Three Essays on Navigating the Stages in New Venture Creation

Starting a new venture is arguably an exciting journey into previously unknown territories. Since entrepreneurs, through their economic activities, are central to social prosperity, academic research has a strong interest to understand who those entrepreneurs are and what they do. Much is yet unknown about how entrepreneurs think and what behaviors emerge from their thought processes. Consequently, in this dissertation I set out to explore and provide new insights on behavior, cognitive processes, and managerial practices that entrepreneurs employ to navigate the demands and complexities of the venturing process. The first paper puts the aspiring entrepreneur center stage. Starting a new venture is an intentional activity; however, not everyone who exhibits the wish to start a new venture actually does so. For a long time, the entrepreneurship research community has clung to the notion that intention is the single best predictor for action. Yet, empirical evidence from large-scale studies indicates that this view may not reflect reality. Significant time lags exist between the intent to found a venture and actual pursuit, and high dropout rates hint that additional elements are necessary beyond intent. Our current understanding of entrepreneurial intention largely fails to predict when and under which circumstances aspiring entrepreneurs will actually implement their intentions. Consequently, this research addresses the question of which amongst those who aspire to become an entrepreneur is more likely to execute their entrepreneurial intentions. In order to answer that question, the paper builds on fragmented and disparate work of personality, cognition, affect, and self-regulatory mechanisms and develops a theoretical model that helps explain individual-level factors that enable the budding entrepreneur to cross the intent-action-gap and persevere in the venturing process. Paper 2 takes as a starting point the belief that resources are essential to the success of firms. To the extent that those resources are fungible, i.e. can be amended to several different services and linked to different market applications, they are an important driver of value creation and the trajectory of new firms. In fact, recent research highlights that new firms derive performance benefits when identifying multiple opportunities prior to market entry. However, it remains hitherto understudied as to which factors play a role in this process of leveraging technological competences. We approach this topic by focusing on the identification of new technology-market- linkages through person-resource-interaction. While previous research has predominantly studied the impact of the person in terms of competencies and prior knowledge, this paper looks at the resource and examines how resource properties shape the human perception of opportunity spaces. Building on 24 in-depth case studies of different early-stage technologies from the labs of EPFL, this study provides detailed insights on how differences in the value creation potential of resources emerge from the interplay between several factors pertinent to the resource itself and the subsequent human reasoning. This work contributes to the microfoundations of the resource-based view of the firm and thus has implications for several areas of research, most notably strategic management, organization and innovation studies, and entrepreneurship. Paper 3 finally shifts focus onto specific managerial practices. From the vantage point that firms develop market strategies and application portfolios built on technological resources, current research has yet to address how the strategic and practical needs of the firm align with the requirements of protecting the intellectual property and inventions comprising those resources and what means of protection provide optimal avenues for future exploitation. Traditionally, protecting IP is associated with patenting. However, the procedural requirements and the high cost of the patenting process often act as a barrier for small firms to obtain legal property rights. This puts them at a potential disadvantage in appropriating returns from their inventions. It is hence surprising how little is known, both in the practical and the research domains, as to the uses of IP defense regimes that combine patenting and non-patenting mechanisms, notably alternative disclosure through defensive publication. This paper advances a framework that helps identify under which circumstances firms may benefit from the strategic use of defensive publication in their IP management. Through survey data from a sample of 89 innovative European SMEs we provide initial empirical evidence on the prevalence of such complementary IP strategies, and thus prepare the ground for further detailed studies. This work advances current literature on IP management by SMEs, introducing the hitherto understudied mechanism of strategic disclosure, and it will ultimately help identify a potential source of performance differences of innovative SMEs. In summary, this dissertation takes up three interesting and hitherto understudied phenomena of the multi-faceted venturing process. Through cross-disciplinary theory- driven inquiry and multi-method approaches, this dissertation adds new perspectives and generates new insights that extend our understanding of how entrepreneurs think and act.

Innovation capacity of the agricultural sector: network of productive interactions, knowledge transfer and differentiation mechanisms

Camille Marguerite Aouinait

Economic growth is increasingly explained and driven by knowledge acquisition and firmsâ capabilities to adapt to new evolving situations to fit economic, societal and environmental frames. Strategic behavior of private companies in differentiating and promoting their products and services is crucial for their competitiveness. In parallel, public research performed at different territorial levels and by a high diversity of actors is a strategic source of key assets adding value to the firms. External actors operate in a non-linear structure allowing frequent feedback and interactive loops in order to optimise the replies to substantial problems and constantly valorise their resources. These features are explored in the thesis through different projects. This dissertation is motivated by international negotiations in the frame of the GATT agreements and bilaterally between the European Union and Switzerland that are going towards the breakdown of borders, threatening the competitiveness of the Swiss agriculture. Negative externalities will affect small firms composing this agricultural network. Thus, the dissertation is focusing on innovation as a strategic asset to maintain the competitiveness and differentiate the domestic agricultural products. The first research project concentrates on interactions occurring in the Swiss apricot network. We investigate the types of interactions producing innovations that come from different sources that are internal or external to the agricultural production supply chain. We use network theory to model the structure of the domain and understand what is inherent to innovation production thanks to collaborations through an empirical work. In the second research project, we examine whether there is a connection between the issues faced by small companies producing food and the innovative solutions and knowledge generated by research institutions. The importance of solutions to daily activities conducted by companies depends on the nature of the sector. Thus, research projects providing outputs like publications might not specifically target these issues. Moreover, access, awareness and affordability of innovations can be hindering factors for small firms composing a low-technology intensive sector. Gaps of knowledge transfer, innovation and implementation are identified in this setting. In the last research project, we address market failures hampering economic and strategic management decisions encountered in the agricultural sector. We empirically construct two case studies highlighting the necessity of intellectual appropriation mechanisms. We explore the use of patents and regional trademark to add value to the emblematic product of a small region. Organisational and marketing innovations have to be supported and diffused by key stakeholders, aiming a good communication based on criteria that take into account diverse interests of those stakeholders; consumers have to be involved in the innovation process. Furthermore, knowledge transfer, innovation generation, diffusion and implementation rely upon the will of stakeholders to take part in an efficient process of interactions and communication in order to produce and perform useful products and services. Practical implications are levered in the projects presented. Finally, digital technologies are efficient for information exchange and can decrease time and transaction costs. These technologies are explored as part of the solution to small firmsâ

