Three Essays on Collective Forms of Organizing for Production and Innovation

This dissertation focuses on collective forms or organizing that through crowds or communities undertake production or innovation activities. Such organizations deviate from the traditional notions of hierarchy, authority, and control; however, they are still able to engage in production and innovation activities, directly competing with bureaucratic organizations. Specifically, this dissertation focuses on communities for production and crowds for innovation, adopting different theoretical angles. The first chapter of this thesis introduces the concept of collective organizations for innovation and production. I present a framework that comprises both traditional and modern collective organizations, such as producer cooperatives, user communities, crowdsourcing, and the most recent distributed ledgers, the base of cryptocurrencies. Chapter two and three concentrates on communities for production, more specifically, on the producer cooperativesâ cooperative-commercial hybrid nature. While chapter two focuses on the influence of organizational hybridity on market strategies and competitive behavior; chapter three analyzes the conditions under which hybrid organizations affect market competitive dynamics and institutions. These chapters speak not only to the literature on communities for production but also to other hybrid organizations, which instantiate different and potentially conflicting logics under the same organizational roof. Chapter four (with Gianluigi Viscusi and Christopher Tucci) focuses on crowds for innovation, investigating the differences between crowds and communities, and the various types of crowds governance modes, such as crowd-driven, crowd-based, and crowded. This chapter not only defines what is a crowd organization but also provides guidelines about how firms can govern crowds for knowledge generativity¿spontaneous innovation.

The organisation of science: topics, incentives and funding.

Omar Ballester Gonzalez

Ever since the links between the development of new technologies and economic growth became evident, researchers have attempted to study how the creation of knowledge fosters progress. If pushing the frontier of knowledge has an impact on progress and well-being, it is essential to pursue some form of science policy. Policymakers rely on the scholarly work of researchers in order to understand the likely impact of new policies and investments, and evaluate the state of the art in science and innovation policy. Therefore, the work of social scientists, economists of science and information scientists, among others, is vital to the characterisation, understanding and management of science. In recent years, the availability and quality of science data (including bibliographic data and metadata, funding, relational databases, ontologies and classifications) has boosted the empirical work in the depiction of the organisational structure of science. In turn, policy analysis has been able to accurately identify many unsuspected effects of past investments and policy decisions both at the macro and micro level. Using topic models, we develop a novel method for evaluating the robustness of different text-to-text similarity models. Employing that procedure, we find that the neural-network-based paragraph embeddings approach seems capable of providing statistically robust estimates of document--document similarities. Finding methods to estimate the similarity between individual publications is an area of long-standing interest in the information science and scientometrics communities. These techniques enable researchers to build indicators and classification methods based on the analysis of large text corpora. We show that the most widely used techniques suffer from inconsistencies upon retraining, and provide a procedure to evaluate and compare the quality of different methods, regardless of the data. Next, we present a game-theoretic model of rewards to scientific contributions. Our model of science may help explain the resulting social organisation of science from a simple social dilemma model. We model a researcher's payoff as a common-pool resource game, intrinsically connecting the appropriability of scientific output to a scientist's optimal strategy. This simple model of reward allocation sheds new light on a variety of behaviours that have been observed amongst researchers. Finally, we propose an empirical analysis of the relationship between basic knowledge generation and spillovers to innovation. Using the United States' 2001 ban on federal funding of human embryonic stem cells (hESC), we disentangle the effect that policy had on downstream innovation. We employ recently developed data on patent-to-scientific-article citations to measure the spillovers, and we characterise the causal impact of the policy on subsequent innovation with a difference-in-differences estimator. Our estimates suggest that in the years following the policy, scholarly publications subject to the ban received 65 to 80 per-cent fewer patent citations than the control group. We then apply topic modelling techniques to examine changes in the direction of science. In particular we build a topic-variety metric. Our findings show that variety decreased in the aftermath of the policy. Our results suggest that even the most modest policy changes have a profound impact on downstream innovation and the advancement at the frontier.

