Collaborate to Innovate: Innovative Capacity for Effective Open Innovation

Collaborate to Innovate: Innovative Capacity Index for Effective Open Innovation A doctoral dissertation by

Dr Dorothea G. Greenwood

Submitted to the Graduate Faculty of University of Maryland University College in Partial Fulfillment of The Requirements for the Degree of Doctor of Management

ISBN: 978-1-909507-51-7 CopyrightŠ Dorothea G. Greenwood Licence to publish granted to Academic Conferences and Publishing International Limited, 2013 For more information see www.academic-conferences.org

Collaborate to Innovate: Innovative Capacity Index for Effective Open Innovation

Dorothea G. Greenwood

A Thesis Submitted to the Graduate Faculty of University of Maryland University College in Partial Fulfillment of The Requirements for the Degree of Doctor of Management

6 December 2010

Dissertation Chairs: James P. Gelatt, Ph.D. Kathleen F. Edwards, Ph.D.

Table of Contents List of Figures …………………………………………………………………………………….3 List of Tables .……………………………………………………………………………………..3 Abstract ........................................................................................................................................... 4 Chapter 1: Introduction .................................................................................................................. 5 Statement of Problem .................................................................................................................. 5 Thesis .......................................................................................................................................... 5 Research Questions ..................................................................................................................... 6 Summary ..................................................................................................................................... 9 Organization of the Dissertation .............................................................................................. 10 Chapter 2: Literature Review ....................................................................................................... 12 Open Innovation.................................................................................................................... 12 Absorptive Capacity .............................................................................................................. 23 Network Relationships .......................................................................................................... 27 Boundary Spanning and Knowledge Brokering ................................................................... 31 Social Capital........................................................................................................................ 36 Summary of Findings ............................................................................................................ 38 Chapter 3: Analysis and Discussion ............................................................................................. 40 Social Capital........................................................................................................................ 41 Network Ties ......................................................................................................................... 42 Boundary Spanning ............................................................................................................... 43 Adaptive Absorptive Capacity............................................................................................... 45 Innovative Capacity Index (ICI) ........................................................................................... 46 Innovative Capacity Index Measurement.............................................................................. 57 Open Innovation Conceptual Framework Propositions ........................................................... 59 Proposition 1......................................................................................................................... 61 Proposition 2a, 2b, 2c ........................................................................................................... 61 Proposition 3......................................................................................................................... 62 Proposition 4......................................................................................................................... 62 Proposition 5......................................................................................................................... 62 Proposition 6......................................................................................................................... 63 Summary ................................................................................................................................... 63 Chapter 4: Conclusions ................................................................................................................. 65 References ..................................................................................................................................... 69 Page | 2

List of Figures Figure 1. Open Innovation Conceptual Framework ……………………………………….....41 Figure 2. Open Innovation Causal Effects …………………………………..……………..…41 Figure 3. Innovative Capacity Index ………………………………………………………….47 Figure 4. Initial MIMIC Model for Innovative Capacity ……….............………………..….. 47 Figure 5. Innovative Capacity Index Spider Chart …………………….……………...…….. 58 Figure 6. Open Innovation Framework Mapped to Propositions ………..……………..……. 60 List of Tables Table 1. Innovation process phases and characteristics (Hsin-Min, et al., 2008) ………….….. 16 Table 2. Innovation business models (Viskari et al. (2007), adapted from Chesbrough (2006)) …………………………………………………………………………………………………...18 Table 3. Forms of Collaboration ……………………………………………….………………21 Table 4. External knowledge sourcing (adapted from Von de Vrande, 2006) ……………...... 22 Table 5. Innovative Capacity Indicators ………………………………………….…………....48 Table 6. Innovative Capacities, Levels and Metrics …………………………….………….….50 Table 7. Open Innovation Propositions ………………………………………………………. 60

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Abstract In today’s economy, enlightened firms collaborate to innovate openly across the entire innovation chain. To sustain competitive advantage in today’s fast moving open innovation ecosystem, the executive leadership of a firm should create and sustain a new business model for open innovation. The four building blocks of an open innovation business model are capacities that allow it to accumulate social capital, organically build network ties, span boundaries of firms to access knowledge, and maintain absorptive capacity crucial for organizational learning and knowledge transfer. This paper develops the Innovative Capacity Index (ICI), based on these four building blocks, to provide executive leadership with a dashboard mechanism to track and cultivate the innovative behaviors and actions of the firm for competitive advantage. The ICI measures provide visibility into a portrayal of “who is talking to whom about what” and give leaders the insights needed to reinforce and redirect priorities, resources, recognition and rewards to influence desired activities and behaviors. Executive leadership can then adapt and refine the corporate strategy, investments, practices and culture to achieve and sustain enduring competitive advantage.

Keywords: open innovation, social capital, network ties, knowledge spanning, absorptive capacity, knowledge management, innovation management.

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Chapter 1: Introduction Statement of Problem The globalization and mobility of workers in the knowledge-based economy has increased the speed of innovation and the cost of research and development (R&D). Open innovation is an emerging business model for leveraging knowledge across corporations to speed innovation at reduced costs while sustaining competitive advantage. Open innovation business models and practices challenge conventional strategies for competitive advantage. While research in this area is increasing in the last decade, there is little research addressing the innovative capacities needed for a corporation’s effective management of open innovation for competitive advantage in the knowledge-based economy.

Thesis To innovate after the shift from manufacturing to knowledge-based economy requires speed and flexibility in leveraging new information in the innovation network (Hsin-Min, SeHwa, Chao-Tung, & Feng-Shang, 2008). Corporations need new business models for innovation in the new knowledge-based ecosystem and new capacities to identify and access external knowledge and take action internally for business opportunities to sustain competitive advantage (Chesbrough, 2007, 2008; Chesbrough & Schwartz, 2007). Four interrelated factors influence a firm’s capacity to master and leverage external knowledge in pursuit of selected market opportunity in the open innovation ecosystem and the management of resulting tensions. These four factors are (1) social capital, (2) network ties, (3) ability to span innovation network boundaries and (4) the agility of its internal absorptive capacity. A firm’s innovative capacity is a consequence of the corporate behaviors and business practices associated with a firm’s management effectiveness regarding these factors. These factors provide the formative indicators

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of the latent variables of “Innovative Capacity” of a firm (Sanchez-Perez & Iniesta-Bonillo, 2004). This research proposes the Innovative Capacity Index (ICI) to provide the measures and metrics for latent variables to manage the effectiveness of a corporation’s open innovation.

Research Questions This study researches the conditions and factors of open innovation for sustained competitive advantage. It develops a conceptual framework for the open innovation factors with propositions for management effectiveness. In response to this framework, it researches the measures and metrics to form an index for a corporation to use to monitor, assess and cultivate its open innovation effectiveness.

Innovation is the driver of economic growth in today’s business ecosystem (Bullinger, Auernhammer, & Gomeringer, 2004). Multinational firms are increasingly globalizing their innovation activities in response to the ever shifting global landscape (Li & Kozhikode, 2009).

The pace and costs of economic, social and technological change have increased dramatically through innovation and globalization (Gopalakrishnan, 2000). The cost of R&D to discover new products has risen tremendously. New products are developed now in 12-18 months from 24-36 months during 1989-1998 with diminishing economies of scale in US industrial research and development (R&D) (Smith & Reinertsen, 1992). Companies under 1000 employees spent five times more in R&D in 2003 compared to expenditures in 1981 and companies with over 25,000 employees are spending almost half as much (Chesbrough, 2008). R&D for an new drug was estimated to cost less than $50 million twenty-five years ago compared to over $800 million today (Chesbrough, 2008). Similarly, R&D for a new consumer product was less than $10 million twenty-five years ago compared to $50 million today (Chesbrough, 2008).

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In this knowledge-based economy, firms are increasingly exploring new business models for innovation and working collaboratively with other firms to share intellectual property, expertise and resources to lower costs and increase the speed of innovation for sustained competitive advantage (Chesbrough & Schwartz, 2007). Open innovation and its potential to accelerate corporate innovation for competitive advantage at lower cost has increased in the last decade through the leverage of the knowledge and resources of other firms for internal R&D (Enkel, Gassmann, & Chesbrough, 2009). Academic research and business practices, however, offer little to guide corporations in developing the capacities needed for the practice of open innovation. As a result, research is needed to understand the conditions and factors for business practices that create and sustain competitive advantage with open innovation.

Innovation has traditionally been accomplished in the Industrial Age through vertical integration within multinational corporations with internal research and development leading to new products that are marketed and sold by the firm (Chesbrough, Vanhaverbeke & West, 2006).

Knowledge needed to innovate today either has to be developed internally or acquired from external sources (Hall & Andriani, 2002, p. 32). Open innovation provides an opportunity to innovate collaboratively exchanging knowledge with other firms across the business ecosystem offering the advantage of sharing knowledge, expertise and resources to lower costs and increase speed of innovation. Pursing external sources of knowledge increases the spillover pool of knowledge available to a firm (Knott, Posen, & Wu, 2009).

Innovative companies are now leveraging knowledge and ideas of external firms within in-house R&D to accelerate the speed and number of innovative products they bring to market (Chesbrough, 2003; Munsch, 2009). These changes and the mobility of global knowledge workers are driving firms to rethink fundamental innovation business models for competitive

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advantage (Teece, 2004; Chesbrough, 2003). Innovation, in the new knowledge economy, improves not just the technologies but the frameworks and business models in which enterprises discover knowledge and pursue opportunity across the innovation network to produce and deliver new goods and services (Chesbrough & Schwartz, 2007; Zuboff, 2010). Companies today are increasingly considering open innovation as the emerging paradigm where firms use external ideas as an integral part of internal business processes to discover, develop and market products and services that create value (Hansen & Birkinshaw, 2008; Chesbrough, 2003).

Porter (1985) states that a firm sustains its competitive advantage by constantly upgrading its facilities and capabilities for innovation. Porter’s theory addresses the cost and differentiation advantage of a corporation for competitive advantage but does not address the open interplay among corporations to trade and leverage knowledge assets. Porter (1985) did not account for the value of external sources of knowledge that a company gains from innovation communities and networks, open publications and social networking websites (Chesbrough & Appleyard, 2007). With open innovation, the concept of competitive advantage shifts from ownership to value capture and creation through leveraged knowledge in external corporations (Dyer & Singh, 1998). Dyer and Singh (1998) found that the relationship between firms is a key variable in competitive advantage. Von Hippel (1988) found that it was the knowledge transfer mechanisms in the production network that permit firms to “out-innovate� others.

Open innovation has been shown to increase the tensions in the balance of corporate priorities, resources and funding between exploratory efforts and the use of unfamiliar external knowledge in search of breakthrough opportunities over the conventional corporate profitoriented exploitation of incremental products and markets (Andriopoulos & Lewis, 2009; Raisch, Birkinshaw, Probst, & Tushman, 2009). Open innovation requires new corporate capacities to

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mediate tensions like these with new corporate business practices to create sustainable market opportunity (Cohen & Levinthal, 1990).

The four factors that influence the practice of open innovation in a corporation are (1) social capital, (2) network ties, (3) boundary spanning and (4) agile absorptive capacity. A framework for these factors with propositions for effective open innovation is needed. This framework and propositions provide the intellectual foundation for an index with latent variables to measure a corporation’s business practices and provide a management tool for a corporation’s effective open innovation.

This research provides a framework and posits six propositions. First, higher social capital leads to more network ties and boundary spanning. Second, appropriate network ties lead to more boundary spanning with more reciprocal exchange. Third, more network ties and boundary spanning result in activation triggers and higher social capital. Fourth, more activation triggers lead to higher agile absorptive capacity. Fifth, agile absorptive capacity produces more selected market opportunities. Sixth, higher Innovative Capacity Index correlates with more differentiating market opportunities advocated by executive leaders.

