Journal of Environmental Management

Journal of Envronmental Management 90 (2009) 3057 3069 Contents lsts avalable at ScenceDrect Journal of Envronmental Management journal homepage: www.elsever.com/locate/jenvman Sustanable value assessment of farms usng fronter effcency benchmarks Steven Van Passel a, *, Gudo Van Huylenbroeck b, Ludwg Lauwers c, Erk Mathjs d a Centre for Envronmental Scences, Hasselt Unversty, Agoralaan, Buldng D, Depenbeek 3590, Belgum b Department of Agrcultural Economcs, Ghent Unversty, Belgum c Insttute for Agrcultural and Fsheres Research, Socal Scences Unt, Belgum d Dvson of Agrcultural and Food Economcs, Catholc Unversty of Leuven, Belgum artcle nfo abstract Artcle hstory: Receved 24 May 2007 Receved n revsed form 8 March 2009 Accepted 16 Aprl 2009 Avalable onlne 23 June 2009 JEL classfcaton: Q56 Q57 Q58 Q51 Q12 Keywords: Sustanablty performance Sustanable value Effcency Performance assessment Fronter method Benchmarks Approprate assessment of frm sustanablty facltates actor-drven processes towards sustanable development. The methodology n ths paper bulds further on two proven methodologes for the assessment of sustanablty performance: t combnes the sustanable value approach wth fronter effcency benchmarks. The sustanable value methodology tres to relate frm performance to the use of dfferent resources. Ths approach assesses contrbutons to corporate sustanablty by comparng frm resource productvty wth the resource productvty of a benchmark, and ths for all resources consdered. The effcency s calculated by estmatng the producton fronter ndcatng the maxmum feasble producton possbltes. In ths research, the sustanable value approach s combned wth effcency analyss methods to benchmark sustanablty assessment. In ths way, the producton theoretcal underpnnngs of effcency analyss enrch the sustanable value approach. The methodology s presented usng two dfferent functonal forms: the Cobb Douglas and the translog functonal forms. The smplcty of the Cobb Douglas functonal form as benchmark s very attractve but t lacks flexblty. The translog functonal form s more flexble but has the dsadvantage that t requres a lot of data to avod estmaton problems. Usng fronter methods for dervng frm specfc benchmarks has the advantage that the partcular stuaton of each company s taken nto account when assessng sustanablty. Fnally, we showed that the methodology can be used as an ntegratve sustanablty assessment tool for polcy measures. Ó 2009 Elsever Ltd. All rghts reserved. 1. Introducton Sustanable development s now an mportant prorty for many countres. Two economc paradgms of sustanable development can be dstngushed: weak sustanablty and strong sustanablty. Weak sustanablty s based on the dea that natural captal can to a certan extent be substtuted as a drect provder of utlty for the producton of consumpton goods. However, proponents of the strong sustanablty vew refuse ths paradgm because they regard natural captal as non-substtutable. Whle weak sustanablty could be seen as an extenson to neoclasscal economcs, strong sustanablty calls for a paradgmatc shft away from neoclasscal envronmental and resource economcs towards ecologcal economcs (Neumayer, 2003). Ecologcal economcs sees the human economy as part of a larger web of nteractons between economc and ecologcal sectors (Constanza et al., 1991). Adherents * Correspondng author. Tel.: þ32 11 26 87 46. E-mal address: steven.vanpassel@uhasselt.be (S. Van Passel). of the weak sustanablty paradgm favour margnal forms of analyss and tend to pay less attenton to the concepts of the scale of an economy n relaton to ts resource base (Norton and Toman, 1997). Daly (1990) was an mportant archtect of the strong sustanablty vew that advocates that resource substtutablty s very lmted and the sustenance of specfc resource sectors s mportant (Pezzey and Toman, 2002). Daly (1991) states that: Just as frms or households of the economy operate as a part of the aggregate economy, so the aggregate economy s lkewse a part of a larger system, the natural ecosystem. Therefore, optmal allocaton of a gven scale of resource flow wthn the economy s one thng; optmal scale of the whole economy relatve to the ecosystem s an entrely dfferent problem. The sustanable value approach developed by Fgge and Hahn (2004a, 2005), on whch ths paper bulds, leaves the total amount of each resource unchanged on the macro level and t can therefore be seen as an approach to measure strong sustanablty. The focus s on the scale of an economy or part of an economy n relaton to ts resource base. In addton, the sustanable value approach can be seen as a value-orentated mpact assessment of economc 0301-4797/$ see front matter Ó 2009 Elsever Ltd. All rghts reserved. do:10.1016/j.jenvman.2009.04.009

3058 S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 actvtes (Fgge & Hahn, 2004b). Value-orentated approaches ntegrate economc, envronmental and socal aspects wth respect to the return that they generate rather than the burden that they cause, and analyse how much value s foregone when a bundle of resources s used. In other words, the value-orentated approach can gude where resources should be allocated; t addresses the queston how much value would have been created wth a specfc set of resources f they had been used by more sustanable effcent frms (real companes or not). Note that other approaches use a burden-orentated logc by concentratng on dfferent envronmental (and socal) mpacts n order to measure the overall damage ( the burden ) caused by economc actvty (e.g., Pretty et al., 2000; Tegtmeer and Duffy, 2004). Burden-orentated approaches focus on the relatve harmfulness of envronmental and socal mpacts. In other words, burden-orentated approaches analyse how resources should be substtuted by each other by assessng the combnaton of envronmental mpacts compared to another set of envronmental mpacts. In our research contrbuton, we propose an approach that prefers a lower resource use to a hgher resource use, all other thngs beng equal, because n ths way we can produce the same amount of output (e.g. food) wth a smaller amount of resources (e.g. labour, captal, energy/water use, carbon doxde emsson, etc.). In other words, we am to use the most sustanable combnaton of resources wthn systems. In fact, less sustanable resource use should be (partly) substtuted by more sustanable resource use. However, t s also mportant to analyse and to compare sustanablty between systems. Improvements n sustanablty may also be found by means of substtutng companes that use ther resources n an unsustanable way by companes that use ther resources n a more sustanable way. The valueorentated sustanable value approach therefore assesses sustanablty between systems by comparng the resource productvty of a system wth the resource productvty of a benchmark (¼the opportunty cost) and ths for all resources consdered. Polcy makers and company managers can use the sustanable value approach to measure, montor and communcate ther sustanablty performance. Furthermore the sustanable value approach can be used to dentfy characterstcs of out- and underperformers (as n Van Passel et al., 2007; Hahn et al., 2007). Moreover, future performance scenaros can be constructed to compare possble frm or polcy actons. Polcy makers can use the smulaton results to take well founded decsons wthn a sustanablty framework. The choce of the most approprate benchmark s mportant, especally wthn the scope of polcy analyss but also for choosng the approprate actons to realse the frm objectves. Hence, usng best performance or performance targets of each resource as a benchmark can be very useful to analyse the efforts of frms n ther am to reach sustanablty (Van Passel et al., 2007). To determne the frms benchmark, fronter methods can be appled. Such methods can be used to assess sustanablty wthn systems (as n Renhard et al., 2000). Ths research wll use fronter methods to determne the sustanable value, and thus to assess sustanablty between systems (or companes). Fronter methods (and effcency analyss) can reveal lnkages between the output and the resources used by frms, and n that way enrch the sustanable value approach. The approach compares the resource productvty of a company wth the maxmum feasble resource productvty of that company. In the followng secton (Secton 2) the theoretcal background s formulated and the research objectves are explaned. In a thrd secton, the theoretcal ntegraton of fronter methods wth the sustanable value approach s explaned usng two functonal forms. In Secton 4, the proposed methodology s appled usng two emprcal applcatons (one for each functonal form). Furthermore, the possblty of usng the approach to support polcy makng s tested on a dataset of Flemsh dary farms. Fnally n Secton 5, conclusons and suggestons for further research are made. 2. Theoretcal background Economc, socal and envronmental effcency can be seen as a necessary but not suffcent step towards sustanablty (Callens and Tyteca, 1999; Templet, 2001). Sustanablty can be enhanced by strateges whch promote resource use effcency n economc systems (Templet, 1999). Effcent use of resources forms the keystone of polcy, plannng and busness approaches to sustanable development but there are a wde range of potental nterpretatons of the effcency concept (Jollands, 2006a,b). Jollands and Patterson (2004) show that effcency s mportant wthn economcs, thermodynamcs and ecology wth the consequence that the term represents a multplcty of meanngs (Jollands, 2006a). Note that all effcency concepts are relatve and context-dependent (Sten, 2001). Several concepts of effcency are used n our methodology (e.g., techncal effcency, productvty, eco-effcency). In order to avod msunderstandng, we start by explanng these concepts n Secton 2.1. After defnng the effcency key concepts, the sustanable value approach and the objectves of the research are explaned. 