In Chapter 10, we examined the processes necessary to develop new products and services within the existing corporate environment, based on the strategy and capabilities identified in Chapter 4. In this chapter, we explore how firms use external relationships with suppliers, users, and partners to develop new technologies, products, and businesses in the context of open innovation. Specifically, we will discuss the role and management of a range of external actors in the creation and execution of new technologies, products, and businesses, specifically the following:

• Joint ventures and alliances
• Role of supplier innovation
• Forms and patterns of collaboration
• Influence of technology and organization
• Supplier collaboration
• User-led innovation
• Extreme users
• Benefits and limitations of open innovation

11.1 Joint Ventures and Alliances

Almost all innovations demand some form of collaborative arrangement, for development or commercialization, but the failure rate of such alliances remains high. In Chapter 7, we reviewed the central role of innovation networks, and here we examine the more specific issue of bilateral alliances or joint ventures. We discuss the role of collaboration in the development of new technologies, products, and businesses. Specifically, we address the following questions:

• Why do firms collaborate?
• What types of collaboration are most appropriate in different circumstances?
• How do technological and market factors affect the structure of an alliance?
• What organizational and managerial factors affect the success of an alliance?
• How can a firm best exploit alliances for learning new technological and market competencies?

Why Collaborate?

Firms collaborate for a number of reasons:

• To reduce the cost of technological development or market entry
• To reduce the risk of development or market entry
• To achieve scale economies in production
• To reduce the time taken to develop and commercialize new products
• To promote shared learning

In any specific case, a firm is likely to have multiple motives for an alliance. However, for the sake of analysis, it is useful to group the rationale for collaboration into technological, market, and organizational motives, see Figure 11.1. Technological reasons include the cost, time, and complexity of development. In the current, highly competitive business environment, the R&D function, as all other aspects of business, is forced to achieve greater financial efficiency and to critically examine whether in-house development is the most efficient approach. In addition, there is an increasing recognition that one company’s peripheral technologies are usually another’s core activities and that it often makes sense to source such technologies externally, rather than to incur the risks, costs, and most importantly of all, timescale associated with in-house development.

The rate of technological change, together with the increasingly complex nature of many technologies, means that few organizations can now afford to maintain in-house expertise in every potentially relevant technical area. Many products incorporate an increasing range of technologies as they evolve; for example, automobiles now include much computing hardware and software to monitor and control the engine, transmission, brakes, and in some cases, suspension. As a result, most R&D and product managers now recognize that no company, however large, can continue to survive as a technological island. For example, when developing the Jaguar XK, Ford collaborated with Nippondenso in Japan to develop the engine management system and ZF in Germany to develop the transmission system and controls. In addition, there is a greater appreciation of the important role that external technology sources can play in providing a window on emerging or rapidly advancing areas of science. This is particularly true when developments arise from outside a company’s traditional areas of business or from overseas.

Two factors need to be considered when making the decision whether to “make or buy” a technology: the transaction costs and strategic implications [1]. Transaction cost analysis focuses on organizational efficiency, specifically where market transactions involve significant uncertainty. Risk can be estimated and is defined in terms of a probability distribution, whereas uncertainty refers to an unknown outcome. Projects involving technological innovation will feature uncertainties associated with completion, performance, and pre-emption by rivals. Projects involving market entry will feature uncertainties due to lack of geographical or product market knowledge. In such cases, firms are often prepared to trade potentially high financial returns for a reduction in uncertainty.

However, sellers of technological or market know-how may engage in opportunistic behavior, such as high pricing or poor performance. Generally, the fewer potential sources of technology, the lower the bargaining power of the purchaser and the higher the transaction costs. In addition, where the technology is complex, it can be difficult to assess its performance. Therefore, transaction costs are increased where a potential purchaser of technology has little knowledge of the technology. In this respect, the acquisition of technology differs from subcontracting more routine tasks such as production or maintenance work, as it is difficult to specify contractually what must be delivered [2].

As a result, the acquisition of technology tends to require a closer relationship between buyers and sellers than traditional market transactions, resulting in a range of possible acquisition strategies and mechanisms. The optimal technology acquisition strategy in any specific case will depend on the maturity of the technology, the firm’s technological position relative to competitors, and the strategic significance of the technology [3]. Some form of collaboration is normally necessary where the technology is novel, complex, or scarce. Conversely, where the technology is mature, simple, or widely available, market transactions such as subcontracting or licensing are more appropriate. However, the cumulative effect of outsourcing various technologies on the basis of comparative transaction costs may limit future technological options and reduce competitiveness in the long term [4].

In practice, transaction costs are not the most significant factors affecting the decision to acquire external technology. Factors such as competitive advantage, market expansion, and extending product portfolios are more important [5]. Adopting a more strategic perspective focuses attention on long-term organizational effectiveness, rather than short-term efficiency. The early normative strategy literature emphasized the need for technology development to support corporate and business strategies, and therefore, technology acquisition decisions began with an evaluation of company strengths and weaknesses. The more recent resource-based approach emphasizes the process of resource accumulation or learning [6]. Competency development requires a firm to have an explicit policy or intent to use collaboration as an opportunity to learn rather than minimize costs. This suggests that the acquisition of external technology should be used to complement internal R&D, rather than being a substitute for it. In fact, a strategy of technology acquisition is associated with diversification into increasingly complex technologies [7].

Neither transaction costs nor strategic behavior fully explains actual behavior, and to some extent, the approaches are complementary. For example, a survey of top executives found that the two most significant issues considered when evaluating technological collaboration were the strategic importance of the technology and the potential for decreasing development risk [8]. Thus, both strategic and transaction cost factors appear to be significant. Strategic considerations suggest which technologies should be developed internally, and transaction costs influence how the remaining technologies should be acquired. Firms attempt to reduce transaction costs when purchasing external technology by favoring existing trading partners to other sources of technology [9]. In short, for successful technology acquisition, the choice of partner may be as important as the search for the best technology. For both partners, the transaction costs will be lower when dealing with a firm with which they are familiar: they are likely to have some degree of mutual trust, shared technical and business information, and existing personal social links. Research Note 11.1 compares formal and relational governance of innovation partnerships.

There is also a growing realization that exposure to external sources of technology can bring about other important organizational benefits, such as providing an element of “peer review” for the internal R&D function, reducing the “not-invented-here” syndrome, and challenging in-house researchers with new ideas and different perspectives. In addition, many managers realize the tactical value of certain types of externally developed technology. Some of these are increasingly viewed as a means of gaining the goodwill of customers or governments, of providing a united front for the promotion of uniform industry-wide standards, and of influencing future legislation.

A survey carried out by UMIST of more than 100 UK-based alliances confirms the relative importance of market-induced motives for collaboration, as shown in Table 11.1. Specifically, the most common reasons for collaboration for product development are in response to changing customer or market needs. However, these data provide only the motives for collaboration, not the outcomes. The same survey found that although many firms formed alliances to reduce the time, cost, or risk of R&D, they did not necessarily realize these benefits from the relationship. In fact, the study concluded that around half of the respondents believed that collaboration made development more complicated and costly. However, it is important to relate benefits to the objectives of collaboration. For example, firms that formed alliances specifically to reduce the cost or time of development often achieved this, whereas firms that formed alliances for other reasons were more likely to complain that the cost and time of development increased. The study also identified potential risks associated with collaboration:

• Leakage of information
• Loss of control or ownership
• Divergent aims and objectives, resulting in conflict

	Mean Score (n = 106)
In response to key customer needs	4.1
In response to a market need	4.1
In response to technology changes	3.8
To reduce risk of R&D	3.8
To broaden product range	3.7
To reduce R&D costs	3.7
To improve time to market	3.6
In response to competitors	3.5
In response to a management initiative	3.3
To be more innovative in product development	3.3

1 = low, 5 = high.

