management programs as part of youth programs and projects. The study aims to determine the awareness to disaster of the student of the Catanduanes State University. The disaster-based questionnaire was prepared and distributed among 636 students selected randomly from different Colleges and Laboratory Schools in the University
The Catanduanes State University students understood some disaster-related concepts and ideas, but uncertain on issues on preparedness, adaptation, and awareness on the risks inflicted by these natural hazards. Low perception on disaster risks are evidently observed among students. The responses of the students could be based on the efficiency and impact of the integration of DRR education in the senior high school curriculum. Specifically, integration of the concepts about the hazards, hazard maps, disaster preparedness, awareness, mitigation, prevention, adaptation, and resiliency in the science curriculum possibly affect the knowledge and understanding of students on DRR. Preparedness drills and other forms of capacity building must be done to improve awareness of the student towards DRRM.
The study further recommends that teachers and instructor must also be capacitated in handling disaster as they are the prime movers in the implementation of the DRRM in education. Preparedness drills and other forms of capacity building must be done to improve awareness of the student towards DRRM. Core subjects in Earth Sciences must be reinforced with geologic hazards. Learning competencies must also be focused on hazard identification and mapping, and coping with different geologic disaster.
The 1857 war was a watershed moment in the history of the Indian subcontinent. The battle has sparked academic debate among historians and sociologists all around the world. Despite the fact that it has been more than 150 years, this battle continues to pique the interest of historians. The war's causes and events that occurred throughout the conflict, persons who backed the British and anti-British fighters, and the results and ramifications, are all aspects of this conflict. In terms of outcomes, many academics believe that the war was a failure for those who started it. It is often assumed that the Indians who battled the British in this conflict were unable to achieve their goals. Many gains accrued to Indians as a result of the conflict, but these achievements are overshadowed by the dispute over the war's failure. This research effort focuses on the war's achievements for India, and the significance of those achievements.
Haryana's Honour Killings: A Social and Legal Point of ViewDr. Amarjeet Singh
Life is unpredictably unpredictable. Nobody knows what will happen in the next minute of their lives. In this circumstance, every human being has the right and desire to conduct their lives according to their own desires. No one should be forced to live a life solely for the benefit and reputation of others. Honour killing is defined as the assassination of a person, whether male or female, who refuses to accept the family's arranged marriage or decides to move her or his marital life according to her or his wishes solely because it jeopardizes the family's honour. The family's supreme authority looks after the family's name but neglects to consider the love and affection shared among family members. I have discussed honour killing in India in my research work. This sort of murder occurs as a result of particular triggers, which are also examined in relation to the role of the law in honour killing. No one can be released free if they break the law, and in this case, it is a felony that violates various regulations designed to safeguard citizens. This crime is similar to many others, but it is distinct enough to be differentiated in the report. When the husband is of low social standing, it lowers the position and caste of the female family, prompting the male family members to murder the girl. But they forget that the girl is their kid and that while rank may be attained, a girl's life can never be replaced, and that caste is less valuable than the girl's life and love spent with them.
Optimization of Digital-Based MSME E-Commerce: Challenges and Opportunities i...Dr. Amarjeet Singh
This document summarizes a research article about optimizing digital-based MSME e-commerce during the COVID-19 pandemic. The article discusses how the pandemic severely impacted MSMEs, with many going out of business. However, digitalization and e-commerce provide opportunities for MSMEs to transform their business models. The article reviews literature showing how technologies like websites, social media, and mobile applications can help MSMEs reach more customers online. Case studies of MSMEs in different countries found that those utilizing digital tools through e-commerce were more successful compared to those relying only on offline sales. The article concludes digitalization is both a challenge and opportunity for MSMEs to adapt their traditional business models and survive or grow
Modal Space Controller for Hydraulically Driven Six Degree of Freedom Paralle...Dr. Amarjeet Singh
This paper presents the Modal space decoupled control for a hydraulically driven parallel mechanism has been presented. The approach is based on singular values decomposition to the properties of joint-space inverse mass matrix, and mapping of the control and feedback variables from the joint space to the decoupling modal space. The method transformed highly coupled six-input six-output dynamics into six independent single-input single-output (SISO) 1 DOF hydraulically driven mechanical systems. The novelty in this method is that the signals including control errors, control outputs and pressure feedbacks are transformed into decoupled modal space and also the proportional gains and dynamic pressure feedback are tuned in modal space. The results indicate that the conventional controller can only attenuate the resonance peaks of the lower eigenfrequencies of six rigid modes properly, and the peaking points of other relative higher eigenfrequencies are over damped, The further results show that it is very effective to design and tune the system in modal space and that the bandwidth increased substantially except surge (x) and sway (y) motions, each degree of freedom can be almost tuned independently and their bandwidths can be increased near to the undamped eigenfrequencies.
It is a known fact that a large number of Steel Industry Expansion projects in India have been delayed due to regulatory clearances, environmental issues and problems pertaining to land acquisition. Also, there are challenges in the tendering phase that affect viability of projects thus delaying implementation, construction phase is beset with over-runs and disputes and last but not the least; provider skills are weak all across the value chain. Given the critical role of Steel Sector in ensuring a sustained growth trajectory for India, it is imperative that we identify the core issues affecting completion of infrastructure projects in India and chalk out initiatives that need to be acted upon in short term as well as long term.
