Open Access

SWOT Framework Based on Fuzzy Logic, AHP, and Fuzzy TOPSIS for Sustainable Retail Second-hand Clothing in Liberia

Peter Davis Sumo
Peter Davis Sumo
, 
Xiaofen Ji
Xiaofen Ji
 and 
Liling Cai
Liling Cai
   | Dec 30, 2022
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Article Category: Research Article
Published Online: Dec 30, 2022
Page range: 27 - 44
DOI: https://doi.org/10.2478/ftee-2022-0050
Keywords
© 2022 Peter Davis Sumo et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Fig. 1

SWOT group matrix analysis
SWOT group matrix analysis

Fig. 2

The SWOT AHP hierarchical model
The SWOT AHP hierarchical model

Fig. 3

A Triangular fuzzy number (TFN)
A Triangular fuzzy number (TFN)

Fig. 4

Local Weights of both AHP & FAHP
Local Weights of both AHP & FAHP

Fig. 5

Global weights of both AHP & FAHP
Global weights of both AHP & FAHP

Results of FAHP pairwise comparison of SWOT group and sub-factors

Fuzzy AHP
SWOT Grp S W O T
S (1, 1, 1) (2, 3, 4) (2, 3, 4) (0.25, 0.333, 0.5)
W (0.25, 0.333, 0.5) (1, 1, 1) (4, 5, 6) (0.2, 0.25, 0.333)
O (0.25, 0.333, 0.5) (0.166, 0.2, 0.25) (1, 1, 1) (4, 5, 6)
T (2, 3, 4) (3, 4, 5) (0.166, 0.2, 0.25) (1, 1, 1)
Strengths S1 S2 S3 S4 S5
S1 (1, 1, 1) (0.25, 0.333, 0.5) (0.166, 0.2, 0.25) (0.25, 0.333, 0.5) (0.142, 0.166, 0.2)
S2 (2, 3, 4) (1, 1, 1) (1, 1, 1) (2, 3, 4) (2, 3, 4)
S3 (4, 5, 6) (1, 1, 1) (1, 1, 1) (2, 3, 4) (1, 1, 1)
S4 (2, 3, 4) (0.25, 0.333, 0.5) (0.25, 0.333, 0.5) (1, 1, 1) (0.25, 0.333, 0.5)
S5 (5, 6, 7) (0.25, 0.333, 0.5) (1, 1, 1) (2, 3, 4) (1, 1, 1)
Weaknesses W1 W2 W3 W4 W5 W6
W1 (1, 1, 1) (0.142, 0.166, 0.2) (0.142, 0.166, 0.2) (0.25, 0.333, 0.5) (4, 5, 6) (1, 1, 1)
W2 (5, 6, 7) (1, 1, 1) (1, 1, 1) (5, 6, 7) (5, 6, 7) (5, 6, 7)
W3 (5, 6, 7) (1, 1, 1) (1, 1, 1) (4, 5, 6) (6, 7, 8) (6, 7, 8)
W4 (4, 5, 6) (0.142, 0.166, 0.2) (0.166, 0.2, 0.25) (1, 1, 1) (4, 5, 6) (5, 6, 7)
W5 (0.25, 0.333, 0.5) (0.142, 0.166, 0.2) (0.125, 0.142, 0.166) (0.166, 0.2, 0.25) (1, 1, 1) (1, 1, 1)
W6 (1, 1, 1) (0.142, 0.166, 0.2) (0.125, 0.142, 0.166) (0.142, 0.166, 0.2) (1, 1, 1) (1, 1, 1)
Opportunities O1 O2 O3 O4
O1 (1, 1, 1) (4, 5, 6) (4, 5, 6) (4, 5, 6)
O2 (0.166, 0.2, 0.25) (1, 1, 1) (4, 5, 6) (2, 3, 4)
O3 (0.166, 0.2, 0.25) (0.166, 0.2, 0.25) (1, 1, 1) (0.166, 0.2, 0.25)
O4 (0.166, 0.2, 0.25) (0.25, 0.333, 0.5) (4, 5, 6) (1, 1, 1)
Threats T1 T2 T3 T4 T5 T6
T1 (1, 1, 1) (4, 5, 6) (0.142, 0.166, 0.2) (0.25, 0.333, 0.5) (0.111, 0.111, 0.125) (0.111, 0.125, 0.142)
T2 (0.166, 0.2, 0.25) (1, 1, 1) (0.125, 0.142, 0.166) (1, 1, 1) (0.111, 0.111, 0.125) (0.125, 0.142, 0.166)
T3 (5, 6, 7) (6, 7, 8) (1, 1, 1) (5, 6, 7) (0.25, 0.333, 0.5) (2, 3, 4)
T4 (2, 3, 4) (1, 1, 1) (0.166, 0.2, 0.25) (1, 1, 1) (0.111, 0.111, 0.125) (0.142, 0.166, 0.2)
T5 (8, 9, 9) (8, 9, 9) (2, 3, 4) (8, 9, 9) (1, 1, 1) (5, 6, 7)
T6 (7, 8, 9) (6, 7, 8) (0.25, 0.333, 0.5) (5, 6, 7) (0.142, 0.166, 0.2) (1, 1, 1)

