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AN ANALYTIC HIERARCHY PROCESS (AHP) APPROACH FOR PRIORITIZATION OF
EXPORT DEVELOPMENT STRATEGIES IN UZBEKISTAN
PhD
Turdibaeva Munisa
Westminster International University in Tashkent
ORCID: 0000-0002-7082-879X
Abstract.
This study applies the Analytic Hierarchy Process (AHP) to evaluate and prioritize
export development strategies for Uzbekistan. The methodology incorporates national strategic
priorities outlined by the President, government policy documents, and the opinions of expert
economists and senior officials. Based on this foundation, relevant criteria and their weights were
derived. The analysis identifies enhancing product competitiveness as the top strategy, with
significant implications for national policy.
Keywords
:
export strategy, Uzbekistan, economic priorities, AHP, competitiveness, national
programs
.
O‘ZBEKISTONDA EKSPORTNI RIVOJLANTIRISHNING USTUVOR STRATEGIYASINI
TANLASH UCHUN ANALITIK IERARXIYANI QAYTA ISHLASH (AHP) USULI
PhD
Turdibayeva Munisa
Toshkentdagi Xalqaro Vestminster universiteti
Annotatsiya
.
Ushbu tadqiqot O‘zbekiston eksportini rivojlantirish strategiyalarini baholash
va ustuvorligini aniqlash uchun Analitik
ierarxiya jarayonini (AHP) qo‘llaydi. Metodologiyada
Prezident tomonidan belgilab berilgan milliy strategik ustuvorliklar, davlat dasturlari,
shuningdek, iqtisodchi ekspertlar va yuqori mansabdor shaxslarning fikrlari inobatga olingan.
Shu asosda mezonlar va vaznlar
shakllantiriladi. Tahlil shuni ko‘rsatadiki, mahsulotlarning
raqobatbardoshligini oshirish yetakchi strategiya bo‘lib, bu davlat siyosati uchun muhim
ahamiyatga ega.
Kalit so
‘
zlar
:
eksport strategiyasi, iqtisodiy ustuvorliklar, ierarxiyalar tahlili usuli (ITU),
raqobatbardoshlik, milliy dasturlar.
МЕТОД АНАЛИЗА ИЕРАРХИЙ (МАИ) ДЛЯ ВЫБОРА ПРИОРИТЕТНОЙ СТРАТЕГИИ
РАЗВИТИЯ ЭКСПОРТА В УЗБЕКИСТАНЕ
PhD
Турдибаева
Муниса
Международный Вестминстерский университет в городе Ташкенте
Аннотация
.
В данном исследовании применяется метод анализа иерархий (МАИ)
для оценки и приоритизации стратегий развития экспорта Узбекистана. Методология
учитывает национальные стратегические приоритеты, определённые Президентом,
правительственные программы, а также мнения экспертов
-
экономистов и руководящих
чиновников. На этой основе сформированы критерии и веса. Анализ выявляет повышение
конкурентоспособности продукции как ведущую стратегию, что имеет важное значение
для государственной политики.
Ключевые слова
:
стратегия экспорта, экономические приоритеты, метод
анализа иерархий (МАИ), конкурентоспособность, национальные программы.
UOʻK:
65.012
111-117
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112
Introduction.
Uzbekistan is actively reforming its foreign trade sector in alignment with its long-term
development strategies. In recent years, a number of presidential decrees, government
programs, and national strategies have been adopted to strengthen the country’s
export
potential. Choosing the optimal path for export growth requires a structured and transparent
decision-making method. This paper employs the Analytic Hierarchy Process (AHP), developed
by Thomas Saaty in (1980), to prioritize export strategies based on well-defined national
priorities and expert opinions.
The purpose of this study is to substantiate the priority areas of export development of
Uzbekistan using the method of hierarchy analysis, which will improve the efficiency of the
country's export policy and ensure sustainable growth of the foreign trade sector.