Around a third of respondents claimed to have experienced such problems. The problem of leakage is the greatest when collaborating with potential competitors, as it is difficult to isolate the joint venture from the rest of the business, and therefore, it is inevitable that partners will gain access to additional knowledge and skills. This additional information may take the form of market intelligence or more tacit skills or knowledge. Consequently, a firm may lose control of the venture, resulting in conflict between partners.

A study of the “make or buy” decisions for sourcing technology in almost 200 firms concluded that product and process technology from external sources often provides immediate advantages, such as lower cost or a shorter time to market, but in the longer term can make it harder for firms to differentiate their offerings and difficult to achieve or maintain any positional advantage in the market [10]. Instead, successful strategies of cost leadership or differentiation (the two polar extremes of Porter’s model, see Chapter 4) are associated with internal development of process and product technologies. However, in highly dynamic environments, characterized by market uncertainty and technological change, sourcing technology externally is a superior strategy to relying entirely on internal capabilities.

For example, high-technology sectors such as information and communications technology and biotechnology are characterized by high levels of collaboration, whereas more mature sectors have lower levels. In the more high-technology sectors, organizations generally seek complementary resources – for example, the many relationships between biotechnology firms (for basic research) and pharmaceutical firms (for clinical trials, production, and marketing and distribution channels). In the pharmaceutical sector, the number of exploration alliances with biotechnology firms is predictive of the number of products in development, which in turn is predictive of the number of exploitation alliances for sales and distribution [11]. In more mature sectors, more often partners’ pool similar resources to share costs or risk or to achieve critical mass or economies of scale. There are also differences in the choice of partner. Firms in higher technology sectors tend to favor horizontal relationships with their peers and competitors, whereas those in more mature sectors more commonly have vertical relations with suppliers and customers [12]. At the firm level, R&D intensity is still associated with the propensity to collaborate, but firms developing products “new to the market” are much more likely to collaborate than those developing products only “new to the firm” [13]. This is because the more novel innovations demand more inputs or novelty of inputs and are associated with greater market uncertainty.

11.2 Forms of Collaboration

Joint ventures, whether formal or informal, typically take the form of an agreement between two or more firms to codevelop a new technology or product. Whereas research consortia tend to focus on more basic research issues, strategic alliances involve near-market development projects. However, unlike more formal joint ventures, a strategic alliance typically has a specific end goal and timetable and does not normally take the form of a separate company. There are two basic types of formal joint venture: a new company formed by two or more separate organizations, which typically allocate ownership based on shares of stock controlled; a simpler contractual basis for collaboration. The critical distinction between the two types of joint venture is that an equity arrangement requires the formation of a separate legal entity. In such cases, management is delegated to the joint venture, which is not the case for other forms of collaboration. Doz and Hamel identify a range of motives for strategic alliances and suggest strategies to exploit each [14]:

• To build critical mass through co-option
• To reach new markets by leveraging cospecialized resources
• To gain new competencies through organizational learning

In a co-option alliance, critical mass is achieved through temporary alliances with competitors, customers, or companies with complementary technology, products, or services. Through co-option, a company seeks to group together other relatively weak companies to challenge a dominant competitor. Co-option is common where scale or network size is important, such as mobile telephony and aerospace (see Case Studies 11.1 and 11.2). For example, Airbus was originally created in response to the dominance of Boeing, and Symbian and Linux in response to Microsoft’s dominance. Greater international reach is a common related motive for co-option alliances. Fujitsu initially used its alliance with ICL to develop a market presence in Europe, as did Honda with Rover. However, co-option alliances may be inherently unstable and transitory. Once the market position has been achieved, one partner may seek to take control through acquisition, as in the case of Fujitsu and ICL, or to go unilateral, as in the case of Honda and Rover [15].

In a co-option alliance, partners are normally drawn from the same industry, whereas in cospecialization, partners are usually from different sectors. In a cospecialized alliance, partners bring together unique competencies to create the opportunity to enter new markets, develop new products, or build new businesses. Such cospecialization is common in systems or complex products and services. However, there is a risk associated with cospecialization. Partners are required to commit to partners’ technology and standards. Where technologies are emerging and uncertain and standards are yet to be established, there is a high risk that a partner’s technology may become redundant. This has a number of implications for cospecialization alliances. First, at the early stages of an emerging market where the dominant technologies are still uncertain, flexible forms of collaboration such as alliances are preferable, and at later stages, when market needs are clearer and the relevant technological configuration better defined, more formal joint ventures become appropriate [16]. Second, restriction of the use of alliances to instances where the technology is tacit, expensive, and time-consuming to develop. If the technology is not tacit, a license is likely to be cheaper and less risky, and if the technology is not expensive or time-consuming to develop, in-house development is preferable [17].

There has been a spectacular growth in strategic alliances, and at the same time, more formal joint ventures have declined as a means of collaboration. In the mid-1980s, less than 1000 new alliances were announced each year, but by the year 2000, this had grown to almost 10,000 per year (based on the data from Thomson Financial). There are a number of reasons for the increase in alliances overall and, more specifically, the switch from formal joint ventures to more transitory alliances [18]:

• Speed: transitory alliances versus careful planning Under turbulent environmental conditions, speed of response, learning, and lead time are more critical than careful planning, selection, and development of partnerships.
• Partner fit: network versus dyadic fit Due to the need for speed, partners are often selected from existing members of a network or, alternatively, reputation in the broader market.
• Partner type: complementarity versus familiarity Transitory alliances increasingly occur across traditional sectors, markets, and technologies, rather than from within. Microsoft and LEGO to develop an Internet-based computer game, Deutsche Bank and Nokia to create mobile financial services.
• Commitment: aligned objectives versus trust The transitory nature of relationships makes the development of commitment and trust more difficult, and alliances rely more on aligned objectives and mutual goals.
• Focus: few, specific tasks versus multiple roles To reduce the complexity of managing the relationships, the scope of the interaction is more narrowly defined and focused more on the task than the relationship.

11.3 Patterns of Collaboration

Research on collaborative activity has been plagued by differences in definition and methodology. Essentially, there have been two approaches to studying collaboration. The approach favored by economists and strategists is based on aggregate data and examines patterns within and across different sectors. This type of research provides useful insights into how technological and market characteristics affect the level, type, and success of collaborative activities. The other type of research is based on structured case studies of specific alliances, usually within a specific sector, but sometimes across national boundaries, and provides richer insights into the problems and management of collaboration.

Industry structure and technological and market characteristics result in different opportunities for joint ventures across sectors, but other factors determine the strategy of specific firms within a given sector. At the industry level, high levels of R&D intensity are associated with high levels of technologically oriented joint ventures, probably as a result of increasing technological rivalry. This suggests that technologically oriented joint ventures are perceived to be a viable strategy in industries characterized by high barriers to entry, rapid market growth, and large expenditures on R&D. However, within a specific sector, joint venture activity is not associated with differences in capital expenditure or R&D intensity. A study of joint ventures in the United States found that technologically oriented alliances tend to increase with the size of firm, capital expenditure, and R&D intensity [19]. Similarly, the number of marketing- and distribution-oriented joint ventures increases with firm size and capital expenditure, but is not affected by R&D intensity. At the level of the firm, different factors are more important. For example, there are significant differences in the motives of small and large firms. In general, large firms use joint ventures to acquire technology, while smaller firms place greater emphasis on the acquisition of market knowledge and financial support.

