The future of open innovation

Institutional openness is becoming increasingly popular in practice and academia: open innovation, open R&D and open business models. Our special issue builds on the concepts,underlying assumptions and implications discussed in two previous R&D Management special issues (2006, 2009). This overview indicates nine perspectives needed to develop an open innovation theory more fully. It also assesses some of the recent evidence that has come to lighta bout open innovation, in theory and in practice

Oliver Gassmann, Ellen Enkel and Henry Chesbrough

An overview of innovation

Models that depict innovation as a smooth, well-behaved linear process badly misspecify the nature and direction of the causal factors at work. Innovation is complex, uncertain, somewhat disorderly, and subject to changes of many sorts. Innovation is also difficult to measure and demands close coordination of adequate technical knowledge and excellent market judgment in order to satisfy economic, technological, and other types of constraints-all simultaneously. The process of innovation must be viewed as a series of changes in a complete system not only of hardware, but also of market environment, production facilities and knowledge, and the social contexts of the innovation organization.

Stephen J. Kline and Nathan Rosenberg

Technology push and demand pull perspectives in innovation studies: Current findings and future research directions

This study updates the debate on the sources of innovation. Using techniques like factor analysis, multidimensional scaling, and pathfinder analysis, we examine the most influential articles that have dealt with the topic. In addition to confirming the role of technology and demand as sources of innovation, our analysis provides two main findings. The first illustrates how competences enable firms to match technology with demand and capitalize on technology and demand as sources of innovation. The second highlights a distinction between external and internal sources of innovations. The sources of innovation can be purely external or internally generated competences that enable the firm to integrate external knowledge within its boundaries. Our work contributes to the classic debate by providing a more granular understanding of how technology and demand interact. In discussing our findings, we link our framework to strategy, innovation and entrepreneurship studies that expressly call for a better understanding of technology and demand factors in value creation and capture.

Giada Di Stefano, Alfonso Gambardella, Gianmario Verona

Emergence of integrated institutions in a large population of self-governing communities

Most aspects of our lives are governed by large, highly developed institutions that integrate several governance tasks under one authority structure. But theorists differ as to the mechanisms that drive the development of such concentrated governance systems from rudimentary beginnings. Is the emergence of integrated governance schemes a symptom of consolidation of authority by small status groups? Or does integration occur because a complex institution has more potential responses to a complex environment? Here we examine the emergence of complex governance regimes in 5,000 sovereign, resource-constrained, self-governing online communities, ranging in scale from one to thousands of users. Each community begins with no community members and no governance infrastructure. As communities grow, they are subject to selection pressures that keep better managed servers better populated. We identify predictors of community success and test the hypothesis that governance complexity can enhance community fitness. We find that what predicts success depends on size: changes in complexity predict increased success with larger population servers. Specifically, governance rules in a large successful community are more numerous and broader in scope. They also tend to rely more on rules that concentrate power in administrators, and on rules that manage bad behavior and limited server resources. Overall, this work is consistent with theories that formal integrated governance systems emerge to organize collective responses to interdependent resource management problems, especially as factors such as population size exacerbate those problems.

Emergence of integrated institutions in a large population of self-governing communities

Emergence of integrated institutions in a large population of self-governing communities

Most aspects of our lives are governed by large, highly developed institutions that integrate several governance tasks under one authority structure. But theorists differ as to the mechanisms that drive the development of such concentrated governance systems from rudimentary beginnings. Is the emergence of integrated governance schemes a symptom of consolidation of authority by small status groups? Or does integration occur because a complex institution has more potential responses to a complex environment? Here we examine the emergence of complex governance regimes in 5,000 sovereign, resource-constrained, self-governing online communities, ranging in scale from one to thousands of users. Each community begins with no community members and no governance infrastructure. As communities grow, they are subject to selection pressures that keep better managed servers better populated. We identify predictors of community success and test the hypothesis that governance complexity can enhance community fitness. We find that what predicts success depends on size: changes in complexity predict increased success with larger population servers. Specifically, governance rules in a large successful community are more numerous and broader in scope. They also tend to rely more on rules that concentrate power in administrators, and on rules that manage bad behavior and limited server resources. Overall, this work is consistent with theories that formal integrated governance systems emerge to organize collective responses to interdependent resource management problems, especially as factors such as population size exacerbate those problems.

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0216335

Knowledge society

Peter Drucker has argued that there is a transition from an economy based on material goods to one based on knowledge. Marc Porat distinguishes a primary (information goods and services that are directly used in the production, distribution or processing of information) and a secondary sector (information services produced for internal consumption by government and non-information firms) of the information economy.

Porat uses the total value added by the primary and secondary information sector to the GNP as an indicator for the information economy. The OECD has employed Porat’s definition for calculating the share of the information economy in the total economy (e.g. OECD 1981, 1986). Based on such indicators, the information society has been defined as a society where more than half of the GNP is produced and more than half of the employees are active in the information economy.

