FACTA UNIVERSITATIS 
Series: Mechanical Engineering Vol. 19, No 3, Special Issue, 2021, pp. 345 - 360 

https://doi.org/10.22190/FUME201125029F 

© 2021 by University of Niš, Serbia | Creative Commons License: CC BY-NC-ND 

Original scientific paper 

GREEN SUPPLIER SELECTION BASED ON 

THE INFORMATION SYSTEM PERFORMANCE EVALUATION 

USING THE INTEGRATED BEST-WORST METHOD 

Hamed Fazlollahtabar1, Navid Kazemitash2 

1Department of Industrial Engineering, School of Engineering,  

Damghan University, Damghan, Iran  
2Department of Management, Faculty of Economics and Administrative Sciences, 

University of Mazandaran, Babolsar, Iran 

Abstract. Information Systems (IS) have become crucial for all the organizations to 

survive in contemporary technology-oriented environment. Consequently, the number of 

companies and organizations which have invested widely in their IS infrastructures to 

present better services and to produce higher value products is increasing. On the other 

hand, nowadays, because of the increase of governmental rules and serious requirements 

of more people in the case of environmental protection, it seems necessary for all the 

enterprises to follow these regulations if they want to survive in the global markets. 

However, what is at issue here is not just the companies’ agreement with the 

environmental laws; in addition, they should apply some strategies to decrease the 

negative environmental impacts of their products in some countries. Thus, the 

aforementioned arguments are the reasons for the compulsory use of the green supplier 

selection (GSS) in all firms. Considering the mentioned contents, the purpose of this study 

is representation of the relation between ISs and GSS as two vital components of firms in 

a novel way which has not been done before. Actually, it shows the ISs' performance or 

effectiveness to select the green suppliers taking into account the different levels of 

importance of GSS measures (including eight criteria and 31 sub-criteria), using a multi-

criteria decision-making method called Best Worst Method (BWM) to identify the weights 

(importance) of GSS measures and compute the GSS performance of 10 ISs in a company 

using the data gathered in a survey from ISs' experts. 

Key Words: Information systems, Green supplier selection, Best worst method, 

Significance scoring 

 
Received November 25, 2020 / Accepted March 02, 2021  

Corresponding author: Hamed Fazlollahtabar 
Department of Industrial Engineering, School of Engineering, Damghan University, Damghan, Iran 

E-mail: h.fazl@du.ac.ir 



346 H. FAZLOLLAHTABAR, N. KAZEMITASH 

 

1. INTRODUCTION  

Information Systems (IS) as an academic field, first of all, attracted research interest in 

the 1960s [1]. That was the time when the applied computer science emerged which in its 

turn aimed at the design and implementation of data processing applications. Information 

Systems (IS) have become essential for all the organizations to survive in today’s technology-

oriented environment. The number of companies and organizations which have invested 

widely in their IS infrastructures to present better services and to produce better value 

products is increasing. This rise has led to the question of how much those systems add value 

to the business or to the organization compared to their investment. The role of information 

systems (IS) in providing business a competitive edge has been the topic of so many 

discussions recently. The conclusion is that not the IS solution but their utilization is what 

provides competitive advantages. Thus, because of the aforementioned functions and 

importance of IS, there are too many studies which show a big role the ISs play in relation to 

the other fields such as health care and medicine [2, 3], transportation [4], energy [5], biology 

[6], education [7], environment [8, 9, 10], geography [11] and so many other disciplines. But 

one of the most important fields that the trace of ISs has been seen is the selection of green 

suppliers. 

Nowadays, because of the increase of governmental rules and serious requirements of 

more people in the case of environmental protection, it seems necessary for all the enterprises 

to follow these regulations if they want to survive in the global market. However, what is at 

issue here is not just the companies’ agreement with the environmental laws; in addition, they 

should apply some strategies to decrease the negative environmental impacts of their products 

in some countries. Therefore, to gain sustainable development, the integration of 

environmental, economic and social performance turned into a complex challenge for them. 

Because of the above reasons, the companies working on this matter buy their required 

materials and services from specific suppliers which can simultaneously fulfill their 

expectations like low-cost, high-quality, short lead-time and environmental criteria,. On the 

one hand, by considering the aforementioned information about the importance of ISs, green 

supplier selection, and the direct impact of ISs on the selection of green suppliers so that ISs 

effect on numerous other factors that impress selecting process in modern organizations, and, 

on the other hand, because of the financial restriction in both fields, a good recognition of 

their relation could be helpful to the reduction of costs and their effectiveness. Inasmuch as 

there are various applied ISs in companies by different tasks, each of them could have 

individual influence on selecting process.  