Joint venture activity is high in the chemical, mechanical, and electrical machinery sectors, as firms seek to acquire external technological know-how in order to reduce the inherent technological uncertainty in those sectors. In contrast, joint ventures are much less common in consumer goods industries, where market position is the result of product differentiation, distribution, and support. If obtaining complementary assets or resources is a primary motive for collaboration, we would expect alliances to be concentrated in those sectors in which mutual ignorance of the partner’s technology or markets is likely to be high [20]. Similarly, joint ventures would occur more frequently between partners who are in the industries relatively unrelated to one another, and such alliances are likely to be short-lived as firms learn from each other. Surveys of alliances in the so-called high-technology sectors such as software and automation appear to confirm that access to technology is the most common motive. Market access appears to be a more common motive for collaboration in the computer, microelectronics, consumer electronics, and telecommunications sectors.

However, these data need to be treated with some caution as in many cases, partners exchange market access for technology access or vice versa. For example, Japanese firms rarely sell technology, but are often prepared to exchange technology for access to markets. Conversely, European firms commonly trade market access for technology [21]. In this way, firms limit the potential for paying high-price premiums for market or technologies because of their lack of knowledge.

A breakdown of alliances by region provides some further explanation. Patterns within and between triad regions are very different. Alliances between US firms appear to be common in all fields. Alliances between European firms are concentrated in software development and telecommunications, but there is relatively little collaborative activity within the European automation, microelectronics, and computing industries. Alliances between Japanese firms appear to be much less common than expected. This may reflect the weakness of the database, but is more likely to reflect the rationale for strategic alliances. The most common reason for international alliances is market access, whereas the most common reason for intraregional alliances is technology acquisition.

The patterns of collaboration between the different triad regions provide some support for this argument. The data provide no indication of the direction of technology transfer, but knowledge of national strengths and weaknesses allows some analysis. Alliances between American and European firms are significant in all fields. Alliances between American and Japanese firms are only significant in computers and microelectronics, presumably the former being dominated by the US partners and the latter by the Japanese. There appears to be relatively little collaboration between Japanese and European companies, perhaps reflecting the weakness of the European electronics industry.

Given the problems of management and organization, potential for opportunistic behavior, and the limited success of alliances, it might be expected that the popularity of alliances might decline as firms gain experience of such problems. However, according to the Cooperative Agreements and Technology Indicators (CATI) database, the number of technology alliances increased from fewer than 300 in 1990 to more than 500 by 2000. It is possible to identify a number of significant trends in recent years, as shown in Figure 11.2.

Overall, the number of alliances has increased over time, and networks of collaboration appear to have become more stable, being based around a number of nodal firms in different sectors. These networks are not necessarily closed, but rather represent the dynamic partnering behavior of large, leading firms in each of the sectors. The nodal firms are relatively stable, but their partners change over time. Contrary to the claims of globalization, the number of domestic alliances has increased faster than international ones. As a result, international partnerships fell from around 80% of all new agreements in 1976 to below 50% by 2000. This trend is particularly strong in the United States. Distinct sectoral patterns exist. In the more high-technology sectors such as pharmaceuticals, biotechnology, and information and communications technologies, most of the collaborative activity is confined within each of the triad regions: Europe, Japan, and North America, the exceptions being aerospace and defense. In contrast, most of the activity in the chemical and automotive sectors is across the triad regions. This suggests that the primary motive for collaborating with domestic firms is access to technology, but market access is more important in the case of cross-border alliances. This concentration of high-technology collaboration within regions appears to be more problematic for some regions than others. For example, a study of European electronics firms found that intra-European R&D agreements had no effect on firm patenting, even when sponsored by the EU. However, R&D collaboration with extra-European firms had a positive effect, which in this case means with US partners [22].

The most recent data from the MERIT-CATI database indicate that flexible forms of collaboration such as strategic alliances have become more popular than the more formal arrangements such as joint ventures. In 1970, more than 90% of the relationships were formal equity joint ventures, but this had fallen to 50% by the mid-1980s and is currently only 10%, the balance being contractual joint ventures and more transitory alliances of some type. This trend has been most marked in high-technology sectors where firms seek to retain the flexibility to switch technology. Together, the pharmaceutical (including biotechnology) and information and communications technology sectors account for almost all 80% of the growth in technology collaboration since the mid-1980s. The other most common sectors are aerospace and instrumentation and medical equipment, but collaboration in the aerospace and defense industries has declined. Collaboration in “mid-technology” sectors such as chemicals, automotive, and electronics has shown little or no increase over the same period.

11.4 Influence of Technology and Organization

Our study of how 23 UK and 15 Japanese firms acquired technology externally identified the conditions under which each particular method is most common [23]. It is possible to identify two dimensions that affect companies’ attitudes toward technology acquisition: the characteristics of the technology and the organization’s “inheritance.” Together, the eight factors shown in Table 11.2 determine the knowledge acquisition strategy of a firm. The relevant characteristics of the technology include the following:

• Competitive significance of the technology
• Complexity of the technology
• Codifiability, or how easily the technology is encoded
• Credibility potential, or political profile of the technology

An organization’s inheritance encompasses those characteristics that, at least in the short run, are fixed and therefore represent constraints within which the R&D function develops its strategies for acquiring technology. These include the following:

• Corporate strategy, for example, a leadership versus follower position
• Capabilities and existing technical know-how
• Culture of the firm, including receptivity to external knowledge
• “Comfort” of management with a given technical area

11.5 Collaborating with Suppliers to Innovate

Alliances can be characterized in a number of different ways. For example, whether they are horizontal or vertical. Horizontal relationships include cross-licensing, consortia, and collaboration with potential competitors of sources of complementary technological or market know-how, as discussed in the previous section. In this section and the next, we review vertical relationships, including subcontracting, and alliances with suppliers and customers. The primary motive of horizontal alliances tends to be access to complementary technological or market know-how, whereas the primary motive for vertical alliances is cost reduction. An alternative way of viewing alliances is in terms of their strategic significance or duration, as shown in Table 11.8. In these terms, contracting and licensing are more tactical, whereas strategic alliances, formal joint ventures, and innovation networks are more strategic and more appropriate structures for learning.

The subcontracting or “outsourcing” of noncore activities has become popular in recent times. Typically, arguments for subcontracting are framed in terms of strategic focus, or “sticking to the knitting,” but in practice, most subcontracting or outsourcing arrangements are based on the potential to save costs: suppliers are likely to have lower overheads and variable costs and may benefit from economies of scale if serving other firms.

Resource dependence and agency theory are more commonly used to explain vertical relationships and are concerned with the need to control key technologies in the value chain. The perceptions of the practices of Japanese manufacturers have led many firms to form closer relationships with suppliers, and indeed, closer links between firms, their suppliers, and customers may help to reduce the cost of components, through specialization and sharing information on costs. However, factors such as the selection of suppliers and users, timing and mode of their involvement, and the novelty and complexity of the system being developed may reduce or negate the benefit of close supplier–user links [45].

The quality of the relationship with suppliers and the timing of their involvement in development are critical factors. Traditionally, such relationships have been short-term, contractual arm’s-length agreements focusing on the issue of the cost, with little supplier input into design or engineering. In contrast, the “Japanese” or “partnership” model is based on long-term relationships, and suppliers make a significant contribution to the development of new products. The latter approach increases the visibility of cost–performance trade-offs, reduces the time to market, and improves the integration of component technologies, as demonstrated by Case Study 11.3. In certain sectors, particularly machine tools and scientific equipment, there is a long tradition of collaboration between manufacturers and lead users in the development of new products. Figure 11.3 presents a range of potential relationships with suppliers. Note that in this diagram, we are not suggesting any trend from left to right, but rather that different types of relationship are appropriate in different circumstances, in essence, an argument for carefully segmenting supply needs and suppliers, instead of the wholesale adoption of simplistic fashions such as “partnerships” or business-to-business (the so-called B2B) supply intranets.

