The AHP approach for selecting an automobile purchase model
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The analytic hierarchy process (AHP) provides a structure on decision-making processes where there are a limited numbers of choices but each has a number of attributes. This paper explores the use of AHP for deciding on car purchase. In the context of shopping, it is important to include elements that provide attributes that make consumer decision making easier, comfortable and therefore, lead to a car purchase. As the car market becomes more competitive, there is a greater demand for innovation that provides better customer service and strategic competition in the business management. This paper presents a new methodological extension of the AHP by focusing on two issues. One combines pair wise comparison with a spreadsheet method using a 5-point rating scale. The other applies the group weight to a reciprocal consistency ratio. Three newly formed car models of midsize are used to show how the method allows choice to be prioritized and analyzed statistically.
The Analytic Hierarchy Process (AHP) is a structured technique for helping people deal with complex decisions. Rather than prescribing a "correct" decision, the AHP helps people to determine one. Based on mathematics and human psychology, it was developed by Thomas L. Saaty in the 1970s and has been extensively studied and refined since then. The AHP provides a comprehensive and rational framework for structuring a problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. It is used throughout the world in a wide variety of decision situations, in fields such as government, business, industry, healthcare, and education. Users of the AHP first decompose their decision problem into a hierarchy of more easily comprehended sub-problems, each of which can be analyzed independently. The elements of the hierarchy can relate to any aspect of the decision problem. Once the hierarchy is built, the decision makers systematically evaluate its various elements, comparing them to one another in pairs. In making the comparisons, the decision makers can use concrete data about the elements, or they can use their judgments about the elements' relative meaning and importance. It is the essence of the AHP that human judgments, and not just the underlying information, can be used in performing the evaluations. The AHP converts these evaluations to numerical values that can be processed and compared over the entire range of the problem. A numerical weight or priority is derived for each element of the hierarchy, allowing diverse and often incomm-ensurable elements to be compared to one another in a rational and consistent way. This capability distinguishes the AHP from other decision making techniques. In the final step of the process, numerical priorities are derived for each of the decision alternatives. Since these numbers represent the alternatives' relative ability to achieve the decision goal, they allow a straightforward consideration of the various courses of action.
For instance let’s consider cars (an example) which touch the lives of hundreds of millions of people nearly everywhere on this planet on a daily basis. Other than a house, a car is perhaps the largest purchase that we make. With the average cost of a car well over US$ 15,000, choosing just the right one becomes a major decision. Buying a new car is regarded as a decision-making problem and a reflection of customer preference. Someone shops for a new car, he or she want to take a look at finances and options. The possible budget is then a constraint in the decision on which car to buy. Most people shopping for a new car rank safety high among their purchase...