A Logistic Regression Analysis to Examine Factors Affecting Gender Diversity on the Boardroom: ISE Case

Sakınç, İlker; Uğurlu, Erginbay

doi:10.2139/ssrn.4242816

Cited by 4 publications

(5 citation statements)

References 14 publications

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“…In this research, the binary logistic regression model was involved because the dependent variable (adoptability or willingness to adopt the proposed SEC measures) is a binary consisting of two values, 1 and 0, for an adopter and a non-adopter, respectively. The expected value is simply the probability p. Practically, the dependent variable is modeled indirectly as the logistic transformation of p, as shown in Equation (2) [25][26][27].…”

Section: Discussionmentioning

confidence: 99%

“…The nine variables commonly associated with SEC adoption are listed in Table 7 [24]. Many studies have shown that various socioeconomic characteristics affect farmers' adoption behavior of SEC measures [24][25][26][27][28][29][30][31][32][33]. In analyzing the impacts of the nine independent variables on the dependent variable (adoption of SEC measures in the Sebeya catchment), the following summary presents the results and interpretation using the chi-square test and the Binary Logistic Regression Model.…”

Section: Adoptability Of Sec Measures In the Sebeya Catchmentmentioning

confidence: 99%

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Analyzing Various Factors Affecting Farmers’ Willingness to Adopt Soil Erosion Control Measures in the Sebeya Catchment, Rwanda

Majoro

Wali

2022

Sustainability

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Soil erosion is a worldwide environmental problem leading to low agricultural productivity and water quality degradation. Improving soil erosion control measures is essential. This study reports the results of a survey of 75 farmers, using structured interviews, field observations, and focus groups to analyze farmers’ perceptions concerning current and future efforts to adopt Soil Erosion Control (SEC) measures in the Sebeya catchment located in the Western Province of Rwanda. Various factors influencing farmers’ perceptions of soil erosion causes, effects, and willingness to adopt SEC measures were analyzed using descriptive statistics and SPSS (Version 20), including t-tests, chi-square tests, and a binary logistic regression model. Chi-square test results indicate that gender, farmer age, land ownership, farmland size, social media access, and credit access were strongly associated (p < 0.05) with the adoption of SEC measures, while marital status and education were not. A binary logistic regression model showed that among farmers’ socioeconomic characteristics, farming experience (B = 0.749; p = 0.020) and access to socio media (B = 2.107; p = 0.027) were positively correlated, while age (B = −0.642; p = 0.035) and gender (B = −2.034; p = 0.032) were negatively correlated (p < 0.05) with the adoption of SEC measures. In order to mitigate high soil erosion rates and increase food production, there is a need for the government to support farmers, and train them. A highly skilled technical team should be mobilized to assist in implementing SEC measures in the Sebeya catchment.

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Section: Discussionmentioning

confidence: 99%

Section: Adoptability Of Sec Measures In the Sebeya Catchmentmentioning

confidence: 99%

Analyzing Various Factors Affecting Farmers’ Willingness to Adopt Soil Erosion Control Measures in the Sebeya Catchment, Rwanda

Majoro

Wali

2022

Sustainability

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“…Binary Logistic Regression analysis is used to assess the influence of independent factors on the probability that a binary dependent variable would fall into one of the alternative categories and the impact of variables on the human component was investigated and determined (King, 2008;Sakinc and Ugurlu, 2013;Zewude and Ashine, 2016;Magalhães et al, 2014). To investigate the Binary Logistic Regression age, occupation, shifting of land, loss of land, and income all are taken as independent variables while security status utilized as the dependent variable.…”

Section: Binary Logistic Regressionmentioning

confidence: 99%

Unstable Behavioral Pattern of Teesta River and Its Impact on Riverine Dwellers: A Case Study of Confluence Area of Teesta and Dharala River, India

Das,

Parveen,

Ghosh

et al. 2024

AFJHSS

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The power of the river does not always work to the benefit of living things; rather, it has the ability to destroy human society and has negative effects on the environment. River Teesta has a prodigious significance on the riverine dweller and its changing precarious behavior has repercussions on the lives of millions. Utilizing satellite images and 41 years of temporal analysis, the mapping of channel extraction and channel shifting has been demonstrated. Delineating the exact channel boundary is a laborious operation, but MNDWI technique is really valuable in this situation to produce valuable results. Descriptive statistics are used to analyze the Teesta River's active flow line migration trend and channel migration behavior. A particular river's oscillating character over time has both beneficial and detrimental power, destroying important resources for environmental sustainability and human society while also providing fertile mother earth as a source of wealth. As a result, another goal of the current study was to determine how vulnerable riverine residents were. A Livelihood Vulnerability Index (LVI) based on the riverine inhab-itants' exposure, sensitivity, and capacity for adaptation was created. According to the findings, the river's erratic behavior is putting the people who live beside it in danger. Therefore, it is vitally necessary to implement a capable management strategy to stop bank failure at the Teesta-Dharala confluence in order to save the riverine residents.

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“…As expected, regular attending to the lectures in Statistics significantly affects the increase of probability odds of success in mastering the course curriculum. In addition, the scores obtained in other quantitative courses significantly increase the probability odds of success in Statistics Sakinc & Ugurlu (2013). conducted a study to investigate the factors affecting gender diversity in the boardroom using a logistic regression analysis which is based on the data of 40 listed firms in the Istanbul Stock Exchange (ISE) in the Corporate Governance Index (XKURY) in the year 2011.…”

mentioning

confidence: 99%

Untitled

2023

EJBIR

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This study attempts to estimate the logistic regression model to find the factors associated with the likelihood of skilled workers in the garment sector of Bangladesh. The study is based on primary data. From the maximum likelihood estimates of the logistic model, it is found that the variables, years of education, years of experience, wage rate, grade, and working years at the present company have significant positive effects on the logit of the outcome variable Y, but the variable age of the companies has a significant negative effect. From the estimated odd ratios, it can be said that the male group is 3.0695 times more likely than the female group to be a skilled worker, which is significant at a 10% level; a group of rural workers is 10.3727 times more likely than the urban group in favour of skilled workers, which is significant at a 15% level; a group of workers have a training program degree is 38.5552 times more likely in favour of skilled workers, than a group of workers who have not, which is statistically significant at any significance level. The estimated results of squared correlation between Y and Ŷ , pseudo-R 2 , Mcfadden's 2 R , Maddala's 2 R , and Count-R 2 support that the model fits the data very well. Based on the findings, different policies are formulated for the sustainable development of Bangladesh's garment sector.

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A Logistic Regression Analysis to Examine Factors Affecting Gender Diversity on the Boardroom: ISE Case

Cited by 4 publications

References 14 publications

Analyzing Various Factors Affecting Farmers’ Willingness to Adopt Soil Erosion Control Measures in the Sebeya Catchment, Rwanda

Analyzing Various Factors Affecting Farmers’ Willingness to Adopt Soil Erosion Control Measures in the Sebeya Catchment, Rwanda

Unstable Behavioral Pattern of Teesta River and Its Impact on Riverine Dwellers: A Case Study of Confluence Area of Teesta and Dharala River, India

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