On the vertical axis, we have objectives ranging from cost reduction, quality improvement, lead-time reduction through to product and process innovation. On the horizontal axis, we distinguish between three types of supply market:

• Homogeneous – all potential suppliers have very similar performance
• Differentiated – suppliers differ greatly and one clearly superior
• Indeterminate – suppliers differ greatly under different conditions

In the case of homogeneous supply conditions and a primary objective to reduce costs, we would argue that a traditional market/contractual relationship is the ideal arrangement. In its most recent form, this might be achieved by means of a B2B intranet exchange or club, whereby potential suppliers to a specific customer or sector pool their price and other data or bid for specific contracts. Examples include Covisint in the automobile industry, established by Ford, General Motors, and DaimlerChrysler, and MetalSite formed by a group of the largest steel producers in the United States. Such developments are not confined to manufacturing, and British Airways, American, United, Delta, and Continental have established an electronic procurement hub for routine supplies with an annual turnover of $32 billion. In the United Kingdom, the retailers Kingfisher, Tesco, and Marks & Spencer have joined the Worldwide Retail Exchange (WWRX) in an effort to reduce the cost of purchases by up to 20%. Savings of 5–10% are more typical of such exchanges, but as with other applications of Internet technology, the most significant savings are in transaction costs rather than the goods purchased. Estimates and efficiencies vary, but reports suggest that transactions costs can be just 10% of conventional supply chains. Such developments attempt to exploit buyer power and make supplier prices more transparent. They are the closest thing in the real world to the market of “perfect information” found in economics textbooks. Nonetheless, there are still some concerns that these might evolve into cartels controlled by the existing dominant companies and thereby restrict new entrants and potential competition. However, where the supply market is more differentiated, other types of relationship are likely be more appropriate. In this case, some form of “partnership” or “lean” relationship is often advocated, based on the quality and development of lead-time benefits experienced by Japanese manufacturers of consumer durables, specifically cars and electronics. Lamming identifies several defining characteristics of such partnership or “lean” supply relations [46]:

• Fewer suppliers, longer-term relations
• Greater equity – real “cost transparency”
• Focus on value flows – the relationship, not the contract
• Vendor assessment, plus development
• Two-way or third-party assessment
• Mutual learning – share experience, expertise, knowledge, and investment

These principles are based on a distillation of the features of the best Japanese manufacturers in the automobile and electronics sectors, and more recent experiments in other contexts, such as aerospace in the United Kingdom and United States [47], and as such may represent best practice under certain conditions. Nishiguchi compared supplier relations in Japan and the United Kingdom and found that lean or partnership approaches had significant advantages over market relations, including more supportive customers and less erratic trade [48]. This resulted in measurable differences in operational performance, such as a reduction in inventory held by customers of 90% and tool development time reduction by some 70%. However, trade-offs existed. In the lean relationships, customers were rated by suppliers as being significantly more demanding than in the market relationships and involved a much higher degree of monitoring by customers. Perhaps of greater strategic significance, in the lean relationships, the suppliers’ sales were dominated by a few key customers, and asset specificity, a measure of how much a suppliers’ plant and equipment are dedicated to a particular customer, was much higher.

These two factors make suppliers in lean relations very vulnerable to the fortunes of their key customers. For example, in the United Kingdom, the retail chain Marks & Spencer was often presented as the model of supplier relations, but following its poor market and financial performance in the late 1990s, many of its long-term supply “partners” have been abandoned or ordered to cut costs or be deselected. Nevertheless, “partnership” models have fast become the norm in both the private and public sectors, irrespective of the supply market conditions or objectives of the relationship. For example, one study found that the main explanation for the adoption of lean supply practices was managerial choice, rather than any rationale based on external factors such as industry structure or supply needs [49].

However, in the case of indeterminate supply markets, a partnership or lean supply strategy may be suboptimal or even dysfunctional. We shall revisit the case of Japanese business groups later in this chapter, but in anticipation of that discussion, there is evidence that such rigid supply structures may offer static efficiencies in terms of cost savings, quality improvement, and reduction in development lead time, but may suffer dynamic inefficiencies when it comes to developing novel technologies, products, and processes. On the one hand, the increase in the global sourcing of technology has reduced the chance that an existing “partner” will be the most appropriate supplier, and on the other hand, the tacit nature or “stickiness” of technological knowledge suggests that a market transaction would be inadequate [50]. Therefore, where innovation is the primary objective of the supply relationship, and the supply market is neither homogeneous nor clearly differentiated, a temporary, ad hoc relationship with a supplier may be more appropriate. These have some features common to horizontal strategic alliances, in that they are clearly focused, project-based forms of collaboration. In such cases, the relationship is neither market nor partnership, but a hybrid. Loose coupling is appropriate where multitechnology products are characterized by uneven rates of advance in the underlying technologies, and in such cases, technology consultants or systems integrators act as a buffer between the suppliers and users of the technology [51]. For suppliers, technological competencies and problem-solving capabilities are associated with high gross margins and a larger share of overseas business [52]. A survey of companies offering specialist services to support new product development found that the most common service offered was industrial design (58% of firms), but 30% offered a complete range of services, including R&D, market research, design, development, and implementation of production processes [53]. The United States accounts for almost half of such firms, and within Europe, the United Kingdom accounts for more than half.

Table 11.9 lists some of the management practices found to contribute to a supplier relationship for successful new product development. This list suggests a number of good practices common to partnership or lean approaches, but unbundles these practices from the need for long-term, stable codependent relationships. The low rating given to colocation and shared equipment suggests a more arm’s-length relation, albeit highly integrated for the purposes of the project. Note the relatively high ranking of the need for consensus that the right supplier has been chosen.

11.6 User-led Innovation

Lead users are critical to the development and adoption of complex products. As the title suggests, lead users demand new requirements ahead of the general market of other users, but are also positioned in the market to significantly benefit from the meeting of those requirements [54]. Where potential users have high levels of sophistication, for example, in B2B markets such as scientific instruments, capital equipment, and IT systems, lead users can help to codevelop innovations and are therefore often early adopters of such innovations. The initial research by Von Hippel suggests that lead users adopt an average of seven years before typical users, but the precise lead time will depend on a number of factors, including the technology life cycle. A recent empirical study identified a number of characteristics of lead users [55]:

• Recognize requirements early – are ahead of the market in identifying and planning for new requirements.
• Expect high level of benefits – due to their market position and complementary assets.
• Develop their own innovations and applications – have sufficient sophistication to identify and capabilities to contribute to development of the innovation.
• Perceived to be pioneering and innovative – by themselves and their peer group.

This has two important implications. First, those seeking to develop innovative complex products and services should identify potential lead users with such characteristics to contribute to the codevelopment and early adoption of the innovation. For example, see Case Study 11.4. Second, lead users, as early adopters, can provide insights into forecasting the diffusion of innovations. For example, a study of 55 development projects in telecommunications computer infrastructure found that the importance of customer inputs increased with technological newness and, moreover, the relationship shifted from customer surveys and focus groups to codevelopment because “conventional marketing techniques proved to be of limited utility, were often ignored, and in hindsight were sometimes strikingly inaccurate” [56].

