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This work analyzes the saving and consumption behavior of agents faced with the possibility of unemployment in a dynamic and stochastic life cycle model. The intertemporal optimization is based on Dynamic Programming with a backward recursion algorithm. The implemented uncertainty is not based on income shocks as it is done in traditional life cycle models but uses Markov probabilities where the probability for the next employment status of the agent depends on the current status. The utility function used is a CRRA function (constant relative risk aversion), combined with a CES function (constant elasticity of substitution) and has several consumption goods, a subsistence level, money and a bequest function.
Media artists have been struggling for financial survival ever since media art came into being. The non-material value of the artwork, a provocative attitude towards the traditional arts world and originally anti-capitalist mindset of the movement makes it particularly difficult to provide a constructive solution. However, a cultural entrepreneurial approach can be used to build a framework in order to find a balance between culture and business while ensuring that the cultural mission remains the top priority.
The present thesis introduces an iterative expert-based Bayesian approach for assessing greenhouse gas (GHG) emissions from the 2030 German new vehicle fleet and quantifying the impacts of their main drivers. A first set of expert interviews has been carried out in order to identify technologies which may help to lower car GHG emissions and to quantify their emission reduction potentials. Moreover, experts were asked for their probability assessments that the different technologies will be widely adopted, as well as for important prerequisites that could foster or hamper their adoption. Drawing on the results of these expert interviews, a Bayesian Belief Network has been built which explicitly models three vehicle types: Internal Combustion Engine Vehicles (which include mild and full Hybrid Electric Vehicles), Plug-In Hybrid Electric Vehicles, and Battery Electric Vehicles. The conditional dependencies of twelve central variables within the BBN - battery energy, fuel and electricity consumption, relative costs, and sales shares of the vehicle types - have been quantified by experts from German car manufacturers in a second series of interviews. For each of the seven second-round interviews, an expert's individually specified BBN results. The BBN have been run for different hypothetical 2030 scenarios which differ, e.g., in regard to battery development, regulation, and fuel and electricity GHG intensities. The present thesis delivers results both in regard to the subject of the investigation and in regard to its method. On the subject level, it has been found that the different experts expect 2030 German new car fleet emission to be at 50 to 65% of 2008 new fleet emissions under the baseline scenario. They can be further reduced to 40 to 50% of the emissions of the 2008 fleet though a combination of a higher share of renewables in the electricity mix, a larger share of biofuels in the fuel mix, and a stricter regulation of car CO$_2$ emissions in the European Union. Technically, 2030 German new car fleet GHG emissions can be reduced to a minimum of 18 to 44% of 2008 emissions, a development which can not be triggered by any combination of measures modeled in the BBN alone but needs further commitment. Out of a wealth of existing BBN, few have been specified by individual experts through elicitation, and to my knowledge, none of them has been employed for analyzing perspectives for the future. On the level of methods, this work shows that expert-based BBN are a valuable tool for making experts' expectations for the future explicit and amenable to the analysis of different hypothetical scenarios. BBN can also be employed for quantifying the impacts of main drivers. They have been demonstrated to be a valuable tool for iterative stakeholder-based science approaches.
Within our research group Bayesian Risk Solutions we have coined the idea of a Bayesian Risk Management (BRM). It claims (1) a more transparent and diligent data analysis as well as (2)an open-minded incorporation of human expertise in risk management. In this dissertation we formulize a framework for BRM based on the two pillars Hardcore-Bayesianism (HCB) and Softcore-Bayesianism (SCB) providing solutions for the claims above. For data analysis we favor Bayesian statistics with its Markov Chain Monte Carlo (MCMC) simulation algorithm. It provides a full illustration of data-induced uncertainty beyond classical point-estimates. We calibrate twelve different stochastic processes to four years of CO2 price data. Besides, we calculate derived risk measures (ex ante/ post value-at-risks, capital charges, option prices) and compare them to their classical counterparts. When statistics fails because of a lack of reliable data we propose our integrated Bayesian Risk Analysis (iBRA) concept. It is a basic guideline for an expertise-driven quantification of critical risks. We additionally review elicitation techniques and tools supporting experts to express their uncertainty. Unfortunately, Bayesian thinking is often blamed for its arbitrariness. Therefore, we introduce the idea of a Bayesian due diligence judging expert assessments according to their information content and their inter-subjectivity.
Be Creative, Now!
(2018)
Purpose – This thesis set out to explore, describe, and evaluate the reality behind the rhetoric of freedom and control in the context of creativity. The overarching subject is concerned with the relationship between creativity, freedom, and control, considering freedom is also seen as an element of control to manage creativity.
Design/methodology/approach – In-depth qualitative data gathered from at two innovative start-ups. Two ethnographic studies were conducted. The data are based on participatory observations, interviews, and secondary sources, each of which included a three months field study and a total of 41 interviews from both organizations.
Findings – The thesis provides explanations for the practice of freedom and the control of creativity within organizations and expands the existing theory of neo-normative control. The findings indicate that organizations use complex control systems that allow a high degree of freedom that paradoxically leads to more control. Freedom is a cover of control, which in turn leads to creativity. Covert control even results in the responsibility to be creative outside working hours.
Practical implications – Organizations, which rely on creativity might use the results of this thesis. Positive workplace control of creativity provides both freedom and structure for creative work. While freedom leads to organizational members being more motivated and committing themselves more strongly to their and the organization’s goals, and a specific structure also helps to provide the requirements for creativity.
Originality/value – The thesis provides an insight into an approach to workplace control, which has mostly neglected in creativity research and proposes a modified concept of neo-normative control. It serves to provide a further understanding of freedom for creativity and to challenge the liberal claims of new control forms.
Entrepreneurship is known to be a main driver of economic growth. Hence, governments have an interest in supporting and promoting entrepreneurial activities. Start-up subsidies, which have been analyzed extensively, only aim at mitigating the lack of financial capital. However, some entrepreneurs also lack in human, social, and managerial capital. One way to address these shortcomings is by subsidizing coaching programs for entrepreneurs. However, theoretical and empirical evidence about business coaching and programs subsidizing coaching is scarce. This dissertation gives an extensive overview of coaching and is the first empirical study for Germany analyzing the effects of coaching programs on its participants. In the theoretical part of the dissertation the process of a business start-up is described and it is discussed how and in which stage of the company’s evolvement coaching can influence entrepreneurial success. The concept of coaching is compared to other non-monetary types of support as training, mentoring, consulting, and counseling. Furthermore, national and international support programs are described. Most programs have either no or small positive effects. However, there is little quantitative evidence in the international literature. In the empirical part of the dissertation the effectiveness of coaching is shown by evaluating two German coaching programs, which support entrepreneurs via publicly subsidized coaching sessions. One of the programs aims at entrepreneurs who have been employed before becoming self-employed, whereas the other program is targeted at former unemployed entrepreneurs. The analysis is based on the evaluation of a quantitative and a qualitative dataset. The qualitative data are gathered by intensive one-on-one interviews with coaches and entrepreneurs. These data give a detailed insight about the coaching topics, duration, process, effectiveness, and the thoughts of coaches and entrepreneurs. The quantitative data include information about 2,936 German-based entrepreneurs. Using propensity score matching, the success of participants of the two coaching programs is compared with adequate groups of non-participants. In contrast to many other studies also personality traits are observed and controlled for in the matching process. The results show that only the program for former unemployed entrepreneurs has small positive effects. Participants have a larger survival probability in self-employment and a larger probability to hire employees than matched non-participants. In contrast, the program for former employed individuals has negative effects. Compared to individuals who did not participate in the coaching program, participants have a lower probability to stay in self-employment, lower earned net income, lower number of employees and lower life satisfaction. There are several reasons for these differing results of the two programs. First, former unemployed individuals have more basic coaching needs than former employed individuals. Coaches can satisfy these basic coaching needs, whereas former employed individuals have more complex business problems, which are not very easy to be solved by a coaching intervention. Second, the analysis reveals that former employed individuals are very successful in general. It is easier to increase the success of former unemployed individuals as they have a lower base level of success than former employed individuals. An effect heterogeneity analysis shows that coaching effectiveness differs by region. Coaching for previously unemployed entrepreneurs is especially useful in regions with bad labor market conditions. In summary, in line with previous literature, it is found that coaching has little effects on the success of entrepreneurs. The previous employment status, the characteristics of the entrepreneur and the regional labor market conditions play a crucial role in the effectiveness of coaching. In conclusion, coaching needs to be well tailored to the individual and applied thoroughly. Therefore, governments should design and provide coaching programs only after due consideration.
The thesis assesses the contribution of technology option of Carbon Capture and Sequestration (CCS) to climate change mitigation. CCS means that CO2 is captured at large industrial facilities and sequestered in goelogical structures. The technology uses the endogenous growth model MIND. Herein the various climate change mitigation options of reducing economic growth, increasing energy efficiency, changing the energy mix and CCS are assessed simultaneously. An important question is whether CCS is a temporary or long-term solution. The results show that in the middle of the 21st century CCS has its peak contribution, which allows prolonged use of relatively cheap fossil energy carriers. However, this leads to delayed introduction of renewable energy carriers. The technology path ways are accombined with different costs of climate change mitigation. The use of CCS delays and reduces the costs of climate change mitigation. However, the delayed introduction of renewable energy carriers leads to reduced technological learning, which induces higher costs in the longer term. All in all the temporary use of CCS reduces the costs of climate change mitigation costs. The result is robust, which is tested with various uncertainty analysis.