2.1. Defnng key concepts There are several defntons of productvty, effcency and ecoeffcency. In our research commonly accepted defntons wthn producton economcs are used. Productvty s calculated by dvdng output by nput. Farell (1957) defnes effcency as the actual productvty of a company compared to the maxmum attanable productvty. Besdes productvty and effcency, one can measure performance also n terms of eco-effcency. A broadly accepted crteron for corporate sustanablty s the eco-effcency measure (e.g., Schmdheny, 1992; OECD, 1998; WBCSD, 2000). Eco-effcency, standng for a better management of the economy wth less envronmental pressure, s a well-known sustanablty approach (Bleschwtz and Henncke, 2004). There s a wde and dverse varety of termnology referrng to eco-effcency. A well-known defnton of eco-effcency s the rato of created value per unt of envronmental mpact. In fact, ths varant of eco-effcency can be seen as envronmental productvty (Huppes and Ishkawa, 2005), and s smlar to the defnton of productvty n economcs. So far, we used the terms nput and output. Output can be expressed as total producton (total revenue) or as value added (total output mnus ntermedate consumpton). To obtan value added as output, economcs tradtonally dstngushes land, labour and captal goods as nputs. These nputs are also called factors of producton, whch are resources used n the producton of goods and servces n economcs. In a more or less smlar way, the concept of captal can be used to dentfy resources used to produce output. Land, captal goods and labour can be seen as captal forms. In order to assess corporate sustanablty, a much broader nterpretaton of the concept of captal than tradtonally used by economsts, s needed (Dyllck and Hockerts, 2002). Pfeffer and Salanck (1978) defne a resource as the means that an organsaton needs n order to survve. In fact, the core argument of ther resource dependency theory states that () organsatons wll respond to demands made by external actors or organsatons upon whose resources they are heavly dependent and () organsatons wll try to mnmze that dependency when possble (Pfeffer and Salanck, 1978; Pfeffer, 1982). Frooman (1999) even states that the resource dependency theory defnes a resource as bascally anythng an actor perceves as valuable. In the language of tradtonal strategc analyss, frm

S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 3059 resources are strengths that frms can use to conceve of and mplement ther strateges that mprove ther effcency and effectveness; frm resources nclude all assets, capabltes, organsatonal processes, nformaton, knowledge, etc. (Barney, 1991). Therefore, we do not make any dstncton between conventonal economc resources (nputs or producton factors) and envronmental and socal assets. Physcally speakng, certan envronmental assets are (undesred) outputs rather than nputs. However, because companes do have an envronmental mpact n the producton of value-added goods, these envronmental aspects can be seen as resources from an economc pont of vew (Fgge and Hahn, 2005). Mnd that the effectve management of the use of all resources s crucal n provdng sound economc performance. Furthermore, Claver et al. (2007) stress that the connecton between envronmental management and economc performance should be seen n a broader perspectve that ncludes the relatonshp between envronmental strategy and frm performance. Also SMEs undertake a range of envronmental strateges from reactve regulatory complance to proactve polluton preventon and envronmental leadershp (Aragón-Correa et al., 2008). Porter and Van der Lnde (1995a,b) state that ncreasng nvestment n envronmental technology can obtan a compettve advantage, whle reducng the negatve envronmental mpact. The so-called Porter Hypothess gave rse to an nterestng scentfc dscusson about the exstence of wn wn opportuntes (e.g. Murty and Kumar, 2003), possbltes of envronmental regulaton, spllover effects of envronmental performance on productvty (e.g. Galdeano-Gómez et al., 2008), strategc qualty competton (e.g. André et al., 2009), etc. In the context of ths paper, the focus wll le on the ntegrated assessment of envronmental and economc performance, although we recognze the mportant nterlnkage wth (frm) strategy. We wll call all captal forms (or aspects derved from captal forms) n the remander of ths paper resources, because we assume that they all contrbute to the producton of value added n a system. We use the term resources over the terms nputs or producton factors or captal forms (economc, socal and envronmental) to ndcate the assets that are used to create value n a broad context. A more detaled dscusson about the treatment of envronmental and socal resources as nputs or as undesred outputs falls beyond the scope of ths paper. We refer for ths to Färe and Grosskopf (2003) and Halu (2003). 2.2. The sustanable value approach The sustanable value approach s developed by Fgge and Hahn (2004a, 2005) and apples the logc of opportunty costs to the valuaton of resources. Usng the captal approach (e.g., Atknson, 2000), all resources (economc, envronmental and socal) are needed to create value. Usng the sustanable value approach, we consder that a frm contrbutes to more sustanable development whenever t uses ts resources more productvely than other companes and the overall resource use s reduced or unchanged. The followng steps are requred to calculate the sustanable value of a company. Frst, the scope of the analyss needs to be determned. In other words, whch economc actvty or actvtes or entty or enttes wll be chosen? Second, the relevant resources to take nto account (e.g., labour and land) need to be determned. Theoretcally, the choce should nclude those resources that are crtcal for the sustanablty performance of the company wthn the chosen scope. Thrd, the benchmark level needs to be determned. The choce of the benchmark determnes the cost of the resource needs of a company, n other words the productvty that a company has to exceed. The benchmark choce reflects a normatve judgement and determnes the explanatory power of the results of the sustanablty assessment. Table 1 shows the calculaton of the sustanable value for a dary farm wth a value added of V 80 000. Ths company represents a dary farm wth 55 mlk cows, 30 ha of land and a mlk quota of 300 000 ltres. The amount used of every resource can be found n column A of Table 1. The productvty (or return on captal) of each resource can be calculated (column B). For example, the return on land s V 2667 per hectare of land (V 80 000/30 ha). In the same way the productvty of the benchmark (column C) can be determned, these are the opportunty costs. In ths example, we choose as benchmark the average return on captal of a large sample of dary farms (as n Van Passel et al., 2007). For the farm gate N-surplus, we choose a performance target (150 kg N/ha) as benchmark, whch s an objectve performance target for sustanable dary farmng n Flanders (Nevens et al., 2006). N-surplus s calculated as the N-nput (e.g. concentrates, straw) mnus the Ntrogen off take (e.g. mlk, crops) at the farm gate. Note that Langeveld et al. (2007) stress the mportance that to evaluate farm performance N-surplus should be supported by other ndcators or model calculatons. Agr-envronmental ndcators should be appled n an ntegrated evaluaton (such as the sustanable value approach), at a scale that reflects the frm s spatal varablty (Langeveld et al., 2007). In ths context, farm typologes (e.g. specalst