Mixed Signals: Why investors may misjudge first time high technology founders

This paper seeks to explain an unexpected result of a previous quantitative study which suggested sub-optimal evaluation by investors of the human capital of first time high tech venture founders. A literature review revealed two possible reasons for this finding: biases/heuristics and signaling. Six investors across three countries (one venture capitalist and one business angel each from the US, UK and Israel) with experience in investing in early stage high technology ventures were interviewed using an identical semi-structured interview protocol. This research design is appropriate for research that seeks to reflect back unexpected findings of previous quantitative research on the subjects of research. Interviewees were first asked to state their own investment criteria, and then presented with the results of the quantitative study and asked for their views. Previous research suggesting a gap between in-use and espoused criteria, and extensive use of gut feeling in decision-making, was supported. Interviewees focused on harvest potential and de-emphasised measures of founder technology capability that predicted early survival and growth in the earlier study. The paper concludes by suggesting how investors might improve funding decisions in high tech ventures led by first-time entrepreneurs, noting the study's limitations and making recommendations for further research

Renewal of Patents and Government Financing

I apply a survival model to a detailed dataset of Swedish patents to estimate how different factors affect the likelihood of patent renewal. Since the owners know more about the patents than potential external financiers, there is a problem of asymmetric information. To overcome this, Sweden has for a long time relied on government support rather than private venture capital. The empirical results show that patents which have received soft government financing in the R&D-phase have a higher probability of expiring than patents without such financing. But patents that have received more market-oriented government loans during the commercialization phase are renewed for as long as other commercialized patents. This finding indicates that it is the financing terms rather than bad choices of projects that explain the low renewal of patents with government financing.Patents; Renewal; Government Financing; Survival Model

What qualities do government-owned venture capital investors seek in a new venture? A comparison of investment criteria across pre-seed, seed, and expansion stage startups

Private venture capital (VC) investors usually do not invest in early life-cycle stage startups such as seed and pre-seed companies, since investment size typically doesn’t reach investment thresholds. The entry of governments with fund managers to venture capital markets presents seed and pre-seed companies with the opportunity to receive funding. This paper examines the main investment preferences of Hungarian government-owned venture capital investors regarding pre-seed, seed, and expansion stage startups. Verbal protocol analysis enabled examination of the screening process in real-time in all three life-cycle stages. It is found that governmental VC funds mostly value financial indicators followed by market-related qualities while private VCs value these characteristics in alternate formation. However, in the pre-seed stage, the financial acumen and capabilities of management teams form the main criteria in similarity to angel investors. Governmental VCs also greatly seek innovational value in target firms

Steering Capital: Optimizing Financial Support for Innovation in Public Education

Examines efforts to align capital to education innovation and calls for clarity and agreement on problems, goals, and metrics; an effective R&D system; an evidence-based culture of continuous improvement; and transparent, comparable, and useful data

Inside the Philanthropic Venture Capital Investment Model: An exploratory comparative Study

