International Journal of Economics and Finance; Vol. 4, No. 10; 2012 ISSN 1916-971X E-ISSN 1916-9728 Published by Canadian Center of Science and Education 131 Management Models of Municipal Solid Waste: A Review Focusing on Socio Economic Factors Jacob Cherian 1 & Jolly Jacob 2 1 College of Business Administration, Abu Dhabi University, Abu Dhabi, UAE 2 College of Arts and Sciences, Abu Dhabi University, Abu Dhabi, UAE Correspondence: Jacob Poopada Cherian, Department of Management, College of Business Administration, Abu Dhabi University, Abu Dhabi, UAE. Tel: 971-5-015-646. E-mail: jacob.cherian@adu.ac.ae Received: July 16, 2012 Accepted: August 2, 2012 Online Published: September 4, 2012 doi:10.5539/ijef.v4n10p131 URL: http://dx.doi.org/10.5539/ijef.v4n10p131 Abstract Waste management is a complex process that requires a lot of information from various sources such as factors on waste generation and waste quantity forecasts. When operations related to promotion of waste management systems are considered it is observed that generation of waste and planning is found to be influenced by different factor of which are impacted by socio demographics. The main aim of this paper is to review previously tested models related to municipal solid waste generation and identify possible factors which will help in identifying the crucial design options within the framework of statistical modelling. Keywords: solid waste management, empirical models, socio economic factors 1. Introduction Waste management is a complex process that requires a lot of information from various sources such as factors on waste generation and waste quantity forecasts ( Bovea et al., 2010; Zurbrügg et al., 2012). Data on the various factors that play a role in waste generation is important as it aids in estimating the consequences of changes in general conditions like economic system (Sjöström and Östblom 2010; Wang et al., 2011) demography (Bandara et al. 2007), domestic heating systems or waste management measures (e.g. increasing the rate of home composting) ((Lebersorger and Beigl 2011) and policy measures (Mazzanti and Zoboli, 2008). A number of studies have focused on the influence of socio economic factors in a bid to understand, define and forecast the unit rate of waste generation and composition of solid waste (Mazzanti, M., & Zoboli, R. 2009; Bandara et al., 2007; Emery et al., 2003). Some of the most common variables that are analyzed are number of individuals in a dwelling, age, sex, land usage, communications, ethnicity of the populations and productive activities (Emery et al., 2003). When operations related to promotion of waste management systems are considered it is observed that generation of waste and planning is found to be influenced by different factor of which are impacted by socio demographics including Amount of waste generated and personnel required: This is directly dependent on the population density and other factors (Henry et al., 2006). Cost of operations: Greater the amount of waste generated, greater is the cost of operations (Christensen, 2011). A significant issue that every nation faces is the need for a proper disposal system of the huge solid wastes that are generated every year. According to (Alhumoud, 2005; Christensen 2011), developed countries have always had to face significant difficulties in trying to devise a manageable way to dispose the waste that they generate. When it comes to non industrialized countries, (Koushki and Alhumoud, 2002; Al-Khatib et al., 2007; Henry et al., 2006), state that a lack of awareness and knowledge coupled with the increasing amount of lands being cleared for waste disposal and storage purposes are one of the major concerns. Therefore although a specific waste disposal protocol or solution cannot be implemented or set due to the ever changing demographics and needs of the population, there is a need to identify the influence of socio demographic factors on municipal solid waste management systems which are currently planned and operated and arrive at different models which will help forecast better models of solid waste management.