Narrow Results

Business cases and customer problem spaces are evolving quicker than ever before and more startups are moving to adopt the lean startup methodology to match this speed of changing customer needs. This phenomenon, however, comes with its own set of opportunities and challenges for startups to build great products, while catering to customer pain points. To this end, there is a need for a metrics framework which can help startups succeed in creating good software solutions and building successful business models around these solutions. Metrics can help measure the effectiveness of the product in relation to the customer problem and help drive key decisions in both the product and business aspects of the startup. This paper reviews current frameworks on metrics for software products, studies the appropriateness in the context of software startups and proposes a metrics framework to help provide good software experiences, while subsequently building good business models around these experiences. The framework is designed to cover aspects of both the product and business space, ranging from considerations of the problem space identification to the evolution of the solution. The proposed framework is validated using a case study approach of a successful startup. The framework aims to help startups in their journey to success by providing an end to end, structured approach to metric identification.

A*STAR and GE Healthcare to improve healthcare outcomes through next generation innovations.

Phylogica enters into research and licensing agreement with Genentech.

FUJIFILM Completes Acquisition of Kalon Biotherapeutics.

Bina Technologies acquired by Roche.

ONO and Gilead enter exclusive license agreement to develop BTK inhibitor for the treatment of B-cell malignancies and other diseases.

Uroplasty and Vision-Sciences to merge, creating medical device company.

Amgen joins with LabCentral to support life-sciences and biotech startups in Cambridge.

Temasek Life Sciences Laboratory appoints Prof Yu Hao as Executive Director.

SomaGenics receives $2,275,000 in NIH funding to develop its RNAi Therapeutics and microRNA Technologies.

Small business owners use a variety of bootstrap financing methods to acquire the needed resources necessary to survive and eventually grow their businesses. One such method is to lease equipment and/or machinery. Leasing is a viable alternative to bank financing and for small businesses, leasing is a flexible strategy to preserve cash. In this study, we analyze the impact of asset specificity and growth opportunities on leasing decisions of a large cohort of startup businesses. To test our hypotheses, we use a unique dataset provided by the Kauffman Foundation.¹ Our longitudinal analyses show that startups with unique/specific assets have a lower propensity to lease whereas startups with high growth opportunities are more likely to lease their assets. We also argue that the owners’ demographic and socioeconomic characteristics are likely to impact their individual risk-taking behavior. Thus, factors such as owners’ experience, education, age, gender, and race are likely to impact the decision to lease assets. Our results show that owners’ characteristics do have a significant impact on these decisions. The findings reveal that female and older entrepreneurs as well as highly educated owners are less likely to lease. Our work advances prior research on the determinants of leasing in large, publicly traded firms and provides additional insights on entrepreneurial bootstrapping.

Manufacturing is undergoing a deep model change due to the convergence of several forces: (a) the simultaneous emergence of new disruptive technologies, (b) the accelerated substitution of men by machines, (c) the restructuring of global competition, with the consolidation of some global manufacturing clusters, and (d) a new market dynamic dominated by a growing consumer power. Much has been said about how industries adapt to these forces (a widely known example is the so-called “industry 4.0” paradigm). Scholarly literature states that, in moments of accelerated technological change and industry effervescence, new technology-based firms play a critical role in reshaping the markets and reconfiguring competition. Yet, little has been said in the literature about the features of new manufacturing start-ups. Our aim is to explore the origins of the new technological firms that are emerging in the manufacturing industry. To do so, we have created a database of 184 manufacturing start-ups, incepted since 2013, and which have attracted some US$ 2.4 billion in total funding; of these firms, we have analyzed a set of 291 founders’ profiles, looking for their backgrounds and previous experiences. Our findings suggest that promising new manufacturing technology-based firms are created mainly by teams formed by experienced managers and experts with solid scientific or technological backgrounds.

