title: 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.
abstract: 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.
authors.affiliation: Department of Civil Engineering, Faculty of Engineering, Tshwane University of Technology, Pretoria, South Africa. Johannes.Worku@gmail.com
authors.forename: Yohannes
authors.initials: Y
authors.lastname: Worku
authors.forename: Mammo
authors.initials: M
authors.lastname: Muchie
mesh_terms: D003132:Commerce / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D012037:Refuse Disposal / Q000379:methods / Q000706:statistics & numerical data*; D012307:Risk Factors; D062611:Solid Waste / Q000706:statistics & numerical data*; D013019:South Africa; D018505:Waste Management / Q000379:methods / Q000706:statistics & numerical data*
chemical_list: D062611:Solid Waste