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Algorithmic management
(2022)
The organisation of legislative chambers and the consequences of parliamentary procedures have been among the most prominent research questions in legislative studies. Even though democratic elections not only lead to the formation of a government but also result in an opposition, the literature has mostly neglected oppositions and their role in legislative chambers. This paper proposes to fill this gap by looking at the legislative organisation from the perspective of opposition players. The paper focuses on the potential influence of opposition players in the policy-making process and presents data on more than 50 legislative chambers. The paper shows considerable variance of the formal power granted to opposition players. Furthermore, the degree of institutionalisation of opposition rights is connected to electoral systems and not necessarily correlated with other institutional characteristics such as regime type or the size of legislative chambers.
This article merges theoretical literature on non-controlling minority shareholdings (NCMS) in a coherent model to study the effects of NCMS on competition and collusion. The model encompasses both the case of a common owner holding shares of rival firms as well as the case of cross ownership among rivals. We find that by softening competition, NCMS weaken the sustainability of collusion under a greater variety of situations than was indicated by earlier literature. Such effects exist, in particular, in the presence of an effective competition authority.
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.
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.
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.
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.
Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.
Defining the metaverse
(2023)
The term Metaverse is emerging as a result of the late push by multinational technology conglomerates and a recent surge of interest in Web 3.0, Blockchain, NFT, and Cryptocurrencies. From a scientific point of view, there is no definite consensus on what the Metaverse will be like. This paper collects, analyzes, and synthesizes scientific definitions and the accompanying major characteristics of the Metaverse using the methodology of a Systematic Literature Review (SLR). Two revised definitions for the Metaverse are presented, both condensing the key attributes, where the first one is rather simplistic holistic describing “a three-dimensional online environment in which users represented by avatars interact with each other in virtual spaces decoupled from the real physical world”. In contrast, the second definition is specified in a more detailed manner in the paper and further discussed. These comprehensive definitions offer specialized and general scholars an application within and beyond the scientific context of the system science, information system science, computer science, and business informatics, by also introducing open research challenges. Furthermore, an outlook on the social, economic, and technical implications is given, and the preconditions that are necessary for a successful implementation are discussed.
Recent research suggests that design thinking practices may foster the development of needed capabilities in new digitalised landscapes. However, existing publications represent individual contributions, and we lack a holistic understanding of the value of design thinking in a digital world. No review, to date, has offered a holistic retrospection of this research. In response, in this bibliometric review, we aim to shed light on the intellectual structure of multidisciplinary design thinking literature related to capabilities relevant to the digital world in higher education and business settings, highlight current trends and suggest further studies to advance theoretical and empirical underpinnings. Our study addresses this aim using bibliometric methods—bibliographic coupling and co-word analysis as they are particularly suitable for identifying current trends and future research priorities at the forefront of the research. Overall, bibliometric analyses of the publications dealing with the related topics published in the last 10 years (extracted from the Web of Science database) expose six trends and two possible future research developments highlighting the expanding scope of the design thinking scientific field related to capabilities required for the (more sustainable and human-centric) digital world. Relatedly, design thinking becomes a relevant approach to be included in higher education curricula and human resources training to prepare students and workers for the changing work demands. This paper is well-suited for education and business practitioners seeking to embed design thinking capabilities in their curricula and for design thinking and other scholars wanting to understand the field and possible directions for future research.
Creative thinking is an indispensable cognitive skill that is becoming increasingly important. In the present research, we tested the impact of games on creativity and emotions in a between-subject online experiment with four conditions (N = 658). (1) participants played a simple puzzle game that allowed many solutions (priming divergent thinking); (2) participants played a short game that required one fitting solution (priming convergent thinking); (3) participants performed mental arithmetic; (4) passive control condition. Results show that divergent and convergent creativity were higher after playing games and lower after mental arithmetic. Positive emotions did not function as a mediator, even though they were also heightened after playing the games and lower after mental arithmetic. However, contrary to previous research, we found no direct effect of emotions, creative self-efficacy, and growth- vs. fixed on creative performance. We discuss practical implications for digital learning and application settings.
Current business organizations want to be more efficient and constantly evolving to find ways to retain talent. It is well established that visionary leadership plays a vital role in organizational success and contributes to a better working environment. This study aims to determine the effect of visionary leadership on employees' perceived job satisfaction. Specifically, it investigates whether the mediators meaningfulness at work and commitment to the leader impact the relationship. I take support from job demand resource theory to explain the overarching model used in this study and broaden-and-build theory to leverage the use of mediators.
