scholarly journals A Binary Logistic Analysis on Factors Affecting the Participation of Smallholder Farmers in the Market of Indigenous Chickens (ICs)

2020 ◽  
Vol 58 (4) ◽  
Author(s):  
Lesiba Andries Sekele ◽  
Jenny Potsiso Mokhaukhau ◽  
Machuene Sharlyn Cholo ◽  
Anele Mayekiso
Keyword(s):  
Smallholder Farmers ◽  
Binary Logistic Regression ◽  
Snowball Sampling ◽  
Binary Logistic Regression Model ◽  
Indigenous Chicken ◽  
Factors Affecting ◽  
Indigenous Chickens ◽  
Logistic Analysis ◽  
Factors Influencing ◽  
Female Farmers

Participation in the market of Indigenous Chickens (ICs) enables farmers an opportunity to generate income and alleviate household food insecurity. The objectives of the study were to profile the socioeconomic characteristics of smallholder farmers and; to determine the factors influencing participation of smallholder farmers in the market of ICs. The study employed purposive and snowball sampling techniques to identify 50 indigenous chicken farmers in Makhuduthamaga Local Municipality, South Africa. Descriptive statistics and Binary Logistic regression model were employed to address the objectives of the study. The results revealed that, most smallholder farmers do not participate in the market of ICs. Moreover, experience in rearing chickens, land size, number of chickens owned, and purpose of rearing the chickens were found as factors influencing participation of farmers in the market of ICs. The study also confirmed that female farmers dominate in the market of ICs when compared to males. This, therefore, calls for government intervention in the promotion of ICs markets to encourage participation by farmers thus improving livelihoods.

scholarly journals Determinants of Participation in Contract Farming Among Smallholder Dairy Farmers: The Case of North Shewa Zone of Oromia National Regional State, Ethiopia

2020 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Mosisa Hirpesa ◽  
Belaineh Legesse ◽  
Jema Haji ◽  
Ketema Bekele
Keyword(s):  
Smallholder Farmers ◽  
Group Discussion ◽  
Binary Logistic Regression ◽  
Price Uncertainty ◽  
Contract Farming ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
The North ◽  
Regional State ◽  
Sex Perception

The study analyzed the determinants of participation in dairy contract farming using data collected from 424 (192 participants and 232 non-participants) randomly selected milk-producing farmers from three districts of the North Shewa Zone of Oromia Regional State, Ethiopia. The study combines both quantitative and qualitative data obtained from household interview using semi structured questionnaire, key informant interview, focus group discussion, and direct personal observation. Descriptive statistics and econometric models were used to analyze data. The binary logistic regression model was employed to identify factors affecting participation in dairy contract farming. Results show that age, sex, perception of price uncertainty, frequency of extension contact and access to training significantly and positively affect participation in dairy contract farming while time taken to milk collection centers affected it significantly and negatively. Results suggest that the need to encourage young farmers, female-headed households, increasing frequency of extension contact, creating access for training, decentralization of milk collection centers and contract farming reduces perceived price uncertainty faced by smallholder farmers from the spot market through creating guaranteed milk price in the study area. 

The Firm-Specific Factors Influencing the Tax Haven Operations of Indian Multinationals

2021 ◽  
pp. 001946622110360
Author(s):  
P. Vineeth ◽  
K. B. Nidheesh
Keyword(s):  
Service Sector ◽  
Positive Impact ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Firm Level ◽  
Return On Equity ◽  
Factors Influencing ◽  
Tax Haven ◽  
Specific Factors ◽  
Knowledge Intensive

The present study measures the role of firm-specific factors influencing the likelihood of establishing a subsidiary in tax haven countries. The panel data of Indian companies, which have business operations in foreign countries, are used for the study. The firm-level data for the period from 2007 to 2018 are analysed by using binary logistic regression model. The result shows that the intangible assets, long-term debt, number of subsidiaries and service sector dummy have significant and positive impact on tax haven operations of multinational companies, but the experience of the firm and return on equity are insignificant, and a firm’s size deters the likelihood of setting a tax haven subsidiary. The results also show that firms from high-technology manufacturing and knowledge-intensive sector have more influence on the likelihood of owning a tax haven subsidiary by Indian multinationals. JEL Codes: F21, F23, H25, H26

scholarly journals Appraisal of Issues Influencing Soil-Steps Application for Sustainable Farmland Management in High-Potential District, Ethiopia

2018 ◽  
Vol 7 (3) ◽  
pp. 102
Author(s):  
Mehretie Belay
Keyword(s):  
Smallholder Farmers ◽  
Group Discussion ◽  
Household Head ◽  
Binary Logistic Regression ◽  
Northwest Ethiopia ◽  
Study Data ◽  
High Potential ◽  
Binary Logistic Regression Model ◽  
Chi Square ◽  
Chi Square Test

