Biotech startups are found to be similar to tech startups overall.
problem The uniqueness of biotech startups was previously overemphasized.
method Extensive research from new databases analyzed similarities and differences.
result Biotech startups share similarities in venture capital, exit time, and geography with tech startups.
Biotech IPOs in Q1 2021: advanced degrees, clinical trials, and IP key.
problem Identifying traits of biotech startups that go public.
method Database of biotech IPOs, analysis of leadership, technology, clinical trials, and financing.
result Advanced degrees, clinical trials, and IP are important for biotech startups.
Business cycles affect startup valuations, both directly and indirectly.
problem How do business cycles impact startup valuations?
method Structural Equation Model approach using a dataset of 1,089 venture capital investments.
result Business cycles impact startup valuations both directly and indirectly.
This paper evaluates investment risks in LATAM AI startups using DCF method.
problem Unique challenges and risks faced by LATAM tech startups.
method Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) metrics; Discounted Cash Flow (DCF) method.
result Developed a ranking of emerging powers in Latin America for tech startup investment.
The paper analyzes sectoral diversity in startup ecosystems in Europe and the USA.
problem Investigating sectoral diversity in startup ecosystems.
method Analysis of 20+ startup ecosystems in Europe and the USA using a new visualization tool and numerical simulations.
result Emerging diversity of startup ecosystems can be explained by a preferential attachment model based on sectoral funding.
Study uses web search data to analyze tech startups growth.
problem Analyzing growth dynamics of tech startups.
method Utilized Google Trends data for 241 US-based tech startups.
result Web search traffic correlates positively with tech startup growth.
Green startups in Italy survive longer than non-green ones.
problem Survival of innovative startups in Italy.
method Comparative analysis of green vs. non-green startups in Italy, 2009-2018.
result Green startups are more than twice as likely to survive than non-green ones.
Study shows startup competition and investor network influence fundraising success at different stages.
problem Misunderstanding of fundraising success factors across startup stages.
method Used Word2Vec for competition measures and Graph Neural Networks for investor network analysis.
result Startup competition is crucial for early-stage fundraising, while growth-stage fundraising is influenced by investor network features.
Enhances VC startup success predictions using graph augmented time series models.
problem Challenges in predicting startup success due to limited financial data and subjective forecasts.
method Integrates inter-company relationships into time series analysis using GraphRAG.
result Significantly outperforms previous models in startup success predictions.
Geoeconomic analysis of venture capital portfolios reveals key emerging tech domains and countries.
problem Quantifying geoeconomic power and technological sovereignty through venture capital data.
method Economic complexity methods applied to venture capital portfolios and RVA metrics.
result Cloud Computing, Cybersecurity Tools, and Medtech have the highest concentration of specialization among high-GCI countries.
Deep learning helps identify promising startups.
problem Identifying successful startups amidst many.
method Literature review and synthesis of DL-based startup evaluation methods.
result Deep learning shows promise in startup success prediction.
YC Bench forecasts startup success in Y Combinator batches with a short-term metric.
problem Difficult forecasting of startup success due to sparse meaningful outcomes and slow evaluation cycles.
method Developed a live benchmark using publicly available traction signals and web visibility metrics.
result Revealed 6 out of 11 top performers at YC Demo Day with a simple proxy for prior brand recognition.
Predicting startup success using Crunchbase data and deep learning.
problem Predicting startup success in a volatile entrepreneurial ecosystem.
method Novel deep learning model integrating funding metrics, founder features, and industry category.
result Achieved 14 times capital growth and identified high-potential startups.
In this paper we propose a quadratic programming model that can be used for calculating the term structure of electricity prices while explicitly modeling startup costs of power plants. In contrast to other approaches presented in the literature, we incorporate the startup costs in a mathematically rigorous manner with…
We consider the problem of evaluating the quality of startup companies. This can be quite challenging due to the rarity of successful startup companies and the complexity of factors which impact such success. In this work we collect data on tens of thousands of startup companies, their performance, the backgrounds of t…
This paper compares token and equity financing for startups.
problem Understanding differences in return rates between token and equity financing.
method Developed a three-period model to analyze liquidity and return differences.
result Entrepreneurs can achieve higher payoffs by issuing tokens, especially for risk-averse investors with liquidity needs.
