House Floor Area as a Correlate of Marital Residence Pattern: A Logistic Regression Approach

2010 ◽  
Vol 44 (4) ◽  
pp. 405-424 ◽  
Author(s):  
Marko Porčić
2019 ◽  
Vol 139 (3) ◽  
pp. 235-245
Author(s):  
Carlos Augusto Ferreira Lobão ◽  
Letícia Miquilini ◽  
Breno Simões Ribeiro da Silva ◽  
Verônica Gabriela Ribeiro da Silva ◽  
Eliza Maria da Costa Brito Lacerda ◽  
...  

2019 ◽  
Vol 108 ◽  
pp. 182-195 ◽  
Author(s):  
Elisa Cuadrado-Godia ◽  
Ankush D. Jamthikar ◽  
Deep Gupta ◽  
Narendra N. Khanna ◽  
Tadashi Araki ◽  
...  

2020 ◽  
Vol 18 (3) ◽  
pp. 363-382
Author(s):  
Aleksandra K. Bordunos ◽  
◽  
Sofia V. Kosheleva ◽  
Anna Zyryanova ◽  
◽  
...  

This paper aims to identify the determinants of return to work after maternity leave in Russia. Can an organisation influence employees’ decision about withdrawal from the market after leave arrangement, or does it fully depend on the contextual and personal characteristics of the employee, as assumed by the discourses of merit and choice? Logistic regression analysis helps to answer the raised questions, referring to responses of 721 mothers with previous working experience. The research revealed that employers indeed can improve inclusion of employees with childcare commitments, fostering their return after the maternity leave. Despite high regional diversity of Russian population, contextual specificity barely influences the decision of employees regarding their returning to work with the same employer, similarly to their level of education, firms’ equity or amount of children. Among personal characteristics, income was found to play an important role in return decisions, as well as the age of the smallest child. The paper contributes to the debates on the fluidity of gender and work identity as well as organizational control over the identity work.


Risks ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 107
Author(s):  
Youssef Zizi ◽  
Mohamed Oudgou ◽  
Abdeslam El Moudden

This paper aims to identify the determinants and predictors of Small and Medium-sized Enterprises (SMEs)’ financial failure. Within this framework, we have opted for a quantitative method based on a sample of healthy and failing SMEs of a Moroccan bank. The main results of the different optimal models are obtained by the stepwise method of estimating logistic regression. These results show, in a normal economic context, that the variables that discriminate between healthy and failing SMEs are the main predictors of financial failure. Autonomy ratio, interest to sales, asset turnover, days in accounts receivable, and duration of trade payables are the variables that increase the probability of financial failure, while repayment capacity and return on assets reduce the probability of failure. These variables present an overall classification rate of healthy and failing SMEs of 91.11% three years before failure and of 84.44% two years and one year before failure.


2010 ◽  
Vol 7 (6) ◽  
pp. 390-396
Author(s):  
Haipeng Wang ◽  
Xiang Xiao ◽  
Xiang Zhang ◽  
Jianping Zhang ◽  
Yonghong Yan

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