Soil damage by moving water is a somber predicament on farmlands in highland Ethiopia. Sizeable number of trial in farmland preservation has been executed to handle the crisis during the last tens of years. However, the attempts have not been vibrant to trim-down the danger to an attractive extent. This paper evaluates factors contributing to application of soil-steps (bunds) as sustainable farmland management technology (SFLMT) by smallholder farmers in one of the high-potential districts of northwest Ethiopia named Dangila Woreda (District). Mixed method triangulation designs involving concurrent acquisition and interpretation of quantitative and qualitative data were used in the study. Data were acquired from randomly chosen 201 farming households during the harvest seasons of 2011 and 2012. Ordered questionnaire, participatory field observation, key informant interview and focus group discussion were mechanisms employed during the data acquisition. Descriptive statistics (means, standard deviations and percentiles), Chi-square test, t-test and the binary logistic regression model were used to analyze the quantitative data. The qualitative information was textually narrated to augment the quantitative results. Findings of the investigation confirm that age of the household head, the number of household members, slope of the farmland, the size of the farmland held, households’ participation in indigenous labour-sharing activities and the number of farm tools owned were significantly increasing the building of soil-steps as SFLMT in the study district. Involvement in off-farm activities and pest invasions were considerably hindering farmers from building soil-steps on their farmlands. The results in general indicated that households’ access to livelihood assets are key promoters for farmers’ implementation of soil-steps on their farmlands. Local resource preservation and improvement trials should thus ponder on convalescing farmers’ material endowments to improve their capability to use soil-steps as SFLMT in their farming activities.

scholarly journals The Effects of Picking Up Primary School Pupils on Surrounding Street’s Traffic: A Case Study in Hanoi

2020 ◽  
Vol 14 (1) ◽  
pp. 237-250
Author(s):  
Dinh Hiep ◽  
Vu V. Huy ◽  
Teppei Kato ◽  
Aya Kojima ◽  
Hisashi Kubota
Keyword(s):  
Primary School ◽  
Traffic Safety ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Primary Schools ◽  
Traffic Accidents ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Almost All

Introduction: One of the significant characteristics of schools in Vietnam is that almost all parents send their children to school and/or pick up their children from school using private vehicles (motorcycles). The parents usually stop and park their vehicle on streets outside the school gates, which can lead to serious congestion and increases the likelihood of traffic accidents. Methods: The objective of this study is to find out factors affecting the picking up of pupils at primary school by evaluating the typical primary schools in Hanoi city. A binary logistic regression model was used to determine factors that influence the decision of picking up pupils and the waiting duration of parents. The behavior of motorcyclists during the process of picking up pupils at the primary school gate has been identified and analyzed in detail by the Kinovea software. Results and Discussion: The study showed that, on the way back home, almost all parents use motorbikes (89.15%) to pick up their children. During their waiting time (8.48 minutes in average), they made a lot of illegal parking actions on the street there by, causing a lot of “cognitive” errors and “crash” points surrounding in front of the primary school entrance gate. Risky picking-up behaviors were significantly observed, i.e. picking-up on opposite side of the school, making a U-turn, backing-up dangerously, parking on the middle of street, and parking on the street next to sidewalk). Conclusion: Based on the analyzed results, several traffic management measures have been suggested to enhance traffic safety and reduce traffic congestion in front of school gates. In addition, the results of the study will provide a useful reference for policymakers and authorities.

scholarly journals Factors influencing migration and settlement of pastoralists in Nairobi City, Kenya

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Walter Magero Wafula ◽  
Oliver Vivian Wasonga ◽  
Oscar Kipchirchir Koech ◽  
Staline Kibet
Keyword(s):  
Land Tenure ◽  
Binary Logistic Regression ◽  
Policy Formulation ◽  
Snowball Sampling ◽  
Binary Logistic Regression Model ◽  
Grazing Land ◽  
Pastoral System ◽  
Pastoral Production ◽  
Alternative Markets ◽  
The City

