Information and Communication Technology for Industrial Symbiosis

Authors


Address correspondence to:
Gabriel B. Grant
Center for Industrial Ecology
Yale University
195 Prospect St
New Haven, CT 06511
gabriel.grant@yale.edu

Summary

Industrial symbiosis describes the mutualistic interaction of different industries for beneficial reuse of waste flows or energy cascading that results in a more resource-efficient production system and fewer adverse environmental impacts. Research shows that many information and communication technology (ICT) tools for industrial symbiosis development have been created, but the results of those efforts are unclear. Drawing from advancements in knowledge-based economics and management, this article applies a knowledge-based framework to evaluate opportunities for ICT within industrial symbiosis development. ICT systems designed to enable industrial symbiosis are surveyed and evaluated within the proposed framework to identify strengths, trends, and opportunities for continued development. An appendix provides a capsule summary of the 17 ICT tools that are assessed in the article.

Introduction

The maturation of the industrial revolution has created an economy that is increasingly interconnected and information based. Where products have been standardized and markets automated, modern information and communication technology (ICT) has significantly reduced transaction costs. However, for nonstandard, or nonmarket transactions between different business organizations such as those that characterize industrial symbiosis (IS), application of ICT is less successful. We hypothesize that the failure of ICT tools for IS is due to the necessity of tacit knowledge, and given that tacit knowledge sharing requires relationship or community, ICT systems built to supplant rather than support a community will fail to achieve IS. Furthermore, as ICT evolves from optimization and data sharing toward community-building, it will become more supportive of IS.

IS describes industrial networks that cooperatively optimize resource flows for a collective benefit greater than the sum of individual benefits that could be achieved by acting alone. Such networks often exchange by-products, share resources and infrastructure, and engage collectively in related environmental projects. The most well known of these networks is located in Kalundborg, Denmark (Ehrenfeld and Gertler 1997), but many exist across the globe.

IS linkages often form between companies of different industrial sectors that do not have established customer/supplier relationships and thus require communication that transcends the existing customer/supplier network. To address this challenge, many ICT tools have been developed in support of IS. Yet, most of these tools have fallen from use having made little impact in the development of IS linkages. Evaluating the evolution of ICT tools for IS with respect for the knowledge requirements of IS provides explanation for the early mixed results and pathways for future development.

Early ICT systems are heavily criticized for their tendency to focus on explicit knowledge, whereas tacit knowledge, such as social capital and trust, is essential for the mutualistic, nonmarket interactions required for IS (Desrochers 2004). Knowledge-based economic theory provides a framework to explain the mixed results of ICT for IS (Grant 1996). Understanding how knowledge is communicated requires a distinction between two types of knowledge: (1) explicit knowledge or information and (2) tacit knowledge or know-how. Explicit knowledge or information is easily communicated, codified, or centralized using tools such as statistics. However, tacit knowledge is complex and is not codified. It is revealed through application and context and is therefore costly to communicate between people (Kogut and Zander 1992; see Table 1).

Table 1.  Tacit versus Explicit Knowledge [adapted from Kogut and Zander (1992)]
DescriptionExampleIndividualGroupOrganizationNetwork
Explicit knowledge or information100110 101001FactsWho knows whatAccounting data, intellectual property, market researchPrices, whom to contact, who has what
Tacit knowledge or know-howinline imageCommunication and problem-solving skills, trustCoordination, who can get things doneMotivations and incentives for cooperationHow to cooperate, network identity, expectations for reciprocity

Unlike commodities such as recycled metals, which can be traded solely on the basis of explicit knowledge, waste materials are typically nonstandard, off-spec, or highly variable in composition. Industrial symbioses, compared with traditional commodity exchanges, are characterized by more tacit knowledge flows and application. This distinction provides understanding for many current observations documented in IS literature. Put simply, tacit knowledge or know-how cannot be transferred vertically through a hierarchy or to and from a central authority (Grant 1996). If IS relies on tacit knowledge, this limitation predicts: (1) the concepts of social capital and trust as key precursors for IS development (Ehrenfeld and Gertler 1997; Gibbs 2003), (2) the importance of a network model for success (Berends 2001; Mirata 2004; Mirata and Emtairah 2005; Van Beers et al. 2007), (3) the failure of autocratic planning analogous to that of a centrally planned economy (Desrochers 2004), and (4) the ability to nurture or accelerate IS where it has already been found to exist (Chertow 2007).

