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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.
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.
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.
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 research focuses on empowering leadership, a leadership style that shares autonomy and responsibilities with the followers. Empowering leadership enhances the meaningfulness of work by fostering participation in decision-making, expressing confidence in high performance, and providing autonomy in target setting (Cheong, 2016). I examine how empowering leadership affects followers’ reflection. I used data from 528 individuals across 172 teams and found a positive relationship between empowering leadership and followers’ reflection. Followers’ reflection, in turn, is negatively associated with followers’ withdrawal, which mediates the beneficial effect of empowering leadership on leaders’ emotional exhaustion. As for the leaders, I propose that empowering leadership is negatively related also to leaders’ emotional exhaustion. This research broadens our understanding of empowering leadership's effects on both followers and leaders. Moreover, it integrates empowering leadership, leader emotional exhaustion, and burnout literature. Overall, empowering leadership strengthens members’ reflective attitudes and behaviors, which result in reduced withdrawal (and increased presence and contribution) in teams. Because the members contribute to team effort more, the leaders experience less emotional exhaustion. Hence, my work not only identifies new ways through which empowering leadership positively affects followers but also shows how these positive effects on followers benefit the leaders’ well-being.
Essays in labor economics
(2022)
This thesis offers insights into the process of workers decisions to invest into work-related training. Specifically, the role of personality traits and attitudes is analysed. The aim is to understand whether such traits contribute to an under-investment into training. Importantly, general and specific training are distinguished, where the worker’s productivity increases in many firms in the former and only in the current firm in the latter case. Additionally, this thesis contributes to the evaluation of the German minimum wage introduction in 2015, identifying causal effects on wages and working hours.
Chapters two to four focus on the work-related training decision. First, individuals with an internal locus of control see a direct link between their own actions and their labor market success, while external individuals connect their outcomes to fate, luck, and other people. Consequently, it can be expected that internal individuals expect higher returns to training and are, thus, more willing to participate. The results reflect this hypothesis with internal individuals being more likely to participate in general (but not specific) training. Second, training can be viewed either as a risky investment or as an insurance against negative labor income shocks. In both cases, risk attitudes are expected to play a role in the decision process. The data point towards risk seeking individuals being more likely to participate in general (but not specific) training, and thus, training being viewed on average as a risky investment. Third, job satisfaction influences behavioral decisions in the job context, where dissatisfied workers may react by neglecting their duties, improving the situation or quitting the job. In the first case, dissatisfied workers are expected to invest less in training, while the latter two reactions could lead to higher participation rates amongst dissatisfied workers. The results suggest that on average dissatisfied workers are less likely to invest into training than satisfied workers. However, closer inspections of quit intentions and different sources of dissatisfaction paint less clear pictures, pointing towards the complexity of the job satisfaction construct.
Chapters five and six evaluate the introduction of the minimum wage in Germany in 2015. First, in 2015 an increase in the growth of hourly wages can be identified as a causal effect of the minimum wage introduction. However, at the same time, a reduction in the weekly working hours results in an overall unchanged growth in monthly earnings. When considering the effects in 2016, the decrease in weekly working hours disappears, resulting in a significant increase in the growth of monthly earnings due to the minimum wage. Importantly, the analysis suggests that the increase in hourly wages was not sufficient to ensure all workers receiving the minimum wage. This points to non-compliance being an issue in the first years after the minimum wage introduction.