Publication details
Decision Support of Waste Management Expenditures Efficiency Assessment
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Proceedings |
| Conference | ENVIRONMENTAL SOFTWARE SYSTEMS: FOSTERING INFORMATION SHARING |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1007/978-3-642-41151-9_61 |
| Field | Management and administrative |
| Keywords | cost-effectiveness analysis; municipal expenditures; efficiency; waste management; decision support; ICT; municipal solid waste |
| Description | This paper is devoted to the development of methodology and information and communication technology tools for decision support in the public sector. It analyses appropriate metrics for a municipal solid waste management expenditure (MSWE) efficiency assessment using cost-effectiveness Analysis (CEA). In addition to many other methodological issues, finding a proper output (performance, outcome) measurement is important. From the point of view of municipalities, such a measurement ought to be as clear and simple to use as possible. We analyse three possible criteria – total generated municipal solid waste, population, and municipality area – for evaluating MSWE efficiency in order to examine their appropriateness for municipal administration. The analysis covers three years, from 2009 to 2011, and municipalities from the South Moravian Region of the Czech Republic. We focus on a sample of 21 municipalities with specific administrative status. Expenditures were estimated using open public data from the Czech Ministry of Finance municipal accounts database. Correlation analysis showed a very strong relationship between the three chosen criteria. Public administration can certainly use all of the criteria for an efficiency assessment of MSWE to aid in decision making. However, the most suitable criterion to be population, since efficiency analysis results showed a strong correlation between population and both CEA for waste amount and CEA for municipality area. Moreover, population has a stronger relationship with MSWE than either of the other two criteria. |
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