Summary Management effectiveness for open innovation comprises four factors: (1) social capital, (2) network ties, (3) boundary spanning and (4) agile absorptive capacity. Social capital reflects the willingness and motivation of individuals in the firm to collaboratively share information (Reagans & McEvily, 2003). Social capital can be an asset of a firm used to pursue and induce relevant network ties with other corporations for the relationships needed to span the boundaries of external knowledge inter-firm and across the innovative network to access other firms’ intellectual property (Ahuja, 2000a). A firm’s social capital leads to the formation and Page | 9

maintenance of the network ties that can provide the ability to span the boundaries of other firms’ intellectual property to access external knowledge. The availability of external information triggers a firm’s internal agile absorptive capacity with collaborative internal processes for developing novel combinations of new external knowledge with internal knowledge leading to ideas for new products and market opportunities (Hargadon, 2005), Absorptive capacity becomes a set of knowledge-based capabilities embedded within a firm’s routines and strategic processes to respond to the dynamic nature of innovation and the industry network (Zahra & George, 2002). These four capacities drive a firm’s new market opportunities and competitive advantage.

This dissertation reviews the literature related to open innovation, identifies the four key factors for innovative capacity and develops an integrated framework with propositions for a corporation’s open innovation management effectiveness. This dissertation proposes an Innovative Capacity Index with measures and metrics for a corporation to assess and monitor the latent variables of social capital, network ties, knowledge boundary spanning and agile absorptive capacity. Further research is needed to validate the effectiveness of this index in measuring and predicting effective open innovation.

Organization of the Dissertation Chapter 1 provides an introduction to the problems associated with open innovation, the research questions and behaviors and business practices of a corporation for management effectiveness of open innovation. Chapter 2 provides a literature review of research related to open innovation for competitive advantage. Chapter 3 provides a conceptual framework for open innovation, propositions for management effectiveness and proposes the Innovative Capacity Index for use by corporation’s to measure the effectiveness of a its open innovation.

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Chapter 4 summarizes key findings and offers implications of future trends and management practices with areas for future research.

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Chapter 2: Literature Review There are five areas of research literature related to open innovation. The first addresses what open innovation is, the business shifts as a result of the emerging business models and strategies of open innovation, frameworks and their implications. The second addresses absorptive capacity as the business processes used to identify valuable external knowledge, bring this knowledge into a corporation, and integrate the new knowledge into a firm’s internal research and current internal knowledge to produce new products or services to bring to market.

The third is network relationships with others in the innovation network. The fourth is spanning boundaries of corporations to access the knowledge in the innovation network. The fifth is the social capital described as the culture of a firm that becomes a firm’s asset based on the firm’s reputation for willingness and motivation to collaborate externally and share intellectual property.

Open Innovation Henry Chesbrough (2003) coined the term “open innovation” in his seminal research observing that companies were increasingly generating ideas and bringing them to market by harnessing the ideas and R&D from other firms at lower cost and in shorter times. He found the drivers for open innovation to be the increased costs of R&D, shorter product lifecycles and smaller product revenue. He provides a theoretical foundation for the principles of closed and open innovation with a key difference in the recognition that being first to commercialize an innovation in closed innovation does not mean you will win. He asserts that a firm with the open innovation business model gets to market first. The open innovation business model includes leveraging the best expertise in the innovation network with internal R&D contributing only some portion of the value with external R&D. The best market opportunities come from the

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combination of the best internal and external ideas and intellectual property. In the open innovation model, the boundaries of a firm are porous and permeable with cooperative research and development leading to business opportunities in new markets with more effective business value than building only on current markets. Gianiodis, Ellis, and Secchi (2010) assert that interest in open innovation is increasing, but a conceptual framework is needed. They provide a typology with four strategies consisting of innovation seekers, innovation providers, intermediaries, and open innovators.

Chesbrough (2003) and Gordon (2001) investigate the shifts occurring in firms like Proctor & Gamble achieving business results with an open business model and sharing knowledge and market opportunity cooperatively with customers, suppliers and business partners. Xerox Parc, in contrast, consistently invented next generation market-changing technology from the computer mouse to graphical user interfaces and browsers but pursued a closed research model, separate from the rest of the business of Xerox, and failed to commercialize any products (Chesbrough & Rosenbloom, 2002).

Corporate open innovation strategies range from “outside-in,” where firms find capabilities externally to bring into a firm for new product generation, to “inside-out,” where firms license or share their knowledge for the development of complementary products at no cost to them (Chesbrough & Garman, 2009). This recent research of Chesbrough and Garman have found significant cases of inside-out in times of economic downturn, including E.J. Lilly who launched Innocentive.com as an independent corporation with an online innovation marketplace (“Innocentive”, 2009). Innocentive.com, started in 2001 by the venture capital arm of E. J. Lilly for internal needs, but was spun off and now operates independently as an online innovation marketplace for “Seeker” organizations to supplement their internal R&D and product

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development by anonymously funding self-motivated “Solvers” who work independently to solve tough challenges posted. Innocentive.com creates challenges identified and funded by corporations or not-for-profits, but anonymous to the public, and mediates the selection of the winner providing the funding corporations or not-for-profits with a solution to drive breakthrough products. The winning solver transfers intellectual property for the winning solution to the Seeker. Innocentive.com claims to reach over 160,000 solvers across more than 175 countries across nine disciplines and with seven thematic pavilions. In 2008, 17 Solvers achieved Top Solver status winning more than two challenges and/or awarded more than $50,000 for their innovative solution (“Winning solvers”, 2009). Chesbrough and Garman (2009) contend that in lean times corporations should especially continue the collaboration across the innovation network and innovation “inside-out” where only some projects are kept inside the corporation and some projects are granted access to investments and development by external firms. A corporation benefits overall through knowledge spillovers in the new technology areas developed by others at no cost and licensing arrangements are possible for inventions cooperatively shared.

Knowledge is at the core of innovation as a capital asset across the innovation network (Hargadon & Fanelli, 2002). Open innovation shifts the business emphasis from ownership to value creation and value capture (Chesbrough & Appleyard, 2007). Hansen and Birchinshaw (2008) assert there is an innovation value chain anchored in the sharing of information and knowledge with partners outside the company. Based on interviews with 130 executives across 30 multinationals in North America and Europe and 4,000 non-executives across 15 multinationals over ten years, Hansen and Birchinshaw (2008) found three innovation stages in the innovation value chain with idea generation, idea conversion to products and idea diffusion

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to the marketplace. They assert that an end-to-end process is needed for innovation to identify and address the links in the chain and the assessment of both the weak and strong links in the process. This research provides a framework for the end-to-end process and a survey to assess a corporation’s innovation value chain from idea generation through product development to market penetration. This research concludes that firms must continually assess and strengthen the links in the chain to achieve an effective integrated innovation chain.

The first stage in Hansen and Birchinshaw’s (2008) model for open innovation is idea generation. This is a highly creative exploration process. Many companies have internal processes for generating new ideas with the freedom to explore and experiment based on proposed concepts or instincts (Leonard & Swap, 1999) consistent with the corporate culture and strategies. Companies such as IBM and Proctor and Gamble are involving business and academia in what they refer to as the “politics” of new opportunities from idea generation that involve business and society (Cooper, 2005; Palmisano, 2006). It is from the idea generation phase that inventions are created for new business products or processes. The second stage converts discovered ideas to internal information to be used for evolution of corporate products and services. The third stage is the diffusion of the idea across the supply chain from in-house R&D, manufacturing, suppliers and consumers.

Hsin-Min, Se-Hwa, Chao-Tung, and Feng-Shang (2008) assert that speed and flexibility in rapid innovation is essential after the shift from manufacturing to a knowledge-based society.

Hsin-Min, et al. (2008), studied the period from 1989-1998 (Smith & Reinertsen, 1992) that investigated new products in 12-18 development month cycles compared to 24-36 months previously. They assert three periods of innovation and the relationship of the social network and relationship to the innovation process, as shown in Table 1. These phases map well with Hansen

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Table 1. Innovation process phases and characteristics (Hsin-Min, et al., 2008)

and Birkinshaw’s (2008) innovation value chain and offer factors to being considered. In the first phase of the fluid period, ideas are generated. In this phase, structural holes provide the opportunity for competitive advantage based on first mover access to information not connected to the innovation network. Strategic alliances with strong network ties are critical to provide access to the individual knowledge assets that are not connected. They found that open accessibility for exploration of intellectual property (IP) can create win-wins for the owner of the IP who can license it and the firm that leverages it in new products and services. In the second phase, there is convergence of the new information on a product or service within a company and with the small-world of trusted firms. Partner firms in the alliance form stronger bonds during this period to exploit the necessary synchronization of knowledge transfer between firms for integration and creation of new products and services, often with prototypes, trials and market tests of intended market advantage. In the third phase, there is network closure to assure the safe and certain transfer of knowledge with price and quality market advantage with partner firms and alliances. This phase is concluded with the diffusion of the new innovation to the market Page | 16

innovation space for return on investment. The tensions between exploration for new products and services and exploitation of current market space must be worked by executives and managers in a firm across these three phases to achieve the ability to do both appropriately for competitive advantage (Andriopoulos & Lewis, 2009). Through these three phases, managers must assess and take action on lack of performance in idea generation, conversion to product and diffusion to market (Hansen & Birkinshaw, 2008).

Research shows that open innovation requires defined business objectives and an open business model of networked firms with integral shared processes for experimentation and assessment of results towards strategic objectives (Badaway & Chesbrough, 2004; Chesbrough, 2007). Chesbrough & Teece (2002) provide a framework for determining when inter-firm arrangements are advisable over internal development. Partnering with other firms typically includes joint ventures, alliances and outsourcing and, in the last twenty years, virtual teams (Chesbrough & Teece, 2002). Firms such as Proctor and Gamble (P&G), IBM and Air Products have demonstrated the power of strategic change in recent years from very internally focused closed business models to models substantially more open, to position them for lower R&D costs and increased product revenues (Chesbrough, 2007).

Viskari, Salmi, and Torkkeli (2007) adapted the six types of innovation business models asserted by Chesbrough (2006) based on the study of eight firms, as shown in Table 2. The study provided empirical evidence to support Chesbrough’s assertion that of the six types identified only Types 4, 5 and 6 should be considered open innovation business models. These firms use intellectual property to create business value to enable business opportunities, to receive licensing fees or to strategically position for innovation network opportunities on patents, research and other intangible assets. The study concluded that CISCO, IBM, Intel, and P&G

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pursue exploratory research of other firms to pull innovation into the corporation. CISCO is identified as a Type 5 using IP as a financial asset with strategic alliances and acquisitions of firms with short and long-term value to CISCO’s open business model. IBM, Intel and P&G are identified as Type 6 using IP as a strategic asset both insourcing and outsourcing research across the innovation networks. DuPont, IBM, Phillips and Sun pursue open business models to push innovation out. DuPont, IBM and Philips use licensing. IBM and Sun use open source. Intel, Lucent and Philips use collaboration, spin-offs and venture capital for their open innovation. All of these corporations use intellectual property proactively as an asset for open innovation.

Table 2. Innovation business models (Viskari, Salmi, & Torkkeli, 2007)

Proctor & Gamble, IBM and CISCO are examples of corporations that have demonstrated strategic corporate success and competitive advantage in moving to an open innovation business model. Proctor and Gamble experienced plunging equity values in the late 1990s and moved to an open innovation business model that they named “Connect and Develop� in 2004 and reported a 17% increase in volume, 19% increase in sales, 25% increase in earnings, and 24% return in shareholder return (Viskari, Salmi, & Torkkeli, 2007). IBM moved from a science to solutions developed entirely inside IBM to an open business model that integrated Page | 18

IBM with its original equipment manufacturer (OEM) market integrators from all segments of the value chain. IBM shares the high cost of R&D with industry alliances and now breaks even on the return-on-investment of advanced, high risk R&D and in some years makes money where it had been losing tens of millions of dollars every year. IBM switched from its proprietary operating system to the open source LINUX and now spends just $100M a year, a fraction of previous costs. IBM is a dominant member of the open source community that contributes an additional $800M a year to operating system research (Viskari, Salmi, & Torkkeli, 2007). IBM has the world’s largest patent portfolio with $2B annual revenues from outsource licensing fees.

