SEKE 2012 Proceedings - Knowledge Systems Institute

Figure 6. Three proposals containing most promising issues.
Using AHP, we can rate the issues according to each
proposal. Tables II and III are used as reference for making the
decision for what points to give to each issue in a proposal. If
the issues belong to the goals that are cooperative, then the
points are higher, and the points are lower if the goals are
conflicting to each other. Table IV shows three proposals with
the points given for different issues. For each issue, we
compare three proposals pair-wise by finding geometric mean
for weighting the issues, and the results are listed in Table V.
TABLE IV.
POINTS FOR ISSUES IN DIFFERENT PROPOSALS
Proposal Price Eloquence Necessity Quantity Quality Budget
A 1 1 5 3 1 5
B 5 3 6 5 6 3
C 6 4 6 7 8 3
TABLE V.
WEIGHTING FOR ISSUES ACCORDING TO PROPOSALS
Proposal Price Eloquence Necessity Quantity Quality Budget
A 0.083 0.125 0.294 0.200 0.067 0.455
B 0.417 0.375 0.353 0.333 0.400 0.273
C 0.500 0.500 0.353 0.467 0.533 0.273
Considering Table V as a matrix M ij and the normalized
matrix in Figure 5 as N j , we can evaluate proposals by the sum
of the product of weights. Thus, P i =M ij N j where P i is the
evaluation for Proposals A to C, produces P 0 =0.376, P 1 =0.376,
and P 2 =0.376. From the result, we see that the proposal C is
most promising. However, it contains more issues and requires
more computation than Proposals A or B. If the computation is
a concern, then Proposal B is a good alternative.
IV. DISCUSSION AND CONCLUSION
The effectiveness (E) of a set of issues can be calculated by
E= IU i /PI i , where the numerator is the sum of weights of
all issues used (a set IU) in a proposal and denominator is the
sum of weights of all possible issues (a set PI) available. When
negotiating a purchase, usually the issue Price is a natural
choice as most influential to affect the sales of an item.
However, compared to those proposals mentioned above, E
becomes small if Price is the only issue in IU. Besides this
intuitive discussion, we have developed a simulation
environment to execute negotiation process to compare the use
of different sets of issues. For experiment, negotiation is run 50
times. The success rate of a salesperson is set as 20% for a
correctly chosen issue; otherwise, a salesperson has only 5%
success rate to land a deal. If no deal is reached, then 1% to 3%
price cut is tried until the price offered is lower than 90% of the
original price. The negotiation based on the single issue Price
resulted in 19 successes and 31 failures while Proposal A had
28 successes, Proposal B 32 su ccesses, and Proposal C 38
successes. A notable performance of Proposal C is that it
enabled a deal with 5 or fewer rounds of negotiation. As seen
in Table VI, the result of the simulation showed that the more
effective the issues are, the higher the number of success
becomes.
Success
6
Price 19
(31.6%)
9
A 28
(32.1%)
8
B 32
(25%)
14
C 38
(36.8%)
TABLE VI.
SIMULATION RESULTS
Rounds to reach a deal
1 2 3 4 5 6~10
8
(42.1%)
5
(17.9%)
11
(34.4%)
7
(18.4%)
1
(5.3%)
8
(28.6%)
3
(9.4%)
7
(18.4%)
1
(5.3%)
2
(7.1%)
3
(9.4%)
4
(10.5%)
1
(5.3%)
3
(10.7%)
4
(12.5%)
6
(15.8%)
2
(10.6%)
1
(3.6%)
2
(6.25%)
0
( 0% )
Many agent negotiation strategies depend on th e correct
issues to work on. The selection of issues for negotiation is
important, and there is a need for a process in determining
usable issues. This paper proposes a systematical method based
on goal-driven requirements analysis to produce a set of issues
for agent negotiation. The issues are traceable to user
requirements for better evaluation of effectiveness of issues
used and also the maintenance of issues. The relationship
between issues is studied to u nderstand whether they are in
cooperative or conflicting matter. Another important advantage
of this method is to have information for comparing the
number of issues to be used in a negotiation process. By
integrating the GDUC and AHP methods, our method provide
a way for the user to determine suitable issues according to the
user requirements. The future work is to consider the
dependency among issues, so that a proposal consists of a set of
mutually related issues.
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Failure
31
22
18
12
762