Seeking open infrastructure: Contrasting open standards, open source, and open innovation | Opensource.com

Seeking open infrastructure: Contrasting open standards, open source, and open innovation

Posted 20 Dec 2010 by 

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While “open” normally has connotations of public goods, the idea of “open”–ness has been used for decades as a competitive strategy by firms in the computers and communications industries. Phrases like “open standard,” “open source” and more recently “open innovation” have been used to refer to these strategies.

What do they have in common? Which ones really are “open”? What does “open” mean, anyway?

To consider the issues faced in the creation and adoption of cyberinfrastructure, here I contrast firm strategies for these three types of “open”–ness in the context of their respective business models. Any firm needs a business model if it hopes to profit from innovation (Chesbrough, 2003). Across disparate research on business models, the three common elements of a business model are value creation, value capture and a value network (West, 2007).

I focus on the issues related to systems-based industries (as with computers or mobile phones) where multiple firms within a value network work together to create and capture value; a simplified example of such a value network is shown in Figure 1. After considering the general issues of openness in IT systems, I look more specifically at the questions of openness as they related to a possible cyberinfrastructure designed to enable new forms of scientific research and collaboration in the twenty–first century (cf. Edwards, et al., 2007).

Figure 1: Value networks in IT-based systems industries Figure 1: Value networks in IT–based systems industries. Source: West (2006a, p. 112).

Open standards

The term “open” has been used for standards since at least the 1960s. For some — as in the U.S. computer industry — “open” merely meant “not IBM” and later “not Microsoft.” For others — such as in the European telecommunications industry — “open standard” was redundant, because if it wasn’t an “open” standard, produced using “open” procedures (e.g. the ITU or ISO), then it wasn’t really a “standard.”

As in the research on organizational fairness, an “open” standard usually has two justifications: open in the process, or open in the outcome (cf. Greenberg, 1990). The open process is the perspective of the standards creators, and is normally associated a particular type of standards–setting organization (SSO) — a formal standards development organization rather than a standards consortium or private firm. The process fairness is achieved through the structure of the SSO: for example, Krechmer (2006) identifies key elements of process fairness as open meetings, due process in voting, and transparency of meeting outcomes.

The other form of openness is openness of outcomes. Buyers seek an open enough outcome to assure competing implementations of the standard, in hopes of providing price competition and thus lower prices. However, no standardization activity that is economically self–supporting can be perfectly open: from an economic perspective, there are limits to openness (West, 2006b). Simcoe (2006) observes that in standardization, firms face an inherent conflict between value creation and value capture. A completely open standard creates lots of value, none of which can be captured; a completely closed standard captures 100 percent of no value created. So a profit–maximizing firm must seek an intermediate point that partially accomplishes both goals.

Thus to pay the bills, there has to be value capture somewhere: everything has some level of openness and some level of proprietary–ness1. Typically, standards that are open in one area are often not open in another. An “open” standard may use the copyright on the standard to charge to view or use the standard. Even a process that is nominally open may be dominated by a few big companies that steer the technical definitions to overlap their own intellectual property and competencies (Bekkers, 2007).

Open source

In the narrowest sense, open source software is defined by a particular form of software license approved by the non–profit Open Source Initiative. In practical terms, the concept of open source has three dimensions: an IP license, a virtual development process and a system of shared governance (O’Mahony and West, 2005).

Compared to open standards, open source has one huge advantage: you can use the technology without bearing the cost of implementing it. If it’s licensed under a permissive (non–viral) license (cf. Rosen, 2005), a firm can even use it to build its own technology for sale. But there is no guarantee that an open source package will be produced using the process fairness of, say, the ISO — even if you ignore the effect of founder privilege (“benevolent dictator for life”). And while a standards setting organization such as the IETF requires multiple implementations as a core value, open source (or particularly “free software”) partisans decry multiple implementations as “forking.”

