empirical influence of environmental management on innovation: evidence from europe

E C O L O G I C A L E C O N O M I C S 6 6 ( 2 0 0 8 ) 3 9 2 – 4 0 2

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ANALYSIS

Empirical influence of environmental management oninnovation: Evidence from Europe

Marcus Wagner ⁎

Bureau d'Economie Théorique et Appliquée, Université Louis Pasteur, 61 avenue de la Fôret Noire, 67085 Strasbourg Cedex, FranceSchöller Chair for Technology and Innovation Management, Technische Universität München, Arcisstr. 21, 80333 Muünchen, Germany

A R T I C L E I N F O

⁎ Corresponding author. Bureau d'EconomieStrasbourg Cedex, France. Fax: +33 390 24207

E-mail address: [email protected]

0921-8009/$ – see front matter © 2007 Elsevidoi:10.1016/j.ecolecon.2007.10.001

A B S T R A C T

Article history:Received 13 March 2007Received in revised form1 October 2007Accepted 1 October 2007Available online 3 December 2007

This paper analyses the hypothesis that environmental management systems (EMS) andmanagerial activities to reduce negative environmental impacts which are not part of EMShave a positive influence on the probability of firms to carry out environmental innovations.Based on binary and multinomial discrete choice models, the relationship of a number ofdeterminants on the occurrence of environmental innovations is studied using datacollected during the “European Business Environment Barometer 2001/2002” survey in 9European states. The study finds that environmental management systems are associatedwith process innovations. However, the study does not find that environmentalmanagement systems are associated with product innovations. For product innovations,mainly information of consumers and eco-labelling activities show a positive association.Market research on the potential of environmental innovations positively relates to bothprocess and product innovations. Importantly, firm size is not found to have any effect onthe probability of a firm carrying out environmental product or process innovations.

© 2007 Elsevier B.V. All rights reserved.

Keywords:EnvironmentalInnovationManagement systemsLabellingMarket researchMarketing

1. Introduction

This paper tests whether environmental management sys-tems and managerial activities to reduce negative environ-mental impacts that are not part of EMS have a positiveinfluence on the probability of firms to carry out environmen-tally-friendly innovations, short environmental innovations.In order to avoid a common issue with empirical studies,namely their limited comparability, care was taken to ensureas much as possible comparability with previous studies.Furthermore, in order to overcome at least some of thelimitations of earlier studies, the empirical analyses used totest the hypotheses developed in this paper are based on aquestionnaire specifically targeted towards environmentalmanagement and innovation aspects which collects data at

Théorique et Appliquée1..fr.

er B.V. All rights reserved

the firm level and includes firms with environmental man-agement systems as well as those without such a system.

Environmental innovations can be defined as “…measuresof relevant actors (firms, …, private households), which:(i) develop new ideas, behaviour, products and processes,apply or introduce them, and (ii) contribute to a reduction ofenvironmental burdens or to ecologically specified sustain-ability targets” (Rennings, 2000, p. 322). Rehfeld et al. (2007)state that the specification of the direction of technologicalchange defined by (ii) is an essential definition criterion forenvironmental innovations. Rennings (2000) furthermoreshows that from (ii) the double externality characteristic ofenvironmental innovations can be derived, which can also beused to delineate them from other innovations. Doubleexternality here means that environmental innovations

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http://dx.doi.org/10.1016/j.ecolecon.2007.10.001

393E C O L O G I C A L E C O N O M I C S 6 6 ( 2 0 0 8 ) 3 9 2 – 4 0 2

have, next to the positive externalities from spillovers whichare common to all innovations, additionally the characteristicof leading to a reduction of external environmental cost as anegative externality. Next to identifying environmental inno-vations as a subset of all innovations in an economy, adistinction can also be made in accordance with the Oslomanual (OECD and Eurostat, 1997) into product innovations(i.e. environmentally-sound product design) and process inno-vations (process-integrated environmental technologies, seealso Ziegler and Rennings, 2004; Rehfeld et al., 2007). Thedebate about environmental innovations is embedded in amore general one about sustainability innovations (Smithet al., 2005; Tidd et al., 2005; Weber and Hemmelskamp, 2005)and coordination mechanisms such as markets, regulation ornetworks (Rennings et al., 2003). In the context of the firm, thisis for example relevant for the so-called Porter hypothesisproposing “innovation offsets” from stringent environmentalregulation (Albrecht, 1998a, 1998b; Porter and van der Linde,1995) which is gradually tightening and economically efficient(Pataki et al., 2003). Strategic niche management (Kemp et al.,1998) and the model of lead markets (Beise-Zee and Rennings,2005) are other fields of research, partly linked to that of leadusers (von Hippel, 1994, 2005; von Hippel et al., 1999) to whichstudying the determinants of environmental innovationsmatters. A number of empirical studies have attempted toidentify such determinants at the level of the firm as well asfor aggregated industries (Jaffe and Palmer, 1997; Hemmels-kamp, 1999; Brunnermeier and Cohen, 2003; Ziegler andRennings, 2004; Rennings et al., 2005; Rennings et al., 2006).

Jaffe and Palmer (1997) analyse the influence of environ-mental expenditures on innovation activities based on paneldata for the U.S. manufacturing sector. They find a positiveinfluence of environmental expenditure on future research anddevelopment (R&D) expenditure, but not on the number ofpatent applications. However, Brunnermeier and Cohen (2003)criticise that the simultaneous influence of environmentalexpenditure on R&D expenditure and patent applications wasnotmodelledand that thenumberofpatentapplicationsdidnotfocus on environmental innovations only. Hemmelskamp(1999) analyses data from the Mannheim Innovation Panel of1993 based on ordered probit models with regard to theinfluence of a number of variables on five innovation objectiveswhich he identified bymeans of factor analysis, amongstwhichare “development of environmentally-friendly products”, “re-duction of environmental impacts fromproduction”, “reductionof energy input” and “improvement of working conditions”. Afocus of the analysis was an assessment of the influence ofenvironmental regulation on innovation activities. This wasmodelled using an index which evaluated separately for eachindustry in the sample towhich degree it is affected by differentregulatory instruments suchas taxesor standards. For example,for the development of environmentally-friendly products asignificant positive effect of taxes and a somewhat weakernegative influenceof standardsare found.These resultspoint tothe relevanceof environmental regulations for the realisation ofenvironmental innovations which in more general form is alsodiscussed by Porter and van der Linde (1995). Surprisingly, aninfluence of environmentally-oriented demand on the devel-opment of environmentally-friendly products could not beidentified, even though especially environmentally-oriented

