scholarly journals Labor Contracts, Wages and SME Failure

2021 ◽  
Vol 13 (14) ◽  
pp. 7864
Author(s):  
Nico Dewaelheyns ◽  
Cynthia Van Hulle ◽  
Yannick Van Landuyt ◽  
Mathias Verreydt
Keyword(s):  
Discrete Time ◽  
Regression Models ◽  
Employment Protection ◽  
Labor Contracts ◽  
Hazard Regression ◽  
Corporate Failure ◽  
Different Types

Although employment protection and employee remuneration has been shown to affect many aspects of a firm’s performance, evidence of their ability to explain firm failure is very limited. This paper examines the effect of different types of labor contracts and wages on the probability of corporate failure between 2012 and 2019 using a sample of 29,596 Belgian SMEs. Using discrete time hazard regression models, we find that the use of contract types with lower employment protection and paying lower wages are significant predictors of failure.

Discrete-Time Hazard Regression Models with Hidden Heterogeneity

2001 ◽  
Vol 29 (3) ◽  
pp. 342-373 ◽  
Author(s):  
KENNETH C. LAND ◽  
DANIEL S. NAGIN ◽  
PATRICIA L. McCALL
Keyword(s):  
Discrete Time ◽  
Regression Models ◽  
Hazard Regression

scholarly journals Absolute mortality risk assessment of COVID-19 patients: the Khorshid COVID Cohort (KCC) study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hamid Reza Marateb ◽  
Maja von Cube ◽  
Ramin Sami ◽  
Shaghayegh Haghjooy Javanmard ◽  
Marjan Mansourian ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Hospital Admission ◽  
Mortality Risk ◽  
Regression Models ◽  
Assessment Method ◽  
Point Of View ◽  
Statistical Point ◽  
Hazard Regression ◽  
Risk Assessment Method ◽  
Discharge From Hospital

Abstract Background Already at hospital admission, clinicians require simple tools to identify hospitalized COVID-19 patients at high risk of mortality. Such tools can significantly improve resource allocation and patient management within hospitals. From the statistical point of view, extended time-to-event models are required to account for competing risks (discharge from hospital) and censoring so that active cases can also contribute to the analysis. Methods We used the hospital-based open Khorshid COVID Cohort (KCC) study with 630 COVID-19 patients from Isfahan, Iran. Competing risk methods are used to develop a death risk chart based on the following variables, which can simply be measured at hospital admission: sex, age, hypertension, oxygen saturation, and Charlson Comorbidity Index. The area under the receiver operator curve was used to assess accuracy concerning discrimination between patients discharged alive and dead. Results Cause-specific hazard regression models show that these baseline variables are associated with both death, and discharge hazards. The risk chart reflects the combined results of the two cause-specific hazard regression models. The proposed risk assessment method had a very good accuracy (AUC = 0.872 [CI 95%: 0.835–0.910]). Conclusions This study aims to improve and validate a personalized mortality risk calculator based on hospitalized COVID-19 patients. The risk assessment of patient mortality provides physicians with additional guidance for making tough decisions.

Mortality Following Trajectories of Mobility Limitations: The Modifying Impact of Social Factors

2018 ◽  
Vol 32 (3-4) ◽  
pp. 134-142
Author(s):  
Terese Sara Høj Jørgensen ◽  
Volkert Siersma ◽  
Rikke Lund ◽  
Charlotte Juul Nilsson
Keyword(s):  
Older Adults ◽  
Social Factors ◽  
Regression Models ◽  
Age Group ◽  
Mobility Limitations ◽  
Hazard Regression ◽  
Trajectory Modeling ◽  
High Level ◽  
Method Group

Objective: How are trajectories of mobility limitations (MLs) among older adults associated with mortality? Do social factors modify these associations? Method: Group-based trajectory modeling was used to identify four trajectories of MLs over a period of 4.5 years among 3,055 older Danes. Mortality analyses were conducted using additive hazard regression models. Results: Compared to older adults without MLs, older adults with high level of MLs who experienced further increase in MLs were associated with the most additional deaths followed by older adults with no MLs at baseline who later experienced limitations and older adults with a medium ML level at baseline who later experienced further increase in limitations. Men and 80-year olds experienced more additional deaths following adverse ML trajectories than women and 75-year olds. Discussion: Trajectories that led to higher ML levels were associated with most additional deaths especially among men and in the oldest age group.

scholarly journals Potential of Root Crops as Source of Electrical Energy

2013 ◽  
pp. 22-39
Author(s):  
Daniel Leslie Tan ◽  
Julie Tan ◽  
Mark Anthony Atanacio ◽  
Ruel Delantar
Keyword(s):  
Fuel Cell ◽  
Microbial Fuel Cell ◽  
Regression Models ◽  
Energy Recovery ◽  
Electrical Energy ◽  
Galvanic Cell ◽  
Waste Waters ◽  
Light Emitting ◽  
Root Crops ◽  
Different Types

Energy from edible and inedible root crop roots and tubers using galvanic cell and processing waste waters through microbial fuel cell (MFC) technology was harnessed. Electrolyte in the roots and tubers was tapped for galvanic cell and the microorganisms from waste waters act as catalyst in MFC. In galvanic cell, the optimized responses of badiang, cassava and sweetpotato were greatly affected by the surface area and distance between anode and cathode electrodes. An increase of nata-de-coco membrane size in MFC increased the voltage and current by 4.94 and 11.71 times, respectively. Increasing the width of anode also enhanced the responses. Different types of microorganisms were isolated from the biofilm anode of MFC. Their growth and proliferation which corresponded to the generation of electricity were also demonstrated in this study. A total of 54 bacterial isolates were collected from the biofilm at the anode of single-chamber MFC (SCMFC). The generated electricity observed using light emitting diodes (LED) showed potential both for galvanic and microbial fuel cell. The generated regression models are reliable tools in predicting desired outputs for future applications. These promising results demonstrated basic information on the electrical energy recovery from rootcrop waste waters and roots/tubers.