grazng lvestock) can serve as an nterestng tool for comprehensve assessment (Andersen et al., 2007). In a next step, the value contrbutons of each resource can be calculated ((B C) AnTable 1). A postve value contrbuton ndcates that the resource s used n a value-creatng way by that company. Ths means that a postve value contrbuton s only obtaned f the resource productvty of the frm s hgher than the resource productvty of the benchmark. In other words, resources are only used n a value-creatng way f the opportunty costs of the resources are at least covered. To determne how much value s created by the entre bundle of resources, the sustanable value can be calculated by summng up all value contrbutons and by dvdng ths value by the number of resources. The sustanable value approach ndcates how much more or less return has been created wth the resources avalable n comparson wth the benchmark. To take the company sze nto account, ADVANCE (2006) suggests calculatng the return-to-cost rato. Ths rato was called sustanable effcency n Fgge and Hahn (2005) and n Van Passel et al. (2007), but the term return-to-cost termnology s more consstent wth the effcency and productvty concepts. The return-to-cost rato s calculated by dvdng the value added of a company by the cost of the sustanablty captal. The cost of sustanable captal s gven by the dfference between the value added and the sustanable value. The return-to-cost rato equals unty f the value added corresponds to the cost of all resources. A return-to-cost rato hgher than one means that the company s overall more productve than ts benchmark. In our example the return-to-cost of the farm s 1.04 (¼V 80 000/(V 80 000 V 3067)). Table 1 Example of the calculaton of the sustanable value. Resources a Amount used Productvty by the company (80 000/A) Value contrbuton (V) (A) Company (B) Benchmark (C) Land 30 ha 2666.67 2600.00 2000.00 Labour 1.00 fte 80 000.00 50 000.00 30 000.00 Non-land captal 300 000 Euro 0.27 0.27 0.00 Energy use 1000 000 MJ 0.08 0.07 10 000.00 N-surplus 6000 kg N 13.33 17.78 26 680.00 Sustanable value ¼ 3064.00 Fte: full tme equvalent. a Remnd that we defne resources as captal forms (economc, envronmental and socal) or aspects derved from captal forms.

3060 S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 The return-to-cost rato shows by whch factor the farm exceeds or falls short of coverng ts cost of economc, envronmental and socal resources or n other words by whch factor t exceeds or falls short of the benchmark productvty. Remember that the sustanable value approach does not clam that the benchmark s sustanable. In other words, the approach does not ndcate whether the overall resource use s sustanable, but only how much a company contrbutes to a more sustanable use of ts resources than the benchmark. Another drawback s that the utlty of the methodology s lmted by the avalable data on corporate captal use and the opportunty cost of the dfferent resources (Fgge and Hahn, 2005). Moreover, even f certan aspects are measurable, t s not always straghtforward how to take these aspects nto account. An nterestng example s farm subsdes. Van Passel et al. (2007) found that the more a farm depends on subsdes, the lower the return-to-cost rato. In Van Passel et al. (2007) farm subsdes are seen as an mportant determnant to explan dfferences n sustanablty performance. However, another possblty s to use subsdes to calculate the sustanable value by assumng that subsdes are relevant resources to realse value added. Another drawback of the sustanable value approach s the fact that t does not take qualtatve aspects of sustanablty nto account. All relevant aspects should be quantfed n a meanngful way. However, the sustanable value approach allows ntegratng economc, envronmental and socal performance. Rather than lookng at how burdensome the use of resources s, t compares the value that can be created wth the resource by dfferent economc actors. The sustanable value approach s the frst value-based methodology that allows an ntegraton of dfferent resources of companes and thus can be used to compare sustanablty between companes. 2.3. Objectves As already explaned, the choce of the most approprate benchmark s essental when usng the sustanable value approach, because the benchmark determnes the opportunty costs of each relevant resource. Moreover, the choce of the benchmark depends on the partcular research objectve. For example to assess the sustanablty performance of BP, Fgge and Hahn (2005) used the UK economy as a benchmark. Wthn the ADVANCE project the sustanable value of 65 European manufacturng companes was calculated, although only envronmental resources were consdered. The EU-15 benchmark was used to calculate the sustanable value of each company. Assumng that envronmental resources are not yet used n a sustanable way n the EU-15, a second benchmark was appled usng performance targets. In ths way the future performance scenaro shows whch companes wll contnue to create sustanable value under the more strngent future performance targets (ADVANCE, 2006). Van Passel et al. (2007) used the weghted average return of captal of a large sample of dary farms to explan dfferences n farm sustanablty. The results of ther analyss were also compared usng other types of benchmarks. Van Passel et al. (2007) showed that the benchmark choce had an mportant mpact on the absolute level of the sustanable value but not on the rankng of the sustanablty performance of the farms. Because benchmarks can gve valuable ndcatons to all decson makers, a well defned benchmark s essental. Otherwse decson support systems can gve wrong sgnals. In fact, an llconsdered choce of the benchmark may result n napproprate and msleadng results n lght of the ntal decson stuaton and research queston. Furthermore, t s mportant that a benchmark s realstc and feasble for each company but t s also preferable that a benchmark s ambtous. Benchmarks usng best performance or specfed targets can be very useful to analyse the efforts of farms n ther am to mprove ther results (Van Passel et al., 2007). In our example n Table 1 we choose the weghted average return on captal of a large sample as benchmark. Van Passel et al. (2007) opted for ths benchmark because ther study tred to understand why farms dffer n ther creaton of sustanable value. Usng for example the best performance of each resource as benchmark wll result n other value contrbutons. In fact, all value contrbutons would be negatve; a value contrbuton of zero would ndcate that the observaton s the best performance. In ths case, the am of all companes would be to get value contrbutons of zero. If all value contrbutons are zero, then the sustanable value of that company would be zero (or the return-to-cost rato would be equal to one), whch s the maxmum achevable score. A sustanable value of zero would mean that the super-company exsts or n other words that such a company has the hghest productvty for all resources. Usng a basc best performance benchmark, Van Passel et al. (2007) found a maxmum return-to-cost rato of 0.7, showng a large scope for mprovement. However, the basc best performance benchmark usng the best performance of each resource has mportant shortcomngs. As ndcated by Fg. 1, such a basc benchmark s not necessarly the best opton to assess the performance of companes. Usng a basc benchmark for all companes (ndependent of the actual resource use and combnaton) can result n a msleadng measurement of the resource performance of a company. The unt soquant K n Fg. 1 shows all the ways of combnng two resources X 1 and X 2 to produce a gven level of output Y. Ponts on the unt soquant are effcent because ther actual productvty equals the maxmum feasble productvty. Observaton a can mprove the productvty of resource X 1 whle observaton r has the maxmum productvty level. In fact, t seems very clear that n ths case observaton r san accurate benchmark for observaton a (even for both resources X 1 and X 2 ), the peer of observaton a s observaton r. The productvty level of observaton a for the resource use of X 1 equals 0X1 r =0Xa 1. However, when lookng to observaton c, the peer for observaton c, usng the basc best performance benchmark, would be observaton r but wth the actual combnaton of resources X 1 and X 2, ths s not always a feasble target. Therefore, a better peer for observaton c would be observaton s (Fg. 1). Ths s an accurate benchmark for a gven rato of dfferent resources. To analyse the efforts of companes towards more sustanable practses, the use of a best performance benchmark wthn the calculaton of the sustanable value of frms s very promsng. Fg. 1. Unt soquant K for resources X 1 and X 2 for a gven level of output Y.

