Logistic Regression, Segmentation Modeling and Governance Choice in the Waste Management Industry

1997 ◽  
pp. 261-277
Author(s):  
Magali Delmas ◽  
Michel Ghertman ◽  
Jacques Obadia
Keyword(s):  
Logistic Regression ◽  
Waste Management ◽  
Governance Choice

scholarly journals ANALISIS PENGARUH SOSIAL EKONOMI TERHADAP PENGELOLAAN SAMPAH DI SUMATERA BARAT (STUDI KASUS DAERAH PERKOTAAN)

2020 ◽  
Vol 2 (1) ◽  
pp. 107
Author(s):  
Nesyana Dewi ◽  
Melti Roza Adry
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Waste Management ◽  
Cross Section ◽  
Urban Areas ◽  
Secondary Data ◽  
Cross Section Data ◽  
Income Per Capita ◽  
Section Data ◽  
Per Capita

This study aims to determine the effect of education, income per capita, age and knowledge on waste management in urban areas West Sumatera. This study uses secondary data in the form of cross section data of urban West Sumatera. Data obtained from BPS- Susenas West Sumatera. This study uses logistic regression analysis. The result of this study indicate that (1) education has not significant effect on waste management in urban areas West Sumatera (2) income per capita has not significant effect on waste management  in urban areas West Sumatera (3) age has not significant effect on waste management in urban areas West Sumatera (4) knowledge has a significant effect on waste management in urban areas West Sumatera

A Logistic Regression Analysis of the Contractor`s Awareness Regarding Waste Management

2006 ◽  
Vol 6 (9) ◽  
pp. 1904-1908 ◽  
Author(s):  
Rawshan Ara Begum ◽  
Chamhuri Siwar . ◽  
Joy Jacqueline Perei . ◽  
Abdul Hamid Jaafar .
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Waste Management ◽  
Logistic Regression Analysis

scholarly journals AN ECONOMIC ANALYSIS OF SOLID WASTE MANAGEMENT OF IBADAN METROPOLIS, OYO STATE: EVIDENCES FROM VALUE BELIEF NORM (VBN) AND WILLINGNESS-TO-PAY THEORY

2019 ◽  
Vol 7 (4) ◽  
pp. 106-125
Author(s):  
Aduralere Opeyemi Oyelade
Keyword(s):  
Logistic Regression ◽  
Waste Management ◽  
Economic Analysis ◽  
Willingness To Pay ◽  
Solid Waste ◽  
Solid Waste Management ◽  
Educational Status ◽  
Regression Result ◽  
Net Income ◽  
Gross Margin

The study investigated the economic analysis of solid waste management of Ibadan metropolis, Oyo State: Evidences from value belief norm (VBN) and willingness-to-pay theory. The study distributed two hundred and fifty (250) to both household and contractors and two hundred questionnaires was distributed to household while fifty questionnaires for contractors. The methods used include descriptive statistic, cross tabulation, both ordinary least square (OLS) and logistic regression as well as gross margin and net income analysis. The OLS regression result revealed that income of the household, educational status, age and sex are the factors that determine the amount pay to Ibadan waste management per month in Ibadan metropolis while the factors that determine willingness-to-pay for environmental goods in Ibadan metropolis from logistic regression are income of the household, household size, educational status, occupation and sex and they are inelastic in nature. Furthermore, gross margin and net income from waste management business to the contractors sampled are N100,408.5299 and N86,852.20 per month respective. The study recommended that contractors in the study area can jointly establish recycle plants where they can recycle waste and make more income from the recycled products. Waste management contractors should be prompt in their service delivery. Also, every household should have solid waste facilities such as garbage bin and dustbin for easy disposal. Lastly, government should re-introduced the monthly sanitation in order to make a lot of household become more conscious of the purity of their surroundings

scholarly journals PENGARUH FAKTOR SOSIAL EKONOMI TERHADAP PERILAKU MASYARAKAT DALAM PENGELOLAAN SAMPAH PERDESAAN DI PROVINSI SUMATERA BARAT

