Innovation and new business through mutually beneficial collaboration and proactive procurement

ABSTRACT This dissertation focuses on new technology commercialization, innovation and new business development. Industry-based novel technology may achieve commercialization through its transfer to a large research laboratory acting as a lead user and technical partner, and providing the new technology with complementary assets and meaningful initial use in social practice. The research lab benefits from the new technology and innovation through major performance improvements and cost savings. Such mutually beneficial collaboration between the lab and the firm does not require any additional administrative efforts or funds from the lab, yet requires openness to technologies and partner companies that may not be previously known to the lab- Labs achieve the benefits by applying a proactive procurement model that promotes active pre-tender search of new technologies and pre-tender testing and piloting of these technological options. The collaboration works best when based on the development needs of both parties. This means that first of all the lab has significant engineering activity with well-defined technological needs and second, that the firm has advanced prototype technology yet needs further testing, piloting and the initial market and references to achieve the market breakthrough. The empirical evidence of the dissertation is based on a longitudinal multiple-case study with the European Laboratory for Particle Physics. The key theoretical contribution of this study is that large research labs, including basic research, play an important role in product and business development toward the end, rather than front-end, of the innovation process. This also implies that product-orientation and business-orientation can contribute to basic re-search. The study provides practical managerial and policy guidelines on how to initiate and manage mutually beneficial lab-industry collaboration and proactive procurement.

Evidence-based Economic Policy - Three Essays in Applied Microeconometrics

Over thirty years ago, Leamer (1983) - among many others - expressed doubts about the quality and usefulness of empirical analyses for the economic profession by stating that "hardly anyone takes data analyses seriously. Or perhaps more accurately, hardly anyone takes anyone else's data analyses seriously" (p.37). Improvements in data quality, more robust estimation methods and the evolution of better research designs seem to make that assertion no longer justifiable (see Angrist and Pischke (2010) for a recent response to Leamer's essay). The economic profes- sion and policy makers alike often rely on empirical evidence as a means to investigate policy relevant questions. The approach of using scientifically rigorous and systematic evidence to identify policies and programs that are capable of improving policy-relevant outcomes is known under the increasingly popular notion of evidence-based policy. Evidence-based economic policy often relies on randomized or quasi-natural experiments in order to identify causal effects of policies. These can require relatively strong assumptions or raise concerns of external validity. In the context of this thesis, potential concerns are for example endogeneity of policy reforms with respect to the business cycle in the first chapter, the trade-off between precision and bias in the regression-discontinuity setting in chapter 2 or non-representativeness of the sample due to self-selection in chapter 3. While the identification strategies are very useful to gain insights into the causal effects of specific policy questions, transforming the evidence into concrete policy conclusions can be challenging. Policy develop- ment should therefore rely on the systematic evidence of a whole body of research on a specific policy question rather than on a single analysis. In this sense, this thesis cannot and should not be viewed as a comprehensive analysis of specific policy issues but rather as a first step towards a better understanding of certain aspects of a policy question. The thesis applies new and innovative identification strategies to policy-relevant and topical questions in the fields of labor economics and behavioral environmental economics. Each chapter relies on a different identification strategy. In the first chapter, we employ a difference- in-differences approach to exploit the quasi-experimental change in the entitlement of the max- imum unemployment benefit duration to identify the medium-run effects of reduced benefit durations on post-unemployment outcomes. Shortening benefit duration carries a double- dividend: It generates fiscal benefits without deteriorating the quality of job-matches. On the contrary, shortened benefit durations improve medium-run earnings and employment possibly through containing the negative effects of skill depreciation or stigmatization. While the first chapter provides only indirect evidence on the underlying behavioral channels, in the second chapter I develop a novel approach that allows to learn about the relative impor- tance of the two key margins of job search - reservation wage choice and search effort. In the framework of a standard non-stationary job search model, I show how the exit rate from un- employment can be decomposed in a way that is informative on reservation wage movements over the unemployment spell. The empirical analysis relies on a sharp discontinuity in unem- ployment benefit entitlement, which can be exploited in a regression-discontinuity approach to identify the effects of extended benefit durations on unemployment and survivor functions. I find evidence that calls for an important role of reservation wage choices for job search be- havior. This can have direct implications for the optimal design of unemployment insurance policies. The third chapter - while thematically detached from the other chapters - addresses one of the major policy challenges of the 21st century: climate change and resource consumption. Many governments have recently put energy efficiency on top of their agendas. While pricing instru- ments aimed at regulating the energy demand have often been found to be short-lived and difficult to enforce politically, the focus of energy conservation programs has shifted towards behavioral approaches - such as provision of information or social norm feedback. The third chapter describes a randomized controlled field experiment in which we discuss the effective- ness of different types of feedback on residential electricity consumption. We find that detailed and real-time feedback caused persistent electricity reductions on the order of 3 to 5 % of daily electricity consumption. Also social norm information can generate substantial electricity sav- ings when designed appropriately. The findings suggest that behavioral approaches constitute effective and relatively cheap way of improving residential energy-efficiency.

Best practice report on policy learning infrastructures in innovative labour market policies

This report synthesizes the findings of 11 country reports on policy learning in labour market and social policies that were conducted as part of WP5 of the INSPIRES project, which is funded by the 7th Framework Program of the EU-Commission. Notably, this report puts forward objectives of policy learning, discusses tools, processes and institutions of policy learning and presents the impacts of various tools and structures of the policy learning infrastructure for the actual policy learning process. The report defines three objectives of policy learning: evaluation and assessment of policy effectiveness, vision building and planning, and consensus building. In the 11 countries under consideration, the tools and processes of the policy learning, infrastructure can be classified into three broad groups: public bodies, expert councils, and parties, interest groups and the private sector. Finally, we develop four recommendations for policy learning: Firstly, learning processes should keep the balance between centralisation and plurality. Secondly, learning processes should be kept stable beyond the usual political business cycles. Thirdly, policy learning tools and infrastructures should be sufficiently independent from political influence or bias. Fourth, Policy learning tools and infrastructures should balance out mere effectiveness, evaluation and vision building.