AHP method for supplier selection: Case of knitpassion garment company
TẠP CHÍ KHOA HỌC YERSIN – CHUYÊN ĐỀ QUẢN LÝ KINH TẾ
AHP METHOD FOR SUPPLIER SELECTION:
CASE OF KNITPASSION GARMENT COMPANY
Tôn Nguyễn Trọng Hiền1
ABSTRACT
Title: AHP method for supplier selection:
Case of Knitpassion garment company
Decision making is one of the important tasks in
the field of economy, society, etc. of human. Decision
making is the top priority, the process through which
one optimal choice is made from several possible
alternatives of solutions for a given situation. Decision
making is often qualitative and quite cognitive biases,
so this article desires to discover a quantitative
analysis and evaluation technique as a decision-
support model for contractor selection. The author has
proposed a multi-criteria decision-making model,
specifically the Analytic Hierarchy Process (AHP) to
assess and select wool suppliers for Knitpassion Textile
Company.
Keywords: Suppliers, analytic hierarchy
process, multi-standard decisions.
Lịch sử bài báo:
Ngày nhận bài: 14/7/2020;
Ngày nhận kết quả bình duyệt: 12/8/2020;
Ngày chấp nhận đăng bài: 15/8/2020.
Tác giả:
1 Lawsgroup, Vietnam.
Email: tonnguyentronghien@gmail.com
GAP, UNIQLO, ANN, TALBOTS, etc. Over the
past four decades Lawsgroup has pursued a
quality policy, minimum costs, and lead-
time guarantees, however, the COVID-2019
epidemic has affected most textile
businesses.
1. Introduction
Statistics show that export turnover of
textiles and garments always accounts for
the top three of the five key commodity
groups (Figure 1), in the first four months,
the third largest export commodity group in
the whole country was US$8.65 billion,
down by 8.8% (Thai & Kieu, 2020).
Vietnam’s textile and garment industry has
for many years been one of the key export
16.00
15.38
12.14
industries
of
Vietnam,
with
the
9.63
9.48
8.65
development of technical technology, the
skilled labor force has increasingly
accounted for a large proportion and the
incentives from state policies, the textile
and garment industry has obtained
encouraging and newly created results.
6.78
5.32
5.54
5.37
Agricultural Machinery Textile
1st quarterly 2019
Computer Cellphone
1st quarterly 2020
Knitpassion Company is a member of
Lawsgroup (Hongkong), produces apparel
in facilities set up in Vietnam. The company
specialises in sweater processing for
partners in the US and Europe; it is
currently a partner of global brands such as
Figure 1. Export turnover of five key
commodity groups, the unit is “billion USD”
(Thai & Kieu, 2020)
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TẠP CHÍ KHOA HỌC YERSIN – CHUYÊN ĐỀ QUẢN LÝ KINH TẾ
According to Forbes Vietnam, 100%
author observed 213 directors when
making decisions, the results show that
the vast majority are based on personal
experience, which leads to “unreasonable
results”, experiences lead to biases and
wrong decisions (Zeni et al., 2016). It has
been well recognised that supplier
of garment manufacturing enterprises
were affected by the Covid-19 epidemic, of
which about 70% of businesses cut their
staff in March and expected 80% of
businesses to reduce the number labor in
April and May (Chi, 2020). At Knitpassion,
the number of workers was cut by 30%
compared to weekdays. The reason for
this reduction is that the EU and US
partners have cut down the contract
output, both the drop in contracts up to
70%. The contract issue is still maintained
the business is nevertheless still very
instable because the company has to
import mainly textile fibers from China. At
present, because the company has to
comply with the commitment of the sales
contract, the company has to import
threads and wool from China to
transshipment into Bangladesh, then
import to the Vietnam factory, which leads
to almost unprofitable. If the company
hesitates, the order must be shipped by air
to meet the delivery schedule as promised
in the contract, the business may incur a
loss. Currently, company materials such as
buttons are purchased from Vietnamese
partners, so the company is considering
selecting new suppliers for yarns and
wool. There are currently too many
selection
implications
has
important
for organisations
strategic
to
understand their business needs and what
they benefit they want to achieve by
gaining
from
selecting
suppliers
competent in particular areas, rather than
simply paying for what suppliers want to
sell. The nature of supplier selection
processes is generally complex, especially
when the firm has a large variety of
products and vendors (De Felice et al.,
2015). Decision making is complicated
because the diversity of quantitative and
qualitative criteria assigns on evaluation
and decision-making processes (Aouadni
et al., 2019). Decision-maker is faced with
both qualitative and quantitative factors.