In addition to the well-established role of lead users, there are a range of different types of users and the methods of engaging these, as shown in Figure 11.4. Research Note 11.2 reviews different types of user innovations.

11.7 Extreme Users

An important variant that picks up on both the lead user and the fringe needs concepts lies in the idea of extreme environments as a source of innovation. The argument here is that the users in the toughest environments may have needs that, by definition, are at the edge – so any innovative solution that meets those needs has possible applications back into the mainstream. An example would be antilock braking systems (ABS), which are now a commonplace feature of cars but which began life as a special add-on for premium high-performance cars. The origins of this innovation came from a more extreme case, though – the need to stop aircraft safely under difficult conditions where traditional braking might lead to skidding or other loss of control. ABS was developed for this extreme environment and then migrated across to the (comparatively) easier world of automobiles.

Looking for extreme environments or users can be a powerful source of stretch in terms of innovation – meeting challenges that can then provide new opportunity space. As Roy Rothwell put it in the title of a famous paper, “tough customers mean good designs” [57]. For example, stealth technology arose out of a very specific and extreme need for creating an invisible airplane – essentially something that did not have a radar signature. It provided a powerful pull for some radical innovation, which challenged fundamental assumptions about aircraft design, materials, power sources, and so on and opened up a wide frontier for changes in aerospace and related fields [58]. The “bottom of the pyramid” concept mentioned earlier also offers some powerful extreme environments in which very different patterns of innovation are emerging. Case Study 11.5 provides examples of such innovations.

As we saw in Chapter 5, there has been significant growth in the use of mobile phone networks as a platform for providing financial services in emerging areas such as Africa, and these offer a powerful laboratory for new concepts, which companies such as Nokia and Vodafone are working closely to explore [59]. The potential exists to use this kind of extreme environment as a laboratory to test and develop concepts for wider application – for example, Citicorp has been experimenting with a design of automatic teller machine (ATM) based on biometrics for use with the illiterate population in rural India. The pilot involves some 50,000 people, but as a spokesman for the company explained, “we see this as having the potential for global application.”

11.8 Benefits and Limits of Open Innovation

We discussed the use of open innovation in Chapter 6 as a way of searching and identifying external sources of innovation. However, open innovation can also be applied to the later stages of the innovation process, including development and commercialization. The open-innovation model emphasizes that firms should acquire valuable resources from external firms and share internal resources for new product/service development, but the question of when and how a firm sources external knowledge and shares internal knowledge is less clear. The concept of open innovation is currently very popular in innovation management research and practice, but can be criticized for being too vague and prescriptive.

The original idea of open innovation was that firms should (also) exploit external sources and resources to innovate, a notion that is difficult to contest [64], but this is not a new idea, simply a repackaging of existing research and practice [65]. However, wider dissemination of the concept shows that it is difficult to research and implement, to the point it has now become “all things to all people,” lacking explanatory or predictive power. There have been numerous studies of open innovation, but still the empirical evidence on the utility of open innovation is limited, and practical prescriptions overly general. Research ranges from individual case studies, which are difficult to generalize, to simple survey-based counts of external sources and partners, which reveal little about the conditions, mechanisms, or limitations of open innovation [66].

The simple dichotomy between open and closed approaches is unhelpful and not realistic, so instead we need to explore the different degrees and types of openness and the extent to which a firm can benefit from external and internal resources and knowledge in the innovation process (Figure 11.5). This provides an opportunity to investigate the use of various collaboration strategies and the types and contexts of sources of innovation, so managing different types and degrees of interfirm relationship with external companies to create value will involve different degrees of openness for innovation [67].

There are many approaches to open innovation, depending on the number and type of sources and partners with which the company collaborates and phases of the innovation process that the company opens to external contributions. Having a totally open strategy for innovation is rarely the best option, rather different degrees and ways of openness can be pursued successfully, including adopting a totally closed approach [68]. For example, some firms will passively respond to external opportunities when these occur, whereas others will proactively seek out such opportunities, a so-called prospector strategy [69].

A number of models are emerging around enabling open innovation – for example, Nambisan and Sawhney identify four [70]. The “orchestra” model is typified by a firm such as Boeing, which has created an active global network around the 787 Dreamliner with suppliers as both partners and investors and moving from “build to print” to “design and build to performance.” In this mode, they retain considerable autonomy around their specialist tasks, while Boeing retains the final integrating and decision-making – analogous to professional musicians in an orchestra working under a conductor.

By contrast, the “creative bazaar” model involves more of a “crowdsourcing” approach in which a major firm goes shopping for innovation inputs – and then integrates and develops them further. Examples here would include aspects of the “Innocentive.com” approach being used by P&G, Eli Lilly, and others, or the Dial Corporation in the United States, which launched a “Partners in innovation” website, where inventors could submit ideas. BMW’s Virtual Innovation Agency operates a similar model.

A third model is what they term “Jam central,” which involves creating a central vision and then mobilizing a wide variety of players to contribute toward reaching it. It is the kind of approach found in many precompetitive alliances and consortia where difficult technological or market challenges are used – such as the 5th Generation Computer project in Japan – to focus efforts of many different organizations. Once the challenges are met, the process shifts to an exploitation mode – for example, in the 5th Generation program, the precompetitive efforts by researchers from all the major electronics and IT firms led to generation of over 1000 patents, which were then shared out among the players and exploited in “traditional” competitive fashion. Philips deploys a similar model via its InnoHub, which selects a team from internal and external businesses and staff and covering technology, marketing, and other elements. They deliberately encourage fusion of people with varied expertise in the hope that this will enhance the chances of “breakthrough” thinking.

Their fourth model is called “Mod Station,” drawing on a term from the personal computer industry, which allows users to make modifications to games and other software and hardware. This is typified by many open-source projects such as Sun Microsystems’s OpenSPARC, Google’s Android developer platform (and before that Nokia’s release of the Symbian operating system), which open up to the developer community in an attempt to establish an open platform for creating mobile applications. It reflects models used by the BBC, Lego, and many other organizations trying to mobilize external communities and amplify their own research efforts while retaining an ability to exploit the new and growing space.

Other models that might be added include NASA’s “infusion” approach in which a major public agency uses its Innovative Partnerships Programme (IPP) to codevelop key technologies such as robotics. The model is essentially one of drawing in partners who work alongside NASA scientists – a process of “infusion” in which ideas developed by NASA or by one or more of the partners are worked on. There is particular emphasis on spreading the net widely and seeking partnerships with “unusual suspects” – companies, university departments, and others, which might not immediately recognize that they have something of value to offer [71].

All of these models of open innovation feature different roles of, and interactions with, users. In all cases, internal and external sources of innovation combine in different ways and are complementary rather than simple alternatives. Research Note 11.4 explores this interaction in more detail.

Table 11.10 identifies the potential benefits of applying open innovation and the key management challenges this presents. In each case, four fundamental factors will influence the best approach to exploit open innovation in practice:

• Conditions and context, for example, environmental uncertainty and project complexity [72]
• Control and ownership of resources [73]
• Coordination of knowledge flows [74]
• Creation and capture of value [75]

Summary

In this chapter, we have explored the rationale, characteristics, and management of external relationships to develop and exploit innovation, ranging from joint ventures and alliances, supplier and user-led innovation, to more fully open-innovation strategies and practices.

Essentially, firms collaborate to reduce the cost, time, or risk of access to unfamiliar technologies or markets. The precise form of collaboration will be determined by the motives and preferences of the partners, but their choice will be constrained by the nature of the technologies and markets, specifically the degree of complexity and tacitness. The success of an alliance depends on a number of factors, but organizational issues dominate, such as the degree of mutual trust and level of communication. The transaction costs approach better explains the relationship between the reason for collaboration and the preferred form and structure of an alliance. The strategic learning approach better explains the relationship between the management and organization of an alliance and the subsequent outcomes.

