Integrated Criteria Decision Making And Multi Criteria Aggregation

Such criteria may include: profit; cost; return on investment (ROI); market share; capacity; risk; and / or, cash flow, to name a few. Qualitative criteria may include: competitive advantage; customer satisfaction; employee morale; corporate image; ease of implementation; synergy; ethics; safety; and / or goodwill, to name a few. There may be other criteria that the Learner / group have determined are essential to the decision making process. Ensure that the criteria chosen are clearly articulated and described.

Provide a description of a scenario in which this kind of decision between two choices, based on weighing their underlying attributes, applies in the “real-world” business setting. Furthermore, what are the benefits and drawbacks, if any, to this method of decision making?

the methods people use measure their satisfaction and how that could result in equitable and

And lastly, the decision making element entails making decisions amid multiple options; the idea is looking at all the data and making the most educated decision possible (Baker & Baker, 2014).

Rational decision making Rational decision making provides a structured and sequenced approach to decision making (Bazerman and Moore, 2013). Using such an approach can help to ensure discipline and consistency is built into decision making process. As the word rational suggests, this approach brings logic and order to decision making, comprising a set of steps which include generating multiple options as part of the process (Fig 2). It is thought to be the ideal way to make the correct decision, however this is difficult to achieve in real

Peacock et al. (2009) stated that “MCDA is important because the degree of conflict between criteria, or conflict between different stakeholders regarding the importance of different criteria, is such that ‘intuitive’ decision-making is unsatisfactory” (p. 127). However, they suggested using MCDA in health care planning for policy makers, they stated that they did not suggest abandoning the current tools that policy makers used to make decision. Therefore, in this review, I have also included an example from priority setting in health interventions without MCDA as well.

There are different methods to solve multi-criteria decision-making problems. Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are two methods introduced by Tomas Saaty. AHP tries to solve the decision problem by modeling it in a hierarchy while ANP is used when the problem is so complex that cannot be modeled as a hierarchy. This complexity occurs because of the effect of criteria on each other or the effect of alternatives on criteria. The Analytic Network Process is a generalization of the Analytic Hierarchy Process. ANP approach comprises four steps [87]:

He has used both qualitative and quantitative techniques in his works. Some of the techniques used by him include MCDM approaches such as Interpretive Structural Modeling, Analytical Hierarchy Process, ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Fuzzy TOPSIS etc. He has also used hybrid approaches such as Analytical Hierarchy Process and Grey Relational Analysis, fuzzy analytical hierarchy process and genetic algorithm etc. These methodologies, although useful, when multiple criteria exist, but many times these do not provide practical real life solutions to many problems. Further, there exists high uncertainty that why one approach is preferred over other in solving a particular problem, except for few situations. It still needs to be found out whether the literature suggesting the above approaches is really used by managers. Recently, Kannan also applied statistical technique, Partial Least Squares, in one of his

The definition of Zeithaml & Bitner (2003) is slightly different from that of Thomassen: “Satisfaction is the consumer fulfilment response. It is a judgement that a product or service feature, or the product of service itself, provides a pleasurable level of consumption-related fulfilment.” The emphasis of Zeithaml & Bitner is thus on obtaining a certain satisfaction in relation to purchasing

Once a decision maker has defined the problem, he or she needs to identify the decision criteria that will be important in solving the problem. In this step, the decision maker is determining what’s relevant in making the decision. This step brings the decision maker’s interests, values, and personal preferences into the process. Identifying criteria is important because what one person thinks is relevant, another may not. Also keep in mind that any factors not identified in this step are considered as irrelevant to the decision maker.

When considering software, one must list the various criteria that the software must meet. A criteria can be defined as a standard that is used to assist in the decision making process. The following criteria may assist in choosing any system;

Multi-criteria (or) attribute decision making (MCDM/MADM) methods have very high applications in industries for solving real world engineering problems. In the present work, MCDM methods of weighted sum method (WSM), Weighted Products Method (WPM) and TOPSIS, have been employed for the computational analysis of multi-responses. AA7075 has been taken as work piece for the experimentation and the experiments were done on CNC lathe as per the Taguchi’s standard L9 Orthogonal Array. The cutting parameters of speed, feed and depth of cut were taken as experimental inputs and Material Removal Rate (MRR) and Surface Roughness (Ra) were considered as responses. From the Weighted sum method (WSM) and Weighted Products Method (WPM) the optimal combination for multi-responses were found at ninth alternative, i.e. speed: 2000 rpm, feed: 0.4 mm/rev and depth of cut: 0.75 mm. Similarly, from the TOPSIS results, the optimal combination for multi-responses were found at seventh alternative, i.e. speed: 2000 rpm, feed: 0.2 mm/rev and depth of cut: 1 mm. Analysis of variance (ANOVA) has been done by using MINITAB-16 statistical software to find the influence of cutting parameters on the multi-responses. From the ANOVA results of WSM, WPM and relative closeness coefficient (C+) of TOPSIS, it is found that feed rate has high influence (For WSM, WPM and C+ the F values are 60.50, 60.30 and 91.42 respectively) in affecting the multi-responses.

Fuzzy output set in given as input to this phase. i.e., the best case from retrieved cases.Converting the fuzzy output to the Boolean value for the acceptance of cases.

Customers will choose a product based on their perceived value of it. Satisfaction is the degree to which the actual use of a product matches the perceived value at the time of the purchase. A customer is satisfied only if the actual value is the same or exceeds the perceived value. Kotler defined five levels to a product:

3. The Multi-Criteria Decision Analysis(MCDA) process is described by taking several indicators in different scenarios which better indicates the assessment of waste management scenarios with energy recovery to get more fruitful results.