J. Nig. Soc. Phys. Sci. 4 (2022) 165–173

Journal of the
Nigerian Society

of Physical
Sciences

Green Information and Communication Technologies
Implementation in Textile Industry Using Multicriteria Method

J. A. Adebisia,∗, O. M. Babatundeb

a University of Namibia, Namibia
b Tshwane University of Technology, Pretoria, South Africa

Abstract

It has been recognized that green Information Communication Technology (ICT) is fast becoming popular in every sector. It’s fundamental
relevance to textile industry requires urgent attention than ever. Over the years selections of technologies to drive the textile industry has been
a debate. There is a need for an efficient technology selection method to realize this goal. Selection of green ICT alternatives is a multicriteria
decision making problem which has been sparsely explored in open literature. This study presents green ICT adoption in the textile industry
using a fuzzy-TOPSIS multi-criteria approach for the most preferred ICT alternative in a textile industry. Criteria for Green ICT selection were
identified by administering interview with selected textile and ICT industry experts at the managerial cadre of organizations and academics.
Criteria considered were Implementation Cost (IC), Operating and Maintenance Cost (OMC), Environmental Impact (EI), Improved System
Performance and Use (ISPU), Supply Chain Management (SCM) and Employment Opportunities (EO). Results shows that the most preferred
ICT alternative is power management with overall coefficient of 0.60 while the least preferred is software optimization with coefficient of 0.23.
This work will allow clean industrial process in the textile industry and also promote sustainable cities and communities through responsible
consumption and production as highlighted by sustainable development goals (SDG) 11 and 12.

DOI:10.46481/jnsps.2022.518

Keywords: Green ICT, Textile, TOPSIS, Multicriteria, Technology.

Article History :
Received: 16 December 2021
Received in revised form: 26 March 2022
Accepted for publication: 30 March 2022
Published: 29 May 2022

c©2022 Journal of the Nigerian Society of Physical Sciences. All rights reserved.
Communicated by: W. A. Yahya

1. Introduction

Now commercialized and computerized, the textile industry
dates back to the early civilization of men when conventional
techniques were adopted to establish the industry. The textile
industry is one of the most important sectors of the economy.
Although the various technological breakthroughs around
the world has led to the globalization of the textile industry,
the requirements for sustainability in the industry involves

∗Corresponding author tel. no: +234-8034496354
Email address: adebisi_tunji@yahoo.com (J. A. Adebisi )

constant monitoring of the emerging trends in the market with
respect to standards and regulations, raw materials, customer
tastes and technical aspects of production [1]. In order to
accomplish some of the targets under the 12th sustainable
development goal, the textile industry is now more conscious
of the issues of sustainability. As a result, the subject of
sustainability in the textile and clothing industry is receiving
special attention especially among the producers. Some of the
strategies adopted are directed at securing the environment,
protecting the people, adoption of renewable energy, energy
efficiency and conservation, and environmentally friendly

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communication. As such, for sustainability purpose, the textile
industry requires extensive and intensive application of various
types of state-of-the- art enabling technologies. The adoption
of information and communication technologies in the textile
industry is one of the main technologies that can drive the
required growth, development and expansion in the textile in-
dustry. The adoption of ICT in the textile industry would drive
the changes required to enhance the sustainability of textile
and clothing manufacturing and trade. Apart from making
transactions and the production processes easier, the adoption
of ICT in the textile industry would make response to emerging
fashion trends prompt; ensure effectiveness and efficiency
during design, processing and mass production; and expansion
of market through the adoption of e-commerce that ensures
ease of transactions and prompt feedback from customers [2].
To stay relevant and sustain growth in the competitive market,
business organizations increasingly invest in way to improve
services delivery. In this quest, the adoption of information and
communication technologies is currently driving the dynamic
of many markets to satisfy the increased thirsts of the con-
sumers. Based on this, many business processes across almost
all sectors depend on ICT for sustainability. Furthermore, with
the mode by which data and information is being managed in
the emerging markets and business, ICT has a great impact on
sustenance of modern [3, 4, 5].