The knowledge-based perspective opens a wealth of research that can be drawn upon to strategically identify opportunities for successful development. The ability of ICT to enable communication of explicit knowledge is commonly understood. Much recent research focuses on the ability of ICT to promote explicit and tacit knowledge sharing through the creation of community, social capital, and trust.

Traditionally, establishing trust favors “co-presence and co-location” and “for ICTs to assist knowledge transfer across distance, the individuals involved must succeed in creating a virtual location in which they share a common social and cultural institutional framework (…). The need to fulfill this prerequisite restricts the scope of technologically assisted communication as a replacement for face-to-face contact” (Roberts 2000). In certain cases, face-to-face communication may be a prerequisite for trust in computer-mediated communication (Hossain and Wigand 2004).

Critics contend that ICT threatens intimate community interaction (as reviewed by Wellman 1999) and tends toward compartmentalizing knowledge, expressing only its explicit sides, suggesting that knowledge can exist independently from its knowing subjects, and reinforcing organizational structures that do not allow knowledge development (as reviewed in Hendriks 2001). ICT systems built to supplant a community rather than support a community are not effective at transferring knowledge to encourage innovation (Swan et al. 2000). However, growing research in sociology, behavioral science, and knowledge management contributes toward a new awareness that ICT can directly enable communities by strengthening social capital. In particular, the Internet reinforces existing community structures through enhanced communication (Blanchard and Horan 1998; DiMaggio et al. 2001; Haythornthwaite 2001; Howard et al. 2001).

ICT systems are now designed with the specific objectives of fostering community social capital and trust (Abdul-Rahman and Hailes 2000; Kasper-Fuehrer and Ashkanasy 2001; Huysman and Wulf 2006) and facilitating the transferability of otherwise highly illusive tacit knowledge (Stenmark 1999). The terms online communities and virtual communities have emerged to describe computer-mediated social groups (Preece 2000; Rheingold 2000). Current research and development of online communities is dually focused on usability (human-computer interaction) and sociability (human-human interaction) (Preece 2000).

As an example, Xerox experienced a knowledge-sharing challenge when they discovered their service representatives were succeeding “primarily by departing from formal processes” (Brown and Duguid 2000). Rather than relying on repair manuals or bulletins, service reps were discovered to be locating knowledge through weak-tie networks held together by storytelling during breakfasts, lunches, coffee breaks, and after-hours activities. To benefit from and reward improvisation, Xerox initiated the Eureka project, which transfers locally generated knowledge between service representatives and their respective breakfast clubs throughout a multinational work force via an online community. Unlike prescriptive “best practice” databases, the Eureka database is driven by service reps who provide and screen their own entries. The reps are motivated to provide high-quality participation to build their reputation and own social capital (Brown and Duguid 2000).

As in the Xerox case study, ICT requires a nuanced approach that is appropriately integrated within a more holistic knowledge management system that clearly respects the social and cultural needs and motivations among its community of users. Successful ICT knowledge management systems focus on the human-human communication and overcome the “Western tendency” to merely “put it in a database” (Skyrme 1998).

We hypothesize that the success and failure of attempts to facilitate IS through ICT are predictable for reasons similar to those of early ICT knowledge management systems as well as early attempts at planned IS (e.g., eco-industrial parks). Autocratic hierarchical design or management fails to facilitate the knowledge flows required to produce the desired relationships. Many early ICT systems built in support of IS were first attempts to “put it in a database” and lacked the required investment in usability or sociability. However, through careful observation of the IS process, opportunities for ICT to support the required communication can be identified.