Hence, the purpose of this study is the evaluation of the impact of IS on the green 

supplier selection and actually finding the level of effectiveness of each IS on the green 

supplier selection process. Therefore, this paper is going to represent a great framework to 

support its goals. At first, it examines other research projects, literatures and experts' 

opinion to gather the most important criteria and sub-criteria which have effects on the 

green supplier selection. Then, through the Best-Worst method (BWM), the local and 

global weights of criteria and sub-criteria will be obtained by the experts' opinions. The 

next step is measuring the ISs' performance in association with green supplier selection 

which is gained by the experts' opinions. Ultimately, as a conclusion, companies could 

focus on the specific IS or ISs which play a more important role in the green supplier 

selection processes and reinforce them if necessary. 



 Green Supplier Selection Based on Information System Performance Evaluation Using the Integrated... 347 

 

2. LITERATURE REVIEW  

Because of the expansion of people awareness about the environmental changes and 

applying of the compulsory green rules which have been exerted by governments, 

approximately all companies should obey, to survive in these competitive markets. 

Therefore, there are so many studies that deal with suppliers. For instance [12] represented a 

green supplier selection model based on the emission of CO2 which is produced through the 

transportation and production processes by considering three models to maximize the total 

profits and the green factors, and minimize the CO2 emissions. Banaeian et al. [13] in their 

research have selected the green supplier using the fuzzy group decision-making methods. 

Actually, they compared the result of three different techniques- TOPSIS, VIKOR and GRA 

methods in a fuzzy environment. Kuo, et al. [14] developed a green supplier selection model in 

the electronic industry by using the new hybrid MCDM method including DANP and VIKOR. 

Environmental Permits and Reporting, Pollution Prevention and Resource Reduction, 

Hazardous Substances Wastewater and Solid Waste, Air Emissions and Product Content 

Restrictions were considered as Environmental dimension, while Company Commitment, 

Management Accountability and Responsibility, Legal and Customer Requirements, Risk 

Assessment and Risk Management, Improvement Objectives, Training, Communication, 

Worker Feedback and Participation, Audits and Assessments and Documentation and 

Records determined as Management systems dimension.  

Govindan et al., [15] reviewed all the research studies related to the green supplier from 

1997 till 2011, in order to find the most common used approaches for evaluating and 

selecting the green supplier as well as the most common criteria which have been 

considered in this case and finally identifying the existent limitations. For instance, their 

study illustrated that the fuzzy single approach has been the most repetitive applied 

technique and the environmental management system has been the most selected criteria. 

Jain et al. [16] presented an initiated decision-making process to evaluate the suppliers 

based on the green criteria in which there are a Carbon Market Sensitive (CMS) and a green 

decision-making approach based on Data Envelopment Analysis (DEA) called CMS–

GDEA. Their applied model in one case displayed that the “Pay Up” factor from carbon 

trading adds a new dimension to competition among suppliers and increases overall supply 

chain profitability; finally, they encourage companies to follow the green rules. Gupta et 

al. [17] worked on the evaluation of supplier selection based on the green innovation 

abilities among small and medium companies. In their study, there are three different 

methodological phases including; selection of green innovative criteria through literature 

review and interviews with decision-makers, ranking of selection criteria using a novel best 

worst method (BWM) and ranking of suppliers with respect to selection criteria weights 

obtained in phase two using fuzzy TOPSIS. In another research, Galankashi et al. [18] 

prioritized the criteria which affect the green supplier selection through the fuzzy analytical 

network process. Hamdan and Cheaitou [19] by using the combination of three techniques 

including AHP, fuzzy TOPSIS and multi-objective optimization approach, evaluated the 

supplier selection and the order allocation based on the green criteria that led into the flexible 

model.  



348 H. FAZLOLLAHTABAR, N. KAZEMITASH 

 

The aim of [20] was to implement hybrid Grey theory-MARCOS methods for decision-

making regarding the selection of suppliers in the Libyan Iron and Steel Company (LISCO). 

This hybrid model was divided into two phases: the first consists of determining the weights of 

the criteria that contribute to decision-making, which has been done using the Grey theory, and 

the second phase consists of selecting the best supplier from among six suppliers, which has 

been completed using the MARCOS model. Durmić et al. [21] performed supplier selection to 

achieve sustainability, taking into account all aspects: economic, social and environmental 

criteria. For this purpose, a combined FUCOM - Rough SAW approach has been used.  

Pamucar [22] provided a multi-criteria decision-making that combines interval grey numbers 

and normalized weighted geometric Dombi-Bonferroni mean operator to address the situations 

where attribute values take the form of interval grey numbers under uncertain information. 

There are too many research studies about GSS and ISs separately as two crucial parts of 

contemporary organizations, while, except for some limited studies in which IS is considered 

as an effective factor for GSS, there is no research that points to the relation between them. This 

is the exact reason why this paper works on. On the other hand, the second issue that is observed 

in the majority of the previous studies is using the complicated and time-consuming techniques 

like DEMATEL, AHP, ANP, DANP, TOPSIS and VIKOR to compute the needed 

requirements, although there are so many studies which have mentioned their weak points. And 

it is the exact reason that why this paper utilized a novel MCDM technique (BWM) that is 

simpler and more practical, functional and usable.     