Green ICT/green computing deals with the aspect of
computer resource relation process towards reducing power
consumption. It concentrates on Central Processing Unit
(CPU) efficiency, recycling and proper disposal of e-waste.
The term “Green ICT” has been associated with manufacturing,
usage, design and disposal of computer subsystems (Printers,
Servers, hard disks, memory, monitors, network cards and so
on) in a more efficient and effective manner with little or no
negative impact on the environment [6].

To attain sustainability in the textile industry, the production
and supply chain must be green as much as possible. These
include the production, transportation, energy and most espe-
cially the communication departments of the industry. How-
ever, the adoption of green ICT technologies comes with var-
ious technical, costs and environmental implications that must
be considered before they are implemented; hence, making the
selection of the most appropriate green ICT in a textile indus-
try is a multi-criteria problem. Based on aforementioned, this
study presents a framework for the selection of the most appro-
priate green ICT adoption in the textile industry using a fuzzy-
TOPSIS multi-criteria approach.

2. Literature

Karabasevic et al., discussed the influence of ICT in mod-
ern society due to increase societal demands [7]. The authors
emphasized on the fact that; there is an aggressive search of
new ideas and approaches to production especially in the textile
industry. The business climate is more competitive, the market
is dynamic, data exchange rate is high, systems integration is

enormous and business support can barely survive without the
technology support. They further emphasized on the need for
green technology and its establishment in the textile industry.
However, the work proposed bipolar fuzzy MILTIMOORA
method. Today, professionals are fast considering Green IT
both in academics and industry. Istrat and Lalić conducted a
research with the objective to analyze various transactions in
the textile industry [8]. Most of the transactions used were ex-
tracted using various database techniques to find the patterns of
buyer’s attitude towards improving decision-making. With this
work, data mining techniques enhanced the decision-making
process. Close to 2000 transactions records were used from
the cloth making industry as a knowledge base. Interesting
rules and various measures including customized offers were
proposed in this work.

In [9] the possible use of automation tools in the manufac-
ture of garment has been proposed. According to [10], supply
selection is simply the process of identifying, contracting and
evaluating suppliers through the purchaser. In another study
[11]; various criteria for supplier evaluation and their impor-
tance were checked towards selecting and retaining competent
suppliers. Some of the criteria identified in this are not based
on specific organisation type or industry rather generalized. A
separate research proposed multiple criteria decision analysis
for supplier selection with focus on factors that can affect
selection decision among others. [12]. To the best of our
knowledge, the application of diverse green ICT alternatives
in the textile industry is rare and emerging. In [13] various
applications of decision-making methods in the textile industry
were described. This paper presents a fantastic approach
to select suitable Information Communication Technology
approach (Green ICT) to enhance the supply chain activities
in the textile industry. The advantages of green ICT such
as Power management, Energy efficiency and conservation,
Virtualization and Cloud computing, Materials recycling,
Software Optimization, User Friendliness to mention few. This
approach will provide more interesting result in the textile
industry.

A subdivision of possible selection criteria in the textile
industry under service, product, cost and supplier performances
as been presented [14]. In [15], researchers gave a proposal
on voting process as a method for making selection on textile
related activities through one of the stages in the supply chain;
the approach encouraged ranking as preferred over comparison
for determining a potential supplier. Fuzzy AHP method
was utilized by [16] for textile supplier’s evaluation in India.
From the same researcher, another review was carried out
on various issues related to suitable supplier selections and
their relationships with buyer. No doubt issues relating to
supplier are dynamic. Organizations tend to invest in Green
ICT to support decision making process for the best result in
the business especially; to survive competition. An interesting
study on general multicriteria decision making system and
its implementation has been described in [13]. In addition, is
an original approach that represents customers aspect in the

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fashion business, so this work addresses research in Green ICT
specifically for Textile industry.

In [17] a theoretical model with dynamic application of
technology related to skills and the impact of technology in
textile industry was considered. This work is only from the
skills perspective rather than holistic and no alternatives were
proposed. However, the paper used common hypothesis in
economics and embedded information systems to complement
new skills required in the textile industry. It further reveals
the room for continuous on-the-job training and higher level
of education. In another research by [18, 19], various surveys
on skilled and unskilled workers in textile industry was carried
out to complement the work of [17]. The work demonstrates
how new technologies can drive workers in the textile industry
for better performances rather than sending deskilled workers
out of job due to required technology skills.

