Factors influencing SME owners’ continuance intention in Bangladesh: a logistic regression model

2019 ◽  
Vol 10 (3) ◽  
pp. 391-415
Author(s):  
Iman Aghaei ◽  
Amin Sokhanvar
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Continuance Intention ◽  
Factors Influencing

scholarly journals An Assessment of Factors Influencing Forest Harvesting in Smallholder Tobacco Production in Hurungwe District, Zimbabwe: An Application of Binary Logistic Regression Model

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Chipo Chivuraise ◽  
Tafireyi Chamboko ◽  
Godfrey Chagwiza
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Forest Harvesting ◽  
Natural Forest ◽  
Selling Price ◽  
Binary Logistic Regression Model ◽  
Factors Influencing ◽  
Tobacco Production

Deforestation is one of the major effects posed by the smallholder tobacco farming as the farmers heavily depend on firewood sourced from natural forest for curing tobacco. The research aims at assessing the factors that influence the harvesting of natural forest in the production of tobacco. Data is collected through the structured questionnaire from 60 randomly selected farmers. Binary logistic regression model is used to explain the significance of factors influencing natural forest harvesting. Results show that farmer experience, tobacco selling price, and agricultural training level negatively affect the harvesting of natural forests (to obtain firewood) for curing tobacco significantly (p<0.05). However, gender, size of the household, tobacco yield, and level of education are insignificant (p>0.05) in influencing natural forest harvesting. Though farmers are exploiting the environment and at the same time increasing foreign currency earning through tobacco production, there is therefore a need to put in place policies that encourage sustainable forest product utilization such as gum plantations, subsidizing price of coal, and introducing fees, as well as penalties or taxes to the offenders.

scholarly journals Debt as a Source of Financial Energy of the Farm—What Causes the Use of External Capital in Financing Agricultural Activity? A Model Approach

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4124
Author(s):  
Danuta Zawadzka ◽  
Agnieszka Strzelecka ◽  
Ewa Szafraniec-Siluta
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Regression Tree ◽  
Agricultural Activity ◽  
Factors Influencing ◽  
External Capital ◽  
Farm Accountancy Data Network ◽  
Using Data ◽  
The One

The aim of this study was to identify and assess the factors influencing the increase in the financial energy of a farm through the use of external capital, taking into account the farmer’s and farm characteristics. For its implementation, a logistic regression model and a classification-regression tree analysis (CRT) were used. The study was conducted on a group of farms in Central Pomerania (Poland) participating in the system of collecting and using data from farms (Farm Accountancy Data Network—FADN). Data on 348 farms were used for the analyses, obtained through a survey conducted in 2020 with the use of a questionnaire. Based on the analysis of the research results presented in the literature to date, it was established that the use of external capital in a farm as a factor increasing financial energy is determined, on the one hand, by the socio-demographic characteristics of the farmer and the characteristics of the farm, and on the other hand, by the availability of external financing sources. Factors relating to the first of these aspects were taken into account in the study. Using the logistic regression model, it was established that the propensity to indebtedness of farms is promoted by the following factors: gender of the head of the household (male, GEND), younger age of the head of the household (AGE), having a successor who will take over the farm in the future (SUC), higher value of generated production (PROD_VALUE), larger farm area (AREA) and multi-directional production of the farm (production diversification), as opposed to targeting plant or animal production only (farm specialization—SPEC). The results of the analysis carried out with the use of classification and regression trees (CRT) showed that the key factors influencing the use of outside capital as a source of financial energy in the agricultural production process are, first of all, features relating to an agricultural holding: the value of generated production (PROD_VALUE), agricultural area (AREA) and production direction (SPEC). The age of the farm manager (AGE) turned out to be of key importance among the farmer’s features favoring the tendency to take debt in order to finance agricultural activity.

scholarly journals Study of Factors Affecting the Entrepreneurship Behavior of Returned Migrants Using Binary Logistic Regression Model

2019 ◽  
Vol 3 ◽  
pp. 57-68
Author(s):  
Madhav Kumar Bhusal ◽  
Hari Prasad Pandey
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Home Country ◽  
Household Head ◽  
Binary Logistic Regression ◽  
Educational Status ◽  
Categorical Variables ◽  
Binary Logistic Regression Model ◽  
Factors Influencing

Background: Entrepreneurship or business ownership is a significant source of employment and economic growth. Many studies conducted by different researchers have shown that increase in entrepreneurial activities helps to reduce unemployment. Thousands of Nepalese youths exodus for foreign migration every year for employments due to lack of adequate working environment in Nepal. In this context, identification of significant factors influencing the entrepreneurship behavior of returned migrants could be useful for planner, decision makers, and other concerned authorities. Objective: To explore the entrepreneurship status of returned migrants and to ascertain the factors influencing the entrepreneurship behavior of returned migrants. Materials and Methods: This study was based on primary data of 393 returned migrants collected through convenience sampling in Sarawal Rural Municipality of Parasi district, Nepal. People who stayed abroad at least one year and returned during 2010 to 2017 were included in the study. On the basis of Industrial Enterprise Act, 2016a, Nepal, a person who has invested Nepalese rupees five lakh or more in business besides housing and land is considered as an entrepreneur. The response variable is entrepreneurship status and it is defined according to the aforementioned act. Both quantitative and categorical variables were used as predictor variables. Factors associated with entrepreneurship behavior were extracted using Chi-square test and binary logistic regression model. Results: Out of sample of 393 returned migrants, 137 (34.9%) were entrepreneur and rest 256 (65.1%) were non-entrepreneur. Results showed that for main occupation of household head odds ratio (OR) = 4.008 & confidence interval (CI) = 2.396 to 6.703. Similarly, for educational status of returned migrants OR = 2.650 & CI = 1.599 to 4.392. For the covariate skills learnt at abroad OR = 2.750 & CI = 1.654 to 4.573. Conclusion: The study revealed that majority of returned migrants were non-entrepreneur. The factors ‘main occupation of household head’, ‘educational status of returned migrant’, ‘remittance received at home per year’ and ‘skills learnt abroad’ are the major determinants behind the entrepreneurship behavior of returned migrants. It is suggested that higher education and adequate skills should be taken before departing from home country so that the migrants can earn more money which will help to start their own businesses once they get back to their home country.