3. STATEMENT OF THE PROBLEM 

On the one hand, in this contemporary business world, there is not any enterprise which 

would be able to compete and even survive without having close relations with outer partners; 

that is exactly the point where the supplier chain management (SCM) arises from and wants to 

optimize the information flow exchanges among all participating factors in the supplier chain. 

Thus, the more effective supplier chain, the more competitive the advantages; so, because of 

the complex condition of today's business, all companies need to have a long-term relationship 

with their partners – this is the reason why all corporations should be aware and alert to identify 

and select supply resources. Hence it can show the extreme importance of supplier selection. 

As mentioned, by considering the growth of worldwide awareness of environmental protection, 

green production has become an important issue for almost every manufacturer and will 

determine his long-term sustainability. Thus, the green factors have changed the face of supplier 

selection. Because of the growth of governmental rules and serious and increasing demands of 

the mass in the case of environmental protection, it seems crucial for all companies to follow 

these regulations if they want to remain in the market. However, the deal of companies with 

these environmental laws is not enough; they should apply some strategies and policies to 

reduce the negative environmental impacts of their products. Consequently, to obtain 

sustainable development, the integration of environmental, economic and social performance 

has turned into a complex challenge for them. Because of the above reasons, companies 

consider various criteria to assign their required materials to suppliers.   



 Green Supplier Selection Based on Information System Performance Evaluation Using the Integrated... 349 

 

On the other hand, ISs have become vital for all of companies to survive and remain in 

today’s technology-oriented market. The number of companies and firms which have invested 

widely in their IS infrastructures to present better services and to produce better value 

products is increasing. Nowadays in majority of the companies, there are some practical and 

basic information systems which have changed from competitive advantage to necessity and 

as it was expressed, because of the significance of the flow of information in the supplier chain, 

the information systems emerge as one of the most effective factors in the green supplier 

selection. 

But there are some barriers and even problems which have played hidden roles in 

selection of the best green supplier and never have been paid attention to: 1- There is no 

localized green supplier selection model for the examined industry. 2- Although all the 

evidence shows the impact of ISs on green supplier selection, there is not any study 

showing the impact of different types of ISs on criteria and sub-criteria of the green supplier 

selection which leads to the evaluation of the ISs' effectiveness regarding green supplier 

selection. 3 -there is not any research that indicates which IS plays the most important role in 

connection with selecting the green supplier. As the aim of this paper is evaluating of each single 

IS in effecting on the green suppliers’ selection and actually finding the level of 

effectiveness of each IS on the green supplier selection process, it could cope with the 

aforementioned problems. At the first step, it represents a localized GSS model including 

eight criteria and 31 sub-criteria of green supplier selection, based on the GSS experts' 

opinions (first problem). Then it illustrates the performance of every IS in relation with 

green supplier selection process using the WBM (which computes the importance (weights) 

of every measure of GSS model) and performance item-scores (which represents the 

effectiveness and performance of ISs to select the green suppliers) of all existent ISs in a 

company (second and third problem). 

After the presentation of the model, the procedures of problems solving are demonstrated 

as techniques, step by step.  

As shown above, there are three primitive operations in which 8 criteria and 31 sub-

criteria have been selected by 12 number of organization experts that have been extracted 

from the principal literature. Then, the BWM as the MCDM technique consists of three 

sub-sections in which the local weights of criteria, the local weights of sub-criteria and 

finally the global weights of sub-criteria are computed, respectively. As the last step, by 

determining the ISs' performances regarding meeting the green supplier selection criterion, 

the scores of the ISs are calculated. Ultimately, based on the computed final scores of ISs, 

they are ranked. In this way, the determined goals of study are achieved, or indeed, the 

mentioned problems of the study are solved. 

4. METHODS AND MATERIALS 

The purpose of this study is to evaluate the performance of various ISs of a company, 

in the green supplier selection process (GSS). As this aim is met by a MCDM method to 

gain the global weights of the green supplier selection' sub-criteria, and another technique 

to rank the ISs, based on their performances in connection with the GSS, it looks necessary 

to show the steps of BWM as the MCDM method and item-scoring to rank the ISs. The 

proposed conceptual model is depicted in Fig. 1. 



