a fuzzy ahp method to support sustainability reporting an application to the water technology

8/18/2019 A Fuzzy AHP Method to Support Sustainability Reporting an Application to the Water Technology

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aphical Abstract (for review)


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A fuzzy AHP method to prioritize ‘materiality’ of sustainability aspects and indicators

The proposed method is based on the G4 GRI Guidelines

The method is especially useful for supporting SMEs in sustainability reporting

ghlights (for review)


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A fuzzy AHP method to support sustainability reporting: an application to the water

technology industry

Armando Calabrese1 , Roberta Costa

1*, Nathan Levialdi

1 , Tamara Menichini

1

1 Department of Enterprise Engineering, University of Rome “Tor Vergata”, Italy

* corresponding author: Roberta Costa

Address: University of Rome Tor Vergata, Department of Enterprise Engineering, Via del

Politecnico 1, 00133 Rome, Italy.

tel.: 0039 06 72597799

fax.: 0039 06 72597951

e-mail: [email protected]

le page

mailto:[email protected]:[email protected]:[email protected]:[email protected]


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1

A fuzzy AHP method to support sustainability reporting: an application to the water

technology industry

Abstract

Sustainability reporting encourages companies to set goals and measure their performance in

the sustainability of operations concerning economic, environmental and social impacts.

However not all sustainability issues have the same relevance for every organization.

Company reporting must cover the ‘material’ aspects of sustainability, meaning the areas that

can be positively or negatively affected by their activities. Reporting on the material aspects

of sustainability provides greater transparency for stakeholders, and achieves greater

accountability of the companies for their actions and effects.

This paper proposes a ‘fuzzy analytic hierarchy process’ (fuzzy AHP) method to support the

identification and prioritization of the company’s material sustainability aspects. Based on the

Global Reporting Initiative (GRI) G4 Guidelines, the method evaluates the significance of

GRI ‘Aspects’ and ‘Indicators’ for reporting the company’s sustainability performance. The

fuzzy AHP method prioritizes the aspects and indicators for inclusion in the report, thus

assisting company managers to disclose results effectively, while also managing the time and

financial constraints that can restrict their efforts in sustainability reporting. To illustrate the

method, the paper presents a case study of an Italian SME active in the water technology

industry.

Keywords: sustainability reporting; Global Reporting Initiative (GRI); fuzzy Analytic

Hierarchy Process (AHP); small and medium enterprises (SMEs)

anuscript

ck here to view linked References

http://ees.elsevier.com/jclepro/viewRCResults.aspx?pdf=1&docID=13020&rev=0&fileID=340440&msid={A662572E-2A92-4404-BFAA-ED9FF33E4C43}http://ees.elsevier.com/jclepro/viewRCResults.aspx?pdf=1&docID=13020&rev=0&fileID=340440&msid={A662572E-2A92-4404-BFAA-ED9FF33E4C43}


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1. Introduction

Company sustainability depends on awareness of corporate responsibilities. Sustainable

companies interact with society, the economy and environment, considering the needs of both

present and future stakeholders, working towards goals of sustainable development

(Robinson, 2004). Sustainability reporting, or the practice of measuring and disclosing the

company’s sustainability performance, ensures accountability to stakeholders and supports

the company in managing change towards operation in a more sustainable manner

(Bebbington, 2001; GRI, 2013a, 2013b). Transparent communication improves the credibility

of the company’s environmental and social commitments and favours its long-term processes

of value creation (Birth et al., 2008; Schmeltz, 2014).

However differing organizational characteristics, such as the business model, size, ownership

and social and cultural context, affect both company impacts and the stakeholder expectations

concerning sustainability (Porter and Kramer, 2006). Because of this, not all aspects of

sustainability have the same relevance for every company (GRI, 2013a, 2013b; ISO, 2010).

For a company to be truly accountable to stakeholders, it is crucial that it identify which

sustainability-related content to disclose, and identify the appropriate levels of detail for

reporting the information (Kolk, 2008). The Global Reporting Initiative (GRI) Sustainability

Reporting Guidelines, which is the best known framework for sustainability reporting,

stresses the importance of focusing on the ‘material’ aspects of sustainability (Marimon et al.,

2012). The ‘material’ sustainability aspects are those that significantly reflect the company

economic, environmental and social impacts (GRI, 2013b). For more transparent and

coherent disclosure of its sustainability performance, the company must identify and

prioritize those aspects and indicators that are material (GRI, 2013a, 2013b). Ideally,

companies would be able to draw on quantitative methods to assess the relative material

importance of sustainability aspects and indicators of multidimensional performance, and


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thus plan and act accordingly (Lozano, 2013; Lozano and Huising, 2011). Few scholars have

inquired into potential quantitative methods for assessing the relative importance of the

different aspects of sustainability (Arena and Azzone, 2012; Hsu et al., 2013; Krajnc and

Glavic, 2005;). To respond to the methodological scarcity, the current paper proposes, applies

and examines a ‘fuzzy analytic hierarchy process’ (fuzzy AHP) method, involving multi-

criteria decision-making (MCDM) and fuzzy linguistic variables, to support companies in

defining the content of their sustainability report. The method offers advantages in terms of

accuracy, thoroughness and efficiency of reporting, as well as generalizability among

companies. The methodological integration of fuzzy variables serves to manage the

ambiguity and uncertainty of subjective judgments, typical in evaluating the ‘materiality’ of

the different sustainability issues (Chen and Fan, 2011). The method is based on the G4 GRI

Guidelines (GRI, 2013a, 2013b), currently in world-wide use. It allows the company to

determine the relative importance and utility of the different GRI ‘Aspects’ and ‘Indicators’

in assessing sustainability performance in environmental, economic and social areas.

Application of the fuzzy AHP method supports companies in the process of defining the

‘material’ content for sustainability reporting, permitting them to identify those GRI aspects

and indicators that better address their key sustainability concerns. The method should be

especially useful to SMEs, which often face time and financial constraints as they engage in

sustainability reporting (Baumann-Pauly et al., 2013), but supports all companies that wish to

‘make reports more relevant, more credible and more user-friendly’ (GRI, 2013a, p. 3).

The next section of the paper provides a brief review of the literature on sustainability

reporting and the GRI Guidelines. Section 3 reviews the theory of the fuzzy AHP approach

and develops the proposed method. Section 4 presents an application of the method to the

case of an Italian SME and Section 5 illustrates its usefulness as a tool to support

sustainability reporting. Finally, Section 6 summarizes and concludes the study.


