Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Mavris, Dimitri N.; Committee Member: German, Brian J.; Committee Member: Osburg, Jan; Committee Member: Ruffin, Stephen M.; Committee Member: Schrage, Daniel P.. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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This dissertation studies firms' strategic interactions in anticipation of random service disruption following technology failure. In particular it is aimed at understanding how contracting decisions between a vendor and one or multiple clients affect the firms' subsequent decisions to ensure disruption response and recovery are managed as efficiently as possible. This dissertation consists of three studies that were written as standalone papers seeking to contribute to the literature on contract design and technology management in operations management. Together, the three studies justify the importance of structuring the right incentives to mitigate disruption risks. In the first study we contribute to this literature by means of an analytical model which we use to examine how a client and vendor should balance investments in response capacity when both parties' efforts are critical in resolving disruption and each may have different risk preferences. We study the difference in the client's optimal expected utility between a case in which investment in response capacity is observable and a case in which it is not and refer to the difference in outcomes between the two cases as the cost of complexity. Firstly, we show that the cost of complexity to the client is decreasing in the risk aversion of vendor but increasing in her own risk aversion. Secondly, we find that a larger difference in risk aversion between a client and vendor leads to underinvestment in system uptime in case the client's investment is observable, yet the opposite happens when the client’s investment is not observable. In the second study we further examine the context of the first study through a controlled experiment. We examine how differences in risk aversion and access to information on a contracting partner’s risk preferences interact in affecting contracting and investment decisions between the client and vendor. Comparing subject decisions with the conditionally optimal benchmarks we arrive at two observations that highlight possible heuristic decision biases. Firstly, subjects tend to set and hold on to an inefficiently high investment level even though it is theoretically optimal to adjust decisions under changing differences in risk preferences. Secondly, subjects tend to set and hold on to a penalty that is too high when interacting with more risk averse vendors and too low in case the vendor is equally risk averse. Furthermore, cognitive feedback on the vendor’s risk aversion appears to have counterproductive effects on subject’s performance in the experiment, suggesting cognitive overload can have a reinforcing effect on the heuristic decision biases observed. In the third study we construct a new analytical model to examine the effect of contract design on a provider's response capacity allocation in a setting where multiple clients may be disrupted and available response capacity is limited. The results show that while clients may be incentivized to identify and report network disruptions, competition for scarce emergency resources and the required investment in understanding their own exposure may incentivize clients to deliberately miscommunicate with the vendor.

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Der Erfolg von Innovationen ist unsicher. Wer Kapital in Innovationen investiert, möchte etwas über die Risiken wissen. Mit diesem Wissen können Fondsmanager von Venture-Capital-Gesellschaften ihre Investitionsentscheidung begründen und die Höhe ihrer Renditeforderung ermitteln. In der vorliegenden Arbeit wird untersucht, wie Patente über Investitionsrisiken von Venture-Capital-Beteiligungen informieren. Fondsmanager können die Patente der eigenen Portfoliounternehmen und die Patente der Wettbewerber nutzen, um systematisch Risiken in der Entwicklung ihrer Portfoliounternehmen zu erkennen und zu bewerten. Der Autor definiert und klassifiziert zunächst sowohl Patentdaten als auch Risiken. Er erklärt, wie die relevanten Informationen durch die Verknüpfung von Patentdaten, Risiken und Portfoliounternehmen entstehen und welche Rolle Indikatoren spielen. In der Hauptuntersuchung prüft er, durch welche Patentinformationen sich konkrete Gefahren erkennen lassen und welche Indikatoren sich zu diesem Zweck eignen. Für die Prüfung nutzt er in explorativer Weise die theoriebildende und empirische Literatur bisheriger Patentindikatorenforschung. Im Ergebnis zeigt sich, dass eine Reihe rechtlicher Risiken gut durch Patentinformationen erkennbar ist. Teilweise ist für ihre Bewertung jedoch nach wie vor qualitatives Fachwissen spezialisierter Patentanwälte unumgänglich. Risiken des technologischen Wandels lassen sich nach Meinung des Autors kaum durch Patentinformationen im Voraus erkennen. An einem Beispiel werden die theoretischen und methodischen Schwächen in der Literatur vorherrschender Technologielebenszyklusmodelle verdeutlicht. Wettbewerbsrisiken hingegen können mit Patentinformationen nicht nur gut erkannt werden, sondern die indizierenden Patendaten lassen sich auch statistisch gut erfassen, auswerten und direkt