To test the hypotheses, evidence was collected in a multi-source, time-lagged design field study of 95 leader-follower dyads. The data was collected in a three-wave study, each survey appearing after one month. Data on employee perception of visionary leadership was collected in T1, data for both mediators were collected in T2, and employee perception of job satisfaction was collected in T3. The findings display that meaningfulness at work and commitment to the leader play positive intervening roles (in the form of a chain) in the indirect influence of visionary leadership on employee perceptions regarding job satisfaction.
This research offers contributions to literature and theory by first broadening the existing knowledge on the effects of visionary leadership on employees. Second, it contributes to the literature on constructs meaningfulness at work, commitment to the leader, and job satisfaction. Third, it sheds light on the mediation mechanism dealing with study variables in line with the proposed model. Fourth, it integrates two theories, job demand resource theory and broaden-and-build theory providing further evidence. Additionally, the study provides practical implications for business leaders and HR practitioners.
Overall, my study discusses the potential of visionary leadership behavior to elevate employee outcomes. The study aligns with previous research and answers several calls for further research on visionary leadership, job satisfaction, and mediation mechanism with meaningfulness at work and commitment to the leader.
Background
Wearables, as small portable computer systems worn on the body, can track user fitness and health data, which can be used to customize health insurance contributions individually. In particular, insured individuals with a healthy lifestyle can receive a reduction of their contributions to be paid. However, this potential is hardly used in practice.
Objective
This study aims to identify which barrier factors impede the usage of wearables for assessing individual risk scores for health insurances, despite its technological feasibility, and to rank these barriers according to their relevance.
Methods
To reach these goals, we conduct a ranking-type Delphi study with the following three stages. First, we collected possible barrier factors from a panel of 16 experts and consolidated them to a list of 11 barrier categories. Second, the panel was asked to rank them regarding their relevance. Third, to enhance the panel consensus, the ranking was revealed to the experts, who were then asked to re-rank the barriers.
Results
The results suggest that regulation is the most important barrier. Other relevant barriers are false or inaccurate measurements and application errors caused by the users. Additionally, insurers could lack the required technological competence to use the wearable data appropriately.
Conclusion
A wider use of wearables and health apps could be achieved through regulatory modifications, especially regarding privacy issues. Even after assuring stricter regulations, users’ privacy concerns could partly remain, if the data exchange between wearables manufacturers, health app providers, and health insurers does not become more transparent.
Public administrations confront fundamental challenges, including globalization, digitalization, and an eroding level of trust from society. By developing joint public service delivery with other stakeholders, public administrations can respond to these challenges. This increases the importance of inter-organizational governance—a development often referred to as New Public Governance, which to date has not been realized because public administrations focus on intra-organizational practices and follow the traditional “governmental chain.”
E-government initiatives, which can lead to high levels of interconnected public services, are currently perceived as insufficient to meet this goal. They are not designed holistically and merely affect the interactions of public and non-public stakeholders. A fundamental shift toward a joint public service delivery would require scrutiny of established processes, roles, and interactions between stakeholders.
Various scientists and practitioners within the public sector assume that the use of blockchain institutional technology could fundamentally change the relationship between public and non-public stakeholders. At first glance, inter-organizational, joint public service delivery could benefit from the use of blockchain. This dissertation aims to shed light on this widespread assumption. Hence, the objective of this dissertation is to substantiate the effect of blockchain on the relationship between public administrations and non-public stakeholders.
This objective is pursued by defining three major areas of interest. First, this dissertation strives to answer the question of whether or not blockchain is suited to enable New Public Governance and to identify instances where blockchain may not be the proper solution. The second area aims to understand empirically the status quo of existing blockchain implementations in the public sector and whether they comply with the major theoretical conclusions. The third area investigates the changing role of public administrations, as the blockchain ecosystem can significantly increase the number of stakeholders.
Corresponding research is conducted to provide insights into these areas, for example, combining theoretical concepts with empirical actualities, conducting interviews with subject matter experts and key stakeholders of leading blockchain implementations, and performing a comprehensive stakeholder analysis, followed by visualization of its results.
The results of this dissertation demonstrate that blockchain can support New Public Governance in many ways while having a minor impact on certain aspects (e.g., decentralized control), which account for this public service paradigm. Furthermore, the existing projects indicate changes to relationships between public administrations and non-public stakeholders, although not necessarily the fundamental shift proposed by New Public Governance. Lastly, the results suggest that power relations are shifting, including the decreasing influence of public administrations within the blockchain ecosystem. The results raise questions about the governance models and regulations required to support mature solutions and the further diffusion of blockchain for public service delivery.
