Information and Communication Technology for Industrial Symbiosis

R E S E A R C H A N D A N A LYS I S

Information andCommunication Technologyfor Industrial SymbiosisGabriel B. Grant, Thomas P. Seager, Guillaume Massard,and Loring Nies

Keywords:

by-productindustrial ecologyknowledge managementrecyclingsoftwaresynergy

Supporting information is availableon the JIE Web site

Address correspondence to:Gabriel B. GrantCenter for Industrial EcologyYale University195 Prospect StNew Haven, CT [email protected]

c© 2010 by Yale UniversityDOI: 10.1111/j.1530-9290.2010.00273.x

Volume 14, Number 5

Summary

Industrial symbiosis describes the mutualistic interaction of dif-ferent industries for beneficial reuse of waste flows or energycascading that results in a more resource-efficient productionsystem and fewer adverse environmental impacts. Researchshows that many information and communication technology(ICT) tools for industrial symbiosis development have beencreated, but the results of those efforts are unclear. Drawingfrom advancements in knowledge-based economics and man-agement, this article applies a knowledge-based frameworkto evaluate opportunities for ICT within industrial symbio-sis development. ICT systems designed to enable industrialsymbiosis are surveyed and evaluated within the proposedframework to identify strengths, trends, and opportunities forcontinued development. An appendix provides a capsule sum-mary of the 17 ICT tools that are assessed in the article.

740 Journal of Industrial Ecology www.wileyonlinelibrary.com/journal/jie


Introduction

The maturation of the industrial revolutionhas created an economy that is increasinglyinterconnected and information based. Whereproducts have been standardized and markets au-tomated, modern information and communica-tion technology (ICT) has significantly reducedtransaction costs. However, for nonstandard, ornonmarket transactions between different busi-ness organizations such as those that character-ize industrial symbiosis (IS), application of ICTis less successful. We hypothesize that the fail-ure of ICT tools for IS is due to the necessity oftacit knowledge, and given that tacit knowledgesharing requires relationship or community, ICTsystems built to supplant rather than support acommunity will fail to achieve IS. Furthermore,as ICT evolves from optimization and data shar-ing toward community-building, it will becomemore supportive of IS.

IS describes industrial networks that cooper-atively optimize resource flows for a collectivebenefit greater than the sum of individual bene-fits that could be achieved by acting alone. Suchnetworks often exchange by-products, share re-sources and infrastructure, and engage collec-tively in related environmental projects. Themost well known of these networks is locatedin Kalundborg, Denmark (Ehrenfeld and Gertler1997), but many exist across the globe.

IS linkages often form between companies ofdifferent industrial sectors that do not have estab-lished customer/supplier relationships and thusrequire communication that transcends the ex-isting customer/supplier network. To address thischallenge, many ICT tools have been developedin support of IS. Yet, most of these tools havefallen from use having made little impact in thedevelopment of IS linkages. Evaluating the evo-lution of ICT tools for IS with respect for theknowledge requirements of IS provides explana-tion for the early mixed results and pathways forfuture development.

Early ICT systems are heavily criticized fortheir tendency to focus on explicit knowledge,whereas tacit knowledge, such as social capitaland trust, is essential for the mutualistic, non-market interactions required for IS (Desrochers2004). Knowledge-based economic theory pro-

vides a framework to explain the mixed resultsof ICT for IS (Grant 1996). Understanding howknowledge is communicated requires a distinc-tion between two types of knowledge: (1) explicitknowledge or information and (2) tacit knowl-edge or know-how. Explicit knowledge or infor-mation is easily communicated, codified, or cen-tralized using tools such as statistics. However,tacit knowledge is complex and is not codified.It is revealed through application and contextand is therefore costly to communicate betweenpeople (Kogut and Zander 1992; see Table 1).

