Introduction
Entrepreneurship has always been in Hong Kong’s DNA. From its early days as a trading port to its rise as a manufacturing and global financial center, the city has spawned “startups” that went on to become regional and global powerhouses.
The dot-com boom of the late 1990s ushered in a new chapter, as Hong Kong began developing a technology startup ecosystem, peaking during 2016-2018. Driven primarily by private enterprise with some public sector support, the ecosystem generated its essential components: venture capitalists, accelerators, incubators, pitch competitions, shared workspaces, training programs, and various industry and public initiatives.
This ecosystem was modeled after Silicon Valley – with mixed results. Local participants attempted to replicate Silicon Valley’s success without fully considering the unique initial conditions that had shaped its development over many decades.
By neglecting Hong Kong’s own historical strengths and weaknesses, this approach, in my opinion, led to what might be termed “innovation theater.” The focus was on chasing, performatively and unsustainably, the outputs of a successful startup ecosystem – large tech firms and high-growth startups – rather than cultivating the necessary inputs: highly skilled talent, technical infrastructure, community support structures, and relevant forms of capital.[1] This first wave of ecosystem development ended with the onset of the COVID-19 pandemic in early 2020.
Today, Hong Kong is at a crossroads again. Technological change, economic uncertainty, and geopolitical realignment are driving Hong Kong to reinvent itself. A crucial element of this process is rethinking Hong Kong’s innovation and technology development.
In December 2022, the city’s government issued the Hong Kong Innovation and Technology Development Blueprint as part of this reinvention. Coinciding with several other private and public initiatives, the Blueprint’s objective is “to establish a clear development path and formulate systematic strategic planning for Hong Kong’s innovation and technology development over the next five to 10 years.”[2]
This second attempt at jumpstarting the startup ecosystem incorporates lessons from the last few decades. Instead of blindly pursuing ill-fitting business models for Hong Kong, the focus is now on developing a group of organizations and policies operating at the public-private interface to promote economic development aligned with Hong Kong’s strengths.
These efforts include revamped government agencies and departments, novel and more effective funding mechanisms, targeted investment incentives, strong industry associations, new public-private partnerships, as well as “global from day one” collaborations in the Greater Bay Area (GBA) and university-sourced entrepreneurship.
A broader community, rather than a firm-focused ecosystem, is key. But a university-dominated ecosystem without input from industry can also be risky, producing research removed from actual economic demands and lacking clear market potential.
While this latest push benefits from a strong will and substantial resources, stakeholders – including policymakers, potential startups, other ecosystem participants, and the general public – are still not familiar with the available pathways and resources and how they all fit into a cohesive framework.
This analysis aims to frame Hong Kong’s startup ecosystem development from a qualitative firm-level microeconomic perspective. The financial, educational, and ecosystem resources required by each startup will vary depending on its stage of development and its technology and product offering.
Through field research and in-depth interviews with ecosystem participants – startups, academics, venture capitalists, and executives at private, government, and educational entities – I present a framework using the startup as the unit of analysis. Although startups come in many flavors, I focus primarily on technology startups, particularly “deep tech” ventures requiring the advancement and commercialization of basic and applied technologies.
By examining how the ecosystem structure relates to startup lifecycles, my analysis seeks to show how different elements interact with each other, identify areas that require additional resources based on Hong Kong’s current state, and provide high-level policy insights that could inform the design and refinement of Hong Kong’s startup ecosystem.[3]
The Startup Lifecycle
Figure 1 illustrates the typical startup lifecycle, though variations of this model exist to capture its distinct phases.[4] The timing shown is schematic and conceptual rather than literal – in practice, some of these phases can be very long. Consider flat panel display technology: basic and applied research took decades before the technology matured enough to present viable business opportunities.[5]
Also critical to understanding startup development is the “Valley of Death”[6], the period between company formation and the first injection of external capital coupled with product launch, when the path to positive cash flows becomes possible. This phase represents the greatest threat to startup survival.
Figure 1. The startup lifecycle
A detailed study[7] finds that 75 percent of venture capital-backed companies never generate equity returns for their founders. Other estimates of startup failure rates range from 50 percent to 90 percent, with variations largely attributable to how researchers define “startup” and “failure.” Some analyses exclude companies that survive or get acquired but are not expected to deliver positive returns to investors.[8]
Startups face multiple risks during their lifecycle: market viability, product development, technological feasibility, management execution, macroeconomic conditions, and funding environment. Given the long odds of success, a thriving and sustainable startup ecosystem is necessary. While places like Silicon Valley, Boston, and New York have favorable initial conditions (top universities, an entrepreneurial culture, a long history of technical innovation), others must carefully craft policies and institutions to increase the chances of success. Moreover, these support structures will vary along the startup lifecycle to address their different needs.
