Page 342 - Solid Waste Analysis and Minimization a Systems Approach

320 MODEL SUMMARY AND RECOMMENDATIONS FOR FUTURE RESEARCH

to environmental regulators and businesses. However, the majority of the research
to date has several critical gaps including a focus on aggregate solid waste analyses
for entire regions, not individual companies. In addition, most studies lack empirical
support and rigorous statistical support specifically related to waste generation
performance.
In this research, a survey was developed to gather data necessary to develop an inte-
grated model to predict and evaluate solid waste generation rates of businesses and
government agencies. The conclusions of this research were

■ U.S. businesses can be grouped based on waste generation compositions (estab-
lished 22 waste generating groups).
■ Solid waste quantities of individual companies can be predicted and evaluated using
statistical techniques and quality control concepts.
■ Incentives for businesses to increase recycling levels can be effectively and effi-
ciently determined (in particular cost-benefits).

One important result from this research is the strong evidence that U.S. businesses
and government agencies can be statistically grouped based upon business functions
and waste stream compositions. Furthermore, the research identified the variables that
significantly influence solid waste quantities and should be monitored to predict and
control generation rates. Variables that do not aid in the prediction of solid waste were
also identified, such as ISO 9000 registration or location.
The findings of this research offer companies and regulators an effective means to
improve environmental performance and allow them to predict and evaluate waste
generation rates. Using the results of the research, companies can learn more about the
strengths and weaknesses in their waste generation performance and assess their per-
formance versus industry specific benchmarks. The results of this study also can form
a foundation for further research. Recommendations for further study include con-
ducting a broader study with more data, incorporating an economic evaluation module
into the environmental model, and further applying artificial intelligence to improve
the model.