The authors of [20] studied strategies related to textile
industry from smart perspective through nanotechnology and
electronic telecommunication. The study explored the high po-
tential of smart materials in the field of textile. They used inno-
vative technology applications different from the conventional
textile approach to cover various market segments. Micro sys-
tems, material engineering and production technology were the
focus of the work. This led to flexible economical fabrication,
production compliance textile-based information system with
more user applications. This work is relevant to next generation
of fabrics and fibre coupled with items they produce. Albeit this
work serves as a leverage for the work under study however, the
current research work considers various experts in the field of
technology especially the Green ICT which brings out more po-
tential of unpopular application of technology to textile, there-
fore presents further implementation of scientific significance.
From the literature review, it is important to note that enhancing
the supply chain process in the textile industry is tightly coupled
with criteria decision challenges, which green ICT can handle
through various alternatives. [21, 22, 23, 24] carried out vari-
ous analysis and algorithm on energy systems, distribution, per-
formance analysis among other alternative power sources that
could enhance going green and eventually saving costs of ser-
vice production in textile industry. Hence this study presents
a multi-criteria framework for the ranking of green ICT alter-
natives based on techno-economic and environmental criteria.
Albeit the framework is developed for the Textile production in-
dustry; other industrial and production related sector can adopt
and modify the framework proposed in this study for energy
consumption reduction and going green.

3. Green Ict Alternatives in Textile Industy

This section discusses the various green ICT alternatives
that could be considered for production, services and process
enhancement in the textile industry. These include Power
management, Virtualization, Cloud computing, Telecommut-
ing, Software Optimization and User Friendliness. The con-
sidered alternatives are:

• Power Management (R1)

• Virtualization (R2)

• Cloud computing (R2)

• Telecommuting (R4)

• Software optimization (R5)

• User Friendliness (R6)

3.1. Power Management
One of the drivers of green computing is the reduction of

power consumption while using latest technology as tools in
business enhancement. This no doubt can help various auto-
mated systems deployed across high end computers, servers,
workstations to mention are few in within textile industry oper-
ation [25]. The efficient handling of various power related sys-
tems and aspects of computer hardware through the use of Ad-
vanced Configuration and Power Interface (ACPI) to temporar-
ily preserve power on terminals that are idle for long period is
fast becoming important. ACPI is an advanced power manage-
ment tool developed by Intel-Microsoft, it is useful for power
consumption control facilitated by various technologies such as
“SpeedStep” and “PowerNow” for under-volting depending on
the workload adjustments [6]. Workers in the textile industry
making use of computers need to be aware of power manage-
ment tools available to minimize cost along economic factors
in achieving sustainable development.

3.2. Virtualization
Virtualization as part of sustainability goals in green ICT re-

duces hardware requirements by ratio of 10:1 or even better [4].
Operational expenses are cut by 50% with resource virtualiza-
tion on each server. Most textile industry can take advantage of
this technology to cut cost of computing resources as part of the
alternatives explored in this work. It is affordable, robust with
high uptime. Virtualization results in far more efficient use of
resources, including energy. One of the main purposes of virtu-
alization is to make a single computer hardware function as if
it is multiple places. Most of the computing resources that can
be virtualized include but not limited to the hard disk, memory,
network accessories among others. These components can be
isolated into different parts and making them accessible by in-
dividual as a virtual infrastructure without necessarily making
a new purchase for different purpose. Application of virtual-
ization in textile can be replicated in the various supply chain
activities in among sole distributors in the use of various En-
terprise resource Planning solutions with heavy traffic and user
requirements. This whole idea also helps in energy consump-
tion reduction in data centers.

