Part II – The effect of data on waste behaviour: The South African waste information system
Highlights
► This empirical study explores the relationship between data and resultant waste knowledge. ► The study shows that “Experience, Data and Theory” account for 54.1% of the variance in knowledge. ► A strategic framework for Municipalities emerged from this study.
Introduction
The Department of Environmental Affairs (DEAs) developed and implemented the South African Waste Information System (SAWIS) in 2006, as part of the National Waste Management Strategy Implementation (NWMSI) project. A project funded by the South African and Danish Governments. The Department requires certain public and private waste organisations to report to SAWIS on the monthly tonnages of waste that they landfill, treat, and reprocess.
An empirical study conducted by the lead author in 2006 (Godfrey and Scott, 2011) explored whether SAWIS could create opportunities beyond simply being a tool for data collection. The authors examined whether collecting data for SAWIS could also build the waste knowledge of those persons tasked with the responsibility of collecting and reporting the data. The authors posited that this new waste knowledge could lead to changes in personal behaviour and ultimately changes in the way organisations manage their waste. The 2006 study, which involved interviews with participant organisations, adopted a qualitative research design, based on an interpretive approach. A theoretical framework of learning (Miller and Morris, 1999) was used to guide the research, as it supported the empirical investigation into the role of data in building knowledge. However, while the theoretical framework provided a useful means of interpreting the interview findings, the results showed that knowledge is a necessary, but insufficient condition for resultant action (Godfrey and Scott, 2011). The theoretical framework was found to be overly simplistic for understanding the role of waste data in a developing country context such as South Africa, in that it did not account for all of the evidence gathered, particularly the existence of behavioural and situational influences (Godfrey and Scott, 2011).
The authors followed up this research from 2006, with a second empirical study in 2011. The aim of this second study is to build a more conceptually inclusive theoretical framework that supports the initial research findings and provides a basis to further explore the research question “Can the collection of data for a national waste information system change the way waste is managed in South Africa, such that there is a noticeable improvement?” The authors present an overview of two social-psychological theories with the aim of incrementally constructing a novel theoretical framework that links the collection of waste data with behaviour change. This framework is then applied to the empirical data collected in the 2011 study. The paper focuses specifically on waste management in South Africa, a developing country in a process of social and political transformation, which faces many waste management challenges (Savage, 2009).
Given the wealth of findings from this second empirical study, the results are presented in two parts. The first paper (Godfrey et al., 2012) re-examines the relationship between data, theory, and experience in building waste knowledge in South Africa, in 2011. In this, the second paper, the authors move beyond the role of waste data in building knowledge, to examining the influence of waste data on waste management behaviour.
Section snippets
Knowledge as a precursor to action
Environmental information disclosure, science communication and environmental education are three theoretical fields that have provided significant contributions to understanding the impact of environmental information on behaviour (Weiss, 2002, Denisov et al., 2005, Stephan et al., 2009).
Information strategies have been successfully used internationally as policy instruments to elicit desired policy outcomes by influencing human behaviour, either directly or indirectly (Weiss, 2002, Antweiler
Participants
Participants in the research were limited to those organisations that had submitted data to the SAWIS in 2009 and 2010. Two main types of organisations report data to SAWIS, namely public organisations (municipalities), and private organisations (itself of two types: industrial and private waste companies). Only 32 organisations in South Africa reported to SAWIS in both 2009 and 2010. In addition, two organisations reported only in 2009, and six organisations only in 2010, giving 40 unique
Global model
The statistics related to the fitted structural model are given in Table 2, Table 3, Table 4, Table 5. A relative goodness of fit (GoF) of ⩾0.9 in considered by Vinzi et al. (2010) to indicate a reasonably well supported model. The overall assessment is that the structural model presented here is sound. Dillon–Goldstein’s ρdg which is preferred to Cronbach’s α for assessing internal consistency reliability (Sijtsma, 2009), is good to very good across all latent variables, with all variables
Conclusions
Combining the process of learning and the theory of planned behaviour into a refined theoretical framework, provides an opportunity to further explore the research question “Can the collection of data for a national waste information system change the way waste is managed in South Africa, such that there is a noticeable improvement?” Fitting the data to this theoretical framework shows that there are only three regressors that have a significant effect on behaviour, namely experience, knowledge
Acknowledgements
The authors acknowledge the South African Department of Environmental Affairs for providing support for further research on this topic; the Danish Foreign Ministry through Danida, who provided project development assistance to the South Africa Government; and the Council for Scientific and Industrial Research (CSIR) for providing the financial support for this research.
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