scholarly journals Factors Influencing Household Adoption of Solar Home System in Baso Liben District, Amhara Regional State of Ethiopia

2021 ◽  
Author(s):  
Asmare Mossie Zeru ◽  
Dawit Diriba Guta
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Information Access ◽  
Farm Income ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Regional State ◽  
Solar Home System

Abstract Background: Although solar energy is abundant, accessible, affordable, and ecologically and environmentally friendly, in rural Ethiopia the majority of households are still using pollutant kerosene for lighting. It is important to understand the demand and supply-side factors affecting adoption of technology. For this purpose, this study investigates the factors influencing household adoption of the solar home system (SHS).Methodology: The data used for the econometric model was collected from randomly selected 228 solar home system adopter and 143 non- adopter households in Baso Liben district, Amhara regional state of Ethiopia. The logistic regression model was applied to examine the factors affecting households’ willingness to adopt SHS. Results: The finding of this study shows significant variation in many of the socioeconomic and demographic characteristics between adopters and non-adopters. The result of the binary logistic regression model indicated that as income of a household increase, their propensity to adopt solar home system also increases. Likewise, participation in off-farm income activities, house type, educational status of the head, training access, media access, and prior knowledge of the technology positively correlated with the probability of adoption. On the other hand, the gender of the head (being male) and access to electricity were negatively associated with the adoption of SHS. Conclusion: Therefore, policy measures should create awareness through training, education, and information access or better media availability, and improving the economic status of households through creating lucrative off-farm income-earning opportunities to achieve enhanced adoption of the solar home system.

scholarly journals The Current Status of Health Promotion Lifestyle and Its Related Factors in Chinese Residents

2021 ◽  
Author(s):  
Qianqian Liu ◽  
Shusheng Huang ◽  
Xiaoyuan Qu ◽  
Aitian Yin
Keyword(s):  
Health Promotion ◽  
Logistic Regression ◽  
Regression Model ◽  
Behavioral Intention ◽  
Logistic Regression Model ◽  
Pearson Correlation ◽  
Current Status ◽  
Related Factors ◽  
Affective Factors ◽  
Factors Influencing

Abstract Objectives: This study aimed to explore the current status of Chinese residents' health promotion lifestyle and its influencing factors, especially explore how health attitudes affect health promotion lifestyle, thus can make targeted recommendations for health promotion in China and similar areas.Study design: This study was based on a household survey of 1769 adults aged 18 and over from Shandong Province of China conducted in 2018.Methods: A cross-sectional, face-to-face survey design was used. The between-group measured data were compared by One-way ANOVA or t-tests. The correlation between the health attitude and health promotion lifestyle was examined by Pearson correlation. Logistic regression model was used to examine the related factors influencing Chinese residents’ health promotion lifestyle.Results: The health promotion lifestyle of residents in Chinese residents was not good. Significant differences existed in health promotion lifestyle among different genders, education levels, income levels, marital status, and health attitude (Ps <0.001). Multivariable Logistic regression model found that gender, education level, annual family per capita income, affection and behavioral intention in health attitude were key factors influencing Chinese residents’ health promotion lifestyle (Ps<0.001). Conclusions: Individual health responsibilities need to be further strengthened. More affective factors and operable measures should be added to enhance health affection and health behavioral intention, so as to enhance health promotion lifestyle.

scholarly journals Factors Influencing Household Adoption of Solar Home System in Baso Liben District, Amhara Regional State of Ethiopia

2020 ◽  
Author(s):  
Asmare Mossie Zeru ◽  
Dawit Diriba Guta
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Information Access ◽  
Educational Status ◽  
Farm Income ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Solar Home System

Abstract Background: Although, solar energy is abundant, accessible, affordable, and ecologically and environmentally friendly, in rural Ethiopia the majority of households are still using pollutant kerosene for lightning. It is important to understand demand and supply-side factors affecting the adoption of the technology. For this purpose, this study investigates the factors influencing household adoption of solar home system (SHS). Methodology: The data used for the econometric model was collected from randomly selected 228 adopters and 143 non-adopter households in Baso Liben district, Amhara region of Ethiopia. The logistic regression model was applied to examine the factors affecting household adoption of solar home system. Results: The finding of this study shows significant variation in many socioeconomic and demographic characteristics between adopters and non-adopters of solar home system. The result of the binary logistic regression model indicated that as income of household increase, their propensity to adopt solar home system also increases. Likewise, participation in off-farm income activities, house type, educational status, training access, media access, and prior knowledge positively correlated with the adoption of SHS. On the other hand, gender and access to electricity are negatively associated with the adoption of SHS. Conclusion: Policy measures should create awareness through training, education, and information access or better media availability, and improving the economic status of households through creating lucrative off-farm income-earning opportunities to achieve enhanced adoption of the solar home system.

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