350 H. FAZLOLLAHTABAR, N. KAZEMITASH 

 

 

Fig. 1 The conceptual model of green supplier selection's criteria and sub-criteria 

4.1. Best Worst Method 

As discussed above, because the green supplier selection is a multi-criteria concept, to 

measure it, we should use MCDM method. MCDM methods allow considering multiple 

criteria with different weights. There are several MCDM methods that have been applied 

in literature but in this study, a newly developed MCDM method called best worst method 

(BWM) is used [23, 24]. In comparison with similar existing MCDM methods, BWM 

needs less data as it does not require a full pairwise comparison matrix, and its results are 

more consistent due to its structured pairwise comparison system; that is the main reason 

why it is applied in this study. Further, it is perceived by the decision-makers as simple and 

very close to the way they judge and reason while making decision. Subsequently, the steps 

of the BWM are described briefly as follows: 

 

Step 1 - Determine a set of decision criteria. In this study, the criteria are presented in 

two levels as criteria and sub-criteria. 

 

Step 2 - Determine the best (B) (e.g., the most desirable, the most important) and the 

worst (W) (e.g., the least desirable, the least important) decision criteria based on the 

decision-maker(s)/expert(s) opinion. 



 Green Supplier Selection Based on Information System Performance Evaluation Using the Integrated... 351 

 

Step 3 - Determine the preference of the best decision criterion (B) over all the other 

decision criteria, using Linguistic 9-point scale for pairwise comparison for best worst 

method (Table 1). The result is a best-to-others (BO) vector as follows: 

 A𝐵 = (𝑎𝐵1, 𝑎𝐵2 , … , 𝑎𝐵𝑛 ) 

whereas aBj represents the preference of B over j and as expected aBB =1. 

Table 1 Linguistic scale for pairwise comparison for best worst 

Linguistic 

scale Equally important 

Equal to 

moderately more 

important 

Moderately more 

important 

Moderately to 

strongly more 

important 

Strongly 

more 

important 

Equivalent 

number 

1 2 3 4 5 

Linguistic 

scale 

Strongly to very 

strongly more 

important 

Very strongly 

more important 

Very strongly to 

extremely more 

important 

Extremely 

more important - 

Equivalent 

number 

6 7 8 9 - 

Step 4 - Determine the preference of all the decision criteria over the worst criterion 

(W), using Linguistic 9-point scale for pairwise comparison for best worst method (Table 

1), which results in the others-to-worst (OW) vector as follows: 

 AW = (𝑎1𝑊 , 𝑎2𝑊 , … , 𝑎𝑛𝑊 )
𝑇  

whereas ajW represents the preference of j over W and, as expected, aWW =1. 

 

Step 5 - Find the optimal weights (W1
*, W2

*,…, Wn
*). The optimal weights should be 

determined so that the maximum absolute differences 

{|WB − 𝑎𝐵𝑗 𝑊𝑗 |, |𝑊𝑗 − 𝑎𝑗𝑊 𝑊𝑤 |}for all j is minimized, or equivalently; 

 𝑚𝑖𝑛  𝑚𝑎𝑥 {|WB − 𝑎𝐵𝑗 𝑊𝑗 |, |𝑊𝑗 − 𝑎𝑗𝑊 𝑊𝑤 |} 

subject to ∑ 𝑊𝑗 = 1𝑗  

 𝑊𝑗 ≥ 0 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑗 (1) 

Problem (2) is equal to the following linear problem: 

 𝑚𝑖𝑛 𝜉𝐿  

subject to |WB − 𝑎𝐵𝑗 𝑊𝑗 | ≤ 𝜉
𝐿  𝑓𝑜𝑟 𝑎𝑙𝑙 𝑗 

 |𝑊𝑗 − 𝑎𝑗𝑊 𝑊𝑤 | ≤ 𝜉
𝐿  𝑓𝑜𝑟 𝑎𝑙𝑙 𝑗 

 ∑ 𝑊𝑗 = 1𝑗  

 𝑊𝑗 ≥ 0 𝑓𝑜𝑟 𝑎𝑙𝑙 j (2) 

 



352 H. FAZLOLLAHTABAR, N. KAZEMITASH 

 

Solving the above model (2), optimized weights (W1
*, W2

*,…, Wn
*) and the optimal 

objective function value ξL will be gained. For this model ξL can be directly considered as 

an indicator of the consistency of the comparisons (here we do not use Consistency Index, 

so that values close to zero show a high level of consistency of the pairwise comparisons 

provided by the decision-maker(s)/expert(s).  

For MCDM problems with more than one level of criteria such as this study, first of all, 

the weights for different levels should be obtained through the BWM steps, then, the 

weights of different levels have to be multiplied to determine the global weights [25]. 

4.2. Evaluation of ISs by item-scoring 

Using the BWM, the optimal weights of the criteria (W1
*, W2

*,…, Wn
*) are calculated. 