Summarized table of SWOT categorized strategies

SO1 It's easier shopping second-hand clothes because it has a solid country-wide presence with a great variety of products and increased choosability options which creates employment avenues that lead to poverty alleviation and women empowerment in particular
SO2 SHC are quality products, durable and affordable for the local majority. Both retailers and suppliers can independently operate businesses with a much faster realization of improvements. If its serviceability range is more comprehensive for consumers, it will extend the garment's life-cycle and reduce fast fashion demand
SO3 Institutional loan opportunities coupled with quantity discounts from wholesalers to retailers may lead to low capital requirements for beginners as well as promote market expansion
WO1 Obtaining financial assistance to startups will promote new market expansion for young entrepreneurs
WO2 Providing skillsets that will improve those clothes that sometimes require alteration creates additional employment avenues.
WO3 The corporation between members of the supply chain could ease the lack of storage/warehouse facilities as well as regulate the increasing pressure to provide lower prices in the competitive environment
ST1 Fast-changing consumers’ choices, particularly in the clothing segment, has created a strong demand for SHC nation-wide upsetting intense competition from new entrants
ST2 Unstable tax schemes and import duties will significantly affect the importation of quality and affordable SHC products for the local majority
ST3 Regulators improving on unstable prices and exchange rates due to dual currency and frequent demolition of market structures will promote the local textile industry in upcycling. Policies on banning the importation of SHC will derail progress in poverty alleviation and women empowerment.
WT1 Due to a volatile tax system, exchange rates, dual currencies, import duties, and the constant breakdown of market structures, retailers face more uncertainties as prices from wholesalers are high, and consumers are reluctant to buy
WT2 The supply chain lacks a sound delivery system due to poor logistics infrastructure to transport goods around
WT3 Consumers’ choices keep changing at a faster pace due to competition from the Fast Fashion market and the growing number of new entrants

Pairwise comparison matrix

X1 X2 X3 X4 X5
X1 a1⁄a1 a1⁄a2 a1⁄a3 a1⁄aj a1⁄an
X2 a2⁄a1 a2⁄a2 a2⁄a3 a2⁄aj a2⁄an
X3 a3⁄a1 a3⁄a2 a3⁄a3 a3⁄aj a3⁄an
X4 ai ⁄a1 ai ⁄a2 ai ⁄a3 ai ⁄aj ai ⁄an
X5 an ⁄a1 an ⁄a2 an ⁄a3 an ⁄aj an ⁄an

Group and ensemble weights of SWOT group from AHP & FAHP computations

Factors Group Weights Ensemble Weights
AHP FAHP
S 0.255 0.321 0.288
W 0.111 0.197 0.154
O 0.193 0.185 0.189
T 0.442 0.298 0.370