3.3. User friendliness
This is also another alternative; most ICT solution users

look out for this a lot. While making choice of Software so-
lutions, user instructiveness and friendliness is one of the vi-
tal factors that drives software acceptability even before testing

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by clients. This proposal as part of the green ICT alternatives
in textile is very important. Textile industry is fashion driven
with various styles colour combinations and attractiveness. So
also, the solutions users expect a colour interface solution, easy
to use, straight and direct while satisfying the business need.
Graphical user interface and interoperability is also very impor-
tant with this alternative. Various graphical packages involved
in aforementioned, consume heavy resources including power
hence need for green ICT consideration in fulfilling this aspect
of textile industrial production processes.

3.4. Cloud computing

This is a scalable style of computing with multiple access
information technology. It does not depend on immediate phys-
ical resource to function. With the idea of sustainable develop-
ment (environment, economic and social). Cloud computing
offers greater flexibility to various business model. Textile in-
dustry being a dynamic one; no doubt needs to update software
solutions used in various stages of production. Most machines
can now record production activities electronically, inventory
is being managed using computer systems. With the proposal
of cloud computing as an alternative; energy cost will be re-
duced and data in cloud are more secured with less worry about
updates. Most of the maintenance activities are shifted to the
cloud services providers. The solutions offered through cloud
computing are pay as you use thereby eliminating unnecessary
overhead associated with incorrect resource demand in organi-
sation’s planning [26].

3.5. Telecommuting

The importance of telecommunication-related technology
in textile industry cannot be overemphasized. It ranges from
phone calls, fleet management, email services, online meetings
among others. Most devices used in the aforementioned are re-
lated to green ICT, with lesser power consumption and large
memory support. Working from anywhere, rendering remote
services especially with the advent of the pandemic is becoming
more popular in every sector including textile. Customers and
wholesalers can nowbook textile products remotely, organiza-
tions can have internal and external meetings through telecom-
muting resources hence a green ICT alternative that cannot be
avoided. This technology has taken green ICT even to doc-
ument management, e-auditing, electronic signatories and ap-
provals. Thus, more space for teleworking with aggressive re-
duction of negative environmental impact. It enables video so-
lutions and online collaborations in business environment like
textile. [27].

3.6. Software optimization

Textile industry is associated with various software solution
ranging from ERP, Customer Relationship Management (CRM)
among other supply chain solutions. Optimizing these solutions
for optimum performance to drive positive services delivery is
very important. With this green ICT factor, no doubt; seri-
ous of unique and efficient initiatives will play a vital role in
the textile industry. Software architectures are becoming smart

through green ICT and this alternative will address series of
conventional software architectural challenges in design, anal-
ysis, synthesis and evaluation.

4. Methods

To rank various alternatives based on conflicting criteria
and metrics, decision makers have developed many robust
multi-criteria-decision-making (MCDM) techniques [28].
Although these techniques typically most times produce
same results, there are times when the techniques produces
conflicting results [14, 29, 30]. MCDM methods allow experts
to select the most preferred alternative from finite number of
feasible alternatives. One of the most robust MCDM methods
that has been extensively used by expert is the TOPSIS method;
this is because of its rationality, simplicity, and comprehensi-
bility. Also attributed to TOPSIS is its ability to quantify and
estimate the relative performance of the alternatives in an easy
mathematical expression and robust computational efficacy
[13]. While it is acknowledged that TOPSIS generates quality
output, professionals usually have preference for giving their
opinions using linguistics terms; this usually makes evaluating
uncertainties easier as compared to crisp value. Because of its
robust nature, Fuzzy TOPSIS method was extended by Chen
to capture uncertainty and the fuzzy nature of some multi-
criteria decision problems [31]; and this has been deployed by
researchers in various fields [11, 32, 33, 34, 35]. For this study,
the efficacy of fuzzy-TOPSIS is deployed to evaluate and rank
the most relevant green ICT strategy applicable to a textile
factory. The ranks of the alternatives are based on the relative
closeness index from the fuzzy negative ideal solution (FNIS)
and fuzzy positive ideal solution (FPIS). The steps followed in
the implementation of the Fuzzy-TOPSIS include:

Step 1: Develop a decision matrix
In this step, the literature is explored to identify relevant green
ICT alternatives and the relevant criteria. These alternatives
were rated by 5 experts using a ten-point fuzzy scale. The data
was collected with the aid of a well-designed questionnaire.

