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Journal of Cleaner Production 16S1 (2008) S1eS6www.elsevier.com/locate/jclepro

Editorial

Cleaner technology diffusion: case studies, modeling and policy*

Abstract

The development and application of cleaner technologies (environmental technologies) offer multiple benefits for the adopter: reduced emis-sions, less waste and cost savings from reduced resource use and savings on waste costs. The question here is: if cleaner technologies offer suchgreat benefits why they are diffusing so slowly across the economy? This special issue is about answering this question by presenting a collectionof contributions that lay down a good foundation for students, scholars, practitioners and policy makers interested in making sustainable devel-opment more than a metaphor. The contributions range from surveys of literature identifying gaps and directions in the field, cleaner technologydiffusion case studies, advances in diffusion modeling and diffusion policy issues and recommendations. In general the set of papers present anoverview of the advances in the field of cleaner technologies diffusion research.� 2007 Elsevier Ltd. All rights reserved.

1. Introduction

This paper aims to introduce the papers compiled in this spe-cial issue. The diffusion of cleaner technologies has been ac-knowledged to potentially be an important multiplier ofeconomic growth in the 21st century. Cleaner technologieshave been reported to bring not only environmental gains butalso increases in the competitiveness of nations [1e3]. This is be-cause the ‘‘cleaner technology’’ concept contrary to end-of-pipetechnologies seeks to prevent emissions and waste and thus saveson pollution treatment costs and waste management costs.Cleaner technologies are more eco-efficient. In terms of govern-ment intervention, policies oriented towards the promotion ofdiffusion of cleaner technologies overcome and leave behindthe debate concerning the effects of environmental policy on na-tional competitiveness (e.g., Refs. [4,5]). The call for innovationto foster competitiveness (see Refs. [6e8]) should be extended tocleaner technology. The rest of the paper gives a short overviewof market trends in cleaner technologies, some comments aboutthe state of the art in diffusion research, presents the papers thatintegrate this special issue and provides some lines of researchneeds e apart from those given in some of the individual papers.

2. State of the cleaner technologies market

The global market for environmental technologies and ser-vices is already very large reaching approximately 556 billion

* The special issue has been sponsored by TNO and the European Sixth

Framework Program through the project POPA-CTDA (EU Commission

contract 502487).

0959-6526/$ - see front matter � 2007 Elsevier Ltd. All rights reserved.

doi:10.1016/j.jclepro.2007.10.014

US dollars in 2003 [9]. Recent estimates project a total valueof 850 billion US dollars by 2010.1 According to one estimate,environmental technologies in Europe employ over two mil-lion people. European firms participating in the global marketaccount for about one-third and are growing at 5% per year[2]. Here is important to notice that the proportion of cleanertechnologies accounted for in these numbers is minimal. Ac-cording to OECD the international trade of cleaner technolo-gies account only for approximately 1% of the total marketof environmental technologies and services [9]. The first signsof a take off of cleaner technologies are evident in few caseslike photovoltaics, bio-fuels and wind power, see Box 1 forprojections of diffusion of cleaner energy technologies in dol-lars terms. The global market for cleaner technologies is con-servatively forecasted by ‘‘Nviro Cleantech PLC’’2 to reach800 billion US Dollars by 2015.

Despite the intrinsic environmental and competitive gains,and the optimistic projections of diffusion given above, thediffusion pace of cleaner technologies innovations is expectedto be slow in the next decade. The low pace is due in first in-stance for the life cycle of current durable goods and installedproduction infrastructures around the globe. Thus, policy

1 Excluding cleaner technologies.2 See http://www.investegate.co.uk/Article.aspx?id ¼ 2007080608010041

08B. Accessed on 12 August 2007. So far all projections found in the literature

available are based on a crude methodology of expert guesses (e.g., Refs.

[9,10]). They are not based on sophisticated diffusion analysis of the drivers

and time-dependent ceilings. In diffusion research the definition of the diffu-

sion ceiling continues to be a challenge difficult to tackle. So, what we can re-

cover from these numbers is the optimistic view that they will diffuse at some

point in time in the future.

S2 Editorial / Journal of Cleaner Production 16S1 (2008) S1eS6

makers still find highly problematic, how best to promotea faster deployment of new cleaner technologies.