Scope of Research

The greater impact of this research is to leverage the information revolution that has dramatically reduced the cost of communication and information through ICT to transform industrial systems toward IS. To understand the facilitation of IS with ICT, this study takes an inductive approach to synthesizing specific case studies publicly available in literature. General conclusions are reached that assess the current progress of ICT in supporting IS. By examining ICT systems designed to facilitate IS and contrasting their approaches with theoretical illustrations and lessons learned from knowledge-based economics and management, this article identifies strengths, weaknesses, and opportunities for continued development.

Survey of Systems

This study identified 17 ICT systems built to support IS. These systems self-identify as purpose built for creating IS, industrial ecology, by-product synergy, and/or eco-industrial parks. We are not reviewing the whole of ICT or subsystems of ICT for their theoretical applications. For example, excluded ICT tools that could be used throughout the process but are not purpose built for IS could include email, GIS, collaborative project management or document technologies, various modeling technologies, water quality or energy software, and waste exchanges, among others. Our conclusions are therefore reflective on the current state of purpose built ICT for IS and not ICT as a whole.

Assessing the degree of success enjoyed by these tools is problematic. First, the many influential outside variables that affect whether a collaboration comes to fruition could not be controlled to isolate the effectiveness of the ICT tool under observation. Second, researchers struggle to determine in hindsight when and where opportunity identification truly took place since the potential linkages are often identified by the facilitator just before or during data entry and are not exclusively the product of the ICT tool. Therefore, an appropriate indication of whether the system adds value for a user, within this study, is whether the tool is still available and in use.

Of the 17 systems identified, nine are not in use today, three are presently in use although not publicly available, and one is available for purchase over the Internet. Four (not shown in table 2), are currently under development with little information yet publicly available, but are based in Kwinana, Australia; Nova Scotia, Canada; Columbus, Ohio; and Sudbury, Ontario. Abstracts for each of the 13 systems with publicly available information are provided as an appendix available as supporting information on the journal web site.

Table 2.  ICT Systems for Industrial Symbiosis
Systems StudiedGeographic ScaleStatusAvailability
  1. 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). fNobel (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).

Knowledge-Based Decision Support System (KBDSS)aIndustrial parkCompletedNone
Designing Industrial Ecosystems Toolkit (DIET)bIndustrial parkCanceledPublic, reportedly unusable, requires MS Office 95
Industrial Materials Exchange Tool (IME)cCityCanceledNone
Dynamic Industrial Materials Exchange Tool (DIME)dRegionCompletedNone
MatchMaker!eCityCompletedNone
Industrial Ecology Planning Tool (IEPT)fIndustrial parkCompletedSource code available, requires ArcView GIS
WasteXgNationCanceledNone
Industrial Ecosystem Development Project (IEDP)hRegionCanceledNone
Residual Utilization Expert System (RUES)iCity/stateCompletedAvailable to the original project funding organizations, requires Level5 software shell
Institute of Eco-Industrial Analysis Waste Manager (IUWAWM)jRegionOperationalReporting software—purchase and demo available over the web; analysis and optimization systems under development
Industrie et Synergies Inter-Sectorielles (ISIS) and PresteokRegionOperationalIn use by the developer
SymbioGISlRegionOperational/continuous developmentIn use by the developer
Core Resource for Industrial Symbiosis Practitioners (CRISP)mNationOperationalIn use by the developer and select partners

Observations and Discussion

IS Process Model

Each ICT system functions to transfer knowledge within, or in support of, a larger IS development process. Each accompanying larger process varies in its stage of development. Core Resource for Industrial Symbiosis Practitioners (CRISP), for example is built in support of the National Industrial Symbiosis Program (NISP) in the United Kingdom. Thus, considerable information is available on the context or development process outside of the tool. MatchMaker!, for extreme comparison, was a student project and existed on its own, relating to a development process perhaps only in conversation.

