Human Capital Development Typology: A Case Study of the Saudi Arabia

Saudi government is struggling to build knowledge based society to encounter social and economic challenges for the year 2030, when oil supply will be just sufficient to meet local Saudi demands. This study embarks upon the importance of the mixed-economy for sustainable growth in the 21st century. This study investigates three objectives. Firstly, it highlights Saudi socio-economic challenges. Secondly, it identifies alternative ways to realize the vision of mixed economic model for oil driven economy. Thirdly, it identifies the relationship between human capital and Saudi economic indicators. This research presents a typology based upon econometric models using secondary data, collected from World-Bank, World Health Organization (2013) and Saudi Monitory Agency annual statistical data-streams. It is recommended that the Saudi youth can play a vital role in economic growth subject to change in their mindset to overcome artificial joblessness among the Saudis

Análise de desenhos experimentais com outliers

Primary purpose of the article is to develop outlier robust designs. As a matter of fact, negative effect of outliers in any experimental settings is established where the outliers at any specific design point can destroy the features of the design for which it is being developed. It is attempted here in this article to develop a version of robustness for central composite designs which may protect it for outliers by introducing the idea of minimax outlying effect. This involves the calculation of the degree of outlying effect(s) outlier(s) may produce and then minimize the maximum of these outlying effects in an attempt to equalize the influence of all design points. On comparison, these outlier robust designs are proved to be more optimal, on the scales of A, D, and E optimalities, against existing conventional rotatable, orthogonal, and other such designs. The outlier robust designs, developed here, are suitable for settings prone to outliers where conventional designs fail to represent and analyze the processes and systems.El objetivo principal del artículo es desarrollar diseños robustos atípicos. De hecho, el efecto negativo de los valores atípicos en cualquier configuración experimental se establece donde los valores atípicos en cualquier punto de diseño específico pueden destruir las características del diseño para el que se está desarrollando. En este artículo se intenta desarrollar una versión de robustez para los diseños compuestos centrales que pueden protegerlo de los valores atípicos mediante la introducción de la idea del efecto periférico minimax. Esto implica el cálculo del grado de efecto (s) externo (s) que puede producir un valor atípico y luego minimizar el máximo de estos efectos externos en un intento de igualar la influencia de todos los puntos de diseño. En comparación, se demuestra que estos diseños robustos atípicos son más óptimos, en las escalas de las optimidades A, D y E, frente a los diseños convencionales existentes, ortogonales, rotativos y otros similares. Los diseños robustos atípicos, desarrollados aquí, son adecuados para configuraciones propensas a los valores atípicos en los que los diseños convencionales no representan ni analizan los procesos y sistemas.Objetivo principal do artigo é desenvolver projetos robustos outlier. De fato, o efeito negativo de outliers em qualquer ambiente experimental é estabelecido onde os outliers em qualquer ponto de design específico podem destruir os recursos do design para o qual ele está sendo desenvolvido. Neste artigo, tenta-se desenvolver uma versão de robustez para projetos compostos centrais que possam protegê-lo de outliers, introduzindo a ideia de efeito periférico minimax. Isso envolve o cálculo do grau de efeito (s) outlier (s) outlier (s) pode produzir e, em seguida, minimizar o máximo desses efeitos periféricos em uma tentativa de equalizar a influência de todos os pontos do projeto. Em comparação, esses designs robustos discrepantes são comprovadamente mais otimizados, nas escalas de otimalidades A, D e E, contra os designs convencionais rotacionais, ortogonais e outros existentes. Os designs robustos outlier, desenvolvidos aqui, são adequados para configurações propensas a outliers em que projetos convencionais não representam e analisam os processos e sistemas

OUTLIER ROBUST DRAPER & LIN DESIGNS

Design robustness to a single outlier is studied for Draper (1990)designs by introducing and applying minimax outlier effect criterion. The criterion uses outlying effect of design points and attempts to minimizes the maximum outlying effect for a design point to have design with almost equal outlying effects and the design is adjusted for maximum outlying effect. Resultant outlier robust Draper & Lin designs have been exhibited as more compact, so less resource intensive, as compare to the other existing equivalent designs

Are Computer Experience and Anxiety Irrelevant? Towards a Simple Model for Adoption of E-Learning Systems

Massive growth of technology based e-learning systems is enabling student access to academic content from higher education institutions around the world. This study explores the antecedents of behavioral intention of students to use e-learning systems in university education to supplement classroom learning. A quantitative approach involving a structural equation model is adopted and research data collected from 358 undergraduate students is used for analysis. The study framework is based upon the technology acceptance model (TAM) and three external factors are proposed to influence the behavioral intention of students to use e-learning. Frequently used external factors in previous researches like computer experience and anxiety were not used and alternate factors were explored. Results show that self-efficacy, enjoyment and results demonstrability have a significant positive influence on perceived usefulness and on perceived ease of use of the e-learning system. The study contributes to understanding such contributory factors from the viewpoint of a student by suggesting that these factors hold well in the Pakistani academia culture where sufficient relevant empirical evidence did not exist due to lack of prior studies