EPFL2020

The link between innovation and finance

Cristiano Zazzara

This thesis comprises three essays on the relationship between innovation and finance. Although previous research has acknowledged the multi-faceted nature of innovation, this thesis unpacks its constituent elements, compares alternative drivers of innovation — focusing on the role of financial variables —, and explores when each of these drivers is important relative to the others. Evidence is based on survey data on Italian manufacturing firms over the years 1995-2003. The main contribution of this dissertation is to show how innovation at the firm level varies across different dimensions, documenting several robust empirical regularities, which must be accounted for. The first essay explores the determinants of various characteristics on the propensity to innovate in the Italian manufacturing sector. First, we concentrate on firms characteristics, and include in the study age of firm, size of firm, export shares of revenues and group membership. Second, we examine industry characteristics, such as type of industry in terms of technology level and market concentration. We also test the impact of characteristics of the firm's geographical area, including an indicator of financial development for the firm region. We finally extend our model including financial variables at the firm level in order to evaluate the association between profitability & risk and innovation. The second essay further examines the determinants of innovation, focusing on why firms develop product innovations rather than process innovation, or product and process innovations simultaneously. Empirical studies have highlighted the different impact of product and process innovation on various factors (such as, for example, international competitiveness, the level of employment and the types of skills used, and on the profit rate of firms). However, little is known from either a theoretical or an empirical point of view about the determinants of these different types of innovation. The third essay examines the question of whether access to credit is empirically more difficult for innovative firms than for those undertaking traditional investment projects. The idea that market financing of innovative projects is likely to encounter severe obstacles is not new. Indeed, it dates back at least to Schumpeter's defence of monopoly power since it not only guarantees that innovative firms can internalise the benefits of their innovations, but also provides funding for future innovative projects. Testing this proposition requires information on the innovative content of a given firm and on the limits to borrowing it encounters. Using the above mentioned survey data, we are able to identify credit constrained firms and use this information to make inferences on bank's lending strategies towards firms whose investment projects differ according to expected return and riskiness.

EPFL2008

Technological innovation strategy in natural resource based industries

Bettina Lynda Bastian

This thesis analyses innovation and technology strategy within a primary industry, notably the upstream oil and gas industry. Industries that exploit and produce finite natural resources are challenged by specific external risks that do not receive much attention from management literature otherwise, especially with regard to organizational innovation behaviour, and thus merit such research focus. On one hand, primary sector firms are confronted with exhaustible nature of finite natural resources. On the other hand, those finite natural resources are fixed to certain locations and companies have to operate in numerous countries in order to exploit resource deposits. In this context, they are often confronted with tremendous socio-political constraints that may have a negative impact on their businesses. This research work raises questions specific to natural resource based industries, notably (1) how can firms defend or even expand their competitive position when they are challenged by the depletion of their core resources? How can firms compensate for an exhaustible resource? (2) How do we evaluate contingencies like political risk for competitive advantage and what role does innovation play in this context? This dissertation takes the format of a "compilation thesis", in this case, three compiled articles. Within the first paper we focus on the resource based view (RBV), a central theoretical approach in management science, which explains how unique firm resources and capabilities contribute to value creation and lead to sustained competitive advantage. We1 apply the assumptions of RBV to the context of finite natural resources and ask if its analytical power is sufficient to explain competitive advantage of companies active in the primary sector, such as hydrocarbon and ore production. Paper 2 analyses how firms respond to geophysical constraints, such as natural resource depletion, and how these depletion issues affect organizational capability building and operational performance in terms of resource exploration and recovery. Paper 3 asks if political risk as external threat influences firm technology and innovation strategies. We find that time horizons of political risk play an important role and analyse why mid-and long term threats positively influence the development of technology and innovation strategies. The dissertation makes several important contributions. First, it contributes to our understanding of innovation and technology strategy within a natural resource based industry. Second, the idea that finite natural resources with their exhaustible nature are different than the "usual" resources investigated by RBV is novel. Third, the analysis also shows how RBV applies to natural resources extracting industries, and how RBV would gain in explicatory power if it was able to integrate factors like "geophysical constraints" and 'exposure to political risk' into the approach. Fourth, the thesis applies RBV and capability approaches to the specific context of primary industries, which is important as it helps to extend the frameworks' usefulness. Fifth, the current thesis combines political risk theory and research on innovation and technology management, and answers why political risk influences firm strategies, differentiation, and entry into new fields. ______________________________ 1 I am going to use the personal pronoun "we" to refer to first person's actions or opinions in this paper. I do so because I want to acknowledge the contributory effort of all who provided ideas and support. Nevertheless, any errors and omissions are completely my own responsibility.

EPFL2009