Fear in Bureaucracy: Comparing Public and Private Sector Workers’ Expectations of Punishment

2018 ◽  
Vol 52 (2) ◽  
pp. 233-264 ◽  
Author(s):  
Jiwon Jung ◽  
Barry Bozeman ◽  
Monica Gaughan
Keyword(s):  
Regression Models ◽  
Robust Regression ◽  
Risk Propensity ◽  
Government Employees ◽  
Public And Private ◽  
Different Types ◽  
Major Predictor ◽  
New Ideas ◽  
Public And Private Sector ◽  
Organizational Rules

When employees fear punishment for taking initiative, organizations are likely to be less effective and, equally important, such fear extracts a human toll, often contributing to a variety of manifestations of unhappiness including diminished health. We focus on two different types of fears of punishment, fear of being punished for presenting new ideas and for bending organizational rules. Employing Mechanical Turk crowdsourcing data from 1,189 participants in the 2015 survey of National Administrative Studies Project Citizen, we test hypotheses about possible differences in fear of punishment according to sector (government vs. business), general risk propensity, views about coworkers, job clarity, gender, and whether respondents are members of an underrepresented racial or ethnic minority. Using nested robust regression models, we find that the two different types of fear of punishment are predicted by different variables. Sector has no bearing on fear of punishment for presenting new ideas but is a major predictor of differences in fear of bending the rules, with government employees being more fearful. While gender has no significant effects, being a racial minority is closely related to fear of presenting new ideas. Having a negative view of one’s fellow workers, particularly one’s supervisor, is associated with greater fear of punishment from both rule bending and presenting new ideas. Those with a clear organization mission and job clarity are less likely to be afraid of punishment for proposing innovative ideas but not necessarily for bending rules. We suggest that the results have implications for managerial practice and human resource reform.

MATHEMATICAL MODELING OF TELEROENTGENOGRAPHIC PARAMETERS ACCORDING TO THE METHOD OF SCHWARZ A. M. DEPENDING ON THE BASIC CEPHALOMETRIC PARAMETERS IN UKRAINIAN YOUNG MEN AND YOUNG WOMEN WITH DIFFERENT FACE TYPES

2021 ◽  
Vol 74 (6) ◽  
pp. 1488-1492
Author(s):  
Аlla V. Маrchenko ◽  
Oleksandr S. Prokopenko ◽  
Іryna V. Dzevulska ◽  
Tatyana R. Zakalata ◽  
Igor V. Gunas
Keyword(s):  
Young Women ◽  
Regression Models ◽  
Young Men ◽  
Cone Beam ◽  
Coefficient Of Determination ◽  
Normal Occlusion ◽  
Different Types ◽  
Dental Intervention ◽  
Individualized Approach ◽  
Facial Types

The aim: Is development and analysis of regression models of teleroentgenographic indices according to Schwarz A. M., which can be adjusted during surgery depending on the parameters that usually do not change in Ukrainian young men and young women with with normal occlusion close to orthognathic occlusion and different facial types. Materials and methods: Teleroentgenographic indices were obtained using a dental cone-beam tomograph Veraviewepocs 3D Morita and studied in 49 young men and 76 young women with normal occlusion close to orthognathic. Persons were divided into groups with different face types according to the recommendations of Schwarz A. M. In the license package “Statistica 6.0”, regression models of teleroentgenographic indices were built according to Schwarz A. M. Results: For young men with orthognathic occlusion and with different types of faces according to Schwarz A. M. constructed 10 of 27 possible reliable regression models of the group of teleroentgenographic indicators, which can be corrected during surgical, orthopedic interventions in dentistry depending on the group of basic, invariable cephalometric indicators greater than 0.6 (R2 = from 0.609 to 0.996); and in young women with different face types, 8 of the 27 possible reliable regression models in which the coefficient of determination is greater than 0.6 (R2 = from 0.642 to 0.986). Conclusions: The developed regression models provide the most individualized approach in determining the method and scope of the required dental intervention.

Innovation in the aftermath of downsizing: evidence from the threat-rigidity perspective

2020 ◽  
Vol 49 (9) ◽  
pp. 1859-1877
Author(s):  
José Fernández-Menéndez ◽  
Óscar Rodríguez-Ruiz ◽  
José-Ignacio López-Sánchez ◽  
María Isabel Delgado-Piña
Keyword(s):  
Regression Models ◽  
Negative Impact ◽  
Content Type ◽  
Logistic Regression Models ◽  
Marketing Innovation ◽  
Different Types ◽  
Threat Rigidity ◽  
The Impact ◽  
Research Show ◽  
Innovation Outcomes

PurposeThe purpose of this paper is to study how job reductions affect product innovation and marketing innovation in a sample of 2,034 Spanish manufacturing firms in the period 2007–2014.Design/methodology/approachPoisson and logistic regression models with random effects were used to analyse the impact of downsizing on some innovation outcomes of firms.FindingsThe results of this research show that the stressful measure of job reductions may have unexpected consequences, stimulating innovation. However downsizing combined with radical organisational changes such as new equipment, techniques or processes seems to have a negative impact on product and marketing innovation.Originality/valueThis research has two original features. First, it explores the unconventional direction of causality from the planned elimination of jobs to innovation outputs. Secondly, the paper looks at the combined effect of downsizing and other restructuring measures on different types of innovation. Following the threat-rigidity theory, we assume that this combination represents a major threat for survivors that leads to lower levels of product and marketing innovation.

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