A Specialty Chemicals Site Assessment Model

Taking an opposite position, Bouyssou (1999, pp. 975-976) is critical of using DEA for selection and ranking problems because DEA does not discriminate between efficiency and convex efficiency leading to discrimination problems in the selection case and arbitrary rankings of convexly dominated alternatives. Furthermore, the ranking DEA returns only consists of each DMUs efficiency measure E. A direct interpretation of the values is impossible because it is related to the virtual DMU which is different for every DMU. Consequently, trade-off analyses to qualitatively assess the different performance levels via drill-downs into a subset of the criteria (inputs) are not supported. 

In the course of this work a site assessment model was developed together with the industrial partner cooperating in the research effort. Attained insights are provided in this chapter in a generalized form to preserve confidentiality. 

---

As discussed in Chapter 2.2.2 a broad range of criteria have to be considered if an in-depth assessment of individual sites is required. In practice matters are further complicated by the fact that the majority of sites host plants from multiple value chains. In this chapter a uniform decision support tool is developed to ensure consistent evaluations in all instances requiring site assessments. To this end Chapter 4.1 introduces the field of Multiple Criteria Decision Analysis (MCDA). Two different families of tools that could be applied to the decision problem at hand are discussed in greater detail in Chapters 4.2 and 4.3 respectively. As the use of Data Envelopment Analysis (DEA) for multiple criteria decision problems has been proposed in literature, too, the method is introduced in Chapter 4.4. An evaluation model for specialty chemicals production sites developed in cooperation with the industrial partner is presented in Chapter 4.5 and insights from application case studies are reported. 

---