Unlike commodities such as recycled metals,which can be traded solely on the basis of explicitknowledge, waste materials are typically nonstan-dard, off-spec, or highly variable in composition.Industrial symbioses, compared with traditionalcommodity exchanges, are characterized by moretacit knowledge flows and application. This dis-tinction provides understanding for many cur-rent observations documented in IS literature.Put simply, tacit knowledge or know-how cannotbe transferred vertically through a hierarchy orto and from a central authority (Grant 1996). IfIS relies on tacit knowledge, this limitation pre-dicts: (1) the concepts of social capital and trust askey precursors for IS development (Ehrenfeld andGertler 1997; Gibbs 2003), (2) the importanceof a network model for success (Berends 2001;Mirata 2004; Mirata and Emtairah 2005; VanBeers et al. 2007), (3) the failure of autocraticplanning analogous to that of a centrally plannedeconomy (Desrochers 2004), and (4) the abilityto nurture or accelerate IS where it has alreadybeen found to exist (Chertow 2007).

The knowledge-based perspective opens awealth of research that can be drawn upon tostrategically identify opportunities for success-ful development. The ability of ICT to enablecommunication of explicit knowledge is com-monly understood. Much recent research focuseson the ability of ICT to promote explicit andtacit knowledge sharing through the creation ofcommunity, social capital, and trust.

Traditionally, establishing trust favors “co-presence and co-location” and “for ICTs to assistknowledge transfer across distance, the individ-uals involved must succeed in creating a virtuallocation in which they share a common socialand cultural institutional framework (. . .). The

Grant el al., Information and Communication Technology for Industrial Symbiosis 741


Table 1 Tacit versus Explicit Knowledge [adapted from Kogut and Zander (1992)]

Description Example Individual Group Organization Network

Explicitknowledge orinformation

100110101001

Facts Who knowswhat

Accountingdata,intellectualproperty,marketresearch

Prices, whom tocontact, whohas what

Tacitknowledge orknow-how

Communicationand problem-solving skills,trust

Coordination,who can getthings done

Motivationsandincentivesforcooperation

How tocooperate,networkidentity,expectationsfor reciprocity

need to fulfill this prerequisite restricts the scopeof technologically assisted communication as areplacement for face-to-face contact” (Roberts2000). In certain cases, face-to-face communica-tion may be a prerequisite for trust in computer-mediated communication (Hossain and Wigand2004).

Critics contend that ICT threatens intimatecommunity interaction (as reviewed by Well-man 1999) and tends toward compartmentalizingknowledge, expressing only its explicit sides, sug-gesting that knowledge can exist independentlyfrom its knowing subjects, and reinforcing orga-nizational structures that do not allow knowledgedevelopment (as reviewed in Hendriks 2001).ICT systems built to supplant a community ratherthan support a community are not effective attransferring knowledge to encourage innovation(Swan et al. 2000). However, growing researchin sociology, behavioral science, and knowledgemanagement contributes toward a new aware-ness that ICT can directly enable communi-ties by strengthening social capital. In particular,the Internet reinforces existing community struc-tures through enhanced communication (Blan-chard and Horan 1998; DiMaggio et al. 2001;Haythornthwaite 2001; Howard et al. 2001).

ICT systems are now designed with the spe-cific objectives of fostering community social cap-ital and trust (Abdul-Rahman and Hailes 2000;Kasper-Fuehrer and Ashkanasy 2001; Huysmanand Wulf 2006) and facilitating the transferabil-

ity of otherwise highly illusive tacit knowledge(Stenmark 1999). The terms online communitiesand virtual communities have emerged to describecomputer-mediated social groups (Preece 2000;Rheingold 2000). Current research and devel-opment of online communities is dually focusedon usability (human-computer interaction) andsociability (human-human interaction) (Preece2000).

As an example, Xerox experienced aknowledge-sharing challenge when they discov-ered their service representatives were succeed-ing “primarily by departing from formal pro-cesses” (Brown and Duguid 2000). Rather thanrelying on repair manuals or bulletins, servicereps were discovered to be locating knowledgethrough weak-tie networks held together by sto-rytelling during breakfasts, lunches, coffee breaks,and after-hours activities. To benefit from and re-ward improvisation, Xerox initiated the Eurekaproject, which transfers locally generated knowl-edge between service representatives and theirrespective breakfast clubs throughout a multi-national work force via an online community.Unlike prescriptive “best practice” databases, theEureka database is driven by service reps who pro-vide and screen their own entries. The reps aremotivated to provide high-quality participationto build their reputation and own social capital(Brown and Duguid 2000).