The factors suggested in the related
literature can be classified into two
categories: Mathematical programming
models and weighting models (Huang &
Hu, 2013). AHP - Analytic Hierarchy
Process initially was proposed by Thomas
L. Saaty in the 1970s, a technique for
supplier selection from the view of
organisations which calculate priorities
from pairwise comparisons. AHP model is
better than a mathematical programming
model (Huang & Hu, 2013). AHP is a
technique for making decisions (multi-
decision tools) in complex environments
using hierarchical analytical methods to
select the best decisions (Longaray et al.,
partners
offering
the
company
consequently requires the most suitable
supplier.
In fact, in the business, when faced
with the decision-making problem,
decision-makers are mainly based on
personal experience without grasping, or
“leaving out” decision-making tools. Tarka
(2018) conducted empirical research, the
Tập 7 (8/2020)
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TẠP CHÍ KHOA HỌC YERSIN – CHUYÊN ĐỀ QUẢN LÝ KINH TẾ
2015). This method helps decision-
we conducted a reference to secondary
sources. Compared to secondary research,
collecting and analysing primary data is
not always feasible due to errors in data
collection, subjective personal biases, and
makers organise important aspects of the
problem into a hierarchical structure
similar to a family tree, determine the
weights of hierarchically non-structured
or particular hierarchical level criteria in
respect of those belonging to a higher
level. Many companies still do not use
Multi-Criteria Decision Making methods
such as AHP when making multi-criteria
decisions and prefer to decide intuitively
(Ishizaka & Siraj, 2018; Asadabadi et al.,
2019). However, the AHP method
provides for this need of organisations
because the determination of an
misinformation.
The
strength
of
secondary data analysis is the approach
that we can utilise good collection of data
already exists. In this spirit, the research
methodology of this article was based on
analysis of secondary data sources, using
this reliable data source, experts had a
visual reference of which criteria should
be available. A lot of material needed to be
gathered, however, a huge amount of data
is flooded with exact information and fake
information, trusted and unreliable
statistics, useful and unusable instruction.
Therefore, in this stage, we set out the
following searching standards:
appropriate supplier selection is
a
multicriteria decision-making problem
essentially (Akcan et al., 2019).
2. Research Methodology
Interviews are one of the main
instruments in this research. In order to
determine the weights of the main
criteria, the committee consisted of three
experts from Lawsgroup with minimum of
10 years working experience; one is an
operations manager, one is an industrial
system engineering engineer (ISE), and
another is purchasing manager. Experts
were interviewed and the paired
comparative evaluation applied to pairs of
homogeneous criteria, eventually creating
overall priorities for ranking options.
- Database: Web of Science (WoS-
SSCI). Multi-disciplinary journal database
produces high-quality research; all
articles and reviews in such journals are
subject to peer review.
- Key term: TITLE = “supplier
selection”
- Languages: English.
- Specific period: 01/01/2016-
20/7/2020
- Excluded criteria: Solely accept peer
review article, excluding book chapter and
proceeding.
Research steps:
Step 1: Set up criteria
The result was 213 articles with a
relatively good citation index (Average
citations per item is 14.44).
Research does not always involve
collection of data from the participants, in
order to select the appropriate criteria,
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TẠP CHÍ KHOA HỌC YERSIN – CHUYÊN ĐỀ QUẢN LÝ KINH TẾ
6. Reputation (F6): Trademark of
supplier.
Step 2: Determine evaluation criteria &
priority level
We build a priority rating scale in pairs
of criteria. The scale used for comparison
in AHP allows the decision-maker to
combine experience and knowledge
Figure 2. Web of Science analysis
documents (Source: WoS)
intuitively and show how many times one
factor dominates another.