consumers seem to be well-suited to be lead users for suchproducts (von Hippel, 1994, 2005). A limitation of the research ofHemmelskamp (1999) is that the underlying Mannheim Inno-vation Panel surveywhich generated the empirical datawas notspecifically oriented towards environmental innovations(Rehfeld et al., 2007). Rennings et al. (2005, 2006) analyse intheir broad-based empirical survey the effects of environmentalmanagement systems on firm-level innovation activities andcompetitiveness based on the European Eco-Audit and Man-agement Scheme (EMAS). Using survey data and detailed casestudies, they show that a stronger integration of innovation andenvironmental management can increase the competitivenessof firms. This finding is based on a telephone survey of 1277EMAS-validated firms. The analysis finds apositive effect on therealisation of environmental innovations and shows, that theenvironmental statements required under EMAS strengtheninformation spillovers in that they are used by other firms togenerate ideas for own environmental innovations. The find-ings also suggest that R&D departments should be integrated ina stronger way in the EMS development of firms in order to linkbetter corporate strategy and innovation activities. A mainconclusion from the study is therefore the need for betterlinkage of environmental and innovation management. Alimitation of the study is that data were only collected forEMAS-verified firms, thereby limiting the generalisability of theidentified determinants for environmental innovations to thepopulationof firms in theGermanmanufacturing sector. ZieglerandRennings (2004) inanother studyalsocast doubtonwhetherthe effects of EMS implementation are related to EMAS vali-dation, since they do not find a significant effect of the latter.Ziegler and Rennings (2004) analyse a sample of German firms(n=588)with regard to theeffect of EMSandof specificmeasuressuch as life-cycle analysis or existence of recycling systems onenvironmental product or process innovations. They are ap-plyingbinary probit andmultinomial logitmodels. In the caseofthe former, only certification according to ISO 14001 has asignificant positive effect on firms carrying out either environ-mental product or process innovations alone. In all other binarymodels (with product innovation only, process innovation onlyand simultaneous product and process innovation, respective-ly) neither ISO certification nor EMAS validation has an effect.Individual measures however do have a significant positiveeffect. These measures also have a significant positive associ-ationwith simultaneous product and process innovation in themultinomial logit models analysed. In these, also ISO 14001certification has a significant positive effect.

2. Model development and formulation ofhypotheses

This paper tests the hypothesis that environmental manage-ment systems (EMS) and particular managerial activities toreduce negative environmental impacts have a positiveinfluence on the probability of firms to pursue environmentalinnovations. There has been considerable research into theeffectiveness and efficiency of EMS in recent years (e.g.Hamschmidt and Dyllick, 2001; Rennings et al., 2003, 2006;Rennings et al., 2005). The general conclusions from thesestudies seem to be that ultimate effects of an EMS e.g. on firm

394 E C O L O G I C A L E C O N O M I C S 6 6 ( 2 0 0 8 ) 3 9 2 – 4 0 2

profitability or reductions in emissions to air or water or wasteproduction are not so large as to imply that emission or wastelevels significantly differ from those of firms without an EMS.On the other hand some authors do find evidence of positiveassociation of the degree of EMS implementation on lesstangible factors such as innovatory activity of firms (e.g.Hamschmidt and Dyllick, 2001; Rennings et al., 2005). Inaddition to this, van Dijken et al. (1999) and Biondi et al. (2002)find that environmental orientation of firms, as reflected inthe implementation level of environmental managementsystems is one important determinant for firms' environmen-tally-related innovation activities in small and medium sizedfirms, which make up an important proportion of the firms'analysed in this paper.

Avadikyan et al. (2001) point out that EMS act as acoordination mechanism and show based on case studiesthat EMS implementation can lead to environmental innova-tion. They also find, that EMS foster team-based approaches.Together with Llerena (1999) they relate this to learningmechanisms and processes of organisational learning thatare strongly oriented towards exploration (March, 1991) andhigher order learning (Argyris and Schön, 1978). This linkadditionally supports the view that EMS foster environmen-tally innovation. Also, Llerena (1999) as well as Porter and vander Linde (1995) discusses the possibility of organisationalfailure in terms of identifying profitable innovation opportu-nities and show that EMS can help to alleviate this. Thisimplies that EMS implementation should have a positiveeffect on firms' propensity to carry out environmentalinnovations, leading to:

Hypothesis 1. A higher level of EMS implementation by a firmresults in a higher propensity of that firm to carry out anenvironmental process or product innovation.

Whether this theoretically derived relationship can beidentified empirically can also depend on the way the level ofEMS implementation is measured. For example, Rehfeld et al.(2007) andZiegler andRennings (2004)measure implementationbased on whether firms have or do not have certification orverification according to ISO 14001 or EMAS, the EU Eco-Management and Auditing Scheme. This may be problematic,because asymmetric information may exist in the case of EMScertification that provides incentives for firms to behaveopportunistically (Russo, 2001). If it is very difficult for thirdparties to gather information about the level of environmentalperformance (including innovatory activity) of a firm with acertified EMS, then the firm may actually have a low level ofperformance, yet third parties may (erroneously) perceivecertification as a signal of high performance. In addition tothis, neo-institutional organisational theory (DiMaggio andPowell, 1983) suggests that certification is a symbolic gesturewith little influence on environmental innovations but rathermotivated out of institutional isomorphism and mimicrybehaviour.Whilst in this view, identification of the relationshippredicted in Hypothesis 1 may be difficult, the resource basedview (Wernerfelt, 1984) suggests that EMS implementationenables the development of strategic resources and competitiveadvantages resulting from these which have a positive influ-ence on firms' innovatory capabilities and thus on the extent ofenvironmental innovation. If only the resource based view

holds true, then EMS certification could be safely interpreted asa signal about competencies of the firm. However even thisbeing the case, the positive influence on innovatory capabilitiesandextent of environmental innovation is essentially causedbyEMS implementation and certification only credibly signals thisfact, but is not causally responsible.

