Improving waste management through a process of learning: the South African waste information system.
Piloting of the South African Waste Information System (SAWIS) provided an opportunity to research whether the collection of data for a national waste information system could, through a process of learning, change the way that waste is managed in the country, such that there is a noticeable improvement. The interviews with officials from municipalities and private waste companies, conducted as part of the piloting of the SAWIS, highlighted that certain organizations, typically private waste companies have been successful in collecting waste data. Through a process of learning, these organizations have utilized this waste data to inform and manage their operations. The drivers of such data collection efforts were seen to be financial (business) sustainability and environmental reporting obligations, particularly where the company had an international parent company. However, participants highlighted a number of constraints, particularly within public (municipal) waste facilities which hindered both the collection of waste data and the utilization of this data to effect change in the way waste is managed. These constraints included a lack of equipment and institutional capacity in the collection of data. The utilization of this data in effecting change was further hindered by governance challenges such as politics, bureaucracy and procurement, evident in a developing country context such as South Africa. The results show that while knowledge is a necessary condition for resultant action, a theoretical framework of learning does not account for all observed factors, particularly external influences.
Godfrey
Linda
L
CSIR, Natural Resources and the Environment, PO Box 395, Pretoria, South Africa, 0001. lgodfrey@csir.co.za
Scott
Dianne
D
D003625:Data Collection; D007256:Information Systems; D012037:Refuse Disposal / Q000191:economics / Q000379:methods*; D013019:South Africa; D018505:Waste Management / Q000191:economics / Q000379:methods*