In addition, IBM has donated over 500 patents recently to the open source community. IBM takes pride in increasing the “intellectual commons” of the open source community for further development of open source code while encouraging other vendors to do the same and realizing new levels of industry architectural innovation (Henderson & Clark, 1990). CISCO’s innovation strategy is a combination of internal development, strategic alliances, acquisitions and partnerships that is unique in the high tech industry. CISCO has acquired 108 innovative firms since 1993 and each with both a clear short and long-term win-win. All manufacturing at CISCO is outsourced. In 2007 and 2010, CISCO awarded $250,000 to the winner of a crowdsourcing competition for the next billion dollar business idea for CISCO (Carpenter, 2010).

CISCO owns the intellectual property for the idea to develop and take to market.

Cooperative competition, called co-petition among firms (Gnyawali & Park, 2009), is inherent open innovation as firms work to realize the potential of corporate value in a dynamic and competitive market (Munsch, 2009). Strategies, sense of urgency and motivation to share knowledge varies among firms as they assess risks to their pace of innovation, resource commitments, intellectual property and market share. Open innovation can threaten a firm’s

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intellectual property and could be perceived as compromising a firm’s ability to be first to market (Teece, 1986). The perceived risks in participating in open innovation could raise problems that might limit a firm’s desire to share information and threaten innovation due to the competition (Hansen & Birkinshaw, 2008, p.7). Viskari, et al. (2007) found the contrary in empirical analysis of eight multi-national firms operating with Type 4, 5 and 6 open innovation business models, as shown in Table 2, who are succeeding with intellectual property as a proactive innovation asset.

Viskari, et al. (2007) analyze the open innovation paradigm cases of eight multi-national corporations in the use of the open innovation paradigm from 1996-2005 in an empirical study of patents in the US companies and innovators in Taiwan. The study analyzes the open innovation strategies of the companies in the forms of collaboration, types of business models and the use of open innovation. Table 2 shows six types of innovation with eight firms grouped by analyses of their innovation processes and use of intellectual property (Viskari, Salmi, & Torkkeli, 2007).

The companies in the case study, CISCO Systems, DuPont, IBM, Intel, Lucent, Proctor and Gamble, Philips and Sun Microsystems, are asserted to be succeeding with open innovation and using intellectual property as an asset. The study acknowledges the importance of a corporation’s adaptive capacity literature to broker access to external knowledge and to recognize the value of external information, assimilate it and apply it to commercial ends as indicated by Cohen and Levinthal (1990). The study finds the forms of collaboration across the eight companies include subcontracting, licensing, consortia, strategic alliance, joint venture, and network as shown in Table 3 (Tidd, 2001; Viskari, Salmi, & Torkkeli, 2007). The study found that only collaboration of joint ventures and across the innovation network has long-term implications with dynamic learning potential with the disadvantages of static inefficiencies in

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maintaining the network relationships. Consortia and strategic alliances are forms of collateral risk knowledge leakage; however, the study also found that the business model of network innovators use diversity of knowledge as a proactive asset, as shown in Table 2. In addition, Viskari, et al. (2007) found that acquisition, equity alliance, non-equity alliance and corporate venture capital methods affect the governance of external knowledge souring, as shown in Table 4 (van de Vrande, Lemmens, & Vanhaverbeke, 2006; Viskari,Salmi & Torkkeli, 2007). As shown, commitment and prior cooperation align with acquisitions in the need for high levels of trust and stability. The others offer more flexible knowledge sourcing options.

Table 3. Forms of Collaboration (Tidd, 2001) Form of Collaboration Time duration

Advantages

Disadvantages

Subcontract / Supplier relation Licensing

Short term

Cost and risk reduction

Fixed term

Consortia

Medium term

Strategic alliance

Flexible

Technology and knowledge acquisition Experience, standards, shared funding Low commitment

Search costs, product performance and quality Contract cost and constraints

Joint venture

Long term

Network

Long term

Complementary know-how, dedicated management Dynamic learning potential, lower cost, diversity of knowledge, economies of scale, indirect ties.

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Knowledge leaks, subsequent differentiation Potential lock-in, knowledge leakage Strategic drift, cultural mismatch Static inefficiencies

Table 4. External knowledge sourcing (adapted from Von de Vrande, et al., 2006)

Zahra and George (2002) found patterns of secrecy among firms fearing their ideas would be imitated. As a result, they did not pursue patents or other forms of publication about ideas to protect intellectual property. Viskari, et al.’s (2007) empirical analysis found eight multi-national corporations successfully competing with open innovation and knowledge sharing. Similarly, firms like Google and Apple, on the other hand, create open networks of value creation in new market spaces created by their new enabling products such as search engines and the iPod ("Google CEO", 2006; Hammonds, 2007; Kim & Mauborgne, 2005).

Reagans and McEvily (2003) advise leadership to develop social cohesion in a corporation with the willingness and motivation for cooperative knowledge sharing to achieve the social capital to affect knowledge transfers across the innovation ecosystem This is supported by Viskari, et al.’s (2007) findings of Type 4, 5 and 6 companies with successful open innovation and use of intellectual property as a strategic asset as shown in Table 1.

Value creation is a function of a firm’s competency to develop a distinctive internal business model to innovatively combine internal and external knowledge for competitive advantage (Teece, 2004). Gopalakrishnan (2000) found in the study of the commercial banking industry that the speed of innovation is a significant predictor of financial performance but not the amount of innovation underway. Zahra and George (2002) assert that speed of innovation

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requires a dynamic management model with activation triggers based on knowledge discovery to adapt investments, resources and priorities based on knowledge discovery and selection of market opportunities. Viskari, et al.’s (2007) study of eight worldwide firms that have successfully adopted the open innovation paradigm in their business models, confirms that those patents and intangible assets, especially knowledge and other intellectual property, are important indicators of future success.

Absorptive Capacity Cohen and Levinthal (1990) provide a seminal model for the theory of absorptive capacity where value is generated from innovation through the exploitation of external knowledge.

Cohen and Levinthal (1990) provide four dimensions in the model to (a) recognize the value of new external information, (b) assimilate it, (c) combine the new knowledge into internal business processes with existing knowledge, and (d) develop innovative products and services for selected market opportunities. They call this “absorptive capacity” and link a firm’s success to a firm’s level of prior related knowledge and diversity of knowledge used by a firm for innovation. They highlight the importance of the diffusion of innovations from cooperative R&D ventures into the internal processes of the firm for business gain.

Zahra and George (2002) extend Cohen and Levinthal (1990)’s model of absorptive capacity and assert that it is inherently a dynamic model affecting the sustainability of competitive advantage in dynamic markets. They define two types of absorptive capacity. First is “potential” absorptive capacity with exogenous and endogenous variables that affect absorptive capacity and the value generated from exploitation of external knowledge. Second is “realized” absorptive capacity that is the result of external and internal knowledge exchange.

Zahra and George (2002, p. 190-191) contend that it is the potential absorptive capacity that

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provides leverage points for management direction regarding the dynamic external knowledge to leverage for competitive advantage. They assert that potential absorptive capacity sharpens a firm’s ability to recognize valuable external knowledge, with activation triggers, access it and move internally to convert it to new products and services. Taleb, Goldstein, and Spitznagel (2009) assert it is the outliers that indicate rare and unpredictable events that have enormous impact that he calls Black Swans. He contends that most companies’ observe regular occurrences and form psychological biases to black swans that make people and firms individually and collectively blind to uncertainty and not accept the reality of black swans. 9-11, oil spills, market crashes, and iPods are black swans. Creative response is unpredictable and affects the future (Schumpeter, 1947). Activation triggers for outliers identified in external knowledge may help firms respond creatively and anticipate black swan (Zahra & George, 2002).

The ability to judge when it is better to take extant knowledge from the other firms versus using internal resources is a critical business decision in line with Penrose (1959) and Teece’s (1986, 2004) theories of the growth of a firm. Zahra and George (2002) conclude that absorptive capacity is a set of knowledge-based capabilities embedded within a firm’s routines and strategic processes to activate triggers to respond to the dynamic nature of innovation and the industry network. They contend that, in addition to the past knowledge and experiences identified by Cohen and Levinthal (1990), knowledge complementarities and diversity of knowledge sources are critical to influence the potential absorptive capacity of a firm. They contend that there are activation triggers that will change a firm’s locus of search, making the firm’s development path fluid and multi-directional. Recognition of these triggers include discovery of new knowledge that when combined innovatively with extant firm knowledge lead to selected market

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opportunity. They contend that a firm’s success depends on the integration of potential absorptive capacity embedded in the firm’s business processes.

Hargadon (2005) similarly asserts that the ability to innovatively recombine extant knowledge in new ways is a critical skill. After ten years of studying innovation, he found that strong social networks both within and across groups sparked many of the technological revolutions and produced a steady stream of opportunities for existing business. He found that there are two types of knowledge in an organization – empirical knowledge and latent knowledge (Hargadon & Fanelli, 2002). Empirical knowledge provides and drives business action. He considers latent knowledge as the often overlooked knowledge of possibility for discovering and linking with empirical internal and external knowledge in new ways for competitive advantage.

Lichenthaler (2008) conducted a multi-informant survey of 175 industrial firms that showed the complementary effects of exploratory, transformative and exploitative learning on innovation performance within a firm. Lichenthaler (2008) shows the inter-firm discrepancy in profiting from external knowledge as a result of differences in absorptive capacity.

Lichenthaler’s (2009) subsequent studies show the importance of dynamic absorptive capacity in firms with high degrees of technological and market turbulence. Lichenthaler (2008) provides validating evidence of Zahra and George’s (2002) assertion for the need to dynamically manage external knowledge within a firm’s knowledge management capacity without necessarily internalizing the external knowledge. He names this the “relative” absorptive capacity of firms to complement absorptive capacity. He provides propositions for further research regarding the antecedents and consequences of relative capacity in a firm’s use of externally gained knowledge as a result of network relationships.

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A key aspect of absorptive capacity is adaptive learning and collaboration with other firms with wide diversity of knowledge diffusion across the inter-firm network and into participating firm business processes. Several researchers found evidence regarding challenges in the learning strategies across network alliances affecting innovation (Bartel-Radic, 2006; Garvin, Edmondson & Gino, 2008; Leonard & Straus, 1997; Leonard & Swap, 1999). BartelRadic (2006) provides a case study with both qualitative and quantitative data to investigate the development of intercultural competence that is relevant to inter-firm behavioral competence across the cultures of diverse firms. Bartel-Radic (2006) finds that long-term interaction, care and conflict characterize global teams in intercultural learning. Garvin, Edmondson and Gina (2008) provide a survey for assessment of the learning style of an organization. Learning with a free-forming group of diverse people is inherently adaptive based on the actions and interactions of the collaboration but fraught with tension (Garvin, Edmondson, & Gino, March 2008; Leonard & Swap, 1999). Their research asserts that inter-group innovation depends on their ability to resolve the collision of different ideas, perceptions and ways of processing and judging information. They call this “creative abrasion.� In their research, they have found a strong correlation between the ability to cooperatively promote the clash of ideas in diverse and dynamic inter-firm collaboration with successful innovation (Leonard & Swap, 1999). This process synergizes divergent and convergent thinking essential to absorptive capacity and learning where new ideas are continually recombined with extant knowledge in new ways across corporate cultures. With it, firms can innovate. Without it, they will fall behind (Leonard & Straus, 1997).

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Network Relationships Ahuja’s (2000a) longitudinal study of the chemical industry found evidence of the benefits and challenges of innovation relationships directly correlated to the network ties of the actors. He provides a theoretical framework that relates three types of a firm’s network affecting the innovation output of the firm. First, firms may form direct network relationships with other firms with varying agreements to interact. Second, firms may choose to leverage other firms indirectly through the direct relationships of other firms. Third, firms in a business ecosystem without direct or indirect connection to a firm are referred to as structural holes. He conducted a longitudinal study of the network relationships among firms in the international chemical industry to observe patterns of innovation success based on the network relationship among the firms. Ahuja’s hypothesis is that the relationships of the network are tied to innovation outcome.