For Daniel Bell the number of employees producing services and information is an indicator for the informational character of a society. “A post-industrial society is based on services. (…) What counts is not raw muscle power, or energy, but information. (…) A post industrial society is one in which the majority of those employed are not involved in the production of tangible goods”.

Alain Touraine already spoke in 1971 of the post-industrial society. “The passage to postindustrial society takes place when investment results in the production of symbolic goods that modify values, needs, representations, far more than in the production of material goods or even of ‘services’. Industrial society had transformed the means of production: post-industrial society changes the ends of production, that is, culture. (…) The decisive point here is that in postindustrial society all of the economic system is the object of intervention of society upon itself. That is why we can call it the programmed society, because this phrase captures its capacity to create models of management, production, organization, distribution, and consumption, so that such a society appears, at all its functional levels, as the product of an action exercised by the society itself, and not as the outcome of natural laws or cultural specificities” (Touraine 1988: 104). In the programmed society also the area of cultural reproduction including aspects such as information, consumption, health, research, education would be industrialized. That modern society is increasing its capacity to act upon itself means for Touraine that society is reinvesting ever larger parts of production and so produces and transforms itself. This makes Touraine’s concept substantially different from that of Daniel Bell who focused on the capacity to process and generate information for efficient society functioning.

Jean-François Lyotard has argued that “knowledge has become the principle [sic] force of production over the last few decades”. Knowledge would be transformed into a commodity. Lyotard says that postindustrial society makes knowledge accessible to the layman because knowledge and information technologies would diffuse into society and break up Grand Narratives of centralized structures and groups. Lyotard denotes these changing circumstances as postmodern condition or postmodern society.

Similarly to Bell, Peter Otto and Philipp Sonntag (1985) say that an information society is a society where the majority of employees work in information jobs, i.e. they have to deal more with information, signals, symbols, and images than with energy and matter. Radovan Richta (1977) argues that society has been transformed into a scientific civilization based on services, education, and creative activities. This transformation would be the result of a scientific-technological transformation based on technological progress and the increasing importance of computer technology. Science and technology would become immediate forces of production (Aristovnik 2014: 55).

Nico Stehr (1994, 2002a, b) says that in the knowledge society a majority of jobs involves working with knowledge. “Contemporary society may be described as a knowledge society based on the extensive penetration of all its spheres of life and institutions by scientific and technological knowledge” (Stehr 2002b: 18). For Stehr, knowledge is a capacity for social action. Science would become an immediate productive force, knowledge would no longer be primarily embodied in machines, but already appropriated nature that represents knowledge would be rearranged according to certain designs and programs (Ibid.: 41-46). For Stehr, the economy of a knowledge society is largely driven not by material inputs, but by symbolic or knowledge-based inputs (Ibid.: 67), there would be a large number of professions that involve working with knowledge, and a declining number of jobs that demand low cognitive skills as well as in manufacturing (Stehr 2002a).

Also Alvin Toffler argues that knowledge is the central resource in the economy of the information society: “In a Third Wave economy, the central resource – a single word broadly encompassing data, information, images, symbols, culture, ideology, and values – is actionable knowledge” (Dyson/Gilder/Keyworth/Toffler 1994).

At the end of the twentieth century, the concept of the network society gained importance in information society theory. For Manuel Castells, network logic is besides information, pervasiveness, flexibility, and convergence a central feature of the information technology paradigm (2000a: 69ff). “One of the key features of informational society is the networking logic of its basic structure, which explains the use of the concept of ‘network society'” (Castells 2000: 21). “As an historical trend, dominant functions and processes in the Information Age are increasingly organized around networks. Networks constitute the new social morphology of our societies, and the diffusion of networking logic substantially modifies the operation and outcomes in processes of production, experience, power, and culture” (Castells 2000: 500). For Castells the network society is the result of informationalism, a new technological paradigm.

Jan Van Dijk (2006) defines the network society as a “social formation with an infrastructure of social and media networks enabling its prime mode of organization at all levels (individual, group/organizational and societal). Increasingly, these networks link all units or parts of this formation (individuals, groups and organizations)” (Van Dijk 2006: 20). For Van Dijk networks have become the nervous system of society, whereas Castells links the concept of the network society to capitalist transformation, Van Dijk sees it as the logical result of the increasing widening and thickening of networks in nature and society. Darin Barney uses the term for characterizing societies that exhibit two fundamental characteristics: “The first is the presence in those societies of sophisticated – almost exclusively digital – technologies of networked communication and information management/distribution, technologies which form the basic infrastructure mediating an increasing array of social, political and economic practices. (…) The second, arguably more intriguing, characteristic of network societies is the reproduction and institutionalization throughout (and between) those societies of networks as the basic form of human organization and relationship across a wide range of social, political and economic configurations and associations”.

Lessons from Lean Startups

“The only way to win is to learn faster than everybody else.”

Implement feedback loops, iterate constantly.

Validation > Assumption

Prove it.

Feedback > Feelings

What you think doesn’t matter. What your customer thinks does.

Value > Vanity

Monitor the metrics that mean something.