Decision-making under uncertainty – the integrated approach of the AHP and Bayesian analysis

Figures & data

Table 1. Matrix of payments.

	C1	C2	C3	C4	C5	C6
A1	70	63,000	4000	2	5	4
A2	65	77,000	3000	5	3	8
A3	55	50,000	5000	3	3	10
A4	60	60,000	2000	4	4	5

Source: Created by authors.

Figure 1. Hierarchical structure of the problem.

Source: Authors’ graphic presentation using Expert Choice.

Figure 2. Pairwise comparison matrix of criteria.

Source: Authors’ calculation using Expert Choice.

Figure 3. The priorities of criteria (criteria relative importance).

Source: Authors’ calculation using Expert Choice.

Figure 4. Rank of alternatives.

Source: Authors’ calculation using Expert Choice.

Table 2. Standardised data.

	C1	C2	C3	C4	C5	C6
A1	1	–0.82	–0.8	0.4	1	0.4
A2	0.93	–1	–0.6	1	0.75	0.8
A3	0.79	–0.65	–1	0.6	0.75	1
A4	0.86	–0.78	–0.4	0.8	0.8	0.5

Source: Authors’ calculation.

Table 3. Conditional probabilities of research results.

Criterion	(G)	(B)
C1	0.6	0.4
C2	0.2	0.8
C3	0.9	0.1
C4	0.5	0.5
C5	0.7	0.3
C6	0.3	0.7

Source: Authors’ calculation.

Table 4. The expected utility of alternatives based on a posteriori probabilities.

Expected utility of alternative	Outcome (G)	Outcome (B)
EU(A1)	0.035	–0.003
EU(A2)	–0.011	0.08
EU(A3)	–0.022	0.204
EU(A4)	0.179	0.066

Source: Authors’ calculation.

Figure 5. Rank of alternatives in the case of outcome G.

Source: Authors’ calculation using Expert Choice.

Figure 6. Rank of alternatives in the case of outcome B.

Source: Authors’ calculation using Expert Choice.