Which of the following is true of interfirm collaborative research and development networks?

Mobilising knowledge assets

The primary purpose of business is to make a profit – and stay in business. Unlike the personal sphere, where these malleable technologies can be adapted to a multitude of private uses, Web 2.0 as business tools must offer a more productive, compelling alternative to accomplish a business task than incumbent methods: or they must facilitate the introduction of new value-adding activities and services. Designing products, taking orders, planning maintenance, resolving complaints and filling in holiday applications are repeated processes which contribute to the success of a streamlined, running business. In general, new information tools need to support these kinds of activities.

The fundamental challenge in business is of course to be competitive and to generate returns from the assets of the firm, creating profits for shareholders each quarter. Productivity is the cornerstone of this, the ability to generate optimal returns from all assets at your disposal. Improvements to productivity occur insofar as profit is generated. Many of those generative assets are intangible and reside in the capacity of knowledge workers to generate new products, new services and better ways to manage the value chain from conception to delivery.

Therefore optimising the capacity and the motivation of those knowledge workers becomes a crucial strategic requirement of competing firms. What hinders this? Much of this can be traced back to complexity. Of 7,900 global executives surveyed by McKinsey in 2005:7

64 per cent noted a significant increase in interactions compared to five years ago (e-mail, meetings, voice-mail);

25 per cent stated that communication was unmanageable;

40 per cent stated that their company does not manage information and knowledge well;

35 per cent found it difficult to find knowledge and information to make decisions.

As interaction costs have decreased through digital networks and communications software, great opportunities have been created, but the ensuing complexity has generated problems of a different kind. While reduced interaction costs have meant that global outsourcing and inter-firm collaboration allow it to be cheaper and more effective to move work to other locations and organisations, the volumes of e-mail and mobile phone use have exploded.8 But although useful for specific interactions, these are highly individual, fragmented, non-persistent and unavailable to the enterprise: the only records left are scattered throughout individual memory traces and massive personal e-mail in-boxes.9 This makes it extremely difficult to learn from previous interactions and decisions, and further means that interactions adopt individual options with their own nuances, leading to greater ‘ad-hocery’ and complexity. Managing this has become much more difficult say 60 per cent of the surveyed global executives.

Digital technologies have also increased the volume of what is called ‘virtual work’, which is the distribution of work across barriers of time, space and the firm. This brings many advantages: access to the best resources and talent, use of all 24 hours in a day, close proximity to customers and the ability to ‘punch above your weight’ by finding business partners with key skills that complement yours. Virtual work takes many forms: telework, mobile virtual work, customer frontline work, virtual teaming and the virtual enterprise. But it also involves risks: miscommunication, loss of trust, loss of managerial control over performance and productivity, a longer working day and impaired coordination and cohesion. How is a unified and positive organisational mindset to be maintained in the face of such workforce fragmentation?

The fundamental proposition is therefore that tools are needed for knowledge workers which reduce information complexity, which minimise unproductive e-mail and one-to-one interactions, and which build up corporate knowledge for others to use in the real-time, digital environment of the modern workplace. Where possible, these tools need to maintain a sense of cohesion and work against the risks and disadvantages of isolation and distance. Properly managed, the Web 2.0 tools we saw in the previous chapter such as wikis and blogs are excellent vehicles for the capture of knowledge within the context of workflow rather than as an additional (and therefore ultimately doomed) data entry step in routine business processes. Add to this the classification of that information through the use of an organisational semantic web augmented by social tagging and the issues of information management begin to improve. Corporate social networking tools (exemplified by the functionality of Facebook or MySpace) offer the ability to disclose information about the self and facilitate group relationships, enhance affective relationships and strengthen cohesion. A coherent and consistent ‘single version of the truth’ may begin to emerge, not because of rigid controls by the few, but because of the attention of and contribution by the many.

4.2 Collaboration and Cooperation within and between Organizations

It is commonly assumed that some level of trust must exist so that cooperation between partners can be achieved freely. Yet, trust as a precondition to cooperation can be subjected to different demands of intensity. Requirements for trust in organizations are dependent on the mechanisms that govern the cooperative decisions and the social arrangements in which those decisions are made.