Local, global, and ensemble weights of all sub-factors from AHP & FAHP computations

Factors Local Weights Group Weights Global Weights Ensemble Weights
AHP FAHP AHP FAHP AHP FAHP
S1 0.086 0.056 0.022 0.018 0.020
S2 0.280 0.316 0.071 0.102 0.086
S3 0.255 0.279 0.255 0.321 0.065 0.089 0.077
S4 0.136 0.112 0.035 0.036 0.035
S5 0.243 0.237 0.062 0.076 0.069
W1 0.082 0.065 0.009 0.013 0.011
W2 0.321 0.353 0.036 0.070 0.053
W3 0.324 0.360 0.111 0.197 0.036 0.071 0.053
W4 0.150 0.141 0.017 0.028 0.022
W5 0.059 0.037 0.007 0.007 0.007
W6 0.064 0.043 0.007 0.008 0.008
O1 0.474 0.581 0.091 0.107 0.099
O2 0.247 0.230 0.193 0.185 0.048 0.043 0.045
O3 0.097 0.053 0.019 0.010 0.014
O4 0.182 0.136 0.035 0.025 0.030
T1 0.060 0.040 0.027 0.012 0.019
T2 0.043 0.028 0.019 0.008 0.014
T3 0.230 0.252 0.442 0.298 0.102 0.075 0.088
T4 0.060 0.047 0.027 0.014 0.020
T5 0.420 0.469 0.186 0.140 0.163
T6 0.186 0.164 0.082 0.049 0.065

Respondents

Measure Items Red Light Waterside Duala Omega
Freq % Freq % Freq % Freq %
Gender Male 4 10 9 30 3 15 1 10
Female 36 90 21 70 17 85 11 90
Age 10–19 2 5 3 10 1 5 1 10
20–29 18 45 9 30 5 25 2 20
30–39 5 12.5 9 30 6 30 3 30
40–49 6 15 5 16.7 5 25 2 20
50–59 4 10 2 6.7 2 10 1 10
60 & above 5 12.5 2 6.7 1 5 1 10
Total 40 100 30 100 20 100 10 100

Results of AHP pairwise comparison of SWOT group and sub-factors

AHP
SWOT Grp S W O T
S 1.000 2.000 2.000 0.500
W 0.500 1.000 0.333 0.333
O 0.500 3.000 1.000 0.333
T 2.000 3.000 3.000 1.000
CR=0.07 λmax=4.19 CI=0.06
Strengths S1 S2 S3 S4 S5
S1 1.000 0.500 0.333 0.500 0.250
S2 2.000 1.000 1.000 2.000 2.000
S3 3.000 1.000 1.000 2.000 1.000
S4 2.000 0.500 0.500 1.000 0.500
S5 4.000 0.500 1.000 2.000 1.000
CR=0.03 λmax=5.16 CI=0.04
Weaknesses W1 W2 W3 W4 W5 W6
W1 1.000 0.250 0.250 0.500 2.000 1.000
W2 4.000 1.000 1.000 4.000 4.000 4.000
W3 4.000 1.000 1.000 3.000 5.000 5.000
W4 2.000 0.250 0.333 1.000 3.000 4.000
W5 0.500 0.250 0.200 0.333 1.000 1.000
W6 1.000 0.250 0.200 0.250 1.000 1.000
CR=0.04 λmax=6.27 CI=0.05
Opportunities O1 O2 O3 O4
O1 1.000 3.000 3.000 3.000
O2 0.333 1.000 3.000 2.000
O3 0.333 0.333 1.000 0.333
O4 0.333 0.500 3.000 1.000
CR=0.09 λmax=4.26 CI=0.08
Threats T1 T2 T3 T4 T5 T6
T1 1.000 3.000 0.250 0.500 0.142 0.166
T2 0.333 1.000 0.200 1.000 0.142 0.200
T3 4.000 5.000 1.000 4.000 0.500 2.000
T4 2.000 1.000 0.250 1.000 0.142 0.250
T5 7.000 7.000 2.000 7.000 1.000 4.000
T6 6.000 5.000 0.500 4.000 0.250 1.000
CR=0.08 λmax=6.51 CI=0.10 CR=0.08