Digital transformation (DT) has not only been a major challenge in recent years, it is also supposed to continue to enormously impact our society and economy in the forthcoming decade. On the one hand, digital technologies have emerged, diffusing and determining our private and professional lives. On the other hand, digital platforms have leveraged the potentials of digital technologies to provide new business models. These dynamics have a massive effect on individuals, companies, and entire ecosystems. Digital technologies and platforms have changed the way persons consume or interact with each other. Moreover, they offer companies new opportunities to conduct their business in terms of value creation (e.g., business processes), value proposition (e.g., business models), or customer interaction (e.g., communication channels), i.e., the three dimensions of DT. However, they also can become a threat for a company's competitiveness or even survival. Eventually, the emergence, diffusion, and employment of digital technologies and platforms bear the potential to transform entire markets and ecosystems.
Against this background, IS research has explored and theorized the phenomena in the context of DT in the past decade, but not to its full extent. This is not surprising, given the complexity and pervasiveness of DT, which still requires far more research to further understand DT with its interdependencies in its entirety and in greater detail, particularly through the IS perspective at the confluence of technology, economy, and society. Consequently, the IS research discipline has determined and emphasized several relevant research gaps for exploring and understanding DT, including empirical data, theories as well as knowledge of the dynamic and transformative capabilities of digital technologies and platforms for both organizations and entire industries.
Hence, this thesis aims to address these research gaps on the IS research agenda and consists of two streams. The first stream of this thesis includes four papers that investigate the impact of digital technologies on organizations. In particular, these papers study the effects of new technologies on firms (paper II.1) and their innovative capabilities (II.2), the nature and characteristics of data-driven business models (II.3), and current developments in research and practice regarding on-demand healthcare (II.4). Consequently, the papers provide novel insights on the dynamic capabilities of digital technologies along the three dimensions of DT. Furthermore, they offer companies some opportunities to systematically explore, employ, and evaluate digital technologies to modify or redesign their organizations or business models.
The second stream comprises three papers that explore and theorize the impact of digital platforms on traditional companies, markets, and the economy and society at large. At this, paper III.1 examines the implications for the business of traditional insurance companies through the emergence and diffusion of multi-sided platforms, particularly in terms of value creation, value proposition, and customer interaction. Paper III.2 approaches the platform impact more holistically and investigates how the ongoing digital transformation and "platformization" in healthcare lastingly transform value creation in the healthcare market. Paper III.3 moves on from the level of single businesses or markets to the regulatory problems that result from the platform economy for economy and society, and proposes appropriate regulatory approaches for addressing these problems. Hence, these papers bring new insights on the table about the transformative capabilities of digital platforms for incumbent companies in particular and entire ecosystems in general.
Altogether, this thesis contributes to the understanding of the impact of DT on organizations and markets through the conduction of multiple-case study analyses that are systematically reflected with the current state of the art in research. On this empirical basis, the thesis also provides conceptual models, taxonomies, and frameworks that help describing, explaining, or predicting the impact of digital technologies and digital platforms on companies, markets and the economy or society at large from an interdisciplinary viewpoint.
Advancing digitalization is changing society and has far-reaching effects on people and companies. Fundamental to these changes are the new technological possibilities for processing data on an ever-increasing scale and for various purposes. The availability of large and high-quality data sets, especially those based on personal data, is crucial. They are used either to improve the productivity, quality, and individuality of products and services or to develop new types of services. Today, user behavior is tracked more actively and comprehensively than ever despite increasing legal requirements for protecting personal data worldwide. That increasingly raises ethical, moral, and social questions, which have moved to the forefront of the political debate, not least due to popular cases of data misuse. Given this discourse and the legal requirements, today's data management must fulfill three conditions: Legality or legal conformity of use and ethical legitimacy. Thirdly, the use of data should add value from a business perspective. Within the framework of these conditions, this cumulative dissertation pursues four research objectives with a focus on gaining a better understanding of
(1) the challenges of implementing privacy laws,
(2) the factors that influence customers' willingness to share personal data,
(3) the role of data protection for digital entrepreneurship, and
(4) the interdisciplinary scientific significance, its development, and its interrelationships.
Although the search for promising business models (BMs) is crucial for every profit-oriented venture, searching for those challenges in particular entrepreneurs. Limited resources, missing expertise and absolute uncertainty call entrepreneurs to strongly rely on their cognition in searching for a promising BM. However, as prior studies have examined cognitive search activities in isolation and neglected cognitive differences, explanations of how cognitive factors affect the BM process and outcomes are thus far insufficient.
Addressing the overall question of how BMs emerge, the dissertation contributes to the cognitive perspective in entrepreneurship and BM research. Building on the dual-process theory from cognitive psychology, the micro-foundations of managerial decision-making and insights from framing literature, this dissertation explicitly investigates the impacts of different cognitive dispositions, search activities and visual framing effects. The core assumption is that cognitive dispositions and entrepreneurs’ searches for information determine their BM decision-making. Furthermore, BM visualisations have become popular instruments with which to explain and manage today’s complex business interactions. As they abstract from reality, they can also unfold impacts on the cognitive processes.
This dissertation offers new explanations to these aspects and consists of three studies and one reflective article. The first study explores the impacts of differences in search activities and cognitive dispositions in a qualitative study with 70 entrepreneurship students. The second qualitative study explores the cognitive impacts of 103 BM visualisations. Third, a quantitative PLS-SEM experiment with 197 entrepreneurs illuminates the link between BM visualisations and cognition. The reflective article expresses the results’ meaning for the teaching of BMs.
In sum, the studies have resulted in a new theory of stabilising factors explaining how cognitive dispositions, search activities and visual framing determine entrepreneurs’ decisions to imitate or deviate from existing BMs. It indicates that the decision depends on the context-dependent strategic orientation and cognitive disposition-dependent cognitive safety, that is the correspondence between characteristics of cognitive dispositions and search activities. Moreover, the studies identified five visual framing effects that are independent of cognitive dispositions and prior experiences. This provides fertile contributions to the literature on BM methods and how BM visualisations affect decisions. Most importantly, BM visualisations provide an emotionally stabilising function to rational entrepreneurs, a cognitively stabilising function to experiential participants and do not affect indifferent participants in general.
Consumer attitudes towards genetically modified foods in Europe : structure and changeability
(2004)
Genetically modified foods have been at the center of debate in European consumer policy in the last two decades. Although the quasi-moratorium has been lifted in May 2004 and the road to the market is in principle reopened, strategies for product introduction are lacking. The aim of the research is to assess potential barriers in the area of consumer acceptance and suggest ways in which they can be overcome. After a short history of the genetically modified foods debate in Europe, the existing literature is reviewed. Although previous research converges in its central results, issues that are more fundamental have remained unresolved. Based on classical approaches in attitude research and modern theories of social cognition, a general model of the structure, function and dynamics of whole systems of attitudes is developed. The predictions of the model are empirically tested based on an attitude survey (N = 2000) and two attitude change experiments (N = 1400 and N = 750). All three studies were conducted in parallel in four EU member states. The results show that consumer attitudes towards genetically modified foods are embedded into a structured system of general socio-political attitudes. The system operates as a schema through which consumers form global evaluations of the technology. Specific risk and benefit judgments are mere epiphenomena of this process. Risk-benefit trade-offs, as often presupposed in the literature, do not appear to enter the process. The attitudes have a value-expressive function; their purpose is not just a temporary reduction of complexity. These properties render the system utterly resistant to communicative interventions. At the same time, it exerts stong anchoring effects on the processing of new information. Communication of benefit arguments can trigger boomerang effects and backfire on the credibility of the communicator when the arguments contrast with preexisting attitudes held by the consumer. Only direct sensory experience with high-quality products can partially bypass the system and lead to the formation of alternative attitude structures. Therefore, the recommended market introduction strategy for genetically modified foods is the simultaneous and coordinated launch of many high-quality products. Point of sale promotions should be the central instrument. Information campaigns, on the other hand, are not likely to have an effect on the product and technology acceptance of European consumers.