Ahuja concludes that direct and indirect ties have a positive impact on innovation and that increasing structural holes has a negative impact on innovation. He finds direct ties are strong ties that provide contractual linkages, resource-sharing (physical, skills, and knowledge) and information sharing benefits of knowledge spillovers and links to indirect ties. He finds direct ties positively and significantly related to greater innovation output in relationship to indirect ties and structural holes. He considers indirect ties as weak ties serving as a key mechanism for knowledge spillovers including industry successes and failures, but not enabling resource-sharing. Weak ties, he asserts, contribute positively and significantly to innovation output with little or no maintenance costs. He finds that indirect ties provide greater innovation output due to the wider range of diverse knowledge available related to the number and strength of direct ties. The magnitude of the benefit of indirect ties, however, may be low since knowledge spillover is dependent on the effectiveness of direct ties (Burt, 1977). A firm may

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learn of technical development, for instance, through indirect ties, but this spillover information reaches all other firms in the network, including competitors. Weak ties are more associated with exploratory discovery of knowledge and strong ties more associated with thick information exchanges, efficient and effective transfer of tacit knowledge and connotes trust among the firms (Ozman, 2006).

Hansen’s (1999) study of 120 new-product development projects in 41 divisions in a large electronics company found that weak inter-unit ties help a project team find useful knowledge in other units, but strong ties are needed for the transfer of complex information.

There are costs to a firm in maintaining network relationships. Strong ties are more expensive than weak ties (Hansen, 1999). Strong ties require continual administrative and technical coordination among firms at varying levels of coordination in the firms. Depending on the proximity of the firms, travel and technical collaboration infrastructure will be needed as well as management processes to monitor the health and performance of the ties.

Ahuja finds structural holes lead to less innovation output as it reflects absence of knowledge. Burt (2004) counters this finding asserting that if a firm actively brokers across structural holes in a network then structural holes between groups provide opportunity for the discovery of unconnected knowledge due to the lack of connection to other firms. This assertion is built on Burt’s market theory that structural holes are the gap between two individuals or firms with complementary information or resources (Burt, 1992). The entrepreneur who fills this gap achieves competitive advantage and opportunity for higher profits since he has unique access to complementary information and resources not discovered in the innovation network. Ozman (2006), like Burt (2004), asserts structural holes may reveal a sparse network with useful gaps in connections to knowledge with opportunity for first mover advantage. Structural holes are

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typically discovered by explicit exploratory search of knowledge brokers beyond local sources or those of direct ties (Rosenkopf & Nerkar, 2001). They reveal new unseen knowledge from either spillovers or serendipitous discovery. These holes typically reflect non-redundancies in sparse networks due to lack of linkages among firms in the network. Dense networks are likely to have redundancies. Filling holes with linkages to knowledge in holes avoids the inefficiencies of redundancies in the network (Ozman, 2006). Additionally, good ideas are disproportionately in the hands of brokers whose networks span structural holes connecting gaps in complementary information and resources (Burt, 1992, 2004). Since networks are inherently dynamic, structural holes may reflect the changing nature and evolution of firms in industrial segments. A firm who fills structural holes has an opportunity for discovery of new knowledge that can be leveraged for competitive advantage (Burt, 1992; Ozman, 2006).

Ahuja (2002a) concludes that network relationships provide an asset referred to as “social capital� that facilitates collaborative inter-firm innovation. The discovery of this knowledge provides the broker with social capital of value to his or her firm as well as those with direct ties to the firm (Burt, 2004). He concludes that the optimal structure of inter-firm networks depends on the objectives of the network members. These network ties provide firms with the ability to identify new and relevant knowledge available - a key factor for a firm’s absorptive capacity (Cohen & Levinthal, 1990; Zahra & George, 2002).

Liu (2010) provides a theoretical background for the network approach and identifies network structure and network content as the two key components. Liu concludes, based on empirical findings from analysis of US patent information, related Taiwan patents and interaction among inventors between 2003 and 2008, that (1) the broader the network connections of a firm, the greater the opportunity for the firms to interact, to share innovative

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ideas, and to develop mutual understanding and trust and that (2) central position in the innovation network, e.g., between firms with structural holes, provides opportunity for discovery of diverse information and knowledge from disconnected networks that is otherwise unavailable to the innovation network, confirming Burt’s (2004) assertion. Liu (2010) references Burt’s (2004) assertion that social network structure is central to the diffusion of information and innovation and provides rapid dissemination of opportunities for and threats to firms in the innovation network. This builds on Burt’s (1992) assertion that network structure replaces the dichotomy between perfect competition and monopoly and offers competitive advantage to certain players. Burt defines structural holes as the gap between two individuals with complementary information or resources, indicating that when they are connected by a third party as an entrepreneur the gap is filled creating competition advantages for the entrepreneur.

Burt’s (1992) theory of market asserts that competitive advantage is, therefore, a matter of access to structural holes. Burt claims that the more structural holes there are in a producer’s network, the higher the profits will be since the producer has few competitors with complementary information or resources and many suppliers and customers in the supply chain.

Alertness, responsiveness and flexibility are critical to profit from information obtained through ties in the innovation network (Vanhaverbeke, Gilsing, & Duysters, 2007; Zaheer & Zaheer, 1997) . Vanhaverbeke, Gilsing and Duystres (2007) provide a theory of explorationexploitation and its relationship to the optimal technology-based alliance network structures.

Their study of 116 companies in chemicals, automotive and pharmaceutical industries resulted in three conclusions: (a) the distinction between exploration and exploitation is less relevant within a firm than across a network, (b) that networks support both exploitation and exploration and are driven by the tasks underway, and (c) the distinction between exploration and exploitation has

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more potential in understanding the role of a firm’s network than a type of industry. Exploitation is oriented toward strengthening the existing knowledge and technology base of a firm and exploration is the search for new technological and business opportunities (Viskari, Salmi, & Torkkeli, 2007).

Boundary Spanning and Knowledge Brokering Firms have well-defined boundaries of corporate information, resources and business processes. Open innovation may span the boundaries of firms permitting access to internal intellectual property and creating relationships among firms with implied and explicit protocols for crossing a firm’s boundaries. Boundary spanning results in linkages across domains in the network of knowledge and resources. Fleming and Waguespack (2007) provide a longitudinal study of the Internet Engineering Task Force and find that technical contribution in communities is enabled by two correlated but distinct social positions: social brokerage and boundary spanning between technological areas. They found that boundary spanners were well rewarded with leadership promotions. Tushman (1977) asserts that defined boundary spanning roles are critical to the innovation process and fulfill special functions to link the internal corporate networks with external sources of information. Boundary spanning relationships and knowledge brokering have been found to be invaluable to inter-firm collaboration and open innovation communities (Fleming & Waguespack, 2007; Hazy, Tivan & Schwandt, 1977; Tushman, 2003).

Social knowledge brokering develops trust through direct personal interaction over time (Fleming, Mingo, & Chen, 2007; Fleming & Waguespack, 2007).

Boundary spanning provides awareness of and access to external knowledge. Hargadon (2002) provides a five step model for how successful firms today with innovation recombine past knowledge in new ways. His five steps are (1) access, (2) bridging, (3) learning, (4) linking and

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(5) building. These five steps rely on boundary spanning and knowledge brokering across the network structure to bridge multiple domains, learn about knowledge there and link the knowledge to new situations. He concludes that new networks must be iteratively built around the resulting innovations to sustain the new knowledge. Based on evidence from a field study of innovative practices of two firms, Hargadon and Fanelli (2002) found that empirical knowledge is routinely used for action. However, they found that there is often valuable latent knowledge that may be unnoticed when exploring possibilities. Spanning boundaries in search of this knowledge and linking it to the empirical knowledge across the network will spawn new ideas for the use of the information. In a ten-year study of innovation in firms, Hargadon (2005) found that successful firms develop strong social networks both within and outside their groups to nurture “genius” in the recombination of old ideas in new ways. He found that successfully managing this knowledge through boundary spanning routines will spark new growth opportunities as prospering firms see possibilities sooner and acquire new ways to link information across the diverse and dynamic knowledge sources. He concludes that innovative firms ask two questions: (1) what are existing technologies to leverage differently in new ways?

(2) what are the market opportunities?

These questions drive the absorptive capacity of a firm and an organization’s ambidexterity in both exploring new knowledge and exploiting current knowledge (Andriopoulos & Lewis, 2009; Raisch, S., Birkinshaw, J., Probst, G., & Tushman, 2009). In the study of five firms in the product design industry, Andriopoulos and Lewis (2009) identified a tension between these two factors - exploring new opportunities and exploiting existing products to enable incremental innovation. These tensions arise in the strategic allocation of resources to span boundaries, broker knowledge and determine the priority, intensity and focus to seek

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external knowledge. Andriopoulos and Lewis (2009) developed an integrative framework for a firm’s ambidexterity in balancing the tensions between the exploitation and exploration strategies. They found three paradoxes in balancing exploitation and exploration nested within strategic, customer and personal objectives. First, the strategic intent of low-risk exploitation investments for assured profit is a temperament at odds with the flexibility and uncertainty inherent in higher risk exploration in the hopes of breakthrough innovation. Second, the customer orientation of exploitation is tightly controlled to assure customer satisfaction within market timeframes while in exploration in consumer desires for new products are loosely coupled with uncertain timeframes. Finally, the personal driver for exploitation efforts is discipline and maintaining control while it is passion that drives exploration.

Raisch, Birkinshaw, Probst and Tusman (2009) present the theory for organizational ambidexterity as the ability of a firm to apply structural mechanisms to balance appropriately between the tensions of exploitation and exploration. Exploration-orientation aligns with the three phases of Hansen and Birkinshaw’s (2008) innovation value chain. The idea generation phase is rich in exploration of external knowledge to discover new novel ideas. Exploration then straddles the idea generation and the second idea conversion phase when exploring new ways to combine diverse external knowledge with existing internal knowledge for the creation of new products and services. Finally, in the third diffusion phase, exploration may trigger the diffusion of new ideas, which are consistent with a firm’s business strategy, for market development to asses customer use of and response to new products and services.

Exploitation strategies are needed to manage and control resource commitments, product and service delivery timelines and schedules for new products and services and response to customer needs. Activation triggers are needed to signal appropriate corporate action when

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boundary spanning activities find relevant new external knowledge that is different but complementary to internal corporate knowledge (Hargadon, 2002). These triggers can alert internal absorptive capacity processes to integrate the new knowledge with the internal knowledge in the hopes of creating variety and diversity of thought for the discovery of new product, services and market ideas (McGrath, 2001; Hansen & Birkinshaw, 2008). The pace and cost of innovation today demands new business models to interact openly across the innovation network (Chesbrough, 2007). To sustain competitive advantage in today’s fast moving innovation ecosystem, the executive leadership of a firm should create and sustain a new business model for open innovation with measure to track the behaviors and actions of the firm.

A firm’s business model should be to use its intellectual property (IP) proactively as an asset to enable open innovation cooperation with other firms rather than protecting its IP (Chesbrough, 2006; Viskari, Salmi & Torkkeli, 2007) and actively leverage novel external knowledge to create breakthrough internally on products and services from extant corporate knowledge for new and expanded markets ahead of competitors (Hargadon & Sutton, 2000; Zahra & George, 2002).

In today’s economy, enlightened firms collaborate to innovate across the entire innovation chain. An open innovation business model nurtures a pervasive corporate culture of cooperative and collaborative engagement across the innovation network – both internally and externally. The four building blocks of an open innovation business model are social capital, network ties, boundary spanning and adaptive absorptive capacity. The Innovative Capacity Index (ICI), based on these four building blocks, provides discerning measures of the social network collaborating across the innovation value chain. Leadership can use the ICI to track and monitor the behaviors and actions of the firm.