Through reviewing the tools within the context of their associated developmental processes, five primary IS developmental phases emerged: (1) opportunity identification, (2) opportunity assessment, (3) barrier removal, (4) commercialization and adaptive management, and (5) documentation, review, and publication. The development process is far from linear and certainly contains many nested feedback loops, but a general circular flow was observed as illustrated in figure 1 and described below. In the discussions that follow, the ICT systems relevant to the developmental stage are identified in figure 2. Capsule descriptions of the ICT systems are provided in an appendix as supporting information on the journal web site.

Figure 1.

Industrial symbiosis development process model.

Figure 2.

Industrial symbiosis information and communication technology tool functionality.

Opportunity Identification

Opportunity identification occurs through three primary means: new process discovery, input-output matching, and relationship mimicking. The first, new process discovery, occurs when a novel approach is created to transform a by-product into a usable resource. The second method, input-output matching, occurs by identifying a resource associated with one organization, and then finding complementary resource inputs or requirements for another organization. The third identification process involves mimicking successful relationships employed by similar organizations.

Input-output matching can be accomplished through brute force investigation, serendipitous discovery, organized workshops, or a coordinated search. Workshops are organized by industry consortia, brokers, and government organizations to identify potential synergies between participating firms. Although opportunity identification through workshops is sometimes successful, obstacles to implementation often prevent these opportunities from realization, unless the workshops are conducted as a single stage of a more comprehensive strategy.

The taxonomical classifications of resources are at present a great challenge to ICT search tools. Without the benefit of a fuzzy logic system to compare resources, the systems studied required common language or specific resource taxonomy to produce relevant search results. For instance, cardboard and paperboard may be substitutable or identical inputs for a by-product process, but their equivalency is based in a more tacit knowledge, which is not easily coded into a computer system. Similarly, resources like “waste water” require an enormous list of attributes for a computer to establish an acceptable match. Therefore, computer-aided input-output matching requires a great deal of upfront investment to create standardized classifications for resources and associated computer interfaces that allow users of widely varying backgrounds and languages to input and retrieve relevant and recognizable information (Massard et al. 2006). Input-output matching is, at this stage, very difficult to codify and thus relies on communication methods more suited to tacit knowledge.

Relationship mimicking is more easily codified and searchable, because unlike resources, standardized classifications for industries are more developed. A successful linkage can therefore be explicitly designated by the two codes for each of the industries it connects. Furthermore, a database of these established linkages combined with a database of existing companies would allow a company to locate geographically proximate complementary firms and successful case study examples of the relevant synergies. Cross-referencing this dataset with a social networking application could target opportunities through established trust relationships by searching for synergies with known friends or prompting introductions through mutual friends. There is opportunity here for ICT to facilitate this search and then to support dialogue between participants.

Opportunity Assessment

Opportunity assessment evaluates the outcomes and challenges associated with a new innovation or process. Common methods for assessment include barrier assessment, benefit/cost analysis, process-based life cycle analysis (LCA) and economic input-output (EIO) LCA modeling. Barrier assessment identifies challenges to realization by assessing market, political, social, environmental, financial, and technical feasibility. Barriers may be difficult to codify and therefore rely heavily on more tacit-based judgments. Other methods are more explicit. Benefit/cost analysis is primarily used to compare monetary outcomes of a decision based on explicit quantifiable information. However, less tangible values such as risk, corporate image, environmental, and social impacts are sometimes quantified in monetary terms for purposes of comparison. Multicriteria objective analysis methods may be employed to weigh outcomes that are not easily quantified into a single unit of measurement. Process-based LCA assesses a product's impact from raw material extraction to end of life and typically incorporates environmental impacts not necessarily felt directly by the producer. EIO analysis predicts the effects of economic changes in one industry on related industries by utilizing a matrix representation of economic flows between industries (Matthews and Small 2000). Combined EIO-LCA modeling performs LCA without the intensive research of following individual processes to termination. EIO-LCA works by first determining the affected industries related to a product or process using EIO and then summing their combined environmental, energy, and employment impacts from aggregated data collected about each industry. In practice, IS development is based primarily on technical feasibility assessment, benefit-cost analysis, and monetary priorities. However, developments in the field of industrial ecology and some of the systems incorporated in this study aim to reduce the cost of employing multicriteria or LCA for future use, and these tools should prove valuable when accounting for social and economic benefits.

