Week 1
Crossan and Apaydin (2010): A multi-dimensional framework of organizational innovation
Brief summary innovation as a process answers how and innovation as outcome answers what. There
are four dimensions of organizational innovation: technological e.g., 1) introduction of new products
or processes, 2) organizational innovation e.g., changes in structure of innovation, 3) market
innovation e.g.; creating new markets or entering existing ones in new ways and lastly 4) social
innovation e.g., new ideas and practices in social context. Challenges when trying to innovate e.g.,
resistance to change and new ideas, lack of resource or leadership. Success can be achieved by
combing these types of innovations and organizations need to be flexible, adaptive and foster a culture
for innovation. Building partnerships and networks to share ideas and resources can help. Innovation
is also about creating new forms of organizational structures and new ways of working and value
creation.
, Week 2: Organizing knowledge and capabilities
Grigoriou and Rothaermel (2017): Organizing for knowledge generation: internal knowledge
networks and the contingent effect of external knowledge sourcing
The effectiveness of a firm’s external knowledge acquisition strategies depends on the characteristics
of the firm’s internal knowledge production. Internal and external knowledge networks should be used
to generate new knowledge. Internal knowledge networks can either enhance or inhibit the
effectiveness of external knowledge sourcing. There can be new internal knowledge production with
the recombination of existing knowledge flocks. External knowledge sourcing can help companies
integrate new ideas and perspectives into existing knowledge base. Network clustering within an
company can identify new patterns of knowledge sharing and collaboration. Combination of strong
internal networks and strategic external knowledge sourcing is effective way to generate knowledge,
particular in high-tech industries where technological uncertainty is high.
Yayavaram and Ahuja (2008): Decomposability in knowledge structures and its impact on the
usefulness of inventions and knowledge base malleability.
Prioritizing decomposability in the design and development process can lead to more useful and
adaptable inventions and knowledge bases. Non-decomposable knowledge structures are those that
cannot be broken down into smaller parts typically complex tasks difficult to solve. Nearly-
decomposable can be broken down into smaller parts but relationships between those parts is not
clearly defined tasks that are complex but still manageable. Fully-decomposable can be broken down
into smaller parts and relationship between those is clear tasks can be easily understood and solved.
The process of decomposition should be ongoing to adapt and evolve the knowledge base as needed
and continuously improve the usefulness of innovations. To increase differentiation between clusters
creation of subunits in R&D and implementation of rewards to encourage individual researchers to
pursue new technologies can help.
Zhou and Wu (2010): Technological capability, strategic flexibility and product innovation
Companies with higher level of technological capabilities are more likely to carry out product
innovations. Strategic flexibility to quickly adapt to market changes has a positive effect on product
innovations. Relationship between technological capabilities and product innovations is stronger
among companies in industries with high technological uncertainty. Companies with higher
technological capabilities are able to quickly identify and respond to new trends. Companies in
industries with lower technological uncertainty can rely on established technologies and trends so
lower technological capability does not hinder product innovations as much as in industries with high
uncertainty. Firms looking to innovate should focus on building their technological capability and
developing their strategic flexibility e.g., investing in R&D and training employees in new technologies.
Crossan and Apaydin (2010): A multi-dimensional framework of organizational innovation
Brief summary innovation as a process answers how and innovation as outcome answers what. There
are four dimensions of organizational innovation: technological e.g., 1) introduction of new products
or processes, 2) organizational innovation e.g., changes in structure of innovation, 3) market
innovation e.g.; creating new markets or entering existing ones in new ways and lastly 4) social
innovation e.g., new ideas and practices in social context. Challenges when trying to innovate e.g.,
resistance to change and new ideas, lack of resource or leadership. Success can be achieved by
combing these types of innovations and organizations need to be flexible, adaptive and foster a culture
for innovation. Building partnerships and networks to share ideas and resources can help. Innovation
is also about creating new forms of organizational structures and new ways of working and value
creation.
, Week 2: Organizing knowledge and capabilities
Grigoriou and Rothaermel (2017): Organizing for knowledge generation: internal knowledge
networks and the contingent effect of external knowledge sourcing
The effectiveness of a firm’s external knowledge acquisition strategies depends on the characteristics
of the firm’s internal knowledge production. Internal and external knowledge networks should be used
to generate new knowledge. Internal knowledge networks can either enhance or inhibit the
effectiveness of external knowledge sourcing. There can be new internal knowledge production with
the recombination of existing knowledge flocks. External knowledge sourcing can help companies
integrate new ideas and perspectives into existing knowledge base. Network clustering within an
company can identify new patterns of knowledge sharing and collaboration. Combination of strong
internal networks and strategic external knowledge sourcing is effective way to generate knowledge,
particular in high-tech industries where technological uncertainty is high.
Yayavaram and Ahuja (2008): Decomposability in knowledge structures and its impact on the
usefulness of inventions and knowledge base malleability.
Prioritizing decomposability in the design and development process can lead to more useful and
adaptable inventions and knowledge bases. Non-decomposable knowledge structures are those that
cannot be broken down into smaller parts typically complex tasks difficult to solve. Nearly-
decomposable can be broken down into smaller parts but relationships between those parts is not
clearly defined tasks that are complex but still manageable. Fully-decomposable can be broken down
into smaller parts and relationship between those is clear tasks can be easily understood and solved.
The process of decomposition should be ongoing to adapt and evolve the knowledge base as needed
and continuously improve the usefulness of innovations. To increase differentiation between clusters
creation of subunits in R&D and implementation of rewards to encourage individual researchers to
pursue new technologies can help.
Zhou and Wu (2010): Technological capability, strategic flexibility and product innovation
Companies with higher level of technological capabilities are more likely to carry out product
innovations. Strategic flexibility to quickly adapt to market changes has a positive effect on product
innovations. Relationship between technological capabilities and product innovations is stronger
among companies in industries with high technological uncertainty. Companies with higher
technological capabilities are able to quickly identify and respond to new trends. Companies in
industries with lower technological uncertainty can rely on established technologies and trends so
lower technological capability does not hinder product innovations as much as in industries with high
uncertainty. Firms looking to innovate should focus on building their technological capability and
developing their strategic flexibility e.g., investing in R&D and training employees in new technologies.