Aquesta tesi doctoral és el primer estudio exploratori sobre el procés d'inversió dels inversors de capital risc filantròpic en empreses socials. El model, des del punt de vista del finançador, uneix els principis del model tradicional de capital risc amb objectius socials. A través de la provisió de capital i de serveis no-financers a empreses socials, el capital risc filantròpic dóna suport a les necessitats de sostenibilitat de les empreses en què inverteix amb l'objectiu d'afavorir els seus creixement i en últim maximitzar els seus impacte social. La hipòtesis bàsica del capital risc filantròpic és que els fons filantròpics han de ser dirigits a problemes socials importants per la qual cosa els finançadors han de esforçar-se de maximitzar l'impacta del seu finançament donant compte dels resultats a les parts interessades. Els inversors de capital risc filantròpic creuen que la sostenibilitat econòmic- financera de les empreses socials participades pugui ser l'enllaç entre creixement i maximització de l'impacta social: només si aquestes empreses són capaços de ser independents des del punt de vista econòmic, poden enfocar en el seu missió social i per tant maximitzar el seu impacte. De tota manera, la value proposition del model de capital risc filantròpic és fortament diferent de la del capital risc tradicional ja que el primer té l'objectiu de maximitzar l'impacta social, i el segon el rendiment financer de la inversió aquesta. És així clau entendre com les tècniques i l'estructura del procés d'inversió del capital risc es pugui adaptada en el cas del capital risc filantròpic. Basant-se en la teoria de les asimetries informatives i utilitzant una metodologia de recerca articulada en dos passos, aquesta recerca contribueix a la literatura existent de capital risc i emprenedoria social mostrant com problemes de selecciona adversa són gestionats en la fase de deal flow i selecció. A més, s'analitza també la manera com problemes de moral hazard impacten en la fase d'estructuració de la inversió i en la seva fase de post-investment. Els resultats indiquen que les inversions de capital risc filantròpic estan efectivament caracteritzades per un alt nivell de selecciona adversa que es gestiona amb una recerca proactiva de noves inversions i tenint en compte sobretot el factor humà. Al contrari, el moral hazard d'unes qüestió marginal en les fases de deal structuring i post-investment, amb els inversors que es aporten més com stewards de les empreses finançades que com a principals.Esta tesis doctoral es el primer estudio exploratorio sobre el proceso de inversión del capital riesgo filantrópico en empresas sociales. El modelo, desde el punto de vista del financiador, une los principios del modelo tradicional de capital riesgo con objetivos sociales. A través de la provisión de capital y de servicios no-financieros a empresas sociales, el capital riego filantrópico apoya las necesidades de sostenibilidad de las empresas en que invierte, con el objetivo de favorecer su crecimiento y como último objetivo maximizar su impacto social. La hipótesis básica del capital riesgo filantrópico es, que los fondos filantrópicos deben ser dirigidos a problemas sociales importantes por lo cual los financiadores tienen que esforzarse en maximizar el impacto de su financiación dando cuenta de los resultados a las partes interesadas. Los inversores de capital riesgo filantrópico creen que la sostenibilidad económico-financiera de las empresas sociales participadas puede ser el enlace entre crecimiento y maximización del impacto social: solo si estas empresas son capaces de ser independientes desde el punto de vista económico, pueden enfocarse en su misión social y por lo tanto maximizar su impacto. De todas formas, la value proposition del modelo de capital riesgo filantrópico es considerablemente distinta de la del capital riesgo tradicional ya que el primero tiene el objetivo de maximizar el impacto social, y el segundo el rendimiento financiero de la inversión misma. Es así clave entender como las técnicas y la estructura del proceso de inversión del capital riesgo se pueda adaptar en el caso del capital riesgo filantrópico. Basándose en la teoría de las asimetrías informativas y usando una metodología de análisis articulada en dos pasos, esta investigación contribuye a la literatura existente de capital riesgo y de iniciativas emprendedoras sociales demostrando, como problemas de selección adversa son gestionados en la fase de deal flow y selección de las inversiones. Además, se analiza también la manera en que problemas de comportamientos oportunistas impactan en la fase de estructuración de la inversión y en su fase de post-investment. Los resultados indican que las inversiones de capital riesgo filantrópico están efectivamente caracterizadas por un alto nivel de selección adversa que se gestiona con una búsqueda proactiva de nuevas inversiones y teniendo en cuenta sobre todo el factor humano. Al contrario, el problema de comportamientos oportunistas resulta ser una cuestión marginal en las fases de estructuración de la inversión y de post-investment, con los inversores que actúan mas como stewards de las empresas financiadas que como principales.This dissertation is a first exploratory study on philanthropic venture capital, a new and particular financing form available for social entrepreneurs that unites the profit-seeking investment principles characterizing the traditional venture capital investment model with social aims. The provision of capital and non-financial services to social enterprises are considered of key importance towards the maximizations of social impact as both elements are needs to enable social enterprises in becoming self-financially sustainable and thus able to successfully play in the marketplace. The main assumption underlying the philanthropic venture capital's value proposition is that size matters: funding growing social organizations is a sign of social success and relevance. The basic commitments are grounded in the belief that philanthropic funds need to be applied to important social problems and that funders must strive to maximize the social impact of their investment and only through growth the aim can be achieved. Philanthropic venture capitalists believe sustainability can be the link between growth and social impact maximization: if social enterprises are able to become self-financially sufficient, they can focus on their social mission. However, since the value proposition of the venture capital and philanthropic venture capital investment models are different, the key issue is understanding how the practices used in the former are modified by the latter. Grounded in an asymmetric information and stewardship theory framework and using a two step research design, I build on and contribute to previous work on venture capital and social entrepreneurship showing how adverse selection is mitigated in the deal flow and selection stages of the investment model. In addition to this, I also analyze how moral hazard issues shape the deal structuring and post-investment phases. Results indicate that philanthropic venture capital investments are indeed characterized by adverse selection which is managed through a proactive search of new deals which are then selected based on the human capital of the social entrepreneur. On the contrary, moral hazard tends to be a marginal issue in the deal structuring and post-investment phased of the investment, with investors acting as stewards of the organizations they back rather than principals