Key Performance Indicators (KPIs)
Measuring a startup’s progress along its lifecycle is crucial for determining appropriate resource allocation. While measuring innovation and technology is inherently challenging, it remains important when evaluating startups. Traditional metrics such as job creation, funds raised, or “unicorn” status are commonly cited,[9] but they are incidental to the policy objective of fostering startup success.
One popular method to determine a technology’s maturity is the Technology Readiness Level (TRL), created by NASA[10] in 1974 for space exploration technologies. Now used extensively by research organizations, innovation agencies, and public funding programs, the TRL scale ranges from 1 to 9, with 9 representing the highest level of technological maturity.
Complementing the TRL is the Business Readiness Level (BRL), which measures the maturity of a business or business model.[11] The BRL evaluates multiple areas: business concept, model, and strategy; team and management structure; awareness of competitors; and financial metrics like capital, cash flow, scalability, and sustainability. BRLs similarly range from 1 to 9 (Figure 2).
The TRL and BRL align roughly with the startup lifecycle of Figure 1, progressing from lower levels on the left to higher ones as the startup matures. Figure 3 presents a proposed breakdown of different TRLs and BRLs assessed in parallel.[12]
| Technology Readiness Level | Business Readiness Level | |
| Purpose | Assesses the maturity of a technology’s development | Assesses the maturity of the business in relation to the technology development |
| When Used | To determine if a technology is ready for the market | To determine if a business based on a technology can be profitable |
| How Used | To benchmark technical risk and understand a startup’s maturity | To establish a technology that is financially commercially viable |
Figure 2. Technology Readiness Level and Business Readiness Level
| TRL/BRL | Technology Readiness Description | Business Readiness Description2 |
| 1 | Scientific research begins to be translated into applied research and development. Examples might include models of a technology’s basic properties. | Brainstorming possible business concepts, with limited knowledge or insight into the market or competition. |
| 2 | Invention begins and practical applications can be developed. Applications are speculative. | First possible business concept described, and overall market and competitors or alternatives identified. |
| 3 | Active research and development targeted at a defined outcome is initiated. Intellectual Property (IP) protection is examined. | Business model drafted. Customer and market segments are identified, and validation of those segments commences. IP licensing (if appropriate) is evaluated. |
| 4 | Basic technological components are integrated to establish that the pieces will work together in a working Proof of Concept device, breadboard, or code. Provisional patent protection is considered. | Validation of the market and/or customer segments for a defined business offering is completed. The product/offering is generally defined. A preliminary pro forma P&L is built based on initial customer/market validation data |
| 5 | The basic technological components are integrated with reasonably realistic supporting elements so it can be tested in a simulated environment. | Market price point is examined. A cash flow analysis is completed. The complete Business Model is defined. The company is established. |
| 6 | Representative model or prototype system is tested in a relevant environment. Non-Provisional patent and/or copyright (for software) filings are determined. | An alpha product test plan is built and executed, one that tests “first article” or prototype units in relevant environments. Sales channels are defined. |
| 7 | Prototype system or product demonstrated in an operational environment. Manufacturing/Operations models, building the product, are exercised and validated. | IP licensing is finalized. Final pricing is determined along with gross and net margins. Financial controls are put in place. |
| 8 | Technology is proven to work. Actual technology completed and qualified through test and demonstration. | Beta test plan is completed validating the product meets or exceeds both operational and customer requirements. |
| 9 | Technology/product proven through successful operations and user experience. | Product is launched and iterated. Marketing strategy is fully launched. Sales channels are fully implemented. Initial sales growth is seen. |
Figure 3. Technology Readiness Levels and Business Readiness Levels
A Startup-Centered Model of the Ecosystem
A startup ecosystem is a complex web of interdependent people, organizations, resources, and initial conditions unique to each time and place. This ecosystem grows and evolves through effective interactions between system participants and startups across their lifecycles. Although it’s important for policies to help ensure ecosystem components are aligned, those that promote collaboration, connectivity, and shared learning are equally critical.