This cumulative dissertation contains four self-contained articles which are related to EU regional policy and its structural funds as the overall research topic. In particular, the thesis addresses the question if EU regional policy interventions can at all be scientifically justified and legitimated on theoretical and empirical grounds from an economics point of view. The first two articles of the thesis (“The EU structural funds as a means to hamper migration” and “Internal migration and EU regional policy transfer payments: a panel data analysis for 28 EU member countries”) enter into one particular aspect of the debate regarding the justification and legitimisation of EU regional policy. They theoretically and empirically analyse as to whether regional policy or the market force of the free flow of labour (migration) in the internal European market is the better instrument to improve and harmonise the living and working conditions of EU citizens. Based on neoclassical market failure theory, the first paper argues that the structural funds of the EU are inhibiting internal migration, which is one of the key measures in achieving convergence among the nations in the single European market. It becomes clear that European regional policy aiming at economic growth and cohesion among the member states cannot be justified and legitimated if the structural funds hamper instead of promote migration. The second paper, however, shows that the empirical evidence on the migration and regional policy nexus is not unambiguous, i.e. different empirical investigations show that EU structural funds hamper and promote EU internal migration. Hence, the question of the scientific justification and legitimisation of EU regional policy cannot be readily and unambiguously answered on empirical grounds. This finding is unsatisfying but is in line with previous theoretical and empirical literature. That is why, I take a step back and reconsider the theoretical beginnings of the thesis, which took for granted neoclassical market failure theory as the starting point for the positive explanation as well as the normative justification and legitimisation of EU regional policy. The third article of the thesis (“EU regional policy: theoretical foundations and policy conclusions revisited”) deals with the theoretical explanation and legitimisation of EU regional policy as well as the policy recommendations given to EU regional policymakers deduced from neoclassical market failure theory. The article elucidates that neoclassical market failure is a normative concept, which justifies and legitimates EU regional policy based on a political and thus subjective goal or value-judgement. It can neither be used, therefore, to give a scientifically positive explanation of the structural funds nor to obtain objective and practically applicable policy instruments. Given this critique of neoclassical market failure theory, the third paper consequently calls into question the widely prevalent explanation and justification of EU regional policy given in static neoclassical equilibrium economics. It argues that an evolutionary non-equilibrium economics perspective on EU regional policy is much more appropriate to provide a realistic understanding of one of the largest policies conducted by the EU. However, this does neither mean that evolutionary economic theory can be unreservedly seen as the panacea to positively explain EU regional policy nor to derive objective policy instruments for EU regional policymakers. This issue is discussed in the fourth article of the thesis (“Market failure vs. system failure as a rationale for economic policy? A critique from an evolutionary perspective”). This article reconsiders the explanation of economic policy from an evolutionary economics perspective. It contrasts the neoclassical equilibrium notions of market and government failure with the dominant evolutionary neo-Schumpeterian and Austrian-Hayekian perceptions. Based on this comparison, the paper criticises the fact that neoclassical failure reasoning still prevails in non-equilibrium evolutionary economics when economic policy issues are examined. This is surprising, since proponents of evolutionary economics usually view their approach as incompatible with its neoclassical counterpart. The paper therefore argues that in order to prevent the otherwise fruitful and more realistic evolutionary approach from undermining its own criticism of neoclassical economics and to create a consistent as well as objective evolutionary policy framework, it is necessary to eliminate the equilibrium spirit. Taken together, the main finding of this thesis is that European regional policy and its structural funds can neither theoretically nor empirically be justified and legitimated from an economics point of view. Moreover, the thesis finds that the prevalent positive and instrumental explanation of EU regional policy given in the literature needs to be reconsidered, because these theories can neither scientifically explain the emergence and development of this policy nor are they appropriate to derive objective and scientific policy instruments for EU regional policymakers.
To reach its climate targets, the European Union has to implement a major sustainability transition in the coming decades. While the socio-technical change required for this transition is well discussed in the academic literature, the economics that go along with it are often reduced to a cost-benefit perspective of climate policy measures. By investigating climate change mitigation as a coordination problem, this thesis offers a novel perspective: It integrates the economic and the socio-technical dimension and thus allows to better understand the opportunities of a sustainability transition in Europe.
First, a game theoretic framework is developed to illustrate coordination on green or brown investment from an agent perspective. A model based on the coordination game "stag hunt" is used to discuss the influence of narratives and signals for green investment as a means to coordinate expectations towards green growth. Public and private green investment impulses – triggered by credible climate policy measures and targets – serve as an example for a green growth perspective for Europe in line with a sustainability transition. This perspective also embodies a critical view on classical analyses of climate policy measures.
Secondly, this analysis is enriched with empirical results derived from stakeholder involvement. In interviews and with a survey among European insurance companies, coordination mechanisms such as market and policy signals are identified and evaluated by their impact on investment strategies for green infrastructure. The latter, here defined as renewable energy, electricity distribution and transmission as well as energy efficiency improvements, is considered a central element of the transition to a low-carbon society.
Thirdly, this thesis identifies and analyzes major criticisms raised towards stakeholder involvement in sustainability science. On a conceptual level, different ways of conducting such qualitative research are classified. This conceptualization is then evaluated by scientists, thereby generating empirical evidence on ideals and practices of stakeholder involvement in sustainability science.
Through the combination of theoretical and empirical research on coordination problems, this thesis offers several contributions: On the one hand, it outlines an approach that allows to assess the economic opportunities of sustainability transitions. This is helpful for policy makers in Europe that are striving to implement climate policy measures addressing the targets of the Paris Agreement as well as to encourage a shift of investments towards green infrastructure. On the other hand, this thesis enhances the stabilization of the theoretical foundations in sustainability science. Therefore, it can aid researchers who involve stakeholders when studying sustainability transitions.
African states are often called corrupt indicating that the political system in Africa differs from the one prevalent in the economically advanced democracies. This however does not give us any insight into what makes corruption the ruling norm of African statehood. Thus we must turn to the overly neglected theoretical work on the political economy of Africa in order to determine how the poverty of governance in Africa is firmly anchored both in Africa’s domestic socioeconomic reality, as well as in the region’s role in the international economic order. Instead of focusing on increased monitoring, enforcement and formal democratic procedures, this book integrates economic analysis with political theory in order to arrive at a better understanding of the political-economic roots of corruption in Sub-Saharan Africa.
Creative intensive processes
(2023)
Creativity – developing something new and useful – is a constant challenge in the working world. Work processes, services, or products must be sensibly adapted to changing times. To be able to analyze and, if necessary, adapt creativity in work processes, a precise understanding of these creative activities is necessary. Process modeling techniques are often used to capture business processes, represent them graphically and analyze them for adaptation possibilities. This has been very limited for creative work. An accurate understanding of creative work is subject to the challenge that, on the one hand, it is usually very complex and iterative. On the other hand, it is at least partially unpredictable as new things emerge. How can the complexity of creative business processes be adequately addressed and simultaneously manageable? This dissertation attempts to answer this question by first developing a precise process understanding of creative work. In an interdisciplinary approach, the literature on the process description of creativity-intensive work is analyzed from the perspective of psychology, organizational studies, and business informatics. In addition, a digital ethnographic study in the context of software development is used to analyze creative work. A model is developed based on which four elementary process components can be analyzed: Intention of the creative activity, Creation to develop the new, Evaluation to assess its meaningfulness, and Planning of the activities arising in the process – in short, the ICEP model. These four process elements are then translated into the Knockledge Modeling Description Language (KMDL), which was developed to capture and represent knowledge-intensive business processes. The modeling extension based on the ICEP model enables creative business processes to be identified and specified without the need for extensive modeling of all process details. The modeling extension proposed here was developed using ethnographic data and then applied to other organizational process contexts. The modeling method was applied to other business contexts and evaluated by external parties as part of two expert studies. The developed ICEP model provides an analytical framework for complex creative work processes. It can be comprehensively integrated into process models by transforming it into a modeling method, thus expanding the understanding of existing creative work in as-is process analyses.
Culture-driven innovation
(2017)
This cumulative dissertation deals with the potential of underexplored cultural sources for innovation.
Nowadays, firms recognize an increasing demand for innovation to keep pace with an ever-growing dynamic worldwide competition. Knowledge is one of the most crucial sources and resource, while until now innovation has been foremost driven by technology. But since the last years, we have been witnessing a change from technology's role as a driver of innovation to an enabler of innovation. Innovative products and services increasingly differentiate through emotional qualities and user experience. These experiences are hard to grasp and require alignment in innovation management theory and practice.
This work cares about culture in a broader matter as a source for innovation. It investigates the requirements and fundamentals for "culture-driven innovation" by studying where and how to unlock cultural sources. The research questions are the following: What are cultural sources for knowledge and innovation? Where can one find cultural sources and how to tap into them?
The dissertation starts with an overview of its central terms and introduces cultural theories as an overarching frame to study cultural sources for innovation systematically. Here, knowledge is not understood as something an organization owns like a material resource, but it is seen as something created and taking place in practices. Such a practice theoretical lens inheres the rejection of the traditional economic depiction of the rational Homo Oeconomicus. Nevertheless, it also rejects the idea of the Homo Sociologicus about the strong impact of society and its values on individual actions. Practice theory approaches take account of both concepts by underscoring the dualism of individual (agency, micro-level) and structure (society, macro-level). Following this, organizations are no enclosed entities but embedded within their socio-cultural environment, which shapes them and is also shaped by them.
Then, the first article of this dissertation acknowledges a methodological stance of this dualism by discussing how mixed methods support an integrated approach to study the micro- and macro-level. The article focuses on networks (thus communities) as a central research unit within studies of entrepreneurship and innovation.