3. State of cleaner technologies diffusion research

In the field of innovation studies the diffusion of new prod-uct innovations has been widely studied yielding in the last 40years valuable knowledge and insight for technology manage-ment and strategy, marketing, and innovation policy. For broadand recent literature reviews in the theories and diffusionmodels see Refs. [11e13]. Following Metcalfe [14] the litera-ture in the field can be divided into two dominant researchfamilies: (i) those characterising the mechanisms and patternsof diffusion and (ii) those seeking to understand and character-ise the decision-making structure and process regarding tech-nology adoption. These two strands of research have beenmainly supported by two models or approaches, the epidemicmodel and the rational choice model. The first type of researchmainly looks at rate and total amount of adoption in a givenpopulation in a time period, using curve fitting exercises.The second research strand seeks to explain it in terms of in-dividual decision-making based on rational choice.

Technological diffusion is the adoption of a technology bya population over time. On this topic there exists a long schol-arship. If we take the works of Fourt and Woodlock [15],Floyd [16], Rogers [17] as the starting point of technology dif-fusion studies, there exists a scholarship of more than 45 years.The study of innovation diffusion is concerned with the

Box 1. Cleaner energy technologies marketgrowth projections

- global markets for bio-fuels (global manu-facturing and wholesale pricing of ethanol andbiodiesel) reached $20.5 billion in 2006 and areprojected to grow to $80.9 billion by 2016;

- wind power (new installation capital costs) isprojected to expand from $17.9 billion in2006 to $60.8 billion in 2016;

- solar photovoltaics (including modules, sys-tem components, and installation) will growfrom a $15.6 billion industry in 2006 to $69.3billion by 2016; and

- the fuel cell and distributed hydrogen marketwill grow from a $1.4 billion industry (primar-ily for research contracts and demonstrationand test units) to $15.6 billion over the nextdecade.

Together, these four clean-energy technologies,which totaled $39.9 billion in 2005 and expanded39% to $55.4 billion in 2006, to quadruple to morethan $226.5 billion within a decade.

Source: Nviro Cleantech PLC (2007).

aggregate of adoption decisions; it does not seek to providedetailed answers to why a company adopted a cleaner processin a particular year (year t instead of t� 1). It is technologyadoption decisions by a population that are studied, insteadof the exact timing of individual adoption decisions throughan investigation of histories. Diffusion studies typically seekto comprehend the influence of particular factors behind theobserved diffusion pattern or try to predict diffusion (usingvarious methods). Factors relevant to diffusion may be dividedin those factors stimulating adoption and those keeping it backbut the studies may also look into the interplay of those fac-tors. The relevant factors range from organizational factorsto wider factors such as regulations and pressure from commu-nities. In addition to changes in the stimuli, it is also possiblethat changes in the characteristics of the innovation lead com-panies into adoption. Price reductions and improvements ina technology may cause a potential adopter to pass the criticalthreshold for adoption.

The above is just as true for cleaner technology diffusion(the topic of the special issue) as for other technologies likeICT and biotechnology. In general cleaner technology is a sub-category of technology, which is not so easily defined. Strictlyspeaking cleaner technologies is about process changes thatprevent and reduce pollution and waste. But cleaner technolo-gies may also be understood in a broader sense of consisting ofall technologies that help to reduce pollution and waste, whichmeans that they also include end-of-pipe technologies andwaste management techniques. Green products may also besubsumed under this category as they involve technology con-figurations, although it is probably better to only include thetechnologies, for example the fuel cell in the case of a fuelcell vehicle.

The second family intends to explore why and when theadoption might occur. Here the models and approaches avail-able include a wider array of factors that arguably influencethe decision to adopt. Today it has been acknowledged, that al-though both family models adopt different approaches andrespond to different questions, these family models arecomplementary. It is individual adopter decisions that underlieaggregate diffusion patterns and individual decisions are influ-enced by the whole of decisions of past adopters through infor-mational processes and processes of taste formation. Adoptionalso depends on supply and distribution that has been built upto meet aggregate demand. In technology diffusion there isa complex interplay between supply and demand and betweenindividual and aggregated adoptions decisions.

