Product-oriented ecological information systems and life-cycle management: quantitative and qualitative analyses in the German chemical and electrical industries

Progress in Industrial Ecology

Volumn 2, Issue 1, 2005, Pages 89-106

  Konrad, Wilfried ^a  

^a Institute for Ecological Economy Research (I W)   (Germany)

Author keywords

case studies; checklists; chemical industry; cluster analysis; electrical industry; Environmental Performance Indicators (EPI); Life Cycle Assessment (LCA); life cycle management; Product oriented ecological Information Systems (PIS); sustainability

Indexed keywords

EID: 84925791110     PISSN: 14768917     EISSN: 14788764     Source Type: Journal    
DOI: 10.1504/PIE.2005.006779     Document Type: Article

References (24)

1. Baumann, H. (1996) ‘LCA use in Swedish industry’, The International Journal of Life Cycle Assessment, Vol. 1, No. 3, pp.122–126.
2. Berkhout, F. and Howes, R. (1997) ‘The adoption of life-cycle approaches by industry: patterns and impacts’, Resources, Conservation, and Recycling, Vol. 20, No. 2, pp.71–94.
3. Erkman, S. (1997) ‘Industrial ecology: an historical view’, Journal of Cleaner Production, Vol. 5, Nos. 1–2, pp.1–10.
4. Frankl, P. and Rubik, F. (2000) Life Cycle Assessment in Industry and Business. Adoption Patterns, Applications and Implications, Berlin et al.: Springer.
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6. Hanssen, O.J. (1999) ‘Status of Life Cycle Assessment (LCA) activities in the nordic region’, The International Journal of Life Cycle Assessment, Vol. 4, No. 6, pp.315–320.
7. Heiskanen, E. (2002) ‘The institutional logic of life cycle thinking’, Journal of Cleaner Production, Vol. 10, No. 5, pp.427–437.
8. Konrad, W. (2002) Produktbezogene Umweltinformationssysteme. Empirische Analysen zu ihrem Einsatz in Unternehmen, Berlin: Institute for Ecological Economy Research, Schriftenreihe No. 163/02.
9. Kytzia, S., Faist, M. and Baccini, P. (2004) ‘Economically extended – MFA: a material flow approach for a better understanding of food production chain’, Journal of Cleaner Production Vol. 12, Nos. 8–10, pp.877–889.
10. Ritzén, S., Hakelius, C. and Norell, M. (1996) ‘Life-cycle assessment, implementation and use in Swedish industry’, in S. Ritzén (2000) (Ed.) Integrating Environmental Aspects into Product Development – Proactive Measures, Stockholm: Royal Institute of Technology.
11. Roberts, B.H. (2004) ‘The application of industrial ecology principles and planning guidelines for the development of eco-industrial parks: an Australian case study’, Journal of Cleaner Production, Vol. 12, Nos. 8–10, pp.997–1010.
12. StBA (German Statistics Office) (1999) Statistisches Jahrbuch 1999 für die Bundesrepublik Deutschland, Stuttgart: Metzler-Poeschel.
13. Tischner, U., Schmincke, E., Rubik, F. and Prösler, M. (2000) How to do EcoDesign? A Guide for Environmentally and Economically Sound Design, Frankfurt am Main: Form Verlag.
14. Zackrisson, M., Enroth, M. and Widing, A. (2000) Environmental Management Systems – Paper Tiger or Powerful Tool, Mölndal: The Swedish Institute of Production Engineering Research, IVF Research Publication 00828.
15. By producing and marketing their products, companies are embedded in large networks of supply and demand relations. Life-cycle oriented PIS reflect these inter-relations and analyse goods beyond the factory gates ‘from cradle to grave’. Hence, PIS are principally apt to be employed in the context of company cooperations (e.g., for product development). In the reported study, however, the main focus was on PIS application within single companies rather than on their use in sustainability networks.
16. For works of this nature, see for example Baumann (1996), Hanssen (1999), Ritzén et al. (1996), or Zackrisson et al. (2000). More complex investigation concepts, though still only referring to LCA, can be found in Berkhout and Howes (1997) and Frankl and Rubik (2000); the latter does also consider the time sequence for PIS implementation.
17. This research project was conducted in the years 2000 to 2002, with financial backing from the Volkswagen foundation. Contributors to the study included Eberhard Feess, Frieder Rubik, Ulla Simshäuser, Sabine Walter, Björn Zapfel, and the author.
18. We chose these sectors because they both belong to the economically most important branches of German industry, but with regards to their environmental relevance, stand in very marked contrast to one another. The chemical industry has the highest energy consumption of all German industry branches. The opposite is true for the electrical industry – it has the lowest energy consumption among the leading German industry sectors (StBA, 1999,p.202).
19. Normally, cluster analysis provides for more than two different sub-groups. Due to the small number of cases (61 companies), however, it was not possible in this study to generate more than two statistically plausible clusters.
20. In this case, the median reveals that half of the companies in both sectors have up to 330 employees. The differences between the two sectors apparently arising from the diverging averages can therefore be explained by a small number of very large chemical enterprises. The median is less sensitive to such outliers and, thus, in this case more meaningful than the average.
21. In this case, the median shows that sector differences are more due to turnover than to the number of employees.
22. It would be going beyond the scope of this essay to describe each such PIS in any detail. For this purpose, see Konrad (2002,p.25 et seq.) and Tischner et al. (2000).
23. As it becomes clear from the results of the cluster analysis (see Chapter 2.6), these evaluation differences suggest the effects not so much of various types of PIS, but rather of various types of company and their respective orientation with regards to PIS usage.
24. Differentiating between the two company types according to the sector to which they belong shows that this connection is, in statistical terms, only slightly significant.