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Sustainability performance evaluation in industry by composite sustainability index

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Abstract

The growing importance of sustainable development as a policy objective has initiated a debate about those suitable frameworks and tools useful for policy makers when making a sustainable decision. Composite indicators (CIs) aggregate multidimensional issues into one index, thus providing comprehensive information. However, it is frequently argued that CIs are too subjective, as their results undesirably depend on the normalization method, a specific weighting scheme, and the aggregation method of sub-indicators. This article applies different combinations of normalization, weighting, and aggregation methods for the assessment of an industrial case study, with the aim of determining the best scheme for constructing CIs. The applied methodology gradually aggregates sustainable development indicators into sustainability sub-indices and, finally, to a composite sustainability index. The normalization methods included in this analysis are: minimum–maximum, distance to a reference, and the percentages of annual differences over consecutive years. Equal weightings, the ‘benefit of the doubt’ approach, and budget allocation process were used for determining the weights of individual indicators and sustainability sub-indices. The linear, geometric, and non-compensatory multi-criteria approaches (NCMCs) were used as aggregation methods. The NCMC is modified to fit the two-level aggregation, then to sub-indices, and finally to a composite sustainable index. Also, a penalty criterion is introduced into the evaluation process with the aim of motivating the company to move towards sustainable development. The results are analyzed by variance-based sensitivity analysis. According to the results the recommended scheme for CIs’ construction is: distance to a reference–benefit of the doubt–linear aggregation.

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Abbreviations

AHP:

Analytical hierarchy processes

BAP:

Budget allocation process

BAT:

Best available techniques

BOD:

Benefit of the doubt

CA:

Conjoint analysis

CI:

Composite indicator

DEA:

Data envelopment analysis

EW:

Equal weighting

FAST:

Fourier amplitude sensitivity test

GME:

Geometric aggregation

GRI:

Global reporting initiative

LIN:

Linear aggregation

MCDA:

Multiple criteria decision analysis

NCMC:

Non-compensatory multi-criteria approach

UCM:

Unobserved component models

WP:

Weighted product

I :

Set of indicator or input quantity of the evaluated model

J :

Group of indicators (group of environmental indicators: j = 1; group of societal indicators: j = 2; group of economic indicators: j = 3) or input quantity of the evaluated model

T :

The analysed time period (2003–2007)

\( I_{i,j,t}^{ + } \) :

Indicator i from group of indicator j in year t with positive impact on sustainable development

\( I_{i,j,t}^{ - } \) :

Indicator i from group of indicator j in year t with negative impact on sustainable development

\( I_{i,j}^{\text{Benchmark}} \) :

Benchmark for indicator i from group of indicators j

\( I_{{_{i,j} }}^{{ + ,{\text{ MAX}}}} \) :

The highest value of indicator i with positive impact on sustainable development from group of indicator j for the analyzed time period

\( I_{{_{i,j} }}^{{ - ,{\text{ MAX}}}} \) :

The highest value of indicator i with negative impact on sustainable development from group of indicator j for the analyzed time period

\( I_{{_{i,j} }}^{{ + ,{\text{ MIN}}}} \) :

The lowest value of indicator i with positive impact on sustainable development from group of indicator j for the analyzed time period

\( I_{{_{i,j} }}^{{ - ,{\text{ MIN}}}} \) :

The lowest value of indicator i with negative impact on sustainable development from group of indicator j for the analyzed time period

X i :

Input quantity i of the evaluated model

\( \tilde{X}_{i} \) :

The true value of input quantity i

E(Y|X i ):

Expected value for the output quantity Y for the whole variation interval of the input quantity X i

\( E\left[ {V\left( {Y\left| {X_{ - i} } \right.} \right)} \right] \) :

Expected amount of residual variance when X i , and only X i were left free to vary over its uncertainty range, all the other variables are fixed

\( I_{{N_{i,j,t} }}^{ + } \) :

Normalized indicator i from group of indicator j in year t with positive impact on sustainable development

\( I_{{N_{i,j,t} }}^{ - } \) :

Normalized indicator i from group of indicator j in year t with negative impact on sustainable development

\( I_{{S_{j,t} }} \) :

Sustainable sub-indices for group of indicator j in year t

\( I_{{S_{j,t} }}^{\text{Benchmark}} \) :

Sustainable sub-indices for group of indicator j determined for the benchmarks in year t

\( I_{{S_{j,t} }}^{*} \) :

The highest value for the sustainable sub-indices for group of indicator j in year t

\( I_{{{\text{SUST}}\,_{t} }} \) :

Composite sustainability index in year t

\( I_{{_{{{\text{SUST}}\,_{t} }} }}^{*} \) :

The highest value for the composite sustainability index in year t

S i :

First-order sensitivity index for input quantity i

S i, j :

Second-order sensitivity index or two-way interaction for input quantities X i and X j

S Ti :

Total sensitivity index for input quantity i

V(Y):

Unconditional variance for the output variable Y

\( V\left[ {E\left( {Y\left| {\tilde{X}_{i} } \right.} \right)} \right] \) :

Conditional variance of the expected value for the output quantity Y when the input quantity is fixed on its true value \( \tilde{X}_{i} \)

\( V\left[ {E\left( {Y\left| {X_{i} ,X_{j} } \right.} \right)} \right] \) :

Conditional variance of the expected value for the output quantity Y when input quantities X i and X j are fixed

w j :

Weight of the group of sustainability indicator (sub-indices) j

w i,j :

Weight of indicator i from group of indicator j

Y :

Output quantity of the evaluated model

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Acknowledgment

The authors are grateful to the National Natural Science Foundations of China (Project 21076180) for the financial support.

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Authors and Affiliations

  1. State Key Laboratory of Chemical Engineering, Department of Chemical and Biochemical Engineering, Zhejiang University, Hangzhou, Zhejiang, 310027, People’s Republic of China

    Li Zhou, Hella Tokos & Yongrong Yang

  2. Laboratory for Process Systems Engineering and Sustainable Development, Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, 2000, Maribor, Slovenia

    Damjan Krajnc

Authors
  1. Li Zhou
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  2. Hella Tokos
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  3. Damjan Krajnc
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  4. Yongrong Yang
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Correspondence to Damjan Krajnc or Yongrong Yang.

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Zhou, L., Tokos, H., Krajnc, D. et al. Sustainability performance evaluation in industry by composite sustainability index. Clean Techn Environ Policy 14, 789–803 (2012). https://doi.org/10.1007/s10098-012-0454-9

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