From these considerations it becomes obvious that for thepurposes of testing Hypothesis 1, it would be desirable tomeasure the level of EMS implementation independent ofcertification since one cannot with certainty assume that onlythe resource based view holds, and that asymmetric informa-tion (leading to opportunistic behaviour) and institutionalisomorphism (leading to EMS being a purely symbolic gesturewithout performance effects) can be ruled out fully. Therefore,to measure the EMS influence independent of certification inthis research, an index variable was defined based on anumber of individual EMS elements. Measuring EMS imple-mentation this way is an improvement on the one hand inthat it does not relate to certification and on the other hand inthat it is a finer measure than a binary variable.

As noted earlier in the paper, product- or market-relatedfactors emerging fromextant literaturemaywell have apositiveinfluence on the propensity of firms to carry out an environ-mental process or product innovations, independent of theexistence of an EMS (regardless of whether certified or not). Inaddition to that, other organisationally-related factorsmay alsobe of relevance and have been identified in the literature (e.g.Strannegard and Boons, 2000). The factors considered here(based on Karl and Orwat, 1999; Noci and Verganti, 1999; Karland Orwat, 2000; Brío and Junquera, 2003; Lefevre et al., 2003;Pujari, 2006) are whether firms inform consumers aboutenvironmental effects of products and production processes(market-/product-related outbound marketing), if market re-search on the potential of “green products” is carried out(market-related inbound marketing), if firms use eco-labelling(Karl andOrwat, 1999; Karl andOrwat, 2000) or carry out productrecycling (product-related), if firmshave implemented life-cycleassessment (product-/organisationally-related) and if firmscarry out benchmarking activities (organisationally-related).For example, Dobers and Wolff (2000) point out that “green”consumers (including stakeholder pressures in a wider sense)represent a market pull that motivates firms towards environ-mental innovation and also Foster and Green (2002) concludethat environmental innovation dependsmuch on environmen-tally-driven users. This is not to say, that they are the exclusivefactor for such innovations, but that evaluating the preferencesof such consumers through market research and providingfeedback to the customers about the environmental quality ofthe resulting products and processes by means of informationdissemination and bymeans of signalling through eco-labellingseem to be important variables that are (as “soft” issues) morerelevant today compared to regulation, technological trajecto-ries or similar “hard” issues (Dobers andWolff, 2000). Recyclingsystems for a firm's products and life-cycle analysis have beenidentified as an important factor related to environmentalinnovation (e.g. Noci and Verganti, 1999; Lefevre et al., 2003;Sharma and Henriques, 2005; Pujari, 2006). For all of the abovevariables, respondents had to state whether their firm carriedout the measure or not and based on the literature, a positiveinfluence is expected on the propensity to innovate, leading to:

1 The full questionnaire can be accessed in English at www.agf.org.uk/pubs/pdfs/UK.pdf.


Hypothesis 2. There is an effect from a firm's adoption ofmanagerial activities not required to form part of a certifiedEMS in that informing customers, life-cycle assessment,market research on green products, recycling, benchmarkingand eco-labelling have an additional positive effect on a firm'spropensity to carry out an environmental process or productinnovation.

A difference of this research to earlier studies is that it usesenvironmental process and product innovations already carriedout by the firm (in the three years preceding the survey) as thedependent variable (any non-structural variables used asexplanatory variables also refer to this period of time). ZieglerandRennings (2004) point out that this could lead to problemsofendogeneity which could be reduced or avoided by usinginformation about environmental innovations planned infuture or by using lagged dependent variables. On the otherhand, using future-oriented statements implies greater uncer-tainty with regard to firms actually innovating in the way theystate and imply potentially higher response bias due to socialdesirability. These problems are avoided when using theinnovations already carried out as the dependent variable. Inaddition to this argument for my dependent variable, Rehfeldet al. (2007) find a very high correlation of environmentalinnovations carried out and planned in the case of both productand process innovations. Therefore results should be verysimilar regardless of whether planned or actual innovationsare used in the analysis.

Next to endogeneity issues, Ziegler and Rennings (2004)also perceive problems resulting from the influence environ-mental innovations have on specific environmental manage-ment activities. For example it may be rational for a firm tointroduce a recycling system (as a specific activity) only after ithas carried out an environmental product innovation becausethe recycling system is essentially part of the productinnovation. However, this is not necessarily the case, if forexample the recycling system is a generic one which can beapplied to a number of products (old and new) that the firmproduces. In this case, the existence of such a recycling systemprovides incentives for carrying out further environmentalproduct innovations (as long as it has not reached its capacitylimit) because these innovations enable the distribution of thesystem's operating cost across a larger product quantity. Asimilar line of argument also applies to eco-labelling as apredictor for environmental innovations and this makes anendogeneity bias unlikely. Also empirically endogeneity ofEMS implementation is not an issue for the data analysedhere. It was possible to survey a subset of 50 German firms onthe same EMS and environmental innovation variables as inthe initial survey for the period of 2003–2005. The analysis ofthis additional data shows that the EMS implementationvariable calculated for the activities carried out in 1998–2000 issignificantly correlated at the 1% level with environmentalprocess innovation activities in 1998–2000 (r=0.31, n=238) and2003–2005 (r=0.40, n=42) and with environmental productinnovation activities in 1998–2000 (r=0.18, n=219).

On the other hand, the EMS variable for activities carriedout in 2003–2005 is not significantly correlated at all withenvironmental (product or process) innovation carried out in1998–2000 but only weakly with environmental processinnovation activities in 2002–2005 at the 5% level (r=0.35,n=42). Therefore empirically there is no evidence of endo-

geneity issues in the data to be analysed in the next sectionwith regard to the hypotheses formulated.