Within interorganizational forms of collaboration, trust is important to the extent that it facilitates information exchange and reciprocity between partners, leading to organizational learning. When interfirm collaborations are forged from common memberships to a professional community, existing ties, or local community partnerships, trust seems to develop more on interpersonal bases and community networks. When alliances are forged mainly from mutual dependencies and/or calculation of resource needs, trust tends to develop from formal bases that can be more costly and time consuming. One way to facilitate collaboration between organizations is to make trust a part of the organizations’ routines and practices so that collaborations between firms can continue successfully. This means that the major source of trust should be institutional. Key individuals or groups (i.e., boundary spanners) do play an important role in interfirm forms of collaboration. However, problems of turnover and the possibility of communication breakdown on the part of these individuals make trust at this level a very fragile form of governance.

Also within organizations, the importance of trust is recognized both at the institutional and interpersonal levels. Trust based on institutional arrangements, such as laws, rules, and professional practices that support the organization as a whole, create a common ground for understanding actions and enhance patterns of behaviors that are extendable to all organizational members. These create a general climate in which trust is produced and generalized to other levels. Although trust is important to the functioning of all forms of the organization, alternative forms have clear trust requirements and managerial philosophies have clear implicit levels of trust. Failures to meet these requirements bring various consequences. For instance, in functional organizational forms, insufficiency of trust reduces efficiency; in divisional forms, it reduces effectiveness and increases costs; in matrix forms, it causes the form to fail; and in networks, it causes organizations to fail. The tendency toward flatter and more team-based forms of organized activity shows that the importance of trust in organizations has been augmented significantly. In the network form, it has become one of the requirements for organizations’ survival.

New policies emphasizing interpersonal and intergroup dynamics in the workplace have accentuated the importance of trust at an interpersonal level. Interpersonal trust is a product of rational decisions and emotional bonds and can be based on different mechanisms, depending on the degree of knowledge or familiarity among the people involved. In situations where individuals have accumulated meaningful knowledge and have established some kind of bond with one another, interpersonal trust tends to be more based on the attributions that individuals make about the other person’s character and the motives and intentions underlying these actions. In situations where individuals have little information about one another or have not yet established any kind of bond with one another, trust may initially develop on the basis of individual dispositions, situational constraints, and/or institutional arrangements.

Geographic Mechanisms of Technological Innovation

Geographers usually explain regional unevenness of technological innovation by invoking a set of localized structural externalities. This tradition goes back to Alfred Marshall who identified three sets of localization economies: (1) economies of specialization due to local access to specialized suppliers, (2) labor market economies due to local access to a pool of specialized workforce, and (3) knowledge spillover due to the advantage of localized informal communications. Economies of specialization and labor market economies are generally referred as pecuniary externalities, and knowledge spillover technological externalities. Pecuniary externalities allow colocated firms to reduce costs and uncertainties through market interactions. Technological externalities, in contrast, materialize through nonmarket interactions within the local community and, in principle, are accessible to all members of the local community.

Theoretically, there is no a priori reason to exclude either pecuniary externalities or technological externalities as drivers of innovation in regional clusters. Empirically, it is difficult to discern direct and indirect contributions to knowledge production. Consequently, some authors maintain that the old-fashioned Marshallian pecuniary economies are still relevant to learning and innovation in the contemporary setting. In the course of time, however, local knowledge spillover (LKS), without explicit consideration of pecuniary externalities, appears to have gained ascendance in academic discourse vis-à-vis Marshallian pecuniary externalities as the principal explainer of regional innovative capacity.

LKSs can be defined as knowledge externalities bounded in space, which allow companies operating nearby important knowledge sources to introduce innovations at a faster rate than rival firms located elsewhere. The ascendance of LKS approach comes from the accredited importance of learning in the knowledge-based economy. Many economic geographers also claim that traded “pecuniary assets” become less important to regional knowledge creation in the globalizing knowledge economy, while “relational assets” or “untraded interdependencies” are seen as increasingly important.

