An update is available for this article. Background: Health care workers (HCWs) are at risk
for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Purpose: To …

Collinearity refers to the non independence of predictor variables, usually in a regression‐
type analysis. It is a common feature of any descriptive ecological data set and can be a …

This study examined the impact of workplace environment on employee task performance
under the mediating role of employee commitment and achievement-striving ability. For this …

During the era of COVID-19 (COronaVIrus Disease of 2019), telework has been adopted
extensively in developing countries for the first time. This study analyzes data of 355 …

In regression analysis it is obvious to have a correlation between the response and predictor
(s), but having correlation among predictors is something undesired. The number of …

Multicollinearity is a potential problem in all regression analyses. However, the examination
of multicollinearity is rarely reported in primary studies. In this article we discuss and show …

Hospitality firms are increasingly investing in corporate social responsibility (CSR) to
generate strong relationships with stakeholders while aiming to benefit their own …

To achieve their innovation and service quality goals and effectively meet customers'
changing demands, hospitality firms are searching for different ways to encourage …

The adverse impact of ignoring multicollinearity on findings and data interpretation in
regression analysis is very well documented in the statistical literature. The failure to identify …

A multivariable analysis is the most popular approach when investigating associations
between risk factors and disease. However, efficiency of multivariable analysis highly …