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waste groups. Second, the regression analysis showed solid waste generation is reduced by ISO 14001 certi cation of the eight manufacturing groups, indicating the usefulness of the certi cation to decrease environmental impact. Several trends were also observed. A trend is visible between average waste generation and solid waste disposal costs per ton for these groups as displayed in Table 16.10 and Fig. 16.13.
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0 0 Regression coefficient for landfill disposal cost ($/ton) 1 2 3 4 5 6 7 8 9 Average waste per company for the 8 waste groups (tons) 500 1000 1500 2000
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Figure 16.13 Waste group comparison of the average solid waste per company versus the regression coef cient for land ll disposal cost.
SOLID WASTE ESTIMATION AND PREDICTION
Examining the t values, allows for a comparison of the land ll disposal cost effects on the eight manufacturing waste groups. Wood and lumber manufacturers indicated the highest absolute value at 3.73 followed by transportation equipment manufacturers at 3.38. These two waste groups achieve greater waste reduction from increased waste costs, indicating they are more sensitive to the economic impact of waste generation. On the contrary, electronic manufacturers and chemical manufacturers were least sensitive. As shown, the greater the average waste per company a waste group generates, the more costly the regression cost coef cient. This indicates solid waste generation is economically driven. The more waste a company within the groups generates the more sensitive to disposal costs. Investigating ISO 14001 certi cation also indicted the more average waste a waste group generated the more sensitive to waste reduction the group. Table 16.11 and Fig. 16.14 display these ndings. As shown by the t value analysis for ISO 14001 certi cation, transportation equipment manufacturers and chemical manufacturers achieve the largest relative solid waste reductions from certi cation. This indicates these two waste groups achieve the largest relative waste reduction gains from the attainment of ISO 14001. An analysis of variance (ANOVA) was conducted to examine the difference in the average waste per company for the eight manufacturing waste groups. This was conducted to examine if signi cant differences existed in the amount of waste these waste
TABLE 16.11 WASTE GROUP COMPARISON OF THE AVERAGE SOLID WASTE PER COMPANY VERSUS THE REGRESSION COEFFICIENT FOR ISO 14001 CERTIFICATION AVERAGE SOLID WASTE PER COMPANY PER ABBREVIATION YEAR (TONS)
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ISO 14001 REGRESSION COEFFICIENT
T VALUE
Wood and lumber manufacturers Metal manufacturers Food manufacturers Chemical and rubber manufacturers Paper manufacturers and publishers Textile and fabric manufacturers Electronic manufacturers Transportation equipment manufacturers
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1707.9 1313.6 784.8 749.8 726.0 584.7 194.5 653.5
217.6 214.9 183.5 140.4 114.8 92.3 56.3 56.2
2.99 2.52 2.89 3.47 2.48 2.36 2.36 4.51
ANALYSIS OF RESULTS AND SUMMARY OF FINDINGS
0 0 Regression coefficient for ISO 14001 certification 50 500 1000 1500 2000
100
150
200
250 Average waste per company for the 8 waste groups (tons)
Figure 16.14 Waste group comparison of the average solid waste per company versus the regression coef cient for ISO 14001 certi cation.
groups generate. Bonferroni paired t-tests were conducted to examine if each pair of waste groups generated signi cantly different amounts of waste at the 95 percent con dence level. First, a single regression equation for the eight waste groups explained by three signi cant variables was developed and is displayed below: Annual waste (tons) = 6.61(number of employees) 2.56(land ll disposal cost/ton) 116.14(ISO 14001 certi cation) Figure 16.15 shows the results for the regression equation developed consolidating all eight manufacturing companies into one group. As shown from the ANOVA table in Fig. 16.15, based on the F-statistic a relationship was established (F = 16.82). Examining the t statistics for each independent variable indicates only the number of employees was signi cant at the 95 percent con dence level (t = 2.345). When lumping the eight manufacturing groups, detail was lost and land ll disposal costs (t = 1.465) and ISO 14001 Certi cation (t = 1.907) were no longer signi cant at the 95 percent con dence level. Also the coef cient of determination was only 30 percent, indicating the relationship is poor. An ANOVA analysis on waste groups with three signi cant variables based on average waste per company using Bonferroni paired t-tests was conducted to examine differences between the eight manufacturing waste groups. Bonferroni paired t-tests is an approach for adjusting the selected alpha level to control the overall Type I error rate (Hair et al., 1998). The Type I error rate is also known as a false positive or the error of rejecting the null hypothesis when it is actually true. This procedure involves computing the adjusted rate as alpha divided by the number of statistical tests to be performed and then using the adjusted rate as the critical value in each separate test. Table 16.12 shows the data used for this analysis.
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