Related papers: Are Biotechnology Startups Different?
We study the optimal investment policy of a firm facing both technological and cash-flow uncertainty. At any point in time, the firm can decide to invest in a standalone technology or to wait for a technological breakthrough. Breakthroughs…
To keep the competitive advantage and adapt to changes in the market and technology, companies need to innovate in an organised, purposeful and systematic manner. However, due to their size and complexity, large companies tend to focus on…
Physical emergence - crystals, rocks, sandpiles, turbulent eddies, planets, stars - is fundamentally different from biological emergence - amoeba, cells, mice, humans - even though the latter is based in the former. This paper points out…
Hardware, systems and algorithms research communities have historically had different incentive structures and fluctuating motivation to engage with each other explicitly. This historical treatment is odd given that hardware and software…
The technical knowledge and soft skills of entrepreneurial team members significantly impact the early stages of software startups. It is widely recognized that the success or failure of a startup is determined by the quality of the…
Biological systems are generally complicated and/or complex. In the former approach, one sets up a model with a large number of parameters to describe the system in detail. The latter approach focuses on understanding the universal aspects…
We use citation data of scientific articles produced by individual nations in different scientific domains to determine the structure and efficiency of national research systems. We characterize the scientific fitness of each nation (that…
Startups face a classic dilemma in innovation strategy: should they pursue cumulative, low-risk improvements or disruptive, high-risk breakthroughs? The Henderson and Clark framework suggests that architectural innovation, which…
In computer science, we can theoretically neatly separate transmission and processing of information, hardware and software, and programs and their inputs. This is much more intricate in biology, Nevertheless, I argue that Shannon's concept…
How do business-cycles impact startup-valuations? While several studies explore VC startupecosystems and pre-money valuations, relatively-few delve deeper into the role of macro-level economic factors in influencing those startup deals…
The pursuit of creating artificial intelligence (AI) mirrors our longstanding fascination with understanding our own intelligence. From the myths of Talos to Aristotelian logic and Heron's inventions, we have sought to replicate the marvels…
We consider in this paper the problem of predicting the ability of a startup to attract investments using freely, publicly available data. Information about startups on the web usually comes either as unstructured data from news, social…
Determining how scientific achievements influence the subsequent process of knowledge creation is a fundamental step in order to build a unified ecosystem for studying the dynamics of innovation and competitiveness. Relying separately on…
The philosophy of blockchain technology is concerned, among other things, with blockchain ontology, how it might be characterised, how it is being created, implemented, and adopted, how it operates in the world, and how it evolves over…
Crowdfunding offers inventors and entrepreneurs alternative access to resources with which they can develop and realize their ideas. Besides helping to secure capital, crowdfunding also connects creators with engaged early supporters who…
Network biology is an interdisciplinary field bridging computational and biological sciences that has proved pivotal in advancing the understanding of cellular functions and diseases across biological systems and scales. Although the field…
It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startups, how fast startups…
Context: On top of the inherent challenges startup software companies face applying proper software engineering practices, the non-deterministic nature of machine learning techniques makes it even more difficult for machine learning (ML)…
The idea of Artificial Intelligence (AI) has a long history. It turned out, however, that reaching intelligence at human levels is more complicated than originally anticipated. Currently we are experiencing a renewed interest in AI, fueled…
A major issue in biology is the understanding of the interactions between proteins. These interactions can be described by a network, where the proteins are modeled by nodes and the interactions by edges. The origin of these protein…