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3.3 Material efficiency in companies of the manufacturing industry:
classification of measures
S. Fischer 1
1 Wuppertal Institute for Climate, Environment, Energy, Germany
Abstract
Improving material efficiency in the manufacturing industry is a sustainability imperative for companies due to
economic and environmental advantages such as the reduction of material costs and resource use.
Innovative solutions in terms of material efficiency measures are diverse and widespread. As a systematic
assessment of efficiency approaches and their effects are likely to support dissemination and deployment,
this paper aims to develop an approach that helps to classify material efficiency measures. The classification
approach presents different dimensions and properties of material efficiency measures based on a literature
analysis regarding existing classification approaches as well as on work that has been conducted for the Eco-
Innovation Observatory. The classification has been designed as basis for an empirical impact assessment of
material efficiency measures based on a data sample that stems from the German Material Efficiency
Agency.
Keywords:
Classification; Material Efficiency Measure; Sustainable Manufacturing
1 INTRODUCTION
Material engineering and processing companies are facing
change. Growing constraints regarding material availability
and increasing raw material prices are increasingly
anticipated as entrepreneurial risks requiring preventive
adaption strategies [1] [2]. At the same time, new business
chances in terms of revenue growth, comparative cost
advantages, an improved risk management and a better
reputation appear to be tangible for those companies that
manage those challenges pro-actively [3]. Pro-active
businesses would not only be in the favourable position to
realise these potentials, but also to “change the rules of the
game” [4].
One opportunity for companies to meet the changing
framework conditions is the implementation of measures that
lead to an improved material efficiency and thus to a reduced
use of material resources. Recently, data from case studies
from the Germany Material Efficiency Agency (demea)—
which offers support to consult small and medium sized
enterprises regarding the implementation of material
efficiency measures (MEMs)—were analysed by a number of
studies and projects [5] [6] [7]. It was revealed that
implementing simple and low-cost MEMs can lead to savings
of around € 200,000 per company and year, corresponding to
2 % of the yearly company turnover and facing one-off
investments of around € 130,000.
Nonetheless, the actual implementation in business leaves
much to be desired—only one in seven of all companies and
one in four innovating companies in the EU-27 are
introducing those kinds of innovation that lead to a material
use reduction [6]. Amongst others, the lack of entrepreneurial
action can be traced back to barriers (e.g. uncertainties
concerning the return on investment). In order to accelerate
the application of MEMs, decision makers in business need
to be better informed about MEMs, their costs and benefits.
To this end, an improved understanding about the range of
different MEMs would be useful.
The present paper addresses this subject. Based on the
analysis of scientific articles, studies and other publications, it
will present a possible classification approach of MEMs. The
developed approach will be the future basis for an in-depth
analysis of the demea case studies.
2 LITERATURE ANALYSIS
2.1 Definitions
The concept of efficiency compares the inputs of a system
with the outputs of that system. Regarding material efficiency
on a corporate level, the inputs of the system are physical
resources that go into a production process with the output of
produced goods (products and services), which have an
economic value. The less material input is needed to
generate the same amount of output (or the more output is
generated with the same amount of input), the more efficient
the system is. Correspondingly, a MEM would be an
entrepreneurial action that has the aim to reduce the input of
materials while the same economic output is generated with
regard to the production of goods.
Material efficiency is closely related to the concept of
resource efficiency, with the difference being that they have
different system boundaries. The material efficiency concept
focuses on one stage of a resource’s life-cycle, in contrast,
the concept of resource efficiency is more broad as it regards
the efficiency of a resource’s extraction, its use and resulting
environmental impacts over all life-cycle stages [8]. This
paper focuses on sustainable manufacturing und thus on the
manufacturing phase, consequently, the efficiency term of
this paper refers to the material efficiency concept.
G. Seliger (Ed.), Proceedings of the 11th Global Conference on Sustainable Manufacturing - Innovative Solutions
ISBN 978-3-7983-2609-5 © Universitätsverlag der TU Berlin 2013
102
S. Fischer
2.2 Method
A plethora of scientific knowledge regarding the subject of
material efficiency has been generated over the past few
years. In order to analyse the diffusion of the classification of
material efficiency measures in companies of the
manufacturing industry in the scientific discussion, a keyword
search was conducted. As part of the search, the publication
databases Web of Knowledge, Scirus, BASE, Google
Scholar and ScienceDirect were scanned for publications that
contain the following keywords and/or combinations of them
(e.g. material, efficiency, measure, categorisation), as far as
possible within the title and/or the full text:
material OR resource,
efficiency OR productivity,
measure OR strategy,
classification OR categorisation,
manufacturing.