To achieve this goal, the study solves the following tasks: (i) Analyze current trends and
strategic goals of Uzbekistan's foreign economic policy, (ii) Formulate criteria for assessing and
ranking export strategies based on state priorities, (iii) Construct a hierarchical model for
making decisions on the choice of export strategies, (iv) Conduct an expert assessment and
aggregate data using the method of hierarchy analysis, (v) Determine priority areas of export
policy for the medium term and formulate practical recommendations.
Literature Review.
The first structured method of making multi-criteria decisions, called the Analytic
Hierarchy Process (AHP), was developed by Thomas Saaty (1980). Since then, AHP has become
widespread and is still actively used in management practice. AHP allows complex decisions to
be broken down into a hierarchy of subtasks, each of which can be analyzed independently. It
is widely used in management, strategic planning, policy analysis, and resource allocation,
especially in situations involving both qualitative and quantitative factors. Forman and Gass
(2001) provided brief descriptions of successful AHP applications. Vaidya and Kumar (2006)
provided a detailed review of the literature on the application of AHP.
Among CIS researchers, Zinenko (2014), Botnaryuk (2018), and some others have studied
the application of AHP in solving national economic management problems.
In Uzbekistan, this area of management science is currently represented only in the form
of educational and methodological support for the training of management personnel of civil
servants.
Methodology.
AHP allows complex decisions to be decomposed into a hierarchy of sub-problems, each
of which can be analyzed independently. It is widely used in strategic planning, policy analysis,
and resource allocation, particularly in situations involving both qualitative and quantitative
factors.
At first stage, a set of alternative decisions is formulated, and a decision maker has to
choose a prioritized decision among alternatives by making use an AHP approach.
At the second stage, a set of criteria is formulated based on brain storming or discussion
or individually by a decision maker. However, these criteria have to be ranked by the experts
who are proficient in the field under consideration. For this purpose, a pairwise comparison
matrix of criteria is compiled by experts. Sometimes, the decision maker can independently
compare the criteria in pairs, thereby determining their priority by assigning a score,
𝑎
𝑖𝑗
. The
aggregated comparison matrices are normalized, and the priority vectors (weights) are derived
by averaging normalized rows.
Then each column is summed and the values are divided by the column sum, i.e., the
pairwise matrix of criterion comparisons is normalized. For each cell:
𝑎
𝑖𝑗
𝑛𝑜𝑟𝑚
= 𝑎
𝑖𝑗
∑
𝑎
𝑖𝑗
𝑛
𝑖=1
⁄
(1)
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where
𝑎
𝑖𝑗
= initial pairwise score,
𝑎
𝑖𝑗
𝑛𝑜𝑟𝑚
= normalized pairwise score.
The normalized pairwise comparison matrix is a key step in the analytic hierarchy process
(AHP) to quantify the relative importance of criteria in decision making.
At this stage, each element of the matrix reflects the share of significance of the
corresponding criterion in the column, i.e., the relative value compared to others. This is
achieved by dividing the value of the element in the original matrix by the sum of the values of
the corresponding column. The rows of the normalized matrix show how important each
criterion is compared to the others for each feature (column), with all values scaled from 0 to
1. The sum for each column in the normalized matrix is 1. This ensures data comparability and
correct calculation of weights. The final weights of the criteria (priority vector) are calculated
as the arithmetic mean of the values in the row, reflecting the average significance of each
criterion relative to others. Thus, the normalized matrix allows systematizing subjective expert
assessments and obtaining objective weighting coefficients suitable for further analysis and
decision-making within the framework of the hierarchical model. After normalization, the
weights of the criteria (priorities) are calculated. This is the average value for the row:
𝑤
𝑗
=
1
𝑛
∑
𝑎
𝑖𝑗
𝑛𝑜𝑟𝑚
𝑛
𝑖=1
(2)
At fourth stage, a consistency check (Consistency Ratio
–
CR) is performed.