Experts involved in the identification, and categorization of SWOT factors

Expert Years of experience Academic Qualification
1 >17 PhD
2 >14 PhD
3 >14 PhD
4 >12 PhD Candidate
5 >10 MBA
6 >8 MSc

SWOT factors for SHC retailing

Strengths Weaknesses
S1 There is a strong presence of SHC country-wide with a great variety of products and increased choosability options W1 Lack of storage/warehouse facilities and pressure to provide lower prices in the competitive environment
S2 SHC are quality products, durable and affordable for the local majority W2 Prices from wholesalers are high because of the high importation and other related costs
S3 Retailers and suppliers can independently operate businesses and grow financially faster W3 Obtaining financial assistance to startups is difficult for young entrepreneurs
S4 The serviceability range is more comprehensive for consumers such that it extends garment's life-cycle and reduces fast fashion demand W4 Poor supply chain delivery systems. There is no good logistics infrastructure to transport goods around
S5 It's easier shopping second-hand; this gives space to boost sales and market growth improvements W5 Clothes are less hygienic and sometimes require alteration for which there are existing skillset-gaps
W6 Low level of corporation between members of the supply chain
Opportunities Treats
O1 Selling SHC creates employment avenues that lead to poverty alleviation T1 Increased competition from new entrants
O2 Favorable conditions for investment that support women empowerment T2 Fast-changing consumers’ choices in the clothing segment
O3 Loan opportunities may lead to growth in demand and promote new market expansion T3 Unstable tax schemes and import duties
O4 Quantity discount from wholesalers to retailers has the potential to allow the low capital requirement for beginners T4 Competition from the Fast Fashion market that changes the taste of consumers
T5 High likelihood of banning SHC to promote the local textile industry
T6 Unstable prices and exchange rates due to dual currency and frequent government demolition of market structures

Saaty's AHP and fuzzy pairwise comparing scale

AHP Rating Inverse Fuzzy Number Linguistic Scale TFN Inverse TFN
1 1 Equally important (EI) (1,1,1) (1,1,1)
2 1/2 Intermediate value (IV) (1,2,3) (1/3, 1/2, 1)
3 1/3 Moderately important (2,3,4) (1/4, 1/3, 1/2)
4 1/4 Intermediate value (IV) (3,4,5) (1/5, 1/4, 1/3)
5 1/5 Strongly more important (SMI) (4,5,6) (1/6,1/5, 1/4)
6 1/6 Intermediate value (IV) (5,6,7) (1/7, 1/6, 1/5)
7 1/7 Very strongly important (VSI) (6,7,8) (1/8, 1/7, 1/6)
8 1/8 Intermediate value (IV) (7,8,9) (1/9, 1/8, 1/7)
9 1/9 Extremely more important (EMI) (8,9,9) (1/9, 1/9, 1/7)

Radom index values

Matrix 1 2 3 4 5 6 7 8 9 10 11 12
Random index (RI) 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.51 1.58

TOPSIS

Strategy d+i d−i CCi Rank
SO1 3.660 3.536 0.491 4
SO2 5.705 1.481 0.206 6
SO3 4.808 2.387 0.332 5
WO1 5.865 1.307 0.182 7
WO2 6.669 0.488 0.068 11
WO3 6.661 0.498 0.070 10
ST1 6.352 0.795 0.111 8
ST2 2.306 4.886 0.679 2
ST3 2.027 5.138 0.717 1
WT1 2.535 4.651 0.647 3
WT2 6.585 0.595 0.083 9
WT3 7.041 0.107 0.015 12
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