As in the Xerox case study, ICT requires a nu-anced approach that is appropriately integrated

742 Journal of Industrial Ecology


within a more holistic knowledge managementsystem that clearly respects the social and culturalneeds and motivations among its community ofusers. Successful ICT knowledge managementsystems focus on the human-human communi-cation and overcome the “Western tendency” tomerely “put it in a database” (Skyrme 1998).

We hypothesize that the success and fail-ure of attempts to facilitate IS through ICT arepredictable for reasons similar to those of earlyICT knowledge management systems as well asearly attempts at planned IS (e.g., eco-industrialparks). Autocratic hierarchical design or man-agement fails to facilitate the knowledge flows re-quired to produce the desired relationships. Manyearly ICT systems built in support of IS werefirst attempts to “put it in a database” and lackedthe required investment in usability or sociabil-ity. However, through careful observation of theIS process, opportunities for ICT to support therequired communication can be identified.

Scope of Research

The greater impact of this research is to lever-age the information revolution that has dramat-ically reduced the cost of communication andinformation through ICT to transform indus-trial systems toward IS. To understand the fa-cilitation of IS with ICT, this study takes aninductive approach to synthesizing specific casestudies publicly available in literature. Generalconclusions are reached that assess the currentprogress of ICT in supporting IS. By examin-ing ICT systems designed to facilitate IS andcontrasting their approaches with theoretical il-lustrations and lessons learned from knowledge-based economics and management, this articleidentifies strengths, weaknesses, and opportuni-ties for continued development.

Survey of Systems

This study identified 17 ICT systems built tosupport IS. These systems self-identify as pur-pose built for creating IS, industrial ecology, by-product synergy, and/or eco-industrial parks. Weare not reviewing the whole of ICT or subsys-

tems of ICT for their theoretical applications.For example, excluded ICT tools that could beused throughout the process but are not purposebuilt for IS could include email, GIS, collabora-tive project management or document technolo-gies, various modeling technologies, water qualityor energy software, and waste exchanges, amongothers. Our conclusions are therefore reflectiveon the current state of purpose built ICT for ISand not ICT as a whole.

Assessing the degree of success enjoyed bythese tools is problematic. First, the many in-fluential outside variables that affect whether acollaboration comes to fruition could not be con-trolled to isolate the effectiveness of the ICT toolunder observation. Second, researchers struggleto determine in hindsight when and where op-portunity identification truly took place since thepotential linkages are often identified by the facil-itator just before or during data entry and are notexclusively the product of the ICT tool. There-fore, an appropriate indication of whether thesystem adds value for a user, within this study, iswhether the tool is still available and in use.

Of the 17 systems identified, nine are not inuse today, three are presently in use althoughnot publicly available, and one is available forpurchase over the Internet. Four (not shownin table 2), are currently under developmentwith little information yet publicly available, butare based in Kwinana, Australia; Nova Scotia,Canada; Columbus, Ohio; and Sudbury, Ontario.Abstracts for each of the 13 systems with pub-licly available information are provided as an ap-pendix available as supporting information on thejournal web site.