More than 20,000 documents (including redundant hits as
well within as across databases) including the above
mentioned keywords and/or combinations were found in the
five databases. However, hits were screened only until a
number of 150 entries per search query, so that around 4,000
documents were screened very roughly for a thematic
relevance to the research question of this paper. As a result,
around four dozen reviewed articles were considered to be
the most promising and were used for a deeper analysis.
Additionally, cross-references with further subjects such as
(eco-)innovation, (cleaner) production, (sustainable)
manufacturing etc. and links to further publications such as
other journal articles, books and book chapters, conference
contributions, project reports etc. were researched and
included into the literature analysis as well.
3 CLASSIFICATION OF MATERIAL EFFICIENCY
MEASURES
3.1 Terminology
The following approach including the ensuing terms will be
used for the classification of MEMs: A MEM can be classified
regarding different dimensions. Each dimension is described
by a bundle of properties, of which only one property can be
valid per dimension. It is possible to specify properties on
further levels by introducing sub-properties. The collection of
all valid properties across the different dimensions forms the
type of the MEM. Distinguishing MEMs by their types, in
terms of valid properties across the different dimensions,
shall constitute this paper’s approach of how to classify
MEMs.
3.2 Classification approaches in the literature
In the course of the literature analysis, general insight
regarding classification approaches of MEMs in scientific
literature was gained.
Due to the fact that there are a lot of different terms when it
comes to describing the material efficiency concept, the
search for classification approaches of material efficiency
measures was aggravated. In order to have a higher or better
hit quota, additional expressions such as resource efficiency,
etc. were included into the search. It is however evident that
this choice was not able to cover the whole range of possible
terms describing the same phenomenon (e.g. expressions
such as material or resource use and savings or benefits
would have been possible, too). There are also a number of
synonyms for measure and strategy (e.g. innovation,
practice, action or opportunity) and classification and
categorisation (e.g. typology, group, set or characteristic).
A further factor making searches more challenging is the
importance of the classification of MEMs for the respective
publication. In most of the cases, the classification approach
is more a methodological step on the way to analyse a
specific research question than the essence of the scientific
publication itself. As the classification happened more
incidentally, the identification of classification approaches in
the literature is possible in limited form only (e.g. as it is not
necessarily listed in the publication title, however the titles
were used for the rough screening regarding the thematic
relevance of the publication).
Only a small number of the publications considered as
promising developed a general approach of how to classify
MEMs (e.g. in [5] [9] [10]). For the most part, the publications
dealt with only one thematic area and therefore with only one
classification dimension and its different properties (e.g.
green technologies in [11] [12] [13]).
Furthermore, there are publications about MEMs that
presented a bundle of common and concrete MEMs, however
failed to introduce a general classification (e.g. in [14] [15]
[16]).
3.3 Own classification approach
As a result of the literature analysis, the following thirteen
dimensions and their properties to classify MEMs were
identified. Some of the dimensions were further specified on
a second- and third-tier level (see Table 1). The choice of
dimensions and properties is not understood to be complete
and exclusive—it is rather a first approach of how a MEM
classification could look like.
General nature (dimension 1)
The general nature of a MEM gives an answer to the question
of the pursued superior strategy: Is it a business model
decision, a technical option, an organisational change or a
personnel development measure? These four properties are
the result of different approaches found in the literature.
Other perspectives for the general nature of a MEM would
have also been possible; for the most part they are, however,
reflected in the following dimensions.
Due to the wide scope of the general nature dimension, the
four properties are further specified on a second-tier level.
Whereas the properties for the business model are based on
a single and pertinent source [17], the technical material
efficiency properties have been compiled on the basis of
several approaches from diverse literature findings. Technical
material efficiency changes can target a company’s
infrastructure, its product design, manufacturing method,
production planning and production process, the sphere of
manufacturing and it can be another technical strategy, too.
