Multiple decision makers

Interviewer Question While you were selling copy machines how did you handle accounts that had multiple decision makers ... 

Increased consistency This should result from the ability of multiple decision makers to use the same model and the associated reduction of inconsistency that would have resulted fix>m use of different data or different versions of a model. 

Almost any decision-making activity involves multiple decision makers (stakeholders). For instance, in the design of a process system, stakeholders must trade off myriad economic, environmental, and safety metrics (objectives) [1]. The stakeholders likely will disagree on which metrics should be used and on how they should be prioritized. If disagreements are not systematically managed, they can leave a subset of stakeholders strongly dissatisfied, a situation that can ultimately delay consensus reaching and lead to arbitrary decisions. 

We have presented a framework to manage conflicts among multiple decision makers. The framework enables the computation of compromise solutions in the presence of many objectives without having to form a Pareto front. The framework also provides a systematic procedure to manage conflicts by using quantifiable metrics of disagreement among stakeholders. 

Determine the weights of the criteria and their rankings based on the sample survey, using the Borda coimt method for multiple decision makers discussed in Section 6.3.9. How does their ranking compare with yours ... 

Velazquez, M. A., D. Claudio, and A. R. Ravindran. 2010. Exp>erimenfs in multiple criteria selection problems with multiple decision makers. International Journal of Operational Research. 7(4) 413—428. 

This work can be extended in several directions. The qualitative assessment scores for hazards and vulnerability can be improved by using the more elaborate quantitative models of risk developed by Bilsel and Ravindran (2012) for major disruptive events. For rare events, such as earthquakes and floods, Bilsel and Ravindran have used extreme value distributions to determine the financial impacts of disruptions. For other events, such as transportation failures, they use Taguchi s loss functions. Efforts can be taken to extend the risk assessment to consider multiple decision makers. Fuzzy logic can also be used to handle ambiguity in the scores. 

Summary This chapter deals with the various end-use applications for which radiation-curable adhesives are used. Successful application of adhesive requires the input of multiple decision makers such as product development engineers, adhesive suppliers, application equipment vendors and end product customers. Nearly 42% of the application of all adhesives comes from the packaging sector. 

Thus, tlie focus of tliis subsection is on qualitative/semiquantitative approaches tliat can yield useful information to decision-makers for a limited resource investment. There are several categories of uncertainties associated with site risk assessments. One is tlie initial selection of substances used to characterize exposures and risk on tlie basis of the sampling data and available toxicity information. Oilier sources of uncertainty are inlierent in tlie toxicity values for each substance used to characterize risk. Additional micertainties are inlierent in tlie exposure assessment for individual substances and individual exposures. These uncertainties are usually driven by uncertainty in tlie chemical monitoring data and tlie models used to estimate exposure concentrations in tlie absence of monitoring data, but can also be driven by population intake parameters. As described earlier, additional micertainties are incorporated in tlie risk assessment when exposures to several substances across multiple patliways are suimned. 

Risk assessors and decision makers both need to be prepared to communicate risk results in an understandable form to other practitioners (regulatory and registrant), stakeholders, and the public. This is particularly critical in the case of uncertainty in the assessment. Most scientists hired to perform risk assessment are thoroughly trained in their subject matter but less familiar with the demands of public presentation or the essentials of educating at multiple levels. Regulators must provide scientists and decision makers with the support and opportunity to develop skills necessary to effectively communicate with stakeholders and the public. 

At each objective level the objectives are in a first step rank-ordered according to their importance by the decision maker. In a second step, a weight of 10 is assigned to the least important objective and all other objectives are judged as multiples of 10. Consistency is assessed by comparing the initial ordinal rank ordering with the ranks obtained from the ratio weighting. 

Figure 1.1.4 Scientific and nonscientific elements of the energy system. Multiple interfaces and control loops exist between the key elements. Science and technology are the enabling elements for all energy processes and additionally serve the important purpose of informing decision makers about necessary regulatory and behavioral boundary conditions.

The issue of type I error inflation caused by multiple testing appears in many guises in the realm of new drug development. This issue is of great importance to decision-makers, and we discuss this topic again later in the chapter. For now, we have not yet provided a full answer to our research question our description of analysis of variance is incomplete without a discussion of at least one analysis method that controls the overall type I error rate when evaluating pairwise comparisons from an ANOVA. 

In reality, many chemical processes are defined by complex equations where the application of SOO techniques does not provide satisfactory results in the presence of multiple conflicting objectives. Instead, the solution lies with the use of MOO techniques. MOO refers to the simultaneous optimization of multiple, often conflicting objectives, which produces a set of alternative solutions called the Pareto domain (Deb, 2001). These solutions are said to be Pareto-optimal in the sense that no one solution is better than any other in the domain when compared on all criteria simultaneously and in the absence of any preferences for one criterion over another. The decision-maker s experience and knowledge are then incorporated into the optimization procedure in order to classify the available alternatives in terms of his/her preferences (Doumpos and Zopounidis, 2002). MOO techniques... 

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