S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 3061 However, the basc best performance benchmark has major shortcomngs and therefore usng a benchmark as n Fg. 1 would be an mportant mprovement to benchmark frm sustanablty because n ths case the value contrbuton of each resource s dependent of the use of the other resources. The sustanablty of each company would be assessed n comparson wth the relevant peers of that company. In applcatons, benchmark unts (peers) can play an mportant role by facltatng dffuson of best practses from effcent unts to neffcent ones (Kuosmanen and Kortelanen, 2005). In ths research, we wll use fronter methods to construct a best performance benchmark to assess the sustanable value. The dea of usng producton economcs (fronter methods) n sustanablty assessment s not new. Tyteca (1996) used producton economcs to defne standardsed, aggregate envronmental performance ndcators. These ndcators do not requre the specfcaton of any a pror weght on the envronmental mpacts that are beng aggregated (Tyteca, 1996). Callens and Tyteca (1999) and Tyteca (1999) worked out ndcators of sustanable development usng the prncples of productve effcency. In fact, they developed a model usng an approach that s smlar to one normally used to quantfy output, nput or overall productve effcency. In our approach we start from a sustanablty assessment method (the sustanable value approach) and use fronter methods to benchmark the value of frm resources. Notce that the focus n Fg. 1 (and n ths research) s only on techncal effcency and not on allocatve effcency. Remember that as n earler applcatons of the sustanable value approach, we assume that there are no scale effects, for example the Cobb Douglas producton assumes constant returns to scale. In contrast, the translog functonal form s more flexble and can take nto account scale effects. In ths research, we dscuss both functonal forms as benchmarks wthn the sustanable value approach. Furthermore, we assume a constant relatve rato between all resources, meanng that we only capture effcency mprovements that do not change the relatve rate by whch dfferent resources are used by a frm. In other words, we assume that companes are not able to change the relatve weght of the dfferent resources wthn the set of resources they are usng. Our approach has the advantage that we take nto account the fact that the use of dfferent resources makes them nterdependable, but ths rules out dfferences n technology. In other words, we assume that all companes use a smlar producton technology. However, we only assume a constant rato between all resources n defnng a benchmark for each resource. After defnng the benchmark usng effcency analyss, we use these benchmarks wthn the sustanable value n a smlar way as n prevous applcatons. Whle the basc best performance benchmarks (used by Fgge & Hahn, 2005; ADVANCE, 2006; Van Passel et al., 2007) assume a lnear producton technology, we apply other knds of producton technologes. Whch producton technology (lnear or non-lnear) s preferable depends on the partcular stuaton (sector, resources consdered) and on the research queston. Hence, the most mportant advantage of usng fronter method benchmarks s that n ths way the sustanable value approach takes producton lnkages nto account. Ths s because producton functons (estmated by fronter methods) show the lnk between the output produced and the resources used (ncludng envronmental and socal resources). Therefore, n ths research we wll develop and test a methodology to mprove the sustanable value method wth fronter methods to construct a sound benchmark. We are aware that other types of benchmarks go along wth dfferent mplcatons and assumptons. Fronter benchmarks broaden the possbltes of the sustanable value approach. In ths way, more applcatons are possble. 3. Methodology As ndcated n the prevous secton, we use the sustanable value methodology and opt for a benchmark whch () compares the combnaton of resources wth other resource combnatons and () selects the most approprate peer as benchmark for each company. The most approprate peer can be defned as a comparable company that uses fewer resources to produce the same amount of output. Ths benchmark can be constructed usng fronter methods. In ths way, producton theory s ntegrated wth a value-orentated assessment method. 3.1. Formulaton of the benchmark In the fronter lterature, two broad classes of approaches are consdered, namely the parametrc and the non-parametrc approaches. Parametrc approaches (e.g., stochastc fronter estmatons) take possble measurement errors and other nose upon the fronter nto account. The dsadvantage s that the researcher has to select a functonal form for the producton fronter. Nonparametrc approaches are robust to the knd of specfcaton error that may arse n the choce of functonal form, but the propertes of the neffcency estmates cannot be determned. In ths research we prefer to work wth a parametrc approach for estmatng the producton fronter, because n our emprcal applcaton farm data s used and we expect that data nose could play an mportant role n the estmaton of an agrcultural producton functon (Coell et al., 1998). Note, however, that our approach s also compatble and operatonal wth non-parametrc approaches. Consder the followng producton functon: lnðy t Þ¼f ðx t ; bþþv t u (1) where y t s the output of the th frm n year t; x t are the nput quanttes n the producton process used by the th frm n year t; b s a vector of unknown parameters; v t accounts for measurement error and random errors whle the second error term u t measures the techncal neffcency. The effcent amount of x t can be expressed as: x effcent ¼ gðy ; x 1 ;.; x n ; u Þ (2) In tradtonal producton economcs, the nputs are for example labour and captal. The strategy of most parametrc studes has been to nclude envronmental effects n the output vector (e.g., Pttman, 1983; Färe et al., 1989; Ball et al., 1994; Hetemäk, 1996). As n Cropper and Oates (1992) and Renhard et al. (1999, 2000) we model the envronmental assets as a conventonal nput rather than as an undesrable output, because ths fts completely n the sustanable value approach. A second reason (also rather pragmatc) s the fact that envronmentally detrmental nput use s easy to measure (e.g., excess ntrogen use), whch s not the case wth envronmental mpacts (Renhard et al., 1999). Nevertheless as brefly dscussed n Secton 2.1, we are aware that the queston of whether envronmental factors are nputs or outputs can be relevant e.g., wth respect to returns to scale. Ths queston has been recently debated by Färe and Grosskopf (2003) and Halu (2003), but ths dscusson falls beyond the scope of ths paper. We therefore specfy the stochastc producton fronter as: lnðva Þ¼f ðx ; z ; bþþv u (3) for all companes ndexed wth a subscrpt ; VA denotes the value added; x s a vector of conventonal economc nputs. Intermedate consumpton s not consdered as an economc nput, because we