The second article contains a network analysis and depicts communities as central loci for cultural sources and knowledge. With data from the platform Meetup.com about events etc., the study explores which overarching communities and themes have been evolved in Berlin's start up and tech scene.
While the latter study was about where to find new cultural sources, the last article addresses how to unlock such knowledge sources. It develops the concept of a cultural absorptive capacity, that is the capability of organizations to open up towards cultural sources. Furthermore, the article points to the role of knowledge intermediaries in the early phases of knowledge acquisition. Two case studies on companies working with artists illustrate the roles of such intermediaries and how they support firms to gain knowledge from cultural sources.
Overall, this dissertation contributes to a better understanding of culture as a source for innovation from a theoretical, methodological, and practitioners' point of view. It provides basic research to unlock the potential of such new knowledge sources for companies - sources that so far have been neglected in innovation management.
Volatile supply and sales markets, coupled with increasing product individualization and complex production processes, present significant challenges for manufacturing companies. These must navigate and adapt to ever-shifting external and internal factors while ensuring robustness against process variabilities and unforeseen events. This has a pronounced impact on production control, which serves as the operational intersection between production planning and the shop- floor resources, and necessitates the capability to manage intricate process interdependencies effectively. Considering the increasing dynamics and product diversification, alongside the need to maintain constant production performances, the implementation of innovative control strategies becomes crucial.
In recent years, the integration of Industry 4.0 technologies and machine learning methods has gained prominence in addressing emerging challenges in production applications. Within this context, this cumulative thesis analyzes deep learning based production systems based on five publications. Particular attention is paid to the applications of deep reinforcement learning, aiming to explore its potential in dynamic control contexts. Analysis reveal that deep reinforcement learning excels in various applications, especially in dynamic production control tasks. Its efficacy can be attributed to its interactive learning and real-time operational model. However, despite its evident utility, there are notable structural, organizational, and algorithmic gaps in the prevailing research. A predominant portion of deep reinforcement learning based approaches is limited to specific job shop scenarios and often overlooks the potential synergies in combined resources. Furthermore, it highlights the rare implementation of multi-agent systems and semi-heterarchical systems in practical settings. A notable gap remains in the integration of deep reinforcement learning into a hyper-heuristic.
To bridge these research gaps, this thesis introduces a deep reinforcement learning based hyper- heuristic for the control of modular production systems, developed in accordance with the design science research methodology. Implemented within a semi-heterarchical multi-agent framework, this approach achieves a threefold reduction in control and optimisation complexity while ensuring high scalability, adaptability, and robustness of the system. In comparative benchmarks, this control methodology outperforms rule-based heuristics, reducing throughput times and tardiness, and effectively incorporates customer and order-centric metrics. The control artifact facilitates a rapid scenario generation, motivating for further research efforts and bridging the gap to real-world applications. The overarching goal is to foster a synergy between theoretical insights and practical solutions, thereby enriching scientific discourse and addressing current industrial challenges.
The business model has emerged as a construct to understand how firms drive innovation through emerging technologies. It is defined as the ‘architecture of the firm’s value creation, delivery and appropriation mechanisms’ (Foss & Saebi, 2018, p. 5). The architecture is characterized by complex functional interrelations between activities that are conducted by various actors, some within and some outside of the firm. In other words, a firm’s value architecture is embedded within a wider system of actors that all contribute to the output of the value architecture.
The question of what drives innovation within this system and how the firm can shape and navigate this innovation is an essential question within innova- tion management research. This dissertation is a compendium of four individual research articles that examine how the design of a firm’s value architecture can fa- cilitate system-wide innovation in the context of Artificial Intelligence and Block- chain Technology. The first article studies how firms use Blockchain Technology to design a governance infrastructure that enables innovation within a platform ecosystem. The findings propose a framework for blockchain-enabled platform ecosystems that address the essential problem of opening the platform to allow for innovation while also ensuring that all actors get to capture their share of the value. The second article analyzes how German Artificial Intelligence startups design their business models. It identifies three distinct types of startup with dif- ferent underlying business models. The third article aims to understand the role of a firm’s value architecture during the socio-technical transition process of Arti- ficial Intelligence. It identifies three distinct ways in which Artificial Intelligence startups create a shared understanding of the technology. The last article exam- ines how corporate venture capital units configure value-adding services for their venture portfolios. It derives a taxonomy of different corporate venture capital types, driven by different strategic motivations.
Ultimately, this dissertation provides novel empirical insights into how a firm’s value architecture determines it’s role within a wider system of actors and how that role enables the firm to facilitate innovation. In that way, it contributes to both business model and innovation management literature.
Digital inclusion
(2021)
In this thesis, we tackle two social disruptions: recent refugee waves in Germany and the COVID-19 pandemic. We focus on the use of information and communication technology (ICT) as a key means of alleviating these disruptions and promoting social inclusion. As social disruptions typically lead to frustration and fragmentation, it is essential to ensure the social inclusion of individuals and societies during such times.
In the context of the social inclusion of refugees, we focus on the Syrian refugees who arrived in Germany as of 2015, as they form a large and coherent refugee community. In particular, we address the role of ICTs in refugees’ social inclusion and investigate how different ICTs (especially smartphones and social networks) can foster refugees’ integration and social inclusion. In the context of the COVID-19 pandemic, we focus on the widespread unconventional working model of work from home (WFH). Our research here centers on the main constructs of WFH and the key differences in WFH experiences based on personal characteristics such as gender and parental status.
We reveal novel insights through four well-established research methods: literature review, mixed methods, qualitative method, and quantitative method. The results of our research have been published in the form of eight articles in major information systems venues and journals. Key results from the refugee research stream include the following: Smartphones represent a central component of refugee ICT use; refugees view ICT as a source of information and power; the social connectedness of refugees is strongly correlated with their Internet use; refugees are not relying solely on traditional methods to learn the German language or pursue further education; the ability to use smartphones anytime and anywhere gives refugees an empowering feeling of global connectedness; and ICTs empower refugees on three levels (community participation, sense of control, and self-efficacy).
Key insights from the COVID-19 WFH stream include: Gender and the presence of children under the age of 18 affect workers’ control over their time, technology usefulness, and WFH conflicts, while not affecting their WFH attitudes; and both personal and technology-related factors affect an individual’s attitude toward WFH and their productivity. Further insights are being gathered at the time of submitting this thesis.
This thesis contributes to the discussion within the information systems community regarding how to use different ICT solutions to promote the social inclusion of refugees in their new communities and foster an inclusive society. It also adds to the growing body of research on COVID-19, in particular on the sudden workplace transformation to WFH. The insights gathered in this thesis reveal theoretical implications and future opportunities for research in the field of information systems, practical implications for relevant stakeholders, and social implications related to the refugee crisis and the COVID-19 pandemic that must be addressed.
In Chapter 1 of the dissertation, the role of social networks is analyzed as an important determinant in the search behavior of the unemployed. Based on the hypothesis that the unemployed generate information on vacancies through their social network, search theory predicts that individuals with large social networks should experience an increased productivity of informal search, and reduce their search in formal channels. Due to the higher productivity of search, unemployed with a larger network are also expected to have a higher reservation wage than unemployed with a small network. The model-theoretic predictions are tested and confirmed empirically. It is found that the search behavior of unemployed is significantly affected by the presence of social contacts, with larger networks implying a stronger substitution away from formal search channels towards informal channels. The substitution is particularly pronounced for passive formal search methods, i.e., search methods that generate rather non-specific types of job offer information at low relative cost. We also find small but significant positive effects of an increase of the network size on the reservation wage. These results have important implications on the analysis of the job search monitoring or counseling measures that are usually targeted at formal search only. Chapter 2 of the dissertation addresses the labor market effects of vacancy information during the early stages of unemployment. The outcomes considered are the speed of exit from unemployment, the effects on the quality of employment and the short-and medium-term effects on active labor market program (ALMP) participation. It is found that vacancy information significantly increases the speed of entry into employment; at the same time the probability to participate in ALMP is significantly reduced. Whereas the long-term reduction in the ALMP arises in consequence of the earlier exit from unemployment, we also observe a short-run decrease for some labor market groups which suggest that caseworker use high and low intensity activation measures interchangeably which is clearly questionable from an efficiency point of view. For unemployed who find a job through vacancy information we observe a small negative effect on the weekly number of hours worked. In Chapter 3, the long-term effects of participation in ALMP are assessed for unemployed youth under 25 years of age. Complementary to the analysis in Chapter 2, the effects of participation in time- and cost-intensive measures of active labor market policies are examined. In particular we study the effects of job creation schemes, wage subsidies, short-and long-term training measures and measures to promote the participation in vocational training. The outcome variables of interest are the probability to be in regular employment, and participation in further education during the 60 months following program entry. The analysis shows that all programs, except job creation schemes have positive and long-term effects on the employment probability of youth. In the short-run only short-term training measures generate positive effects, as long-term training programs and wage subsidies exhibit significant locking-in'' effects. Measures to promote vocational training are found to increase the probability of attending education and training significantly, whereas all other programs have either no or a negative effect on training participation. Effect heterogeneity with respect to the pre-treatment level education shows that young people with higher pre-treatment educational levels benefit more from participation most programs. However, for longer-term wage subsidies we also find strong positive effects for young people with low initial education levels. The relative benefit of training measures is higher in West than in East Germany. In the evaluation studies of Chapters 2 and 3 semi-parametric balancing methods of Propensity Score Matching (PSM) and Inverse Probability Weighting (IPW) are used to eliminate the effects of counfounding factors that influence both the treatment participation as well as the outcome variable of interest, and to establish a causal relation between program participation and outcome differences. While PSM and IPW are intuitive and methodologically attractive as they do not require parametric assumptions, the practical implementation may become quite challenging due to their sensitivity to various data features. Given the importance of these methods in the evaluation literature, and the vast number of recent methodological contributions in this field, Chapter 4 aims to reduce the knowledge gap between the methodological and applied literature by summarizing new findings of the empirical and statistical literature and practical guidelines for future applied research. In contrast to previous publications this study does not only focus on the estimation of causal effects, but stresses that the balancing challenge can and should be discussed independent of question of causal identification of treatment effects on most empirical applications. Following a brief outline of the practical implementation steps required for PSM and IPW, these steps are presented in detail chronologically, outlining practical advice for each step. Subsequently, the topics of effect estimation, inference, sensitivity analysis and the combination with parametric estimation methods are discussed. Finally, new extensions of the methodology and avenues for future research are presented.