Step 2: Develop the normalized decision matrix using the
following expression which is based on negative and positive
ideal solutions:

r̃i j =

 ai jc∗j ,
bi j
c∗j
,

ci j
c∗j

 and c∗j = maxi {ci j} (beneficial) (1)
or

r̃i j =
 a−j

ci j
,

a−j
bi j
,

a−j
ai j

 and a−j = mini {ai j} (non − beneficial)(2)
Step 3: Develop the weighted normalized decision matrix

using the following expression:

Ṽ =
(
ṽi j

)
; ṽi j = r̃i j × w j (3)

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Adebisi & Babatunde / J. Nig. Soc. Phys. Sci. 4 (2022) 165–173 169

Step 4: Calculate the fuzzy positive-ideal solution (FPIS)
and fuzzy negative-ideal solution (FNIS) using the mathemati-
cal expression:

FPIS(A∗) =
(
ṽ∗1, ṽ

∗
2, . . . ṽ

∗
n
)
, where ṽ∗j = maxi

{
vi j3

}
; (4)

FNIS(A−) =
(
ṽ−1 , ṽ

−
2 , . . . ṽ

−
n
)
, where ṽ−j = maxi

{
vi j1

}
; (5)

Step 5: Compute the distance between each alternative and
FPIS and FNIS using the expression:

d∗i =
n∑

j=1

d
(
ṽi j, ṽ

∗
j

)
, (6a)

d−i =
n∑

j=1

d
(
ṽi j, ṽ

−
j

)
. (6b)

But

d(x̃, ỹ) :=

√
1
3

[
(a1 − a2)

2
+ (b1 − b2)

2
+ (c1 − c2)

2
]
. (7)

Step 6: Evaluate the closeness coefficient and rank the al-
ternatives

CCi =
d−i

d−i + d
∗
i

(8)

4.1. Illustrative example

Green computing and technology have gained popularity
in recent times however, in future services arms of Original
Equipment Manufacturers (OEMs) will consider incorporating
green ICT into their service offerings with good focus on
optimization, integration and customer centric offers. Telecom-
munication service providers will also play more role in the
future of green ICT through recycling programs and sustainable
innovations [28, 36, 37]. Recently, some government agencies
took radical actions resurrect textile industry so as to regulate
their importation especially in western Africa. One of the
major issues that lead to importation is the economic recession
that affected many nations in past few years. Considering
all forms of textile materials being blessed by some African
countries as a case study, the adoption of green ICT in the
journey will provide better results considering the various
criteria identified in this work [38]. The textile industry in
Taiwan also faced with some challenges such as low labour and
manufacturing cost. This work will create increased awareness
on how green ICT alternative/multicriteria framework will
encourage competition, reduce environmental hazards in the
midst of harsh economy and global recession.

In [38] an illustrative overview of a typical Textile industry
was provided. The challenges and possible solution reveal from
this work is leveraged upon to support the green ICT perspec-
tives and impact in the textile industry. The authors mentioned
a textile industry in western Africa as the largest employer of
labour, and a major player in the manufacturing sector of the
economy in the past. Unfortunately, it has seized to be a major

contributor to the foreign exchange due to inadequate power
supply, inconsistent government policies smuggling of foreign
materials among others. A critical assessment of this cases
study and its challenges proposed solutions along political
will for sustainable development. The solution can be best
implemented using the green ICT, green ICT drives policy, the
use of modern software solutions for tracking of importation,
automation of supply chain activities with technology that
consume less power will elevate and resuscitate the sector.

Most western African countries used to be the most thriv-
ing textiles industry in Africa. The discovering of other eco-
nomic resources such as oil no doubt impacted its sustainabil-
ity among other challenges [39]. With the advent of green ICT,
most of these challenges can be solved and application of tech-
nology to this industry can possibly make it another oil for most
nations whom have suffered similar setback in the textile indus-
try. The future is green, and green ICT is here to stay. The
rapid increase of technology development also reveals huge op-
portunities power management, decreasing pollution effects in
the environment as identified in Table 1.