3062 S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 choose the value added as output and not the total value of returns. z s a vector of envronmental and socal assets; b s a vector of unknown parameters; v s a random error term ntended to capture events beyond the control of the managers; u s a non-negatve random error ntended to capture techncal neffcency. The effcent amount of x and z can be expressed as: x effcent z effcent ¼ gðva ; x 1 ;.; x n ; z 1 ;.; z n ; u Þ ¼ gðva ; x 1 ;.; x n ; z 1 ;.; z n ; u Þ As mentoned n Secton 2.1, no dstncton s made between conventonal economc nputs (x) and envronmental and socal assets (z). We assume that they all contrbute to the producton of value added n a sustanable system. Therefore, we ntroduce the term resource r whch ncludes economc, envronmental and socal captal forms (and aspects derved from captal forms): r effcent ¼ gðva ; r 1 ;.; r n ; u Þ (4) Note that the sustanable value of a company wth n dfferent resources can be calculated as: sustanable value ¼ 1 X n VA VA r n (5) r s ¼ 1 r benchmark where r stands for a resource (economc, envronmental and socal captal forms) of company and VA for value added of company. Usng effcency analyss, we propose the followng benchmark: VA ¼ r benchmark VA r effcent ¼ VA gðva ; r 1 ;.; r n ; u Þ Brngng equaton (6) nto equaton (5) gves us the calculaton of the sustanable value of a company wth a company specfc benchmark: sustanable value ¼ 1 n X n ¼ 1 " VA r r VA r effcent Note that the benchmark s dfferent for each company, because the benchmark depends on the amount and combnaton of resources of that company (as n Fg. 1). To summarze, the benchmark calculaton usng fronter methods takes neffcency of the resource use and ntal resource use nto account.!# 3.2. Formulaton of the framework usng functonal forms Before estmatng the producton fronter the researcher has to choose a functonal form. An mportant step n any parametrc emprcal applcaton s the selecton of the approprate sustanable value ¼ 1 2 * 2 (6) (7) 0 6 VA r 1 4 f! B fva @ r h 1 fva expð b 0 Þk b2 2 0 6 VA 4 f! B fva @ r 2 h 1 gva expð b 0 Þk b1 ðb 1þb 2Þ functonal form for the producton functon. A commonly used functonal form s the Cobb Douglas functonal form. The smplcty of ths functonal form s very attractve, but a drawback s that the Cobb Douglas producton functon assumes constant nput elastctes, constant returns to scale for all frms and an elastcty of substtuton to be equal to one. A number of alternatve functonal forms exst, such as the translog functonal form (Chrstensen et al., 1973). An advantage of the translog form s that t mposes no restrctons upon returns of scale or substtuton possbltes (Coell et al., 1998). In the followng sectons, we use both forms. 3.2.1. Methodology usng the Cobb Douglas functonal form Assume a Cobb Douglas technology wth two resources r 1 and r 2 to produce VA (value added). Company does not use ts resources 100% effcently, n other words u dffers from zero. We formulate the Cobb Douglas stochastc producton fronter model as: ln VA ¼ b 0 þ b 1 ln r 1 þ b 2 ln r 2 þ v u (8) To perform the calculaton, we frst have to purge the output measure (VA) of ts nose component (v ) so that we can work n a determnstc framework: ln VA f ¼ b 0 þ b 1 ln r 1 þ b 2 ln r 2 u wth ln VA f ¼ ln VA v (9) We are lookng for the nput-orentated techncally effcent resource r effcent for a gven level of value added ðvaþ. f Ths can be derved by smultaneously solvng equaton (9) and the resource rato ðr 1 =r 2 Þ¼k. Note that the soluton of the smultaneous system of equaton s made after the parameters of the producton fronter have been estmated usng maxmum lkelhood methods. After estmaton we get: ln VA ¼ b 0 þ b 1 ln r 1 þ b 2 ln r 2 and wth ln VA f ¼ ln VA v ¼ ln VA u Notce that VA s the predcted fronter output and VA s the observed output. The r effcent are: r effcent 1 r effcent 2 ¼ ¼ h 1 fva expð b 0 Þk b2 ðb 1 þb 2 Þ h 1 fva expð b 0 Þk b1 ðb 1 þb 2 Þ (10) Brngng equaton (10) nto equaton (7), we can calculate the sustanable value of company usng only 2 resources and assumng Cobb Douglas technology as: 1 ðb 1 þb 2 Þ 13 C7 A5 + 13 C7 A5 þ r 2

Because the Cobb Douglas functonal form has a constant elastcty of substtuton (and equal to one), we can smplfy the calculaton of the sustanable value for company as: sustanable value ¼ r 1 "! fva r 1 S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 3063 fva h fva expð b 0 Þk b2 1 ðb 1 þb 2 Þ We are lookng for the nput-orentated techncally effcent resource r effcent for a gven level of value added ð f VAÞ. Ths can be derved by smultaneously solvng equaton (12) and the resource # ¼ r2 "! fva r 2 fva h fva expð b 0 Þk b1 1 ðb 1 þb 2 Þ # The suggested benchmark offers two mprovements. Frst, the benchmark ncorporates neffcency. Ths s because we consdered (n)effcency (as u ) n our estmaton of the producton fronter usng stochastc fronter analyss. Second, the benchmark allows dentfcaton of a benchmark consderng the ntal resource use of each company. In fact, each company can benchmark ts resource use wth the most approprate peer. Note that n ths case, we only consdered techncal (nputorentated) effcency and not allocatve and economc effcency. Economc effcency s the combnaton of techncal effcency and r effcent 1 2 rato ðr 1 =r 2 Þ¼k. Note that the soluton of the smultaneous system of equaton s made after the parameter of the producton fronter has been estmated usng maxmum lkelhood methods. After estmaton we get: ln VA ¼ b 0 þ b 1 ln r 1 þ b 2 ln r 2 þ b 3 ðln r 1 Þ 2 þb 4 ðln r 2 Þ 2 þb 5 ðln r 1 ln r 2 Þ Notce that VA s the predcted fronter output and VA s the observed output. The r effcent are: rffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff n ¼ exp4 ðb 1 þ b 2 Þ ðb 1 þ b 2 Þ 2 4 ln VA f þ b 0 ðb 2 þ b 5 Þlnðk Þþb 4 ðln k Þ 2on o b 3 þ b 4 þ b 5 2ðb 3 þ b 4 þ b 5 Þ 3 5 r effcent 2 2 rffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff n ¼ exp4 ðb 1 þ b 2 Þ ðb 1 þ b 2 Þ 2 4 ln VA f þ b 0 þ ðb 1 þ b 5 Þlnðk Þ þ b 3 ðln k Þ 2on o b 3 þ b 4 þ b 5 5 (13) 2ðb 3 þ b 4 þ b 5 Þ 3 allocatve effcency. Assumng Cobb Douglas technology, the economc effcency nput vectors can be calculated, because the Cobb Douglas functon s self-dual. For ths, prce nformaton of each resource s needed, whch s not always possble (and relevant) for all resources, especally for envronmental and socal aspects. 