1. Organizations collaborate for many reasons, to reduce the cost, time, or risk of access to unfamiliar technologies or markets.
2. The precise form of collaboration will be determined by the motives and preferences of the partners, but their choice will be constrained by the nature of the technologies and markets, specifically the degree of knowledge complexity and tacitness.
3. The success of an alliance depends on several factors, but organizational issues dominate, such as the degree of mutual trust and level of communication.
4. Open innovation is a very broad and therefore popular concept, but needs to be applied with care as its relevance is sensitive to the context. The appropriate choice of partner and specific mechanisms will depend on the type of innovation project and environmental uncertainty.
5. User innovation is a special case of open innovation. It is much more than simply good market research or listening to customers. Users can contribute to all phases of the innovation process, acting as sources, designers, developers, testers, and even the main beneficiaries of innovation.
6. In most cases, open-innovation and internal-innovation capabilities are complementary, rather than substitutes.

Further Reading

The literature on innovation collaboration and networks is large, fragmented, and still growing, but the following provide a good introduction: Innovation, alliances, and networks in high-tech environments, edited by Fiorenza Belussi and Luigi Orsi (Routledge, 2015); O. Jones, S. Conway, and F. Steward, Social interaction and organizational change: Aston perspectives on innovation networks (Imperial College Press, London, 2001); International Journal of Innovation Management, Special Issue on Networks, 2(2) (1998); R. Gulati, “Alliances and networks,” Strategic Management Journal, 19, 293–317 (1998); and F. Belussi and F. Arcangeli, “A typology of networks,” Research Policy, 27, 415–28 (1998). For a less academic treatment of alliances, Bleeke and Ernst provide a practical guide, albeit a little dated, for managers of collaborative projects in Collaborating to compete (John Wiley & Sons, Inc., 1993), written by two management consultants at McKinsey & Co., and based on a survey of international alliances and acquisitions. In Alliance advantage (Harvard Business School Press, 1998), Yves Doz and Gary Hamel develop a framework to help understand and better manage alliances, drawing on their earlier work on learning through alliances.

On the more specific subject of customer–supplier alliances, Jordan Lewis provides a practical guide based on studies of a number of American and British present and past exemplars such as Motorola and Marks & Spencer in The connected corporation (Free Press, 1995). More academic and rigorous treatments of customer–supplier alliances are provided by Alex Brem and Joe Tidd in Perspectives on supplier innovation (Imperial College Press, 2012), Richard Lamming’s Beyond partnership (Prentice-Hall, 1993), and Toshihiro Nishiguchi in Strategic industrial sourcing: The Japanese advantage (Oxford University Press, 1994), the latter two based mainly on the experience of the automobile industry. For user innovation, the classic text is Eric von Hippel’s The sources of innovation (Oxford University Press, 1995), but for more recent and broader reviews, see Steve Flowers and Flis Henwood’s Perspectives on user innovation (Imperial College Press, 2010) and the special issue on user innovation. International Journal of Innovation Management, 12(3), 2008.

The open-innovation movement includes a lot of relevant work on collaboration and networks, and Henry Chesbrough, Wim Vanhaverbeke, and Joel West have edited a good overview of the main research themes in Open innovation: Researching a new paradigm (Oxford University Press, 2008). Recently, there has been a lot of work on open innovation, much of it not very original or insightful, but a good place to start is three journal special issues: Research Policy, 2014, 43(5); R&D Management, 2010, 40(3); and Technovation, 2011, 31(1). For more critical accounts of open innovation, see Joe Tidd’s Open innovation management, research and practice (Imperial College Press, 2014); Paul Trott and Hartmann, D. (2009) Why open innovation is old wine in new bottles, International Journal of Innovation Management 13(4), 715–36; and Mowery, D.C. (2009) Plus ca change: Industrial R&D in the third industrial revolution, Industrial and Corporate Change, 18(1), 1–50. For a review of crowdsourcing, see Alex Brem, Joe Tidd and Tugrul Daim (2018) Managing Innovation – Understanding and Motivating Crowds. World Scientific, London.

Case Studies

Additional case studies are available on the companion website, including the following:

• Adidas describing some of its work in user innovation
• The Lego identifying ways in which it engages with users as codesigners