Now the ISi so that (i=1,…,m) with respect to its green supplier selection measurement j, 

so that (j=1,…,n) is obtained. Therefore, xij using, for instance, a 7-point scale (very low to 

very high), to determine the overall green supplier selection's performance of ISi. For the 

GSSi the following formula: 

 𝐺𝑆𝑆𝑖 = ∑ 𝑊𝑗 ∗ 𝑥𝑖𝑗
𝑛
𝑗=1 ,   𝑎𝑛𝑑 𝑖 = 1,2, … , 𝑚. (3) 

5. CASE STUDY 

The proposed information system effectiveness model is tested to evaluate and rank the 

use of ISs in Emdad-Khodro Company. Saipa automotive group as one of the two biggest 

automotive companies of Iran decided to found Emdad-khodro firm as its subdivision 

company with the purpose of responding to relief requirements of their customers to 

complete the after-sale services network in 2003. To achieve the planned goals and be 

adaptable in the contemporary market compared with the rivals, it has implemented some 

management systems such as Quality Management Systems based on ISO9001, 

Complaints Management System based on ISO10002, Training Management System based 

on ISO10015 and Risk Management System based on ISO31000 and information systems 

which are explained in detail in the following. 

According to the functions of the determined model, it is obviously necessary to specify 

using ISs in the company and start the analysis. Based on the record of company, there 

have existed windows-based ISs for 15 years; although almost all the web-based systems 

which have been implemented since 2011, have replaced the windows-based ISs as a major 

platform, there are some minor parts which still use windows-based systems. Web-based 

systems work in the field of employees, customers and representations. Finally, mobile ISs 

have been applied since 2014 which actually cover the whole activities related to company. 

However, there are 10 active information systems such as transaction processing system 

(TPS), electronic commerce (EC), customer relation management (CRM), decision support 

system (DSS), management information system (MIS) and office automation system 

(OAS), knowledge management (KM), supply chain management (SCM), enterprise 

resource planning (ERP) and business intelligence (BI). But there is not any research of 

their performance and effectiveness in the case of GSS; this is an opportunity to try to do 

that and that is the reason why it is selected as the case study. 

Here, firstly, the conceptual framework of GSS is presented which adopted from the 

literature to measure ISs' performance as a multi-criteria decision-making problem, as 



 Green Supplier Selection Based on Information System Performance Evaluation Using the Integrated... 353 

 

shown in Fig. 1. In fact, it is a visualization of Table 2, including eight perspectives (main 

criteria) to measure ISs' performance (green design, Service, Green Image, Quality, 

Environmental Management, Green Product, Delivery and Cost), as well as the items (sub-

criteria) of each perspective (three sub-criteria to measure Green Design perspective, two 

sub-criteria to measure Service perspective, two sub-criteria to measure Green Image 

perspective, three sub-criteria to measure Quality perspective, six sub-criteria to measure 

Environmental Management perspective, seven sub-criteria to measure Green Product 

perspective, four sub-criteria to measure Delivery perspective and ultimately four sub-

criteria to measure Cost perspective). As mentioned before, to measure the ISs' performance 

of a firm, it is necessary to have two sets of data: the optimal weight for the criteria (W1
*, 

W2
*,…, Wn

*) and the ISs' score on various sub-criteria, xij. The optimal weights are obtained 

through the expert opinions, while the scores are computed based on the data from a survey 

among the 100 experts of ISs. In the following sections, gaining weights is described firstly, 

and then the scores and, finally, the use of the equation (3) to calculate the overall 

performance of each IS. 

5.1. Weights of green supplier selection measures 

To obtain the weights of the criteria and sub-criteria, the comparison data needed for 

BWM is gained by interviewing 20 experts in the field of green supplier selection, 

individually. Next, the weights of criteria and their sub-criteria are determined using BWM. 

Finally, the overall weights for the criteria and sub-criteria are computed by using the 

aggregation (based on a simple average). Table 2 shows the aggregated weights of the eight 

main criteria and their items (sub-criteria) based on the inputs which are provided by the 

experts. The consistency ratios are all close to zero ranging from 0 to 0.17, which shows a 

high reliability of the results. As can be seen from Table 2, Column 2, Green Product 

(weight = 0.2468) criteria is the most important green supplier selection perspective, 

followed by Green Design perspective (weight = 0.1741), Quality perspective (weight = 

0.1330), Delivery perspective (weight = 0.1219), Service perspective (weight = 0.1008), 

Environmental Management perspective (weight = 0.0994), Cost perspective (weight = 

0.0894) and Green Image perspective (weight = 0.0346) which is by far the least important 

perspective of the green supplier selection based on the experts' opinion. 

The global weights of the sub-criteria (the multiplication of the weights of the sub-

criterion by the weights of the main criterion to which it belongs) are calculated in Table 

2, Column 5. Based on these results, Design for reduction or elimination of hazardous 

materials as the third sub-criteria of the Green Design (weight = 0.1176) has the most 

weight which illustrates the most effectiveness role which a sub-criterion could play with 

respect to the green supplier selection, though the Green Product has the most amount of 

weight among the criteria. 