The founders of startups in Sergipe state, Brazil, began to unite in 2012, with a purpose of strengthening the innovation ecosystem in the state. The aim of this paper was to deepen the knowledge about the entrepreneurs’ movement entitled “Caju Valley”, in order to propose measures to strengthen the group. From the analysis realized, it was possible to observe that the Caju Valley group, although being important to the startups’ ecosystem, still suffers due to the lack of balance between the various stakeholders, and also faces the lack of maturity of the entrepreneurs, timid or suspicious investors, accelerators without effective action and incubators with low effectivity.

This research aims to evaluate the impact of lean product development (LPD) and lean startup (LS) practices on startup performance. A survey with 114 responses from Brazilian startups in the Information Technology sector evaluated the direct effects of LPD and LS on organizational performance, as well as the potential cross-effects between them. The assumptions were validated using a structural equation modeling for data analysis, which confirms that the adoption of these methodologies has a positive significant impact on startup performance, especially the practices involving teamwork and the design of minimum viable products.

In order to achieve successful open innovation partnerships, small- and medium-sized enterprises (SMEs) need to choose very carefully whom they partner with. Open innovation has gained significant attention as a strategy for organizations to leverage external knowledge and resources to foster innovation and competitiveness. However, few studies have examined the dynamics of open innovation partnerships between startups and SMEs. This study adopts a qualitative research approach, employing multiple case studies to gather data. We mapped the reasons German medium-sized enterprises chose to partner with startups, enumerated the benefits and challenges they encountered during the projects, and uncovered the keystones of successful open innovation partnerships. Furthermore, our findings led to the discovery that startups can help SMEs to become more digital. Finally, we suggest future research topics in this field.

In spite of their significance, the analyses of public subsidies for startups have been scant in the scientific literature. The focus has been more on justifying or arguing against the state's intervention through the granting of subsidies. The main aim of these public policies is to create companies by disadvantaged groups. Looking at the data we observe that the aim was achieved. Given this evidence, this paper analyzes how public programs that promote the creation of companies affect those companies' survival and net profits over a period of five years. Using a bivariate probit econometric model for a sample of businesses in a particular region of Spain, the results do not reveal the existence of differences, in terms of survival and profits, between companies created with and without public subsidies. The results do not support the arguments for or against the effectiveness of public programs, because subsidized companies neither survive longer nor have less net profits than unsubsidized companies.

Young companies need support concerning decisions related to intellectual properties. Entrepreneurs can resort to a menu of strategies, not only patenting. First, we explore the literature on standardisation and patenting and relate it to entrepreneurship to identify the internal and external influencing factors as well as the motives and risks related to decision making. Then, we conduct five case studies to explore these influencing factors, while trying to reconstruct the decision making process. We find five main factors: technology, resources, knowledge protection vs. knowledge diffusion, need for partnerships, and pace of innovation. Companies should use patents when their technology is patentable and knowledge protection is perceived essential. Standardisation is suitable when knowledge diffusion is more important than protection, and companies look for establishing new partnerships. These insights are integrated into a decision tree that provides guidance to young entrepreneurs to make an informed decision regarding intellectual properties.

Although it is argued that competitiveness and successful performance in the long term is facilitated if ventures engage in innovations in diverse domains (e.g., product, process, production, administration, etc.), the development of diversified innovation has been rarely analysed. As the entrepreneurs’ initial motivations to startup are likely to influence their subsequent entrepreneurial behaviour, this study aims to explore whether and how entrepreneurial motivations affect diversified innovation behaviour in startups. Using data on over 48,000 French startups, we present novel insights into the consequences of entrepreneurial motivation for innovation behaviour. In fact, we find that distinct startup motivations can have different effects on the development of diverse innovations. As such, our findings contribute to extant research on innovation development of startups and advance the present understanding of the determinants of startups’ innovative behaviour.