Until today few efforts have been made to unite both ap-proaches towards the explanation and prediction of technologydiffusion and its application to specific policy problems. Cor-respondingly in the realm of environmental policy consider-able attention has been given in the last decade to the studyof the factors affecting the adoption of environmentallyfriendly practices at the meso- or micro-levels. Despite suchan interest little attention has been given to the applicationof diffusion models to the case of cleaner technologies diffu-sion. At a more general level most diffusion studies, althoughcarrying out analyses at the meso-level, leave many questions

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concerning the drivers of the innovative behaviour of the firmunanswered. Similarly, research focusing on the factors affect-ing adoption at the firm level loses perspective of what is hap-pening at the sector and macro policy level.

The objective of the planners of this special issue of theJCP on Cleaner Technologies Diffusion was to collect per-spectives and case studies from governmental, business, tech-nical and financial sectors and academia, from around theworld. As guest editors we were particularly interested in orig-inal research papers that fill-in the gaps in the intersection ofinnovation and environmental policy mentioned above. Tothis end, a call for contributions was send out in the beginningof 2004. In response to the call we received 46 abstracts out ofwhich we selected 25 papers for further review. Of the 25papers, 18 were selected for inclusion in the JCP. The callexpressly did not exclude studies into the diffusion of end-of-pipe (EOP) technologies for the reason that EOP technolo-gies still are an important class of environmental technologies,against which cleaner process changes must compete. Thisshows that EOP technologies are still relevant for a study ofgreen process changes. Important questions for considerationare: the ceilings and bands of adoption (i.e., how much?);who is adopting; when is adoption likely to occur; why adop-tion takes place, and how to promote diffusion.

What the studies show in different ways is that diffusionprocess is a dynamic process with different kinds of feedbackmechanisms and multidirectional linkages. Within technologydiffusion there is information exchange, persuasion and pres-sures that operate through markets and social networks.Cleaner technologies compete with existing process technolo-gies and with each other, although they may also support eachother. The diffusion process is governed by information trans-fer, changes in the technology and changes in the adopter en-vironment: the tightening of regulations, changes in the priceand cost structure, pressures from customers and the largerpublic.

The journal issue brings together a heterogeneous mix ofpapers, which have been put in one of four categories: over-view studies (3), case studies (7), modeling (5) and policy (3).

The contributions included in the first part provide an over-view of the advances of the field and challenges ahead. Thepapers included in the second part describe specific advancesin the diffusion of cleaner technologies in several sectors viathe presentation of case studies. The third part of this specialissue includes advances in the area of cleaner technology dif-fusion modeling. The fourth and last part of this special issueconsists of policy analyses about the impact of policy oncleaner technology diffusion and how diffusion may be fos-tered through the use of policy.

The first part starts with a survey of the literature on factorsaffecting the adoption of cleaner technologies. Here Montalvostarts of by saying that diffusion of technology is a function ofadoption, which therefore warrants special attention. He goeson to note that the adoption of a technology is contingent ona myriad of factors whose importance in the decision structure,process and outcomes will vary according to the specific con-text and time. Two more papers integrate this overview part.

Kemp and Volpi present a review of literature on cleaner tech-nologies diffusion, the insights of which are presented in theform of 10 stylized facts about cleaner technology diffusion.They also outline gaps in our understanding and the way for-ward in the field. Battisti gives an overview of the theoreticalmodels of inter-firm diffusion the models can be grouped intwo categories: the disequilibrium models and the equilibriummodels. She then goes on to discuss intra-firm diffusion, pre-senting results about the diffusion of four advancedmanufacturing technologies in a sample of 341 British engi-neering and manufacturing firms, showing that also withinfirms the adoption of innovations is a protracted process.She performs a test to disentangle the determinants of the dif-fusion of unleaded petrol in the UK, finding that regulation isthe main determinant.

The contributions included in the second part describe spe-cific advances in the diffusion of cleaner technologies in sev-eral sectors via the presentation of case studies. These casesmake more explicit why is difficult to account at the macrolevel, in the national account system, the contribution ofcleaner technologies to trade at the national and internationallevel. Here the innovations accounted for are process orientedand are much interlinked with the supply chain of equipment,components and materials. This makes it difficult to clearlysee what is being diffused as process technologies representbundles of different technological components.