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2. Literature review

2.1 Sustainability reporting

‘Sustainability reporting is the practice of measuring, disclosing, and being accountable to

internal and external stakeholders for organizational performance, towards the goal of

sustainable development’ (GRI, 2006, p. 3). Sustainability reporting has been the subject of

growing attention from policy makers, market regulators, stakeholders, managers and

academics, and thus the practice of reporting has increased significantly over the last two

decades (GRI, 2013c). The literature offers different theoretical and empirical explanations

concerning the motivations and drivers for sustainability reporting (Burritt and Schaltegger,

2010; Herzig and Schaltegger, 2011). Currently, the main approaches to the issue are

‘impression management theory’, ‘signaling theory’ and ‘legitimacy theory’(Dawkins and

Ngunjiri, 2008). In impression management theory, sustainability reporting is viewed as a

way to manage stakeholder perceptions, while under signaling theory, the company uses

reporting to ‘communicate company values’ (Hooghiemstra, 2000; Mahoney et al., 2013).

Legitimacy theory instead presents reporting as a way to face the increasing demands,

arriving from various actors, that companies must manage their impacts (Deegan, 2002).

Through sustainability reports, stakeholders can establish if a company’s activities are in line

with their values and expectations, and consequently approve or ‘disapprove’ of the actions.

Appropriate reporting enhances company-stakeholder relationships (Calabrese et al., 2013b)

and so contributes to processes for the creation of shared value, connecting society with

economic progress (Porter and Kramer, 2011).

In spite of the advantages, some companies can be inhibited from sustainability reporting due

to the added resources required for conforming to accountability procedures, both in finances

and the acquisition and training of competencies (Kolk, 2005). The company’s organizational

characteristics, such as its business model, cultural operating contexts, size and ownership,


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will affect sustainability practices and reporting (Adams, 2002; Belal and Copper, 2011;

Gamerschlag et al., 2011; Hahn and Kuhnen, 2013; Lepoutre and Heene, 2006; Meyskens

and Paul, 2010). A study by Baumann-Pauly, Wickert, Spence and Scherer (2013) reveals a

‘sustainability reporting gap’ relative to company size: large companies adopt strong

reporting, aiming to improve their image with the general public; SMEs tend to concentrate

their efforts at communication on their most important stakeholders, particularly employees,

adopting only informal mechanisms. For SMEs, the reporting gap derives primarily from a

lack of time and the specialized knowledge and financial resources necessary for appropriate

documentation of sustainability performance. The ‘reporting gap’ both contributes to and

derives from the low visibility of smaller companies.

SMEs are thus reluctant to adopt the existing international frameworks of standards for

sustainability practice and reporting (Kolk, 2005). Sustainability standards are a form of

voluntary accreditation and self-regulation, aimed at encouraging companies to adopt

systematic approaches to stakeholder engagement in sustainability practice, and at improving

comparability in performance (Ligteringen and Zadek, 2005). Koerber (2010) classifies

sustainability standards as: ‘ Normative Frameworks, Management Systems, and Process

Guidelines’. Normative Frameworks regulate performance and goals (e.g. OECD Guidelines

for Multinational Enterprises). Management Systems regulate the integration of social and

environmental issues with the company operations (e.g. Social Accountability SA8000).

Process Guidelines offer guidance on measurement, communication and assurance (e.g. GRI

Reporting Framework).

The method proposed in the current paper is based on the GRI Guidelines, which are the most

widely used framework for voluntary sustainability reporting (Marimon et al., 2012). The

following subsections provide a brief review of the G4 GRI Guidelines (GRI, 2013a, 2013b)


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and some of the advantages of this standard. Subsequently, we examine how their

implementation can be supported by a fuzzy AHP method.

2.2 GRI Sustainability Reporting Guidelines

The GRI Sustainability Reporting Guidelines combine reporting of financial and non-

financial information in a standardized framework, resulting in full characterization of the

company’s sustainability performance in the economic, environmental and social dimensions

(GRI, 2013a, 2013b).

The GRI Guidelines are appropriate for sustainability reporting regardless of company

dimension or industrial sector (Bouten et al., 2011). The guidelines offer companies a series

of potential advantages: they permit standardization in the contents of reporting and the

processes of implementation; they can improve stakeholder relationships; they permit

comparison to the practices and performance of other organizations (Fortanier et al., 2011;

Koerber, 2010; Schadewitz and Niskala, 2010). The guidelines are developed by multi-

stakeholder technical working groups, with the aim of obtaining flexibility and global

relevance. The guidelines are structured to elicit company reporting on both the positive and

negative effects of their activities, ensuring stakeholders a reasonable and balanced

representation of the sustainability practices and performance. Company use of the guidelines

enhances accountability, by taking into account the expectations and viewpoints of different

types of stakeholders about engagements in sustainability (Brown et al, 2009).

GRI Guidelines analyze sustainability issues not only in terms of negative impact reduction,

but also in terms of wealth creation and distribution. This characteristic ensures that

companies address ‘eco-efficiency’ (environmental impact) and ‘eco- justice’ (wealth creation

and distribution) issues, and consider future patterns of development (Bebbington, 2001).

The current paper applies the most recent generation of GRI Guidelines, known as ‘G4’

(GRI, 2013a, 2013b).


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2.2.1 The G4 framework

G4 considers sustainability performance under a framework of three ‘Categories’:

‘Economic, Environmental, Social’. The Social Category is further divided into four ‘Sub-

Categories’: Labor Practices and Decent Work, Human Rights, Society, and Product

Responsibility. The actual description of sustainability under the Categories and Sub-

Categories is accomplished by applying specific ‘Aspects’ and ‘Indicators’ (Table 1).

--------------------------------------------

INSERT TABLE 1 ABOUT HERE

-------------------------------------------

2.2.2 ‘M ateriality ’ in sustainabil ity reporti ng

The G4 Guidelines stress the importance of providing reports that are material to the

company’s business and stakeholders, meaning ‘centered on matters that are really critical in

order to achieve the organization’s goals and manage its impact on society’ (GRI, 2013a, p.

3). To accomplish this, the reports must deal with the specific GRI aspects and indicators that

are in turn material. An aspect is material if it has significant relevance to the company’s

economic, environmental and social impacts; an aspect is immaterial if it is not sufficiently

relevant (GRI, 2013a, 2013b). In addition, an aspect is deemed ‘not applicable’ when it is

completely unsuitable for describing the areas of company sustainability performance. In this

case it is excluded from the sustainability report, and the reasons for this decision must be

explained.

The objective of the so-called ‘Materiality Principle’ is to provide stakeholders with relevant,

complete and coherent information for the assessment of company performance. For this, the

G4 reporting guidelines recommend that companies prioritize the GRI aspects in terms of

their relative significance (materiality) in revealing sustainability performance. The

materiality principle must then also be applied to the indicators for the GRI aspects that are


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more significant: first the company must select the indicators that are material to measuring

the sustainability performance; second, the indicators must be prioritized. Finally, the report

should offer appropriate ‘levels of detail’, meaning combinations of indicators, quantitative

measures and narrative information suitable to the significance of each aspect judged as

material.

In the next section we propose a fuzzy AHP method to support companies in identifying the

GRI aspects and indicators that are more significant to disclosing the company’s

sustainability performance.