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The ICI illustrates the social network of who is talking to whom across the innovation value chain and about what, when and how. With the ICI, leadership can more readily recognize and draw attention to individuals in the corporation who seek unfamiliar knowledge outside their comfort zone and integrate novel ideas into the design of new products and services. With the ICI, leadership can encourage the clusters of innovation and incentivize collaboration in areas where there are gaps. With the ICI, leadership can identify “hot topics” across the value chain and be the first mover on new knowledge that is structural holes with no connections to other firms. Finally, using the ICI, executives will balance and shift the strength of strong and weak network ties with other firms based on depth and diversity of knowledge needed and the payoff of these ties.

Open innovation is the emerging business model for a firm in today’s economy to work across the innovation value chain in the generation of novel ideas and development of new products, services and markets. The innovative capacities of a corporation provide the building blocks for effective open innovation. The ICI provides corporate executives with the measures and metrics of these capacities to continually track and respond decisively to a firm’s innovation behaviors and actions for competitive advantage.

McGrath (2001) contends that innovation is the creation of variety and that exploration is critical for diversity. She studied 56 exploratory projects, in large companies, designed to create new business. She found that with exploration greater autonomy in goals and supervision is best; however, as the project moves to exploitation, less autonomy in goals and supervision gives better results. Further, she found that exploration is most successful when variances in research are explored rather than the mean. This is consistent with Taleb, el al.’s (2009) extensive research of invention that he asserts comes from attention to anomalous behavior and discovery

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rather than normal operations and findings. It is the sensing of novel knowledge with activation triggers to explore and the balance of exploration and exploitation that differentiates firms in new market opportunities leading to competitive advantage (Andriopoulos & Lewis, 2009; Raisch, Birkinshaw, Probst and Tusman,2009; Zahra & George, 2002).

Social Capital Social capital is described as the goodwill that is engendered by the fabric of social relations and mobilized as an asset to facilitate action (Alder & Kwon, 2002). It has been found to influence many things in research including the facilitation of inter-unit resource exchange and product innovation (Hansen, 1999; Nahapiet & Ghoshal, 1998; Tsai & Ghoshal, 1998).

Social capital results from the development of a firm’s social cohesion with a willingness and motivation to invest time, energy and effort in collaborative sharing of knowledge (Reagans & McEvily, 2003).

Ahuja and Carley’s (1999) case study of communications in virtual organizations found that social capital provides power benefits in gaining access to information in the network but requires considerable investment to establish and maintain relationships. Ahuja (2000b) studied the technical collaborative linkages in the chemical industry. He found that firms with technical, commercial and social capital stock affect the firm’s ability to induce other firms to collaborate and provides opportunities to form linkages. Technical capital represents a firm’s capabilities in creating new technology, products and processes. Social capital represents a firm’s reputation and brings with it the prior relationships leading to the reputation and building of trust. A firm’s social capital affects its ability to induce other firms to collaborate and share knowledge (Ahuja, 2000b). The social network formed facilitates collaboration in strategically important groups (Cross, Borgatti, & Parker, 2002). The research of Reagans and McEvily (2003) assert that the

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social cohesion of a firm for collaborative sharing and extensive network ties affect the social capital and knowledge transfer for information diffusion.

Scillitoe and Chakrabarti (2005), in the study of fifty-four new technology-based venture (NTBV) firms affiliated with technology incubators in the United States and Finland, identified three sources of beneficial social capital within human networks: historical ties, organizational facilitation and trust-based shared pursuit of common goals. They found organizational facilitation as the primary source of social capital between the NTBVs and incubators.

A key factor in social capital is trust. Trust provides the building blocks for successful inter-firm behavior during collaboration (Ammeter, Douglas, Ferris, & Goka, 2004; Child, 2001). Research provides practical recommendations for developing and sustaining trust relationships applicable to the inter-firm exchange of information, ideas and intelligence (Handy, 1995; Leonard & Swap, 1999; Meyerson, Weick, & Kramer, 1996; Prather, 1996). Trust and openness is a crucial dimension of a climate for innovation (Prather, 1996). Open innovation inherently begins with thin trust among the individuals in the firms involved in forming new or temporary groups (Meyerson, Weick & Kramer, 1996). These groups build thicker trust relationships as the relationships mature through shared experiences (Fleming & Waguespack, 2007; Meyerson, Weick, & Kramer, 1996; Weibel, 2001). Working across inter-firm teams raises trust issues that Handy (1995) offers seven principles for managing around the interaction and behaviors to most effectively share information, ideas and intelligence.

Leonard and Strauss (1997) identify conflict management as a major requirement for innovation and an opportunity to build trust through respectful sharing of differences of opinion and perspective. Fleming and Waguespack (2007) identify the trust required for boundary spanning. They find that trust is most easily established through physical interaction. This

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research supports Child (2001) findings defining mutual trust as an essential ingredient with three stages to build: between people and firms working together; team members sharing positive experiences strengthening mutual understanding; extended periods of fruitful collaboration where strong personal bonds develop. Social capital represents the asset that a corporation must build and sustain to facilitate the absorptive capacity across inter-firm and intra-firm networks.

While still a relatively immature theory, researchers are modeling social capital as a means of illustrating the implications of behavior of people and corporations in social networks addressing inter-firm challenges and opportunities (Burt, 2004; Fleming,& Waguespack,2007; Nahpiet & Ghoshal, 1998). Social capital is found to promote socially-minded behaviors and build trust by influencing the social norms and values of firms, facilitate the spread of knowledge for innovation and reduce the cost of conducting day-to-day business (Alder & Kwon, 2002; Batt, 2008). Research shows that social capital helps actors gain access to information in the innovation network (Alder & Kwon, 2002).

Summary of Findings The literature related to open innovation shows an increasing recognition of the importance of open innovation due to the significant increase in cost of research, pace of innovation and mobility of knowledge. The literature shows the successes of leading corporations in the adoption of open innovation and the variety of the business models emerging.

The literature shows the challenges in four key areas in the adoption and use of open innovation.

First, a company must build its social capital with a culture of willingness and motivation for external collaboration and use of unfamiliar research. Firms build reputations that become their social capital for external knowledge sharing and market opportunities in the innovation network. Second, social capital facilitates the network relationships that a firm builds to enable Page | 38

access to external knowledge and resources and the alliances and partnerships formed. Third, social capital and network relationships enable the spanning of corporate boundaries to access external knowledge and the corporate priorities and resources. Firms that are first movers on structural hole gaps in knowledge connected to the innovation network provide significant opportunity for competitive advantage. Finally, a firm’s ability to recognize novel external network knowledge, integrate it with corporate and alliance knowledge to produce innovative product and services and scale to the market is built on social capital, network ties, boundary spanning and absorptive capacity to realize the goals of open innovation and positions a firm for continual competitive advantage.

Corporate leader involvement in balancing open innovation to achieve ambidexterity in exploration and exploitation across the innovation phases is crucial to success with a central position in the innovation network and strong relationships with relevant firms for knowledge sharing. Dynamic corporate processes and metrics are needed to assure appropriate spanning of the innovation network, access to novel information and triggers for novel and anomalous knowledge that signal new discovery and novel combinations of extant external knowledge to new products and services. Frameworks are needed to synthesize research and integrate with empirical data on corporate practice to affect the transition to emerging business models supporting open innovation. Metrics are needed to guide corporate executives through the tensions balancing exploration in search of breakthrough technologies and the discipline for exploitation of product and market development. These metrics are necessary for executives to dynamically adapt priorities and resources to pursue opportunities for network relationships and spanning boundaries of other firms to leverage new external knowledge and stimulate the internal culture for innovation beyond incremental change.

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Chapter 3: Analysis and Discussion

Open innovation provides the opportunity for the acceleration of corporate innovation for business value at lower cost (Chesbrough, 2003). Innovative firms design a corporate environment with the willingness and motivation to openly innovate across idea generation, product, service and market development business practices (Chesbrough, 2003; Reagans & McEvily, 2003). Major multi-national corporations are successfully developing and transitioning to open innovation business models globally today with intellectual property with varying business practices and proactive use of intellectual property (Chesbrough, 2006; Viskari, Salmi & Torkkeli, 2007). The open approach to innovation positions a firm to collaboratively discover novel ideas externally and exploit internally. This would be hard, if not impossible, with traditional business processes (Almirall & Casadesus-Masanell, 2010; Chesbrough, 2006). The promise of open innovation introduces a need for an enlightened culture and mindset for the corporation with an openness to explore and consider external knowledge internally that may be unfamiliar and possibly disruptive to product, service and market development phases of operations (Andriopoulos & Lewis, 2009).

Based on investigation of the leading research of open innovation, the capacities needed in a corporation to openly innovate are social capital, network ties, boundary spanning and adaptive absorptive capacity. Figure 1 provides a conceptual framework for these capacities with the causal effects shown in Figure 2. This framework and the causal effects are discussed in the following sections.

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Figure 1. Open Innovation Conceptual Framework

Figure 2. Open Innovation Causal Effects

Social Capital Social capital is a result of a corporate culture with openness for innovation within the firm and with other firms. Social capital is an asset for building relationships and trust across the innovation network (Kim & Mauborgne, 1997; Reagans & McEvily, 2003). A firm develops a reputation for cooperatively sharing knowledge with others in the innovation network while protecting its business interests (Ahuja, 2000a, Reagans & McEvily, 2003). This reputation Page | 41

becomes the firm’s social capital that induces or hinders formation and evolution of the network relationships with firms across the innovation network to facilitate the spread of knowledge for innovation and reduce costs while achieving complementary competitive advantage (Alder & Kwon, 2002). This reputation includes how the firm handles the delicate area of “selective revealing” of knowledge and expertise (Henkel, 2006) to build trust while keeping other aspects of intellectual property private consistent with the firm’s innovation business model (Chesbrough, 2006; Viskari, Salmi & Torkkeli, 2007).

Network Ties Social capital facilitates the formation of network ties in relationships with other firms, forming relationships and trust to span the boundaries of the firms. Network ties are formed based on the objectives of a firm and its social capital in the network (Ahuja, 2000a). The optimal structure of inter-firm networks depends on the objectives of the network members Ahuja (2000a). Network ties may be in the form of direct relationships between firms with varying types of agreements ranging from alliances, joint ventures, and other formal agreements to trust-based relationships developed through professional and social interaction. Strong direct ties have been shown to have the most effective means to gain in-depth access to complex knowledge. Weak ties have been shown to provide the best access to the widest range of diverse knowledge, but strong ties are needed for the transfer of knowledge (Hansen, 1999).

Agreements for direct relationships will provide higher quality access but take time, energy and resources to maintain (Ahuja, 2000a; Hansen & Birkinshaw, 2008).

Network ties may also be indirect where a corporation gains knowledge spillover of the knowledge of other firms through trusted interaction with those with whom they have direct connections (Ahuja, 2000b). Significant information is publically available or available through

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membership-based innovation communities requiring ties with the sources of the information.

Valuable “structural holes” are the absence of links in the innovation network to new knowledge.

Structural holes may be discovered by innovative firms through relationships with firms or communities with new knowledge that is not yet linked (Hsin-Min, Se-Hwa, Chao-Tung & Fend-Shang, 2008). Discovering structural holes provides first mover competitive advantage after the discovery of untapped knowledge possibly advancing the network position of a firm (Burt, 2004). Liu (2010) and Burt (2004) assert that the breath of ties across the innovation network and the centrality of a firm’s position in the network between structural holes and other firms will lead to competitive advantage and higher performance. In innovative firms, novel knowledge found externally stimulates triggers for action of the absorptive capacity processes in the firm to explore the new external knowledge with extant knowledge of the firm. Success in the generation of novel products and services and markets from external knowledge reinforces the culture for open innovation.