This classification, however, is still too rough. Therefore a
third-tier level has been introduced that specifies the
technical material efficiency strategies:
The infrastructure dimension distinguishes between
changes regarding technology, machines, tools and the
building including other equipment. The technology
dimension again is manifold and could be further
specified, such as into environmental, optical,
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Material efficiency in companies of the manufacturing industry: classification of measures
automation, information and communication, production,
energy, material and building technology and nano- and
biotechnology [18]. Again, the environmental
technologies could be further specified to e.g. cleansing,
cleaner process and clean technologies, etc. [11].
The product design determines the material use of a
product during its life-cycle phases to an enormous
extent—80 % of the economic cost and environmental
and social impacts are fixed through the product design
[19]. There are a lot of opportunities to determine the
material use already in the design phase [20] [21] [22]:
changes in the product function (e.g. combined
functions), durability, size, construction, choice of
materials (e.g. use of secondary raw materials) and
auxiliary materials and considering resource efficiency
aspects during the phases of manufacturing, packaging,
use, reuse (or remanufacturing or recycling) and final
waste treatment.
The decision for a certain manufacturing method can be
the subject of a MEM. Decisions regarding the following
manufacturing method properties are possible: material
flow structure (e.g. convergent material flows), cross
linking of manufacturing steps (e.g. circular material flow),
degree of repetition (e.g. serial production), physical
arrangement of manufacturing steps (e.g. workshop
production) and other technical determinants (e.g.
changing from a chemical to a biological process).
Whereas changes regarding infrastructure, product
design, and manufacturing method are of a more long-
term nature, modifications concerning the production
planning are characterised by mid- and short-term
actions. Setting the production program (e.g. volume of
products to be produced in a certain period), materials
management (e.g. determination of material requirement)
and actual operation scheduling (e.g. capacity and
sequence planning) is also part of technical material
efficiency strategies.
In connection with the production planning the actual
physical production process offers further possibilities to
influence material efficiency on a technical basis—in
terms of production control (e.g. concrete job approval),
machine setting (e.g. technical adjustments) and the
operating of machines (e.g. optimised handling).
The sphere of manufacturing also offers material
efficiency opportunities in terms of actions regarding the
workplace design [5], maintenance and cleaning, storage
and cleaning and packaging.
In addition to the named sub-properties of the technical
material efficiency dimension, superior technical
strategies that target quality management (e.g.
implementation of a company wide monitoring, controlling
and benchmarking system), use of information
technology (e.g. new software) and a material flow
management (e.g. in order to implement in-house and
closed-loop material flows) have been introduced as final
classification properties for technical MEMs.
Life-cycle stage (dimension 2)
The MEM can target different life-cycle stages: the phase of
the resource extraction, manufacturing, transport, etc. The
properties describing those phases have been taken from the
supply chain operations reference model [23] and comprise
the stages of plan, source, make, deliver and return.
The dimension of the planning level takes different time
horizons into account. Planning decisions can be normative,
strategic, tactical and operational [24] with decisions affecting
the above listed technical material efficiency strategies (e.g.
strategic decisions about product design, or tactical
determination of the production program).
Corporate division (dimension 3)
The dimension of the corporate division comprises the
properties management, corporate culture, human resources,
research and development, product design, marketing,
controlling, procurement, manufacturing, maintenance and
cleaning, storage and logistics and packaging. These could
be assigned to the life-cycle stages, too (e.g. research and
development to planning or manufacturing to making)—it is,
however, interesting to learn which corporate division is able
to influence the material efficiency performance of the
enterprise.
Mechanism (dimension 4)
The idea regarding a mechanism dimension has been taken
from a methodology of how to describe sustainable
manufacturing tactics [25]. It depicts how the material
efficiency effect takes place. The concrete properties were
chosen in analogy with the waste hierarchy defined by the
European Union [26] that differentiates between prevention,
reuse, recycling, recovery and disposal (as the latter one is
not relevant in terms of material efficiency improvements, it is
not included in the properties of this dimension).
Material (dimension 5)
A MEM reduces the use of materials. The material dimension
gives an overview of the saved material type. On the first-tier
level the dimension is simply characterised by input and by
output material. In accordance with a guideline of how to
calculate the material input per service unit [27], on a second-
tier level, the input material is further specified by abiotic and
biotic raw materials, energy sources and carriers, water, air,
components, models, auxiliary and operating materials.