An Empirical Study Analyzing Job Productivity in Toxic Workplace Environments

Purpose: This empirical study aims to determine the effects of a toxic workplace environment, which can negatively impact the job productivity of an employee. Methodology: Three hundred questionnaires were randomly distributed among the staff members of seven private universities in Pakistan with a final response rate of 89%. For analysis purposes, AMOS 22 was used to study the direct and indirect effects of the toxic workplace environment on job productivity. Confirmatory Factor Analysis (CFA) was conducted to ensure the convergent and discriminant validity of the factors, while the Hayes mediation approach was used to verify the mediating role of job burnout between the four dimensions of toxic workplace environment and job productivity. A toxic workplace with multiple dimensions, such as workplace ostracism, workplace incivility, workplace harassment, and workplace bullying, was used in this study. Findings: By using the multiple statistical tools and techniques, it has been proven that ostracism, incivility, harassment, and bullying have direct negative significant effects on job productivity, while job burnout was shown to be a statistical significant mediator between the dimensions of a toxic workplace environment and job productivity. Finally, we concluded that organizations need to eradicate the factors of toxic workplace environments to ensure their prosperity and success. Practical Implications: This study encourages managers, leaders, and top management to adopt appropriate policies for enhancing employees’ productivity. Limitations: This study was conducted by using a cross-sectional research design. Future research aims to expand the study by using a longitudinal research design

Prediction of rock interlocking by developing two hybrid models based on GA and fuzzy system

Rock shear strength parameters (interlocking and internal friction angel) are considered as significant factors in the designing stage of various geotechnical structures such as tunnels and foundations. Direct determination of these parameters in laboratory is time-consuming and expensive. Additionally, preparation of good quality of core samples is sometimes difficult. The objective of this paper is introducing and evaluating two hybrid artificial neural network (ANN)-based models by considering genetic algorithm (GA) and fuzzy inference system for prediction of interlocking of shale rock samples. Therefore, hybrid GA-ANN and adoptive neuro-fuzzy inference system (ANFIS) were developed and to show the capability of the hybrid models, the predicted results were compared to those of a pre-developed ANN model. In development of these models, the results of rock index tests, i.e., point load index, dry density, p-wave velocity, Brazilian tensile strength and Schmidt hammer were taken into account as the input parameters, whereas the interlocking of the shale samples was set as the output. The results obtained in this study confirmed the high reliability of the developed hybrid models, however, ANFIS predictive model receives slightly higher performance prediction compared to GA-ANN technique. The obtained results of the developed models were (0.865, 0.852), (0.933, 0.929) and (0.957, 0.965) for ANN, GA-ANN and ANFIS models, respectively, based on coefficient of determination (R2). ANFIS can be introduced as an innovative model to the field of rock mechanics

Developing and testing student engagement scale for higher educational students

PurposeThe purpose of this study is to develop and empirically test the student engagement scale and to understand the factors that contribute to student engagement at higher educational institutions.Design/methodology/approachThe investigation started with a rummage for variables, available in the literature, 59 in numbers, which were then used to collect data from a sample of university students in Lahore, Pakistan. An exploratory factor analysis (EFA) was applied to develop an initial structure of the construct. A confirmatory factor analysis (CFA) was then conducted to confirm the reliability and validity of these factors for the student engagement construct.FindingsIt has been found that factors, predominantly social and exogenous to the classroom environment, such as campus atmosphere and facilities, are more responsible for creating engagement among students at higher educational institutions of Pakistan.Originality/valueThis is one of the pioneer studies for developing a student engagement scale for measuring the students' engagement in higher educational institutions. The authors believe that the scale developed in this study contributes substantially to the student engagement literature. Limitations, future research directions and implications are discussed.</jats:sec

Structural Equation Model for Evaluating Factors Affecting Quality of Social Infrastructure Projects

The quality of the constructed social infrastructure project has been considered a necessary measure for the sustainability of projects. Studies on factors affecting project quality have used various techniques and methods to explain the relationships between particular variables. Unexpectedly, Structural Equation Modeling (SEM) has acquired very little concern in factors affecting project quality studies. To address this limitation in the body of knowledge, the objective of this study was to apply the SEM approach and build a model that explained and identified the critical factors affecting quality in social infrastructure projects. The authors developed a quantitative approach using smart-PLS version 3.2.7. This study shed light on the views of different experts based on their experience in public construction projects in Pakistan. Particularly, the authors aimed to find out the relationships between construction, stakeholders, materials, design, and external factors, and how these relate to project quality. The findings of this study revealed that the R2 value of the model was scored at 0.749, which meant that the five exogenous latent constructs collectively explained 74.9% of the variance in project quality. The Goodness-of-Fit of the model was 0.458. The construction related factor was the most important out of the five constructs. This study determined that better planning and monitoring and evaluation should be developed to better address and control the quality defects by decision-makers, project managers as well as contractors. These findings might support practitioners and decision makers to focus on quality related problems that might occur in their current or future projects

Using random inquiry optimization method for provision of heat and cooling demand in hub systems for smart buildings

A technique for planning the energy hub is proposed in this work that provides electrical, thermal and cooling demands with respective energies and managing the continuous and on/off controllable loads. Features of energy hub elements including the energy losses, cost of degradation in cooling, thermal and electrical energy storage and feasible operation region of the combined heat and power plants are comprehensively simulated. The presented equation is utilized on two different days in winter and summer considering different scenarios to investigate the effect of energy storage, selling power to the main grid, intelligent charge and discharge of vehicles with electric engine and managing the controllable loads. The results suggest that utilizing energy hub and managing loads has significant advantages in both user and main grid sides, and results in a flatter load curve in time of use demand response

A Child Labour Estimator: A Case of Bahawalpur Division

Child labor is a distressing issue. There have been many attempts to estimate its magnitude. It is attempted here to develop an estimator to assess the magnitude of this issue using a (Horvitz and Thompson in J Am Stat Assoc 47(260):663–685, 1952) type of estimator where weights are calculated on the basis of poverty and illiteracy to increase the sampling efficiency. The estimator is used to assess the magnitude of child labor in Bahawalpur division. Subsequent different statistical properties of this estimator, like its unbiasedness, variance, probability distribution, confidence intervals are also developed for its study from different angles