The AHP approach for selecting an automobile purchase model
Dae-Ho Byun
*Management Information Systems, Division of Business Administration, College of Commerce and Economics, Kyungsung University, Daeyeon-Dong 110-1, Nam-Ku, Pusan 608736, South Korea
Received 24 July 1998; received in revised form 10 August 2000; accepted 1 October 2000
Abstract
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 pairwise 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.#2001 Elsevier Science B.V. All rights reserved.
Keywords:Analytic hierarchy process; Car purchase model; Group decision-making; Sensitivity analysis; Automobile
1. Introduction
Cars 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 re¯ection of customer preference. Before someone shops for a new car, he or she want to take a look at ®nances 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 considerations. Other
important attributes include: fuel economy; comfort and convenience features; insurance information; spe-ci®cation and warranties and resale value.
Constant changes in customer demands lead man-ufactures to produce new and improved designs. Automation of manufacturing technologies allows this. Recently the production life cycle has become shorter. For example, General Motors in the USA is leading the industry in developing ground-breaking technologies to improve the driving experience and to meet the changing needs and life styles of modern drivers. They are making efforts to lower the cost of the technology to a level that will make advanced cars an attractive purchase.
As the automobile market becomes more competi-tive, the industry has no choice but to adopt innovation that brings better customer service. Many customers seek advice from car experts or friends when purchas-ing a car. In many cases, there are times when the price
*Tel.:82-51-620-4452; fax:82-51-625-4536.
E-mail address: [email protected] (D.-H. Byun).
and special features do not match the budget. The frequency of making such a decision is much less, as the average person does not purchase cars annually and the effect is greater than, say that of buying laundry powder [8]. An appropriate decision-making method for selecting the best car is useful to both customers and producers. An analytic method not only reduces the dealer's burden, but also may increase sales. In addition, it plays a kind of strategic role, increasing customer services in the competitive mar-ket environment.
The analytic hierarchy process (AHP) is an intui-tively easy method for formulating and analyzing decisions [13,14]. It was developed to solve a speci®c class of problems that involves prioritization of poten-tial alternate solutions. This is achieved by evaluation of a set of criteria elements and sub-criteria elements through a series of pairwise comparisons. Numerous applications of the AHP have been made since its development and it has been applied to many types of decision problems [2,9,11,16].
Together with the AHP, the Delphi process repre-sents one of the ®rst formalized methods for system-atically obtaining and aggregating group judgements [7]. The Delphi method was developed by the RAND corporation in the 1960's. The method is generally used as a forecasting technique. Also, group decision-making problems are easily formulated by the Expert Choice software package [3,5]; this allows the deci-sion-maker to derive geometric means as weights or priorities instead of using an eigenvector method. The geometric mean is an appropriate rule for combining individual judgements to obtain the group judgement for each pairwise comparison. Here the decision-maker is considering the sub-nodes in the hierarchy as part of the whole.
This paper presents extensions of the AHP with the selection of the best car model with respect to the following.
1. Some inconsistency of the given pairwise compar-isons: A consistency ratio (C.R.) provides a mea-sure of the probability that the pairwise comparison matrix was filled in purely at random. The number 0.2 which is the upper limit for C.R. says that there is a 20% chance that the decision-maker will answer the questions in random manner. A value of the C:R:0:2 is typically considered tolerable.
To fulfill the Saaty's C.R. limit: repeating the survey is difficult and costly. Sometimes it is not possible to acquire consistent responses from domain experts, because they may refuse to respond to the question that appears to be burden-some. Some pairwise comparison matrices with respect to a specific criterion cannot but be included, even with a C:R: >0:2.
2. Lack of enough data: In this case, it is almost impossible to perform pairwise comparisons. For example, suppose that the buyer has not driven both car models.
On the other hand, a spreadsheet model [6,10] using a 5-point rating scheme has been used to reduce the number of pairwise comparison. There aren nÿ1=2 judgements required to develop each matrix wherenis the total number of elements being compared. The AHP is used to group decision situations by gathering the entire group together in a single session. However, how much do we assign to each individual weight? Conventionally, it is possible to combine the different judgements. One method is to multiply the judgements and take thekth root of the AHP hierarchy ifkexperts are participating. In fact, the priority of overall alter-natives tends to change according to the different weights for the decision-makers [15].
The AHP model depicted in this paper uses the following decision criteria: exterior, convenience, performance, safety, economic aspect, dealer, and warranty as well as 39 sub-criteria. For the imple-mentation of the AHP, we considered the three mid-size passenger car models as alternatives that were announced recently in the Korean domestic market.