Accordingly, the output material is further specified by main
and by-products, waste, emissions, waste water and exhaust
air.
Degree of change (dimension 6)
MEMs lead to a change in the respective company. To which
degree that change takes place gives occasion to introduce a
further classification dimension. Commonly, it is distinguished
between small and high degree changes—in terms of e.g.
incremental and radical innovations [28] [29] [30]. In this
paper the focus lies more on business-related incremental
than society-related radical changes, therefore an approach
[31] is chosen that focuses more on incremental changes.
Modification, redesign, alternatives, and (with respect to
radical and system changes) creation are the properties of
the degree of change dimension.
Degree of novelty (dimension 7)
Complementary to the degree of change, a differentiation
regarding the degree of the MEM’s novelty is possible. As the
definition of novelty is not possible per se [32], a framework
for comparison is necessary: Is the measure just new to the
firm, but already implemented by other companies in the
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S. Fischer
same market segment? Is it new to the market or new to the
world? The answers to these questions are the properties
chosen for the classification approach of this paper.
Directness of effect (dimension 8)
Whether the material reduction effect of a MEM occurs
immediately after the implementation or is delayed by a
certain amount of time or whether the effect occurs at the
place where the measure has been implemented or further
downstream is a further classification dimension. It is
differentiated between direct and indirect effects [33] [34].
Measurability (dimension 9)
Related with the question regarding the directness of effect is
the measurability of an effect. Effects can be measured on a
quantitative (e.g. saved material amount through changed
machine adjustments) or a qualitative basis (e.g. better
housekeeping through awareness raising measures).
Risk structure (dimension 10)
The introduction of MEMs can pose a path dependence risk
to the company in terms of the ecological, economic and
technical reversibility [35]. These features could be taken as
properties for the dimension of risk structure. However, a
MEM could be all three—difficult to be reversed in ecological,
economic and technical terms. Therefore, a differentiation
between a low, middle and high risk, based on the different
reversibility aspects are chosen as properties in order to
describe the risk structure of a MEM.
Technical education (dimension 11)
The technical education that is needed in order to introduce
and to implement the MEM is a further classification
dimension of MEMs. The chosen properties for that
dimension differentiate between maintenance personnel,
engineering personnel and technology expert [9].
Implementation time (dimension 12)
The time that a measure needs to be implemented is a
further dimension of MEM classification. The implementation
time is short when it is below six months; it is medium when it
takes between six months and one year. In case it takes
longer than one year, the implementation time is long.
Measure duration (dimension 13)
The duration of the MEM constitutes another classification
dimension. In case it has a five year life expectancy it is a
short-term measure. With a lifetime between 5 and 20 years
it is a medium-term and more than 20 years it is a long-term
measure [9].
Table 1: Classification of material efficiency measures (first-, second- and third-tier level)
Dimensions
Properties
1
General nature
business model
technical material
efficiency
personnel
development
1.1
Business
model
value proposition
target customer
relationship
value
configuration
core competency
partner network
revenue model
1.2
Technical
material
efficiency
infrastructure
product design
production planning
production
process
sphere of
manufacturing
other technical
strategy
1.2.1
Infrastructure
technology
machine
building and
equipment
1.2.2
Product design
function
durability
construction
material choice
auxiliary
materials
manufacturing
use
reuse
waste treatment
1.2.3
Manufacturing
method
material flow
structure
cross linking of
manufacturing
steps
physical
arrangement of
manufacturing steps
technical
determinants
1.2.4
Production
planning
production
program
materials
management
1.2.5
Production
process
production
control
machine setting
1.2.6
Manufacturing
sphere
workplace design
maintenance and
cleaning
packaging
1.2.7
Other
technical
strategy
quality
management
IT assistance
1.3
Personnel
development
awareness
raising and good
housekeeping
position creation
105
2
Life-cycle stage
plan
source
deliver
return
2.1
Planning level
normative
strategic
operational
3
Corporate
division
management
corporate culture
research and
development
product design
marketing
controlling
manufacturing
maintenance
and cleaning
storage and
logistics
packaging
4
Mechanism
prevention
reuse
recovery
5
Material
input material
output material
5.1
Input material
abiotic
raw materials
biotic
raw materials
water
air
components
modules
operating materials
5.2
Output material
main products
by-products
emissions
waste water
6
Degree of
change
modification
redesign
creation
7
Degree of
novelty
new to the
firm
new to the
market
8
Directness of
effect
direct
indirect
9
Measurability
quantitative
qualitative
10
Risk structure
high risk
middle risk
11
Technical
education
maintenance
personnel
engineering
personnel
12
Implementation
time
short
(<6 months)
medium
(6-12 months)
13
Measure
duration
short-term
(<5 years)
medium-term
(5-20 years)
4 CONCLUDING REMARKS
Based on literature research, this paper has developed an
approach of how to classify MEMs in companies of the
manufacturing industry. The approach consists of thirteen
dimensions that are specified by a number of properties
(and where appropriate also on a second- and third-tier
level), of which only one property per dimension is valid for a
certain MEM. The collection of all valid properties regarding
the thirteen dimensions forms the respective MEM type.