Financial capital for startups comes in various forms, each suited to different lifecycle stages and their target technologies, products, or end markets. Startups can be bootstrapped (self-funded), or they can access non-dilutive financing such as grants or corporate R&D contracts. As startups grow, they may need external financing, and typically tap individual investors, family offices, angel groups, or seed funds for external equity. Later stages attract traditional venture capital, growth capital, vendor financing, and debt capital. The final stage – exit via IPO or acquisition – provides returns to investors and management. This progression has led to inordinate focus on establishing diverse funding sources across all lifecycle stages.
But we must recognize there is more than one type of capital. In the book The Startup Community Way[13], Feld and Hathaway describe seven forms of capital: intellectual (technologies, ideas, information); human (talent, knowledge, skills); financial (equity, debt, non-dilutive financing); institutional (ecosystem organizations, markets, stability); physical (density, infrastructure, standards of living); network (connectedness, relationships, collaborations); and cultural (attitudes, mindset, behaviors). Government policy can influence many of these forms of capital, and how they are promoted should align with the nature and lifecycle of startups in a given ecosystem.
It is important to prioritize supporting people and networks over buildings and institutions, and to focus on experimentation and learning over rigid planning and execution. Although startups drive productivity, innovation, and job growth, most of them will likely end in failure. Designing an ecosystem that maximizes their chances of success over the long term is crucial.
Figure 4 illustrates how a startup, across its lifecycle, engages with financial and other select forms of capital, potentially shaped by government policy and mapped against different TRLs and BRLs. While not exhaustive – and geared toward hardware-centric ventures – this framework shows the components required of a successful ecosystem beyond financial resources.
Figure 4. A startup-centered ecosystem
For example, human capital in the early TRL/BRL phase of a startup could involve university scientists and academics carrying out applied research from first principles in deep tech (e.g. robotics or semiconductors), or technically savvy business innovators who see an opportunity. As the idea starts to take shape, people with translational and business skills can be brought in to assess its market potential. As prototypes and first articles are produced, sales and marketing experts can scope out potential customers and partners. And as the company aims to exit, financial intermediaries can help with the transaction.
Similarly, in terms of institutional capital, an early-stage startup could rely on funding agencies for financial support, and university technology licensing and transfer offices to help identify and protect its intellectual property and craft an agreement for its commercialization. Firm formation involves law and accounting firms, and the need for reasonably accessible third-party partners and service providers will arise as the product develops. Of course, customers are essential for generating revenues, and partners are likely needed to help expand markets and amplify reach.
The optimal mix of different capital forms in a thriving ecosystem varies by startup type and maturity (TRL and BRL). For example, in an environment dominated by early-stage deep tech companies, academic funding, functioning technology, entrepreneurship education, and licensing programs are more important than having a large local end market or a thriving market for IPOs. Conversely, a hub for late-stage biotech firms (like Cambridge, Massachusetts) needs advanced laboratory facilities and manufacturing capabilities rather than basic entrepreneurship training or IP licensing support, as their founders likely have prior startup experience or have already navigated these processes years ago.
This mix will evolve as startups mature, fail, or exit. Job hopping, business failure or success, and knowledge diffusion also create endogenous effects that shape the kinds of capital needed in the future. Effective ecosystem development policies must account for this dynamic endogeneity.
The Hong Kong Startup Ecosystem – A High-Level Framework and Issues
Hong Kong has begun to reimagine its startup ecosystem in recent years. The city’s government, working alongside private entities, has launched initiatives and investment programs to harness Hong Kong’s strengths and entrepreneurial drive.
At the heart of this approach is leveraging Hong Kong’s universities and research institutes. Hong Kong’s eight University Grants Council-funded institutions of higher learning,[14], particularly its five world-class research universities (HKU, HKUST, PolyU, CUHK, and CityU), offer an untapped reservoir of scientific and technical intellectual property that could be commercialized.
Focusing on scientific advances that could be turned into products (and companies) utilizes Hong Kong’s unheralded but significant capabilities in basic and applied science.[15] This contrasts with the previous laissez-faire approach that relied on organic ecosystem growth. The shift toward policy-driven ecosystem development should align with Hong Kong’s strengths and weaknesses as an innovation hub: top-flight pure and applied research universities, a high-quality talent pool, a compact footprint conducive to collaboration, and a business-friendly environment; coupled with a small market size, high living costs and expensive infrastructure.