3.2.2. Methodology usng the translog functonal form In ths secton we use a translog functonal form to benchmark the sustanable value. Assume a translog functonal form wth two resources r 1 and r 2 to produce VA (value added). Company does not use ts resources 100% effcent, n other words u dffers from zero. We formulate the translog stochastc producton fronter model as: ln VA ¼ b 0 þ b 1 ln r 1 þ b 2 ln r 2 þ b 3 ðln r 1 Þ 2 þb 4 ðln r 2 Þ 2 þb 5 ðln r 1 ln r 2 Þþv u (11) To apply the calculaton, agan we frst have to purge the output measure (VA) of ts nose component (u ) so that we can work n a determnstc framework: ln VA f ¼ b 0 þ b 1 ln r 1 þ b 2 ln r 2 þ b 3 ðln r 1 Þ 2 þb 4 ðln r 2 Þ 2 þb 5 ðln r 1 ln r 2 Þ u wth ln VA f ¼ ln VA v (12) Once ths s obtaned, the same approach as n the Cobb Douglas case can be followed by brngng the r effcent (equaton (13)) for every resource nto equaton (7). In ths way the sustanable value can be calculated. 4. Emprcal applcatons In ths secton, the methodology consdered s appled usng emprcal data. Frst, the Cobb Douglas functonal form s used, and second the translog functonal form s used as benchmark to calculate the sustanable value. Fnally, the mpact on the sustanable value wll be estmated for dfferent polcy optons to llustrate how the approach may be used as a decson support system. 4.1. Cobb Douglas functonal form as benchmark The frst applcaton uses the data of a large sample of Flemsh dary farms. As n Van Passel et al. (2007) we consder fve dfferent resources: () farm labour, () farm captal, () farm land, (v) ntrogen surplus and (v) energy consumpton (drect and ndrect). Captal, land and labour can be seen as tradtonal economc resources, whle ntrogen surplus and energy consumpton are mportant envronmental aspects n dary farmng. The dataset contans nformaton of 645 Flemsh dary farms durng the perod

3064 S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 Table 2 Descrptve statstcs. Varable Mean Mnmum Maxmum Std. devaton Total output (Euro) 150 293 20 445 622791 68 765 Land use (ha) 31.73 6.72 83.08 11.28 Labour (full-tme equvalent) 1.48 0.63 3.50 0.34 Farm captal (Euro) 284 466 37338 789 404 152140 Intermedate consumpton (Euro) 66 361 13 600 295 465 31535 Energy consumpton (MJ) 1248 410 268 185 3 803 592 522 292 Ntrogen surplus (kg N) 8884 1934 25 570 3879 Table 4 Actual and techncal effcent resource use of a sample farm for achevng a value added of 149 283 Euro. Resource Actual use (r) Techncal effcent use (r effcent ) Labour (fte) 1.50 1.23 Farm captal (Euro) 244 039 200 024 Farm land (ha) 50.09 41.09 N-surplus (kg N) 13 308 10 908 Energy consumpton (MJ) 1950 770 1598 926 Fte ¼ full tme equvalent. 1995 2001. Some descrptve statstcs of the data sample can be found n Table 2. As explaned n Secton 2.1 we use conventonal economc and envronmentally detrmental resources to estmate a producton functon. The value added of the farms s used as dependant varable. Furthermore, tme dummes are added to ndcate the dfferent years. Ths leads to the followng Cobb Douglas functonal form: VA ¼ expðb 0 Þ$Labour b 1$Captal b 2$Land b 3$N-surplus b 4! $Energyconsumpton b 5$exp Xn g j $Yeardummy j j ¼ 1 $expðv u Þ (14) We can rewrte equaton (14) n logarthmc form as: ln VA ¼ b 0 þ b 1 lnðlabourþ þb 2 lnðcaptalþ þb 3 lnðlandþ þb 4 lnðn-surplusþ þb 5 lnðenergyconsumptonþ þ Xn g j j ¼ 1 $Yeardummy j þ v u (15) The estmaton results of equaton (15) usng maxmum lkelhood methods can be found n Table 3. We apply the methodology as explaned n Secton 3.2.1. Frst the output measure s separated from ts nose component to work n a determnstc framework (as n equaton (9)). Then we calculate the nput-orentated techncally effcent resource for each resource consdered usng the estmated coeffcents of equaton (15) and the resource ratos. After we obtaned the nput techncally effcent amount of each resource for each company, the sustanable value can be calculated usng those values as benchmarks. Notce that n ths applcaton the techncal nput-orentated effcency s used. Farms can mprove ther effcency by reducng ther amount of resources and producng the same amount of output (value added). We chose for an nput-orentated effcency because Flemsh dary farms have mlk quotas and have to pay hgh leves n the case of exceedng ther mlk quota. Farms have to obtan an extra mlk quota f they want to ncrease ther producton level. Table 4 llustrates the results of one of the observatons n our dataset. Ths farm uses fve resources to produce a value added of 146 448 Euro. Correctng ths for random errors (n other words subtractng v ) the value added becomes 149 283 Euro. The actual use as well as the techncal effcent use of the resources s calculated n Table 4. In our example the farm uses 50 ha of land, whle the same amount of value added could be produced usng only 41 ha agrcultural land (Table 4). Notce that the rato of the techncal effcent use to the actual of the resources s the same for all resources (¼0.80 or 80%). Ths s due the choce of the Cobb Douglas formulaton as functonal form. As already mentoned the Cobb Douglas functonal form has an elastcty of substtuton equal to one. The sustanable value of all observatons of the dataset can be calculated usng the nput effcent resource use as benchmark. In Fg. 2 the sustanable value of all our observatons from low sustanable value to hgh sustanable value s represented. It s qute obvous that for all farms the sustanable value s negatve. In fact, a sustanable value of 0 would ndcate that the farm uses all ts resources n the most productve way. Such a super farm does not exst n our sample. Nevertheless, large dfferences are observed rangng from dary farms wth a sustanable value of V 2000 to V 94 000. Farms can mprove ther sustanable value by applyng ther resources n a more productve way, n other words, by movng towards the producton fronter. Farms can mprove ther sustanable value by replacng more sustanable value-creatng resources by resources wth low value contrbutons. Table 3 Estmaton coeffcents of the Cobb Douglas producton fronter. Varables Coeffcent St. error Varables Coeffcent St. error Constant 0.5297 0.4344 D_1995 0.0057 0.0358 Labour 0.2886*** 0.0510 D_1996 0.0519 0.0340 Farm captal 0.2496*** 0.0220 D_1997 0.0602* 0.0355 Farm land 0.2184*** 0.0479 D_1998 0.1757*** 0.0398 N-surplus 0.1828*** 0.0462 D_1999 0.3842*** 0.0414 Energy-consumpton 0.6147*** 0.0545 D_2000 0.1545*** 0.0356 Number of observatons 645 Iteratons completed 20 Sgma 0.3975 *Sgnfcant at 10%; **sgnfcant at 5%; ***sgnfcant at 1%. Fg. 2. Hstogram of the sustanable value of all observatons.

