Technology spillover as a complement for high-level R&amp;D intensity in the pharmaceutical industry

Watanabe, Chihiro; Takayama, Makoto; Nagamatsu, Akira; Tagami, Takashi; Griffy‐Brown, Charla

doi:10.1016/s0166-4972(01)00004-9

Cited by 40 publications

(13 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In parallel with such forefront innovation, it is endeavoring to absorb external innovation resources, particularly soft innovation resources (Tou et al, 2019) from external markets and assimilate them into its business model, which transforms the latter business activities into the former during its R&D process. This transformation depends on its high level of assimilation capacity, which can be attributed to the rapid and notable increase in its R&D investment (Watanabe et al, 2002), and also to the absorption of broad innovation resources based on the Amazon empire chain and big data collection system, together with the deployment of architecture for participation that harnesses the power of its users (Colin, 2016).…”

Section: Amazon's Unique Randd Modelmentioning

confidence: 99%

Transformative direction of R&D– lessons from Amazon's endeavor

Watanabe

Tou

2019

Technovation

Self Cite

View full text Add to dashboard Cite

Amazon jumped up to the world's top Research and Development (R&D) firm in 2017. Such a rapid and notable increase in R&D investment has raised the question of a new R&D definition in the digital economy, which Amazon insists includes both "routine or periodic alterations" (traditionally classified as non-R&D) and "significant improvement" (classified as R&D), as Amazon transforms the former into the latter during its R&D process. A convincing answer to this question will give rise to insightful suggestions regarding a new concept of R&D in the digital economy.

show abstract

Section: Amazon's Unique Randd Modelmentioning

confidence: 99%

Transformative direction of R&D– lessons from Amazon's endeavor

Watanabe

Tou

2019

Technovation

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this activation process, development trajectory transforms from the captured GDP-based co-evolution cycle into the uncaptured GDP-driven co-evolution cycle. This transformation can be attributed to the Internet function [23] which awakes and activates such innovation resources as SIRs that bridge economic functionality and supra-functionality beyond an economic value.…”

Section: Transformation Dynamism Core Function Of Disruptive Businessmentioning

confidence: 99%

Co-Evolutionary Coupling Between Captured and Uncaptured GDP Cycles:cross Learning From Amazon and Finland Models for Sustainability

Moriya¹,

Tou²,

Watanabe³

et al. 2019

IJMIT

Self Cite

View full text Add to dashboard Cite

A solution to the critical problem of a dilemma between R&D expansion and productivity decline that a majority of information and communication technology (ICT) leaders have been confronting in the digital economy is expected. It can be expected by a spinoff from economic functionality-seeking GDP-based coevolution cycle to supra-functionality beyond an economic value-seeking uncaptured GDP-driven coevolution cycle. However, the transformation dynamism remains a black box. By means of numerical simulations based on empirical analyses of the development trajectories of global ICT leaders, focusing on Amazon and Finland, together with an intensive review of preceding analyses, this paper attempted to elucidate the inside the black box of the above dynamism. By developing a practically applicable numerical approach, inspired attempts to explore a new elucidation frontier were conducted, thereby enabling a new concept of co-evolutionary coupling between two cycles to be postulated. An insightful suggestion regarding possible consequences in the future stemming from the trajectory option was thus provided.

show abstract

“…4 In the assimilation dynamism described, its capacity is a function of the ratios of volume and growth rate of the donor and the host. See the details of its mathematical development in Watanabe et al (2002).…”

Section: Assimilation Capacitymentioning

confidence: 99%