This dissertation consists of four self-contained papers that deal with the implications of financial market imperfections and heterogeneity. The analysis mainly relates to the class of incomplete-markets models but covers different research topics.
The first paper deals with the distributional effects of financial integration for developing countries. Based on a simple heterogeneous-agent approach, it is shown that capital owners experience large welfare losses while only workers moderately gain due to higher wages. The large welfare losses for capital owners contrast with the small average welfare gains from representative-agent economies and indicate that a strong opposition against capital market opening has to be expected.
The second paper considers the puzzling observation of capital flows from poor to rich countries and the accompanying changes in domestic economic development. Motivated by the mixed results from the literature, we employ an incomplete-markets model with different types of idiosyncratic risk and borrowing constraints. Based on different scenarios, we analyze under what conditions the presence of financial market imperfections contributes to explain the empirical findings and how the conditions may change with different model assumptions.
The third paper deals with the interplay of incomplete information and financial market imperfections in an incomplete-markets economy. In particular, it analyzes the impact of incomplete information about idiosyncratic income shocks on aggregate saving. The results show that the effect of incomplete information is not only quantitatively substantial but also qualitatively ambiguous and varies with the influence of the income risk and the borrowing constraint.
Finally, the fourth paper analyzes the influence of different types of fiscal rules on the response of key macroeconomic variables to a government spending shock. We find that a strong temporary increase in public debt contributes to stabilizing consumption and leisure in the first periods following the change in government spending, whereas a non-debt-intensive fiscal rule leads to a faster recovery of consumption, leisure, capital and output in later periods. Regarding optimal debt policy, we find that a debt-intensive fiscal rule leads to the largest aggregate welfare benefit and that the individual welfare gain is particularly high for wealth-poor agents.
This dissertation consists of five self-contained essays, addressing different aspects of career choices, especially the choice of entrepreneurship, under risk and ambiguity. In Chapter 2, the first essay develops an occupational choice model with boundedly rational agents, who lack information, receive noisy feedback, and are restricted in their decisions by their personality, to analyze and explain puzzling empirical evidence on entrepreneurial decision processes. In the second essay, in Chapter 3, I contribute to the literature on entrepreneurial choice by constructing a general career choice model on the basis of the assumption that outcomes are partially ambiguous. The third essay, in Chapter 4, theoretically and empirically analyzes the impact of media on career choices, where information on entrepreneurship provided by the media is treated as an informational shock affecting prior beliefs. The fourth essay, presented in Chapter 5, contains an empirical analysis of the effects of cyclical macro variables (GDP and unemployment) on innovative start-ups in Germany. In the fifth, and last, essay in Chapter 6, we examine whether information on personality is useful for advice, using the example of career advice.
Persistently high unemployment rates are a major threat to the social cohesion in many societies. To moderate the consequences of unemployment industrialized countries spend substantial shares of their GDP on labor market policies, while in recent years there has been a shift from passive measures, such as transfer payments, towards more activating elements which aim to promote the reintegration into the labor market. Although, there exists a wide range of evidence about the effects of traditional active labor market policies (ALMP) on participants’ subsequent labor market outcomes, a deeper understanding of the impact of these programs on the job search behavior and the interplay with long-term labor market outcomes is necessary. This allows policy makers to improve the design of labor market policies and the allocation of unemployed workers into specific programs. Moreover, previous studies have shown that many traditional ALMP programs, like public employment or training schemes, do not achieve the desired results. This underlines the importance of understanding the effect mechanisms, but also the need to develop innovative programs that are more effective. This thesis extends the existing literature with respect to several dimensions.
First, it analyzes the impact of job seekers’ beliefs about upcoming ALMPs programs on the effectiveness of realized treatments later during the unemployment spell. This provides important insights with respect to the job search process and relates potential anticipation effects (on the job seekers behavior before entering a program) to the vast literature evaluating the impact of participating in an ALMP program on subsequent outcomes. The empirical results show that training programs are more effective if the participants expect participation ex ante, while expected treatment effects are unrelated to the actual labor market outcomes of participants. A subsequent analysis of the effect mechanisms shows that job seekers who expect to participate also receive more information by their caseworker and show a higher willingness to adjust their search behavior in association with an upcoming ALMP program. The findings suggest that the effectiveness of training programs can be improved by providing more detailed information about the possibility of a future treatment early during the unemployment spell.
Second, the thesis investigates the effects of a relatively new class of programs that aim to improve the geographical mobility of unemployed workers with respect to the job search behavior, the subsequent job finding prospects and the returns to labor market mobility. To estimate the causal impact of these programs, it is exploited that local employment agencies have a degree of autonomy when deciding about the regional-specific policy mix. The findings show that the policy style of the employment agency indeed affects the job search behavior of unemployed workers. Job seekers who are assigned to agencies with higher preferences for mobility programs increase their search radius without affecting the total number of job applications. This shift of the search effort to distant regions leads to a higher probability to find a regular job and higher wages. Moreover, it is shown that participants in one of the subsidy programs who move to geographically distant region a earn significantly higher wages, end up in more stable jobs and face a higher long-run employment probability compared to non-participants.
Third, the thesis offers an empirical assessment of the unconfoundedness assumption with respect to the relevance of variables that are usually unobserved in studies evaluating ALMP programs. A unique dataset that combines administrative records and survey data allows us to observe detailed information on typical covariates, as well as usually unobserved variables including personality traits, attitudes, expectations, intergenerational information, as well as indicators about social networks and labor market flexibility. The findings show that, although our set of usually unobserved variables indeed has a significant effect on the selection into ALMP programs, the overall impact when estimating treatment effects is rather small.
Finally, the thesis also examines the importance of gender differences in reservation wages that allows assessing the importance of special ALMP programs targeting women. In particular, when including reservation wages in a wage decomposition exercise, the gender gap in realized wages becomes small and statistically insignificant. The strong connection between gender differences in reservation wages and realized wages raises the question how these differences in reservation wages are set in the first place. Since traditional covariates cannot sufficiently explain the gender gap in reservation wages, we perform subgroup analysis to better understand what the driving forces behind this gender gap are.
This thesis offers new insights on the effects of Start-Up Subsidies (SUS) for unemployed individuals as a special kind of active labor market program (ALMP) that aims to re-integrate individuals into the labor market via the route of self-employment. Moreover, this thesis contributes to the literature on methods for causal inference when the treatment variable is continuous rather than binary. For example, this is the case when individuals differ in their degree of exposure to a common treatment.
The analysis of the effects of SUS focuses on the main current German program called “Gründungszuschuss” (New Start-Up Subsidy, NSUS) after its reform in 2011. Average Effects on participants' labor market outcomes - as measured by employment and earnings - as well as subjective well-being are estimated mainly based on propensity score matching (PSM) techniques. PSM aims to achieve balance in terms of observed characteristics by matching participants with at least one comparable non-participant in terms of their probability to receive the treatment. This estimation strategy is valid as long as all relevant characteristics that explain selection patterns into treatment are observed and included in the estimation of the propensity score. To make our analysis as credible as possible, we control for a large vector of characteristics as observed through the combination of rich administrative data from the Federal Employment Agency as well as through survey data.