The initiatives and institutions, both public and private, are too numerous to list here,[16] but we can map them onto our framework with some key examples. At the early stages (TRL/BRL 1-2), there are plenty of institutions and forms of capital that provide a solid foundation, including the eight UGC-funded universities and their research centers populated by world-class scientists and engineers. Educational resources for early-stage entrepreneurship abound (e.g. HKU’s Techno-Entrepreneurship Core.[17]). Technology and knowledge transfer offices at universities scout the IP space and help extract IP for commercialization. R&D grants and other early-stage financial support are readily available (e.g. CUHK Innovation Limited[18]).
At the next level (TRL/BRL 3-4), incubation and acceleration programs are available at Hong Kong Science and Technology Park[19] and Cyberport.[20] Financial support can be obtained from programs such as RAISe+[21] and ITF’s Technology Start-up Support Scheme for Universities (TSSSU).[22] For more mature and late-stage startups (TRL/BRL 9), vehicles like the Hong Kong Growth Portfolio[23] and the Hong Kong Investment Corporation[24] funds offer ample capital resources.
The ecosystem is weakest at the intermediate “Valley of Death” stages (TRL/BRL 5-8) – precisely where startups need the most support. Our interviews and research reveal several challenges:
- Technology entrepreneurship in Hong Kong remains poorly understood. It is easy for young people to see their futures as doctors, bankers, or lawyers; it is much harder to see a path toward successful entrepreneurship. Technology startup formation rates are therefore low. There is not much of a “flywheel” where successful entrepreneurs reinvest experience and capital into new ventures, serving as role models or offering lessons for aspiring founders.
- Research often develops in isolation from industry needs, making it difficult to tease out a product and market. Many academics and researchers are focused on their own agendas and lack business mindsets, hindering innovation. Many founders have scattered and informal business knowledge, which can lead to major blind spots – they don’t know what they don’t know. Promising prototypes may struggle to bridge the gap to commercialization.
- Interactions and integration between business schools and early-stage R&D efforts are weak. Technical founders struggle to find business-focused partners, which is fundamental to success. At universities, program directors are siloed, and there is little incentive for a business school and an engineering school at the same institution to exchange knowledge and develop ties or cross-faculty initiatives. There is no institutional clearinghouse to facilitate collaboration across universities and technologies, resulting in fragmented access to information and missed opportunities for partnerships.[25]
- Current accelerator and incubator programs, while well-structured, often fail to provide tools for long-term growth. Many startups face an “accelerating into a wall” phenomenon, unable to maintain momentum, raise funds and commercialize their technology after completing those programs.
- Early-stage investor (e.g. angel investor) education is weak. Small investors do not have the bandwidth and do not know what to do post-investment. There aren’t any structured programs to train individuals or angel investors such as family offices on investing in startups. They only learn through failure, which hinders continuous risk-taking and development of a broader investment culture.
- Early and mid-stage venture capital remains scarce. Very few investors understand and are willing to support technologies that require many years to mature and offer only modest financial returns over the life of a VC fund. Many Mainland VC funds have onerous redemption clauses that make it impossible to fund promising startups. Private capital and corporate R&D play crucial roles in bringing new technologies to market, but they lack the patience and consistency to cultivate something fundamentally new over multiple decades.
- Hong Kong’s end markets for technology startups are small and likely insufficient to support large and scaled revenue models. Its small local market prevents startups from achieving the critical mass or scale necessary to attract traditional venture capital. Partnership opportunities are equally limited due to the narrow focus of established homegrown technology corporations.
Policy Recommendations and Conclusion
This analysis provides a framework for understanding startup ecosystems, applied here to Hong Kong’s landscape. While Hong Kong demonstrates considerable strengths, my research identifies a critical pain point: a dearth of resources following firm formation and proof of concept, creating a notable gap between prototyping a technical concept and commercial viability. This shortfall leaves startups poorly positioned to attract traditional venture capital. Some high-level policy suggestions for strengthening the ecosystem include:
- Foster a Culture of Innovation: Promote a culture that embraces risk-taking and innovation through education, public campaigns, and support for entrepreneurial activities in schools and universities. Look beyond Hong Kong for sources of technology that could be commercialized in the city. At the same time, provide a social and psychological “safety net” that reduces the personal cost of entrepreneurial failure.
- Establish a Clearinghouse for Innovation and Startup Support:Currently, the available resources for startups are not easily understood or accessible. Establish a physical center with a virtual element, staffed by human experts and supported by AI, where startup participants can learn about the resources at hand and how to utilize them.