EPFL2019

Three essays on the role of proximity in science and innovation

Stefano Horst Baruffaldi

This thesis proposes three studies that provide novel empirical evidence on how different types of proximity can affect innovation and science activities through various mechanisms and in different contexts. In the first study (second chapter of this thesis), in collaboration with Julio Raffo, we analyze the relationship between geography and the likelihood of duplication in inventive activities. We argue that the uneven diffusion of knowledge means that the duplication of inventions will not be randomly distributed geographically and over time. First, as knowledge diffuses over time and competitive incentives decrease, the probability of a claimed invention duplicating an existing one will decrease in the time distance between the two. Second, for recent and upcoming inventions, competitive incentives are high, and localized knowledge flows increase the probability of duplication. Therefore, over a brief time period, the probability of duplication decreases with geographic distance. Conversely, the duplication of less recent inventions is more likely to occur at long distances as a consequence of less awareness of a technology existing due to missing knowledge flows. We test our hypotheses on European Patent Office (EPO) patent bibliographical data on patent citation categories. Geographic distance matters significantly less in sectors in which patents are known to be more effective as a source of information such as discrete technologies. In the second study (third chapter), in collaboration with Annamaria Conti and Fabiana Visentin, we investigate the effects of professorsâ social proximity with external universities on the level of productivity of PhD students hired from these universities. Researchers hired from external environments tend to have high scientific productivity compared to those who completed their studies in the same institution where they are employed. In a population of 4,666 PhD students, we further study the scientific productivity of external students from professorsâ networks, defined as students with a master's degree from a different university from that of their PhD, and also from a university with which their supervisors' co-authors are affiliated. We find that these students are significantly more productive, both compared to other students with a master's degree from a different university, and to students with a master's degree from the same university as that of their PhD. In our analyses, we control for the heterogeneity of supervisors and the heterogeneity of institutions where the students obtained their master's degrees, including proxies for the specific relevance of these universities for a given supervisor. Thus, we conclude that professors hire students with higher scientific productivity from universities where their co-authors are affiliated. Additional analyses further suggest that the reduction of information asymmetries is the main mechanism to explain this finding. In the third study (fourth chapter), in collaboration with Guillaume Burghouwt, we investigate the role of interregional knowledge integration as a driver of firm innovative performance. We adopt an unbalanced panel of 3,871 innovative companies in Germany between 1992 and 2010, for a total of 15,819 observations, and we study their innovative productivity. [...]

EPFL2015

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

In this dissertation, I develop theory and evidence to argue that new technologies are central to how firms organize to create and capture value. I use computational methods such as reinforcement learning and probabilistic topic modeling to investigate three topics: the automation of routines, the organization of artificial intelligence (AI), and the evaluation of technology risk. Overall, I argue that new technologies are not a panacea for the firm but require deliberate strategic planning to manage the potential downsides of myopic automation, AI interdependencies, and the disclosure of technology risks.In the first essay, I argue that while automation can increase productivity by reducing the costs of coordinating individuals, the automation of routines can also incur an indirect opportunity cost due to slow adaptation to environmental change. I develop a reinforcement learning simulation to model the impact of automation on the returns from the division of labor in dynamic environments and to show how automation incurs opportunity costs through lost learning and slow adaptation. Moreover, automation can be suboptimal when it brings about myopic behavior, i.e. high returns from the division of labor in the short term, but negative returns in the long term. Given the simulation results, I argue that firms need dynamic routines to simultaneously balance learning and automation. I open-source the simulation platform as OrgSim-RL on GitHub.In the second essay, I argue that a data-driven culture - what I define as a Data Clan - can help to coordinate complex interdependencies between AI components within a firm. I analyze in-depth semi-structured interview data with a hierarchical stochastic block model (hSBM) and hand-coding to find that managers focus primarily on building a strong culture and establishing high-quality data assets when allocating resources to AI initiatives. Given the results, I inductively develop implications for theory and argue that the emergence of a Data Clan can be a governance mechanism to reduce coordination frictions and build a competitive advantage in the age of AI.In the third essay, I argue that investors require a higher initial return to take on more technology risk disclosure during an IPO. I quantify the magnitude of disclosed risk and the risk disclosure topics based on a latent Dirichlet allocation (LDA) topic model of IPO prospectus text and find a return-for-risk association between text-based technology risk disclosure and underpricing. The study also finds evidence that owning granted patents is associated with a lower return-for-risk association, suggesting that intellectual property allows the disclosure of risk without losing the competitive advantage. I open-source the code for quantifying risk disclosure as RiskyData-LDA on GitHub.In summary, this dissertation develops theory and finds evidence across three essays to argue that leveraging new technologies requires deliberate strategic planning to manage potential downsides of new technologies, such as the opportunity costs of automation, coordination costs, and costs associated with raising capital. The results suggest three mitigating solutions: dynamic routines to balance learning and automation, a Data Clan to improve coordination, and disclosure through patents to reduce underpricing.

EPFL2022