The decision-maker can express the
priority between each pair of elements
verbally as equally important, nearly
equally important, more important, much
more important, extremely more important.
The description will then be translated into
numerical values of 1, 3, 5, 7, 9, which are
intermediate values to compare pairs
according to the qualitative judgment on the
Satty scale (Table 1).
Based on the average citations per year
(ACY), from the results, we decided to
choose the research results of the authors
with the highest ACY index that is 30.6.
Rezaei et al. (2016) point out supplier
selection criteria are as follows: Cost of
delivery, Lead time, Non-competitor on
specialties, Production facilities and
capacity,
Quality,
Compliance
on
certification, Sustainable performance.
Table 1. Priority rating scale
The company currently has
a
supplier list set. The purpose is to
eliminate suppliers who do not meet the
criteria set out and select the most
suitable supplier, using the Delphi
method, the company conducts meetings
and sets criteria. The experts will be
independently surveyed, and then they
will gather to agree on the criteria. The
textile company proposes six items:
Important
level
Saaty
value
Explanation
The two factors
are equally
important
Support one
Equally
important
1
3
5
7
Nearly
equally
important
element over
another
Strongly support
one element over
another
This factor is a
trend, prevailing
over another
More
important
1. Quality (F1): Quality fabric (color,
size, composition, etc.)
Much
more
important
2. Cost (F2): Selling price
This factor is
3. Distance (F3): The distance from the
extremely important
to overwhelm the
other factor, being
the trend, is
partner’s warehouse to the delivery location
Extremely
more
important
9
4. Technology (F4): The ability to
modernise,
dyeing,
and
weaving
extremely dominant.
technologies.
5. Responsibility (F5): The ability to
quickly respond to customer’s orders.
Step 3: Calculate weight for criteria
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TẠP CHÍ KHOA HỌC YERSIN – CHUYÊN ĐỀ QUẢN LÝ KINH TẾ
There are six factors that we set up
Table 2. Pair-wise comparison matrix [F]
the square matrix as in Table 2, in which
the types of factors are designated as F
= {F1, F2, F3, F4, F5, F6}. In this F
matrix, each element represents pairs
that compare with each other, the
elements above and below the diagonal
have reciprocal values, telling how
many times this criterion is equal to the
other criterion. Experts are asked to
give their answers. For example:
“Criteria F1 is nearly as important as F2
with a score of 3”. When there is
disagreement, the group will discuss
and agree on the final decision. The
results are shown in Table 2.
F
F1
1
1/3
1/5 1/3
1/7 1/5
1/5 1/3
F2
3
1
F3
5
3
1
1
F4
7
5
1
1
F5
5
3
1
1
F6
1
F1
F2
F3
F4
F5
F6
1/3
1/5
1/7
1/3
1
1
5
1
7
1
3
1
3
TOTAL 2.88 7.87 16.0 22.0 14.0 3.01
Table 3- we have a 6 x 6 square matrix,
weighting the criteria by taking the value of
each cell divided by the total value. The
calculation formula is described as follows:
The weight (Wij), presented in the cells
of the tables (Table 3), is based on the
importance of the i element to the j element,
on the Saaty scale.
Table 3. Paired comparison matrix in % [X]
F
F1
F1
F2
F3
F4
F5
F6
MEAN
0.3477
0.1159
0.0695
0.0497
0.0695
0.3477
1
0.3814 0.3125 0.3182
0.1271 0.1875 0.2273
0.0424 0.0625 0.0455
0.0254 0.0625 0.0455
0.0424 0.0625 0.0455
0.3814 0.3125 0.3182
0.3571 0.3323 0.3415
0.2143 0.1108 0.1638
0.0714 0.0665 0.0596
0.0714 0.0475 0.0503
0.0714 0.1108 0.0670
0.2143 0.3323 0.3177
F2
F3
F4
F5
F6
TOTAL
1
1
1
1
1
1
Step 4: Consistency test
*The
maximum
eigenvector
is
calculated according to the equation:
An analysis of the consistency of the
translated pinions was performed, as the
decision-makers may be uncertain or make
negative judgments when comparing some
of the elements.