Cagno and Trucco investigate the adoption of best availabletechnologies (BATs) in the Galvanic Industry in Italy. Theyshow that it is not a simple issue of pay back time but thatthere are also important issues of knowehow involved aswell, pointing to the need for creating capabilities in thissector.

Schwarz investigates future technology diffusion in theGerman aluminium smelting industry, on the basis of a com-puter-based partial equilibrium model. The model is an eco-nomic model that assumes that a company adopts a newtechnology when discounted revenues from adoption exceedthe investment costs. The model results show the importanceof different factors, such as technological potential or the pri-ces of main inputs, in particular electricity, on technology dif-fusion in the metal industries.

Using questionnaire survey analysis, Y}uksel analyses theapproaches to environmental management, environmentaltechnologies and environmental performance of large firmsin Turkey. According to the findings, the majority of the largefirms still consider the environmental issues as a cost driverand this consideration causes to firms not to use more re-sources for environmental technologies. At the same time,the majority of the companies stated that the advantagesgained after the pollution prevention programs meet the costsfor these programs. They also agreed that environmentallyconscious business practices help the firms to find opportuni-ties for gaining competitive advantages. This shows thatcleaner production rather than end-of-pipe control is the wayto go.

Nill examines the diffusion of the electric arc furnace andthe (non) diffusion of the new smelting reduction technology

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in the iron and steel sector in Germany, with attention to timecritical aspects and how policy may deal with these throughthe preparation, creation and use of techno-economicwindows.

Using survey analysis, Luken and van Rompaey analyse thefactors affecting environmentally sound technology (ETS) uti-lization by 106 plants in nine developing countries. They stud-ied barriers and drivers for both cleaner process techniquesand technologies (CT) and pollution abatement technologies(PAT). The three most important drivers from the perspectiveof plant managers for utilizing ETS in descending order aggre-gated across the nine countries are: (i) reduction of productioncosts; (ii) current environmental regulation; and (iii) antici-pated future environmental regulation. The three most impor-tant barriers to CT utilization from the perspective of plantmanagers are: (i) high implementation costs; (ii) no alternativeprocess technology; and (iii) lack of tradition/skills. Interest-ingly, the rating of drivers and the rating of barriers by key in-formants differs from that of plant managers, which hints thatthere is a mismatch in perceptions between plant managersand the informants, who advise plant managers on or supplyservices.

Koefoed and Buckley present the results of a 4 year cleanerproduction (CP) programme in South Africa to create CPawareness, build full-scale CP demonstration projects, and ca-pacity in sector for sustainable uptake of Cleaner Technology(CT). The study finds that multiple factors are at play. Themost important CP drivers for the bigger companies are envi-ronmental standards and norms set by clients (particularly in-ternational clients), cost savings and stakeholders influence.The most important drivers for the SME are cost savingsand regulators. For dealing with wider sustainability issues,the study shows the importance of owners’ commitment andattitude, staff training and study tours for staff representatives,regulators and suppliers.

Visser, Jongen and Zwetsloot offer an analysis of innova-tion processes in five companies that developed innovationstowards more sustainable chemical products and processesfor use in other companies. They found that commercial man-agers played an important role in the innovation processes,whereas environmental managers hardly played a role at all.As to the role of policy, they found that most of the innova-tions studied were indirectly triggered by (the expectationof) new regulations in frontrunner countries, which were re-garded as indications of future market changes (market trig-gering regulation).

The third part of this special issue contains the results in thearea of cleaner technology diffusion modeling. The first arti-cle, by Barreto and Kemp, looks at the ways in which technol-ogy diffusion is modeled in energy-systems models andidentifies shortcomings. Areas where improvements areneeded are: the spatial patterns of diffusion and spatial tech-nology spillovers, the role of technology learning and R&Dactivities, social network effects, technology clusters and un-certainty. An improved dialogue and exchange between thetechnology diffusion and energy-systems modeling communi-ties is suggested, such that the representation of technology

diffusion in energy-systems models could be improved, thusenhancing the policy insights derived from these models.