Open innovation is an innovation framework proposing that established firms use external sources as pathways to new ideas, technologies, business models and markets. Within this framework, established companies can use startups, or young, growth-oriented business to help them achieve radical or breakthrough innovations. In this paper, we focus on established firms which use “corporate accelerators” to run fast-moving, competitive programs in which startup companies participate. Our purpose is to identify inhibitors to the collaboration between established firms and startups in these accelerator programs. We conducted 27 interviews with participants from startups, established companies using startups as innovators, and the accelerator management who provided the platform for this engagement. Our theoretical framework is the social realist theory of Margaret Archer. This provides a conceptualisation of the reflexivity of the participants and the “situational logic” of conflict and competition in which they find themselves. We found that collaboration will be inhibited by conflicts in basic beliefs, or propositions, about concepts such as authority, autonomy and risk, as well as competition for material resources and personal goals.

Being embedded in an open innovation (OI) ecosystem can be the road to success for startups. In order to survive and become competitive, they must collaborate with external partners. Not only could large corporations be suitable partners, but innovation with small and medium enterprises (SMEs) can be constructive and fruitful as well. Furthermore, accelerators, incubators and other institutions can offer value to startups. Despite this fact, little attention has been paid to startups and SMEs embedded in OI ecosystems, especially from their point of view. The aim of this paper is to fulfil this research gap and deliver empirical data about the benefits and challenges of an OI ecosystem orchestrated by a startup and to investigate the potential role of an SME in these ecosystems. To answer the research questions, a case study approach was used.

In recent years, the phenomenon of open innovation has been on the rise in established firms, especially in terms of collaboration with startups. While the success factors of open innovation endeavours have been researched intensively, how collaborations are established is not well understood. Furthermore, there is a lack of research regarding asymmetric partnerships in open innovation, occurring when incumbents and startups collaborate. This study used a qualitative research design to approach the question of how incumbents select startups as partners in open innovation. The data incorporate the perspectives of both incumbents and startups along with the views of external experts. The findings are consolidated into a process model of partner selection for open innovation.

In search of innovation, incumbent firms are leveraging the creativity, knowledge and capabilities of corporate accelerators and are boosting their innovation engines by collaborating with startups. While this form of collaboration network with its heterogeneous partners is theoretically compelling and growing in popularity practically, the majority of corporate accelerators fails to deliver the desired results. Existing research still lacks an in-depth exploration of corporate accelerators explaining and suggesting how failure and challenges of incumbent firms can be overcome. Twenty-eight semi-structured interviews were conducted with managers and innovation experts across industries and within one of Europe’s biggest corporate accelerators. This study contributes to the field of open innovation and collaboration networks by expanding our knowledge about challenges of corporate accelerators and in particular to decode the difficulties that occur during the different phases of accelerator programmes. Based on the findings, guidelines for practitioners are presented to enhance organisational learning and innovation performance for incumbent firms.

This study focuses on high-tech startups in the Norwegian context and investigates the use of data and/or big data to support validation at the early stage of development. Early-stage startups often fail due to lack of validation and incur loss to all the stakeholders involved in the process. Early validation through a lean or agile approach can help these young companies to manoeuvre through a turbulent external environment. The results from the study show that big data and/or data can act as a support at this stage but is not necessarily the sole solution to the problem. There are various barriers that need to be addressed for successful data-based validation. Based on multi-case study research method, this study proposes an early validation user guide (EVU) to overcome these barriers and make data adoption easier. The EVU can provide startups support to show how and when to use data and/or big data depending on the market context. The study thus contributes to the current body of knowledge of innovation and entrepreneurship concerning validation for early stage startups and can also guide practitioners in validating their startup ideas.

Startups play an important role in creating job opportunities and promoting economic stability, growth, and development. However, it is noted that most startups collapse within the first decade of operation, and those that continue to survive will remain small. The major cause of large-scale failure is primarily the difficulty in predicting the internal and external risk factors that influence the startups’ potential success. The techno-economic feasibility study in startup financing is an effective method to safeguard against such risks preventing startup failures and the wastage of valuable investment resources. This study aims to explore the significance and the essence of the techno-economic feasibility study in stepping up the growth and advancement prospects of startups. The study findings promote useful insights into the value of techno-economic feasibility methods in startups by scholars, professionals, entrepreneurs, investors, banks, and financial institutions and provide some policy recommendations.