3. Research method and analysis

3.1. Data set

The empirical analysis for which results are presented in thefollowing section is based on the data collected during theEuropean Business Environment Barometer (EBEB) survey. Thiswas a bi-annual survey on the state of environmental manage-ment inpractice carried out in several Europeancountries basedon a mail questionnaire. The questionnaire asked firms for aself-assessment of their main environmental effects andstakeholder demands; for their innovation and environmentalmanagement activities and for general information about thefirmand its structure.1 The data is basedon the last EBEB surveyround in 2001 carried out in nine European countries (Belgium,France, Germany, Hungary, Netherlands, Norway, Sweden,Switzerland, United Kingdom). Prior work provides somedescriptive results and some comparison of the effects thatseveral stakeholders have on the companies, the relevance ofdifferent management and technology measures as well asinfluences of strategy choice (Baumast and Dyllick, 2001).

In the 2001 EBEB round, almost 2100 firms in themanufacturing industries were surveyed Europe-wide basedon random sampling, corresponding to an average responserate of 26%. As concerns response bias, it is possible that thereplies received contain over-proportionally many firms thatare particularly active in terms of environmental manage-ment. Such a bias is a frequent problem of surveys based onwritten questionnaires (Armstrong and Overton, 1977). How-ever, in the case of the German responses, the characteristicsand response behaviour of early respondents was notsignificantly different from the late replies, based on thecomparison of means for all variables used between the firstand last 10% of respondents, except for a slightly higher levelof environmental activities of the latter. Also, there is nounique definition of environmentally-active/innovative firmsand earlier studies partly had relatively high numbers in theirsample. Rehfeld et al. (2007) categorised only 20% of theirrespondents as not carrying out environmental product orprocess innovations, whilst Hemmelskamp (1999) classifiedonly 33% and Ziegler and Rennings (2004) only 27% of theirrespondents as not being environmentally-innovative. With35% of respondents classified this way the research reportedhere has more firms that do not carry out any environmentalinnovations. As well, only 26% of the firms in this researchcarry out both, environmental product and process innova-tions, compared to 30% in Rehfeld et al. (2007), 31% in Zieglerand Rennings (2004) and 50% in Hemmelskamp (1999). Ifanything, this indicates that the data analysed here lead toresults that are more conservative than those of earlierstudies.

http://www.agf.org.uk/pubs/pdfs/UK.pdf

http://www.agf.org.uk/pubs/pdfs/UK.pdf

Table 1 – Multivariate probit model of product and processinnovation

Type of environmentalinnovation

Productinnovation

Processinnovation

Food and tobacco 0.14 (0.18) −0.02 (0.17)Textile products 0.62 (0.25)⁎ 0.19 (0.28)Leather products 0.44 (0.87) −0.07 (0.78)Wood products 0.48 (0.26)y −0.41 (0.25)Pulp and paper products 0.84 (0.25)⁎⁎ 0.33 (0.26)Publishing and printing 0.45 (0.23)y 0.003 (0.23)Energy, cokes and oil fuel 0.11 (0.62) −4.91 (0.24)⁎⁎⁎

Chemical products and fibres 0.69 (0.19)⁎⁎ 0.15 (0.19)Rubber and plastics 0.30 (0.20) −0.51 (0.19)⁎⁎

Non-ferrous mineral products 0.86 (0.31)⁎⁎ −0.29 (0.27)Machines and equipment 0.63 (0.19)⁎⁎ −0.08 (0.18)Electrical and optical equipment 0.70 (0.21)⁎⁎ −0.07 (0.20)Transport products 0.70 (0.28)⁎ −0.29 (0.26)Other manufacturing 0.52 (0.17)⁎⁎ −0.13 (0.16)Germany 0.52 (0.17)⁎⁎ 0.27 (0.16)y

Sweden −0.20 (0.15) 0.10 (0.14)Switzerland −0.08 (0.23) −0.44 (0.22)⁎

United Kingdom −0.20 (0.19) 0.12 (0.18)Hungary −1.28 (0.44)⁎⁎ 0.46 (0.39)France 0.02 (0.22) −0.01 (0.21)Belgium −0.12 (0.17) 0.12 (0.16)Norway −0.06 (0.20) −0.25 (0.19)Firm age 0.26 (0.13)⁎ −0.12 (0.13)Quality management system 0.09 (0.13) 0.04 (0.12)Firm size 0.04 (0.02) 0.03 (0.02)y

Company in sole proprietorship 0.14 (0.11) 0.08 (0.10)Environmental managementsystem index

0.05 (0.02)⁎⁎ 0.10 (0.02)⁎⁎⁎

Environment as competitive factor 0.70 (0.11)⁎⁎⁎ 0.20 (0.11)⁎

Constant −1.87 (0.30)⁎⁎⁎ −0.44 (0.28)No. of observations 849Log likelihood −1004.47Rprocess innovation, product innovation 0.26⁎⁎⁎Likelihood ratio test of correlation 19.70⁎⁎

Robust standard errors in parentheses; ypb0.10; ⁎pb0.05; ⁎⁎pb0.01;⁎⁎⁎pb0.001.


3.2. Regression model

The EBEB survey asked in two questions about environmentalproduct and process innovations in general (“green” design ofa new product in the years 1998–2000 and implementation ofcleaner technology during the same period). These were usedas the dependent variables in the research. Firms couldanswer these questions with “yes” or “no” or could choosethat a question was not applicable to their circumstances inwhich case they were excluded from the analysis. Based onthese dependent variables, the study applies binary andmultinomial discrete choice models (Greene, 2002; Hair et al.,1998). More specifically, in a first analysis step a multivariateprobit model (Greene, 2002: 714–719) was used which isappropriate when error terms are correlated, after theinfluence of the explanatory variables in the model isaccounted for (Greene, 2002: 717). This is the case when twobinary dependent variables can both occur simultaneously oronly one of them can occur and the other not.

In a second analysis step, a multinomial logit model wasestimated under the same conditions as the multivariateprobit model in order to identify the main determinants forthe progression in the level of innovatory activity (in terms ofwhether firms do not carry out any innovation at all, carry outexclusively product or process innovations, or pursue bothtypes of innovation simultaneously) beyond the innovationtype (product or process innovation). The independent vari-ables for all models were based on prior empirical work inindustrial economics (Schmalensee, 1989; Wagner, 1992; 1995;Nguyen Van et al., 2004), innovation economics (Ziegler andRennings, 2004; Tidd et al., 2005) and environmental manage-ment research (e.g. Russo, 2001; Brío and Junquera, 2003;Lefevre et al., 2003; Wagner and Schaltegger, 2004). Next toindustry membership and the environmental managementvariables already introduced in Section 2, they include asignificant number of explanatory factors such as countryorigin of a firm, firm size, existence of a quality managementsystem (a dummy variable taking the 1 if firm has ISO 9001)and firm legal structure.