Boundary Spanning Network ties facilitate boundary spanning by the corporate representatives responsible for building relationships and trust with other firms to scan the firms’ knowledge. Boundary spanning develops peripheral vision of relevant knowledge beyond the firm’s expertise and a firm’s immediate business interests. Boundary spanning provides a firm with the opportunity for the discovery of unusual perspectives and competitor trends (Zien & Buckler, 1997). Network ties provide firms with the ability to span the boundaries of other firms to discover and access new and relevant knowledge available in firms with whom they have relationships. Boundary spanning is a key driver to triggering a firm’s absorptive capacity (Cohen & Levinthal, 2990: Zahra & George, 2002).

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The nature of a firm’s network ties with other firms will determine the degree and ease of access the firm will have to the other’s intellectual property. Competitive advantage is highest in the discovery of structural holes where there are weak innovation network links to knowledge (Burt, 2004). Firms reach strategic agreements with the owners of the intellectual property regarding its access to and use of the knowledge for new products, services and market development. Firms will reach agreements for the terms of use of the knowledge ranging from licensing, strategic alliances, joint venture and acquisition (Tidd, 2001) in line with the intellectual property strategy of the innovation business model of the firm (Chesbrough, 2006; Viskari, Salmi & Torkkeli, 2007).

Strong collaborative social capital of boundary spanners induces the cooperation of firms, including competitors, in appropriate interaction with the knowledge of the firm. Reciprocity of the boundary spanner in negotiating its corporate knowledge will enhance the trust and opportunity for knowledge sharing and further the network ties. The boundary spanning representative of a firm will meet with relevant companies, participate in conferences and meetings, review published information and hold technical discussions to exchange knowledge.

In lean times, boundary spanners continue to build rapport with cooperative partners in complementary and sometimes competitive fields. Firms may license technology, knowledge or patents with trusted competitors who have the resources to develop a technology area and market (Chesbrough & Garman, 2009). The firms will agree to preferential access to the technology developed providing opportunity for collaborative and complementary market development as conditions improve (Chesbrough & Garman, 2009).

Boundary spanning results in a perspective of the knowledge in the innovation network and the identification of novel knowledge relevant to the firm’s business interests. An

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innovative firm should have dynamic processes for a boundary spanner to alert a firm to new, novel external knowledge that triggers its absorptive capacity.

Adaptive Absorptive Capacity Adaptive capacity is a firm’s ability to identify new relevant external knowledge, integrate it with internal knowledge to create new novel products, services and markets (Cohen & Levinthal, 1990; Zahra & George, 2002). The knowledge perspective and novel knowledge alerts that are identified by boundary spanners should be continually tracked by the firm’s adaptive absorptive capacity processes. Relevant information should be rapidly assessed and absorbed into the knowledge bases of the corporation for the novel combination of the external knowledge with extant internal information in new and innovative ways (Zahra & George, 2002). Discoveries are likely to occur quickly and can be disruptive to disciplined corporate efforts. Exploration of new knowledge is driven by passion to lead to breakthrough ideas and associated triggers to identify opportunities for novel product ideas (Andriopoulos & Lewis, 2009). Exploitation is driven by discipline to evolve the current products, services and markets.

Exploration operates best with autonomy with respect to goals and supervision while exploitation has better results with less autonomy and more discipline (McGrath, 2001).

A firm’s absorptive capacity processes should balance the tension of distraction of knowledge exploration with disciplined exploitation efforts for product, service and market development. Breakthrough ideas are higher risk and will not always lead to market opportunities. Leadership should stay actively involved, alert and responsive to mediate priorities, funding and resource allocation working ambidextrously with exploration and exploitation efforts to discover new knowledge and develop innovative products, services and

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markets (Andriopoulos & Lewis, 2009; McGrath, 2001; Taleb, Goldstein & Spitznagel, 2009; Zaheer & Zaheer, 1997).

Innovative Capacity Index (ICI) Executive leadership needs measures and metrics to guide decisions for priorities, investments and resources for knowledge exploration and exploitation in support of the firm’s open innovation strategy. The Innovative Capacity Index (ICI), shown in Figure 3, provides the four innovative capacities of a firm for open innovation. Each capacity has five levels of innovative behavior. The four innovative capacities of the ICI are social capital, network ties, boundary spanning and adaptive absorptive capacity of a firm. Each indicator is described in Table 5 and its mapping to the innovative capacities variables. The ICI provides executives with measures and metrics for each level. The ICI provides a corporation with a strategy and mechanism to collect data for statistical analysis of strategic trends to continually refine, correlate with corporate performance and improve the corporate innovation strategy.

The ICI is a latent measure of the formative structure (Sanchez-Perez & Iniesta-Bonillo, 2004) of the multiple indicators and multiple causes (MIMIC) of innovative behavior as shown in IC-1 through IC-8 in Figure 4 and described in Table 6. IC-1 is an indicator of a firm’s behavior and actions to form network relationships with firms with valuable knowledge. IC-2 is an indicator of the access provided to external knowledge as a result of the network relationships.

IC-3 is an indicator of collaborative behaviors and actions of a firm with individuals in external organizations. IC-4 is an indicator of the corporate rewards and recognition and their impact on the collaborative behaviors and actions of individuals in the firm. IC-5 is an indicator of the behaviors and actions to find the best-in-class knowledge in areas complementary to a firm. IC-6 is an indicator of the behaviors and actions of collaboration internally and externally that result

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in the generation of new, novel ideas. IC-7 is the indicator of the corporate awareness of and alerts for external knowledge and ideas that augment the expertise and knowledge of a firm providing peripheral vision for the topics of interest. IC-8 is an indicator in the adaptation and responsiveness of the firm when novel external knowledge is discovered and new promising products, services and markets are developed.

Figure 3. Innovative Capacity Index

Figure 4. Initial MIMIC Model for Innovative Capacity

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Table 5. Innovative Capacity Indicators Item

Description

IC-1

Firms will form network relationships with firms they believe have valuable knowledge and will be cooperative and respectful.

Network ties facilitate access to external knowledge.

Firms will establish effective values and norms for knowledge sharing within the firm and across the innovation network for cooperative gain.

Individuals will collaborate when rewarded, recognized and given executive advocacy.

Firms will seek knowledge sharing with those who are best-in-their class in complementary areas.

Firms will adaptively respond to external knowledge, harmonize each other’s efforts with complementary research and idea generation for cooperative gain.

External knowledge will facilitate peripheral vision for internal discovery of new value opportunities internally.

IC-2 IC-3

IC-4

IC-5

IC-6

IC-7

IC-8

Reference

Adaptive balance in priorities, investment and resources between discovery exploration and product / market exploitation leads to selected market opportunity.

Begley, 2006; Brickley, et al.

2009; Reagans & McEvily, 2003

Innovative Capacity Variable Network Ties

Ahuja, 2000a; Scillitoe & Chakrabarti, 2005 Alder & Kwon, 2002, Chesbrough, 2007; Leonard & Strauss, 1997; Reagans & McEvily, 2003

Network ties

Brickley et al, 2009; Zien & Buckler, 1997, Menzel, Aaltio & Ulijin, 2007 Chesbrough & Garman, 2009

Social Capital

Chesbrough & Garman, 2009, Haragdon Sapienza & Davidsson, 2006; Zahra & George, 2002; Teece, 2004; Cohen & Levinthal, 1990; Cunha & Chia (2007), Hargadon, 2002; Knott, Posen & Wu, 2009, Kim & Mauborgne, 2005, Zien & Buckler, 1997 Andriopoulos & Lewis, 2009; Raisch, 2009; Hargadon, 2002; Zahra & George, 2002

Adaptive Absorptive Capacity

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Social Capital

Boundary spanning

Boundary Spanning

Adaptive Absorptive Capacity

represent the measures of each innovative capacity indicators IC-1 through IC-8 as represented in the MIMIC model illustrated in Figure 4.

1-

4 represent

the values of

aggregated innovative indicators associated with each variable of the MIMIC model as shown in Figure 4.

1

-

4 represent

the errors affecting the MIMIC model for innovative capacity in

Figure 4. The errors remain in the model for subsequent empirical research beyond the scope of this paper.

For each measure of innovative capacity, metrics are provided in Table 6 for observable behaviors and actions of individuals in the corporation that are desirable. By observing these behaviors and actions, an assessment can be made of the metrics to assess the level of innovative capacity performance in the organization as shown in Table 6. A higher level is associated with higher innovative capacity. For instance, the metrics for social capital will collect metrics for the collaborative interactions occurring and the rewards and recognition from leadership. The analysis of these metrics includes the spanning of the occurrence of the collaborative interaction, what behavior is being rewarded and an assessment of the degree of diversity in the groups collaborating. Lower diversity occurs when similar groups interact. Higher diversity occurs when groups across organizations and across firms interact. Collaboration among diverse groups will position a firm at a higher level of innovative capacity and collaboration with formal community organizations will position the firm highest.

Table 6 provides the levels of increasing capacity for each variable of the index and the metrics observable in the business processes of a firm for each of the indicators. The five levels in the ICI for the social capital dimension, in increasing capacity, are (a) individual competencies, (b) competencies of groups of individuals collaborating, (c) competencies of inter-

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Table 6. Innovative Capacities, Levels and Metrics Capacity

Metrics

Levels

Social Capital - Number, frequency and repeated Capacity interactions - Span and clustering of relevant (IC-3, IC-4) interactions - Number, frequency and repeat requests to participate in collaborative events; level of participation.

- Number, frequency and levels of rewards, recognition and communication Network Ties - Number and duration of direct and Capacity indirect ties and ties to structural holes - Speed of access to new knowledge by (IC-1, IC-2) source - Degree of relevance of knowledge discovered to new products, services and market development by source - Relative cost of maintaining ties and relationships Boundary - Frequency of relevant new knowledge Spanning awareness Capacity - Activation triggers for idea generation - Cost and timeliness of relevant new (IC-5, IC-7) knowledge capture Dynamic - Frequency of action on alert of new Absorptive external knowledge Capacity - Frequency of assimilation of relevant new knowledge (IC-6, IC-8) - Frequency of new ideas leading to new products - Frequency of new ideas leading to market opportunity

- Individual collaboration competencies - Group collaboration competencies - Inter-group collaboration competencies - Inter-firm collaboration competencies - Inter-network collaboration competencies

- Ties to publically accessible knowledge - Ties to protected permission-based community knowledge - Ties to internal organizations - Ties to external firms - Ties to formal innovation communities -

Individual spot knowledge awareness Individual knowledge accessibility Collective knowledge awareness Collective knowledge accessibility Real-time alerts of new knowledge Internal awareness of new knowledge Assimilation of new knowledge into internal processes Combination of new and existing knowledge for new product/process/service ideas New product development Selected market opportunity development

group collaboration, (d) competencies of inter-firm collaboration, and (e) competencies of internetwork collaboration. The social capital measure provides leadership with information to assess the behaviors of the firm towards willingness and motivation to collaboratively share knowledge both inside and outside the company (Reagans & McEvily, 2003). This information provides a

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firm with the information on the success of conveying the desired corporate culture and the value of the incentives. Rewards and recognition from executive leadership for desired collaborative behaviors leading to successful market pursuits provides valuable opportunity for communication of the expectations of executive leadership to reinforce the desired social capital (Zien & Buckler, 1997).

Social Capital Capacity As shown in Table 6, there are four metrics to measure the first Innovative Capacity Index variable of social capital. The social capital capacity is derived from the innovative capacity indicators IC-3 and IC-4. These metrics are the observables from behaviors and actions of individuals in the corporation in collaborative interaction internally and with other firms. The first tangible metric captures the number, frequency and repeated collaborative interactions intraand inter-firm. The second metric measures the span and clustering of interactions. It is critical to monitor informal network relationships underway to support strategically important collaboration (Cross, Borgatti & Parker, 2002) and incentivize needed collaboration that may be lacking especially regarding knowledge in structured holes undiscovered by others in the innovation network (Burt, 2004; Hsin-Min, Se-Hwa, Chao-Tung & Feng-Shang, 2008). The third metric measures the impact of the corporate culture on external firms and organizations.