5. Results

To establish the viability of the proposed framework,
the proposed model is adapted to a textile industry. Six
green ICT alternatives that will enhance the textile industry
operations were evaluated based on six criteria. The green
ICT alternatives considered in this regard include Power
Management (R1), Virtualization (R2), Cloud computing
(R3), Telecommuting (R4), Software optimization (R5), User
Friendliness (R6). For ease, the alternatives are denoted by
the set Q = R1,R2,R3,R4,R5,R6, respectively. Using the six
criteria C = W1,W2,W3,W4,W5,W6 described in Table 1, the
alternatives were ranked in order of preference.

In this illustrative example, a total of five experts (g ∈ G)
from the industry and the academics with a sound knowledge
on the issue of various textile production and value chain re-
lated to computing and ICT were contacted for their knowledge
and expertise on the subject. Some of the experts have a Doctor-
ate degree while the minimum educational qualification of the
experts is Masters in the field of textile, processing, production,
supply changing management and ICT with not less than 10 to
20 years of experience respectively. They all acknowledged that
they are aware of the numerous impact green ICT could make
in the textile industry. They also agreed that various criteria
should be considered in selecting green ICT technologies with
respect to textile industry. Table 2 presents the details of some
of the questions and their responses.

The opinions of the experts were collected with the aid of a
well-structured questionnaire that points toward the importance
of the criteria and the relationship between the alternatives and
the criteria that was selected. The experts were assigned equal
weights during the analysis of their responses. The linguistic
responses obtained from the experts are presented in Table 3
based on the triangular fuzzy number [1, 2, 26, 40]. The fuzzy

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Table 1: Criteria considered in the study

Factor Criteria Description Remark

Environmental
Environmental Impact
(W1)

Use of ICT to drive policies that reduces negative im-
pact on environment and general human living condi-
tions.

Beneficial

Operating and Mainte-
nance (W2)

Smooth and continuous operation, services and textile
equipment.

Non-beneficial

Economic
Implementation Cost (W3) Cost of deployment and implementation of Green ICT

tools in line with global practices and standards.
Non-beneficial

Improved System Perfor-
mance and Use (W4)

Improvement of services and general performance
ranging from training of staff, acquisition of additional
knowledge and skills in the area of Green ICT

Beneficial

Technical
Supply Chain Management
(W5)

Simple, friendly, and interactive ICT Solutions that are
usable by citizen of different categories and specializa-
tions towards climate change adaptation.

Beneficial

Employment(W6) Oppor-
tunities

ICT Solutions that are flexible with easy upgrade fea-
tures in case of change. Modifiable technical compo-
nents as climate change evolves

Beneficial

Table 2: Excerpt of Expert Response

Questions g1 g2 g3 g4 g5

Have you heard of “green ICT”? Yes Yes Yes Yes Yes

Do you feel the green ICT can impact textile
industry positively?

Yes Yes Yes Yes Yes

If yes, do you agree that different criteria
should be considered in selecting green ICT
technologies with respect to Textile industry
processes?

Yes Yes Yes Yes Yes

Highest Qualification Ph.D. M.Sc. M.Sc. Ph.D. Ph.D.

Years of Experience 16-20 16-20 16-20 11-15 16-20

Organisation Academics Industry Industry Academics Industry

decision matrix of each expert’s opinions are combined using
the elementary operators of the fuzzy triangular numbers such
that the overall judgments and preference rating are extracted
for the various green ICT alternatives (Table 4). The same pro-
cedure is followed to obtain the weights of the criteria from the
preferences provided by the experts before conversion to crisp
values. The aggregate results of the weights of the criteria are
presented in Table 5. The weighted normalized decision matrix
and the Fuzzy PIS and fuzzy NIS are given in Tables 6 and 7,
respectively.