2. Evaluation criteria
The source for deriving the evaluation criteria candidate was:
2. the use of personal experiences recorded on an online bulletin board was corrected using the Internet;
3. Korean automobile manufacturers' Internet sites were examined, with some from foreign car man-ufacturer. The sales information to a car in General Motors (http://www.gm.com) mainly represents exterior and interior features, functionality, en-gine types and specifications and price informa-tion. On the Chrysler (http://chryslercorp.com), Ford (http://www.ford.com) and Toyota (http:// www.toyota.com) homepages, the following cri-teria were considered of importance and were included in the AHP hierarchy: exterior, interior,
functionality, convenience, style, engine types, comfortableness, performance, model, color and price.
The AHP model shown in Fig. 1 consists of three levels. Exterior involves components and factors seen from the outside such as color, length and width, tyres, trunk, wheels, doors and headlamp styles. It includes the following sub-criteria: model, style, length, quality of interior decoration, number of available color types, and instrument cluster.
Convenience is related to the design of the equip-ments for easy operation. It includes: inside width, ease of loading or unloading packages, convenience of
operating instruments, modern ®ttings (such as elec-tronic systems and a burglar alarm), forward visibility and quality of the audio system.
Performance is related to the functioning of the car. It includes maximum torque, maximum speed, fuel tank capacity, braking ability, cornering ability, inside noises and traveling comforts.
Safety is enhanced by a body designed to protect the drivers and passengers against collisions. The most important safety features are those that reduce the risk of death or serious injury. It includes: airbags, anti-lock braking system ABS, impact protection systems, trunk safety, seat belts, safety of the body and number of alarm facilities. Airbags provide total chest and face protection. The ABS allows drivers full steering control and shorter stopping distance in adverse situations.
The economic aspect refers to the price and cost of a new car, or maintaining the car within budgets, etc. It includes: purchasing prices, fuel consumption per month, insurance costs and installment conditions, re-sale prices of used cars and optional equipment costs. The dealer criterion refers to personal characteris-tics and attitudes that lead the customer to make the purchasing decision. This criterion includes: visits or calls needed to persuade the customer to buy, the dealer's attitude, the dealer's expertize and belief in the dealer's promises.
The warranty criterion include: the number of service stations, ease of acquiring spare parts,
customer satisfaction after services, and the average repair time for minor troubles.
Some of these criteria are not mutually exclusive. This may be a limitation in the use of the AHP. We
Fig. 2. Procedure for determining synthesized priorities.
Table 1
Consistency ratio for each main criterion and sub-criterion
Decision-makers Parent nodes in the AHP model hierarchya
C0 C1 C2 C3 C4 C5 C6 C7
A1 0.616 1.304 0.314 0.615 0.354 0.424 2.589 0.473
A2 0.350 0.419 0.183 0.202 0.168 0.162 0.267 0.152
A3 0.756 0.175 0.191 0.235 0.214 0.132 0.062 0.301
A4 0.605 0.106 0.319 0.145 0.138 0.303 0.273 0.186
A5 0.568 0.362 0.969 0.570 0.738 0.816 0.419 0.415
A6 0.218 0.219 0.050 0.114 0.155 0.289 0.085 0.111
B1 0.509 0.314 0.423 0.219 0.096 0.159 0.433 0.204
B2 0.104 0.125 0.439 0.123 0.122 0.160 0.135 0.179
B3 0.686 0.897 1.246 1.592 0.504 0.496 2.319 0.469
C1 0.598 0.193 0.133 0.190 0.333 1.018 0.246 0.308
C2 0.409 1.489 1.122 0.477 0.404 0.401 0.389 0.358
C3 0.319 0.390 0.317 0.278 0.090 0.230 0.168 0.140
C4 0.469 0.083 0.116 0.190 0.408 0.210 0.250 0.429
should consider all interdependent components at the same time. For example, we can change the height of a car, lowering it to help increase its maximum speed, or the seats could be specially designed to make the car safer or to reduce noise.
3. Implementation and ranking
We mailed questionnaires to each of two groups. The ®rst group was given a questionnaire that con-tained a pairwise comparison sheet. The members consisted of 13 managers who were serving in the sales department and who had experience exceeding 10 years (see Appendix A for this questionnaire). Respondents were domain experts who easily recog-nized their own sales products and have valuable knowledge about the customer requirements and pre-ferences. Twenty-two potential customers with experi-ence over 7 years were in the second group (see Appendix B). They answered about their satisfaction with their current car.