 

 

 

 

 



354 H. FAZLOLLAHTABAR, N. KAZEMITASH 

 

Table 2 Relative importance (weights) of the criteria and sub-criteria 

Criteria 
Local 

weights 
Sub-criteria 

Local 

weights 

Global weights of 

sub-criteria 

Green design 0.1741 

Design for resource efficiency 0.0885 0.0154 

Design of products for reuse, 

recycle, and recovery of material 
0.2360 0.0411 

Design for reduction or elimination 

of hazardous materials 
0.6755 0.1176 

Service 0.1008 
Rate of processing order 0.2336 0.0235 

Service quality 0.7664 0.0773 

Green Image 0.0346 

Ratio of green customers to total 

customers 
0.8418 0.0291 

Green purchase trend of customers 0.1582 0.0055 

Quality 0.1330 

Quality-related certificates 0.6316 0.0840 

Capability of quality management 0.2535 0.0337 

Reject Rate 0.1149 0.0153 

Environmental 

Management 

 

0.0994 

Environmental Protection 

policies/plans 
0.1472 0.0146 

Environment Protection System 

Certification 
0.1106 0.011 

EUP 0.4448 0.0442 

ODC 0.0543 0.0054 

RoHS 0.1151 0.0114 

WEE 0.1280 0.0127 

Green Product 0.2468 

Cost of Component Disposal 0.1376 0.034 

Green Production 0.2922 0.0721 

Green Certifications 0.1190 0.0294 

Green Packaging 0.1351 0.0333 

Recycle 0.1272 0.0314 

Remanufacturing 0.0427 0.011 

Reuse 0.1463 0.0361 

Delivery 0.1219 

Order Frequency 0.0866 0.011 

Order Fulfillment Rate 0.2520 0.0307 

Lead time 0.1810 0.0221 

Delivery efficiency 0.4804 0.0586 

Cost 0.0894 

Buying Friendly Materials 0.0837 0.0075 

Compliance with Sectorial Pricing 0.1422 0.0127 

Performance Value/Price 0.5277 0.0472 

Transportation Cost 0.2463 0.0220 

5.2. Green supplier selection item-scores of ISs 

As the first step, in a survey among the 50 ISs' experts of the mentioned firm, their 

opinions about the ISs performance and effectiveness with respect to the selection of green 

suppliers are provided, in which the respondents rated 10 most common ISs level based on 

items from different GSS determined sub-criteria on a nine-point Likert type scale. And 

finally, the last operation of this step is that the experts' opinions for every single sub-

criterion are averaged (Table 3). Then, the aggregated GSS performance of the various ISs 

with respect to different perspectives (Columns 2, 4, 6, 8, 10, 12, 14, 16), as well as the 

ranking of each IS based on each perspective (Columns 3, 5, 7, 9, 11, 13, 15, 17) are 



 Green Supplier Selection Based on Information System Performance Evaluation Using the Integrated... 355 

 

computed (Table 4). Furthermore, the overall aggregated GSS performance of each IS 

based on items of all perspectives and overall ranking based on this aggregated number are 

shown in Table 4, Columns 18 and 19, respectively. Assigning weights to different items 

(sub-criteria) and to different perspectives (main criteria) produces significant differences 

in the overall (and perspective-based) GSS score of different ISs. 

Table 3 Green supplier selection item-scores of 10 ISs 

  
Green Design Service Green Image Quality    

G1 G2 G3 S1 S2 G1 G2 Q1 Q2 Q3    
TPS 3.67 4.31 4.52 7.16 3.09 5.07 4.14 4.59 5.56 5.14    
OAS 3.54 3.78 4.63 7.86 3.96 5.26 4.39 4.48 6.21 5.49    
MIS 6.53 7.09 6.9 5.87 5.48 6.79 7.54 7.87 7.79 7.19    
DSS 5.92 6.73 7.08 6.16 4.97 6.66 6.92 6.67 6.86 6.97    
EC 5.01 6.19 4.74 8.27 6.07 7.51 6.74 6.13 5.45 4.77    
ERP 8.69 4.99 7.21 7.12 5.13 5.12 6.59 6.19 7.37 4.16    
SCM 8.15 4.96 7.59 7.66 5.34 4.88 5.9 5.79 7.03 4.99    
CRM 5.79 8.14 6.68 7.7   7.93 7.99 8.43 7.28 7.84 6.18    
KM 4.91 5.61 5.63 6.02 5.18 5.64 6.47 6.47 5.72 5.45    
BI 6.13 7.17 5.13 6.59 6.11 7.26 7.09 6.52 5.02 6.16    
 Environmental Management Green Product 