6. Discussion

The closeness coefficient of the various green ICT alterna-
tives is obtained as 0.60, 0.43, 0.47, 0.45, 0.23 and 0.27 for
R1, R2, R3, R4, R5 and R6, respectively (Figure 1). The result
shows that power management is the most effective green ICT
alternative for the textile industry. This is not far-fetched from
the fact that textile industry is greeted with large and industrial
machineries which are now being integrated with Information
technology tools through data centers, server management and
end to end technology driven processes that are used in the pro-
duction and manufacturing processes hence power plays a vital

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Table 3: Alternative rating using linguistic terms

g1 g2
W1 W2 W3 W4 W5 W6 W1 W2 W3 W4 W5 W6

R1 H EH VVH VH A AA R1 VL L AA VH L VH
R2 A EH EH EH H BA R2 VL L A EH BA A
R3 VH VH VH VVH AA AA R3 VL L A AA H A
R4 AA EH VVH VVH VH VVH R4 VL L A VVH A A
R5 A VH EH EH VH H R5 VL EH A EH VH VH
R6 L VVH A VVH VVH VH R6 VL EH A VVH VVH A

g3 g4
W1 W2 W3 W4 W5 W6 W1 W2 W3 W4 W5 W6

R1 VL L A VH L H R1 VL L A VH L H
R2 L L L H L H R2 L L L H L H
R3 VL VL A VH L H R3 VL VL A VH L H
R4 VL L A VH L H R4 VL L A VH L H
R5 VL A A VH VL H R5 VL A A VH VL H
R6 VL L A H H H R6 VL L A H H H

g5
W1 W2 W3 W4 W5 W6

R1 A H EH A AA H
R2 A AA VH A AA L
R3 A AA H A EH L
R4 AA A H A EH L
R5 AA A A A VH L
R6 L L A A H L

Table 4: Combined responses of the experts

W1 W2 W3 W4 W5 W6
R1 (1,3.6,8) (1,4.8,10) (1,5.2,10) (47.4,9) (1,3.6,7) (5,7,9)
R2 (1,3.6,6) (1,4.6,10) (2,5.8,10) (4,7.8,10) (2,4.6,8) (2,5.2,8)
R3 (1,3.8,9) (1,3.8,9) (4,6,9) (4,6.6,9) (2,5.8,10) (2,5.4,8)
R4 (1,3.6,7) (1,4.4,10) (4,6.2,10) (4,7.8,10) (2,5.8,10) (2,6.2,10)
R5 (1,3.4,7) (4,6.6,10) (4,6,10) (4,8.2,10) (1,5.6,9) (2,6.4,9)
R6 (1,2.4,4) (2,5.6,10) (4,5,6) (47.4,10) (6,7.8,10) (2,6,9)

Table 5: Consolidated weight allocated to criteria

Criteria
Weight of the selection index

Combined weight
g1 g2 g3 g4 g5

W1 EMI VMI EMI VVMI MI (6,8.8,10))
W2 EMI I VVMI EMI VVMI (5, 8.8, 10)
W3 VVMI I I MI VVMI (5, 7.4, 10)
W4 VVMI VMI VMI I VMI (5, 8, 10)
W5 EMI I I I VVMI (5, 7.4, 10)
W6 MI MI I I MI (7, 6.6, 8)

role and results shows, it is the most preferred alternative, fol-
lowed by cloud computing, telecommuting and virtualization
respectively; these closeness in the results shows how tightly
coupled the technology drivers of the production output in tex-
tile industry are. Most processes are now reachable by very
wide audience due to popular and increased rate of cloud ser-
vice migration; down the line are some previous on - premise
technologies as shown in the result (telecommuting and virtu-

alization). User friendliness and software optimization are the
least preferred alternatives based on the output of this research;
although also important but compared to other options the ef-
fect of these criteria in line with the textile industries operations
and service delivery could be taken care of at a relatively mod-
erate level in the supply chain process without creating much
negative impact in the entire service delivery. Overall, the most
preferred green ICT alternative is making a choice of green ICT

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Adebisi & Babatunde / J. Nig. Soc. Phys. Sci. 4 (2022) 165–173 172