Certainly there is open source software that is developed for shared benefit by altruistic volunteers.2 However, the provision of labor and other resources for major open source projects has been increasingly driven by contributors working to advance the goals of their employers, i.e. corporate interests (Hars and Ou, 2001). When firms sponsor open source projects, they have an easier time providing transparency to outsiders than sharing control with them (O’Mahony and West, 2005).

Given an open source IP license makes it difficult to capture value, how do firms create profitable business models around open source? Typically, they give away the open source to create value, but capture value through the sale of related products or services (West, 2007).

Open innovation

A lot of open source and open standards participants wonder what’s “open” about “open innovation.” After all, both of the former have a shared or public goods element to them, whereas a prime goal of open innovation (as defined by Chesbrough, 2003) is that firms have a way to capture a private return. In fact, in West and Gallagher (2006) I argue that the purest forms of open source or free software (such as Project GNU) are specifically not open innovation.

Still, open innovation can incorporate a public goods aspect. The pooled R&D of an open source consortium (such as the IBM–led Project Eclipse) inherently creates spillovers outside the consortium, no matter how much the consortium partners might want to appropriate the returns for their own. Eclipse, the Globus Alliance and other such projects offer a new paradigm for collaboration between for–profit actor to support both public gain and private value capture, in particularly by generating compatible implementations of essential industry technologies.

Even without such public goods, the practice of open innovation is inherently open in other ways. Innovation occurs across the boundaries of the firm, and both the value creation and value capture activities are spread across the value network, rather than controlling them within the scope of a single firm (cf. Vanhaverbeke and Cloodt, 2006). It is for these reasons that shifting from closed to open innovation is often traumatic for a large firm that was previously successful in its vertical integration.

Enabling collaboration and competition

For open standards, open source and open innovation, the “open” part refers to collaboration by firms in producing some form of shared output. While sometimes openness is forced by buyers or regulators, today many firms voluntarily favor openness for those problems that require coordination and cooperation.

Openness can be deliberately used to attract user adopters (West, 2003), as well as others in the value network. It also can be used to align the interests of firms across the value network. Systems industries (such as in the IT sector) inherently require a value network in which the suppliers, customers, competitors and complementors collaborate to create value (West, 2006a). If anything, being open only cements these relationships as it more closely aligns the interests of the various firms in the network.

At the same time, in even the most open business ecosystem, firms will pursue their own (inherently competing) private interests (Iansiti and Levien, 2004). O’Mahony (2005) refers to this as “competing on a common platform.” Such private interests require that firms ultimately capture value.

Thus for all three forms of cooperation, openness makes it easier to create value and assure cooperation across the value network, but harder to capture value.

Open innovation is not “open” like the other two. If anything, open innovation brings a note of realism to the discussion of open standards and open source, by putting the profit motive front and center. Both open standards and open source must serve the interests of those stakeholders that provide the essential resources. If firms choose not to participate (or not participate seriously) in a standards effort, that is a signal from the market about how well they feel that effort fits with their business model. While standardization cannot be held hostage to the private interests of any one firm, SSOs have long known that a standard not endorsed by major vendors is the tree that falls in the forest — and thus incorporate such market signals into their decisions.

Conversely, open standards and open source provide existence proofs for building effective institutions that align and coordinate the interests of potential competitors. For example, the open source license provides a “credible commitment” to make it less likely that commercial interests will under–invest in specific technologies.

Openness in infrastructure

Standardization is an important prerequisite to the deployment and use of a shared infrastructure. American railroads were not successful until they standardized time, rail gauge, and safety equipment across various manufacturers and operators (Friedlander, 1995). For electric power, standardization choices had major impacts throughout an entire system, from generation, transmission, delivery and use (Friedlander, 1996).