A linkage between learning and geography usually is made through the notion of collective learning: the cumulative creation of common knowledge that takes place among a community of actors in a locality by interactive mechanisms based on shared rules, norms, organizations, and procedures. It is argued that colocation of economic agents provides multiple opportunities to benefit from interfirm linkages, high-density communication, interactive learning, collective problem-solving, and enables firms to develop a shared cognitive frame (codebook) and common understanding. In large enterprises, organizational learning is enabled through the creation of common rules and routines, imposed by hierarchy and control. Within a regional innovation system, the literature suggests that organizational learning is achieved through user–producer relationships, formal and informal collaborations, interfirm mobility of skilled workers, and the spin-off of new firms from existing organizations (firms, universities, and public research centers) through the formation of new enterprises.

In the geographic literature of collective learning, emphasis has been placed on the role of “tacit” as against “codified” knowledge, in that the former is seen as more conducive to rapidly changing markets, and flexibly specialized innovative activity, whereas codified knowledge is equated more with standardized mass production type activity. In a world in which codified knowledge is becoming increasingly ubiquitously available, tacit knowledge attains a higher premium in deriving competitive advantage owing to its uniqueness. Direct, face-to-face interactions enabled by geographic proximity are considered as crucial for the exchange of tacit knowledge.

However, economic geographers emphasize that it is not geography per se that matters for learning and innovation, but it is the embeddedness of firms in localized networks that facilitate the diffusion of knowledge and enhance collective learning in clusters or regional innovation systems. First, knowledge spillovers are considered to occur mainly through direct interactions on the individual level. Second, to enable and foster these interactions, it is argued that the existence of social networks and their perceived stability and reliability are of pivotal importance. In this sense, tacit learning is a form of social learning. It depends not only on spatial proximity, but also on social embeddedness or “social capital,” which is built upon particular relational conditions, common cultural understandings, and shared norms of trust and reciprocity. The origin and sources of such social capital, or regional culture, however, are not yet adequately understood.

Knowledge that spills over through social networks has also been argued as a local public good. As collective learning processes develop, it is suggested that knowledge becomes diffused pervasively in an unstructured manner through the channel of business networks, turning into a public good within the local, or regional, boundaries. In this view, all firms within a region or an industrial district are assumed as relatively homogeneous. Knowledge creation and regional development, however, continues to be very much shaped by decision-making firms as private, profit-seeking agents. Firms in industrial districts or clusters are usually characterized by heterogeneous and asymmetrically distributed knowledge bases and absorptive capacities. Embodied scientific and technical knowledge (individual-tacit) also largely remains a private good, unless sharing agreements turn it into common property or a club good. Meanwhile, social networks are not necessarily fair or democratic; rather they are often characterized by strategic behavior and unequal power status. Moreover, the communication of tacit knowledge can be willfully manipulated to serve as a key exclusionary mean, so that certain actors (even local ones) can be prevented from understanding the content of scientific and technical messages. In light of these, recent literature has come to emphasize that the local diffusion of innovation-related knowledge is selective and uneven, a property that reflects the different internal capabilities and willingness of firms to transfer and absorb knowledge.

Another challenge to the LKS approach is the lack of empirical evidence. The empirical studies so far do not offer any definite answer to the question of “the role of geographical distance in the economics of knowledge transmission.” Networking, which is said to be a central feature of local cluster and new industrial districts, is as much an international phenomenon linking actors in the global economy as it is a characteristic of regional production nodes. Moreover, it has been recognized that tacit knowledge can also be shared within physically dispersed “epistemic communities” as long as the decoding capability of the addressees can be adequately developed.

As a result, economic geographers have increasingly acknowledged the fact that geographic proximity per se is not sufficient to explain processes of localized learning and innovation. The knowledge spillover argument thus has been reformulated. The assumed correlation between learning and geographic proximity is now relaxed, while the association between learning and networking retained. Now it is largely agreed that the creation of new knowledge must be based on the combination of close and distant interactions. The importance of local networks remains emphasized, but nonlocal linkages are considered as vital in order to pump novel ideas and technologies into the local knowledge system to increase its dynamics and to reduce the risk of lock-in. However, when the LKS approach is increasingly questioned, the role of geography becomes blurred and a viable alternative theory is yet to emerge.

Which of the following statements is true of collective research organizations?

Which of the following statements is true of technology diffusion quizlet?

Which of the following is true of technological innovations?

Which of the following is the typical sequence of steps for the science push approach to research and development?