Sectormembership ismeasured by dummyvariables basedon two-digit NACE codes with firms in the metal productssector being the reference group. EMS implementation isdefined as the sum of activities based on 10 elements (variablemean: 5.7; standard deviation: 3.5).2 The sum variable wasstrongly associated with another question asking for the EMSimplementation levels on a 4-point scale, which additionallyvalidates the measure. The variables for managerial activitiesnot required to form part of an EMS refer to agreement or not

2 The ten EMS elements are: written environmental policy,procedure for identification and evaluation of legal requirements,initial environmental review, definition of measurable environ-mental goals, programme to attain measurable environmentalgoals, clearly defined responsibilities, environmental trainingprogramme, environmental goals are part of a continuousimprovement process, separate environmental/health/safety re-port or environmental statement and audit system to checkenvironmental programme. The scale of the sum variable thusranges from zero (no activity carried out) to 10 (all listed activitiescarried out).

with whether the firm carries out market research on greenproducts; informs consumers about environmental effects ofproducts and processes; makes use of eco-labelling; asimplemented product life-cycle analysis, carries out bench-marking and carries out product recycling.

Country membership is measured using dummy variablesfor each country with firm location in the Netherlands beingthe reference group omitted in the regression. As concernsother control variables, firm size is measured by the logarithmof the number of employees (in thousands), firm age as thelogarithm of firm age in 2001 (in years) and firm legal status interms of a dummy variable taking unity value if the firm issolely owned. In addition to these variables, following Zieglerand Rennings (2004) I include a dummy measure taking thevalue of 1 if environmental aspects have competitive rele-vance for a firm.

Using these explanatory variables, I initially estimate amultivariate probit model with a more limited specification inorder to test Hypothesis 1 of Section 2 above alone, i.e.whether there is a significantly positive EMS influence on theprobability of environmental innovation activities (Table 1). Ithen use a more extended specification by adding the

Table 3 –Multinomial logit model of product and processinnovation


Product andprocess

Either productor process

Food and tobacco 0.17 (0.39) −0.08 (0.29)Textile products 1.15 (0.65)y 0.75 (0.49)Leather products 0.66 (1.03) −31.82 (0.93)⁎⁎⁎

Wood products 0.20 (0.55) −0.45 (0.47)Pulp and paper products 1.83 (0.66)⁎⁎ 1.19 (0.56)⁎

Publishing and printing 0.64 (0.48) −0.09 (0.42)Energy, cokes and oil fuel −31.34 (0.74)⁎⁎⁎ −1.16 (1.32)Chemical products and fibres 1.24 (0.43)⁎⁎ 0.56 (0.38)Rubber and plastics −0.41 (0.48) −0.27 (0.32)Non-ferrous mineral products 0.79 (0.65) 0.31 (0.55)Machines and equipment 0.75 (0.40)y 0.12 (0.32)Electrical and optical equipment 0.84 (0.43)y −0.06 (0.39)Transport products 0.44 (0.65) −0.08 (0.54)


variables used to operationalise Hypothesis 2 of Section 2additionally to the model (Table 2). This stepwise approachreveals if they have additional explanatory value for thepropensity to carry out environmental innovations beyond thevariables already included in the limited specification, asproposed by Hypothesis 2 in Section 2. Data for all countriessurveyed are pooled, whilst introducing a dummy variable foreach country to control for differences across countries.Because the benchmarking, product recycling and life-cycleassessment variables were not significant in all the modelspecifications, they were excluded from the final modelspresented here for reasons of parsimony.

For the second analysis step, instead of a multivariate, athree-category multinomial logit model is used which distin-guishesbetweenfirmscarryingoutneither anenvironmentally-related process nor a product innovation, firms that carry out

Table 2 –Multivariate probit model of product and processinnovation with managerial activity variables


Productinnovation

Processinnovation

Food and tobacco 0.08 (0.20) −0.04 (0.18)Textile products 0.41 (0.27) 0.13 (0.28)Leather products 0.39 (0.74) −0.007 (0.74)Wood products 0.04 (0.29) −0.53 (0.26)⁎Pulp and paper products 0.33 (0.30) 0.13 (0.27)Publishing and printing 0.23 (0.27) −0.17 (0.26)Energy, cokes and oil fuel 0.06 (0.49) −5.04 (0.22)⁎⁎⁎

Chemical products and fibres 0.59 (0.23)⁎⁎ −0.01 (0.20)Rubber and plastics 0.29 (0.22) −0.50 (0.20)⁎Non-ferrous mineral products 0.84 (0.32)⁎⁎ −0.27 (0.29)Machines and equipment 0.63 (0.21)⁎⁎ −0.07 (0.19)Electrical and optical equipment 0.54 (0.25)⁎ −0.15 (0.23)Transport products 0.77 (0.33)⁎ −0.33 (0.28)Other manufacturing 0.59 (0.19)⁎⁎ −0.13 (0.18)Germany 0.39 (0.19)⁎ 0.20 (0.18)Sweden −0.30 (0.17)y 0.08 (0.15)Switzerland −0.11 (0.25) −0.52 (0.24)⁎United Kingdom −0.49 (0.21)⁎ 0.04 (0.19)Hungary −1.12 (0.49)⁎ 0.35 (0.41)France −0.07 (0.25) 0.06 (0.23)Belgium −0.27 (0.19) 0.10 (0.17)Norway −0.05 (0.24) −0.29 (0.20)Firm age 0.24 (0.15) −0.15 (0.14)Quality management system 0.11 (0.14) 0.05 (0.13)Firm size 0.03 (0.02) 0.03 (0.02)Company in sole proprietorship 0.17 (0.12) 0.12 (0.11)Environment as a competitive factor 0.49 (0.13)⁎⁎⁎ 0.16 (0.12)Environmental managementsystem index

0.01 (0.02) 0.09 (0.02)⁎⁎⁎

Informing consumers (i) 0.52 (0.12)⁎⁎⁎ 0.13 (0.12)Market research on green products (ii) 0.90 (0.16)⁎⁎ 0.57 (0.15)⁎⁎⁎

Eco-labelling (iii) 0.66 (0.15)⁎⁎ −0.06 (0.14)Constant −1.90

(0.34)⁎⁎⁎−0.42 (0.29)

Observations 763Log likelihood −837.72Rprocess innovation, product innovation 0.19⁎⁎

Likelihood ratio test of no correlation 8.24⁎⁎

Test for joint significance (i)–(iii) 105.04⁎⁎⁎

Robust standard errors in parentheses; ypb0.10; ⁎pb0.05; ⁎⁎pb0.01;⁎⁎⁎pb0.001.