References

1. 1. Denicolai, S., M. Ramirez, and J. Tidd, Creating and capturing value from external knowledge: The moderating role of knowledge intensity. R&D Management, 2014. 44(3), 248–264; McGee, J. and M. Dowling, Using R&D cooperative arrangements to leverage managerial experience. Journal of Business Venturing, 1994. 9, 33–48.
2. 2. Schweitzer, J., How contracts and culture mediate joint transactions of innovation partnerships. International Journal of Innovation Management, 2016. 20(1), 1650005; Hauschildt, J., External acquisition of knowledge for innovations – A research agenda. R&D Management, 1992. 22(2), 105–10; Brusconi, S., A. Prencipe, and K. Pavitt, Knowledge specialization and the boundaries of the firm. Administrative Science Quarterly, 2002. 46(4), 597–621.
3. 3. Welch, J. and P. Nayak, Strategic sourcing: A progressive approach to the make or buy decision. Academy of Management Executive, 1992. 6(1), 23–31.
4. 4. Bettis, R., S. Bradley, and G. Hamel, Outsourcing and industrial decline. Academy of Management Executive, 1992. 6(1), 7–21.
5. 5. Henttonen, K., P. Hurmelinna-Laukkanen, and P. Ritala, Managing the appropriability of R&D collaboration, R&D Management, 2016. 46(1), 145–158; Atuaheme-Gima, K. and P. Patterson, Managerial perceptions of technology licensing as an alternative to internal R&D in new product development: An empirical investigation. R&D Management, 1993. 23(4), 327–36; Chiesa, V., R. Manzini, and E. Pizzurno, The externalization of R&D activities and the growing market of product development services. R&D Management, 2004. 34, 65–75.
6. 6. Robins, J. and M. Wiersema, A resource-based approach to the multi-business firm. Strategic Management Journal, 1995. 16(4), 277–300.
7. 7. Granstrand, O., et al., External technology acquisition in large multi-technology corporations. R&D Management, 1992. 22(2), 111–33.
8. 8. Tyler, B. and H. Steensma, Evaluating technological collaborative opportunities: A cognitive modeling perspective. Strategic Management Journal, 1995. 16, 43–70.
9. 9. Bidault, F. and T. Cummings, Innovating through alliances: Expectations and limitations. R&D Management, 1994. 24(2), 33–45.
10. 10. Scott Swan, K. and B. Allred, A product and process model of the technology-sourcing decision. Journal of Product Innovation Management, 2003. 20, 485–96.
11. 11. Rothaermel, F. and D. Deeds, Exploration and exploitation alliances in biotechnology: A system of new product development. Strategic Management Journal, 2004. 25, 201–21.
12. 12. Miotti, L. and F. Sachwald, Cooperative R&D: why and with whom? An integrated framework of analysis. Research Policy, 2003. 32, 1481–99.
13. 13. Teher, B., Who cooperates for innovation, and why? An empirical analysis. Research Policy, 2002. 31, 947–67.
14. 14. Doz, Y. and G. Hamel, Alliance advantage: The art of creating value through partnering. 1998, Harvard Business School Press, Boston, MA.
15. 15. Carr, C., Globalisation, strategic alliances, acquisitions and technology transfer: Lessons from ICL/Fujitsu and Rover/Honda and BMW. R&D Management, 1999. 29(4), 405–21.
16. 16. Mauri, A. and G. McMillan, The influence of technology on strategic alliances. International Journal of Innovation Management, 1999. 3(4), 367–78.
17. 17. Añón Higón, D., In-house versus external basic research and first-to-market innovations, Research Policy, 2016. 45(4), 816–829; Jay Lambe, C. and R. Spekman, Alliances, external technology acquisition, and discontinuous technological change. Journal of Product Innovation Management, 1997. 14, 102–16.
18. 18. Duysters, G. and A. de Man, Transitionary alliances: An instrument for surviving turbulent industries? R&D Management, 2003. 33, 49–58.
19. 19. Berg, S., J. Duncan, and P. Friedman, Joint venture strategies and corporate innovation. 1982, Gunn & Ham, Cambridge, MA.
20. 20. Balakrishnan, S. and M. Koza, “An information theory of joint ventures.” In L. Gomez-Mejia and M. Lawless, eds, Advances in global high technology management: Strategic alliances in high technology. 1995, JAI Press, Greenwich, CN, Vol. 5, Part B, pp. 59–72.
21. 21. Krubasik, E. and H. Lautenschlager, “Forming successful strategic alliances in high-tech businesses.” In J. Bleeke and D. Ernst, eds, Collaborating to compete. 1993, John Wiley & Sons, Inc., New York, pp. 55–65.
22. 22. Duysters, G., G. Kok, and M. Vaandrager, Crafting successful strategic technology partnerships. R&D Management, 1999. 29(4), 343–51; Hagedoorn, J., Inter-firm R&D partnerships: An overview of major trends and patterns since 1960. Research Policy, 2002. 31, 477–92; Giarrantana, M. and S. Torrisi, “Competence accumulation and collaborative ventures: Evidence from the largest European electronics firms and implications for EU technological policies.” In S. Lundan, ed., Network knowledge in international business. 2002, Edward Elgar, Cheltenham, pp. 196–215.
23. 23. Tidd, J. and M. Trewhella, Organizational and technological antecedents for knowledge acquisition and learning. R&D Management, 1997. 27(4), 359–75.
24. 24. Rothaermel, F., Complementary assets, strategic alliances, and the incumbent’s advantage: An empirical study of industry and firms effects in the biopharmaceutical industry. Research Policy, 2001. 30, 1235–51.
25. 25. Orsenigo, L., F. Pammolli, and M. Riccaboni, Technological change and network dynamics: Lessons from the pharmaceutical industry. Research Policy, 2001. 30, 485–508.
26. 26. Nicholls-Nixon, C. and C. Woo, Technology sourcing and the output of established firms in a regime of encompassing technological change. Strategic Management Journal, 2003. 24, 651–66.
27. 27. Harrigan, K., Managing for joint venture success. 1986, Lexington Books, Lexington, MA.
28. 28. Dacin, M., M. Hitt, and E. Levitas, Selecting partners for successful international alliances. Journal of World Business, 1997. 32(1), 321–45.
29. 29. Spekmen, R., et al., Creating strategic alliances which endure. Long Range Planning, 1996. 29(3), 122–47.
30. 30. Bleeke, J. and D. Ernst, Collaborating to compete. 1993, John Wiley & Sons, Inc., New York.
31. 31. Tidd, J. and Y. Izumimoto, Knowledge exchange and learning through international joint ventures: An Anglo-Japanese experience. Technovation, 2001. 21(2).
32. 32. Brockhoff, K. and T. Teichert, Cooperative R&D partners’ measures of success. International Journal of Technology Management, 1995, 10(1), 111–23.
33. 33. Bruce, M., F. Leverick, and D. Littler, Complexities of collaborative product development. Technovation, 1995. 15(9), 535–52.
34. 34. Kelly, M., J. Schaan, and H. Joncas, Managing alliance relationships: Key challenges in the early stages of collaboration. R&D Management, 2002. 32(1), 11–22.
35. 35. Schweitzer, J., How contracts and culture mediate joint transactions of innovation partnerships. International Journal of Innovation Management, 2016. 20(1), 1650005; Hoecht, A. and P. Trott, Trust, risk and control in the management of collaborative technology development. International Journal of Innovation Management, 1999. 3(3), 257–70.
36. 36. Denicolai, S., M. Ramirez, and J. Tidd, Overcoming the false dichotomy between internal R&D and external knowledge acquisition: Absorptive capacity dynamics over time, Technological Forecasting and Social Change, 2016. 104, 57–65; Lane, P. and M. Lubatkin, Relative absorptive capacity and inter-organizational learning. Strategic Management Journal, 1998. 19, 461–77.
37. 37. Nonaka, I. and H. Takeuchi, The knowledge-creating company. 1995, Oxford University Press, Oxford.
38. 38. Johnson, W., Assessing organizational knowledge creation theory in collaborative R&D projects. International Journal of Innovation Management, 2002. 6(4), 387–418.
39. 39. Levinson, N. and M. Asahi, Cross-national alliances and inter-organizational learning. Organizational Dynamics, 1995. Autumn, 50–63.
40. 40. Hamel, G., Competition for competence and inter-partner learning within international strategic alliances. Strategic Management Journal, 1991. 12, 83–103.
41. 41. Jones, K. and W. Shill, “Japan: Allying for advantage.” In J. Bleeke and D. Ernst, eds, Collaborating to compete. 1993, John Wiley & Sons, Inc., New York, pp. 115–44; Sasaki, T., What the Japanese have learned from strategic alliances. Long Range Planning, 1993. 26(6), 41–53.
42. 42. Biemans, W., “Internal and external networks in product development.” In M. Bruce and W. Biemans, eds, Product development: Meeting the challenge of the design–marketing interface. 1995, John Wiley & Sons, Ltd, Chichester, pp. 137–59.
43. 43. Schrader, S., “Informal alliances: Information trading between firms.” In L. Gomez-Mejia and M. Lawless, eds, Advances in global high-technology management: Strategic alliances in high technology. 1995, JAI Press, Greenwich, CN, Vol. 5, Part B, pp. 31–55.
44. 44. Spencer, J., Firms’ knowledge-sharing strategies in the global innovation system: Evidence from the flat panel display industry. Strategic Management Journal, 2003. 24, 217–33.