Chapters two to four of this thesis puts special emphasis on aspects regarding (the evaluation of) SUS programs that have received no or only limited attention thus far. The first aspect relates to the interplay of institutional details of the program and its effectiveness. So far, relatively little is known about the importance of SUS program features such as the duration of support. Second, there is no experimental benchmark evaluation of SUS available and thus, the reliability of non-experimental estimation techniques such as PSM is of crucial importance as estimates are biased when relevant confounders are omitted from the analysis. Third, there may be potentially detrimental effects of transitioning into (relatively risky) self-employment on subjective well-being among subsidized founders out of unemployment. These were to remain undetected if the analysis would focus exclusively on labor market outcomes of participants. The results indicate positive long-term effects of SUS participation on employment and earnings among participants. These effects are substantially larger than what estimated before the reform, indicating room for improvement in program design via changes in institutional details. Moreover, non-experimental estimates of treatment effects are remarkably robust to hidden confounding. Regarding subjective well-being, this thesis finds a positive long-run impact on job satisfaction and a detrimental effect on satisfaction with social security. The latter appears to be driven by adverse effects on social insurance contributions.
In chapter five, a novel automated covariate balancing technique for the estimation of causal effects in the context of continuous treatments is derived and assessed regarding its performance compared to other (automated) balancing techniques. Although binary research designs that only differentiate between participants and non-participants of some treatment remain the most-common case in empirical practice, many applications can be adapted to include continuous treatments as well. Often, this will allow for more meaningful estimates of causal effects in order to further improve the design of programs. In the context of SUS, one may further investigate the effects of the size of monetary support or its duration on participants' labor market outcomes. Both Monte-Carlo investigations and analysis of two well-known datasets suggests superior performance of the proposed Entropy Balancing for continuous treatments (EBCT) compared to other existing estimation strategies.
The promotion of self-employment as part of active labor market policies is considered to be one of the most important unemployment support schemes in Germany. Against this background the main part of this thesis contributes to the evaluation of start-up support schemes within ALMP. Chapter 2 and 4 focus on the evaluation of the New Start-up Subsidy (NSUS, Gründungszuschuss) in its first version (from 2006 to the end of 2011). The chapters offer an advancement of the evaluation of start-up subsidies in Germany, and are based on a novel data set of administrative data from the Federal Employment Agency that was enriched with information from a telephone survey. Chapter 2 provides a thorough descriptive analysis of the NSUS that consists of two parts. First, the participant structure of the program is compared with the one of two former programs. In a second step, the study conducts an in-depth characterization of the participants of the NSUS focusing on founding motives, the level of start-up capital and equity used as well as the sectoral distribution of the new business. Furthermore, the business survival, income situation of founders and job creation by the new businesses is analyzed during a period of 19 months after start-up. The contribution of Chapter 4 is to introduce a new explorative data set that allows comparing subsidized start-ups out of unemployment with non-subsidized business start-ups that were founded by individuals who were not unemployed at the time of start-up. Because previous evaluation studies commonly used eligible non-participants amongst the unemployed as control group to assess the labor market effects of the start-up subsidies, the corresponding results hence referred to the effectiveness of the ALMP measure, but could not address the question whether the subsidy leads to similarly successful and innovative businesses compared to non-subsidized businesses. An assessment of this economic/growth aspect is also important, since the subsidy might induce negative effects that may outweigh the positive effects from an ALMP perspective. The main results of Chapter 4 indicate that subsidized founders seem to have no shortages in terms of formal education, but exhibit less employment and industry-specific experience, and are less likely to benefit from intergenerational transmission of start-ups. Moreover, the study finds evidence that necessity start-ups are over-represented among subsidized business founders, which suggests disadvantages in terms of business preparation due to possible time restrictions right before start-up. Finally, the study also detects more capital constraints among the unemployed, both in terms of the availability of personal equity and access to loans. With respect to potential differences between both groups in terms of business development over time, the results indicate that subsidized start-ups out of unemployment face higher business survival rates 19 months after start-up. However, they lag behind regular business founders in terms of income, business growth, and innovation. The arduous data collection process for start-up activities of non-subsidized founders for Chapter 4 made apparent that Germany is missing a central reporting system for business formations. Additionally, the different start-up reporting systems that do exist exhibit substantial discrepancies in data processing procedures, and therefore also in absolute numbers concerning the overall start-up activity. Chapter 3 is therefore placed in front of Chapter 4 and has the aim to provide a comprehensive review of the most important German start-up reporting systems. The second part of the thesis consists of Chapter 5 which contributes to the literature on determinants of job search behavior of the unemployed individuals by analyzing the effectiveness of internet search with regard to search behavior of unemployed individuals and subsequent job quality. The third and final part of the thesis outlines why the German labor market reacted in a very mild fashion to the Great Recession 2008/09, especially compared to other countries. Chapter 6 describes current economic trends of the labor market in light of general trends in the European Union, and reveals some of the main associated challenges. Thereafter, recent reforms of the main institutional settings of the labor market which influence labor supply are analyzed. Finally, based on the status quo of these institutional settings, the chapter gives a brief overview of strategies to adequately combat the challenges in terms of labor supply and to ensure economic growth in the future.
Public debate about energy relations between the EU and Russia is distorted. These distortions present considerable obstacles to the development of true partnership. At the core of the conflict is a struggle for resource rents between energy producing, energy consuming and transit countries. Supposed secondary aspects, however, are also of great importance. They comprise of geopolitics, market access, economic development and state sovereignty. The European Union, having engaged in energy market liberalisation, faces a widening gap between declining domestic resources and continuously growing energy demand. Diverse interests inside the EU prevent the definition of a coherent and respected energy policy. Russia, for its part, is no longer willing to subsidise its neighbouring economies by cheap energy exports. The Russian government engages in assertive policies pursuing Russian interests. In so far, it opts for a different globalisation approach, refusing the role of mere energy exporter. In view of the intensifying struggle for global resources, Russia, with its large energy potential, appears to be a very favourable option for European energy supplies, if not the best one. However, several outcomes of the strategic game between the two partners can be imagined. Engaging in non-cooperative strategies will in the end leave all stakeholders worse-off. The European Union should therefore concentrate on securing its partnership with Russia instead of damaging it. Stable cooperation would need the acceptance that the partner may pursue his own goals, which might be different from one’s own interests. The question is, how can a sustainable compromise be found? This thesis finds that a mix of continued dialogue, a tit for tat approach bolstered by an international institutional framework and increased integration efforts appears as a preferable solution.
Fiscal federalism has been an important topic among public finance theorists in the last four decades. There is a series of arguments that decentralization of governments enhances growth by improving allocation efficiency. However, the empirical studies have shown mixed results for industrialized and developing countries and some of them have demonstrated that there might be a threshold level of economic development below which decentralization is not effective. Developing and transition countries have developed a variety of forms of fiscal decentralization as a possible strategy to achieve effective and efficient governmental structures. A generalized principle of decentralization due to the country specific circumstances does not exist. Therefore, decentralization has taken place in different forms in various countries at different times, and even exactly the same extent of decentralization may have had different impacts under different conditions. The purpose of this study is to investigate the current state of the fiscal decentralization in Mongolia and to develop policy recommendations for the efficient and effective intergovernmental fiscal relations system for Mongolia. Within this perspective the analysis concentrates on the scope and structure of the public sector, the expenditure and revenue assignment as well as on the design of the intergovernmental transfer and sub-national borrowing. The study is based on data for twenty-one provinces and the capital city of Mongolia for the period from 2000 to 2009. As a former socialist country Mongolia has had a highly centralized governmental sector. The result of the analysis below revealed that the Mongolia has introduced a number of decentralization measures, which followed a top down approach and were slowly implemented without any integrated decentralization strategy in the last decade. As a result Mongolia became de-concentrated state with fiscal centralization. The revenue assignment is lacking a very important element, for instance significant revenue autonomy given to sub-national governments, which is vital for the efficient service delivery at the local level. According to the current assignments of the expenditure and revenue responsibilities most of the provinces are unable to provide a certain national standard of public goods supply. Hence, intergovernmental transfers from the central jurisdiction to the sub-national jurisdictions play an important role for the equalization of the vertical and horizontal imbalances in Mongolia. The critical problem associated with intergovernmental transfers is that there is not a stable, predictable and transparent system of transfer allocation. The amount of transfers to sub-national governments is determined largely by political decisions on ad hoc basis and disregards local differences in needs and fiscal capacity. Thus a fiscal equalization system based on the fiscal needs of the provinces should be implemented. The equalization transfers will at least partly offset the regional disparities in revenues and enable the sub-national governments to provide a national minimum standard of local public goods.
Foresight in networks
(2021)
The goal of this dissertation is to contribute to the corporate foresight research field by investigating capabilities, practices, and challenges particularly in the context of interorganizational settings and networked organizations informed by the theoretical perspectives of the relational view and dynamic capabilities.
Firms are facing an increasingly complex environment and highly complex product and service landscapes that often require multiple organizations to collaborate for innovation and offerings. Public-private partnerships that are targeted at supporting this have been introduced by policy-makers in the recent past. One example for such a partnership is the European Institute of Innovation and Technology (EIT) with multiple Knowledge and Innovation Communities (KICs). The EIT has been initiated by the European Commission in 2008 with the ambition of addressing grand societal challenges, driving innovativeness of European companies, and supporting systemic change. The resulting network organizations are managed similarly to corporations with managers, boards, and firm-like governance structures. EIT Digital as one of the EIT KICs are a central case of this work.