Consistency
Ratios (CR) are calculated to ensure logical coherence of expert judgments. First, the
consistency index is calculated:
𝐶𝐼 =
𝜆
𝑚𝑎𝑥
− 𝑛
𝑛 − 1
(3)
where
𝜆
𝑚𝑎𝑥
–
maximum eigenvalue of a matrix. The consistency ratio is then calculated:
𝐶𝑅 =
𝐶𝐼
𝑅𝐶𝐼
(4)
where
RCI
–
random consistency index (for example, for
n=5
:
RCI = 1.12
).
If CR < 0.10, consistency is considered acceptable.
At fifth stage, the strategy priority scores accross criteria are obtained on the basis of
expert evaluations, using the Saaty scale (from 1 to 9), where: 1
–
equal
importance/significance, 3
–
moderate advantage, 5
–
strong advantage, 7
–
very strong, 9
–
absolute advantage, and 2, 4, 6, 8
–
intermediate values.
The procedure for obtaining strategy assessments based on criteria is as follows: (i) a
matrix of pairwise comparisons of strategies is formed for each criterion (separately), for
example, for the criterion S1 "Economic efficiency" compared with S2, S1 with S3, etc. (ii)
experts give judgments on which strategy is more important and by how much for each
criterion, in a paired format (for example, if S2 is 2 times more important than S1 then score is
equal to 2), (iii) A matrix of pairwise comparisons is built, normalized, and average values are
calculated by rows, i.e., local weights of strategies for this criterion, (iv) to simplify
interpretation, these local weights are multiplied by 9 and rounded to an integer: the results
are strategy scores from 1 to 9 for each criterion.
Sometimes the assessments are set directly by the experts, bypassing the comparison
matrix, especially if the number of strategies is small and the criteria are well defined. In this
case: (i) a group of experts individually or collectively assigns each strategy a score from 1 to 9
for each criterion, (ii) these scores are aggregated (averaged or agreed upon), (iii) the values
used in the calculations are obtained.
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Finally, at the last stage, it is necessary to obtain the final scores of the strategies based on
the weighted sum method:
𝑆
𝑗
= ∑
𝑤
𝑖
𝑟
𝑖𝑗
𝑛
𝑖=1
(5)
where:
•
𝑤
𝑖
= weight of the
𝑖
-th criterion (from AHP),
•
𝑟
𝑖𝑗
= rating of the
𝑗
-th strategy under the
𝑖
-th criterion.
To quantify the relative importance of the above criteria and assess the performance of
each export strategy, structured interviews have been conducted with nine experts, including
senior policymakers, academic economists, and trade practitioners. Using Sa
aty’s fundamental
scale (1
–
9), experts provided pairwise comparisons for both criteria and alternatives.
The selection of criteria was informed by a triangulation of sources: (i) presidential policy
directives of the Republic of Uzbekistan, especially the strategic tasks defined in the
"Uzbekistan - 2030" Strategy adopted by Presidential Decree of February 21, (2024), (ii)
national export development programs (for instance, one of them has been approved by
Presidential Decree of the Republic of Uzbekistan of March 14, (2025)), (iii) reports delivered
by international and national organizations (for instance, OECD, 2022; IMF, 2024; NAS, 2024),
(iv) expert consultations with economists, trade specialists, and government officials, who
provided practical insights into feasibility, risks, and implementation timelines. Based on this
foundation, five criteria were identified as most relevant for ev
aluating Uzbekistan’s export
development strategies, and the criteria weights have been assigned based on the expert
evaluations
which show the relative importance of five criteria identified through expert
interviews and analysis of national strategic documents:
С
1
–
“Economic Efficiency” received the highest weight (0.30), indicating that maximizing
economic returns is the foremost consideration in selecting export strategies.
С
2
–
“Feasibility” ranks second (0.25), highlighting the
importance of practical
implementation within existing institutional and financial capacities.
С
3
–
“Sustainable Development Contribution” is given notable weight (0.20), reflecting
Uzbekistan's policy alignment with long-term ecological and inclusive growth goals.
С
4
–
“Time to Effect” (0.15) indicates a moderate preference for strategies that can yield
faster results.
С
5
–
“Political Risk”, although the least weighted (0.10), is still considered relevant,
especially in strategies involving regional integration and foreign policy implications.