Observations and Discussion

IS Process Model

Each ICT system functions to transfer knowl-edge within, or in support of, a larger IS develop-ment process. Each accompanying larger processvaries in its stage of development. Core Resourcefor Industrial Symbiosis Practitioners (CRISP),for example is built in support of the NationalIndustrial Symbiosis Program (NISP) in theUnited Kingdom. Thus, considerable informa-tion is available on the context or development



Table 2 ICT Systems for Industrial Symbiosis

Systems Studied Geographic Scale Status Availability

Knowledge-Based DecisionSupport System (KBDSS)a

Industrial park Completed None

Designing IndustrialEcosystems Toolkit(DIET)b

Industrial park Canceled Public, reportedly unusable,requires MS Office 95

Industrial MaterialsExchange Tool (IME)c

City Canceled None

Dynamic Industrial MaterialsExchange Tool (DIME)d

Region Completed None

MatchMaker!e City Completed NoneIndustrial Ecology Planning

Tool (IEPT)fIndustrial park Completed Source code available, requires

ArcView GISWasteXg Nation Canceled NoneIndustrial Ecosystem

Development Project(IEDP)h

Region Canceled None

Residual Utilization ExpertSystem (RUES)i

City/state Completed Available to the original projectfunding organizations, requiresLevel5 software shell

Institute of Eco-IndustrialAnalysis Waste Manager(IUWAWM)j

Region Operational Reporting software—purchaseand demo available over theweb; analysis and optimizationsystems under development

Industrie et SynergiesInter-Sectorielles (ISIS)and Presteok

Region Operational In use by the developer

SymbioGISl Region Operational/continuousdevelopment

In use by the developer

Core Resource for IndustrialSymbiosis Practitioners(CRISP)m

Nation Operational In use by the developer andselect partners

Sources: aBoyle and Baetz (1997). bIndustrial Economics (1998); Dubester (2000); Vigon et al. (2002). cYoung (1999);Burnham et al. (2001). dShropshire et al. (2000). eBrown et al. (1997). f Nobel (1998); Nobel and Allen (2000).gClayton et al. (2002). hKincaid (1999); Kincaid and Overcash (2001). iFonseca et al. (2005). jSterr and Ott (2004).kAdoue and Bouzidi (2004); Massard et al. (2006). lMassard and Erkman (2009). mNISP (2006).

process outside of the tool. MatchMaker!, forextreme comparison, was a student project andexisted on its own, relating to a developmentprocess perhaps only in conversation.

Through reviewing the tools within the con-text of their associated developmental processes,five primary IS developmental phases emerged:(1) opportunity identification, (2) opportunityassessment, (3) barrier removal, (4) commercial-ization and adaptive management, and (5) doc-

umentation, review, and publication. The devel-opment process is far from linear and certainlycontains many nested feedback loops, but a gen-eral circular flow was observed as illustrated infigure 1 and described below. In the discussionsthat follow, the ICT systems relevant to the de-velopmental stage are identified in figure 2. Cap-sule descriptions of the ICT systems are providedin an appendix as supporting information on thejournal web site.



Figure 1 Industrial symbiosisdevelopment process model.

Opportunity IdentificationOpportunity identification occurs through

three primary means: new process discovery,input-output matching, and relationship mim-icking. The first, new process discovery, occurswhen a novel approach is created to transforma by-product into a usable resource. The secondmethod, input-output matching, occurs by iden-tifying a resource associated with one organiza-

tion, and then finding complementary resourceinputs or requirements for another organization.The third identification process involves mimick-ing successful relationships employed by similarorganizations.

Input-output matching can be accomplishedthrough brute force investigation, serendipitousdiscovery, organized workshops, or a coordinatedsearch. Workshops are organized by industry

Figure 2 Industrial symbiosisinformation and communicationtechnology tool functionality.



consortia, brokers, and government organizationsto identify potential synergies between partic-ipating firms. Although opportunity identifica-tion through workshops is sometimes successful,obstacles to implementation often prevent theseopportunities from realization, unless the work-shops are conducted as a single stage of a morecomprehensive strategy.

The taxonomical classifications of resourcesare at present a great challenge to ICT searchtools. Without the benefit of a fuzzy logic sys-tem to compare resources, the systems studiedrequired common language or specific resourcetaxonomy to produce relevant search results. Forinstance, cardboard and paperboard may be sub-stitutable or identical inputs for a by-product pro-cess, but their equivalency is based in a moretacit knowledge, which is not easily coded into acomputer system. Similarly, resources like “wastewater” require an enormous list of attributes fora computer to establish an acceptable match.Therefore, computer-aided input-output match-ing requires a great deal of upfront investmentto create standardized classifications for resourcesand associated computer interfaces that allowusers of widely varying backgrounds and lan-guages to input and retrieve relevant and recog-nizable information (Massard et al. 2006). Input-output matching is, at this stage, very difficult tocodify and thus relies on communication meth-ods more suited to tacit knowledge.