Barrier Removal

Barrier removal overcomes or eliminates challenges associated with realization. Regulatory approval may be required for by-product linkages as nontraditional resources are introduced into established industries. Business-to-business contractual agreements may require more investment as quantity and quality assurances for use of by-products must be negotiated. The challenges of financing or procuring investment capital for new linkages are similar to those of any innovation seeking the appropriation of internal or external financing. Traditional support infrastructure through economic development and venture centers, U.S. Small Business Innovation Research grants, and business loans are available. However, new linkages present an inherent public benefit and thus may be eligible for subsidies through environmental incentives or agencies. Technology development of processes to utilize by-products is often required, including pilot implementation or small-scale production utilizing the by-product resource to provide proof-of-concept prior to full-scale commercialization.

Commercialization and Adaptive Management

Commercialization is full-scale implementation of the by-product-based industrial process, and adaptive management provides a feedback loop for continual improvement of the firm's process and strategy based on internal and external assessment. Internal assessment evaluates the actual performance of the synergetic process using similar methods to the opportunity assessment to target opportunities for process improvement or refinement. Within the systems studied, however, this stage is almost entirely isolated from the IS program and handled for development within individual organizations.

Documentation, Review, and Publication

Documentation, review, and publication communicate the success of individual firms and their associated synergies. This phase is critical to establishing a knowledge base to support innovation diffusion within a greater IS community. Third-party validation can occur both systematically (e.g., an auditing process) or spontaneously. Case studies, self-reported or prepared by third parties such as academic institutions, industry consortia, or brokers, can be coded and made searchable within an opportunity identification framework.

ICT System Functionality Throughout the Process Model

The intensity of involvement of each of the tools studied within each of the corresponding IS developmental phases is displayed in figure 1. As previously explained, a broader IS context or program outside of the ICT systems often exists which incorporates other media for storing and communicating knowledge throughout each phase of a symbiosis development. However this analysis shows where investments have been made to specifically leverage ICT within each of the phases.

The surveyed ICT systems predominantly focused their resources toward opportunity identification. Relationship mimicking and input-output matching algorithms were the core components of the ICT systems, with some emphasis on opportunity assessment. Other phases of IS development were mostly addressed through other media, work flow, or communication. The CRISP system was an identifiable exception that broadened its scope beyond opportunity identification and assessment by providing collaborative project management and work flow tools to manage a project toward completion while documenting the process (NISP 2006).

The emphasis on opportunity identification may have several explanations. First, even when recognizing that development is cyclical, opportunity identification appears as a logical starting place. Second, when one focuses on explicit information, there are clear opportunities for ICT within the opportunity identification process. Input-output matching appears as a simple nonlinear optimization routine until the more tacit knowledge concerning the resources is brought into perspective. Programs like REaLiTy Check in the U.S. Environmental Protection Agency's (EPA) Designing Industrial Ecosystems Toolkit (DIET) system attempted to overcome the tacit knowledge challenge through an extensive rule-based expert system. Attempting to codify more tacit knowledge with this approach is less than elegant and can quickly balloon into a seemingly inexhaustible and arbitrary alchemy of rule-based methods. Third, perhaps a naïve perspective led planners and facilitators to believe that, once identified, synergies would naturally take off or become implemented of their own accord. Lastly, outside of an established knowledge network, reciprocity and collaboration may not be available.