3. The fuzzy AHP method for decisions in sustainability reporting

The ‘analytic hierarchy process’ (AHP) is a structured technique for organizing and analyzing

complex decisions. It provides a comprehensive framework for structuring a decision-making

problem: representing and quantifying its elements, relating these elements to an overall goal.

AHP decomposes the overall problem into a hierarchy of readily comprehended sub-

problems and further items. The procedure permits the inclusion of both quantitative and

qualitative criteria in the evaluation process.

In this paper we adopt the ‘fuzzy’ extension of classic AHP, an approach that deals with the

vagueness or fuzziness of the linguistic and subjective judgments typically formulated in

decision-making processes (Chen and Fan, 2011). In sustainability reporting, such fuzziness

is characteristic of the stage in which company decision-makers must judge the GRI aspects

and indicators material to the disclosure of sustainability performance. We expect the fuzzy

AHP method to assist in the assessment of the relative significance of the GRI aspects and

indicators.

In the following subsections we explain fuzzy AHP in more detail and develop the method

for application to the problem at hand.


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3.1 AHP and fuzzy AHP

AHP is a decision-making approach used to arrive at solutions to complex multiple-criteria

problems involving qualitative judgements (Saaty, 1980). The process decomposes the

decision-making process into constituent parts, progressing from the general to the specific.

The problem is structured in hierarchical form, with the overall decision-making goal at the

top, above the lower levels of criteria and alternatives. Each criterion or sub-criterion can be

further divided into appropriate levels of detail. Finally, the decision alternatives or selection

choices are laid down at the last level of the hierarchy.

Decision-makers decompose their problem into the hierarchy, and then progressively judge

the importance of each criterion in paired comparisons. The judgement is performed from the

point of view of the next criterion up. The judgements score the decision alternatives, one

relative to another. The process includes consideration of subjective opinions, gathered by

direct questioning or questionnaires that reveal the necessary decision-making information

and the priority weighting of the elements. The AHP process thus captures both subjective

and objective criteria in decision-making, while providing an instrument for checking the

coherence of the decision-makers’ evaluations (Saaty, 1980).

Nevertheless AHP does not completely capture the peculiarities of qualitative assessment

because its discrete scale cannot reflect the true character of human thinking (Huang et al.,

2008). Given that expert preferences are almost universally affected by uncertainty and

imprecision, it is unrealistic to use definite and precise numbers to represent the entailing

linguistic judgments (Kwong and Bai, 2003). The ‘fuzzy AHP method’ provides a means to

deal with this ambiguity, by integrating ‘triangular fuzzy numbers’ (TFNs) and classic AHP

in a single process. The fuzzy AHP method is thus better suited to solving decision-making

problems concerning subjective evaluations.


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Fuzzy AHP converts linguistic judgments into TFNs, organized in fuzzy pair-wise

comparison matrices. Many methods of ‘comparison matrices’ have been introduced (e.g.

Chang, 1996; Csutora and Buckley, 2001), to obtain the relative weights of the decision items

(criteria, subcriteria and alternatives). Among others methods, the fuzzy extension of AHP

proposed by Chang (1996) is well known and widely applied. However Wang et al. (2008)

demonstrate that it can lead to incorrect prioritization, through assigning ‘zero weights’ to

some decision items and thus excluding them from the analysis. To avoid this shortcoming

we adopt a fuzzy AHP approach proposed by Calabrese et al. (2013a), which resolves the

zero weight issue, taking into account Wang et al.’s (2008) criticisms of Chang’s method and

the consistency test of Kwong and Bay (2003). The following section details how the general

fuzzy AHP method can be applied to the particular problem of judging the materiality of GRI

aspects and indicators.

3.2 The hierarchical structure for identifying ‘materiality’

As described, fuzzy AHP structures complex decisions as a hierarchy, from the overall

objective at the top to criteria, subcriteria, and downwards to lower levels. Moreover the

hierarchical structure of fuzzy AHP remains flexible, permitting different levels of detail to

reflect the peculiarities of each decision problem.

In this case, to take account of the multi-dimensional nature of company sustainability

performance (economic, environmental and social dimensions), we propose a model

consisting of three hierarchical structures of criteria and subcriteria. The GRI sub-categories,

aspects and indicators are organized in three separate hierarchies, in keeping with the three

sustainability categories of the G4 Guidelines. At the top level of the hierarchical structures is

the goal of each analysis. Each goal is formulated in terms of deciding the more significant or

‘material’ aspects and indicators, relevant to the three dimensions of sustainability

(economic, environmental, social) as identified in the GRI guidelines:


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Economic Goal ‒ The goal of the economic hierarchy is to assess the level of

significance of the GRI aspects and indicators of the economic category, deciding

those aspects that best reflect the company’s economic impacts and the indicators that

best allow assessment of its economic sustainability performance. Economic impacts

can be direct and indirect. The direct ones result from company economic activities,

transactions and interactions in specific markets. Indirect impacts are those that have

an indirect effect on stakeholders, such as investments that are realized for broader

public benefit (GRI, 2013a, 2013b);

Environmental Goal ‒ The goal of the environmental hierarchy is to assess the level

of significance of the GRI aspects and indicators of the environmental category,

deciding those aspects that best reflect the company’s environmental impacts and the

indicators that allow assessment of its environmental sustainability performance. The

environmental impacts refer to those caused by the inputs and the outputs of company

processes: energy and water consumption, gas emissions, biodiversity protection,

waste recycling, sustainability in transport, and disposal of products and materials

(GRI, 2013a, 2013b);

Social Goal ‒ The goal of the social hierarchy is to assess the level of significance of

the GRI aspects and indicators of the social category, deciding those aspects that best

reflect the company’s social impacts and the indicators that allow assessment of its

social sustainability performance. Social impacts concern the effects of company

activities on social systems: work practices, respect of human rights, public policy,

consumer health and safety protection (GRI, 2013a, 2013b).

Under each goal are structured the related GRI aspects, with the next level down being the

GRI indicators (Figures 1, 2, 3). The social hierarchical structure presents a further level of

criteria corresponding to the GRI ‘Social Sub-Categories’.


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---------------------------------------------------

INSERT FIGURES 1, 2, 3 ABOUT HERE

---------------------------------------------------

3.3 Conversion of decision-maker judgments to relative weights

Given the proposed hierarchical structures (Figures 1, 2, 3), decision-makers can now be

asked to compare the relevance of GRI aspects and indicators, in pair-wise comparisons,

under the economic, environmental and social goals of the analysis.

The decision-makers judge the relative importance of the items in a pair by means of

linguistic terms: ‘equally’, ‘weakly more’, ‘moderately more’, ‘strongly more’ or ‘extremely

more important’. The linguistic judgments are then converted into triangular fuzzy numbers

(TFNs) using the scale shown in Table 2.