Relationship mimicking is more easily cod-ified and searchable, because unlike resources,standardized classifications for industries are moredeveloped. A successful linkage can thereforebe explicitly designated by the two codes foreach of the industries it connects. Furthermore, adatabase of these established linkages combinedwith a database of existing companies would al-low a company to locate geographically prox-imate complementary firms and successful casestudy examples of the relevant synergies. Cross-referencing this dataset with a social networkingapplication could target opportunities throughestablished trust relationships by searching forsynergies with known friends or prompting in-troductions through mutual friends. There isopportunity here for ICT to facilitate thissearch and then to support dialogue betweenparticipants.

Opportunity AssessmentOpportunity assessment evaluates the out-

comes and challenges associated with a new in-novation or process. Common methods for as-sessment include barrier assessment, benefit/costanalysis, process-based life cycle analysis (LCA)and economic input-output (EIO) LCA model-ing. Barrier assessment identifies challenges torealization by assessing market, political, social,environmental, financial, and technical feasibil-ity. Barriers may be difficult to codify and there-fore rely heavily on more tacit-based judgments.Other methods are more explicit. Benefit/costanalysis is primarily used to compare monetaryoutcomes of a decision based on explicit quantifi-able information. However, less tangible valuessuch as risk, corporate image, environmental, andsocial impacts are sometimes quantified in mone-tary terms for purposes of comparison. Multicrite-ria objective analysis methods may be employedto weigh outcomes that are not easily quanti-fied into a single unit of measurement. Process-based LCA assesses a product’s impact from rawmaterial extraction to end of life and typicallyincorporates environmental impacts not neces-sarily felt directly by the producer. EIO analysispredicts the effects of economic changes in oneindustry on related industries by utilizing a ma-trix representation of economic flows between in-dustries (Matthews and Small 2000). CombinedEIO-LCA modeling performs LCA without theintensive research of following individual pro-cesses to termination. EIO-LCA works by firstdetermining the affected industries related to aproduct or process using EIO and then summingtheir combined environmental, energy, and em-ployment impacts from aggregated data collectedabout each industry. In practice, IS developmentis based primarily on technical feasibility assess-ment, benefit-cost analysis, and monetary pri-orities. However, developments in the field ofindustrial ecology and some of the systems incor-porated in this study aim to reduce the cost ofemploying multicriteria or LCA for future use,and these tools should prove valuable when ac-counting for social and economic benefits.

Barrier RemovalBarrier removal overcomes or eliminates chal-

lenges associated with realization. Regulatory



approval may be required for by-product link-ages as nontraditional resources are introducedinto established industries. Business-to-businesscontractual agreements may require more invest-ment as quantity and quality assurances for use ofby-products must be negotiated. The challengesof financing or procuring investment capital fornew linkages are similar to those of any innova-tion seeking the appropriation of internal or ex-ternal financing. Traditional support infrastruc-ture through economic development and venturecenters, U.S. Small Business Innovation Re-search grants, and business loans are available.However, new linkages present an inherentpublic benefit and thus may be eligible for subsi-dies through environmental incentives or agen-cies. Technology development of processes to uti-lize by-products is often required, including pilotimplementation or small-scale production utiliz-ing the by-product resource to provide proof-of-concept prior to full-scale commercialization.

Commercialization and Adaptive Manage-mentCommercialization is full-scale implementa-

tion of the by-product-based industrial process,and adaptive management provides a feedbackloop for continual improvement of the firm’s pro-cess and strategy based on internal and exter-nal assessment. Internal assessment evaluates theactual performance of the synergetic process us-ing similar methods to the opportunity assess-ment to target opportunities for process improve-ment or refinement. Within the systems studied,however, this stage is almost entirely isolatedfrom the IS program and handled for develop-ment within individual organizations.