Research in this dissertation was based on the expectation that corporate foresight activities will increasingly be embedded in such interorganizational settings and a) can draw on such settings for the benefit of themselves and b) may contribute to shared visions, trust building and planning in these network organizations. In this dissertation the EIT Digital (formerly EIT ICT Labs) is a central case, supplemented with insights from three additional cases. I draw on the rich theoretical understanding of the resource-based view, dynamic capabilities, and particularly the relational view to further the discussion in the field of corporate foresight—defined as foresight in organizations in contrast to foresight with a macro-economical perspective—towards a relational understanding. Further, I use and revisit Rohrbeck’s Maturity Model for the Future Orientation of Firms as conceptual frame for corporate foresight in interorganizational settings. The analyses—available as four individual publications complemented by on additional chapter—are designed as exploratory case studies based on multiple data sources including an interview series with 49 persons, two surveys (N=54, n=20), three supplementary interviews, access to key documents and presentations, and observation through participation in meetings and activities of the EIT Digital. This research setting allowed me to contribute to corporate foresight research and practice by 1) integrating relational constructs primarily drawn from the relational view and dynamic capabilities research into the corporate foresight research stream, 2) exploring and understanding capabilities that are required for corporate foresight in interorganizational and networked organizations, 3) discussing and extending the Maturity Model for network organizations, and 4) to support individual organizations to tie their foresight systems effectively to networked foresight systems.
Modern welfare states aim at designing unemployment insurance (UI) schemes which minimize the length of unemployment spells. A variety of institutions and incentives, which are embedded in UI schemes across OECD countries, reflect this attempt. For instance, job seekers entering UI are often provided with personal support through a caseworker. They also face the requirement to regularly submit a minimum number of job applications, which is typically enforced through benefit cuts in the case of non-compliance. Moreover, job seekers may systematically receive information on their re-employment prospects. As a consequence, UI design has become a complex task. Policy makers need to define not only the amount and duration of benefit payments, but also several other choice parameters. These include the intensity and quality of personal support through caseworkers, the level of job search requirements, the strictness of enforcement, and the information provided to unemployed individuals. Causal estimates on how these parameters affect re-employment outcomes are thus central inputs to the design of modern UI systems: how much do individual caseworkers influence the transition out of unemployment? Does the requirement of an additional job application translate into increased job finding? Do individuals behave differently when facing a strict versus mild enforcement system? And how does information on re-employment prospects influence the job search decision? This dissertation proposes four novel research designs to answer this question. Chapters one to three elaborate quasi-experimental identification strategies, which are applied to large-scale administrative data from Switzerland. They, respectively, measure how personal interactions with caseworkers (chapter one), the level of job search requirements (chapter two) and the strictness of enforcement (chapter three) affect re-employment outcomes. Chapter four proposes a structural estimation approach, based on linked survey and administrative data from Germany. It studies how over-optimism on future wage offers affects the decision to search for work, and how the provision of information changes this decision.
There are numerous situations in which people ask for something or make a request, e.g. asking a favor, asking for help or requesting compliance with specific norms. For this reason, how to ask for something in order to increase people’s willingness to fulfill such requests is one of the most important question for many people working in various different fields of responsibility such as charitable giving, marketing, management or policy making.
This dissertation consists of four chapters that deal with the effects of small changes in the decision-making environment on altruistic decision-making and compliance behavior. Most notably, written communication as an influencing factor is the focus of the first three chapters. The starting point was the question how to devise a request in order to maximize its chance of success (Chapter 1). The results of the first chapter originate the ideas for the second and third chapter. Chapter 2 analyzes how communication by a neutral third-party, i.e. a text from the experimenters that either reminds potential benefactors of their responsibility or highlights their freedom of choice, affects altruistic decision-making. Chapter 3 elaborates on the effect of thanking people in advance when asking them for help. While being not as closely related to the other chapters as the three first ones are, the fourth chapter deals as well with the question how compliance (here: compliance with norms and rules) is affected by subtle manipulations of the environment in which decisions are made. This chapter analyzes the effect of default settings in a tax return on tax compliance.
In order to study the research questions outlined above, controlled experiments were conducted. Chapter 1, which analyzes the effect of text messages on the decision to give something to another person, employs a mini-dictator game. The recipient sends a free-form text message to the dictator before the latter makes a binary decision whether or not to give part of her or his endowment to the recipient. We find that putting effort into the message by writing a long note without spelling mistakes increases dictators’ willingness to give. Moreover, writing in a humorous way and mentioning reasons why the money is needed pays off. Furthermore, men and women seem to react differently to some message categories. Only men react positively to efficiency arguments, while only women react to messages that emphasize the dictator’s power and responsibility.
Building on this last result, Chapter 2 attempts to disentangle the effect of reminding potential benefactors of their responsibility for the potential beneficiary and the effect of highlighting their decision power and freedom of choice on altruistic decision-making by studying the effects of two different texts on giving in a dictator game. We find that only men react positively to a text that stresses their responsibility for the recipient by giving more to her or him, whereas only women seem to react positively to a text that emphasizes their decision power and freedom of choice.
Chapter 3 focuses on the compliance with a request. In the experiment, participants are asked to provide a detailed answer to an open question. Compliance is measured by the effort participants spend on answering the question. The treatment variable is whether or not they see the text “thanks in advance.” We find that participants react negatively by putting less effort into complying with the request in response to the phrase “thanks in advance.”
Chapter 4 studies the effect of prefilled tax returns with mostly inaccurate default values on tax compliance. In a laboratory experiment, participants earn income by performing a real-effort task and must subsequently file a tax return for three consecutive rounds. In the main treatment, the tax return is prefilled with a default value, resulting from participants’ own performance in previous rounds, which varies in its relative size. The results suggest that there is no lasting effect of a default value on tax honesty, neither for relatively low nor relatively high defaults. However, participants who face a default that is lower than their true income in the first round evade significantly and substantially more taxes in this round than participants in the control treatment without a default.
Inequalities in health are a prevalent feature of societies. And as societies, we condemn inequalities that are rooted in immutable circumstances such as gender, race, and parental background. Consequently, policy makers are interested in measuring and understanding the causes of health inequalities rooted in circumstances. However, identifying causal estimates of these relationships is very ambitious for reasons such as the presence of confounders or measurement error in the data. This thesis contributes to this ambitious endeavour by addressing these challenges in four chapters.
In the first Chapter, I use 25 years of rich health information to describe three features of intergenerational health mobility in Germany. First, we describe the joint permanent health distribution of the parents and their children. A ten percentile increase in parental permanent health is associated with a 2.3 percentile increase in their child’s health. Second, a percentile point increase in permanent health ranks is associated with a 0.8% to 1.4% increase in permanent income for, both, children, and parents, respectively. Non-linearities in the association between permanent health and income create incentives to escape the bottom of the permanent health distribution. Third, upward mobility in permanent health varies with parental socio-economic status.
In the second Chapter, we estimate the effect of maternal schooling on children’s mental health in adulthood. Using the Socio-Economic Panel and the mental health measure based on the SF-12 questionnaire, we exploit a compulsory schooling law reform to identify the causal effect of maternal schooling on children’s mental health. While the theoretical considerations are not clear, we do not find that the mother’s schooling has an effect on the mental health of the children. However, we find a positive effect on children’s physical health operating mainly through physical functioning. In addition, albeit with the absence of a reduced-form effect on mental health, we find evidence that the number of friends moderates the relationship between maternal schooling and their children’s mental health.
In the third Chapter, against a background of increasing violence against non-natives, we estimate the effect of hate crime on refugees’ mental health in Germany. For this purpose, we combine two datasets: administrative records on xenophobic crime against refugee shelters by the Federal Criminal Office and the IAB-BAMF-SOEP Survey of Refugees. We apply a regression discontinuity design in time to estimate the effect of interest. Our results indicate that hate crime has a substantial negative effect on several mental health indicators, including the Mental Component Summary score and the Patient Health Questionnaire-4 score. The effects are stronger for refugees with closer geographic proximity to the focal hate crime and refugees with low country-specific human capital. While the estimated effect is only transitory, we argue that negative mental health shocks during the critical period after arrival have important long-term consequences.
In the last Chapter of this thesis, we investigate how the economic consequences of the pandemic and the government-mandated measures to contain its spread affect the self-employed – particularly women– in Germany. For our analysis, we use representative, real-time survey data in which respondents were asked about their situation during the COVID-19 pandemic. Our findings indicate that among the self-employed, who generally face a higher likelihood of income losses due to COVID-19 than employees, women are 35% more likely to experience income losses than their male counterparts. We do not find a comparable gender gap among employees. Our results further suggest that the gender gap among the self-employed is largely explained by the fact that women disproportionately work in industries that are more severely affected by the COVID-19 pandemic. Our analysis of potential mechanisms reveals that women are significantly more likely to be impacted by government-imposed restrictions, e.g., the regulation of opening hours. We conclude that future policy measures intending to mitigate the consequences of such shocks should account for this considerable variation in economic hardship.
Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions.
This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets.
Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information.
Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure.