- Promote Cross-University Collaboration: Avoid duplicating R&D efforts and create a pool of knowledge and intellectual property by uniting the “brain trusts” of different universities and research centers. Present it as a mutual gains partnership to overcome the “Not Invented Here” syndrome. Establish strong derisking programs that offer grants to help companies transition from TRL 5/6 to TRL 8, and staff evaluation committees with a mix of technologists and businesspeople.
- Bridge Industry-Startup Divide: Encourage collaborations between startups, academic institutions, and private industry to create structured pathways from prototypes to viable products. Build networks and connectivity to identify end-market opportunities.
- Support Market Expansion: Provide support for “global from day one” technology startups to expand into markets outside Hong Kong through trade missions, networking opportunities, and partnerships with overseas corporate partners. In particular, encourage collaborations with GBA corporations to tap neighboring markets.
[1] This mismatch between initial conditions and efforts to seed an ecosystem was not unique to Hong Kong and is quite widespread. See, for example, the Inter-American Development Bank report on establishing a startup ecosystem in Latin America: https://publications.iadb.org/en/best-practices-creating-venture-capital-ecosystem
[2] https://www.info.gov.hk/gia/general/202212/22/P2022122200213.htm
[3] Other recent work similar to this monograph include KPMG-Alibaba Entrepreneurs Fund’s Transforming Hong Kong through Entrepreneurship 2020; Transforming Hong Kong through Entrepreneurship 2018;
(with Professor Marta Dowejko at Hong Kong Baptist University); FoundersHK Internet Report 2023; and Our Hong Kong Foundation and Alibaba Entrepreneurs Fund’s Building Hong Kong as a Cradle for Successful Entrepreneurship.
[4] This particular version was first developed in Professor Andrew Hargadon’s center at UC Davis (https://innovate.ucdavis.edu/)
[5] Conversely, for software-centric technology startups, the phases can be much shorter, but equally as risky to the success of the enterprise.
[6] A related concept is the “the Chasm”, where companies are unable to move past early adopters of the product or service into mass market adoption and scale. This concept was popularized by Geoffrey Moore in his book “Crossing the Chasm”, 1991.
[7] Robert Hall and Susan Woodward, “The Burden of the Non-Diversifiable Risk of Entrepreneurship,” American Economic Review 100, no. 3 (2010): 1163–1194
[8] For a detailed review of startup failure, see Professor Tom Eisenmann’s research at HBS on the topic (www.whystartupsfail.com)
[9] A “unicorn” is a common term (coined by Aileen Lee of Cowboy Ventures) for a startup valued at over USD 1 billion.
[10] https://www.nasa.gov/directorates/somd/space-communications-navigation-program/technology-readiness-levels/
[11] Ramsden and Chowdhury popularized the concept in their book The Business Readiness Levels (2019). The BRL is based on the philosophies of Design Thinking and Lean Startups.
[12] TRL adapted from NASA guidelines, BRL adapted from Steve Blank’s Lean Launchpad course at Stanford, both captured in the State of Wyoming’s incubator, Impact 307 (https://impact307.org/)
[13] https://startupcommunityway.com/
[14] City University of Hong Kong (CityU), Hong Kong Baptist University (HKBU), Lingnan University (LU), The Chinese University of Hong Kong (CUHK), The Education University of Hong Kong (EdUHK), The Hong Kong Polytechnic University (PolyU), The Hong Kong University of Science and Technology (HKUST), and The University of Hong Kong (HKU).
[15] Although Hong Kong universities rank low on the patents per capita issued, the universities and their science and engineering departments have a high ranking in global university surveys, such as the QS survey (https://www.topuniversities.com/university-rankings).
[16] A topic for subsequent in-depth quantitative research.
[17] https://tec.hku.hk/
[18] https://cuhkinnovation.hk/en
[19] https://www.hkstp.org/en/programmes/incubation/incubation-programme
[20] https://www.cyberport.hk/en/cyberport_incubation_programme
[21] https://www.itf.gov.hk/en/raiseplus
[22] https://www.itf.gov.hk/en/funding-programmes/supporting-start-ups/tsssu/index.html
[23] https://www.fstb.gov.hk/en/financial_ser/hong-kong-growth-portfolio.htm
[24] https://www.hkic.org.hk/
[25] An exception is the InvestHK Innovation & Technology site (https://innotech.investhk.gov.hk/) but even that is geared for external actors, not local participants.