Table 6: Weighted normalized decision matrix

W1 W2 W3 W4 W5 W6

R1 (0.7,3.5,8.9) (0.5,1.8,10,0) (0.5,1.4,10.0 ) (2.0,5.9,9.0) (0.5,2.7,7.0) (2.5,3.5,7.2 )
R2 (0.7,3.5,6.7) (0.5, 1.9, 10.0) (0.5,1.3,5.0) (2.0,6.2,10.0 ) (1.0,3.4,8.0) (1.0,2.6,6.4 )
R3 (0.7,3.7,10.0 ) (0.5, 2.3,10) (0.5,1.2,2.5) (2.0,5.3,9.0) (1.0,4.3,10) (1.0,2.7,6.4 )
R4 (0.7,3.5,7.8) (0.5,2.0,10.0) (0.5,1.2,2.5) (2.0,6.2,10.0 ) (1.0,4.3,10.0 ) (1.0,3.1,8.0 )
R5 (0.7,3.3,7.8) (0.5,1.3,2.5) (0.5,1.2,2.5) (2.0,6.6,10.0 ) (0.5,4.1,9.0) (1.0,3.2,7.2 )
R6 (0.7,2.3,4.4) (0.5,1.6,5.0) (0.8,1.5,2.5) (2.0,5.9,10.0 ) (3.0,5.8,10) (1.0,3.0,7.2 )
A* (0.7,3.7,10.0 ) (0.5, 2.3,10.0) (0.8,1.5,10.0 ) (2.0,6.6,10.0 ) (3.0,5.8,10) (2.5,3.5,8.0 )
A- (0.7,2.3,4.4) (0.5,1.3,2.5) (0.5,1.2,2.5) (2.0,5.3,9.0) (0.5,2.7,7.0) (1.0,2.6,6.4 )

Table 7: Fuzzy PIS and fuzzy NIS

Distance from FPIS
W1 W2 W3 W4 W5 W6 di*

R1 0.7 0.3 0.2 0.7 2.9 3.9 8.56
R2 1.9 0.2 2.9 0.2 2.1 4.4 11.75
R3 0 0 4.3 0.9 1.4 4.4 11.09
R4 1.3 0.2 4.3 0.2 1.4 4.8 12.25
R5 1.3 4.4 4.3 0 1.8 4.6 16.41
R6 3.3 2.9 4.3 0.4 0 4.6 15.5

Distance from FNIS
R1 W1 W2 W3 W4 W5 W 6 di-
R2 2.7 4.3 4.3 0.4 0 1.1 24.76
R3 1.5 4.3 1.4 0.8 0.8 0 33.08
R4 3.3 4.4 0 0 2 0.1 33.26
R5 2 4.3 0 0.8 2 1 35.27
R6 2 0 0 0.9 1.4 0.6 43.57
R7 0 1.4 0.3 0.7 2.9 0.5 40.28

related services that makes provision for effective power man-
agement in achieving set goals and objectives.

Figure 1: Closeness Coefficient

7. Conclusion

The application of green ICT using a multicriteria decision
making method is a highly important task especially in tex-
tile industry. The great potential positive impact in the textile
industry will not only boost performance in the entire supply
chain trend but also create diverse opportunities to tackle var-
ious challenges at different stages resulting to improved cus-
tomer satisfaction. This research provided a method for select-
ing the best technology that will enhance textile industry activi-
ties using green ICT with the use of real case study as an exam-
ple. Three major novel contribution has been achieved with this
research namely, application of green ICT to textile industry,
confident selection of the best technology that will encourage
transparent and profit-oriented service delivery, incorporation
of customers perspectives into service delivery through the use
of ICT techniques and lastly, this research is capable of being a
decision-making reference tool in the selection of IT tools es-
pecially for startups in the textile industry. The outcome of this
study is expected to save cost, reduce energy consumption as
well as emission in the society. Furthermore, climate change,
environmental and health impact will be drastically reduced. It
is anticipated that decision makers will adopt and implement the
proposed framework in developing a green textile production.
Although the advantage of the Fuzzy Topsis approach are nu-
merous which include simplicity, rationality, comprehensibility,
good computational efficiency and ability to measure the rela-
tive performance for each alternative in a simple mathematical
form. The limitation of this method include high labor input,
large amount of initial data, and limited nature of the assess-
ment scale. Future study will adopt/develop robust multi crite-
ria methods to test the efficacy of the proposed framework and
possibly use other MCDM methods to benchmark the present
fuzzy-TOPSIS approach developed as well as comparison of
the result obtained from the study.

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