A procedure of prioritizing each car model is shown in Fig. 2. Table 1 shows the C.R. for each individual, where the circle represents meaningful C.R. Using Expert Choice, we obtained the synthesized priorities of the main criteria and sub-criteria. The reason that the group's weight is 1/C.R., is to assign higher weights for higher consistent persons. As a result, safety gains is the highest priority in the main criteria. The body safety is especially important.
The synthesized priorities and ranks resulted in Table 2 (Case-II). The priorities of the sub-criteria are not proportional to those of the main criteria. This means the decision-makers have different opinions on the importance of the main criteria. By synthesizing the drivers' rating values with the priorities, we obtain the priorities of the car models and the ranks with respect to the goal and synthesized priorities for each main criterion when the C.R. is bounded by the limit (see Table 3).
In Case-I and Case-II, the computational methods used are reasonable when the groups' consistency is more important than the individual ones. Because the conventional AHP has no choice but to increase the Delphi rounds in order to increase the groups' con-sistency, much effort is required to reduce the C.R. If the Delphi rounds are not suf®ciently processed, it is
unreliable through the inclusion of inconsistent matrices [12].
Using the Spearman rank correlation test [1], acceptingH0means that the ranks are either uncorre-lated or negatively correuncorre-lated. That is, two decision-makers exhibit an insigni®cant level of agreement in ranking for each criterion. RejectingH0means that the
Table 2
Synthesized priorities and ranks for criteria (Case-II)
Main criteria Sub-criteria Priority Rank
Exterior (0.116) Style 0.0532 3
Model 0.0380 8
Length 0.0189 25
Decoration 0.0176 27 Color type 0.0118 32 Instrument cluster 0.0073 37
Convenience (0.078) Fittings 0.0629 2 Operating 0.0267 16 Audio system 0.0190 24 Visibility 0.0139 29 Loading 0.0124 30 Inside width 0.0119 31
Performance (0.192) Braking 0.0401 7
Noise 0.0380 9
Cornering 0.0310 11
Speed 0.0179 26
Torque 0.0093 34
Comfort 0.0064 38 Fuel tank 0.0039 39
Safety (0.291) Body 0.0414 6
Seat belts 0.0353 10
ABS 0.0300 12
Alarm 0.0264 18
Airbags 0.0199 22
Impact 0.0154 28
Trunk 0.0077 36
Economic aspect (0.159) Insurance 0.0300 13
Resale 0.0286 14
Fuel 0.0273 15
Price 0.0222 20
Equipment 0.0093 35
Dealer (0.085) Expertize 0.0525 4
Visit 0.0246 19
Attitude 0.0211 21
Belief 0.0193 23
ranks are positively correlated. As shown in Table 4, we conclude that there are signi®cant effects between groups since the rate of the H0 acceptance is 83% (65=78100). This shows that Case-I is the more appropriate method. It re¯ects greater agreement between groups.
4. Sensitivity analysis
Sensitivity analysis allowed us to verify the results of the decision. A sensitivity analysis can be formed to see how sensitive the alternatives are to change with the importance of the criteria. The Expert Choice
implementation of AHP provides four graphical sen-sitivity analysis modes: dynamic, gradient, perfor-mance and two-dimensional analysis [4]. Here performance sensitivity analysis is employed. It depicts how well each alternative performs on each criterion by increasing or decreasing the importance of the criteria. In addition to this, each sub-criterion performs on each main criterion by increasing or decreasing the importance of the main criteria. It should be noted that if a criterion is not sensitive, it would be better to eliminate it from the AHP model. In the case of increasing importance of a criterion to the maximum value of 1.0, we assigned the alternative that gained the highest rank to score 5 and the lowest rank to score 1. The value of Model 1 is 25, Model 2 is 21 and Model 3 is 15. In summary, we can conclude Model 1 is the best among the alternatives, although the highest priorities were different in Case-I and Case-II.