More directly related to the problems of cyberinfrastructure comes from the past 40 years of the I.T. industry, which developed computing and networking standards — the “plumbing” for future cyberinfrastructure. Formal standards development organizations (SDOs) played a role in a few of these standards, such as ASCII. However, voluntary industry cooperation through professional organizations such as the IEEE was responsible for many more standards, such as Ethernet and Unix APIs (cf. Isaak, 2006). And some of the most important infrastructure standards — such as TCP/IP, FTP, and SMTP — were established by a single organization (U.S. Department of Defense) working with its suppliers to define standards for its own use.

Cyberinfrastructure standardization can build upon the best practices established by existing Internet SSOs such as the IETF and the W3C. Such organizations — along with formal SDOs such as those accredited by the ISO — have already developed the processes and policies necessary for open standardization (Krechmer, 2006; West, 2006b).3 Any form of standardization must include the relevant stakeholders if the backers hope to see widespread development and deployment of implementations. One way to facilitate development is to combine standardization with open source implementations, much as the open source Globus Toolkit from the Globus Alliance is helping deploy the grid computing that will be an essential part of cyberinfrastructure.

Like the Internet infrastructure, the eventual cyberinfrastructure is expected to comprise an internetwork of systems, much as the Internet linked disparate local and wide–area networks with a unified addressing scheme (cf. Edwards, et al., 2007). One obvious implication is that cyberinfrastructure standards must define the interfaces to allow interconnection of these various infrastructural elements. Another is that even with such standards, a key prerequisite to deployment will be the willingness of vendors to modify their existing products to support these interfaces and thus enable cyberinfrastructure connectivity.

Facilitating deployment and adoption

As with any other innovation, overall adoption of cyberinfrastructure will depend on the decisions of individual researchers and organizations. A key factor in adoption is what Rogers (1995) terms “relative advantage,” which I.T. buyers have come to expect means “better, faster and cheaper.” In some cases, the new technology will replace previously labor–intensive processes, much as Google Scholar today makes it easy to search a broad pool of research published in the last decade4. In other cases, the new technology will make possible a scope or depth of research that was previously impossible, much as the rise of inexpensive supercomputers made gene sequencing possible for individual research labs.

There is also the question of overcoming prior path dependencies. Today, cyberinfrastructure is being designed and deployed to a world that already has existing solutions, and so most potential users will face some form of switching costs, both economic and psychic. Faced with such switching costs, individual adopters (e.g. harried, under–funded academics) will tend towards locally rational decisions reflecting their own individual cost–benefit analysis, rather than some sort of aggregate societal good. As Liebowitz and Margolis (1999) remind us, the rational adopter considers not only whether a new technology is better, but whether it’s enough better to recover the costs (both economic and psychic) that will be incurred in switching to it.

As an extreme measure, sponsors can compel adoption, as the Defense Department did with the ARPANET and the National Science Foundation did with NSFNet (Edwards, et al., 2007). This may be applicable for research domains where a single funding agency holds a large share of the purse strings, as the National Institutes of Health does for U.S. medical research, but it will potentially leave untouched the switching costs of entire fields of scientific study.

To make migration easier, here open standards are not enough: a shared specification for cyberinfrastructure standards limits support to those organizations large enough to develop their own implementations. One solution is to make the core implementation widely available, to facilitate a migration path for legacy technologies by reducing the development time and costs faced by vendors of such technologies5. Open source software is one solution — much as the Berkeley implementation of TCP/IP allowed the networking protocol to become ubiquitous among computer companies in the 1980s and 1990s. Open innovation provides another possibility, if multiple organizations work together to develop a shared implementation of a commodity technology (West and Gallagher, 2006).

Future research

Much as 13 years ago we wondered about the future of the shared information infrastructure (which became the Internet), today there are many unresolved questions about the future of cyberinfrastructure. Some are normative questions for policymakers, centering on what is the best way to make cyberinfrastructure succeed?6 Other questions belong in the domain of positive or causal research, such as the cost–benefit tradeoffs faced by individual stakeholders in deploying such infrastructure.