Study reveals which startup valuation factors are most critical.
problem Understanding the complex factors influencing startup valuations.
method Hierarchical prediction models using decision trees and random forests.
result Identifies which factors most significantly impact startup valuations.
Study finds internal view preferred over external view in defining startups.
problem Insufficient understanding of how to start a new business.
method Empirical study with 701 entrepreneurs reflecting on nine resource categories and three business mission elements.
result Tendency to favor internal view over external view, stronger in stable economies.
A new method to value IPOed companies.
problem Valuing companies after IPO.
method Growth Average U1 method.
result Benchmark stocks using linear extrapolation of revenues and profits.
Study predicts startup outcomes like funding, patenting, IPOs using machine learning.
problem Forecasting startup success metrics like funding, patenting, IPOs.
method Developed interpretable machine learning framework, used preprocessing, class imbalance handling, and compared multiple models.
result Achieved high AUROC values for patent, funding, and exit predictions.
Designed to compete with fiat currencies, bitcoin proposes it is a crypto-currency alternative. Bitcoin makes a number of false claims, including: solving the double-spending problem is a good thing; bitcoin can be a reserve currency for banking; hoarding equals saving, and that we should believe bitcoin can expand by …
This research examines relationship between staging of Venture Capital (VC) investments and social feedback visible in publicly available data on the Web. We address the question of Venture Capital investment sensitivity to performance and prospects of new venture, given as likelihood of obtaining future financing, ava…
Analyzes how venture investment strategies have evolved over time in different sectors.
problem Understanding changes in venture investment strategies across sectors over time.
method Applied PCA and TCA to analyze a dataset of 52,000 startups and 110,000 funding rounds.
result There has been a shift in venture investment towards lower-tech sectors and a rise in accelerator investments.
New algorithm detects and handles concept drift in data streams.
problem Handling concept drift in data streams for timely predictions.
method Hybrid Forest algorithm combining Hoeffding Trees and fast startup.
result The algorithm outperforms other methods in classification and regression tasks.
A new auction model for zero-marginal cost products.
problem Determining fair prices for zero-marginal cost products.
method Continuous bidding with self-organized criticality mechanism.
result Avalanches of sales above a critical price.
Study evaluates early-stage cybersecurity firms' performance using Crunchbase data.
problem Assessing performance of early-stage cybersecurity startups.
method Empirical analysis of 19 cybersecurity sectors using Crunchbase data.
result Significant variations in capital raised and post-money valuations across cybersecurity sectors.
Develops a deep learning framework to predict future tech directions for high-tech companies.
problem Difficult task in predicting future R&D trends for high-tech companies due to complexity and variety of factors.
method Deep Technology Forecasting (DTF) framework with three components: PCR, CTR, and DTT neural network.
result DTF framework precisely predicts future tech emphasis of companies using hybrid factors.
Study of dynamic competition between old and new technologies using a nonlinear map.
problem Dynamic competition between old and new technologies in market share.
method Simulations with three key parameters: scientific-technological, purely technological, and economic.
result Different outcomes in terms of technology prevalence based on interaction of key parameters.
The paper analyzes tech specialization and diversification at various scales.
problem Trade-offs between specialization and diversification in economic development.
method Patent data and Economic Complexity framework.
result Technological Coherence positively impacts growth at metropolitan areas but negatively at larger scales.
How technology affects growth or employment has long been debated. With a hiatus, the debate revived once again in the form of how Information and Communications Technology, as a form of new technology, exerts on productivity and employment. Information and Communications Technology perceived as General Purpose Technol…
Quantum crypto-economics models price risks in blockchain technology.
problem Quantum technology's potential to undermine blockchain security.
method Building financial models to price quantum risk in blockchain scenarios.
result Quantum crypto-economics models can assess and price quantum risks in blockchain.
Estimates yearly improvement rates for nearly all technologies using US patent data.
problem Providing a comprehensive account of technological change rates.
method Mapping patents to technology domains, calculating average centrality, and estimating improvement rates.
result Variation in improvement rates from 1.9% to 228.8% per year, with software-based domains often the fastest.