The approach does not claim to represent the entire reality,
it is even highly likely that the dimensions and properties can
be amended or refined. Changes in some other form could
also be possible because defining distinct properties for
dimensions that look from different perspectives on a similar
issue cannot always happen without any overlap (e.g.
packaging is a property of the dimensions product design,
manufacturing sphere and corporate division).
Despite possible weaknesses, the developed classification
approach could serve as the basis for a detailed analysis of
case studies as conducted by the demea. MEM types shall
be compared with each other in order to find patterns that
allow deductions regarding MEM type-related material
saving potentials (in physical and monetary terms),
investment costs and payback times.
To give an example, measures in the demea cases
comprise amongst others changes concerning the reduction
of set-up times, changed temperature in the production
process, use of filters, alternative coating method, re-use of
dissolvent, improved definition of employee responsibilities,
machinery cleaning, product size, use of IT in order to
support production simulation and quality control of
purchased commodities [36]. According to this paper’s
classification approach, they all target the technical material
efficiency property within the general nature dimension. On a
second- and third-tier level the MEMs are further specified
by sub-properties such as process organisation (production
planning), machine setting (production process), tool
(infrastructure), technical determinants and material flow
structure (manufacturing method), operating of machines
(production process), maintenance and cleaning
(manufacturing sphere), size (product design), IT assistance
and quality management (other technical strategy).
Identifying the properties of the remaining twelve dimensions
and building the MEM types would be the next steps on the
way to the classification of the given MEMs.
In order to accelerate the dissemination and deployment of
MEMs in companies of the manufacturing industry, the
classification of MEMs needs to take place on a larger scale
combined with the deduction of MEM patterns and
determination of the economic leverages and payback
times.
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5 REFERENCES
[1] KPMG, 2012, Expect the Unexpected: Building
business value in a changing world.
[2] World Economic Forum, 2011, Global Risks 2011.
[3] WBCSD, 2010, Vision 2050: The new agenda for
business.
[4] Sommer, A, 2012, Managing Green Business Model
Transformations, Springer.
[5] Schmidt, M., Schneider, M., 2010,
Kosteneinsparungen durch Ressourceneffizienz in
produzierenden Unternehmen, Uwf, 18:153–164.
[6] EIO, 2012, Closing the eco-innovation gap: An
economic opportunity for business, DG Environment.
[7] Greenovate! Europe, 2012, Guide to resource
efficiency in manufacturing, Europe Innova.
[8] Abdul Rashid, S., Evans, S., Longhurst, P., 2008, A
comparison of four sustainable manufacturing
strategies, Int. J. Sustain. Eng., 1:214–229.
[9] Fleiter, T., Hirzel, S., Worrell, E., 2012, The
characteristics of energy-efficiency measures – a
neglected dimension. Energy Policy, 51:502–513.
[10] Allwood, J. M., Ashby, M. F., Gutowski, T. G., Worrell,
E., 2011, Material efficiency: A white paper, Resour.
Conserv. Recycl., 55:362–381.
[11] Kuehr, R., 2007, Environmental technologies – from
misleading interpretations to an operational
categorisation & definition, J. Clean. Prod., 15:1316–
1320.
[12] Lang-Koetz, C., Pastewski, N., Rohn, H., 2010,
Identifying New Technologies, Products and
Strategies for Resource Efficiency, Chem. Eng. &
Technol., 33/4:559–566.