S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 3065 (Spearman s rho ¼ 0.9967). The use of a feasble benchmark for each company (applyng fronter methods) results n a dfferent rankng. We found a much lower rank correlaton (Spearman s rho ¼ 0.2327) between the return-to-cost rato usng the smple performance on each resource as a benchmark and the return-tocost rato usng a Cobb Douglas producton fronter as a benchmark. Ths confrms our pont that the sustanable value approach can dffer by usng fronter methods to benchmark the resource use of companes. The benchmark usng fronter aspects takes underlyng producton aspects (e.g., ntal resource use) nto account. Hence, each farm s compared wth a realstc but ambtous peer. That s why we call ths fronter benchmark approach more complete than the basc benchmark approach. 4.2. Translog functonal form as benchmark Fg. 3. The evoluton of the average sustanable value and return-to-cost rato of Flemsh dary farms. The value contrbutons of all captal forms are equal usng the Cobb Douglas functonal form as benchmark, because of the constant elastcty of substtuton. Hence, usng the Cobb Douglas functonal as benchmark cannot dentfy substtuton possbltes because the assumpton of constant elastcty of substtuton. That s the reason why all value contrbutons of all resources are equal. Fg. 3 shows the development over tme of the sustanable value and the return-to-cost of the dary farms n the data sample between 1995 and 2001. Notce that n ths case we used a balanced panel data sample, n other words only the farms wth data for all seven consecutve years (1995 2001) are used n Fg. 3. The average sustanable value of the farms fluctuates between V 18 000 and V 23 000, except n 1999. In 1999 the average sustanable value of our dary farms was over V 26 000. As already explaned, the sustanable value calculatons do not take the farm sze nto account. Therefore, we use a sze ndependent rato: the return-tocost rato. The return-to-cost rato relates the value added created by a farm to the opportunty costs t causes. The average return-tocost s calculated as the sum of the return-to-cost ratos of all observatons n one year dvded by the number of observatons n that year. Usng the Cobb Douglas producton fronter as benchmark, a maxmum return-to-cost of 0.96 has been found. The mnmum return-to-cost of an observaton n our data sample s 0.51. That farm uses ts resources only half as productve as the benchmark (the maxmum attanable producton), more specfcally that farm uses a double amount of resources to produce ts output. We do not observe large yearly average return-to-cost shfts (Fg. 3). Note that n ths case a low average sustanable value certanly does not mean a low average return-to-cost rato, moreover the reverse s true. For example, n 1999, we observe a low average sustanable value and a hgh average return-to-cost rato n comparson wth the other years. Ths s not very surprsng gven the fact that the average value added n 1999 was hgh (resultng n a hgh return-to-cost). Note that although the productvtes of the dfferent resources n 1999 were n general hgher n comparson wth other years, the benchmark productvtes were also hgher, because the farms could acheve hgher productvtes due to benefcal crcumstances (e.g., weather condtons) that result n a lower sustanable value for the farms n 1999. As ndcated by Fg. 1, we suggest usng a fronter benchmark nstead of usng a smple best performance benchmark. In Van Passel et al. (2007) dfferent benchmark types were used to analyse the robustness of the result. The rank correlaton between the return-to-cost rato usng the weghted average return on resource as a benchmark and the return-to-cost rato usng the basc best performance on each resource form as a benchmark was very hgh Important drawbacks of the Cobb Douglas functonal form are the restrctve propertes such as the constant nput elastctes and a substtuton elastcty equal to unty. The translog functonal form does not mpose these restrctons upon the producton structure: t s a more flexble functonal form. But ths s at the expense of havng a form whch s more dffcult to estmate and whch can suffer from degrees of freedom and multcollnearty problems (Coell et al., 1998). Usng for example fve dfferent resources as n Secton 4.1 wll result n a producton functon wth 21 varables. A lot of observatons are needed to estmate such an equaton. Estmatons wth only 645 observatons (as n Secton 4.1) were nadequate. Therefore, we wll use an extended data sample (2651 observatons) wth only two resources (farm labour and farm captal). We wll use only economc resources because n our extended data sample nformaton about envronmental resources was not avalable yet. We are aware that the lack of envronmental varables mples that the applcaton wll not be sutable for a sustanablty assessment. In ths secton, t s not our objectve to make a sustanablty assessment of Flemsh agrculture but to test the methodology usng an emprcal applcaton. Our data sample contans 2651 observatons of Flemsh dary farms durng 1989 2002. Note that n ths example farm captal ncludes land captal. In ths case the translog functonal form can be wrtten as equaton (11): ln VA ¼ b 0 þ b 1 lnðlabourþ þb 2 lnðcaptalþ þb 3 lnðlabourþ 2 þb 4 lnðcaptalþ 2þb5 lnðlabour $Captal Þ þ Xn j ¼ 1 Yeardummy j þ v u (16) The estmaton results of equaton (16) usng maxmum lkelhood methods can be found n Table 5. We apply the methodology as Table 5 Estmaton coeffcents of the translog producton fronter. Varables Coeffcent St. error Varables Coeffcent St. error Constant 9.2995*** 0.1262 D_1994 0.1641*** 0.0350 Labour 1.0696*** 0.1802 D_1995 0.1156*** 0.0346 Captal 0.3573*** 0.0849 D_1996 0.0559 0.0358 Labour 2 0.2141** 0.1046 D_1997 0.1582*** 0.0359 Captal 2 0.0448*** 0.0155 D_1998 0.3453*** 0.0395 Labour captal 0.2125*** 0.0634 D_1999 0.5452*** 0.0411 D_1990 0.1018*** 0.0298 D_2000 0.2681*** 0.0373 D_1991 0.0654** 0.0303 D_2001 0.1693*** 0.0433 D_1992 0.0155 0.0323 D_2002 0.0998** 0.0390 D_1993 0.2577*** 0.0347 Number of observatons 2651 Iteratons completed 28 Sgma 0.5179 *Sgnfcant at 10%; **sgnfcant at 5%; ***sgnfcant at 1%.

3066 S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 Table 6 The actual and techncal effcent resource use of a sample farm for achevng a value added of 67602 Euro. Resource Actual use (r) Techncal effcent use (r effcent ) Labour (fte) 1.55 0.88 Total farm captal (Euro) 298 571 225 942 Fte ¼ full tme equvalent. Fg. 4. The evoluton of the average value contrbutons and sustanable value of Flemsh dary farms. explaned usng a two resource example n Secton 3.2.2. Frst we separate the output measure wth ts nose component to work n a determnstc framework (as n equaton (12)). Thenwe calculate the nput-orentated techncally effcent resource for each resource consdered usng the estmated coeffcents of equaton (16) and the resource rato. After we obtaned the effcent resource amount to produce the value added for each resource and for each company, the sustanable value can be calculated usng those values as benchmarks. Table 6 llustrates the results of one of the observatons n our dataset. Ths farm uses two resources to produce a value added of 76 949 Euro. Correctng ths for random errors (n other words subtractng v ) the value added becomes 67602 Euro. The actual use and the techncal effcent use of the resources can be found n Table 6. In our example the farm uses for example 1.55 full-tme equvalent (fte) unts of labour, whle the farm could create the same amount of value added usng only 0.88 fte of labour (Table 6). Note that the relaton between the actual use to the techncal effcent use of the resources s not the same for all captal forms (n contrast wth the Cobb Douglas functonal form). Our results ndcate that farms use labour less effcently than captal. However, our analyss does not take allocatve effcency nto account. In other words, the prces of the nputs are not consdered. The sustanable value of all observatons of the dataset can be calculated usng the nput effcent resource use as benchmark. In ths case the (negatve) mpact of labour captal wll be hgher than the (negatve) mpact of total farm captal n the calculaton of the sustanable value (see Fg. 4). Farm captal s used n a more valuecreatng way (n fact a less value-wastng way) than labour captal. As explaned n Secton 2.2, a resource s defned as value-creatng f the resource productvty of the frm s hgher than the resource productvty of the benchmark On the other hand, we can defne a resource as value-wastng f the resource productvty s lower than the benchmark. Gven that our suggested benchmark s an estmated best practce benchmark, all resources are categorzed as value-wastng (or value-neutral f the frm come up to the level of the best practce). Nevertheless, some resources are less valuewastng because the dstance to the benchmark s smaller. Fg. 4 shows the average value contrbutons of farm captal and labour and the average sustanable value of a balanced panel set of Flemsh dary farms (55 dary farms durng 1989 2002). We observe a decrease n sustanable value tll 1999. Startng from 1999 we see a rather lmted ncrease n sustanable value creaton. Farms can mprove ther sustanable value by applyng ther resources n a more productve way. They can ncrease ther techncal effcency by movng towards the producton fronter. On the one hand, farms can decrease the amount of resources used whle producng the same amount of output. On the other hand, farms can change the composton of resources, value-wastng resources can be partly substtuted by value-creatng resources (or less valuewastng resources). In our restrcted emprcal applcaton, ths means that farms could replace a small amount of labour by a small amount of captal to ncrease the sustanable value. The sustanable value methodology usng the translog producton fronter as benchmark consders both possbltes. In other words substtuton effects between resources are clearly taken nto account to determne the opportunty cost (or benchmark) of each resource. A major drawback s the data requrements to estmate the translog producton fronter (a lot of observatons are needed). The more resources are consdered as crtcal captal forms to assess frm sustanablty, the more data s needed. 