Other manufacturing 0.50 (0.36) −0.13 (0.30)Germany 1.10 (0.37)⁎⁎ 0.60 (0.33)y

Sweden −0.17 (0.32) 0.14 (0.26)Switzerland −0.79 (0.54) −0.32 (0.39)United Kingdom −0.12 (0.40) 0.26 (0.32)Hungary −1.04 (0.94) 0.37 (0.66)France −0.22 (0.54) 0.37 (0.39)Belgium −0.02 (0.54) −0.09 (0.30)Norway −0.49 (0.43) −0.18 (0.34)Firm age 0.19 (0.29) −0.13 (0.24)Quality management system 0.07 (0.28) 0.24 (0.22)Firm size 0.16 (0.09)⁎ 0.13 (0.09)Company in sole proprietorship 0.37 (0.23) 0.03 (0.19)Environmental managementsystem index

0.22 (0.04)⁎⁎⁎ 0.09 (0.03)⁎⁎

Environment as competitivefactor

1.26 (0.24)⁎⁎ 0.23 (0.21)

Constant −3.29 (0.67)⁎⁎ −0.59 (0.50)No. of observations 849Wald test 5669.81⁎⁎⁎

Log likelihood −812.77Pseudo R2 0.11

Robust standard errors in parentheses; base category is “neitherprocess nor product innovation”; ypb0.10; ⁎pb0.05; ⁎⁎pb0.01;⁎⁎⁎pb0.001.

exactly one of these two and firms carrying out both types ofenvironmental innovations. Again, the correspondingmultino-mialmodels are first estimated (in Table 3) based on the limitedmodel specification including only the EMS implementationvariable and subsequently (in Table 4) using the extendedspecification including again the three managerial activityvariables relating to activities not forming part of an EMSwhich were found to be significant in the regression models.

4. Results

Table 1 provides the results of the estimation withoutincluding managerial activity variables outside an EMS aswell as several important statistics providing informationabout the quality of the estimation. As can be seen, based onthe corresponding likelihood ratio (LR) test, the assumptionthat the error terms are uncorrelated can be rejected,confirming the use of a multivariate probit model being

Table 4 –Multinomial logit model of product and processinnovation with managerial activity variables


Product andprocess

Either productor process

Food and tobacco 0.04 (0.44) −0.18 (0.31)Textile products 0.87 (0.72) 0.44 (0.50)Leather products 0.69 (0.96) −33.81 (0.94)⁎⁎⁎

Wood products −0.73 (0.59) −0.84 (0.51)Pulp and paper products 0.83 (0.79) 0.72 (0.57)Publishing and printing 0.15 (0.62) −0.35 (0.45)Energy, cokes and oil fuel −33.19 (0.74) −1.17 (1.20)Chemical products and fibres 0.80 (0.49) 0.34 (0.40)Rubber and plastics −0.41 (0.50) −0.47 (0.35)Non-ferrous mineral products 0.91 (0.69) 0.18 (0.61)Machines and equipment 0.83 (0.46)y 0.12 (0.33)Electrical and optical equipment 0.53 (0.54) −0.18 (0.44)Transport products 0.53 (0.74) 0.12 (0.58)Other manufacturing 0.67 (0.40) −0.19 (0.33)Germany 0.84 (0.43)⁎ 0.60 (0.35)y

Sweden −0.33 (0.37) −0.01 (0.28)Switzerland −1.00 (0.61)y −0.50 (0.42)United Kingdom −0.73 (0.46) 0.13 (0.33)Hungary −1.58 (1.20) 0.19 (0.78)France −0.29 (0.61) 0.28 (0.41)Belgium −0.23 (0.41) −0.12 (0.32)Norway −0.52 (0.50) −0.42 (0.37)Firm age 0.12 (0.33) −0.16 (0.26)Quality management system 0.10 (0.32) 0.27 (0.23)Firm size 0.16 (0.10)y 0.13 (0.10)Company in sole proprietorship 0.51 (0.26)y 0.05 (0.21)Environmental managementsystem index

0.17 (0.05)⁎⁎⁎ 0.07 (0.03)⁎

Environment as a competitivefactor

0.95 (0.28)⁎⁎ 0.12 (0.23)

Eco-labelling (iii) 0.86 (0.33)⁎⁎ 0.25 (0.28)Informing consumers (i) 0.98 (0.27)⁎⁎ 0.40 (0.22)y

Market research on greenproducts (ii)

2.20 (0.40)⁎⁎ 1.17 (0.38)⁎⁎

Constant −3.45 (0.79)⁎⁎⁎ −0.52 (0.54)Observations 762Wald test 6693.89⁎⁎⁎

Log likelihood −678.89Pseudo R2 0.17Test for joint significance (i)–(iii) 75.73⁎⁎⁎

Robust standard errors in parentheses; base category is “neitherprocess nor product innovation”; ypb0.10; ⁎pb0.05; ⁎⁎pb0.01;⁎⁎⁎pb0.001.


more appropriate than estimating two independent binaryprobit models. In addition, the model is overall significant.

Table 2 provides results after inclusion of the threeadditional variables for the managerial activities going beyondthose linked to EMS implementation. Again, this extendedmultivariate probit model is overall significant and the hypoth-esis of (weakly) correlated error terms cannot be rejected.

4.1. Industry effects in the multivariate probit model

I find that a number of industry dummies which have beenincluded to address industry-specific effects are significant forboth environmental product as well as process innovations inthe limited multivariate probit model including only the EMSvariable. Industry effects become somewhat weaker in theextended multivariate probit model, but where they remainsignificant it is for the same sectors as in the limited model.