5. Conclusion
Our paper presented a decision-making method for selecting the best passenger car models through com-bining the AHP and a spreadsheet model. The C.R. is used as the decision-maker's weights. As an imple-mentation of the AHP, three car models were prior-itized. Through the sensitivity analysis, the fact that Model 1 ranked the highest, is consistent with the
Table 3
Synthesized priorities and ranks with respect to the goal node and main criteria
Model 1 Model 2 Model 3
Goal node
Case-I 0.339(2) 0.341(1) 0.320(3) Case-II 0.340(1) 0.338(2) 0.322(3)
Main criteria
Exterior 0.338(2) 0.351(1) 0.311(3) Convenience 0.427(1) 0.298(2) 0.275(3) Performance 0.347(1) 0.336(2) 0.317(3) Safety 0.324(2) 0.357(1) 0.319(3) Economic aspect 0.338(2) 0.319(3) 0.342(1) Dealer 0.287(3) 0.351(2) 0.362(1) Warranty 0.356(1) 0.322(2) 0.322(2)
Table 4
The Spearman rank correlation testa
C1 C2 C3 C4 C5 C6 C7 Sd2 Rho z Accept
vdots vdots vdots vdots vdots . . .
vdots vdots vdots vdots . . .
result of the highest market share. The sales volumes during 1999 for Model 1, Model 2, and Model 3 were 76,771, 38,705 and 29,797, respectively.
An appropriate method for selecting the best car would be helpful to manufactures and dealers. While the size of decision-making groups is larger, custo-mers can receive help from expert groups. A systema-tic approach could contribute to reduce much
advertising costs and shorten time consuming pur-chasing procedures. There are obvious limitations of the method. It depends on qualitative data in the evaluation of a car model by its owners. It would be better if convenience, comfort, visibility and per-formance of brake systems could be evaluated more objectively by means of the data obtained by results of testing.
Appendix A. Questionnaire items for dealers
Compare the relative preference with respect to: main criteria<goal
Evaluation criteria
Numerical scale Evaluation
criteria
Exterior 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Convenience
Exterior 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Performance
Exterior 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Safety
Exterior 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Economic aspect
Exterior 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Dealer
Exterior 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Warranty
Convenience 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Performance
Convenience 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Safety
Convenience 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Economic aspect
Convenience 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Dealer
Convenience 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Warranty
Performance 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Safety
Performance 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Economic aspect
Performance 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Dealer
Performance 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Warranty
Safety 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Economic aspect
Safety 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Dealer
Safety 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Warranty
Economic aspect
9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Dealer
Economic aspect
9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Warranty
Dealer 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Warranty
Compare the relative preference with respect to: sub-criteria<exterior
Evaluation criteria
Numerical scale Evaluation
criteria
Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Style
Model 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 Length
1. How many different types of body colors does the car model have? ( )
2. How many kinds of modern fittings provided as optional specifications does the car model have? ( )
3. Does the car model provide airbags? ( ) 4. How many alarm facilities does the car model
have? ( )
5. How many times does dealers visit a customer to sell a car on average? ( )
6. How many service stations are there for repairing each car maker? ( )
7. How long does it take to fix minor car troubles on average? ( )
Appendix B. Questionnaire items for drivers
1. How many years have you driven? ( ) years What do you think about your current car?
2. Style
Bad Normal Excellent
1 3 5
2 4
3. Quality of interior decoration
Bad Normal Excellent
5. Ease of loading or unloading packages
Bad Normal Excellent
1 2 5
2 4
6. Conveniences of operating instruments
Bad Normal Excellent
8. Quality of the audio system
Bad Normal Excellent
13. Performance of the ABS facility
Bad Normal Excellent
1 3 5
2 4
14. Impact protection systems
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Dae-Ho Byunis an Assistant Professor of Management Information Systems at Kyungsung University at Pusan, Repub-lic of Korea. He received his Ph D degree from Pohang University of Science and Technology, his MS degree from Korea Advanced Institute of Science and Technology and his BS degree from Korea University at the Department of Industrial Engineering. He worked in Daewoo Motor company as a system analyst from 1987 to 1991. He has published in Expert Systems With Applications, Expert Systems, Human Systems Management, Journal of End User Computing, International Journal of Information Management, Encyclopedia of Computer Science and Technology, Encyclopedia of Library and Information Science and International Journal of Computer Applications in Technology. His research interests include knowledge-based expert systems, managerial decision-making using the analytic hierarchy process and electronic commerce.
16. Seat belts
Bad Normal Excellent
1 3 5
2 4
17. Safety of the body
Bad Normal Excellent
20. Belief in the dealers' promises
Bad Normal Excellent
1 3 5
2 4
21. Ease of acquiring spare parts
Bad Normal Excellent
1 3 5
2 4
22. Customer satisfaction after services
Bad Normal Excellent
1 3 5