Table 1
Pairwise matrix of comparisons of criteria
Criterion
C1
C2
C3
C4
C5
C1
1
1.5
2
3
4
C2
2/3
1
1.5
2
3
C3
1/2
2/3
1
1.5
2
C4
1/3
1/2
2/3
1
1.5
C5
1/4
1/3
1/2
2/3
1
(The numbers are obtained by averaging the ratings of 9 experts on the Saaty scale of 1
–
9)
These weights illustrate that decision-makers prioritize economically impactful and
realistically implementable strategies, while also considering sustainability and time horizons.
Then, in the second stage, a pairwise matrix of comparisons of criteria was built based on
the evaluations made by experts.
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Then each column is summed up, and the values are divided by the column sum, i.e., the
pairwise matrix of criterion comparisons is normalized, and as a result, we obtain a normalized
pairwise matrix of criterion comparisons (Table 1). This matrix shows that economic efficiency
as a criterion received the highest value across all columns, especially in comparison with less
significant criteria.
Table 2
Normalized Pairwise Comparison Matrix
Criterion
C1
C2
C3
C4
C5
C1
0.364
0.375
0.353
0.367
0.348
C2
0.242
0.250
0.265
0.245
0.261
C3
0.182
0.167
0.176
0.184
0.174
C4
0.121
0.125
0.118
0.122
0.130
C5
0.091
0.083
0.088
0.082
0.087
The normalized matrix demonstrates a balanced, but economically oriented approach to
assessing export strategies. The most important criteria are economic efficiency and feasibility,
while political risks and the time factor are of secondary importance. Such a distribution is
logical for a developing country striving for sustainable economic growth in a limited
institutional environment.
The consistency rate was:
𝐶𝐼 =
(𝜆𝑚𝑎𝑥 − 𝑛)/(𝑛 − 1) = (5.825 − 5)/4 = 0.206
. From the
Saaty table we obtain the random consistency index:
𝐶𝐼 = 1.12
для
𝑛 = 5
. Now let's calculate
the consistency ratio:
𝐶𝑅 =
𝐶𝐼/𝑅С𝐼 = 0.206/1.12 ≈ 0.184
.
Since
𝐶𝑅 = 0.184 > 0.10
, the
level of consistency is at the border of the acceptable. It is advisable to conduct clarification
with experts to improve consistency, but in research practice
𝐶𝑅
values up to
0.2
are sometimes
acceptable under complex criteria.
Table 3
Weights, Eigenvalues, and Consistency Calculation
Criterion
𝒘
𝒊
𝝀
𝒊
(𝝀
𝒊
− 𝒏)𝒘
𝒊
C1
0.30
6.33
0.399
C2
0.25
5.80
0.200
C3
0.20
5.38
0.076
C4
0.15
5.50
0.075
C5
0.10
5.75
0.075
Intermediate result
—
—
0.825
Maximum Eigenvalue (
𝜆
𝑚𝑎𝑥
)
5.825
Table 4 presents how each of the four export development strategies scores against the
five criteria:
S2
–
Enhancing Product Competitiveness consistently scores high across most criteria,
especially in
economic efficiency (8)
and
sustainable development (8)
, confirming its broad
strategic appeal,
S1
–
Market Diversification performs well in
economic efficiency (7)
and
political risk (7)
,
indicating its potential to reduce dependence on specific markets,
S3
–
Export Infrastructure Development scores lower in
time to effect (4)
and
feasibility
(5)
, reflecting the high resource demands and long lead times typically associated with
infrastructure projects,
S4
–
Regional Integration achieves a strong score in
time to effect (7)
, as trade bloc
membership can yield relatively fast access benefits, but it is penalized in
political risk (4)
due
to potential sovereignty concerns.