A blockchain is a decentralised database that is shared across computer network nodes. A blockchain acts as a database, storing information in a digital format. The study primarily aims to explore how in the future, block chain technology will alter several areas of the Indian economy. The current study aims to obtain a deeper understanding of blockchain technology's idea and implementation in India, as well as the technology's potential as a disruptive financial technological innovation.
Secondary sources such as reports, journals, papers, and websites were used to compile all the data. Current and relevant information were utilised to help understand the research goals. All the information is rationally organised to fulfil the objectives. The current research focuses on recommendations for enhancing India's Blockchain ecosystem so that it may become one of the best in the world at utilising this new technology.
Org Design is a core skill to be mastered by management for any successful org change.
Org Topologies™ in its essence is a two-dimensional space with 16 distinctive boxes - atomic organizational archetypes. That space helps you to plot your current operating model by positioning individuals, departments, and teams on the map. This will give a profound understanding of the performance of your value-creating organizational ecosystem.
Comparing Stability and Sustainability in Agile SystemsRob Healy
Copy of the presentation given at XP2024 based on a research paper.
In this paper we explain wat overwork is and the physical and mental health risks associated with it.
We then explore how overwork relates to system stability and inventory.
Finally there is a call to action for Team Leads / Scrum Masters / Managers to measure and monitor excess work for individual teams.
A team is a group of individuals, all working together for a common purpose. This Ppt derives a detail information on team building process and ats type with effective example by Tuckmans Model. it also describes about team issues and effective team work. Unclear Roles and Responsibilities of teams as well as individuals.
Public Speaking Tips to Help You Be A Strong Leader.pdfPinta Partners
In the realm of effective leadership, a multitude of skills come into play, but one stands out as both crucial and challenging: public speaking.
Public speaking transcends mere eloquence; it serves as the medium through which leaders articulate their vision, inspire action, and foster engagement. For leaders, refining public speaking skills is essential, elevating their ability to influence, persuade, and lead with resolute conviction. Here are some key tips to consider: https://joellandau.com/the-public-speaking-tips-to-help-you-be-a-stronger-leader/
Ganpati Kumar Choudhary Indian Ethos PPT.pptx, The Dilemma of Green Energy Corporation
Green Energy Corporation, a leading renewable energy company, faces a dilemma: balancing profitability and sustainability. Pressure to scale rapidly has led to ethical concerns, as the company's commitment to sustainable practices is tested by the need to satisfy shareholders and maintain a competitive edge.
Employment PracticesRegulation and Multinational CorporationsRoopaTemkar
Employment PracticesRegulation and Multinational Corporations
Strategic decision making within MNCs constrained or determined by the implementation of laws and codes of practice and by pressure from political actors. Managers in MNCs have to make choices that are shaped by gvmt. intervention and the local economy.
Originally presented at XP2024 Bolzano
While agile has entered the post-mainstream age, possibly losing its mojo along the way, the rise of remote working is dealing a more severe blow than its industrialization.
In this talk we'll have a look to the cumulative effect of the constraints of a remote working environment and of the common countermeasures.
Sethurathnam Ravi: A Legacy in Finance and LeadershipAnjana Josie
Sethurathnam Ravi, also known as S Ravi, is a distinguished Chartered Accountant and former Chairman of the Bombay Stock Exchange (BSE). As the Founder and Managing Partner of Ravi Rajan & Co. LLP, he has made significant contributions to the fields of finance, banking, and corporate governance. His extensive career includes directorships in over 45 major organizations, including LIC, BHEL, and ONGC. With a passion for financial consulting and social issues, S Ravi continues to influence the industry and inspire future leaders.
Impact of Effective Performance Appraisal Systems on Employee Motivation and ...Dr. Nazrul Islam
Healthy economic development requires properly managing the banking industry of any
country. Along with state-owned banks, private banks play a critical role in the country's economy.
Managers in all types of banks now confront the same challenge: how to get the utmost output from
their employees. Therefore, Performance appraisal appears to be inevitable since it set the
standard for comparing actual performance to established objectives and recommending practical
solutions that help the organization achieve sustainable growth. Therefore, the purpose of this
research is to determine the effect of performance appraisal on employee motivation and retention.
Enriching engagement with ethical review processesstrikingabalance
New ethics review processes at the University of Bath. Presented at the 8th World Conference on Research Integrity by Filipa Vance, Head of Research Governance and Compliance at the University of Bath. June 2024, Athens
Colby Hobson: Residential Construction Leader Building a Solid Reputation Thr...dsnow9802
Colby Hobson stands out as a dynamic leader in the residential construction industry. With a solid reputation built on his exceptional communication and presentation skills, Colby has proven himself to be an excellent team player, fostering a collaborative and efficient work environment.
12 steps to transform your organization into the agile org you deservePierre E. NEIS
During an organizational transformation, the shift is from the previous state to an improved one. In the realm of agility, I emphasize the significance of identifying polarities. This approach helps establish a clear understanding of your objectives. I have outlined 12 incremental actions to delineate your organizational strategy.