The Reverse Supply Chain of E-Waste Management Processes
Read this article. The authors propose that reverse supply chains can achieve economic as well as environmental and social benefits. Regarding your electronic devices, do you know how you can recycle and reverse supply them back to a vendor?
Correlation between WEEE Collection Performance and Collection Center Distribution
In order to verify the existence of a relationship between WEEE collection and CC distribution national, we have analyzed the correlation between the quantity (kg) of e-waste collected and the number of WEEE's CCs for the period 2009–2017 for the Italian provinces.
The analysis confirms that a correlation exists being the average correlation coefficient equal to 0.67. Moreover, analyzing the time series of the distribution of the correlation coefficient by territorial areas, it emerges that it decreases for all of the areas (North: −9.5%, Central: −6.3%; South: −8.7%.). Thus, we can suppose that, even though the weight of the role of the collecting infrastructure is becoming less crucial, it still remains a critical aspect of the Italian WEEE management system, which requires further analysis.
Table 10 is a representation at a glance of the comparison of the two dimensions considered: positive, negative or null variation (+, −, =) of WEEE collection performance and CCs. The matrix considers each year of the period 2009–2017 and the cells represent the number of times in which the provinces have registered a positive (+), negative (−) and null (=) variation. For example, the cell "++" shows the times the provinces have incremented both WEEE's collection and CCs (37.6% for all the Italian provinces). This matrix permits acquiring useful information to compare the behavior of provinces by territorial area in the considered period. In particular, we can distinguish both the presence/absence of the correlation and to obtain information of the trends of specific areas and provinces (this last aspect is not considered in this paper).
Table 10. WEEE Collection and Collection Centers by variation correlation groups.
| OLLECTION | + | Area 2 - Group (+ −) | Area 2 - Group (+ =) | Area 1 - Group (+ +) |
| Central - (1.4%) | Central - (4%) | Central - (10.5%) | ||
| North - (6.3%) | North - (9.4%) | North - (12.6%) | ||
| South - (2.3%) | South - (4%) | South - (14.5%) | ||
| Italy - (9.9%) | Italy - (17.4%) | Italy - (37.6%) | ||
| - | Area 1 - Group (−−) | Area 3 - Group (− =) | Area 3 - Group (− +) | |
| Central - (1.5%) | Central - (2.7%) | Central - (3.6%) | ||
| North - (3.1%) | North - (5.3%) | North - (6%) | ||
| South - (2.4%) | South - (3.3%) | South - (7.2%) | ||
| Italy - (6.9%) | Italy - (11.4%) | Italy - (16.8%) | ||
| − | = | + | ||
| COLLECTION CENTERS | ||||
- AREA 1-Groups (++) and (−−). These groups have a positive even though opposite relation. The Group (++) is the highest (37.6%). The Group (−−) which represents a contemporary reduction of the two dimensions is the lowest (6.9%). Both of these results are in line with the high correlation coefficient mentioned above. We can guess that the first group have carried out structural investments; meanwhile, the second have reduced the number of CCs. The Southern provinces are the most represented in the Group (++) (14.5%)
- AREA 2-Groups (+−) and (+=). The provinces in these groups (9.9% + 17.4%) are not in line with the correlation hypothesis. They have showed an increase in the WEEE collection together with a reduced or stable number of CCs. These results are probably due to the investment in the promotion (information and education campaigns, media awareness initiatives, etc.) or to the improvement of e-waste management processes since the CC investments were made previously. The Northern provinces are the most represented (total 15.7%)
- AREA 3-Groups (−=) and
(−+). These groups show a worsening of the collection result even though
have increased or unchanged the number of CCs, Thus, they are not
coherent with the correlation hypothesis. They both represent the 28.2%
of the total and denote an area of ineffectiveness since investment in
CCs do not result in collection improvements. We can guess that
different problems affect the WEEE management system for these
provinces. The Northern provinces show the higher presence (11.3%) even
though Southern provinces are the highest in the group (−+), which is
the most effective.
| Groups by WEEE Collected Transition Matrix | Province (Area) | Population in 2017 | Transition Behavior of CC State |
|---|---|---|---|
| Best performing provinces(6) | Aosta (N) | 126,883 | MPC to HPC (+1) |
| Bologna (N) | 1,009,210 | MPC to MPC (-) | |
| Como (N) | 600,190 | MPC to MPC (-) | |
| Gorizia(N) | 139,673 | LPC to MPC (+1) | |
| Isernia (S) | 85,805 | MPC to HPC (+1) | |
| Nuoro(S) | 156,096 | MPC to HPC (+1) | |
| Second-best performing provinces(2) | Sassari (S) | 333,116 | MPC to HPC (+1) |
| Trento (N) | 538,604 | HPC to HPC (+1) | |
| Worst performing provinces ** (11) | Agrigento (S) | 442,049 | LPC to LPC (-) |
| Barletta-Andria-Trani (S) | 392,546 | LPC to LPC (-) | |
| Caltanissetta (S) | 269,710 | LPC to LPC (-) | |
| Cosenza (S) | 711,739 | LPC to LPC (-) | |
| Crotone(S) | 175,566 | LPC to LPC (-) | |
| Enna (S) | 168,052 | LPC to LPC (-) | |
| Foggia (S) | 628,556 | LPC to MPC (+1) | |
| Pescara (C) | 321,309 | LPC to LPC (-) | |
| Siracusa (S) | 402,822 | LPC to LPC (-) | |
| Taranto (S) | 583,479 | LPC to LPC (-) | |
| ViboValentia (S) | 161,619 | LPC to LPC (-) |