We collect a network dataset of tenured economics faculty in Austria, Germany and Switzerland. We rank the 100 institutions included with a minimum violation ranking. This ranking is positively and significantly correlated with the Times Higher Education ranking of economics institutions. According to the network ranking, individuals on average go down about 23 ranks from their doctoral institution to their employing institution. While the share of females in our dataset is only 15%, we do not observe a significant gender hiring gap (a difference in rank changes between male and female faculty). We conduct a robustness check with the Handelsblatt and the Times Higher Education ranking. According to these rankings, individuals on average go down only about two ranks. We do not observe a significant gender hiring gap using these two rankings (although the dataset underlying this analysis is small and these estimates are likely to be noisy). Finally, we discuss the limitations of the network ranking in our context.
Sustainable urban growth
(2022)
This dissertation explores the determinants for sustainable and socially optimalgrowth in a city. Two general equilibrium models establish the base for this evaluation, each adding its puzzle piece to the urban sustainability discourse and examining the role of non-market-based and market-based policies for balanced growth and welfare improvements in different theory settings. Sustainable urban growth either calls for policy actions or a green energy transition. Further, R&D market failures can pose severe challenges to the sustainability of urban growth and the social optimality of decentralized allocation decisions. Still, a careful (holistic) combination of policy instruments can achieve sustainable growth and even be first best.
Background:
Research into the application of virtual reality technology in the health care sector has rapidly increased, resulting in a large body of research that is difficult to keep up with.
Objective:
We will provide an overview of the annual publication numbers in this field and the most productive and influential countries, journals, and authors, as well as the most used, most co-occurring, and most recent keywords.
Methods:
Based on a data set of 356 publications and 20,363 citations derived from Web of Science, we conducted a bibliometric analysis using BibExcel, HistCite, and VOSviewer.
Results:
The strongest growth in publications occurred in 2020, accounting for 29.49% of all publications so far. The most productive countries are the United States, the United Kingdom, and Spain; the most influential countries are the United States, Canada, and the United Kingdom. The most productive journals are the Journal of Medical Internet Research (JMIR), JMIR Serious Games, and the Games for Health Journal; the most influential journals are Patient Education and Counselling, Medical Education, and Quality of Life Research. The most productive authors are Riva, del Piccolo, and Schwebel; the most influential authors are Finset, del Piccolo, and Eide. The most frequently occurring keywords other than “virtual” and “reality” are “training,” “trial,” and “patients.” The most relevant research themes are communication, education, and novel treatments; the most recent research trends are fitness and exergames.
Conclusions:
The analysis shows that the field has left its infant state and its specialization is advancing, with a clear focus on patient usability.
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.
Traditional organizations are strongly encouraged by emerging digital customer behavior and digital competition to transform their businesses for the digital age. Incumbents are particularly exposed to the field of tension between maintaining and renewing their business model. Banking is one of the industries most affected by digitalization, with a large stream of digital innovations around Fintech. Most research contributions focus on digital innovations, such as Fintech, but there are only a few studies on the related challenges and perspectives of incumbent organizations, such as traditional banks. Against this background, this dissertation examines the specific causes, effects and solutions for traditional banks in digital transformation − an underrepresented research area so far.
The first part of the thesis examines how digitalization has changed the latent customer expectations in banking and studies the underlying technological drivers of evolving business-to-consumer (B2C) business models. Online consumer reviews are systematized to identify latent concepts of customer behavior and future decision paths as strategic digitalization effects. Furthermore, the service attribute preferences, the impact of influencing factors and the underlying customer segments are uncovered for checking accounts in a discrete choice experiment. The dissertation contributes here to customer behavior research in digital transformation, moving beyond the technology acceptance model. In addition, the dissertation systematizes value proposition types in the evolving discourse around smart products and services as key drivers of business models and market power in the platform economy.
The second part of the thesis focuses on the effects of digital transformation on the strategy development of financial service providers, which are classified along with their firm performance levels. Standard types are derived based on fuzzy-set qualitative comparative analysis (fsQCA), with facade digitalization as one typical standard type for low performing incumbent banks that lack a holistic strategic response to digital transformation. Based on this, the contradictory impact of digitalization measures on key business figures is examined for German savings banks, confirming that the shift towards digital customer interaction was not accompanied by new revenue models diminishing bank profitability. The dissertation further contributes to the discourse on digitalized work designs and the consequences for job perceptions in banking customer advisory. The threefold impact of the IT support perceived in customer interaction on the job satisfaction of customer advisors is disentangled.