Although figure 1 reduces a cyclical process to a linear diagram, each individual system's horizontal representation should be viewed as a circular process as shown in figure 2. From this perspective, opportunity identification would appropriately appear as one step in a cyclical process and not necessarily the only starting point. Industrie et Synergies Inter-Sectorielles (ISIS) initially began by gathering a large set of documented successful synergies. Starting with documentation and publication, instead of opportunity identification, would provide a strategy similar to that as described by Chertow (2007) if the synergies documented belonged to the community in which the system was to be employed. Furthermore, closing the loop between commercialization and opportunity identification is a critical step in transforming IS from an ad hoc process to an evolving community of practice.

User Interaction Models

Four distinct user interaction models emerged from the systems studied. These models—planner/designer, facilitator, networked facilitator, and participant—are based on the targeted users who interact with the ICT system (figure 3).

Figure 3.

Industrial symbiosis information and communication technology interaction models and associated attributes.

Autocratic

The autocratic model is characterized by top-down management and flows of information through a central node. The process was often referred to as “planning,”“engineering,”“optimization,”“architecture,” or “design.” This model employs ICT to input explicit knowledge gathered from participants and output an optimized design for resource or energy flows that is then disseminated back to the participants. For the systems studied, this was generally a single iteration process resulting in a fixed optimum design. Regardless of an autocratic system's complexity, the single network hub creates a knowledge bottleneck and an inability to communicate tacit knowledge. As witnessed during application of the EPA's DIET system, ICT tools can provide a focal point to bring a community together during an interactive planning process (Industrial Economics 1998). These gatherings would themselves offer a participatory process even if the ICT was not designed to support it. Furthermore, modern practices in planning tend away from an autocratic approach, toward a participatory communicative process.

Facilitator

The facilitator model resembles the autocratic model in that there is a single person or small group that collects information from the participants, employs a central ICT solution to process the data, and then relays results back to the participants. However, unlike the autocratic model, the facilitator's goal is to build network ties by establishing connections through introductions between the individual participants. The participants can then communicate with each other to assess their complementary processes and any potential synergies. The facilitator role is an ongoing process of continual iteration as participants join, update their information, or as new processes are discovered. This model is less focused on an optimum or centrally planned network, but more so on making knowledge accessible to and between the members, and encouraging cooperation through a participatory process.

Networked Facilitator

The networked facilitator model closely resembles the facilitator model but is characterized by a large number of facilitators who use a combination of distributed and networked ICT systems to communicate among one another. The ICT systems cater toward multiple remote users and include a primary focus on communication.

Participant

The participant model facilitates communication directly between networked participants. This approach provides direct and distributed access to participants, allowing them use of ICT tools designed to store and transfer knowledge throughout the synergy development process. Participants are the primary users, identifying potential opportunities, establishing dialogue with complementary users, posting successful synergies, reviewing and vetting information, and harnessing ICT to support and initiate offline communication. Even though communication is taking place online, a participant system enables the flow of less explicit knowledge and builds relationships necessary to support the exchange of more tacit knowledge. The various functionalities associated with the facilitator and designer ICT technologies, such as case study mimicking, may be incorporated into a participant-based system, but will require larger investments in usability and sociability to successfully interact with a great number of inexperienced users.

Although not yet established within the documented case studies, a networked participant model could emerge if many nested, perhaps regional, participant networks communicated among one another through shared system protocols. This model could evolve by either transferring access from a networked facilitator system to the participants or by connecting many established participant networks.

Interaction Model Summary

When drawn in figure 3, the evolution of interaction models is similar to the development of a high-performance knowledge network (Dyer and Nobeoka 2000). The oldest systems [Matchmaker!, Knowledge-Based Decision Support System (KBDSS), DIET, Industrial Materials Exchange Tool (IME)] illustrate an initiation or immature network. Recent systems (Presteo) use a facilitator interaction model that resembles a developing knowledge network. The most developed ICT systems incorporate networks of facilitators [Institute of Eco-Industrial Analysis Waste Manager (IUWAWM) and CRISP]. While some attempts have been made (WasteX), a successful participant-based network has not yet been observed.