Information as an envirommental policy instrument : a case study for the economics of Eco-Labeling
(2007)
Bad governance causes economic, social, developmental and environmental problems in many developing countries. Developing countries have adopted a number of reforms that have assisted in achieving good governance. The success of governance reform depends on the starting point of each country – what institutional arrangements exist at the out-set and who the people implementing reforms within the existing institutional framework are. This dissertation focuses on how formal institutions (laws and regulations) and informal institutions (culture, habit and conception) impact on good governance. Three characteristics central to good governance - transparency, participation and accountability are studied in the research.
A number of key findings were: Good governance in Hanoi and Berlin represent the two extremes of the scale, while governance in Berlin is almost at the top of the scale, governance in Hanoi is at the bottom. Good governance in Hanoi is still far from achieved. In Berlin, information about public policies, administrative services and public finance is available, reliable and understandable. People do not encounter any problems accessing public information. In Hanoi, however, public information is not easy to access. There are big differences between Hanoi and Berlin in the three forms of participation. While voting in Hanoi to elect local deputies is formal and forced, elections in Berlin are fair and free. The candidates in local elections in Berlin come from different parties, whereas the candidacy of local deputies in Hanoi is thoroughly controlled by the Fatherland Front. Even though the turnout of voters in local deputy elections is close to 90 percent in Hanoi, the legitimacy of both the elections and the process of representation is non-existent because the local deputy candidates are decided by the Communist Party.
The involvement of people in solving local problems is encouraged by the government in Berlin. The different initiatives include citizenry budget, citizen activity, citizen initiatives, etc. Individual citizens are free to participate either individually or through an association.
Lacking transparency and participation, the quality of public service in Hanoi is poor. Citizens seldom get their services on time as required by the regulations. Citizens who want to receive public services can bribe officials directly, use the power of relationships, or pay a third person – the mediator ("Cò" - in Vietnamese).
In contrast, public service delivery in Berlin follows the customer-orientated principle. The quality of service is high in relation to time and cost. Paying speed money, bribery and using relationships to gain preferential public service do not exist in Berlin.
Using the examples of Berlin and Hanoi, it is clear to see how transparency, participation and accountability are interconnected and influence each other. Without a free and fair election as well as participation of non-governmental organisations, civil organisations, and the media in political decision-making and public actions, it is hard to hold the Hanoi local government accountable.
The key differences in formal institutions (regulative and cognitive) between Berlin and Hanoi reflect the three main principles: rule of law vs. rule by law, pluralism vs. monopoly Party in politics and social market economy vs. market economy with socialist orientation.
In Berlin the logic of appropriateness and codes of conduct are respect for laws, respect of individual freedom and ideas and awareness of community development. People in Berlin take for granted that public services are delivered to them fairly. Ideas such as using money or relationships to shorten public administrative procedures do not exist in the mind of either public officials or citizens.
In Hanoi, under a weak formal framework of good governance, new values and norms (prosperity, achievement) generated in the economic transition interact with the habits of the centrally-planned economy (lying, dependence, passivity) and traditional values (hierarchy, harmony, family, collectivism) influence behaviours of those involved.
In Hanoi “doing the right thing” such as compliance with law doesn’t become “the way it is”.
The unintended consequence of the deliberate reform actions of the Party is the prevalence of corruption. The socialist orientation seems not to have been achieved as the gap between the rich and the poor has widened.
Good governance is not achievable if citizens and officials are concerned only with their self-interest. State and society depend on each other. Theoretically to achieve good governance in Hanoi, institutions (formal and informal) able to create good citizens, officials and deputies should be generated. Good citizens are good by habit rather than by nature.
The rule of law principle is necessary for the professional performance of local administrations and People’s Councils. When the rule of law is applied consistently, the room for informal institutions to function will be reduced.
Promoting good governance in Hanoi is dependent on the need and desire to change the government and people themselves. Good governance in Berlin can be seen to be the result of the efforts of the local government and citizens after a long period of development and continuous adjustment.
Institutional transformation is always a long and complicated process because the change in formal regulations as well as in the way they are implemented may meet strong resistance from the established practice. This study has attempted to point out the weaknesses of the institutions of Hanoi and has identified factors affecting future development towards good governance. But it is not easy to determine how long it will take to change the institutional setting of Hanoi in order to achieve good governance.
It is the intention of this study to contribute to further rethinking and innovating in the Microcredit business which stands at a turning point – after around 40 years of practice it is endangered to fail as a tool for economic development and to become a doubtful finance product with a random scope instead. So far, a positive impact of Microfinance on the improvement of the lives of the poor could not be confirmed. Over-indebtment of borrowers due to the pre-dominance of consumption Microcredits has become a widespread problem. Furthermore, a rising number of abusive and commercially excessive practices have been reported.
In fact, the Microfinance sector appears to suffer from a major underlying deficit: there does not exist a coherent and transparent understanding of its meaning and objectives so that Microfinance providers worldwide follow their own approaches of Microfinance which tend to differ considerably from each other.
In this sense the study aims at consolidating the multi-faced and very often confusingly different Microcredit profiles that exist nowadays. Subsequently, in this study, the Microfinance spectrum will be narrowed to one clear-cut objective, in fact away from the mere monetary business transactions to poor people it has gradually been reduced to back towards a tool for economic development as originally envisaged by its pioneers.
Hence, the fundamental research question of this study is whether, and under which conditions, Microfinance may attain a positive economic impact leading to an improvement of the living of the poor.
The study is structured in five parts: the three main parts (II.-IV.) are surrounded by an introduction (I.) and conclusion (V.). In part II., the Microfinance sector is analysed critically aiming to identify the challenges persisting as well as their root causes. In the third part, a change to the macroeconomic perspective is undertaken in oder to learn about the potential and requirements of small-scale finance to enhance economic development, particularly within the economic context of less developed countries. By consolidating the insights gained in part IV., the elements of a new concept of Microfinance with the objecitve to achieve economic development of its borrowers are elaborated.
Microfinance is a rather sensitive business the great fundamental idea of which is easily corruptible and, additionally, the recipients of which are predestined victims of abuse due to their limited knowledge in finance. It therefore needs to be practiced responsibly, but also according to clear cut definitions of its meaning and objectives all institutions active in the sector should be devoted to comply with. This is especially relevant as the demand for Microfinance services is expected to rise further within the years coming. For example, the recent refugee migration movement towards Europe entails a vast potential for Microfinance to enable these people to make a new start into economic life. This goes to show that Microfinance may no longer mainly be associated with a less developed economic context, but that it will gain importance as a financial instrument in the developed economies, too.
In recent years, entire industries and their participants have been affected by disruptive technologies, resulting in dramatic market changes and challenges to firm’s business logic and thus their business models (BMs). Firms from mature industries are increasingly realizing that BMs that worked successfully for years have become insufficient to stay on track in today’s “move fast and break things” economy. Firms must scrutinize the core logic that informs how they do business, which means exploring novel ways to engage customers and get them to pay. This can lead to a complete renewal of existing BMs or innovating completely new BMs.
BMs have emerged as a popular object of research within the last decade. Despite the popularity of the BM, the theoretical and empirical foundation underlying the concept is still weak. In particular, the innovation process for BMs has been developed and implemented in firms, but understanding of the mechanisms behind it is still lacking. Business model innovation (BMI) is a complex and challenging management task that requires more than just novel ideas. Systematic studies to generate a better understanding of BMI and support incumbents with appropriate concepts to improve BMI development are in short supply. Further, there is a lack of knowledge about appropriate research practices for studying BMI and generating valid data sets in order to meet expectations in both practice and academia.
This paper-based dissertation aims to contribute to research practice in the field of BM and BMI and foster better understanding of the BM concept and BMI processes in incumbent firms from mature industries. The overall dissertation presents three main results. The first result is a new perspective, or the systems thinking view, on the BM and BMI. With the systems thinking view, the fuzzy BM concept is clearly structured and a BMI framework is proposed. The second result is a new research strategy for studying BMI. After analyzing current research practice in the areas of BMs and BMI, it is obvious that there is a need for better research on BMs and BMI in terms of accuracy, transparency, and practical orientation. Thus, the action case study approach combined with abductive methodology is proposed and proven in the research setting of this thesis. The third result stems from three action case studies in incumbent firms from mature industries employed to study how BMI occurs in practice. The new insights and knowledge gained from the action case studies help to explain BMI in such industries and increase understanding of the core of these processes.
By studying these issues, the articles complied in this thesis contribute conceptually and empirically to the recently consolidated but still increasing literature on the BM and BMI. The conclusions and implications made are intended to foster further research and improve managerial practices for achieving BMI in a dramatically changing business environment.
Companies have a keen interest in developing skilled negotiators in order to improve their negotiation outcome. A crucial determinant of the negotiation outcome are negotiation styles that represent the negotiator’s actual behavior during the negotiation process. In this context, the author examines the variation in negotiation styles throughout the negotiation process, points out the relevance of the negotiator’s characteristics and situational context as determinants of negotiation styles, and emphasizes the importance not only of actual but also of perceived negotiation behavior. As a result, existing negotiation research is advanced as new perspectives on negotiation styles are offered to improve a negotiator’s performance.