 E1 E2 E3 E4 E5 E6 G1 G2 G3 G4 G5 G6 G7 

TPS 4.31 4.62 4.09 4.18 3.75 3.62 2.42 4.39 4.73 5.29 6.14 5.92 6.27 

OAS 4.57 5.26 3.68 4.3   4.12 3.79 3.59 4.79 5.02 5.4   6.52 6.3   6.55 

MIS 7.7 7.41 5.58 5.73 7.96 5.8   6.23 8.08 7.28 7.58 7.91 7.44 7.4 
DSS 6.23 6.52 4.78 6.14 6.47 6.26 5.89 7.53 6.46 6.79 6.57 6.81 6.78 

EC 6.69 6.17 6.59 6.93 6.85 7.47 6.44 6.12 7.26 5.55 5.59 6.85 6.62 

ERP 7.85 7.55 5.18 5.63 7.69 7.15 7.13 7.71 7.93 8.32 8.21 8.06 7.79 
SCM 8.1 7.29 5.14 5.22 6.67 7.81 7.61 6.18 7.89 5.14 6.83 7.14 7.34 

CRM 5.94 6.26 4.49 5.06 4.53 5.34 5.7   5.18 6.23 6.67 7.43 6.99 6.76 

KM 5.63 5.2   5.01 5.29 5.37 5.76 6.09 7.03 5.35 5.81 6.86 7.16 7.51 
BI 5.15 5.51 5.37 5.71 6.11 4.39 6.43 7.1   5.03 6.32 5.94 6.05 6.16 

 Delivery Cost   

 D1 D2 D3 D4 C1 C2 C3 C4      
TPS 3.13 5.48 5.77 4.69 5.6 5.47 6.71 5.4        
OAS 3.47 6.23 6.12 5.66 6.07 5.9   6.8   5.81      
MIS 6.27 5.69 6.49 6.17 6.35 7.83 6.55 6.79      
DSS 6.14 4.18 5.83 5.67 5.71 6.79 6.97 5.54      
EC 6.77 6.17 6.16 6.47 7.01 7.35 7.49 7.74      
ERP 6.52 7.38 7.59 7.53 8.14 5.15 6.73 5.18      
SCM 6.63 7.09 8.13 7.79 7.57 6.58 7.76 5.12      
CRM 7.19 5.57 5.88 7.63 5.04 7.12 6.37 4.65      
KM 5.12 4.25 5.27 6.92 5.44 6.03 6.34 4.3        
BI 6.38 4.27 6.43 6.51 6.56 6.52 6.86 5.95      

According to Table 4, there are two different ways in which it is possible to evaluate 

and investigate the performance of ISs to support the GSS process it is based on. On the 

one hand, it is available to assess the performance of ISs through their overall aggregations 

and rankings, so that the more overall aggregation, the better ranking. For instance, MIS 

possesses the most overall aggregation (6.8800), so it is the first information system as the 

best one. 



356 H. FAZLOLLAHTABAR, N. KAZEMITASH 

 

Table 4 Green supplier selection performance of 10 ISs. 
 

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 Green Supplier Selection Based on Information System Performance Evaluation Using the Integrated... 357 

 

It means that it has the most effectiveness and best performance in relation with GSS. 

And after that, ERP (6.7986), CRM (6.6319), SCM (6.5756), DSS (6.3210), EC (6.1931), 

BI (6.0805), KM (5.8977), OAS (5.0642) and TPS (4.7460) are placed in the following 

ranking, respectively. On the other hand, it is possible to investigate the ISs based on their 

scores and rankings in every single part (the aggregation of every criterion). For example, 

MIS performance as the best one among the 10 mentioned ISs, is placed as the first one in 

the Quality criteria, the second one in three criteria, including Environmental Management, 

Green Product and Cost criteria, the third one in the Green Design criteria, the fourth one 

in the Green Image criteria and the sixth one in the Service criteria. As this way evaluates 

the performance of ISs in every GSS criteria, it is the best one to compare two different ISs 

which have close overall aggregations (not exactly the same). For example, there is a slight 

difference between the overall aggregation of MIS and ERP which are 6.8800 and 6.7986, 

respectively, thus in the eyes of someone, it could not clearly explain the superiority of 

MIS over ERP. Therefore, they rely on the second way to describe the differences and 

performance of every one in comparison with others. In this case, ERP's performance (rank 

or actually aggregated score) is better than MIS in three criteria consisting of Service, 

Delivery and Green Product in which the ERP has the best performance, while in the other 

criteria MIS has better scores and rankings. Based on the given information in Table 4, CRM 

as the third ranked IS according to the overall aggregated has the best performance (score) in 

two perspectives including Service and Green Image. In the same situation, SCM as the fourth 

effective IS, possesses two first ranks in Green Design and Delivery criteria and finally as the 

sixth effective IS in relation to GSS, EC is placed as the first one in Environmental 

Management and Cost criteria, even though it is mentioned as the most effective IS, it is the 

best just in one perspective. 