---------------------------------------------------


---------------------------------------------------

The TFNs are organized in fuzzy comparison matrices (1):

12 12 12 1 1 1

21 21 21 2 2 2

1 1 1 2 2 2

(1,1,1) ( , , ) ( , , )

( , , ) (1,1,1) ( , , )

( , , ) ( , , ) (1,1,1)

n n n

n n nij n n

n n n n n n

l m u l m u

l m u l m u A a

l m u l m u

(1)

where

1 1 1 1( , , ) ( ) , , , , 1,... ;ij ij ij ij ji

ji ji ji

a l m u a i j n i ju m l

(2)

is a TFN that represents the linguistic judgment for the items i with respect to j performed

from the perspective of the next criterion up. A is a square, symmetrical matrix.


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The fuzzy AHP method proposed by Calabrese et al. (2013a) is then applied to each

comparison matrix (steps 1 to 4, below), thus identifying the relative weights of the GRI

aspects and indicators, without the problem of zero weights.

Step 1. Convert the fuzzy comparison matrix (1) into a crisp comparison matrix using the

centroid defuzzification method called ‘center of gravity’ (Yager, 1981). In the case of TFNs

the translating formula is (Wang and Elhang, 2007):

( ) , , 1,...,3

ij ij ijij ij

l m ua a i j n

(3)

Step 2. Analyze the consistency of the comparison matrix by calculating the consistency

index (CI ) and the consistency ratio (CR):

max( )

1

nCI

n

(4)

100%CR CI RI n (5)

where max is the largest eigenvalue of the comparison matrix, n is the dimension of the

matrix and RI (n) is a random index depending on n as shown in Table 3.

---------------------------------------------------


---------------------------------------------------

Usually, the consistency of the matrix is acceptable only if CR (5) is less than 10% (Forman,

1990). However the threshold of 10% can be reduced or increased depending on the tolerance

of the decision-makers (Alonso and Lamata, 2006). If a matrix results as inconsistent, new

pair-wise comparison judgments must be obtained, for preparation of a new pair-wise fuzzy

comparison matrix and a repeat analysis. The matrix review must be continued until

consistency is obtained.


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Step 3 . Determine the local priority weight of each criterion, sub-criterion and alternative by

summing up each row of the consistent fuzzy comparison matrix A (6) and then normalizing

the row sums to obtaini

S by means of (7).

1 1 1 1

( , , ), 1,...,n n n n

i ij ij ij ij j j j j

RS a l m u i n

(6)

1 1 1

1 1, 1 1, 1 1 1, 11

, , ( , , ), 1,...,

n n n

ij ij ij j j ji

i i i in n n n n n n nn

ij kj kj ij kj j j k k i j k j j k k i j j

l m u RS

S l m u i n

l u m u l RS

(7)

Finally, the crisp weights are calculated converting fuzzy weights as follows:

( ) , 1,...,3

i i ii i i

l m uw S S i n

(8)

Via normalization, the normalized crisp weight vector is:

1 2( ', ',..., ') nW w w w (9)

Step 4. Aggregate local priority weights into global priorities: the rank of each sub-criterion

is calculated by multiplying its local weight with the corresponding local weights of

subcriteria and criteria along the hierarchy. The global weights of criteria in the upper level

hierarchy are equivalent to the local weights.

In case of participation by two or more decision-makers, for each hierarchical level the

evaluating process results in different comparison matrices, one for each decision-maker.

Before applying the steps 1-4, it is then necessary to synthesize these in a single aggregate

matrix, as follows (Chang, 1996; Wang and Elhag, 2007):

If( ) ( ) ( ) ( )( , , )k k k k ij ij ij ija l m u (10)

is the triangular fuzzy number which expresses the linguistic judgment provided by the k-th

decision-maker ( 1,...,

k m ) and


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( ) 1

( ) ( ) ( )

1 1 1( ) , ,

k ij k k k

ij ij ij

au m l

(11)

is the reciprocal of( )k

ija . The average judgment, according to the fuzzy addition operation

for TFNs (Kaufmann and Gupta, 1991) is:

( ) ( ) ( ) ( )

1 1 1 1

1 1 1 1, , , , 1,..., ;

m m m mk k k k

ij ij ij ij ijk k k k

a a l m u i j n j im m m m

(12)

The previous aggregate matrix is then utilized as input in the steps 1-4.

4. A case study of an Italian SME

In this paper we apply the proposed fuzzy AHP method to the case of ACMO Group SpA, an

Italian SME operating in design, manufacturing and consulting for water projects and

hydraulic components. ACMO is certificated under ISO 14001:2000 (Environmental

Management System) and ISO 9001:2008 (Quality Management Systems), indicating that the

company is committed to corporate responsibility and deeply oriented towards its

stakeholders. The direction of ACMO is interested in implementing appropriate reporting to

further improve company accountability for performance in sustainability, but has never

prepared a sustainability report, making this an ideal case to illustrate the proposed method.

4.1 Implementing the fuzzy AHP method

The process of defining the sustainability report content is carried out through face-to-face

interviews with the expert decision-makers of the concerned company, particularly the top

managers (GRI, 2013). When the company is an SME, it is especially important to engage the

CEO in planning the content, because of his or her deep understanding of the company’s

organizational structure, processes and resources. In the case of ACMO, the interviews were

conducted with the company owner, who is also CEO.


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To begin the AHP procedure, the interviewee(s) must first be asked to judge the

‘applicability’ of all the GRI aspects and indicators (see Table 1), excluding those not

suitable to the assessment of sustainability performance for that company. The reasons for the

exclusions must later be explained in the sustainability report. In this case study, the company

CEO judged all GRI aspects and indicators as applicable.

Then, applying the three hierarchies (Figures 1, 2, 3), the interviewee is asked to express the

relative ‘material’ importance of the GRI aspects by means of pair-wise comparisons, under

the different sustainability dimensions of the analysis: the economic, environmental

categories and social subcategories. Since the social hierarchy (Figure 3) includes the extra

level of the social subcategories, for this hierarchy it is first necessary to compare the

subcategories under the perspective of the broad social category before arriving at the still

lower level of the GRI aspects.

For brevity, Table 4 shows only the example of answers from ACMO’s CEO about the

relative importance of the GRI aspects under the ‘Environmental’ category, where the GRI

aspect of ‘Water’ is one of the terms of comparison. In the full implementation of the method,

all the material GRI aspects must be evaluated in pair-wise comparisons: in the ACMO case

there are a total of 12 material GRI aspects (Table 1) and 66 pair-wise comparisons. As an

illustrative example, the first comparison of Table 4 is between the GRI aspects ‘Water ’ and

‘Materials’, applying the following question:

-----------------------------------------------------


-----------------------------------------------------

The respondent expresses the relative importance by means of linguistic terms (Table 4).