4.2. Environmental management effects and hypothesistesting in the multivariate probit model

The most important finding is that Hypothesis 1 can beconfirmed in the limitedmultivariate probitmodel in that EMSimplementation has a significant positive effect on bothproduct and process innovations. Opposed to this, the EMSvariable is in the extended multivariate probit model onlysignificantly positive for process innovations.

To test Hypothesis 2 which proposes that there is an effectbeyond EMS implementation from a firm's adoption ofmanagerial activities not required in an EMS is the purposeof the extended multivariate probit model. These activitieswere the information of customers, market research on greenproducts and eco-labelling. All three have an additionalpositive effect on a firm's propensity to carry out anenvironmental product innovation, which is strongest formarket research, and the latter has also a positive effect onprocess innovations.

4.3. Country effects in the multivariate probit model

The strongest significant country effect in the limitedmultivariate probit model is the one for Germany, which ispositive for process and product innovations. For Hungary andSwitzerland significant negative effects are found. The stron-gest significant country effect in the extended multivariateprobit model is again found for Germany but is now onlypositive for product innovation. As before, significantlynegative effects for Hungary and Switzerland, but also forthe United Kingdom are found.

The second approach to analyse the hypotheses in theempirical analysis identifies the determinants under whichenvironmental product and process innovations are carriedout separately or simultaneously, using the same explanatoryvariables as before. The results are summarised in Tables 3and 4.

4.4. Industry effects in the multinomial logit model

As for the multivariate probit model, also in the multinomiallogit model significant industry effects exist. For firms in the

paper and chemicals industries these are positive in thelimited model for firms carrying out process and productinnovations simultaneously, whereas for the energy industryit is negative. Only the paper industry dummy has also apositive effect for firms carrying out exactly one type ofinnovation (either product process), and here also the leatherindustry has a significant effect which is however negative.This changes in the extended multinomial logit model in thatonly the negative effect for the leather industry remainssignificant, indicating that the additionally introduced vari-ables pick up some of the variance that previously was in theindustry dummies.


4.5. Environmental management effects and hypothesistesting in the multinomial logit model

As can be seen in Table 3 for the (limited) model withoutactivity variables a significant positive association with theprobability to simultaneously carry out “green” productdevelopment and to implement cleaner technology (relativeto carrying out no environmental innovation) is found forEMS implementation as is a positive association of EMSimplementation with whether firms carry out either prod-uct or process innovation, relative to firms not carrying outany environmental innovation at all. In the extendedmultinomial logit model, the association of the EMSimplementation level weakens considerably for both simul-taneously and separately carrying out process and productinnovation.

4.6. Country effects in the multinomial logit model

For the limited multinomial logit model, Germany has asignificant positive influence (relative to the Netherlands) onboth firms carrying out simultaneous product and processinnovations and on firms carrying out only one of themrelative to carrying out no environmental innovations at all.For the model based on the extended specification (includingthe managerial activity variables) it is found that the effect forGermany on simultaneous product and process adoptionrelative to no adoption weakens (compared to the limitedspecification) from 1.11 to 0.85, whereas that for carrying outone of the two types of innovation (relative to none) staysalmost the same.

5. Discussion

Two hypotheses were tested in this research in two analysissteps, based on multivariate and multinomial probit/logitmodels. Hypothesis 1 was that EMS implementation (inde-pendent of EMS certification) has a positive effect on firmscarrying out environmentally-related product or processinnovations. This could be confirmed in the multivariateprobit model, indicating that EMS implementation likelytriggers more systematic search processes for environmen-tal innovation and seems to lead to learning processestriggered by the implementation of an EMS. However, thisneeds to be qualified for the multivariate probit modelas Hypothesis 2 was confirmed especially for productinnovations.

The difference of the effects of EMS between themultivariate probit and multinomial logit model is explainedby the different combination of product or process innova-tions in both models. The stylized fact common to bothmodels is however, that when additional variables measur-ing activities not required in an EMS are involved, thesignificance of EMS becomes less or even disappearscompletely for product innovation, indicating that theadditional variables are better predictors taking awayvariance explained from the EMS variable especially forproduct innovations. This stylized fact was also confirmedwith a more recent, smaller data set of firms in Germany

(n=134) surveyed in 2006–2007, and again a decrease in theexplanatory value of the EMS variable was observed whenbinary variables for informing customers, use of eco-labelsand market research were included in the model estimation.The results of this recent validation study are not reportedhere for brevity, but are available from the author on request.In the case of the multinomial logit model the estimationrefers (other than in the multivariate probit model) in bothcases to a joint process-product innovation variable. There-fore the remaining association found for EMS is stronger(and thus remains significant, but at lower levels and with alower strength of the association compared to the multivar-iate logit model in which the association on productinnovation is isolated), but this does not contradict thestylized fact described above and the insight that EMS seemto mainly associate with process innovation.

This change of the EMS implementation level in theextended multivariate/multinomial probit/logit modelsmeans that product innovation is associated with themanagerial activity variables, rather than EMS implementa-tion. In the case of the additional activities, the strongesteffect was found for market research, followed by eco-labelling and informing consumers and market research alsohad an effect on process innovation. In the following I discusscausal mechanisms that can explain why the managerialactivity variables, rather than EMS implementation, areassociated with product innovation.

Market research on “green” products likely leads to a betterunderstanding of profitable demand for product innovationswith environmental benefits, for example in cooperation withlead users. As well, it enables firms to identify environmen-tally-oriented customer segments. Therefore, its strong pos-itive effect on environmental product innovations can beexplained well. The additional effect on process innovations ismore surprising, it may however be explained by the fact thatan environmental product innovation can also imply changesin the production process required. Rubik and Teichert (1997,p. 24) suggest that for reasons of reputation and credibilityfirms forcing environmental product innovation also need toshow above-average environmental performance in produc-tion which may imply simultaneous promotion of environ-mental process innovations.