This metric captures the requests received by the corporation for individuals of the firm to participate in external collaboration. The frequency of invitations as well as the level of stature in the request for participation, to include invitations for keynote speakers and leaders of forums or round-tables, indicates respect for the individuals and the firm. The fourth metric measures the internal reward and recognition system to incentivize the norms and behaviors of individuals.

A corporation should ensure appropriate awards are given and communicated well to reinforce

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the executive leadership demand for innovation (Brickley, Smith, Zimmerman, & Willett, 2009; Zien & Buckler, 1997). Based on these metrics, leadership can take action to influence appropriate external knowledge exploitation. Learned path-dependent processes that lead to the not-invented-here syndrome in a corporation are difficult to change in the short term and result in a tendency toward internal versus external knowledge exploitation (Lichtenthaler, Ernst, & Hoegl, 2006). Firms that are open to transferring knowledge based on their prior experience tend to identify a large number of knowledge transfer opportunities that influence better R&D performance (Lichtenthaler, Ernst, & Hoegl, 2006).

Network Ties Capacity The second ICI capacity measure shown in Table 6 is network ties and is derived from the IC- 1 and IC-2 indicators. This measures the productivity of the network ties that a corporation has established for access to relevant knowledge in the innovation network to offset rising R&D costs, accelerate product revenue and life cycles (Bullinger, Auernhammer, & Gomeringer, 2004; Chesbrough, 2007). Inter-firm networks are now accepted as playing a central role in a process of innovation forming collaborative networks to leverage and exploit the knowledge needed and to motivate technological change (Ozman, 2006). The network structure, and a firm’s position in it, facilitates awareness of other firms’ relevant knowledge and enables access to the knowledge (Tsai, 2001). Network ties facilitate collaborative inter-firm innovation, contribute to “social capital” and have a positive impact on innovation as a key mechanism for knowledge spillovers of industry successes and failures (Ahuja, 2002a).

The types and payoff of network ties established with firms with potential relevant knowledge provides essential pathways to valuable knowledge sources. Knowledge sources are those within firms, publically available, on the Internet and within innovation communities. Ties

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with individuals and firms controlling access to these sources may be direct, trust-based connections, indirect through direct ties, or awareness-based spillovers from knowledge made publically available by firms. Access to sources of knowledge is based on professional and social relationships with legal, contractual or experience-based trust arrangements, indirect spillovers from direct ties, internet-based access, public published materials, and communitybased memberships. Professional and social relationships require time and resources to establish and sustain. Direct ties provide deep access to knowledge. Indirect ties provide knowledge spillover. Structural holes discovered through spillovers, public and private communities provide unique opportunities to first movers. Network ties have varying costs. Strong ties are more expensive to maintain than weak ties (Hansen, 1999).

The five increasing levels of capacity for network ties align the type of ties with the type of knowledge available. The first level is access to publically accessible knowledge requiring no ties. The second level is trust-based ties for access to protected permission-based knowledge.

The third level is direct inter-firm ties for deeper access to public knowledge. The fourth level is trust-based inter-firm ties for access to confidential private knowledge. The fifth level is trustbased ties for innovation community-based knowledge with access to knowledge available to the trusted community. The decisive metrics for this dimension are the number of ties, level of relevant knowledge exchanged and relative cost per unit of relevant knowledge gained by type of tie. The ability to form and leverage ties is linked to the social capital of a firm.

It is the IC -1 and -2 innovative capacity indicators that focus on how rewarding the network ties are and how much knowledge is associated with those ties. This will provide leadership with measures of the payoff of those ties for boundary spanning and intra- and interfirm collaboration for each of the forms presented previously in Table 3. This will provide

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essential real-time insight and trends for executive leadership to dynamically adapt in accordance with the innovation business model (Chesbrough, 2006; Viskari, Salmi, & Torkkeli, 2007) and communicate successes and realities of achieving the strategic vision (Brickley, Smith, Zimmerman & Willett, 2009).

Boundary Spanning Capacity The third capacity measured by the ICI is a firm’s capacity for spanning the boundaries of knowledge domains. This measure is derived from IC-5 and IC -7 indicators as shown in Table 6. Boundary spanning provides the opportunity to develop strategic peripheral vision of relevant knowledge outside the focus of a firm for unusual and anticipatory market opportunities external to the firm (Cunha & Chia, 2007). A key role of the boundary spanners is to develop the relationships with those in the innovation network with relevant expertise for access into the breadth and depth of the knowledge. Knowledge brokering provides the linkage between a firm’s internal networks and external sources of information (Tushman, 1977; Tushman & Scanlan, 1981). Firms draw extensively on strong social networks both within and outside their firms to spark technological revolution with a steady stream of growth opportunities from existing businesses (Hargadon, 2005). The discovery of this knowledge contributes to the social capital increasing a firm’s ability to span boundaries and broker knowledge. This provides the alerts of new relevant external knowledge to the adaptive absorptive capacity processes of a firm from knowledge within the innovation network (Burt, 2004).

The five increasing levels of capacity of the boundary-spanning dimension as shown in Table 6 are (a) uncoordinated instances of awareness of relevant external knowledge and its sources, (b) coordinated awareness of aggregate external knowledge and its sources, (c) uncoordinated access to instances of relevant external knowledge (d) coordinated access to

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aggregate relevant external knowledge, (e) alerts to new relevant external knowledge. The decisive metrics of knowledge spanning are (a) the amount of relevant external knowledge discovered, (b) minimizing the delay in accessing relevant external knowledge relative to when it first became available, and (c) the average cost per unit of relevant external knowledge gained over time for each source for each knowledge spanner. IC-5 and IC-7 provides indication of the success in boundary spanners creating knowledge of and access to the best in-class knowledge within the firm and across the innovation network for alertness, responsiveness and flexibility that are critical to profit from information obtained through ties (Vanhaverbeke Gilsing, & Duysters, 2007; Zaheer & Zaheer, 1997). For IC-7, the peripheral vision gained through boundary spanning can incite exploratory discovery of the combination and use of new knowledge with existing knowledge (Cunha & Chia, 2007) especially when encouraged by leadership through personal advocacy of the balancing of priorities needed (Andriopoulos & Lewis, 2009) and allocation of the time, attention and resources needed (Menzel, Aaltio, & Ulijn, 2007). The metrics for tracking boundary spanning include frequency of identification of new relevant knowledge discovered, activation triggers initiated for relevant knowledge, cost and timeliness of acquisition of new knowledge for internal idea generation, and new products.

Agile Absorptive Capacity The fourth capacity measured by the ICI is the agile absorptive capacity of the firm as indicated by IC-6 and IC-8. Agile absorptive capacity assures the appropriate balance of exploratory and exploitive efforts in the firm to maximize pursuit of new market opportunity (Zahra & George, 2002). Absorptive capacity has been introduced by researchers as an essential competency to integrate external knowledge into the internal innovation processes of a firm (Cohen & Levinthal, 1990; Lichtenthaler, 2008; Tsai, 2001; Zahra & George, 2002). Leveraging

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the diversity of expertise across the firm combining new knowledge is essential (Cohen & Levinthal, 1990). The brokering of ideas and efforts towards new products and markets aligns three essential inter-dependent factors at work in the corporation: innovation strategy, work practices and people (Hargadon, 2005). Absorptive capacity relies on network ties and boundary spanning for peripheral vision to recognize and access relevant external knowledge and energize internal business processes to exploit the external knowledge for breakthrough ideas, new products and markets (Cunha & Chia, 2007). The exploratory efforts are driven by the strategic drive and personal passion for breakthrough innovation to discover new customer uses for new innovative products and services. Exploration pursuits should be balanced with the disciplined pursuit of exploitation of new product, services and market development (Andriopoulos & Lewis, 2009). Assimilation and integration bring discovered knowledge into the firm, leads to an understanding of its relationship to internal knowledge and facilitates strategic pathways for linkages with internal knowledge to generate innovative ideas for new business value. The ambidexterity of innovative firms to navigate and balance the tension between the exploratory and exploitative efforts to identify selected market opportunities leads to sustained competitive advantage (Andriopoulos & Lewis, 2009; Raisch, Birkinshaw, Probst & Tushman, 2009).

The increasing levels of capacity of the absorptive capacity of a firm, as shown in Table 6, are (a) awareness of new knowledge, (b) new ideas from the combination of new and existing knowledge, (c) assimilation of new knowledge into internal innovation processes, (d) new product development, and (e) selected market opportunity development. The metrics for absorptive capacity are the frequency and value of new knowledge identified, most productive knowledge sources leading to new ideas, and time span of new knowledge and ideas leading to market opportunity. IC-6 and IC-8 are the indicators of innovative capacity in the business environment

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related to absorptive capacity. IC- 6 provides insights into the relevancy and harmonization of this peripheral vision knowledge discovered through boundary spanning and the activation triggers that lead to new combinations with extant knowledge (Cunha & Chia, 2007) for new idea generation and the results of the corporation’s social capital (Alder & Kwon, 2002) and network ties (Ahuja, 2000a). IC-8 tracks corporate ambidexterity on the realization of the balanced alignment of exploration and exploitation to achieve selected market opportunity as a key attribute of adaptive absorptive capacity (Andriopoulos & Lewis, 2009; Raisch, Birkinshaw, Probst, & Tushman, 2009). A firm pursuing exploratory knowledge is seeking breakthrough ideas while a firm pursuing exploitation of knowledge is seeking continuous improvement (Andriopoulos & Lewis, 2009; McGrath, 2001).

The ICI metrics and levels of capacity will assist leadership in assessing the culture of the firm for innovative knowledge collaboration and balancing the challenges of managing the nearterm project and product allocation of priorities, resources and funding with the free-form exploration of breakthrough potential (Raisch, Birkinshaw, J., Probst, G., & Tushman, 2009).

Executives can use the ICI, its indicators and metrics for feedback on priorities, funding and rewards. Adjustments can be made as needed to incent the corporate culture and mindset of individuals towards the innovation strategy of the corporation.

Innovative Capacity Index Measurement A firm collecting metrics based on the measures shown in Table 6 for the innovative behaviors and actions of its staff can quantify its Innovative Capacity Index and monitor changes over time. Figure 5 provides an example measurement from a hypothetical assessment of the sample metrics assumed to be collected from the IC indicators shown in Tables 5 and 6.

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Figure 5. Innovative Capacity Index Spider Chart

These metrics can be collected from tracking day-to-day actions of individuals across firms.

Example of metrics can include, but are not limited to, social network analysis of emails, meetings and discussions between people, corporate invitations between firms, and external knowledge shared between firms and new projects initiated as a result of external knowledge.

Persons can be tracked anonymously to retain privacy of individuals bit retain type of people involved. Tracking, monitoring and acting on metrics such as these requires executive action.

Responding appropriately to changes and trends will result in the adaptive ambidextrous capacity of innovative firms (Andriopulos & Lewis, 2009; Hargadon & Fagnelli, 2002; Raisch, Birkinshaw, Probst & Tushman, 2009).

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The example in Figure 5 illustrates the grading of the firm for each of the four innovative capacities. Social capital is graded at the third level of social capital where individuals in the firm are collaborating between groups in the firm but not with other firms. In this example, network ties received the highest score of five indicating that the firm has ties at all levels of sources of external knowledge from publically accessible knowledge to the most powerful community-based innovative knowledge. Boundary spanning, however, is scored as a four indicating accessibility to community knowledge, but no real-time alerting to the firm. Adaptive capacity is scored with the metrics as a two indicating that new knowledge is being assimilated into internal processes, but not influencing any new products, services or markets. Regular assessments like this can provide signals for executive leadership to adapt business practices, incentives and priorities to improve the culture for openness to external knowledge and innovative use with the firm’s knowledge and expertise (Hargadon, 2005; Zahra & George, 2002). In addition, these assessments reveal patterns of tendencies to reject external knowledge as not invented here (NIH) and increase openness to external knowledge to advance the firm’s innovative performance (Hamaoka, 2008).