4.3. Benchmarkng sustanablty assessment for polcy evaluaton The sustanable value approach dscusses the need to conserve resources n order to generate hgher return. It s nterestng to know whch frms are creatng greater value consderng economc, envronmental and socal resources, but t s even more crucal to know the mpact of (future) decsons on the sustanable value. If a company or polcy maker has to choose between several optons, t s mportant that n terms of sustanable development that the opton s selected whch ncreases the sustanable value of the company, sector or regon. In ths secton, we explan how the suggested approach may be used to support polcy makng. We llustrate the approach for the Flemsh dary sector usng a large accountancy data sample (see Secton 4.1). Assume that polcy makers consder mprovng the sustanablty performance of the Flemsh dary sector based on the two followng polcy optons. We make the mplct assumpton that both optons have dentcal costs. The frst opton s to provde subsdes to mprove the energy use (drect and ndrect) of dary farmng (e.g., decrease n concentrate use or electrcty use). Assume that these measures wll result n an average decrease of 10% energy use whle the value added remans the same. The second opton s to provde subsdes to nvest n labour savng technques (e.g., tme management tools, removng admnstratve burden). Agan we assume that these measures wll result n an average decrease of 10% labour use whle the value added remans the same. Because polcy makers have a lmted budget, they have to choose between opton A (energy use decrease) and opton B (labour use decrease). To support polcy makers, the sustanable value (and return-tocost rato) of both optons can be smulated. To do so, we use the balanced panel data of dary farms as n Fg. 3, and we smulate the sustanable value of every farm n the sample for a future year for three optons: opton A, opton B and the base scenaro. We use the estmated Cobb Douglas functonal form as benchmark. The base scenaro s a smulaton of the sustanable value wthout a polcy nterventon (busness as usual). As n Secton 4.1 fve dfferent resources are selected: labour, farm captal, farm land, energy consumpton and N-surplus. The resource use s calculated as the average of the seven precedng years. Furthermore, the

S. Van Passel et al. / Journal of Envronmental Management 90 (2009) 3057 3069 3067 be studed and estmated before ncorporatng these results wthn the sustanable value approach. Our assumpton of equal value added whle decreasng the energy or labour use s for example not very realstc. Nevertheless, these results show that the suggested approach can be very useful to support decsons of polcy makers and company managers and that the mpact of potental decsons can be evaluated wthn an ntegrated sustanablty framework. 5. Concluson Fg. 5. The evoluton of the average sustanable value and return-to-cost rato of Flemsh dary farms ncludng the smulaton results of the polcy optons (busness as usual, opton A: energy use decrease; opton B: labour use decrease). value added and the yearly varaton (ndcated by the coeffcents of the year dummes n Table 3) are fxed on the average values of the precedng years. To calculate the mpact of the optons, the energy use and labour use are decreased by 10% compared to the calculated average (or base scenaro) for opton A and opton B respectvely. The smulaton results can be found n Fg. 5. As expected (gven the assumptons) the average sustanable value and the return-tocost rato ncrease for the two optons. More nterestng s the fact that subsdzng a decrease n energy use results n a hgher ncrease of sustanable value than subsdzng a decrease n labour use. In other words, these results suggest that polcy makers should support energy use reducton nstead of labour use reducton. Furthermore, we can analyse the smulaton results consderng characterstcs of the farm manager. Table 7 shows that the returnto-cost rato s hgher for young, educated farmers wth certanty about ther successon. Furthermore, we found n each case a smlar trend as n Fg. 5: opton A s preferred over opton B whch s better than busness as usual. We are aware of the smplcty of the suggested polcy optons. To support polcy makers, the suggested optons have to be refned n more detal (e.g., dfferentatng among farmers recevng a subsdy). Furthermore, the mpact of the suggested polcy measures on all dfferent resources and on the value added must Table 7 Average return-to-cost consderng manageral farm characterstcs for the dfferent polcy optons. Return-to-cost rato Busness as usual Return-to-cost rato Opton A: energy use decrease Educaton of farmer No educaton (34%) 0.766 0.809 0.786 Educaton (66%) 0.826 0.872 0.847 Age of farmer Young (39 year) (34%) 0.814 0.860 0.835 Mddle (40 46 year) 0.803 0.848 0.824 (37%) Old (46 year) (29%) 0.798 0.842 0.818 Successon of farmer No successor (37%) 0.811 0.857 0.832 Doubt about successon 0.797 0.842 0.818 (59%) Successor (5%) 0.858 0.906 0.880 Number of dary farms: 41. Return-to-cost rato Opton B: labour use decrease The performance of companes s usually defned n terms of return on captal and proft. Recently, the vew on performance has been broadened. To create value, companes do not only need economc captal but also envronmental and socal resources. Ths means that all relevant frm resources should be consdered when assessng frm performance. In ths broad vew, hgh performance, ndcatng effcent use of all resources, s smlar to mproved sustanablty. Dfferent assessment tools have been developed to assess frm sustanablty. An nterestng approach s the one developed by Fgge and Hahn (2004a, 2005), who apply a value-orentated methodology to calculate the cost of sustanablty captal. Ther approach s based on the noton of strong sustanablty, because t assumes that the amount of each resource remans unchanged on the macro level (Fgge and Hahn, 2005). Ths means that frm performance s analysed as a scale ssue rather than as the optmal effcent allocaton of resources. The approach consders the total amount of resources rather than just the change n resource use. Thus, the sustanable value approach ntroduces scale-senstvty nto the performance analyss. Note that value- and burdenorented mpact assessments are necessarly complementary and both need to be consdered to arrve at an optmal allocaton of resources (Fgge and Hahn, 2004b). A dverse use of methodologes to assess sustanablty fts wth the defntonal dversty of sustanablty. The sustanable value methodology as shown n ths paper allows flexblty n the use and choce of benchmarks. It should be noted that the choce of benchmark does not (and cannot) make any statement on the absolute sustanablty of the benchmark as a status. Rather, sustanable value assessments wll only ndcate contrbutons to a more sustanable resource use dependng on the actual benchmark chosen. In Van Passel et al. (2007) the sustanable value and the returnto-cost rato of a large sample of Flemsh dary farms were calculated and dfferences n the return-to-cost rato were detected and explaned. For ths, the weghted average return on captal was chosen as benchmark. However, wthn the scope of polcy analyss the choce of an accurate benchmark s mportant, because for polcy makers a benchmark ndcatng the maxmum attanable productvty level s more useful to analyse the efforts of frms n ther am towards best performance. Choosng the most approprate benchmarkng s mportant. From a producton perspectve pont of vew, usng fronter effcency benchmarks can be useful for the followng reasons. Frst, mprovement n eco-effcency (as measured by the sustanable value approach) s often the most cost-effectve way of reducng envronmental pressures (Kuosmanen and Kortelanen, 2005). Effcency mprovements can be seen as the frst mportant step towards sustanablty. Therefore, t makes economc sense to explot these optons as much as possble. Second, polces targetng effcency mprovements tend to be more easly adopted than polces that restrct the level of economc actvty (Kuosmanen and Kortelanen, 2005).