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Once the GRI aspects are examined, the analysis proceeds with the evaluation of the relative

importance of the GRI indicators. As an example, Table 5 shows the comparison between the

GRI indicators under the ‘Water ’ aspect. The first comparison is between the GRI indicators

G4-EN8 (total water withdrawal by source) and G4-EN9 (water sources significantly affected

by withdrawal of water), applying the following question:

< In the perspective of the GRI Aspect ‘Water’, to what extent is the indicator G4-EN8 more

(or less) significant than the indicator G4-EN9 in describing, monitoring and analyzing the

environmental sustainability performance of the company?>

For brevity we again present only one table describing the comparison of the GRI indicators,

however the fuzzy AHP method requires elaboration of a comparison table for each of the

material GRI aspects considered (Table 1). In the ACMO case study, all GRI Aspects were

deemed applicable and 46 tables were necessary.

-----------------------------------------------------


-----------------------------------------------------

As an example of collecting and elaborating the data, Table 6 shows the conversion of the

Table 5 linguistic judgments into TFNs, applying the conversion scale in Table 2.

-----------------------------------------------------


-----------------------------------------------------

The fuzzy AHP method then continues, step by step.

Step 1 . Using formula (3) the fuzzy comparison matrix (Table 6) is converted into a crisp

comparison matrix (Table 7).

-----------------------------------------------------


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Step 2. The consistency of the crisp matrix is analyzed: in this example the matrix (Table 7)

is consistent with CI=0.034 and CR=0.06.

Step 3. The row sum (6) and the normalized row sum (7) are calculated for each GRI

indicator associated with a row of Table 7. In particular, the value of the row sum for the

indicator G4-EN8 is calculated using (6) as follows:

1 (1,1,1) (1,1.5,2) (0.33,0.4,0.5) (2.33,2.9,3.5) RS

The row sum values for the GRI indicators belonging to ‘Water’ are summarized in Table 8.

-----------------------------------------------------


---------------------------------------------

The normalized row sum value for the indicator G4-EN8 is calculated utilizing (7) as follows:

1 1 11

1 1, 1 1, 1 1 1, 11

2.33 2.9 3.5, , , ,1

11.83 10.97 10.33

(0.1969, 0.2644, 0.3388)

n n n

ij ij ij j j j

n n n n n n n nn

ij kj kj ij kj j j k k i j k j j k k i j j

l m u RS

l u m u l RS

S

The normalized row sum values for GRI indicators under ‘Water ’ are summarized in Table 9.

------------------------------------------------------


-----------------------------------------------------

Then crisp weights are calculated using (8), and via normalization, the relative weights for

the GRI Indicators belonging to ‘Water ’ are:

The same procedure must be applied to all comparison matrices relative to the GRI aspects of

the environmental category (see Figure 2).

Step 4 . The overall results (global weights) of the ‘Environmental Category’ (Table 10) are

obtained by multiplying the relative weights of the GRI aspects and indicators along the


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hierarchy. For example, the global weight of G4-EN8 (2.6%) is obtained from multiplying

the global weight of the ‘Water ’ aspect (10%) by the local weight of G4-EN8 (26%).

-----------------------------------------------------


-----------------------------------------------------

To complete the case study, the fuzzy AHP method is repeated for the GRI ‘Economic’ and

‘Social’ categories. The overall results are shown in the Appendix, Tables A.1, A.2, A.3.

4.2 Results

For brevity, we will discuss the results obtained for only one of the three categories of GRI

sustainability reporting aspects. Figure 4 presents the global weights calculated for the

environmental aspects (Table 10), for ACMO SpA. They express the relative materiality of

the different GRI aspect in assessing the company’s sustainability performance in the

environmental area. In this case, the most significant (material) GRI aspects are ‘Effluents

and Waste’ (13%) and ‘Overall’ (11%). Slightly below this, with the equal scores of 10%, are

‘Materials’, ‘Water ’, ‘Emissions’, ‘Product and Services’ and ‘Supplier Environmental

Assessment’. The ‘Compliance’ aspect receives the lowest score, and is thus the least

significant for this company (4%).

-----------------------------------------------------

INSERT FIGURE 4 ABOUT HERE

-----------------------------------------------------

From the analysis, the CEO’s answers suggest that the most important factors in ACMO’s

environmental sustainability performance are the methods and management of water

discharge and waste disposal (GRI aspect ‘Effluents and Waste’). ACMO’s commitment to

reducing environmental impact is witnessed in the high weight for the GRI aspect ‘Overall’,

which deals with expenditures on environmental protection. The fact that five further GRI

aspects score a relative significance of 10% show that ACMO is uniformly committed to a


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series of production practices for sustainability, corresponding to the GRI aspects concerning

materials recycling, emissions reduction, mitigation of product and service impacts, and

screening the supply chain. On the basis of these results, ACMO should focus its reporting on

sustainability performance on all practices that enhance the company’s production efficiency

and minimize environmental impacts, as indicated. These correspond to the specific GRI

aspects: Effluents and Waste, Materials, Water, Emissions, Product and Services and

Supplier Environmental Assessment.

Figure 5 shows the ranking of the detailed GRI indicators entering under the above GRI

aspects of the environmental category, again for the case of ACMO SpA.

-----------------------------------------------------

INSERT FIGURE 5 ABOUT HERE

-----------------------------------------------------

For example under aspect ‘Effluents and Waste’, the ACMO’s CEO considers G4-EN22

(‘total water discharge by quality and destination’, with relative significance 3.22%) as the

GRI indicator most significant in describing the company water discharge performance.

Reflecting this result, the section of the ACMO sustainability performance report dealing

with the ‘Effluents and Waste’ aspect should stress indicator G4-EN22.

The high relative importance given by ACMO’s CEO to the ‘Overall’ environmental aspect,

and under this, G4-EN31 (total environmental protection expenditures and investments),

means this is another indicator that should be described fully in the sustainability report.

Under the environmental aspect of ‘Materials’, indicators G4-EN1 and G4-EN2 have the

same relative importance. For this reason, ACMO’s sustainability report should describe both

of these indicators with roughly the same emphasis and thoroughness, in order to capture the

company sustainability performance with respect to the relatives subjects (material used for

producing and packaging products and services; percentage of materials recycled). Among

the indicators under the ‘Water ’ aspect, G4-EN10 is the most significant (5%) and


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accordingly, for this aspect, ACMO’s sustainability report should focus on the percentage and

total volume of water recycled and reused.

Furthermore, to describe the environmental impacts related to ‘Emissions’, the ACMO’s

CEO considers G4-EN19 (reduction of greenhouse gas emissions) as the most important

(1.9%) of the seven possible indicators for reporting. This ranking in fact reflects the

subjective opinion of the CEO, who stresses that the company takes a proactive attitude

concerning the reduction of greenhouse gases resulting from its productive processes.