Documentation, Review, and PublicationDocumentation, review, and publication

communicate the success of individual firms andtheir associated synergies. This phase is criticalto establishing a knowledge base to support inno-vation diffusion within a greater IS community.Third-party validation can occur both systemati-cally (e.g., an auditing process) or spontaneously.Case studies, self-reported or prepared by thirdparties such as academic institutions, industryconsortia, or brokers, can be coded and made

searchable within an opportunity identificationframework.

ICT System FunctionalityThroughout the Process Model

The intensity of involvement of each of thetools studied within each of the correspondingIS developmental phases is displayed in figure 1.As previously explained, a broader IS contextor program outside of the ICT systems oftenexists which incorporates other media for stor-ing and communicating knowledge throughouteach phase of a symbiosis development. Howeverthis analysis shows where investments have beenmade to specifically leverage ICT within each ofthe phases.

The surveyed ICT systems predominantly fo-cused their resources toward opportunity identifi-cation. Relationship mimicking and input-outputmatching algorithms were the core componentsof the ICT systems, with some emphasis on op-portunity assessment. Other phases of IS develop-ment were mostly addressed through other media,work flow, or communication. The CRISP systemwas an identifiable exception that broadened itsscope beyond opportunity identification and as-sessment by providing collaborative project man-agement and work flow tools to manage a projecttoward completion while documenting the pro-cess (NISP 2006).

The emphasis on opportunity identificationmay have several explanations. First, even whenrecognizing that development is cyclical, oppor-tunity identification appears as a logical startingplace. Second, when one focuses on explicit in-formation, there are clear opportunities for ICTwithin the opportunity identification process.Input-output matching appears as a simple non-linear optimization routine until the more tacitknowledge concerning the resources is broughtinto perspective. Programs like REaLiTy Checkin the U.S. Environmental Protection Agency’s(EPA) Designing Industrial Ecosystems Toolkit(DIET) system attempted to overcome the tacitknowledge challenge through an extensive rule-based expert system. Attempting to codify moretacit knowledge with this approach is less thanelegant and can quickly balloon into a seemingly



inexhaustible and arbitrary alchemy of rule-basedmethods. Third, perhaps a naıve perspective ledplanners and facilitators to believe that, onceidentified, synergies would naturally take offor become implemented of their own accord.Lastly, outside of an established knowledge net-work, reciprocity and collaboration may not beavailable.

Although figure 1 reduces a cyclical processto a linear diagram, each individual system’shorizontal representation should be viewed as acircular process as shown in figure 2. From thisperspective, opportunity identification would ap-propriately appear as one step in a cyclical processand not necessarily the only starting point. Indus-trie et Synergies Inter-Sectorielles (ISIS) initiallybegan by gathering a large set of documented suc-cessful synergies. Starting with documentationand publication, instead of opportunity identifi-cation, would provide a strategy similar to thatas described by Chertow (2007) if the syner-gies documented belonged to the community inwhich the system was to be employed. Further-more, closing the loop between commercializa-tion and opportunity identification is a criticalstep in transforming IS from an ad hoc process toan evolving community of practice.

User Interaction Models

Four distinct user interaction models emergedfrom the systems studied. These models—planner/designer, facilitator, networked facilita-tor, and participant—are based on the targetedusers who interact with the ICT system (figure 3).

AutocraticThe autocratic model is characterized by top-

down management and flows of informationthrough a central node. The process was oftenreferred to as “planning,” “engineering,” “opti-mization,” “architecture,” or “design.” This modelemploys ICT to input explicit knowledge gath-ered from participants and output an optimizeddesign for resource or energy flows that is thendisseminated back to the participants. For thesystems studied, this was generally a single itera-tion process resulting in a fixed optimum design.Regardless of an autocratic system’s complexity,the single network hub creates a knowledge bot-tleneck and an inability to communicate tacit

knowledge. As witnessed during application ofthe EPA’s DIET system, ICT tools can provide afocal point to bring a community together dur-ing an interactive planning process (IndustrialEconomics 1998). These gatherings would them-selves offer a participatory process even if theICT was not designed to support it. Furthermore,modern practices in planning tend away from anautocratic approach, toward a participatory com-municative process.