λmax =
= 6.0569
The advantage of the AHP method is
the use of a consistent index to assess the
consistency of the answers of experts. In
practical problems, it is not always possible
to establish a bridging relation while
comparing pairs. For example, F1 may be
better than F2, F2 may be better than F3, but
not necessarily F1 better than F3, which
*Priority vector [W] = [F] x [X]
We have: W(F1) = 2.1042; W(F2)=
0.9959; W(F3)= 0.3570; W(F4)= 0.2975;
W(F5)= 0.3994; W(F6)= 1.9828
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TẠP CHÍ KHOA HỌC YERSIN – CHUYÊN ĐỀ QUẢN LÝ KINH TẾ
demonstrates several methods such as ISM
3. Conclusion
that are flawed when calculating based on
bridging rules. Therefore we have to accept
the practice of the problem, we call it
inconsistency. Inconsistency is a fact that
must be accepted but if the inconsistency is
too much then we say the problem we are
solving is the unreasonable problem. To
check for inconsistencies in the evaluation,
we use the CR-Consistency rate.
In traditional applications, the company
has to identifyits customer’s expectations and
their relative importance (external variables)
to identify which design characteristics
(internal variables) should be allocated the
most resources. The quality and reputation of
the supplier is the concern of Knitpassion
Company, followed by the price is also a
concern when selecting suppliers. We also
realise that the company doesn’t pay much
attention to the technology that its partners
use. Finally, the research shows that in
general S3 is the most optimal choice with
total scores is approximate 18.
The consistency index is determined as
follows: CR = CI / RI.
Therefore, CI=6. 0569- 6/(6-1)= 0, 0114
Table 4. Random index table
n 1 2
3
4
5
6
…
The process of selecting logistics
providers is becoming increasingly important
in today's complex environment. The
selection process involves identifying
quantitative and qualitative factors to choose
the best supplier. The application of AHP
established removing bias, unscientific, or
possibly prejudiced in the judgment of an
expert since the steps leading to the judgment
are made explicit via relational assessment.
AHP has attracted the attention of scholars in
various fields because of its ability to provide
support to different decision-makers, in areas
ranging from business management to
environmental studies and so on. Managers
however rely on intuition to help them
make decisions, thus, this study provides
significant support to the management
board when decision marker faces a
situation with at least two alternatives of
action with conflicting objectives.
RI 0 0 0.52 0.89 1.11 1.25 …
The result is CR = CI / RI = 0. 00114 / 1. 25
= 0. 0252 = 0. 9 % < 10 % (acceptable). In case
of CR > 10% we must meet to revise the
consistencyofthefactorswasreasonableornot.
Step 5: Computation of individual scores
for each supplier
For every single criterion, the six
suppliers are compared using AHP, scores
of each supplier for the criteria are
computed individually.
There are 3 suppliers in all, we conduct
the selection of suppliers based on the rule: If
supplier S achieves the best condition i then S
will get 3 points, points 2 and point 1 will be
distributed to the remaining suppliers in
descending levels respectively. Table 5
reveals individual scores of each supplier.
Table 5. Individual scores of each
supplier.
Score
Suppliers
F1
F2
F3
F4
F5
F6
Σ (W x
Score)
S1
S2
S3
The drawback of AHP is that it is
difficult to compare criteria perfectly
without consistency. The purpose of AHP is
to make very relevant comparisons so that
a perfect result of the AHP method is
expected when there is no contradiction,
without contradiction, AHP becomes
simple. Therefore, AHP for more difficult
problems with more criteria, this method is
not optimal but needs to apply many
methods together such as ISM, or TOPSIS.
1
2
3
1
2
2
2
1
1
2
1
1
3
3
2
3
3
3
10.2289 8.5385 18.0534
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TẠP CHÍ KHOA HỌC YERSIN – CHUYÊN ĐỀ QUẢN LÝ KINH TẾ
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