To monitor sustainability performance under ‘Product and Services’, the identification of

‘extent of impact mitigation of environmental impacts of products and services’ (G4-EN27)

is more relevant than the other possible indicator, of ‘ percentage of products sold and their

packaging materials that are reclaimed’ (G4-EN28). The company CEO considers the first

indicator (G4-EN27) as more significant, because it allows describing the impact of products

and services in a more comprehensive way.

In terms of the aspect ‘Supplier environmental assessment’, there are two possible indicators.

Here, the ACMO’s CEO has indicated G4-EN32 (percentage of new suppliers screened using

environmental criteria) as more important than G4-EN33, which reports on series of impacts

involving the company supply chain and actions. Based on these results, it appears that the

CEO considers new suppliers as presenting important risks and possibilities for sustainability

action, making reporting on their screening more significant than reviewing the entire chain.

Figure 5 also shows the ranking of the remaining indicators, for the GRI aspects of the

environmental category that ACMO’s CEO considers of lesser significance.

The company should use the outcomes from the fuzzy AHP method (as summarized in Figure

5 for the environmental category) to achieve more effective and efficient sustainability

reporting. By focusing on the most significant aspects and indicators, as indicated by the

analyses for all three GRI categories, ACMO can focus its sustainability reporting on topics


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material to its business and stakeholders. It can achieve reports that matter, containing

information about its most critical sustainability issues, while spending less resources in time,

money and expertise to carry out the actual reporting tasks.

5. Managerial implications for sustainability reporting

The proposed fuzzy AHP method offers a guide to companies in identifying the appropriate

content for preparation of their sustainability reports, in terms of the priority to place on the

different GRI ‘Aspects’ and ‘Indicators’. The fuzzy AHP method indicates the relative

importance of the different aspects and their indicators in assessing company performance. In

keeping with the GRI reporting guidelines, each aspect must be described with a level of

accuracy corresponding to its level of importance. The most significant aspects should be

analyzed not only in qualitative terms, but also through presentation of quantitative

information. Under the GRI aspects, the prioritization of the indicators using fuzzy AHP

identifies the more suitable ones to report the sustainability performance for the issues of

concern. The higher is the relative importance of an indicator, the more attention should be

paid to its reporting, for example through analysis of quantitative information, time series and

trends.

For instance in the case study of the SME, ACMO SpA, the fuzzy AHP analysis points to

G4-EN22 as the highest priority indicator under the ‘Effluents and Waste’ aspect. In

reporting on this aspect, ACMO would then be advised to disclose detailed information on

G4-EN22, for example enumerating the total volume of water discharges by destination and

over different periods, as well as giving the procedures for these calculations. However for

the same GRI aspect, G4-EN24 is less significant than G4-EN22, and in this case ACMO can

report in less detail: for example disclosing preventive measures, or identifying the number

and volume of spills should any occur over the reporting period.


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The proposed fuzzy AHP method also serves in planning performance reporting in a further

way. In particular, it permits the company to identify of a threshold percentage of

significance, below which it will consider GRI indicators or the higher level of aspects as

‘immaterial’, or irrelevant to sustainability reporting. For this purpose, we define the variable

‘Completeness’ that is calculated as the sum of the global weights of all the indicators whose

level of priority is greater than or equal to the one considered. For example in the ACMO

case, referring to Figure 5, the indicators whose global weights are to be summed are the ones

on the left of the indicator under analysis, plus that indicator itself. The priority levels for the

indicators are established applying two rankings. The first is on the basis of the aspect

ranking: continuing the example of Figure 5, the ‘Water’ aspect ranks higher than

‘Emissions’, therefore the group of ‘Water ’ indicators score higher in priority than those for

‘Emissions’. Second, the indicators are ranked within their aspect: again in Figure 5, among

the group of ‘Water ’ indicators, G4-EN10 has a higher priority than G4-EN8. Examining

Figure 5, we see that ACMO could choose to achieve a level of Completeness of

approximately 81%, which would be accomplished by selecting GRI indicator G4-EN30 and

all the indicators and aspects to its left. As described in the paragraphs above, the company

would then report on the selected material aspects and indicators with a level of accuracy

corresponding to the level of priority (significance).

For ACMO, all GRI indicators and aspects with a level of priority lower than that of G4-

EN30 would then be ‘not relevant’ (immaterial). These would not be described in the

sustainability report, instead being noted only with a short explanation of omission. For

example, the lowest ranked GRI aspect is ‘Compliance’, which deals with fines and sanctions

for non-compliance to environmental laws and regulations. In subjective opinion, the

ACMO’s CEO considers the fact that the company is free of sanctions as not relevant in

reporting sustainability performance, because the Italian water technology industry is in any


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case characterized by very low frequency of sanctions for environmental violations.

Similarly, at the level of the indicators under ‘Compliance’, G4-EN29 (total numbers of fines,

sanctions, cases subjected to resolution) is deemed not relevant to describing ACMO SpA’s


Obviously, the maximum level of Completeness in sustainability reporting (100%) could be

obtained by detailing all GRI aspects and indicators. However, higher levels of Completeness

require that the company commit to engaging greater resources in the implementation of

reporting. The ex-ante choice of a level of engagement is particularly important in the case of

companies with limited resources, such as is typical for SMEs. In this regard, the fuzzy AHP

method offers a tool to assist SMEs in planning reporting levels, and then further tools to

obtain properly balanced reporting on the ‘material’ aspects and indicators, thus optimizing

the time and resources needed to collect the information for disclosing the company


6. Conclusions

The purpose of a company’s sustainability report is to disclose information on its critical

economic, environmental and social impacts. Reporting on sustainability performance must

disclose appropriate levels of information on those aspects that are truly affected by company

activities, because not all sustainability issues have the same relevance for every company

(ISO, 26000; GRI, 2013a, 2013b). The current paper presents a fuzzy AHP method that

supports companies in the identification of the most appropriate areas and levels of content to

be included in their sustainability reports.

The method involves face-to-face interviews with the company’s expert decision-makers

(CEO, top managers) to collect linguistic judgments that feed in to a specifically developed

fuzzy AHP method. The method deals with the imprecision and ambiguity typical of


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linguistic judgments, and elaborates them to support informed decision-making in the

planning of sustainability reporting. The paper presents a case study to illustrate the

implementation of the method, applied to an Italian SME operating in the water technology

industry.

The method is based on the G4 GRI Sustainability Reporting Guidelines. It prioritizes the

GRI aspects and indicators in terms of their significance for reporting the company’s

sustainability performance. The level of priority of each aspect or indicator is used to identify

the type and degree of detail necessary for the sustainability report (e.g. quantitative

information, time series, trends). Using the fuzzy AHP method, company managers also

define a threshold of significance, below which GRI aspects and indicators will be excluded

from reporting, due not being relevant (not ‘material’).