Driving venture capital funding efficiencies through data driven models. Why is this important and what are its implications for the startup ecosystem?

This thesis aims to test whether data models can fit the venture capital funding process better, and if they do fit, can they help improve the venture capital funding efficiency? Based on the reported results, venture capitalists can only see returns in 20% of their investments. The thesis argues that it is essential to help venture capital investment as it can help drive economic growth through investments in innovation. The thesis considers four startup scenarios and the related investment factors. The scenarios are a funded artificial intelligence startup seeking follow-on funding, a new startup seeking first funding, the survivability of a sustainability-focused startup, and the importance of patents for exit. Patents are a proxy for innovation in this thesis. Through quantitative analysis using generalized linear models, logit regressions, and t-tests, the thesis can establish that data models can identify the relative significance of funding factors. Once the factor significance is established, it can be deployed in a model. Building the machine learning model has been considered outside the scope of this thesis. A mix of academic and real-world research has been used for the data analysis of this thesis. Accelerators and venture capitalists also used some of the results to improve their own processes. Many of the models have shifted from a prediction to factor significance. This thesis implies that it could help venture capitalists plan for a 10% efficiency improvement. From an academic perspective, this study focuses on the entire life of a startup, from the first funding stage to the exit. It also links the startup ecosystem with economic development. Two additional factors from the study are the regional perspective of funding differences between Asia, Europe, and the US and that this study would include the recent economic sentiment. The impact of the funding slowdown has been measured through a focus on first funding and longitudinal validations of the data decision before the slowdown. Based on the results of the thesis, data models are a credible alternative and show significant correlations between returns and factors. It is advisable for a venture capitalist to consider these

Group decision-making models for venture capitalists: the PROMETHEE with hesitant fuzzy linguistic information

Venture capitalists (VCs) have long been preoccupied by the issue of selecting a promising start-up firm, whereas, ranking the available start-up firms is an effective way to solve this issue. In this paper, the PROMETHEE is chosen to be the fundamental ranking method. Also, the hesitant fuzzy linguistic term set is a suitable tool to simulate VCs’ evaluation information. Additionally, as the deepening of social division of labor and specialization of individuals, group decision making is famous for improving decision-making quality. Moreover, in the decision-making process, VCs exhibit behavioral characteristics which is depicted well by prospect theory that VCs are risk averse for gains and risk seeking for losses and rely on the transformed probability to make their decisions rather than unidimensional probability. Thus, a group prospect PROMETHEE with hesitant fuzzy linguistic information is constructed for VCs to make a better decision. Then, the proposed method is applied to rank start-up firms and the comparative analyses are made as well. It confirms that the group prospect PROMETHEE is better in describing the common behavioral characteristics of VCs and in enhancing the quality of evaluation

Innovation Options and Organizational Capabilities

Organizational capabilities, whether in product development, efficient production, or market access, provide firms with opportunities to achieve and maintain strategic advantages over competitors. Recently, many researchers have argued that certain organizational capabilities add to a firm’s value in the form of its yet-to-be realized opportunities for profitable investments. But do such capabilities help all firms and under all conditions? The objective of this paper is to develop a model that helps us better understand the factors that influence the value of future growth opportunities for the firm and the organizational capabilities required to realize those opportunities