45. 45. Leonard-Barton, D. and D. Sinha, Developer–user interaction and user satisfaction in internal technology transfer. Academy of Management Journal, 1993. 36(5), 1125–1139.
46. 46. Lamming, R., “Assessing supplier performance,” in Tidd, J. (ed.), From knowledge management to strategic competence. 2006, Imperial College Press, London, pp. 229–253.
47. 47. Bozdogan, K., et al., Architectural innovation in product development through early supplier integration. R&D Management, 1998. 28(3), 163–173.
48. 48. Nishiguchi, T., Strategic industrial sourcing: The Japanese advantage. 1994, Oxford University Press, Oxford.
49. 49. Bidault, F., C. Despres, and C. Butler, The drivers of cooperation between buyers and suppliers for product innovation, Research Policy, 1998. 26, 719–732; Ragatz, G.L., R.B. Handfield, and T.V. Scannell, Success factors for integrating suppliers into new product development. Journal of Product Innovation Management, 1997. 14, 190–202.
50. 50. Andersen, P.H., Organizing international technological collaboration in subcontractor relationships, Research Policy, 1999. 28, 625–642.
51. 51. Brusconi, S., A. Prencipe, and K. Pavitt, Knowledge specialization, organizational coupling, and the boundaries of the firm: Why do firms know more than they make?, Administrative Science Quarterly, 2001. 46(4), 597–621.
52. 52. Kaufman, A., C.H. Wood, and G. Theyel, Collaboration and technology linkages: A strategic supplier typology. Strategic Management Journal, 2000. 21, 649–663.
53. 53. Chiesa, V., R. Manzini, and E. Pizzurno, The externalization of R&D activities and the growing market of product development services, R&D Management, 2004. 34, 65–75.
54. 54. Von Hippel, E., Lead users: A source of novel product concepts. Management Science, 1986. 32(7), 791–805; The sources of innovation. 1988, Oxford University Press, Oxford.
55. 55. Morrison, P., J. Roberts, and D. Midgley, The nature of lead users and measurement of leading edge status. Research Policy, 2004. 33, 351–62.
56. 56. Callahan, J. and E. Lasry, The importance of customer input in the development of very new products. R&D Management, 2004. 34(2), 107–17.
57. 57. Rothwell, R. and P. Gardiner, Tough customers, good design. Design Studies, 1983. 4(3), 161–169.
58. 58. Rich, B. and L. Janos, Skunk works. 1994, London: Warner Books.
59. 59. Corbett, S., Can the cellphone help end global poverty? 2008, The New York Times, New York.
60. 60. Gamble, J.R., M. Brennan, and R. McAdam, A contemporary and systematic literature review of user-centric innovation: A consumer perspective. International Journal of Innovation Management, 2016. 20(1), 1650011; Flowers, S. and F. Henwood, Perspectives on user innovation, 2010, Imperial College Press; Special issue on user innovation. International Journal of Innovation Management, 2008, 12(3).
61. 61. Kosonen, M., et al., User motivation and knowledge sharing in idea crowdsourcing. International Journal of Innovation Management, 2014. 18(5), 1450031; Afuah, A. and Tucci, C.L., Crowdsourcing as a solution to distant search, Academy of Management Review, 2012. 37(3), 355–375.
62. 62. Von Hippel, E., The democratization of innovation. 2005, Cambridge, Mass.: MIT Press.
63. 63. Moser, K. and F. Piller, Special issue on mass customisation case studies: Cases from the International Mass Customisation Case Collection. International Journal of Mass Customisation, 2006. 1(4).
64. 64. Proponents of open innovation include: Chesbrough, H.W., Open innovation: The new imperative for creating and profiting from technology. 2003, Boston, MA: Harvard Business School Publishing; Chesbrough, H.W. and A.K. Crowther, Beyond high tech: Early adopters of open innovation in other industries. R&D Management, 2006. 36(3), 229–236; Chesbrough, H.W., W. Vanhaverbeke, and J. West, Open innovation: Researching a new paradigm. 2006, Oxford: Oxford University Press; Gassmann, O., E. Enkel, and H. Chesbrough, The future of open innovation. R&D Management, 2010. 40, 213–221; Enkel, E., O. Gassmann, and H. Chesbrough, Open innovation: Exploring the phenomenon. R&D Management, 2009. 39(4): 311–16.
65. 65. Good critiques of open innovation from: Trott, P. and D. Hartmann, Why open innovation is old wine in new bottles. International Journal of Innovation Management, 2009. 13(4): 715–36; Mowery, D.C., Plus ca change: Industrial R&D in the third industrial revolution. Industrial and Corporate Change, 2009. 18(1): 1–50; Groen, A.J. and J.D. Linton, Is open innovation a field of study or a communication barrier to theory development? Technovation, 2010. 30, 554; Knudsen, M.P. and T.B. Mortensen, Some immediate – but negative – effects of openness on product development performance. Technovation, 2011. 31(1), 54–64.
66. 66. Examples of the numerous simple survey-based counts, many based on the EU Community Innovation Survey (CIS), include: Laursen, K. and A. Salter, Open for innovation: The role of openness in explaining innovation performance among UK manufacturing firms. Strategic Management Journal. 2006, 27(2): 131–50; Poot, T., D. Faems, and W. Vanhaverbeke. Toward a dynamic perspective on open innovation: A longitudinal assessment of the adoption of internal and external innovation strategies in the Netherlands. International Journal of Innovation Management, 2009. 13(2): 177–200; Mention, A-L., Co-operation and co-opetition as open innovation practices in the service sector: Which influence on innovation novelty? Technovation, 2011. 31(1), 44–53.
67. 67. Lazzarotti, V. and R. Manzini, Different modes of open innovation: A theoretical framework and an empirical study. International Journal of Innovation Management, 2009. 13, 615–636; Lichtenthaler, U., Open innovation in practice: An analysis of strategic approaches to technology transactions. IEEE Transactions of Engineering Management, 2008. 55, 148–157.
68. 68. Lazzarotti, V. and R. Manzini, Different modes of open innovation: A theoretical framework and an empirical study. International Journal of Innovation Management, 2009. 13, 615–636; Lichtenthaler, U. Open innovation in practice: An analysis of strategic approaches to technology transactions. IEEE Transactions of Engineering Management, 2008. 55, 148–157.
69. 69. Enkel, E. and K. Bader, “How to balance open and closed innovation: Strategy and culture as influencing factors,” in Tidd, J., Open innovation research, management and practice. 2014, Imperial College Press, London.
70. 70. Nambisan, S. and M. Sawhney, The global brain: Your roadmap for innovating smarter and faster in a networked world. 2007, Philadelphia Wharton School Publishing.
71. 71. Cheeks, N., How NASA uses “infusion partnerships,” in PDMA Visions. 2007, Product Development Management Association: Mount Laurel, N.J. pp. 9–12.
72. 72. Añón Higón, D., In-house versus external basic research and first-to-market innovations. Research Policy, 2016. 45(4), 816–829; Bahemia, H, B. Squire, A contingent perspective of open innovation in new product development projects. International Journal of Innovation Management, 2010. 14(4), 603–627; Huizingh, E.K.R.E., Open innovation: State of the art and future perspectives. Technovation, 2011. 13(1), 2–9; Schweitzer, F.M., O. Gassmann, and K. Gaubinger, Open innovation and its ability to embrace turbulent environments. International Journal of Innovation Management, 2011. 15(6), 1191–1208.
73. 73. Denicolai, S., M. Ramirez, and J. Tidd, Overcoming the false dichotomy between internal R&D and external knowledge acquisition: Absorptive capacity dynamics over time. Technological Forecasting and Social Change, 2016. 104, 57–65; Remneland-Wilkhamn, B., et al., Open innovation, generativity and the supplier as peer. International Journal of Innovation Management, 2011. 15(1), 205–230; Klioutch, I. and J. Leker, Supplier involvement in customer new product development: New insights from the supplier’s perspective. International Journal of Innovation Management, 2011. 15(1), 231–248.
74. 74. Colombo, G., C. Dell’era, and F. Frattini, New product development service suppliers in open innovation practices: Processes and organization for knowledge exchange and integration. International Journal of Innovation Management, 2011. 15(1), 165–204; Fredberg, T., M. Elmquist, and S. Ollila, Managing open innovation-present findings and future directions. VINNOVA Report. VINNOVA – Verket för Innovationssystem/Swedish Governmental Agency for Innovation Systems, 2008, Stockholm, Sweden. http://www.openinnovation.eu/download/vr-08-02.pdf.
75. 75. Hopkins, M.M., et al., Generative and degenerative interactions: Positive and negative dynamics of open, user-centric innovation in technology and engineering consultancies. R&D Management, 2011. 41(1), 44–60; Remneland-Wilkhamn, B., et al., Open innovation, generativity and the supplier as peer. International Journal of Innovation Management, 2011. 15(1), 205–230.