The ex-ante choice of a level of completeness is particularly important for companies with

limited resources to dedicate to reporting activities, such as is typical for SMEs. The

proposed fuzzy AHP method is a tool that can assist SMEs in their sustainability reporting,

by focusing and reducing the tasks of data collection and report preparation. The method

makes sustainability reporting more feasible for the many SMEs that do not yet provide

formal, fully-structured reports. For those companies engaged in sustainability reporting, the

method serves to improve relevance and precision, while containing costs in terms of time

and resources.

Acknowledgments

We especially thank Paolo Sebastiani (ACMO’s CEO) and Costanza Sebastiani for their

contribution in the realization of the case study.


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References

Adams, C.A., 2002. Internal organizational factors influencing corporate social and ethical

reporting: beyond current theorizing. Accounting, Auditing & Accountability Journal,

15(2), 223-50.

Alonso, J.A., Lamata M.T., 2006. Consistency in the analytic hierarchy process: a newapproach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems,

14(4), 445−459.

Arena, M., Azzone, G., 2012. A process-based operational framework for sustainability

reporting in SMEs. Journal of Small Business and Enterprise Development , 19(4), 669-

686.

Baumann-Pauly, D., Wickert, C., Spence, L.J., Scherer, A.G., 2013. Organizing corporate

social responsibility in small and large firms: size matters. Journal of Business

Ethics , 115(4), 693-705.

Bebbington, J., 2001, June. Sustainable development: a review of the international

development, business and accounting literature. Accounting Forum, 25 (2), 128-157.

Blackwell Publishers Ltd.Belal, A.R., Cooper, S., 2011. The absence of corporate social responsibility reporting in

Bangladesh. Critical Perspectives on Accounting, 22(7), 654-667.

Birth, G., Illia, L., Lurati, F., Zamparini, A., 2008. Communicating CSR: practices among

Switzerland's top 300 companies. Corporate Communications: An International

Journal, 13(2), 182-196.

Bouten, L., Everaert, P., Van Liedekerke, L., De Moor, L., Christiaens, J., 2011, September.

Corporate social responsibility reporting: a comprehensive picture?. Accounting

Forum, 35 (3), 187-204.

Brown, H.S., de Jong, M., Levy, D.L., 2009. Building institutions based on information

disclosure: lessons from GRI's sustainability reporting. Journal of Cleaner

Production, 17(6), 571-580.Burritt, R. L., Schaltegger, S., 2010. Sustainability accounting and reporting: fad or

trend?. Accounting, Auditing & Accountability Journal, 23(7), 829-846.

Calabrese, A., Costa, R., Menichini, T., 2013a. Using fuzzy AHP to manage intellectual

capital assets: an application to the ICT service industry. Expert Systems with

Applications, 40(9), 3747-3755.

Calabrese, A., Costa, R., Menichini, T., Rosati, F., 2013b. Does corporate social

responsibility hit the mark? A stakeholder oriented methodology for CSR

assessment. Knowledge and Process Management, 20(2), 77-89.

Chang, D.Y., 1996. Application of extend analysis method on fuzzy AHP. European Journal

of Operational Research , 95(3), 649-655.

Chen, S., Fan, J., 2011. Measuring corporate social responsibility based on a fuzzy analyticalhierarchy process. I.J. Computer Network and Information Security, 5, 13-22.

Csutora, R., Buckley, J.J., 2001. Fuzzy hierarchical analysis: the Lambda-Max

method. Fuzzy sets and Systems , 120(2), 181-195.

Dawkins, C., Ngunjiri, F.W., 2008. Corporate social responsibility reporting in South Africa,

a descriptive and comparative analysis. Journal of Business Communication, 45(3), 286-

307.

Deegan, C., 2002. Introduction: the legitimising effect of social and environmental

disclosures – a theoretical foundation. Accounting, Auditing & Accountability

Journal, 15(3), 282-311.Forman, E.H., 1990. Random indices for Incomplete Pairwise Comparison Matrices.

European Journal of Operational Research , 48(1), 153-155.


31/50

1

2

3

4

5

67

8

9

10

11

12

13

14

15

16

17

18

1920

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

27

Fortanier, F., Kolk, A., Pinkse, J., 2011. Harmonization in CSR reporting. Management

International Review, 51(5), 665-696.

Gamerschlag, R., Möller, K., Verbeeten, F., 2011. Determinants of voluntary CSR disclosure:

empirical evidence from Germany. Review of Managerial Science, 5, 233-262.

GRI-Global Reporting Initiative, 2006. G3.1, Sustainability Reporting Guidelines, available

at: www.globalreporting.org GRI-Global Reporting Initiative (2013a). G4, Part1, Reporting Principles and Standard

Disclosure, available at: www.globalreporting.org.

GRI-Global Reporting Initiative (2013b). G4, Part2, Implementation Manual,

available at: www.globalreporting.org.

GRI-Global Reporting Initiative, 2013c. Sustainability Reporting Policies Worldwide,

available at: www.globalreporting.org.

Hahn, R., Kühnen, M., 2013. Determinants of sustainability reporting: a review of results,

trends, theory, and opportunities in an expanding field of research. Journal of Cleaner

Production, 59, 5-21.

Herzig, C., Schaltegger, S., 2011. Corporate sustainability reporting, in: Godemann J.,

Michelsen G. (Eds.), Sustainability Communication. Springer, Netherlands, pp.151-169.

Hooghiemstra, R., 2000. Corporate communication and impression management: new

perspectives why companies engage in corporate social reporting. Journal of Business

Ethics, 27(1-2), 55-68.

Hsu, C.W., Lee, W.H., Chao, W.C., 2013. Materiality analysis model in sustainability

reporting: a case study at Lite-On Technology Corporation. Journal of Cleaner

Production, 57, 142-151.

Huang, C.C., Chu, P.Y., Chiang, Y.H., 2008. A fuzzy AHP application in government-

sponsored R&D project selection. Omega, 36(6), 1038-1052.

ISO - International Organization for Standardization, 2010. Guidance on Social

Responsibility - ISO 26000:2010(E). Geneva.Kaufmann, A., Gupta, M.M., 1991. Introduction to Fuzzy Arithmetic: Theory and

Applications, VanNostrand Reinhold, New York.

Koerber, C.P., 2010. Corporate responsibility standards: current implications and future

possibilities for peace through commerce. Journal of Business Ethics , 89, 461-480.

Kolk, A., 2005. Sustainability reporting. VBA Journal , 21(3), 34-42.

Kolk, A., 2008. Sustainability, accountability and corporate governance: exploring

multinationals' reporting practices. Business Strategy and the Environment, 17(1), 1-15.

Krajnc, D., Glavič, P., 2005. How to compare companies on relevant dimensions of

sustainability. Ecological Economics , 55(4), 551-563.

Kwong, C.K., Bai, H., 2003. Determining the importance weights for the customer

requirements in QFD using a fuzzy AHP with an extent analysis approach. IIETransactions, 35(7), 619-626.