In the third part of the dissertation, solutions are developed design-oriented for core action areas of digitalized business models, i.e., data and platforms. A consolidated taxonomy for data-driven business models and a future reference model for digital banking have been developed. The impact of the platform economy is demonstrated here using the example of the market entry by Bigtech. The role-based e3-value modeling is extended by meta-roles and role segments and linked to value co-creation mapping in VDML. In this way, the dissertation extends enterprise modeling research on platform ecosystems and value co-creation using the example of banking.
The reduction in cost and increasing benefits of 3D printing technologies suggest the potential for printing dental prosthetics. However, although 3D printing technologies seem to be promising, their implementation in practice is complicated. To identify and rank the greatest implementation challenges of 3D printing in dental practices, the present study surveys dentists, dental technicians, and 3D printing companies using a ranking-type Delphi study. Our findings imply that a lack of knowledge is the most crucial obstacle to the implementation of 3D printing technologies. The high training effort of staff and the favoring of conventional methods, such as milling, are ranked as the second and third most relevant factors. Investment costs ranked in seventh place, whereas the lack of manufacturing facilities and the obstacle of print duration ranked below average. An inclusive implementation of additive manufacturing could be achieved primarily through the education of dentists and other staff in dental practices. In this manner, production may be managed internally, and the implementation speed may be increased.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
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.
This paper-based dissertation aims to contribute to the open innovation (OI) and technology management (TM) research fields by investigating their mechanisms, and potentials at the operational level. The dissertation connects the well-known concept of technology management with OI formats and applies these on specific manufacturing technologies within a clearly defined setting.
Technological breakthroughs force firms to continuously adapt and reinvent themselves. The pace of technological innovation and their impact on firms is constantly increasing due to more connected infrastructure and accessible resources (i.e. data, knowledge). Especially in the manufacturing sector it is one key element to leverage new technologies to stay competitive. These technological shifts call for new management practices.
TM supports firms with various tools to manage these shifts at different levels in the firm. It is a multifunctional and multidisciplinary field as it deals with all aspects of integrating technological issues into business decision-making and is directly relevant to a number of core business processes. Thus, it makes sense to utilize this theory and their practices as a foundation of this dissertation. However, considering the increasing complexity and number of technologies it is not sufficient anymore for firms to only rely on previous internal R&D and managerial practices. OI can expanse these practices by involving distributed innovation processes and accessing further external knowledge sources. This expansion can lead to an increasing innovation performance and thereby accelerate the time-to-market of technologies.
Research in this dissertation was based on the expectations that OI formats will support the R&D activities of manufacturing technologies on the operational level by providing access to resources, knowledge, and leading-edge technology. The dissertation represents uniqueness regarding the rich practical data sets (observations, internal documents, project reviews) drawn from a very large German high-tech firm. The researcher was embedded in an R&D unit within the operational TM department for manufacturing technologies. The analyses include 1.) an exploratory in-depth analysis of a crowdsourcing initiative to elaborate the impact on specific manufacturing technologies, 2.) a deductive approach for developing a technology evaluation score model to create a common understanding of the value of selected manufacturing technologies at the operational level, and 3.) an abductive reasoning approach in form of a longitudinal case study to derive important indicator for the in-process activities of science-based partnership university-industry collaboration format. Thereby, the dissertation contributed to research and practice 1.) linkages of TM and OI practices to assimilate technologies at the operational level, 2.) insights about the impact of CS on manufacturing technologies and a related guideline to execute CS initiatives in this specific environment 3.) introduction of manufacturing readiness levels and further criteria into the TM and OI research field to support decision-makers in the firm in gaining a common understanding of the maturity of manufacturing technologies and, 4.) context-specific important indicators for science based university-industry collaboration projects and a holistic framework to connect TM with the university-industry collaboration approach
The findings of this dissertation illustrate that OI formats can support the acceleration of time-to-market of manufacturing technologies and further improve the technical requirements of the product by leveraging external capabilities. The conclusions and implications made are intended to foster further research and improve managerial practices to evolve TM into an open collaborative context with interconnectivities between all internal and external involved technologies, individuals and organizational levels.
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.
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.
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.