5.3. Managerial implications 

Our results possess critical managerial implications. Firstly, positioning is an important 

participator in GSS performance because it provides an acceptable basis for ISs to compare 

their GSS performance to that of other ISs. Secondly, regardless of positioning, having 

knowledge about the importance of different GSS perspectives, and about the different items 

of each perspective, GSS related managers can formulate more effective strategies to improve 

their GSS performance based on their own purposes. The presented methodology in this study 

has been used to determine the weight and importance of different aspects of overall IS 

performance. This gives managers a chance to have a good view of critical aspects of 

performance and allows them to focus more on the important aspects. This study has 

considered GSS performance from eight perspectives which have been used in the literature. 

As such, GSS related managers can enhance GSS performance of their ISs, based on their 

purposes. According to this study's findings, Green Product criteria of GSS play the most 

important role in enhancing GSS performance, which means that, if the Green Product 

aspects should be the purpose of a firm, focusing more on the Green Production 

measurements will improve the firm’s GSS performance, as this measure is the most 

important of all Green Product measurements. Furthermore, for other criteria, this study 

also determines the sub-criteria which are the most important and how the green supplier 

selection related managers can improve their firms’ GSS performance based on different 

goals. 



358 H. FAZLOLLAHTABAR, N. KAZEMITASH 

 

6. CONCLUSIONS 

Although there are so many research studies of the GSS and information systems 

separately, and there are some studies which refer to the IS as one of the criteria or sub-

criteria to select the green supplier, there is not any study to evaluate and investigate the 

direct relation between these two vital elements of the disciplines that are related to firms 

and identify the performance of every IS and its effectiveness with respect to GSS, though 

ISs have been turned into the necessity of all companies. Actually, the advantages of this 

evaluation is that understanding the importance of different GSS measures helps managers 

spend more time, money, energy and resources on the critical aspects on their objectives. 

The methodology proposed in this paper can be utilized in two general contexts: (1) as a 

systematic way to compare the GSS performance of a set of ISs. In this context, based on 

the results of similar evaluation and the determined purposes of the companies, the position 

of every ISs and their superiorities could be found. Plus, the results can also be used by 

other stakeholders, for instance allowing venture capitalists to identify the best investment 

opportunities; (ii) as a systematic way to specify the importance (weight) of different criteria 

and measurements for a single IS. In this context, the results can be used by the firm in 

question to formulate effective GSS strategies that are adjusted to its competitive strategy. 

6.1. Findings  

The results show the importance of taking into account the weights of different green 

supplier selection items, which allows each IS to determine not only its overall aggregation 

position (Quality), while at the same time providing accurate information of its position 

with regards to each criterion. Moreover, ISs can improve their green supplier selection 

performance based on the importance of each perspective. For example, if SCM wants to 

maintain or improve this ranking, it should focus more on the Ratio of green customers to 

total customers which has the highest importance among all items of Green Image 

perspective, in which SCM is located in the ninth place (see Table 2). Moreover, in some 

situations, where the aim is not to compare the position of ISs with each other or such a 

comparison is impossible to make, knowing the importance of each criterion and their sub-

criteria can help ISs to improve their performance based on their main objectives. More 

precisely, if an IS wants be prominent in Green Product as the most important criteria in 

GSS process, it should focus on and invest in Green Production, since the given information 

in Table 2 shows that the Green Production level is the most important item from a Green 

Product perspective. In addition, by changing their objectives, ISs can change their strategy and 

invest more in specific perspective(s) in line with their new purposes. For instance, if an IS has 

thus far concentrated more on the Quality perspective, focusing more on Green Design 

aspects can help the IS improve its GSS by looking at Design for reduction or elimination 

of hazardous materials since the results in Table 2 show that it is the most important 

measurement within the Green Design perspective. Therefore, regardless of knowing its 

position relative to other firms, based on the weight of the sub-criteria of different GSS 

perspectives (Table 2), an IS can recognize which sub-criteria(s) can improve or change its 

green supplier selection performance from each perspective. As such, these results can help ISs 

enhance their overall performances. 



 Green Supplier Selection Based on Information System Performance Evaluation Using the Integrated... 359 

 

6.2 Limitations  

The proposed methodology utilized to solve the defined problem, has no limitations 

and can be used for solving any MCDM problem. What makes this paper stand out from 

others is that it is the first time that one study evaluates the direct relation of ISs and GSS 

individually, and, on the other hand, it is the first time that a study measures the GSS 

performance of ISs in which the contributions of ISs in related to GSS are computed. But, like 

every other study, interviewing numerous experts in every part of methodology took the time 

out of standard range. Plus, gathering the data through the questionnaire from 100 experts is too 

hard and time-consuming, and consequently, the calculations and operations of their opinions 

are so complicated.  

6.3. Future research direction  

In the future research, it could be possible to measure the same thing with different GSS 

model including different criteria and sub-criteria. As another suggestion for future, it is 

possible to change the first or second part of this relation, for instance, the evaluation of 

online ISs' performance in GSS. 

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