Industry evolution caused by various reasons, among which technology progress driving industry development has been approved, but with the new trend of industry convergence, inter-industry convergence also plays an increasing important role. This paper plans to probe the industry synergetic evolution mechanism based on…
Paper reviews neurolinguistics and language technologies, emphasizing mutual enrichment.
problem Understanding brain activity during language processing.
method Brain imaging studies and natural language representations.
result Development of brain-aware natural language representations.
At the heart of technology transitions lie complex processes of social and industrial dynamics. The quantitative study of sustainability transitions requires modelling work, which necessitates a theory of technology substitution. Many, if not most, contemporary modelling approaches for future technology pathways overlo…
Different technological domains have significantly different rates of performance improvement. Prior theory indicates that such differing rates should influence the relative speed of diffusion of the products embodying the different technologies since improvement in performance during the diffusion process increases th…
Tech sector decouples from non-tech sectors post-2015, predicting economic growth.
problem Understanding the relationship between technology and economic growth.
method ARIMA modeling, stationarity tests, data wrangling, exploratory data analysis.
result The technology sector decouples from non-technology sectors post-2015 and predicts economic growth.
Qlib aims to integrate AI into quantitative investment.
problem Challenges in applying AI to quantitative investment.
method Design and develop Qlib to accommodate AI-driven workflow.
result Qlib realizes the potential of AI technologies in quantitative investment.
Tool uses text mining to define innovative tech fields from abstracts.
problem Defining scope in dynamic, multidisciplinary tech projects.
method Text mining of Elsevier's Scopus abstracts.
result Tool provides crucial information for tech field definition.
PHBench predicts Series A funding from Product Hunt launch signals with 7.8% accuracy.
problem Predicting startup Series A funding from launch signals on Product Hunt.
method Constructed PHBench from 67,292 Product Hunt posts, linked to funding records, and used a three-component ensemble model.
result Best-performing model achieved F0.5 = 0.097 and AP = 0.037, with a statistically significant advantage over logistic regression.
This paper analyzes the dynamic incentives for technology adoption under a transferable permits system, which allows for strategic trading on the permit market. Initially, firms can invest both in low-emitting production technologies and trade permits. In the model, technology adoption and allowance price are generated…
Modeling tech transfer to explain convergence in Central and Eastern Europe.
problem Understanding mechanisms of technological diffusion in developing economies.
method Introducing a herding-based mechanism to model technological adoption and productivity growth.
result Explicit analytical solution showing nonlinear convergence to a moving frontier.
Smart contracts are a digital technology with potential but also flaws.
problem Understanding the potential and limitations of smart contracts.
method Exploratory study combining statistics, IT, and law.
result Smart contracts have both idealistic promises and practical challenges.
Speed bumps reduce but do not fully eliminate investment in fast trading technology.
problem Limiting low-latency trading to curb investment in fast trading technology.
method Built an experimental trading platform to test the effects of speed bumps on investment in fast trading technology.
result Asymmetric speed bumps reduce investment in speed by only 20%, and increasing the magnitude further reduces investment by 8.33%. Symmetric speed bumps have no effect on investment levels.
TechRank ranks companies and technologies based on investor preferences.
problem Estimating influence and ranking companies and technologies.
method Recursive algorithm based on a bi-partite graph with weighted nodes, incorporating investor preferences.
result Provides investors with a quantitative ranking of technologies for optimal portfolio design.
Margin trading and short selling boost green tech innovation in China.
problem Encouraging green technology innovation in Chinese companies.
method Quasi-experimental research using panel data of Chinese listed companies, double difference model.
result Margin trading and short selling increase green tech innovation significantly.
Production networks amplify economic growth through technology diffusion.
problem Understanding how technology improvements propagate through production networks.
method Analyzing a production network model to study the effects of technological improvements.
result Longer production chains lead to faster price reduction and GDP growth.
New method assesses energy storage value beyond cost reduction.
problem Improving energy storage value beyond cost reduction.
method Market potential method to evaluate and compare energy storage technologies.
result High-cost hydrogen storage can be more valuable than low-cost hydrogen storage.