The public encounter
(2019)
This thesis puts the citizen-state interaction at its center. Building on a comprehensive model incorporating various perspectives on this interaction, I derive selected research gaps. The three articles, comprising this thesis, tackle these gaps. A focal role plays the citizens’ administrative literacy, the relevant competences and knowledge necessary to successfully interact with public organizations. The first article elaborates on the different dimensions of administrative literacy and develops a survey instrument to assess these. The second study shows that public employees change their behavior according to the competences that citizens display during public encounters. They treat citizens preferentially that are well prepared and able to persuade them of their application’s potential. Thereby, they signal a higher success potential for bureaucratic success criteria which leads to the employees’ cream-skimming behavior. The third article examines the dynamics of employees’ communication strategies when recovering from a service failure. The study finds that different explanation strategies yield different effects on the client’s frustration. While accepting the responsibility and explaining the reasons for a failure alleviates the frustration and anger, refusing the responsibility leads to no or even reinforcing effects on the client’s frustration. The results emphasize the different dynamics that characterize the nature of citizen-state interactions and how they establish their short- and long-term outcomes.
The development of new and better optimization and approximation methods for Job Shop Scheduling Problems (JSP) uses simulations to compare their performance. The test data required for this has an uncertain influence on the simulation results, because the feasable search space can be changed drastically by small variations of the initial problem model. Methods could benefit from this to varying degrees. This speaks in favor of defining standardized and reusable test data for JSP problem classes, which in turn requires a systematic describability of the test data in order to be able to compile problem adequate data sets. This article looks at the test data used for comparing methods by literature review. It also shows how and why the differences in test data have to be taken into account. From this, corresponding challenges are derived which the management of test data must face in the context of JSP research.
Keywords
How Will We Dine?
(2020)
Haute cuisine, the cooking style for fine dining at gourmet restaurants, has changed over the last decades and can be expected to evolve in the upcoming years. To engage in foresight, the purpose of this study is to identify a plausible future trend scenario for the haute cuisine sector within the next five to ten years, based on today’s chefs’ views. To achieve this goal, an international, two-stage Delphi study was conducted. The derived scenario suggests that the coronavirus disease 2019 (COVID-19) pandemic will lead to significant restaurant bankruptcies and will raise creativity and innovation among the remaining ones. It is expected that haute cuisine tourism will grow and that menu prices will differ for customer segments. More haute cuisine restaurants will open in Asia and America. Local food will remain a major trend and will be complemented by insect as well as plant-based proteins and sophisticated nonalcoholic food pairings. Restaurant design and the use of scents will become more relevant. Also, private dining and fine dining at home will become more important. The scenario also includes negative projections. These findings can serve as a research agenda for future research in haute cuisine, including the extension of the innovation lens towards the restaurant and the business model. Practical implications include the necessity for haute cuisine restaurants to innovate to cope with increasing competition in several regions. Customers should be seen as co-creators of the value of haute cuisine.
Social Media, Quo Vadis?
(2020)
Over the past two decades, social media have become a crucial and omnipresent cultural and economic phenomenon, which has seen platforms come and go and advance technologically. In this study, we explore the further development of social media regarding interactive technologies, platform development, relationships to news media, the activities of institutional and organizational users, and effects of social media on the individual and the society over the next five to ten years by conducting an international, two-stage Delphi study. Our results show that enhanced interaction on platforms, including virtual and augmented reality, somatosensory sense, and touch- and movement-based navigation are expected. AIs will interact with other social media users. Inactive user profiles will outnumber active ones. Platform providers will diversify into the WWW, e-commerce, edu-tech, fintechs, the automobile industry, and HR. They will change to a freemium business model and put more effort into combating cybercrime. Social media will become the predominant news distributor, but fake news will still be problematic. Firms will spend greater amounts of their budgets on social media advertising, and schools, politicians, and the medical sector will increase their social media engagement. Social media use will increasingly lead to individuals’ psychic issues. Society will benefit from economic growth and new jobs, increased political interest, democratic progress, and education due to social media. However, censorship and the energy consumption of platform operators might rise.
It is well known that the inverted Collatz sequence can be represented as a graph or a tree. Similarly, it is acknowledged that in order to prove the Collatz conjecture, one must demonstrate that this tree covers all odd natural numbers. A structured reachability analysis is hitherto unavailable. This paper investigates the problem from a graph theory perspective. We define a tree that consists of nodes labeled with Collatz sequence numbers. This tree will be transformed into a sub-tree that only contains odd labeled nodes. Furthermore, we derive and prove several formulas that can be used to traverse the graph. The analysis covers the Collatz problem both in it’s original form 3x + 1 as well as in the generalized variant kx + 1. Finally, we transform the Collatz graph into a binary tree, following the approach of Kleinnijenhuis, which could form the basis for a comprehensive proof of the conjecture.