Experience with eco-labelling may result into betterknowledge about the benefits of this activity. If a firm hasalready positive experiences with eco-labelling then itsincentive to develop environmentally-sound products whichare suitable for labelling should increase and this can explainthe observed positive effect of eco-labelling on environmentalproduct innovations. This is because from the perspective ofcustomers, the choice is essentially one between productswith or without an eco-label. For example, whilst in the case ofelectricity (discussed e.g. by Truffer et al., 2001), the environ-mental quality is actually brought about by the productionprocess (production of electricity through photovoltaic pro-cesses or using biomass), the customers choose betweenelectricity tariffs as products. Also, e.g. in the case ofappliances, the product is exclusively the focus of eco-labelling (Banerjee and Solomon, 2003). Reverse causalitycannot be ruled out completely in the case of eco-labellingwith the data at hand (since this would require panel data).


Yet, since in half of all theoretically possible sequences ofinnovation and labelling (which each can take place in 1998,1999 or 2000), the product innovation takes place before eco-labelling at least some positive effect from prior eco-labellingexperiences on environmental product development can beexpected and can thus explain the significant positive effectobserved empirically.

Finally, it has been argued that for labels to be effective,organisations need to enter into a dialogue with customers orother stakeholders to learn about societal expectations thatneed translation into business practices certified throughlabelling (Boer, 2003). This implies that eco-labelling is inmany ways essentially a learning process and strengthens theargument that it leads to innovation when what was learnedgets implemented.

The third managerial activity variable introduced is that ofinforming consumers on environmental effects of productsand production processes. Doing so may induce additionaldemand if an environmentally-oriented customer segmentexists and therefore increases the incentive and thus theprobability of a firm carrying out an environmental productinnovation. Again reverse causality cannot be ruled out in thatinformation provision can happen before or after the productinnovation is carried out. However, in the latter case, no effecton the propensity to carry out a product innovation shouldexist, and therefore the joint effect should be positive but maybe understated if in many cases information took place afterthe product innovation, i.e. the reported coefficient is conser-vative in this sense. Nevertheless, the empirical result can beexplained by this logic. Also, the insignificant effect on processinnovations of informing consumers is plausible, since theirdecisions focus on products and even in the case ofinformation about production processes, these will manifestin buying a particular product for which some relatedimprovement of the production process took place.

An important finding of this research is also that the use ofEMS certification as a measure for EMS implementation (ratherthan an activity-based measure as used here) is a possibleexplanation for its insignificant effect on environmentalinnovations in other empirical studies (e.g. Ziegler andRennings, 2004). EMS basically work through their implemen-tation level but not bymeans of certification which either takesplace after implementation or evennot at all. In order to directlytest the role of certification, the regressionmodelswere also runwith additional dummy variables for EMAS and ISO 14001certification included. The certification dummies where insig-nificant for both, product and process innovations, regardless ofwhether EMAS or ISO certification is considered. Also nosignificant associations were identified for an of interactionterm of the certification dummy and the original EMS imple-mentation variable which was additionally introduced in themodel. This confirms the initial argument that implemen-tation is potentially a less confounded measure than EMScertification.3

3 I am particularly grateful to one referee for pointing out thepossibility of more direct testing of the argument concerningcertification. The results of the respective estimations are notreported here for brevity, but are available from the author onrequest.

The motivation for the second analysis step is that therelevance of factors may differ depending on whether firmscarry out either environmental product or process innovation,neither of them, or both. Therefore, in the second analysisstep, I apply a multinomial logit model to the data, results ofwhich are reported in Section 4. In line with the results of thefirst analysis step, I find that both, EMS implementation leveland the different managerial activities outside of it have alsopositive effects on simultaneous realisation of environmentalproduct and process innovation.

As concerns the limitations of the study, variation inresponse rate by countries, self-selection of respondents andself-assessment need to be acknowledged. However, asconcerns response rate variations as an indication of possibleself-selection, other than low responses of small firms(implying that the replies received contain over-proportion-allymany firms of larger size), no systematic non-response ofspecific groups of firmswas found. Self-assessment ismainlya concern in terms of common method bias, but testing forthis using Harman's single factor test indicated that this isnot an issue. Also, a number of procedural steps whereundertaken during the preparation and implementation ofthe survey to minimise the risk of common method biasoccurring.

In addition to these limitations the European focus of theanalysis needs to be acknowledged as one feature of theresearch that may limit transferability of the findings in lightof the institutional differences to other regions. A Europeanfocus on the other hand is complementary in that much ofthe research to date has been carried out on US data. Thecountry differences identified with regard to environmentalinnovation indicate, that in Germany above-average levels ofenvironmental innovation are found, whereas in Switzer-land, Hungary and the UK environmental innovation levelsare below average, especially with regard to environmentalproduct innovation. The significantly higher levels in Ger-many, relative to other European countries are likely relatedto the more stringent environmental regulation there. Also,liberalization in some important areas of the economy couldexplain the above-average performance in Germany (see e.g.Markard and Truffer (2006) for an account of how innovationpractices can change due to sector deregulation). The lowerlevels of environmental innovation in Switzerland for bothproduct and process innovation could be related to thepredominance of the service sector (especially banking andinsurance) in the Swiss economy. Given this predominance,manymanufacturing firms in Switzerland are subsidiaries ofinternational firms which makes embodied environmentaltechnology transfer (rather than innovation activity in thesubsidiary) more likely (Lanjouw and Mody, 1996; Rabbiosiet al., 2007). Similar arguments apply to Hungary, where after1990 the industrial sector was largely rebuilt through foreigndirect investment of multinational corporations and relatedembodied environmental technology transfer (e.g. Rondi-nelli and Vastag, 1999). For the UK, it seems that the lessstringent regulatory environment is an important explana-tory factor. Finally, the binary dependent variable used inthis analysis could certainly be improved upon. For example,it could help to have at least an ordinal evaluation or evendata on environmentally-related patenting activities of


firms.4 However, collecting ordinal data on environmentalinnovations was considered to have a negative influence onthe response rate to the survey, given its already consider-able length. Also, no agreed definition exists of whatenvironmentally-related patenting consists of and agreeingon such a definition was unfortunately beyond the scope ofthe paper. Nevertheless future research could improve uponand hopefully confirm the findings reported here with moredetailed measures of environmental innovation activities.5

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