The article by Wilting, Faber and Idenburg model describeshow the relationships between consumption, production andemissions prospectively for sectors. Technology per sector isdescribed by the inputs from other sectors (represented byIO coefficients) and capital, labour and emission coefficients.The paper presents a methodology for projecting these coeffi-cients for different scenarios. The methodology combinestrend analysis with detailed information of specific technolo-gies per sector, which differentiates between scenarios. Thepaper outlines the methodology and presents the main out-comes for four scenarios for the period 2000e2030.

Taanman, de Groot, Kemp and Verspagen analyse the diffu-sion of micro-cogeneration systems using hydrogen producedfrom natural gas in the Netherlands for the 2000e2050 period.The estimate future diffusion on the basis of an economic(threshold) model, looking at the costs and benefits for hetero-geneous users. The most important factors behind the diffusionare: growing energy demand, resulting in lower hydrogencosts and higher energy costs in the reference case and lowercosts of micro-cogeneration stemming from learning econo-mies. The individual users in the model have the option touse hydrogen to satisfy a part of their energy needs (hot water,space heating and electricity). They find that early adopterswill adopt hydrogen some time during the 2020s. The modelanalysis among other things shows that the use of a separateheating installation using natural gas has little effect on thetime of first adoption of hydrogen systems but considerablydelays the time at which full adoption (100% use of hydrogen)is reached.

Reinstaller examines the transition to chlorine-free pulpbleaching technologies in Sweden, Finland and the US. It findsthat problem definitions, regulatory cultures and consumer de-mand play an important role. Together these factors help to ex-plain why in Sweden several pulp manufacturers shifted tototal chlorine-free pulp bleaching in contrast to Finish andUS companies that shifted to elemental chlorine-free pulpbleaching. The article concludes that an analysis of technologydiffusion based purely on techno-economic criteria ignores thecomplex processes underlying the endogenous formation ofpreferences, which was an important factor in the case ofpulping.

The fourth and last part of this special issue includes con-tributions addressing policy analysis and design for the promo-tion of the diffusion of cleaner technology. The first article, byFoxon and Pearson, advances two guiding principles for im-proving sustainable innovation policy processes, drawing ontheoretical and empirical analysis, including a case study oflow carbon energy innovation in the UK, and interactionswith policy makers and other stakeholders through a seriesof workshops. The guiding principles advocated are: (1) stim-ulating the development of a SI policy regime, bringing to-gether innovation and environmental policy regimes; (2)engaging with the complexity and systemic interactions of in-novation systems and policy-making processes, by applyingsystems thinking, to promote a transition to sustainability.

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Mickwitz, Hyvattinen and Kivimaa examine claimsfrequently made in the literature on the relationship betweenpolicy instruments and technological development. The claimsconcern regulations, environmental taxation and funding ofresearch and development on eco-innovation. The claims areexplored on the basis of empirical evidence from two sectors:the pulp and paper industry and the marine engine industry.The evidence does not unequivocally demonstrate the environ-mental taxes are superior in stimulating innovation new to theworld. Like environmental taxes, regulation has mixed resultsin spurring innovation. Regulation is found to have sparkedinnovative solutions and to act as a brake. It is the way inwhich policy instruments are used and the techno-economiccontext in which they are used that appears to determinewhether there will be innovative solutions.

Sartorius advances a behavioural approach to drivers andbarriers to technology diffusion, which is used to determinethe most suitable policy instruments. Assessing the case of sta-tionary fuel cell technology it was found that the availabilityof the technical capacity and community pressure were themost important drivers whereas economic risk and the existingregulation represented the most powerful barriers. The case offuel cell technology suggests that a mix of policy instrumentsis needed, consisting of the R&D support and the use of roadmaps, combined with demand-oriented support schemes.

4. Reflection upon the state of the art andproposal of research agenda

At the end of this editorial we would like to use the oppor-tunity to identify topics and areas for further research. Fromthe general literature on innovation diffusion we know that dif-fusion is governed by endogenous en exogenous mechanisms.Examples of endogenous mechanisms are information transferduring the diffusion process, improvements in the technologyand price reductions as a result of learning processes, scaleeconomies and competition between suppliers. Examples ofexogenous mechanisms for cleaner technology diffusion arechanges in the price of energy, income changes and changesin the regulatory framework. Few studies into cleaner technol-ogy diffusion have tried to measure the relative importance ofthe two mechanisms (which can vary over time). We proposemore work is being done on this, allowing for generalizationsabout the mechanisms at work.