Corporate Citizenship
(2020)
Corporate citizenship, which is firms’ societal engagement beyond customer and shareholder interests, is a prominent topic in management practice and has led to extensive research. This increased interest resulted in a complex and fragmented scholarly literature. In order to structure and map the field quantitatively, we conducted a temporal analysis of publications and citations, an analysis of the productivity of involved disciplines, an analysis of the productivity of publication forms including journal impact factors, an author productivity and citation analysis, a co-author analysis, an article citation analysis, an article co-citation analysis, and a keyword co-occurrence analysis. Results of these bibliometric analyses show that corporate citizenship research seems to have been in a phase of stagnation since 2014 and shows a rather low degree of interdisciplinarity. Papers are predominantly published in high impact journals. Authors show little collaboration with other researchers. Current research relates to other business ethics topics, addresses philosophical foundations, and starts to relate to human resource management and organization studies.
Envy is an unpleasant emotion. If individuals anticipate that comparing their payoff with the (potentially higher) payoff of others will make them envious, they may want to actively avoid information about other people’s payoffs. Given the opportunity to reduce another person’s payoff, an individual’s envy may trigger behavior that is detrimental to welfare. In this case, if individuals anticipate that they will react in a welfare-reducing way, they may also avoid information about other people’s payoffs from the outset. We investigated these two hypotheses using three experiments. We found that 13% of our potentially envious subjects avoided information when they did not have the opportunity to reduce another participant’s payoff. Psychological scales do not explain this behavior. We also found that voluntarily uninformed subjects did neither deduct less of the payoff nor less frequently than subjects who could not avoid the information.
It is well known that the inverted Collatz sequence can be represented as a graph or a tree. Similarly, it is acknowledged that in order to prove the Collatz conjecture, one must demonstrate that this tree covers all odd natural numbers. A structured reachability analysis is hitherto not available. This paper investigates the problem from a graph theory perspective. We define a tree that consists of nodes labeled with Collatz sequence numbers. This tree will be transformed into a sub-tree that only contains odd labeled nodes. The analysis of this tree will provide new insights into the structure of Collatz sequences. The findings are of special interest to possible cycles within a sequence. Next, we describe the conditions which must be fulfilled by a cycle. Finally, we demonstrate how these conditions could be used to prove that the only possible cycle within a Collatz sequence is the trivial cycle, starting with the number one, as conjectured by Lothar Collatz.
This paper challenges the solely rational view of the scenario technique as a strategy and foresight tool designed to cope with uncertainty by considering multiple possible future states. The paper employs an affordance-based view that allows for the identification and structuring of hidden, emergent attributes of the scenario technique beyond the intended ones. The suggested framework distinguishes between affordances (1) that are intended by the organization and relate to its goals, (2) that emergently generate organizational benefits, and (3) that do not relate to organizational but individual interests. Also, constraints in the use of scenarios are discussed. Affordance theory’s specific lens shows that the emergence of such attributes depends on the users’ specific intentions.
It is well known that the inverted Collatz sequence can be represented as a graph or a tree. Similarly, it is acknowledged that in order to prove the Collatz conjecture, one must demonstrate that this tree covers all (odd) natural numbers. A structured reachability analysis is hitherto not available. This paper investigates the problem from a graph theory perspective. We define a tree that consists of nodes labeled with Collatz sequence numbers. This tree will be transformed into a sub-tree that only contains odd labeled nodes. The analysis of this tree will provide new insights into the structure of Collatz sequences. The findings are of special interest to possible cycles within a sequence. Next, we describe the conditions which must be fulfilled by a cycle. Finally, we demonstrate how these conditions could be used to prove that the only possible cycle within a Collatz sequence is the trivial cycle, starting with the number 1, as conjectured by Lothar Collatz.
In this study, we analyze the forecast accuracy and profitability of buy recommendations published in five major German financial magazines for private households based on fundamental analysis. The results show a high average forecast accuracy but with a very high standard deviation, which indicates poor forecast accuracy with regard to individual stocks. The recommendation profitability slightly exceeds the performance of the MSCI World index. Considering the involved risk, which is represented by a high standard deviation, the excess returns appear to be insufficient.