Lee, S.H., 2010. Using fuzzy AHP to develop intellectual capital evaluation model for

assessing their performance contribution in a university. Expert Systems with

Applications, 37(7), 4941-4947.

Lepoutre, J., Heene, A., 2006. Investigating the impact of firm size on small business social

responsibility: a critical review. Journal of Business Ethics, 67(3), 257-273.

Ligteringen, E., Zadek, S., 2005. The future of corporate responsibility codes, standards and

frameworks, available at: www.globalreporting.org.

Lozano, R., 2013. Sustainability inter-linkages in reporting vindicated: a study of European

companies. Journal of Cleaner Production, 51, 57-65.

Lozano, R., Huisingh, D., 2011. Inter-linking issues and dimensions in sustainabilityreporting. Journal of Cleaner Production, 19(2), 99-107.

http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/http://www.globalreporting.org/


32/50

1

2

3

4

5

67

8

9

10

11

12

13

14

15

16

17

18

1920

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

28

Mahoney, L.S., Thorne, L., Cecil, L., LaGore, W., 2013. A research note on standalone

corporate social responsibility reports: signaling or greenwashing?. Critical Perspectives

on Accounting, 24(4), 350-359.

Marimon, F., Alonso-Almeida, M.D.M., Rodríguez, M.D.P., Cortez Alejandro, K.A., 2012.

The worldwide diffusion of the global reporting initiative: what is the point?. Journal of

Cleaner Production, 33, 132-144.Meyskens, M., Paul, K., 2010. The evolution of corporate social reporting practices in

Mexico. Journal of Business Ethics, 91(2), 211-227.

Porter, M.E., Kramer, M.R., 2006. Strategy and society: the link between competitive

advantage and corporate social responsibility. Harvard Business Review, 84(12), 78-92.

Porter, M.E., Kramer, M.R., 2011. Creating shared value. Harvard Business Review , 89(1/2),

62-77.

Robinson, J., 2004. Squaring the circle? Some thoughts on the idea of sustainable

development. Ecological Economics, 48(4), 369-384.

Saaty, T.L., 1980. The Analytic Hierarchy Process , McGraw-Hill, New York.

Schadewitz, H., Niskala, M., 2010. Communication via responsibility reporting and its effect

on firm value in Finland. Corporate Social Responsibility and Environmental

Management , 17, 96-106.

Schmeltz, L., 2014. Introducing value-based framing as a strategy for communicating

CSR. Social Responsibility Journal, 10(1), 184-206.

Wang, Y.M., Elhag, T.M.S., 2007. A fuzzy group decision making approach for bridge risk

assessment. Computer & Industrial engineering , 53(1) , 137-148.

Wang, Y.M., Luo, Y., Hua, Z., 2008. On the extent analysis method for fuzzy AHP and its

applications. European Journal of Operational Research , 186 (2), 735-747.

Yager, R.R., 1981. A procedure for ordering fuzzy subsets of unit interval. Information

Sciences, 24, 143-161.


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Figure 1: Hierarchical structure of GRI aspects and indicators of the economic category.

Assessing the significance of GRI aspects and indicators of the economic category

EconomicPerformance

G4-EC1

G4-EC2

G4-EC3

G4-EN4

Market Presence

G4-EC5

G4-EC6

Indirect EconomicImpacts

G4-EC7

G4-EC8

Procurement Practices

G4-EC9

re


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Figure 2: Hierarchical structure of GRI aspects and indicators of the environmental category.

Assessing the significance of GRI aspects and indicators of the environmental category

Materials

G4-EN1

G4-EN2

Energy

G4-EN3

G4-EN4

G4-EN5

G4-EN6

G4-EN7

Water

G4-EN8

G4-EN9

G4-EN10

Biodiversity

G4-EN11

G4-EN12

G4-EN13

G4-EN14

Emissions

G4-EN15

G4-EN16

G4-EN17

G4-EN18

G4-EN19

G4-EN20

G4-EN21

Effluents andWaste

G4-EN22

G4-EN23

G4-EN24

G4-EN25

G4-EN26

Products andServices

G4-EN27

G4-EN28

Compliance

G4-EN29

Transport

G4-EN30

Overall

G4-EN31

SupplierEnvironmental

Assessment

G4-EN32

G4-EN33


Mechanisms

G4-EN34


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Figure 3: Hierarchical structure of GRI aspects and indicators of the social category.

Assessing the significance of GRI aspects and indicators of the social category

Labor Practicesand Decent Work

Employment

Labor ManagementRelations

Occupational Healthand Safety

Training andeducation

Diversity and

Equal Opportunity

Equal Remunerationfor Women and Men

Supplier Assessment

for Labor Practices

Labor PracticesGrievance

Mechanisms

Human Rights

Investment

Non-discrimination

Freedom of

Association andCollective argaining

Child Labor

Forced andCompulsoryLabor

SecurityPractices

IndigenousRights

Assessment

Human RightsGrievanceMechanisms

Supplier HumanRights Assessment

Society

Local

Communities

Anti-Corruption

Public Policy

Anti-competitiveBehavior

Compliance

Supplier Assessment

for Impacts on Society

Grievance

Mechanisms

for Impacts on Society

Product Responsibility

Customer Healthand Safety

Product andService Labeling

MarketingCommunications

CustomerPrivacy

Compliance

G4-LA1G4-LA2

G4-LA3

G4-LA4

G4-LA5

G4-LA6 G4-LA7

G4-LA8

G4-LA9

G4-LA10

G4-LA11

G4-LA12

G4-LA13

G4-LA14G4-LA15

G4-HR1

G4- HR2

G4-HR3

G4-HR4

G4-HR5

G4-HR6

G4-HR7

G4-HR8

G4-HR9

G4-HR10

G4- HR11

G4-HR12

G4-SO1G4- SO2

G4-SO3G4-SO4

G4-SO5

G4-SO6

G4-SO7

G4-SO8

G4-SO9

G4-SO10

G4-SO11

G4-PR1G4- PR2

G4-PR3G4-PR4

G4-PR5

G4-PR6G4-PR7

G4-PR8

G4-PR9

G4-LA16


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Figure 4: Level of significance (materiality) of GRI aspects under the environmental category.

10%

5%

10%

5%

10%

13%10%

4%

7%

11%

10%

5%

Materials

Energy

Water

Biodiversity

Emissions

Effluents and Waste

Products andServices

Compliance

Transport

Overall

Supplier

EnvironmentalAssessment


Mechanisms


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Environmental Aspect Description Environmental Aspect Description

ENA1 Effluents and Waste ENA7 Supplier Environmental Assessment

ENA2 Overall ENA8 Transport

ENA3 Materials ENA9 Energy

ENA4 Water ENA10 Biodiversity

ENA5 Emissions ENA11 Environmental Grievance Mechanisms

a fuzzy ahp method to support sustainability reporting an application to the water technology

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