AbstractPastoralism is globally recognized as the backbone of the economy in the vast arid and semi-arid rangelands. Despite its enormous economic contribution, the system is facing a myriad of challenges, among them, land use and land tenure changes, resulting in diminished grazing land. Accompanying such changes is the conversion of traditional grazing lands into other uses such as settlements, with urbanization being one of the key drivers of pastoral system dynamics. Understanding such dynamics in the face of compounding factors such as frequent droughts linked to climate change is key in guiding policy formulation and interventions aimed at achieving a sustainable pastoral production system. This study investigated factors determining migration and settlement of pastoralists in Nairobi City of Kenya. Data was collected through a snowball sampling approach using semi-structured household questionnaires, focus group discussions (FGDs) and key informant interviews (KIIs) in five Sub-counties of Nairobi City County. A total of 144 household interviews, 6 FGDs and 16 KIIs were conducted to elucidate drivers of urban pastoralism, opportunities and challenges encountered by pastoralists in the city. A binary logistic regression model was used to analyse the determinants of their migration. Results show that search for pasture and water resources, and alternative markets especially during droughts, are the main reasons for pastoralists’ migration to the city. In addition, educated herders were found to be more likely to migrate to the city as they pursue wage employment. Whereas these findings revealed that migration to the city exposes pastoralists to diverse livelihood opportunities, they are equally faced by a number of challenges - mainly road accidents involving livestock, frequent land displacements to pave way for development of real estates, and livestock poisoning from sewage and garbage wastes. There is a need for policy and regulatory interventions to recognize pastoralism alongside other forms of urban farming and addressing challenges facing sustainable pastoral production.

scholarly journals Usaha Ternak Domba sebagai Jalur Keluar dari Kemiskinan Buruh Tani di Perdesaan

2020 ◽  
Vol 7 (3) ◽  
pp. 189
Author(s):  
Sondi Kuswaryan ◽  
Cecep Firmansyah ◽  
Muhammad Hasan Hadiana
Keyword(s):  
Regression Model ◽  
Poverty Alleviation ◽  
Binary Logistic Regression ◽  
Farm Labor ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Poor Households ◽  
Simple Regression Model ◽  
Poverty Status ◽  
Household Members

ABSTRAKPenelitian ini bertujuan untuk mengevaluasi kemungkinan usaha ternak domba sebagai aktivitas nafkah untuk pengentasan kemiskinan, serta menentukan jumlah kepemilikan domba yang dapat  membawa rumah tangga buruh tani keluar dari kemiskinan. Survey telah dilakukan di Desa Walangsari Kecamatan Kalapanunggal Kabupaten Sukabumi, melibatkan rumah tangga buruh tani miskin sebanyak 65 orang dan 22 orang tidak miskin. Faktor yang berpengaruh terhadap kemiskinan dianalisis menggunakan model regresi logistik biner, sedangkan jumlah kepemilikan domba yang harus dipelihara untuk keluar dari kemiskinan ditentukan dengan model regresi sederhana. Hasil penelitian menunjukkan bahwa usia kepala keluarga, dan pengalaman beternak tidak mempengaruhi kemiskinan, sedangkan jumlah kepemilikan domba, jumlah anggota rumah tangga, keterlibatan dalam kelembagaan, serta sumber pendapatan dari non pertanian mempengaruhi status kemiskinan rumah tangga buruh tani. Pada rata-rata jumlah anggota rumah tangga sebanyak 4,45 orang,untuk keluar dari kemiskinan buruh tani harus memelihara minimal sebanyak 36,63 ekor domba per rumah tangga. Hasil penelitian ini menegaskan bahwa usaha ternak domba dapat digunakan sebagai sarana untuk pengentasan kemiskinan buruh tani, program pengentasan kemiskinan akan efektif bila melibatkan kelembagaan lokal.Kata Kunci: buruh tani, jumlah kepemilikan domba, kemiskinanABSTRACTThis study aims to determine the possibility of sheep farming as a livelihood activity for poverty alleviation and to determine the amount of sheep ownership that can bring farm laborers households out of poverty. Survey research has been carried out in Walangsari Village, Kalapanunggal District, Sukabumi Regency, involving 65 poor farmer households and 22 non-poor households. Factors affecting poverty were analyzed using a binary logistic regression model, while the number of sheep ownership needed to escape poverty was determined by a simple regression model. The results showed that the age of the head of the family, and experience of sheep farmers did not affect poverty, while the number of sheep ownership, number of household members, involvement in institutions, and sources of income from non-agriculture affected the poverty status of farm laborers' households. In the average number of household members as many as 4.45 people, to get out of poverty must maintain a minimum of 36.63 sheep per household. This research explains that sheep farming can be used as a means to reduce the poverty of farm laborers, and poverty alleviation programs will be effective if they involve local institutions.Keywords: farm labor, number of sheep ownership, poverty

scholarly journals Determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia

2020 ◽  
Vol 12 (4) ◽  
pp. 463-476
Author(s):  
Hurgesa Hundera Hirpha ◽  
Sylvester Mpandeli ◽  
Amare Bantider
Keyword(s):  
Climate Change ◽  
Logistic Regression ◽  
Regression Model ◽  
Climate Change Adaptation ◽  
Logistic Regression Model ◽  
Smallholder Farmers ◽  
Binary Logistic Regression ◽  
Adaptation Strategies ◽  
Binary Logistic Regression Model ◽  
Content Type