2020 ◽  
Vol 2 (1) ◽  
pp. 93
Author(s):  
Ayu Rahmadani Utama ◽  
Dewi Zaini Putri
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Waste Management ◽  
Solid Waste ◽  
Employment Status ◽  
Solid Waste Management ◽  
Secondary Data ◽  
Rural Solid Waste ◽  
West Sumatra ◽  
Household Members

This study aims to determine and analyze the influence of age (X1), gender (X2), education (X3), income (X4), employment status (X5), number of household members (X6), and knowledge (X7) towards rural waste management opportunities in West Sumatra Province. This type of research is descriptive and associative research while the type of data is secondary data. The data used is the 2017 SUSENAS data with documentation data collection techniques from the Central Statistics Agency. Analysis of the data used is logistic regression analysis with all respondents totaling 5,996 people. The results showed: (1) Age was not significant to the opportunities for rural solid waste management in West Sumatra Province. (2) Gender is significant for rural waste management opportunities in West Sumatra Province. (3) Significant education towards rural waste management opportunities in West Sumatra Province. (4) Income is not significant to the opportunities for rural waste management in West Sumatra Province. (5) Significant employment status of opportunities for rural solid waste management in West Sumatra Province. (6) The number of household members is not significant to the opportunities for rural waste management in West Sumatra Province. (7) Insignificant knowledge of opportunities for rural solid waste management in West Sumatra Province.

scholarly journals An Attempt at Quantifying Factors that Affect Efficiency in the Management of Solid Waste Produced by Commercial Businesses in the City of Tshwane, South Africa

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Yohannes Worku ◽  
Mammo Muchie
Keyword(s):  
South Africa ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Waste Management ◽  
Solid Waste ◽  
Logistic Regression Analysis ◽  
Binary Logistic Regression ◽  
Predictor Variables ◽  
Binary Logistic Regression Analysis ◽  
The City

Objective. The objective was to investigate factors that affect the efficient management of solid waste produced by commercial businesses operating in the city of Pretoria, South Africa.Methods. Data was gathered from 1,034 businesses. Efficiency in solid waste management was assessed by using a structural time-based model designed for evaluating efficiency as a function of the length of time required to manage waste. Data analysis was performed using statistical procedures such as frequency tables, Pearson’s chi-square tests of association, and binary logistic regression analysis. Odds ratios estimated from logistic regression analysis were used for identifying key factors that affect efficiency in the proper disposal of waste.Results. The study showed that 857 of the 1,034 businesses selected for the study (83%) were found to be efficient enough with regards to the proper collection and disposal of solid waste. Based on odds ratios estimated from binary logistic regression analysis, efficiency in the proper management of solid waste was significantly influenced by 4 predictor variables. These 4 influential predictor variables are lack of adherence to waste management regulations, wrong perception, failure to provide customers with enough trash cans, and operation of businesses by employed managers, in a decreasing order of importance.

How Useful is the Power Law of Practice for Recognizing Practice in Concentration Tests?

2007 ◽  
Vol 23 (3) ◽  
pp. 157-165 ◽  
Author(s):  
Carmen Hagemeister
Keyword(s):  
Logistic Regression ◽  
Reaction Time ◽  
Power Law ◽  
Error Rate ◽  
Reaction Times ◽  
Practice Effect ◽  
Practice Effects ◽  
Rate Decrease ◽  
Small Practice

Abstract. When concentration tests are completed repeatedly, reaction time and error rate decrease considerably, but the underlying ability does not improve. In order to overcome this validity problem this study aimed to test if the practice effect between tests and within tests can be useful in determining whether persons have already completed this test. The power law of practice postulates that practice effects are greater in unpracticed than in practiced persons. Two experiments were carried out in which the participants completed the same tests at the beginning and at the end of two test sessions set about 3 days apart. In both experiments, the logistic regression could indeed classify persons according to previous practice through the practice effect between the tests at the beginning and at the end of the session, and, less well but still significantly, through the practice effect within the first test of the session. Further analyses showed that the practice effects correlated more highly with the initial performance than was to be expected for mathematical reasons; typically persons with long reaction times have larger practice effects. Thus, small practice effects alone do not allow one to conclude that a person has worked on the test before.

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