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This table shows that while all strategies offer value, there is clear variation in their
suitability based on policy priorities and contextual constraints. Each export strategy is
evaluated against the five criteria using a 1
–
9 scoring scale. The final composite scores were
computed using the weighted sum model according to formula (5). For example, the final score
for strategy S1 (Market diversification) was calculated as follows:
𝑆1 = (0.30 ⋅ 7) + (0.25 ⋅ 6) + (0.20 ⋅ 5) + (0.15 ⋅ 6) + (0.10 ⋅ 7) = 2.10 + 1.50 + 1.00 +
0.90 + 0.70 = 6.25
.
Table 4
Strategy scores against criteria (scale 1
–
9)
Strategy
C1
C2
C3
C4
C5
S1
7
6
5
6
7
S2
8
7
6
8
6
S3
6
5
4
7
8
S4
7
6
7
5
4
The final aggregate scores for each strategy after applying AHP weighting and score
normalization are as follows: (i) Enhancing Product Competitiveness achieves the highest
integrated score (7.25), affirming it as the top-ranked strategy under current national
conditions, (ii) Market Diversification comes second (6.25), showing that diversification
remains a robust option, albeit slightly less impactful than direct competitiveness measures,
(iii) Regional Integration follows closely (6.05), reflecting mixed potential
—
moderate
feasibility and faster returns but higher political sensitivity, and (iv) Infrastructure
Development scores lowest (5.85), mainly due to concerns over time and feasibility, despite
long-term value. These results quantitatively support the prioritization of competitiveness as a
strategic pillar while recognizing the auxiliary role of other approaches. Figure 1 graphically
illustrates the final integrated scores of the four evaluated export development strategies based
on the Analytic Hierarchy Process (AHP).
Figure 1. Integrated scores of export development strategies
This figure visually emphasizes the strategic preference for policies that deliver relatively
fast, economically efficient, and sustainable results, while also highlighting trade-offs between
political feasibility, investment scale, and timing.
7.25
6.25
6.15
5.7
0
1
2
3
4
5
6
7
8
S2
–
Increasing Competitiveness S1
–
Diversification of Markets
S4
–
Regional Integration
S3
–
Export Infrastructure
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Discussion.
The analysis confirms that the strategy of enhancing export product competitiveness (S2)
is the most favorable under current national priorities. This approach is consistent with the
Presidential goals of increasing added value, improving product standards, and promoting
branding. While diversification and infrastructure development remain important, they require
greater resource allocation and longer timeframes. Integration into trade blocs, though
beneficial, carries political risks that must be balanced with sovereign interests. Moreover,
regarding the strategy “Increasing competitiveness” (S1), the highest scores were obtained for
the criteria “Economic efficiency”, “Feasibility”, “Speed of effect”. This result is consistent with
practice. Thus, the Development Strategy "Uzbekistan - 2030" directly emphasizes the course
on increasing the competitiveness of the national economy, including the development of
exports, innovations and industry. The program for localization, import substitution and
support of non-resource exports is actively financed and administered.
Despite the stated goals, not all initiatives are implemented with equal efficiency due to:
low labor productivity; limited access to modern technologies; shortage of qualified personnel;
limitations in logistics and infrastructure.
Conclusion.
By incorporating national strategies, official priorities, and expert feedback, this study
applies the AHP method to rank export strategies for Uzbekistan. The results advocate
prioritizing competitiveness as a foundation for long-term export growth.
The results of this study are generally consistent with current practice in Uzbekistan:
increasing competitiveness is indeed a key focus of the state strategy. This is reflected both in
strategic planning documents and in ongoing institutional and economic reforms.
The methodology can support evidence-based policymaking in the area of foreign trade.
Further research may involve broader surveys and dynamic adjustments of criteria weights as
economic conditions evolve.
References:
About the State Program on Strategy Implementation "Uzbekistan - 2030" In "Year of
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—
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International Monetary Fund (IMF). (2023). Uzbekistan: Economic Outlook. IMF Country
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https://www.imf.org/en/Countries/UZB
OECD (2022). Boosting the Internationalization of Firms through better Export Promotion
Policies
in
Uzbekistan.
−URL:
https://www.oecd.org/content/dam/oecd/en/publications/reports/2022/02
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47. − URL: www.lex.uz
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–
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М.: Юнайтед Версити Пресс.