Some of these questions relate to open standards. Cyberinfrastructure faces the same openness issues of lower–level IT infrastructure, such as the questions of whether openness a process or an outcome, what degree of openness is required, and for whom should it be opened. But will the process of cyberinfrastructure standardization be more similar to the vendor–driven process of IT standardization, or the user–driven standardization of domain–specific standards such as vertical industry standards? (cf. Wigand, et al., 2005).

There is also the relationship between standards creation and standards implementation. Do cyberinfrastructure standards need multiple implementations, as the IETF requires for Internet standards? Multiple public implementations? A single, shared, open source implementation? When it comes to implementations, which goal is most important: technical competition, market competition or eliminating redundant investment?

Finally, there are questions of the economic incentives for participation by the various actors. If the open technology is a commodity technology, how is it partitioned? Who decides how it is partitioned? One firm’s infrastructure is another firm’s core product.

Prior research on open standards, open source and open innovation offers ways of studying these questions, but new research will be required to understand how the problems of cyberinfrastructure openness are similar to and different from those faced in developing the existing IT infrastructure.

 


Notes

1. In claiming that all standards have open and proprietary elements, I don’t mean to suggest that the architecture of a Lisa is as open as a Lintel box.

2. While the “open source” and particularly the “free software” movement have been accused of being socialist or worst, even within these movements there is considerable individual variation in the relative importance ideological vs. pragmatic motivations for open source contributors (see Raymond, 1998).

3. The one notable exception is the increasing and unresolved problem of managing patent royalties for nominally “open” standards (cf. Simcoe, 2006).

4. This functionality has been available for years through traditional article databases in a few fields (like MedlinePlus in medicine and EconLit in economics). Journal coverage has been fragmented between multiple competing databases in other fields such as management (ABI/Inform vs. Business Source Premier) and engineering (IEEE vs. ACM vs. INSPEC).

5. For commercial products, the incentive for vendors would be to rehost the existing product on top of the new infrastructure rather than to supplant their revenue–producing products. For open source packages (or internal research tools), users are more likely to get help migrating to new shared applications made available as part of the cyberinfrastructure.

6. As Edwards, et al. (2007) and the research cited therein remind us, the success of infrastructure standardization is often considered only in the technical domain, but also has economic and social dimensions as well.

References

Rudi Bekkers, 2007. “Patent drag and stacking IPR fees,” paper presented at the Tilburg Law and Economics Center High–level Workshop on Standardization, IP Licensing and Antitrust, Brussels (18 January), at http://home.tm.tue.nl/rbekkers/Bekkers%20(2007)%20Position%20paper%20-%20TILEC%20conference%20.pdf, accessed 20 June 2007.

Henry Chesbrough, 2003. Open Innovation: The New Imperative for Creating and Profiting from Technology. Boston: Harvard Business School Press.

Paul N. Edwards, Steven J. Jackson, Geoffrey C. Bowker and Cory P. Knobel, 2007. “Understanding Infrastructure: Dynamics, Tensions, and Design,” Report of a Workshop on History & Theory of Infrastructure: Lessons for New Scientific Cyberinfrastructures, University of Michigan, School of Information, (January), at http://deepblue.lib.umich.edu/handle/2027.42/49353, accessed 20 June 2007.

Amy Friedlander, 1996. Power and Light: Electricity in the U.S. Energy Infrastructure, 1870–1940. Reston, Va.: Corporation for National Research Initiatives.

Amy Friedlander, 1995. Emerging Infrastructure: The Growth of Railroads. Reston, Va.: Corporation for National Research Initiatives. Jerald Greenberg, 1990. “Organizational Justice: Yesterday, Today, and Tomorrow,” Journal of Management, volume 16, number 2 (June), pp. 399–432.