in Scoringmodelle übertragen. Abschließend hinterfragt der Autor kritisch die Zuverlässigkeit und Aussagekraft der Befunde durch grundlegende Klassifizierungsprobleme und gibt Anstöße für weiterführende Forschung auf dem Gebiet der Risiko- und Performancemessung von Venture-Capital-Investments. / The success of innovations is uncertain. People investing capital in innovations would like to know something about their risks. If fund managers of venture capital firms knew these risks, they would be able to justify their investment decisions and to determine the height of their claim for yield. In this thesis, the author examines how patents inform about investment risks of ven-ture capital participations. Fund managers can use those patents of their own portfo-lio companies and the patents of the competitors in order to recognize and evaluate risks systematically in the development of their ventures. First, the author defines and classifies both patent data and risks. He explains how the relevant information arises by linking patent data, risks and venture and he ex-plains the importance of indicators. In the main part of this thesis, he examines by which patent information concrete dangers could be recognized and which indicators are suitable to this purpose. For this examination, he uses theory grounding and em-pirical literature of past patent indicator research in an explorative way. It shows up that a couple of legal risks are well recognizable by patent information. However, in part, the qualitative knowledge of specialized patent lawyers is still needed. According to the author's opinion, risks of technological changes are hardly to recognize by patent information in advance. An example shows the theoretical and methodical weaknesses of the technology life cycle models, predominating in the lit-erature. However, competitive risks can be well recognized by patent information. Furthermore, the indicating patent data can be well seized statistically, evaluated and transferred directly in scoring models, too. Finally, the author discusses the reliability and explanatory power of the results using basic classification problems and gives hints for further research in the area of risk and performance measuring of venture capital investments.

Breakthrough innovations are vital for the global economy and even our survival as a species. They appear as creative leaps and insights without obvious connection to existing knowledge and are extremely valuable to organisations, giving them significant competitive advantage. Historiometric and psychopathological evidence shows that breakthrough innovations are often associated with individuals and affective dysfunction; yet innovation today is widely held to be an organisational phenomenon operationalised though a model of creativity based on positive affective experiences and group activities which may be particularly unsuited to innovative thinkers. Research upon which the current paradigm for creativity and innovation are based is detached from real world outcomes and has been challenged as to its validity. Little data exists outside of experiments or indirect observation of naturally occurring affective experiences and the mood-creativity-innovation link has yet to be proven; we still know very little about how breakthrough innovations occur. This unique study addresses this significant gap in innovation research with a two-year longitudinal case study of a breakthrough innovation being developed for a multi-national Fast-Moving Consumer Goods company. It followed the journey of a lone innovator and attempts to answer the research question: “Can a fear of failure lead to breakthrough innovation?” The innovation space was investigated from three perspectives: technology, organisation and innovator, to build a picture of the highly immersive and emotionally charged experience of innovating. Many new insights were gained, and with extensive support from literature, new tools for the management of technology and the interface between innovators and organisations were developed, along with ground-breaking research into the mood-creativity innovation link. These are delivered through a series of four journal papers. The key finding from this research has been the discovery of the innovation-wave, a phenomenon which for the first time provides evidence for the mood-creativity-innovation link; intimately connecting real-world creative efficacy with emotion and specifically a ‘fear of failure’. From this finding a new theory and psycho-cognitive model for a distinct form of creativity called innovative thinking, driven by negative affect (mood) and specifically suited to achieving a breakthrough innovation through overcoming apparently insoluble problems, was posited and a hypothesis proposed and tested using a sophisticated innovation simulation developed especially for this purpose. Evidence from the case study and later experiment provide support for the research question and the lone innovator. This study makes a unique contribution to our understanding of creativity and innovation which could have a significant impact on how both are researched, taught and managed in the future. Being able to understand and possibly manipulate the innovation-wave, if proven correct, could be vitally important for maximising the potential for creating breakthrough innovations to the benefit of us all.