As digital media infiltrate an increasingly greater proportion of our lives, concern about the possibility of various forms of technology addictions has emerged. For technology addiction, researchers have developed a variety of self-reported scales in areas such as Internet, smartphones, videogames, social network sites (SNS) or television. However, no uniform criteria or definition exists for technology addiction. Utilized dimensions of technology addiction, to measure specific outcomes, lack a conceptual standard. Therefore, linkages between technology areas dimensions have not been examined in a broader way by the research community, in order to develop a uniform technology addiction scale.
In this regard, firstly, a theoretical model was developed in order to extract common technology dimensions. Secondly, a systematic literature review in the areas of Internet, smartphone, video games and SNS was conducted in order to extract the dimensions used. To identify relevant studies, nine databases (GoogleScholar, ScienceDirect, PubMed, EmeraldInsight, Wiley, SpringerLink, ACM, iEEE and JSTOR) were searched, producing 4698 results, and 50 studies met the inclusion criteria. Thirdly, the developed theoretical model was utilized in order to determine the dimension in each of the identified scales.
Based on analysis of the dimensional distributions, the findings suggest that there are common dimensions across areas of technology such as “compulsive use” and “negative outcomes” but also differences in dimensions across areas such as “social comfort” and “mood regulation”, which are more used in the area of SNS. Moreover, new dimensions such as “cognitive absorption” or “utility and function loss" for technology addiction were extracted, which should be considered as these have not yet been researched in a broader way. In addition, no gold standard for the conceptual criteria or definition for technology addiction has been developed yet.
What Makes an Employer?
(2019)
As the policy debate on entrepreneurship increasingly centers on firm growth in terms of job creation, it is important to better understand which variables influence the first hiring decision and which ones influence the subsequent survival as an employer. Using the German Socio-economic Panel (SOEP), we analyze what role individual characteristics of entrepreneurs play in sustainable job creation. While human and social capital variables positively influence the hiring decision and the survival as an employer in the same direction, we show that none of the personality traits affect the two outcomes in the same way. Some traits are only relevant for survival as an employer but do not influence the hiring decision, other traits even unfold a revolving door effect, in the sense that employers tend to fail due to the same characteristics that positively influenced their hiring decision.
The Collatz conjecture is a number theoretical problem, which has puzzled countless researchers using myriad approaches. Presently, there are scarcely any methodologies to describe and treat the problem from the perspective of the Algebraic Theory of Automata. Such an approach is promising with respect to facilitating the comprehension of the Collatz sequence’s "mechanics". The systematic technique of a state machine is both simpler and can fully be described by the use of algebraic means.
The current gap in research forms the motivation behind the present contribution. The present authors are convinced that exploring the Collatz conjecture in an algebraic manner, relying on findings and fundamentals of Graph Theory and Automata Theory, will simplify the problem as a whole.
From an active labor market policy perspective, start-up subsidies for unemployed individuals are very effective in improving long-term labor market outcomes for participants. From a business perspective, however, the assessment of these public programs is less clear since they might attract individuals with low entrepreneurial abilities and produce businesses with low survival rates and little contribution to job creation, economic growth, and innovation. In this paper, we use a rich data set to compare participants of a German start-up subsidy program for unemployed individuals to a group of regular founders who started from nonunemployment and did not receive the subsidy. The data allows us to analyze their business performance up until 40 months after business formation. We find that formerly subsidized founders lag behind not only in survival and job creation, but especially also in innovation activities. The gaps in these business outcomes are relatively constant or even widening over time. Hence, we do not see any indication of catching up in the longer run. While the gap in survival can be entirely explained by initial differences in observable start-up characteristics, the gap in business development remains and seems to be the result of restricted access to capital as well as differential business strategies and dynamics. Considering these conflicting results for the assessment of the subsidy program from an ALMP and business perspective, policy makers need to carefully weigh the costs and benefits of such a strategy to find the right policy mix.
Cooperation is — despite not being predicted by game theory — a widely documented aspect of human behaviour in Prisoner’s Dilemma (PD) situations. This article presents a comparison between subjects restricted to playing pure strategies and subjects allowed to play mixed strategies in a one-shot symmetric PD laboratory experiment. Subjects interact with 10 other subjects and take their decisions all at once. Because subjects in the mixed-strategy treatment group are allowed to condition their level of cooperation more precisely on their beliefs about their counterparts’ level of cooperation, we predicted the cooperation rate in the mixed-strategy treatment group to be higher than in the pure-strategy control group. The results of our experiment reject our prediction: even after controlling for beliefs about the other subjects’ level of cooperation, we find that cooperation in the mixed-strategy group is lower than in the pure-strategy group. We also find, however, that subjects in the mixedstrategy group condition their cooperative behaviour more closely on their beliefs than in the pure-strategy group. In the mixed-strategy group, most subjects choose intermediate levels of cooperation.