FacilitatorThe facilitator model resembles the autocratic

model in that there is a single person or smallgroup that collects information from the partici-pants, employs a central ICT solution to processthe data, and then relays results back to the par-ticipants. However, unlike the autocratic model,the facilitator’s goal is to build network ties byestablishing connections through introductionsbetween the individual participants. The partic-ipants can then communicate with each otherto assess their complementary processes and anypotential synergies. The facilitator role is anongoing process of continual iteration as par-ticipants join, update their information, or asnew processes are discovered. This model is lessfocused on an optimum or centrally planned net-work, but more so on making knowledge accessi-ble to and between the members, and encourag-ing cooperation through a participatory process.

Networked FacilitatorThe networked facilitator model closely re-

sembles the facilitator model but is characterizedby a large number of facilitators who use a combi-nation of distributed and networked ICT systemsto communicate among one another. The ICTsystems cater toward multiple remote users andinclude a primary focus on communication.

ParticipantThe participant model facilitates communi-

cation directly between networked participants.This approach provides direct and distributed ac-cess to participants, allowing them use of ICTtools designed to store and transfer knowledgethroughout the synergy development process.Participants are the primary users, identifying po-tential opportunities, establishing dialogue with



Figure 3 Industrial symbiosis information and communication technology interaction models and associatedattributes.

complementary users, posting successful syner-gies, reviewing and vetting information, andharnessing ICT to support and initiate offlinecommunication. Even though communication istaking place online, a participant system enablesthe flow of less explicit knowledge and builds re-lationships necessary to support the exchange of

more tacit knowledge. The various functionali-ties associated with the facilitator and designerICT technologies, such as case study mimick-ing, may be incorporated into a participant-basedsystem, but will require larger investments inusability and sociability to successfully interactwith a great number of inexperienced users.



Although not yet established within the doc-umented case studies, a networked participantmodel could emerge if many nested, perhapsregional, participant networks communicatedamong one another through shared system pro-tocols. This model could evolve by either trans-ferring access from a networked facilitator systemto the participants or by connecting many estab-lished participant networks.

Interaction Model Summary

When drawn in figure 3, the evolution of in-teraction models is similar to the developmentof a high-performance knowledge network (Dyerand Nobeoka 2000). The oldest systems [Match-maker!, Knowledge-Based Decision Support Sys-tem (KBDSS), DIET, Industrial Materials Ex-change Tool (IME)] illustrate an initiation orimmature network. Recent systems (Presteo) usea facilitator interaction model that resembles adeveloping knowledge network. The most devel-oped ICT systems incorporate networks of facili-tators [Institute of Eco-Industrial Analysis WasteManager (IUWAWM) and CRISP]. While someattempts have been made (WasteX), a success-ful participant-based network has not yet beenobserved.

Conclusions

Knowledge-based economics provides under-standing for many current observations docu-mented in IS literature. A respect for both ex-plicit and tacit knowledge not only predicts manyof the challenges associated with IS; it opens awealth of previous research that can be drawnupon to strategically identify opportunities forsuccessful development. The growing research inknowledge management provides tactical meth-ods for leveraging the “information revolution” tofacilitate both tacit and explicit knowledge flow.

The systems studied clearly demonstrate tech-nological feasibility of ICT to enhance IS de-velopment. Almost every study resulted in theidentification of opportunities for a majority ofthe participants. Further development should beconsidered to provide ICT support that followssynergy development through barrier removal,commercialization, review, and documentation.

Once a knowledge network is constructed that iscapable of storing, applying, and creating knowl-edge throughout the development process, IS cantransition from an ad hoc process to a flourishingindustrial practice.