Purpose The Ethiopian economy is mainly based on the rain-fed agriculture practiced by smallholder farmers. The sector is highly vulnerable to climate change impacts. This study aims to examine the determinants of adaptation strategies to climate change among the smallholder farmers in Adama District, Ethiopia. Design/methodology/approach A cross-sectional survey design was used to collect quantitative data using questionnaire with 351 randomly selected smallholder farmers. To collect qualitative data focus group discussions, key informant interviews and field observations were also used. Triangulated with thematic analysis, descriptive statistics and binary logistic regression model were used for the analysis. Findings The result indicated that the majority of the smallholder farmers use at least one climate change adaptation strategy in their local areas though the strategy is generally weak. In this regard, some of the dominant climate change adaptation activities identified in the study area are using improved crop varieties, planting trees, watershed management, adjusting planting date and terracing. The result from binary logistic regression model showed that age and sex of household head, as well as their education, family size, access to agricultural extension services and training on climate change significantly influence the practices of adaptation measures. Originality/value This study would help the practitioners to modify the existing weak adaptation activities by introducing advanced and technological-based adaptation strategies to the rural farming communities.

scholarly journals Modeling and Analyzing the Factors Affecting the Mortality of Pedestrians in Urban Accidents

2018 ◽  
Vol 14 (4) ◽  
pp. 10-21
Author(s):  
Ahmet Tortum ◽  
Alireza Motamadnia
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Binary Logistic Regression ◽  
Education Level ◽  
Road Surface ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Surface Conditions

Abstract The nature of urban and rural accidents has been different from each other in some of the factors and even the severity of damage rate, mayhem, and death. In this research, using statistical methods and binary logistic regression model, we have addressed to analyze important parameters such as age, gender, education level, the color of the pedestrian dress, season of accident, time of accident, the speed of the vehicle colliding with pedestrians and road surface conditions at the time of accident on the way of death (at the scene of the incident or in the hospital) pedestrians who have been traumatized. After the creation of the binary logistic regression model, it was determined that only the parameters of speed and the accident time have been significant in the level less than 5%. And other parameters such as age, gender, the season of accident occurrence, the color of the pedestrian dress, road surface conditions and education level had no significant effect in terms of statistical on the incidence of mortality arising from a pedestrian accident with the motor vehicle. The results revealed that by adopting decisions related to the traffic calming, attention to passages lighting and brightness the mortality rate of a pedestrian due to the urban accidents can be reduced.

scholarly journals FACTORS AFFECTING ACCESS TO FORMAL CREDIT BY SMALLHOLDER FARMERS IN AN GIANG PROVINCE

2015 ◽  
Vol 18 (1) ◽  
pp. 28-39
Author(s):  
Ngoc Nhan Nhu Nguyen ◽  
Chinh Duc Pham
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Smallholder Farmers ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Factors Affecting ◽  
Five Factors ◽  
Household Assets ◽  
Loan Guarantees

This study was conducted to determinefactors that affect the access to formal credit by smallholder farmers in An Giang province. Applying binary logistic regression analysis on a sample of 210 households, we found that the access to formal credit by these households are affected by five factors, namely total value of household assets, participation in organizations, demand for loans from credit institutions, loan guarantees and accumulated income, in which the demand for loans has the greatest impact. From the regression results, we built a model to forecast the access to formal credit by households with 93.8%. precise forecastprobability.

scholarly journals Gender Differences in Healthcare-Seeking Behaviors in China’s Ageing Population: An Empirical Study of Shanghai

2020 ◽  
Author(s):  
Luxue Liu ◽  
Chunlan Wang ◽  
Shangguang Yang ◽  
Kevin Lo ◽  
Xi Yang
Keyword(s):  
Gender Differences ◽  
Elderly Population ◽  
Binary Logistic Regression ◽  
The Elderly ◽  
Influential Factors ◽  
Ageing Population ◽  
Binary Logistic Regression Model ◽  
Healthcare Seeking ◽  
Factors Influencing ◽  
Tertiary Hospitals

Abstract Background: Given the growing healthcare demands of the elderly, an improved understanding of the factors influencing their healthcare-seeking behaviors is necessary to enhance the effectiveness of the current healthcare system. This study empirically investigates the factors influencing the elderly population’s healthcare-seeking behaviors in Shanghai, China, from a gender differences perspective.Methods: We combine both quantitative and qualitative analyses by constructing a binary logistic regression model and identifying the relevant influential factors based on the following types of dimensions: individual, family, and cultural.Results: The results indicate that gender differences exist in the elderly population with common diseases but not in those with severe diseases, and that the female elderly are more likely to choose non-tertiary hospitals than males. In addition, age, marital status, employment status, income, health conditions, medical insurance, family support, and social capital are found to be critical influencing factors.Conclusions: The findings provide a better understanding of the elderly population’s healthcare demands and can be used to promote healthcare equality.

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