Conclusions

Knowledge-based economics provides understanding for many current observations documented in IS literature. A respect for both explicit and tacit knowledge not only predicts many of the challenges associated with IS; it opens a wealth of previous research that can be drawn upon to strategically identify opportunities for successful development. The growing research in knowledge management provides tactical methods for leveraging the “information revolution” to facilitate both tacit and explicit knowledge flow.

The systems studied clearly demonstrate technological feasibility of ICT to enhance IS development. Almost every study resulted in the identification of opportunities for a majority of the participants. Further development should be considered to provide ICT support that follows synergy development through barrier removal, commercialization, review, and documentation. Once a knowledge network is constructed that is capable of storing, applying, and creating knowledge throughout the development process, IS can transition from an ad hoc process to a flourishing industrial practice.

Perhaps the most critical challenge to the systems surveyed was their lack of sociability. This was best illustrated by their focus on connecting inputs and outputs rather than people. Although the tools produce technical opportunities between firms, the earlier tools overwhelmingly catered toward a master designer, planner, or broker and away from the individual participants who are expected to form highly invested, symbiotic relationships. Although stated intentions were otherwise, early tools appear to have been designed for the engineer who built them, perhaps partly explaining their short lifetime. The tools still in use today are those built in support of and utilized by very specific existing communities of users and not those that were built merely in hopes of inspiring such a community.

Relationship management and participant communication are only the most recent developments within the tools surveyed. Further development in sociability will begin to identify and harness resources through established trusted relationships, and also explore the nuances of creating those relationships when they are not already present. The second immense challenge faced by the existing tools is usability. Many of the designer/planner tools surveyed require sophisticated computer and programming skills in addition to a comprehensive knowledge of a multitude of industrial organizations. As systems are designed for networked facilitators and participants, large upfront investment will be necessary in usability and sociability to shorten the learning curve and establish motivation for new users.

Nonstandardized classifications restrict searchability, create noise or meaningless results, and prohibit automated or suggestive matching that could significantly save time for the user. Significant classification developments have been made on an individual basis among the systems studied. However, the IS community would stand to benefit greatly from a collaborative initiative to establish standardized taxonomies or classifications for resources. This initiative may resemble communication protocol development in the ICT community. Similarly, an industrial classification system that transcended continents would go a long way toward facilitating explicit information transfer to target synergies for diffusion throughout the world.1

Lastly, creating a successful knowledge network requires establishing a critical mass as networks’ value is in the user participation. A knowledge network requires a great deal of upfront investment to create the participant-driven value required to self-perpetuate the system. However, an IS network will require a great deal of offline communication, and substantial investment is required to initiate these offline communication channels. The investment required to create such a community should not be taken lightly.

Fostering IS requires driving down the cost of creating, storing, and transferring both explicit and tacit knowledge. Through examples of collaboratively built knowledge networks, precedent exists for strategically and intentionally developing social capital required for innovation and development within an industrial community. Furthermore, strong evidence exists to suggest that ICT can enable this process, and thus the “information revolution” can be leveraged to support an “industrial symbiosis revolution”.

Acknowledgements

Support for this research was provided by a Purdue University School of Civil Engineering Ross Fellowship.

Notes

  • 1

    Editor's note: See the discussion of the possible application of new web technologies for use in industrial ecology by Davis and colleagues (2010) in this issue.

About the Authors

Gabriel B. Grant is a doctoral student at the Center for Industrial Ecology in the Yale School of Forestry and Environmental Studies in New Haven, CT, USA. Thomas P. Seager is a professor in the School of Sustainable Engineering & the Built Environment and the Ira Fulton Schools of Engineering at Arizona State University in Tempe, Arizona, USA. Guillaume Massard is a doctoral student in the Industrial Ecology Group at the Institute for Land Use Policy and Human Environment in the Faculty of Geosciences and Environment at the University of Lausanne in Switzerland. Loring Nies is a professor in the Division of Ecological & Environmental Engineering and the School of Civil Engineering at Purdue University in West Lafayette, Indiana, USA.

Ancillary