In emerging and developing countries, the development of soft skills has been less emphasized. Attempts were made to get funding on the seed rounds by the founders, investors care the most to get the desired return on their investment, and employees are interested in securing their job compensation with minimum effort level. As a part of a firm’s culture, there are essential soft factors which can establish a strong drive for succeeding and creating a high-commitment culture between founders, investors, employees, which can shape a vibrant culture of survival, growth, and success in a firm. The present study aimed to evaluate financial toughness, share option, networking, and performance management. In fact, the main hypothesis is whether startups with these attributes rely less on external funding or not. After collecting data from active startups in the Iranian startup ecosystem, no evidence was available regarding a strong association between the existence of these soft factors in the firm and the firm’s survival/success rate.

In many Asian countries, we observe a rapid expansion of technology-oriented startups. Governments hope that these startups will boost economic growth, create jobs, and foster sustainable development. However, transforming an innovative idea into a successful business is not easy and is constrained by limited access to funding. We analyze access to funding for tech startups in four sectors — greentech, agritech, edtech, and healthtech — that are linked directly to the Sustainable Development Goals. The chapter focuses on four countries, Cambodia, India, Thailand, and Viet Nam, and includes insights from interviews with startups, incubators, and other players. We find that tech startups rely on an array of funding sources and that venture capital is not a common source. In addition, greentech and agritech startups produce products that require long-term support through the design, testing, prototyping, and certification stages. Such “patient capital” is in short supply. On the positive side, enterprises in development-oriented sectors can seek funds from impact investors and international development (aid) agencies.

India has the third-largest startup ecosystem in the world with an estimated 26,000 startups, 26 “unicorns” (startups valued at over US$1 billion), and US$36 billion in consolidated investments over 2017–2019. The ecosystem has expanded rapidly, mainly through private investments including seed, angel, venture capital, and private equity, along with technical support from incubators/accelerators, and public policy. On its part, the government has tried to create a conducive environment through its flagship Startup India initiative. With India pushing towards a knowledge-based, digital economy, the government is also attempting to deploy ICT infrastructure and provide policy support for enhanced e-governance, investments, and technology innovation through research and funding higher education to spur entrepreneurship and economic growth. Data suggest that the startup ecosystem is largely clustered in large (Tier 1) cities and states with financial depth, more so in IT-enabled sectors including e-commerce, transport, and finance. Despite the progress made so far, Indian startups face huge challenges, such as the unorganized and fragmented nature of consumer and business markets, lack of clear and transparent policy initiatives, lack of infrastructure and access to government incentives (e.g., tax breaks), lack of knowledge and exposure, and complexities in doing business. Increasing awareness of government initiatives and incentives, credit disbursement to priority sectors, promoting outreach and network benefits to Tier 2 and Tier 3 cities, as well as simplifying investment opportunities and taxation rules for foreign and domestic investors could improve opportunities for startups in India.

Manufacturing is undergoing a deep model change due to the convergence of several forces: (a) the simultaneous emergence of new disruptive technologies, (b) the accelerated substitution of men by machines, (c) the restructuring of global competition, with the consolidation of some global manufacturing clusters, and (d) a new market dynamic dominated by a growing consumer power. Much has been said about how industries adapt to these forces (a widely known example is the so-called “industry 4.0” paradigm). Scholarly literature states that, in moments of accelerated technological change and industry effervescence, new technology-based firms play a critical role in reshaping the markets and reconfiguring competition. Yet, little has been said in the literature about the features of new manufacturing start-ups. Our aim is to explore the origins of the new technological firms that are emerging in the manufacturing industry. To do so, we have created a database of 184 manufacturing start-ups, incepted since 2013, and which have attracted some US $2.4 billion in total funding; of these firms, we have analyzed a set of 291 founders’ profiles, looking for their backgrounds and previous experiences. Our findings suggest that promising new manufacturing technology-based firms are created mainly by teams formed by experienced managers and experts with solid scientific or technological backgrounds.