Open Innovation Conceptual Framework Propositions Figure 6 provides six key propositions mapped to the conceptual framework for collaborative open innovation and summarized in Table 7.

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Figure 6. Open Innovation Framework Mapped to Propositions

Table 7. Open Innovation Propositions Proposition

Description

P1

Higher social capital leads to more network ties and boundary spanning.

P2a

More direct network ties lead to more boundary spanning for the reciprocal exchange of complex knowledge and resources with external firms.

More indirect network relationships with firms lead to more boundary spanning for the reciprocal exchange of knowledge spillovers but not complex technological knowledge from external firms.

More structural holes lead to more boundary spanning for knowledge spillovers and discovery of more novel differentiating market ideas.

More network ties and boundary spanning will result in more activation triggers for internal knowledge exploration More activation triggers lead to higher adaptive absorptive capacity.

P2b

P2c P3 P4 P5 P6

Adaptive absorptive capacity will produce more selected differentiating market opportunities.

A higher Innovative Capacity Index correlates with more differentiating market opportunities selected by executive leader advocates

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Proposition 1 Social capital helps individuals in firms gain access to information in the innovation network (Alder & Kwon, 2002). The business interest of firms and their capacity to engage in open innovation is driven by the firm’s perception of business value from market opportunities (Chesbrough & Appleyard, 2007) and network relationships that can be employed to discover relevant external knowledge and resources (Ahuja, 2000a, 2000b; Alder & Kwon, 2002). Social capital positively influences social norms and values of a firm towards socially-minded behaviors for the openness to external knowledge (Hamaoka, 2008) to provide power benefits inducing the spread of needed knowledge and innovation, access to the knowledge inter-firm and a reduction in the cost to collaborate (Ahuja & Carley, 1999: Alder & Kwon, 2002; Batt, 2008).

This leads to Proposition 1 where firms with higher social capital will have more network ties and span more boundaries.

Proposition 2a, 2b, 2c Firms develop network relationships to gain access to external information in the innovation network (Alder & Kwon, 2002). The structure of this network is dependent on the objectives of firms in the innovation network (Ahuja, 2000a). This leads to Proposition 2a where firms with more direct network relationships lead to more boundary spanning for the reciprocal exchange of complex knowledge and resources with external firms; Proposition 2b where firms with more indirect network relationships with firms lead to more boundary spanning for the reciprocal exchange of market knowledge but not complex technological knowledge from external firms; and Proposition 2c where more structural holes in the innovation network leads to more boundary spanning for discovery of breakthrough ideas in ideas unconnected to the innovation network.

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Proposition 3 More network relationships and boundary spanning will provide wider access to a higher diversity of new knowledge for use by a firm (Ahuja, 2000a; Tushman & Scanlan, 1981). More relevant new knowledge feeds a firm’s absorptive capacity to adaptively combine new knowledge with extant knowledge in new ways to pursue the selected market opportunities (Zahra & George, 2002). This leads to Proposition 3 where more network relationships and boundary spanning will correlate with higher absorptive capacity.

Proposition 4 Firms realize a higher corporate absorptive capacity through the dynamic balance of corporate attention to knowledge exploration seeking breakthrough discovery with disciplined processes for product and market development (Andriopoulos & Lewis, 2009; Cohen & Levinthal, 1990; Zahra & George, 2002). Triggers from boundary spanners on knowledge of interest induces individuals and firms to interact with one another internally and inter-firm for the discovery of new, innovative products and services (Burt, 2004; Fleming & Waguespack, 2007; Hansen & Birkinshaw, 2008; Tsai & Ghoshal, 1998; Zahra & George, 2002). This leads to Proposition 4 where more organizational ambidexterity in exploration and exploitation of relevant external knowledge results in higher absorptive capacity.

Proposition 5 With higher absorptive capacity, a firm will recognize the value of external information, negotiate the terms and conditions to access information to assimilate the knowledge into the firm and apply it to new market opportunities (Cohen & Levinthal, 1990). These firms will achieve lower R&D costs and faster time to market (Chesbrough, 2007; Chesbrough, 2003; Hansen & Birkinshaw, 2008). With network ties, research has shown absorptive capacity to be

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especially important to firms experiencing a high degree of technological and market turbulence (Lichtenthaler, 2009) and is a discriminating factor in higher profits resulting from inter-firm collaboration with selected market opportunities (Lichtenthaler, 2008). This leads to Proposition 5 where firms with higher absorptive capacity are more likely to engage in open innovation collaboration and the knowledge transfers result in internal business operations to rapidly develop new products and services and pursue selected market opportunities.

Proposition 6 Competitive advantage with changing market conditions demands dynamic response (Zahra & George, 2002). Alertness, responsiveness and flexibility are critical to profit from information obtained through ties (Vanhaverbeke, Gilsing, Duyssters, 2007; Zaheer & Zaheer, 1997). The Innovative Capacity Index provides a tool for corporate leadership to track and assess the corporation’s competencies in the critical areas of social capital, network ties, boundary spanning and absorptive capacity. This leads to Proposition 6 asserting that a higher ICI enables more selected market opportunities.

Summary The pace and cost of innovation today demands new business models to interact openly across the innovation network (Chesbrough, 2007). To sustain competitive advantage in today’s fast moving innovation ecosystem, the executive leadership of a firm should create and sustain a new business model for open innovation with measures to track the behaviors and actions of the firm. A firm’s business model should include using its intellectual property (IP) proactively as an asset to enable open innovation with other firms rather than restricting access to its IP (Chesbrough, 2006; Viskari, Salmi & Torkkeli, 2007). A firm can actively leverage novel external knowledge to create breakthrough products and services internally from existing Page | 63

corporate knowledge for new and expanded markets ahead of competitors (Andriopoulos & Lewis, 2009; Hargadon & Sutton, 2000; Zahra & George, 2002).

In today’s economy, enlightened firms increasingly collaborate to innovate openly across the entire innovation chain. An open innovation business model relies on a pervasive corporate culture of cooperative and collaborative engagement across the innovation network – both internally and externally. The four building blocks of an open innovation business model are social capital, network ties, boundary spanning and adaptive absorptive capacity. The Innovative Capacity Index (ICI), based on these four building blocks, provides discerning measures of the social network collaboration across the innovation value chain illustrating who is talking to whom and about what, when and how. The ICI provides executive leadership with a dashboard mechanism to continually track and cultivate the open innovation behaviors and actions of the firm.

With the ICI, leadership can more readily recognize and draw attention to individuals in the corporation who seek unfamiliar knowledge openly outside their comfort zone, share and integrate novel ideas into the design of new products and services. With the ICI, leadership can encourage clusters of innovation and incentivize collaboration in areas where there are gaps.

They can identify “hot topics” across the value chain and make the firm the first mover for business opportunity on new knowledge that represents structural holes with no connections to other firms. Finally, using the ICI, executives will balance and shift the strength of strong and weak network ties with other firms based on depth and diversity of knowledge needed and the payoff of these ties.

Open innovation is emerging as a preferred business model for a firm in today’s economy seeking to work across the innovation value chain to generate novel ideas for the development of

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new products, services and markets. The innovative capacities of a corporation provide the building blocks for effective open innovation. The ICI provides corporate executives with the measures and metrics of these capacities to continually track and respond decisively to a firm’s innovation behaviors and actions for enduring competitive advantage.

Chapter 4: Conclusions Business models of corporations today are changing to respond more openly to consumer-focused innovation driven by volatile market trends. The traditional internally focused innovation funnel pursued by many corporations is shifting to a network model of interaction among firms discerning the value proposition and targeting markets across a more open value chain (Chesbrough, 2006). The firms that best leverage the inter-dependencies and opportunities of the network are more likely to reduce costs of R&D, realize higher revenue, and generate more innovative product, service and market ideas (Chesbrough, 2007).

There are five trends in today’s economy of fast-paced innovation. First, firms increasingly leverage external research and development to stimulate new and novel internal products, services and markets (Andriopoulos & Lewis, 2009; Chesbrough, 2008; Hargadon, 2005). Second, intellectual property is being used proactively as an asset in innovative firms’ business models rather than holding knowledge closely and restricting access (Viskari, Salmi & Torkkeli, 2007). Third, firms are using more creative forms of collaboration to profitably exchange intellectual property with other firms (Tidd, 2001). Fourth, firms are increasingly contributing to open source efforts to build the collective market knowledge in enabling product areas and to lead change in the architectural framework of the industry (Henderson & Clark, 1990; Viskari, Salmi & Torkkeli, 2007). Finally, social media is increasingly influencing the product lifecycles and market direction (Edelman, 2010).

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These trends impact the business models, motivation and reward structures and fundamental social dynamics of firms in the innovation network. Business models are becoming more open requiring new levels of sensemaking, openness to change and speed of action in chaotic market dynamics (McCann, Selsky, & Lee, 2009; Weick, 1993). The “not-inventedhere” syndrome found often in firms significantly inhibits a firm’s competitive advantage and requires change to a corporate philosophy of openness to external ideas (Lichtenthaler, Ernst & Hoegl, 2006). The position of a firm and its level of prestige in an innovative network influence its awareness of and access to external knowledge (Ahuja, 2000b; Ibarra, 1993). Achieving centrality of position in the network and trust among key players is a top priority among innovative firms (Bjork & Magnusson, 2009; Burt, 1977). Social media provides new channels of customer knowledge and market insight necessary for innovation (Edelman, 2010; Hsin-Min, Se-Hwa, Chao-Tung & Feng-Shang, 2008). Creative response emerges from taking agile action on the unexpected and shaping subsequent events (Schumpeter, 1947). In today’s turbulent market economy, unanticipated rare events are the tipping points for innovative firms to seek, create or leverage innovation of large magnitude and consequences, such as Google search or the iPhone (Taleb, Goldstein, and Spitznagel, 2009).

This study develops the Innovative Capacity Index (ICI) for effectiveness of open innovation based on the four key capacities of social capital, network ties, boundary spanning and absorptive capacity, derived from extensive research on the emerging factors of open innovation in today’s market economies. The ICI provides executive leadership with a dashboard mechanism to communicate the behaviors and actions of individuals in the corporation as the corporation pursues open innovation. The behaviors and actions demonstrate the level of innovative capacity of the individuals and of the groups in the firm. The ICI provides

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dynamic feedback to the leadership on the corporation’s capacity for innovation for leadership to take appropriate and timely action to adapt corporate practices and culture.

There are three primary areas for future research to enhance the ICI for use by the leadership of corporations in today’s economy. First, empirical research is needed for the validation of the factors, measures and metrics asserted in this study. The goal should be to identify where the conceptual model is validated and instances where refinement is needed.

Second, the ICI asserts causal effects for four key factors of effective open innovation. Further research is needed to validate these effects and to investigate additional factors and effects. A better understanding of these and other environmental contingencies may lead to a finer-grained understanding of emerging trends and advice for management practice. Finally, the investigation of additional factors that influence the new practice of and culture for open innovation is needed, such as proactive use of intellectual property, the implications of social networking and the trust paradigm in open inter-firm relationships.

My summary conclusion is that to grow and sustain an innovative business, the firm must develop capacities that allow it to accumulate social capital, organically build network ties, span boundaries of firms to access knowledge, and maintain absorptive capacity crucial for organizational learning and knowledge transfer. The pace of innovation in corporations and across the innovation chain leads to tensions complicating the balance of corporate attention on external exploration and internal execution as these capacities are developed. Corporate executives need a dashboard with key measures of the actions and behaviors of the individuals and groups in the firm for the innovative capacities reflecting the execution of the corporate strategy and culture for open innovation. The ICI measures provide visibility into a portrayal of “who is talking to whom about what” and give leaders the insights needed to reinforce and

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redirect priorities, resources, recognition and rewards to influence desired activities and behaviors. Executive leadership can then adapt and refine the corporate strategy, investments, practices and culture to achieve and sustain enduring competitive advantage.

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