[13] Ritthoff, M., Liedtke, C., Kaiser, C., 2007,
Technologien zur Ressourceneffizienzsteigerung: Hot
Spots und Ansatzpunkte, Wuppertal Institut.
[14] Barrett, J., Scott, K., 2012, Link between climate
change mitigation and resource efficiency: A UK case
study, Glob. Environ. Change, 22:299–307.
[15] Schröter, M., Lerch, C., Jäger, A., 2011,
Materialeffizienz in der Produktion: Einsparpotenziale
und Verbreitung von Konzepten zur
Materialeinsparung im Verarbeitenden Gewerbe,
Fraunhofer ISI.
[16] Ackroyd, J., Titmarsh, L., Coulter, B., Dombey, A.,
Phillips, P. S., 2006, Business excellence through
resource efficiency (betre): East Sussex waste
minimisation programme, Resour. Conserv. Recycl.,
46:217–241.
[17] Osterwalder, A., Pigneur, Y., Tucci, C. L., 2005,
Clarifying business models: Origins, present, and
future of the concept, Commun. Assoc. Inf. Syst., 1-
40.
[18] Rohn, H., Lettenmeier, M., Pastewski, N., 2011,
Identification of Technologies, Products and Strategies
with High Resource Efficiency Potential, in Int. Econ.
Resour. Effic. (Bleischwitz, R., Welfens, P. J. J. &
Zhang, Z.) 335–347, Physica.
[19] Tischner, U., Charter, M., 2001, Sustainable product
design, in Sustain. Solutions (Charter, M. & Tischner,
U.) 118–138, Greenleaf Publishing.
[20] Van Berkel, R., Willems, E., Lafleur, M., 1997,
Development of an industrial ecology toolbox for the
introduction of industrial ecology in enterprises, I. J.
Clean. Prod., 5:11–25.
[21] Ji, Y., Jiao, R. J., Chen, L., Wu, C., 2013, Green
modular design for material efficiency: a leader–
follower joint optimization model, J. Clean. Prod.,
41:187–201.
[22] Charter, M., Gray, C., 2008, Remanufacturing and
product design, Int. J. Prod. Dev., 6:375–392.
[23] Francis, J., 2011, SCC and SCOR Overview.
[24] Dyckhoff, H., 2006, Produktionstheorie: Grundzüge
industrieller Produktionswirtschaft, Springer.
[25] Despeisse, M., Ball, P. D., Evans, S., 2012, in
Sustain. Manuf. (Seliger, G.) 9–16, Springer.
[26] The European Parliament and the Council of the
European Union, 2008, DIRECTIVE 2008/98/EC on
waste and repealing certain Directives.
[27] Ritthoff, M., Rohn, H., Liedtke, C., 2002, Calculating
MIPS : resource productivity of products and services.
[28] Freeman, C., Perez, C., 1988, Structural Crises of
Adjustment, Business Cycles and Investment
Behaviour, in Tech. Change Econ. Theory (Dosi, G.,
Freeman, C., Nelson, R. R., Silverberg, G. & Soete,
L.) 38–66, Pinter.
[29] Rennings, K., 2000, Redefining innovation — eco-
innovation research and the contribution from
ecological economics. Ecol. Econ., 32:319–332.
[30] Carrillo-Hermosilla, J., del Río, P., Könnölä, T., 2010,
Diversity of eco-innovations: Reflections from selected
case studies, J. Clean. Prod., 18:1073–1083.
[31] OECD, 2009, Sustainable Manufacturing and Eco-
Innovation: Framework Practices and Measurement.
[32] Konrad, W., Nill, J., 2001, Innovationen für
Nachhaltigkeit, IÖW.
[33] Fichter, K., Arnold, M., 2004,
Nachhaltigkeitsinnovationen, Universität Oldenburg.
[34] Kristof, K., Welfens, M. J., Türk, V., Walliczek, K.,
2007, Ressourceneffizienzsteigerungen durch
organisatorische und institutionelle Innovationen,
Wuppertal Institut.
[35] Paech, N., 2005, Nachhaltige Innovationen: Zur
Gestaltung ambivalenter Prozesse des Wandels, in
Jahrb. Ökologische Ökonomik 225–250, Metropolis.
[36] Fischer, S., O’Brien, M., 2012, Eco-innovation in
Business: reducing cost and increasing profitability via
Material Efficiency Measures, EIO.
107