We also propose more work is being done on the actuallearning processes that underlie technology diffusion, whetherthis is from personal contacts or mass media, and what is beinglearned to what effect. Learning could be broken down intovarious types of learning (learning from using, learning by do-ing and learning about the existence of a new technology).This may help to better explain the learning curve (fallingcosts and improvements in the technology) which is not a sim-ple result from cumulative production (for a discussion we re-fer to Barreto and Kemp, this issue).

Thirdly, we propose research into the topic of technologychoice. Diffusion analysis typically concerns itself with thediffusion of a particular innovation, leaving out of sight the

adoption of alternatives. As there are usually various technol-ogy options for dealing with environmental issues it is worthto look into the choice between those options: why did compa-nies opt for the option being adopted and not for other ones?Did their economics of the various options lead them to favourthe cheapest one; did companies fail to look at other options,in particular emerging new options; or where they forced bylaw to opt particular options (if so, what features of the lawwere responsible for this, is it the actual requirements or theway in which they are implemented?)

Finally, more work is needed on the influence of variouspolicy instruments, in particular on new instruments such asthe Integrated Pollution Prevention and Control (IPPC) Direc-tive of the EU and counterpart regulations used in other partsof the world. The influence of regulations based on BAT on in-novation and diffusion is seriously understudied.

The IPPC Directive of the European Union is an importantpiece of legislation which applies to new installations, and ex-isting installations that are subject to ‘‘substantial changes’’,since 30 October 1999 and to other existing installationsfrom 30 October 2007 on. It is based on four principles,namely (1) an integrated approach, (2) best available tech-niques, (3) flexibility and (4) public participation. The inte-grated approach means that the permits must take intoaccount the whole environmental performance of the plant.The second requirement says that permit conditions includingemission limit values (ELVs) must be based on Best AvailableTechniques (BAT).

To assist the licensing authorities and companies to deter-mine BAT, the Commission organised exchanges of informa-tion between experts from the EU Member States, industryand environmental organizations about BAT; this work is coor-dinated by the European IPPC Bureau in Seville who has cre-ated reference documents (BREFs), which must be taken intoaccount by competent authorities of Member States when theydetermine conditions for IPPC permits. A discussion of theBAT system of the IPPC is offered in the Note to the fieldof Nacho Calleja and Luis Delgado [18]. It will be interestingto analyse the influence of BREFs on company compliancechoices, for example the extent to which they determinechoices. Do they fix choices or merely shape them? Does itstimulate companies to opt for process-integrated changesrather than for the use of EOP solutions? And what aboutthe incentives on innovations new to the world? Does it offerincentives to suppliers to innovate new and better techniquesor does it provide disincentives to do so? Little work hasbeen done on this.

More work is also needed on the influence of waste policyon cleaner technology diffusion and the role of innovation pol-icy on innovation diffusion. The effects of those policies areseldom taken into account in econometric analysis.

With these suggestions we invite readers to engage anew inthe study of cleaner technology diffusion because it remains animportant area for research, even after 45 years. We thank theauthors of the articles of the journal issue for their contribu-tions and their patience. A special word of thanks goes tothe reviewers who gave so generously of their time and whose

S6 Editorial / Journal of Cleaner Production 16S1 (2008) S1eS6

comments offered many useful suggestions for improvements.Finally we want to thank Don Huisingh, the journal editor, forproviding an outlet for the papers and for his assistancethroughout. Special thanks are due to Arnold Tukker ofTNO for his help at the final stage, when one of us fell ill.It has taken us long to have the special issue out. We apologiseto all the authors and the editor of the journal for the long de-lay. Like the authors, we are very happy to finally see the re-sults in print and hope this issue creates new interest in the oldtopic of technology diffusion.

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Carlos MontalvoTNO The Netherlands Organization for Applied Scientific

Research, Shoemakerstraat 97, 2600JA Delft, The NetherlandsE-mail address: carlos.montalvo@tno.nl

Rene KempUNU-MERIT, ICIS and DRIFT, Keizer Karelplein 19,

NL-6211 TC Maastricht, The NetherlandsE-mail address: r.kemp@merit.unimaas.nl

Available online 28 November 2007