Alexander Hars and Shaosong Ou, 2001. “Working for Free? Motivations of Participating in Open Source Projects,” Proceedings of the 34th Hawai’i International Conference on System Sciences (January), volume 7, p. 7014, and at http://www.hicss.hawaii.edu/HICSS_34/PDFs/INCDE05.pdf, accessed 20 June 2007.

Marco Iansiti and Roy Levien, 2004. The Keystone Advantage: What The New Dynamics of Business Ecosystems Mean for Strategy, Innovation, and Sustainability. Boston: Harvard Business School Press.

Jim Isaak, 2006. “The Role of Individuals and Social Capital in POSIX Standardization,” International Journal of IT Standards and Standardization Research, volume 4, number 1 (January), pp. 1–23.

Ken Krechmer, 2006. “Open Standards Requirements,” International Journal of IT Standards and Standardization Research, volume 4, number 1 (January), pp. 43–61.

Stan J. Liebowitz and Stephen E. Margolis, 1999. Winners, Losers & Microsoft: Competition and Antitrust in High Technology. Oakland, Calif.: Independent Institute.

Siobhán O’Mahony, 2005. “Competing on a Common Platform,” paper presented at the Davis Conference on Qualitative Research, Davis, Calif. (March).

Siobhán O’Mahony and Joel West, 2005. “What Makes a Project Open Source? Migrating from Organic to Synthetic Communities,” paper presented at the Academy of Management Annual Meeting, Honolulu (August).

Eric S. Raymond, 1998, “Homesteading the Noosphere,” First Monday, volume 3, number 10 (October), at http://www.firstmonday.org/issues/issue3_10/raymond/, accessed 20 June 2007.

Everett M. Rogers, 1995. Diffusion of Innovations. Fourth edition. New York: Free Press.

Lawrence E. Rosen, 2005. Open Source Licensing: Software Freedom and Intellectual Property Law. Upper Saddle River, N.J.: Prentice Hall PTR.

Tim Simcoe, 2006. “Open Standards and Intellectual Property Rights,” In: Henry Chesbrough, Wim Vanhaverbeke, and Joel West (editors). Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press, pp. 161–183.

Wim Vanhaverbeke and Myriam Cloodt, 2006. “Open Innovation in Value Networks,” In: Henry Chesbrough, Wim Vanhaverbeke, and Joel West (editors). Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press, pp. 258–281.

Joel West, 2007. “Value Capture and Value Networks in Open Source Vendor Strategies,” Proceedings of the 40th Annual Hawai’i International Conference on System Sciences, Waikoloa, Hawai’i (January), at http://doi.ieeecomputersociety.org/10.1109/HICSS.2007.600, accessed 20 June 2007.

Joel West, 2006a. “Does Appropriability Enable or Retard Open Innovation?” In: Henry Chesbrough, Wim Vanhaverbeke, and Joel West (editors). Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press, pp. 109–133.

Joel West, 2006b. “The Economic Realities of Open Standards: Black, White and Many Shades of Gray,” In: Shane Greenstein and Victor Stango (editors). Standards and Public Policy. Cambridge: Cambridge University Press, pp. 87–122.

Joel West, 2003. “How Open is Open Enough? Melding Proprietary and Open Source Platform Strategies,” Research Policy, volume 32, number 7 (July), pp. 1259–1285; version at http://opensource.mit.edu/papers/rp-west.pdf, accessed 20 June 2007.

Joel West and Scott Gallagher, 2006. “Patterns of Open Innovation in Open Source Software,” In: Henry Chesbrough, Wim Vanhaverbeke, and Joel West (editors). Open Innovation: Researching a New Paradigm. Oxford: Oxford University Press, pp. 82–106.

Rolf T. Wigand, Charles W. Steinfield, and M. Lynne Markus, 2005. “IT Standards Choices and Industry Structure Outcomes: The Case of the United States Home Mortgage Industry,,” Journal of Management Information Systems, volume 22, number 2 (Fall), pp. 165–191.

 

This article was originally published by Dr. Joel West and is reprinted here with permission.

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