Perhaps the most critical challenge to the sys-tems surveyed was their lack of sociability. Thiswas best illustrated by their focus on connect-ing inputs and outputs rather than people. Al-though the tools produce technical opportunitiesbetween firms, the earlier tools overwhelminglycatered toward a master designer, planner, or bro-ker and away from the individual participantswho are expected to form highly invested, sym-biotic relationships. Although stated intentionswere otherwise, early tools appear to have beendesigned for the engineer who built them, per-haps partly explaining their short lifetime. Thetools still in use today are those built in supportof and utilized by very specific existing communi-ties of users and not those that were built merelyin hopes of inspiring such a community.

Relationship management and participantcommunication are only the most recent devel-opments within the tools surveyed. Further de-velopment in sociability will begin to identifyand harness resources through established trustedrelationships, and also explore the nuances ofcreating those relationships when they are notalready present. The second immense challengefaced by the existing tools is usability. Many ofthe designer/planner tools surveyed require so-phisticated computer and programming skills inaddition to a comprehensive knowledge of a mul-titude of industrial organizations. As systems aredesigned for networked facilitators and partici-pants, large upfront investment will be necessaryin usability and sociability to shorten the learningcurve and establish motivation for new users.

Nonstandardized classifications restrictsearchability, create noise or meaningless results,and prohibit automated or suggestive matchingthat could significantly save time for the user.Significant classification developments havebeen made on an individual basis among the sys-tems studied. However, the IS community wouldstand to benefit greatly from a collaborativeinitiative to establish standardized taxonomies orclassifications for resources. This initiative mayresemble communication protocol development



in the ICT community. Similarly, an industrialclassification system that transcended continentswould go a long way toward facilitating explicitinformation transfer to target synergies fordiffusion throughout the world.1

Lastly, creating a successful knowledge net-work requires establishing a critical mass asnetworks’ value is in the user participation. Aknowledge network requires a great deal of up-front investment to create the participant-drivenvalue required to self-perpetuate the system.However, an IS network will require a great dealof offline communication, and substantial invest-ment is required to initiate these offline commu-nication channels. The investment required tocreate such a community should not be takenlightly.

Fostering IS requires driving down the cost ofcreating, storing, and transferring both explicitand tacit knowledge. Through examples of col-laboratively built knowledge networks, precedentexists for strategically and intentionally develop-ing social capital required for innovation and de-velopment within an industrial community. Fur-thermore, strong evidence exists to suggest thatICT can enable this process, and thus the “infor-mation revolution” can be leveraged to supportan “industrial symbiosis revolution”.

Acknowledgements

Support for this research was provided by aPurdue University School of Civil EngineeringRoss Fellowship.

Note

1. Editor’s note: See the discussion of the possible ap-plication of new web technologies for use in indus-trial ecology by Davis and colleagues (2010) in thisissue.

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About the Authors

Gabriel B. Grant is a doctoral student at theCenter for Industrial Ecology in the Yale Schoolof Forestry and Environmental Studies in NewHaven, CT, USA. Thomas P. Seager is a profes-sor in the School of Sustainable Engineering &the Built Environment and the Ira Fulton Schoolsof Engineering at Arizona State University inTempe, Arizona, USA. Guillaume Massard is adoctoral student in the Industrial Ecology Groupat the Institute for Land Use Policy and HumanEnvironment in the Faculty of Geosciences andEnvironment at the University of Lausanne inSwitzerland. Loring Nies is a professor in the Di-vision of Ecological & Environmental Engineer-ing and the School of Civil Engineering at PurdueUniversity in West Lafayette, Indiana, USA.

Supporting information

Supporting Information may be found in the online version of this article:

Supplement S1. This appendix contains capsule summaries of the information and commu-nication technology (ICT) applications developed for the facilitation of industrial symbiosisassessed in this article.

Please note: Wiley-Blackwell is not responsible for the content or functionality of any supple-mentary materials supplied by the authors. Any queries (other than missing material) should bedirected to the corresponding author for the article.


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Information and Communication Technology for Industrial Symbiosis

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