Entrepreneurial persistence is demonstrated by an entrepreneur’s continued positive maintenance of entrepreneurial motivation and constantly-renewed active engagement in a new business venture despite counter forces or enticing alternatives. It is thus a crucial factor for entrepreneurs when pursuing and exploiting their business opportunities and to realize potential economic gains and benefits. Using rich data on a representative sample of German business founders, we investigate the determinants of entrepreneurial persistence. Next to observed survival we also construct a hybrid persistence measure capturing also the motivational dimension of persistence. We analyze the influence of individual-level (human capital and personality) and business-related characteristics on both measures as well as their relative importance. We find that the two indicators emphasize different aspects of persistence. For the survival indicator, the predictive power is concentrated in business characteristics and human capital, while for hybrid persistence, the dominant factors are business characteristics and personality. Finally, we show that results are heterogeneous across subgroups. In particular, formerly-unemployed founders do not differ in survival chances, but they are more likely to lack a high psychological commitment to their business ventures.
Being ignorant of key aspects of a strategic interaction can represent an advantage rather than a handicap. We study one particular context in which ignorance can be beneficial: iterated strategic interactions in which voluntary cooperation may be sustained into the final round if players voluntarily forego knowledge about the time horizon. We experimentally examine this option to remain ignorant about the time horizon in a finitely repeated two-person prisoners’ dilemma game. We confirm that pairs without horizon knowledge avoid the drop in cooperation that otherwise occurs toward the end of the game. However, this effect is superposed by cooperation declining more rapidly in pairs without horizon knowledge during the middle phase of the game, especially if players do not know that the other player also wanted to remain ignorant of the time horizon.
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.
The Collatz conjecture is a number theoretical problem, which has puzzled countless researchers using myriad approaches. Presently, there are scarcely any methodologies to describe and treat the problem from the perspective of the Algebraic Theory of Automata. Such an approach is promising with respect to facilitating the comprehension of the Collatz sequences "mechanics". The systematic technique of a state machine is both simpler and can fully be described by the use of algebraic means.
The current gap in research forms the motivation behind the present contribution. The present authors are convinced that exploring the Collatz conjecture in an algebraic manner, relying on findings and fundamentals of Graph Theory and Automata Theory, will simplify the problem as a whole.
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.
We use panel data from Germany to analyze the effect of population density on urban air pollution (nitrogen oxides, particulate matter and ozone). To address unobserved heterogeneity and omitted variables, we present long difference/fixed effects estimates and instrumental variables estimates, using historical population and soil quality as instruments. Our preferred estimates imply that a one-standard deviation increase in population density increases air pollution by 3-12%.
”Thanks in Advance”
(2019)
This paper studies the effect of the commonly used phrase “thanks in advance” on compliance with a small request. In a controlled laboratory experiment we ask participants to give a detailed answer to an open question. The treatment variable is whether or not they see the phrase “thanks in advance.” Our participants react to the treatment by exerting less effort in answering the request even though they perceive the phrase as polite.
The German start-up subsidy (SUS) program for the unemployed has recently undergone a major make-over, altering its institutional setup, adding an additional layer of selection and leading to ambiguous predictions of the program’s effectiveness. Using propensity score matching (PSM) as our main empirical approach, we provide estimates of long-term effects of the post-reform subsidy on individual employment prospects and labor market earnings up to 40 months after entering the program. Our results suggest large and persistent long-term effects of the subsidy on employment probabilities and net earned income. These effects are larger than what was estimated for the pre-reform program. Extensive sensitivity analyses within the standard PSM framework reveal that the results are robust to different choices regarding the implementation of the weighting procedure and also with respect to deviations from the conditional independence assumption. As a further assessment of the results’ sensitivity, we go beyond the standard selection-on-observables approach and employ an instrumental variable setup using regional variation in the likelihood of receiving treatment. Here, we exploit the fact that the reform increased the discretionary power of local employment agencies in allocating active labor market policy funds, allowing us to obtain a measure of local preferences for SUS as the program of choice. The results based on this approach give rise to similar estimates. Thus, our results indicating that SUS are still an effective active labor market program after the reform do not appear to be driven by “hidden bias”.