Unicorn Ventures

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RESEARCH PAPER

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INTRODUCTION

Blockchain, artificial intelligence, data science, edtech and internet-of-things are all buzzwords today in this new innovation era. More and more founders and investors begin to see the potential of innovation in Asia today. Meanwhile, local governments in the region have introduced new policies and initiatives to explore new technological innovation frontiers in order to boost the competitiveness of various knowledge-based industries. In recent years, both Hong Kong and Singapore government has pumped in Resources (link: https://www.cnbc.com/2018/04/10/singapore-and-hong-kong-are-winning-over-start-up-accelerators.html) including start-up clusters, grants and fundings to boost its start-up Ecosystem.

The two Asian-Tigers, Singapore and Hong Kong, will be the main contexts for this project. They are two high-growth metropolitan city-states in Asia that share many characteristics in common in terms of GDP per capita and population density. Beyond that, both Hong Kong and Singapore offers a comprehensive financial and technical infrastructure and has attracted a considerable amount of foreign investment. It is commendable that both countries have achieved stellar economic performance despite the lack of natural resources and large land size. Unicorn Ventures strives to study the current start-up ecosystem in these two city-based regions and hope to generate new insights for policy-makers, founders and investors.

MOTIVATION

Our research is motivated by the lack of comprehensive comparison between these two countries’ startup ecosystem. Currently, there are many sources of fragmented datasets on different aspects of the startup ecosystem such as top-funded companies, industry breakdown and funding analysis. Our project aims to consolidate the data sources and study the two different startup ecosystems through a centralized interactive web application.

This project will focus on start-up companies and funding organizations in the tech ecosystem. The insights generated could help: Hong Kong and Singapore policy makers improve its existing infrastructures or policies to cultivate a more robust startup ecosystem Potential and current founders to understand the growing industries, competitor landscape and investors Potential investors to identify the growing industries and dominant players

OBJECTIVES

Our project aims to explore and compare the following aspects for the startup ecosystem in Singapore and Hong Kong by considering the startups founded after 2000.

Ecosystem Index Analysis:

• What is the difference of Hong Kong and Singapore in terms of Global Entrepreneurship Index and Global Competitiveness Index?

Startup Analysis:

• Time-series analysis for startups that has formed/exited across the years by different industries
• What is the current breakdown of startups by industries, key industries, team size, funding stage, age and gender of founders?

Funding Analysis:

• What are top funded startups and their funding stages and industries?
• Time-series analysis of the disclosed funding over the years by industries
• Where does the investors originate from and what are the investor types?

SELECTED DATASET

Dataset
Global Entrepreneurship Index Score in Singapore and Hong Kong in 2018 Description: The GEI measures both the quality of entrepreneurship in a country and the extent and depth of the supporting entrepreneurial ecosystem. The GEI consistsof 3 sub-indices including entrepreneurial attitudes, entrepreneurial abilities and entrepreneurial aspirations. Source: Global Entrepreneurship and Development Institute Dateset Components: Sub-index Attributes Attitudes Sub-index Opportunity Perception Startup Skills Risk Acceptance Networking Cultural Support Abilities Sub-index Opportunity Perception Technology Absorption Human Capital Competition Aspiration Sub-index Product Innovation Process Innovation High Growth Internationalization Risk Capital
Global Competitiveness Index 2017-2018 for Singapore and Hong Kong Description: It measures national competitiveness which is defined as the set of institutions, policies and factors that determine the level of productivity. Source: World Economic Forum Dataset Components: Sub-index Attributes Basic Requirements Sub-index Institutions Infrastructure Macroeconomic environment Health and primary education Efficiency Enhancers Sub-index Higher education and training Goods market efficiency Labour market efficiency Financial market development Technological readiness Market Size Innovation and Sophistication Factors Sub-index Business sophistication Innovation
Startup Information in Singapore and Hong Kong Description: This dataset includes various key attributes on startups in Singapore and Hong Kong that was founded after 2000. Source: Crunchbase Dataset Components: Information Type Attributes Basic Info Organization Name Categories Category Groups Headquarters Location Operating Status Founded Date Exit Date Closed Date Team Number of Founders Female_Founder Founders Number of Employees Funding Number of Funding Rounds Funding Status Last Funding Date Last Funding Amount Currency (in USD) Last Funding Type Last Equity Funding Amount Currency (in USD) Last Equity Funding Type Total Equity Funding Amount Currency (in USD) Total Funding Amount Currency (in USD) Number of Lead Investors Number of Investors Number of Acquisition Acquisition Status IPO and Stock Price IPO Status IPO Date Stock Symbol Stock Exchange

DATA MODEL

BACKGROUND SURVEY OF RELATED WORKS

Related Works	What We Can Learn

SKETCHES STORYBOARD

Sketches	How Analyst Can Conduct Analysis

ARCHITECTURE DIAGRAM

KEY TECHNICAL CHALLENGES

PROJECT TIMELINE

REFERENCES

COMMENTS

Feel free to comments, suggestions and feedbacks to help us improve our project!:D