@phdthesis{Koehler2024,
  author    = {K{\"o}hler, Wolfgang},
  title     = {Challenges of efficient and compliant data processing},
  doi       = {10.25932/publishup-62784},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-627843},
  school      = {Universit{\"a}t Potsdam},
  pages     = {195},
  year      = {2024},
  abstract  = {Die fortschreitende Digitalisierung ver{\"a}ndert die Gesellschaft und hat weitreichende Auswirkungen auf Menschen und Unternehmen. Grundlegend f{\"u}r diese Ver{\"a}nderungen sind die neuen technologischen M{\"o}glichkeiten, Daten in immer gr{\"o}ßerem Umfang und f{\"u}r vielf{\"a}ltige neue Zwecke zu verarbeiten. Von besonderer Bedeutung ist dabei die Verf{\"u}gbarkeit großer und qualitativ hochwertiger Datens{\"a}tze, insbesondere auf Basis personenbezogener Daten. Sie werden entweder zur Verbesserung der Produktivit{\"a}t, Qualit{\"a}t und Individualit{\"a}t von Produkten und Dienstleistungen oder gar zur Entwicklung neuartiger Dienstleistungen verwendet. Heute wird das Nutzerverhalten, trotz weltweit steigender gesetzlicher Anforderungen an den Schutz personenbezogener Daten, aktiver und umfassender verfolgt als je zuvor. Dies wirft vermehrt ethische, moralische und gesellschaftliche Fragen auf, die nicht zuletzt durch popul{\"a}re F{\"a}lle des Datenmissbrauchs in den Vordergrund der politischen Debatte ger{\"u}ckt sind. Angesichts dieses Diskurses und der gesetzlichen Anforderungen muss heutiges Datenmanagement drei Bedingungen erf{\"u}llen: Erstens die Legalit{\"a}t bzw. Gesetzeskonformit{\"a}t der Nutzung, zweitens die ethische Legitimit{\"a}t. Drittens sollte die Datennutzung aus betriebswirtschaftlicher Sicht wertsch{\"o}pfend sein. Im Rahmen dieser Bedingungen verfolgt die vorliegende kumulative Dissertation vier Forschungsziele mit dem Fokus, ein besseres Verst{\"a}ndnis (1) der Herausforderungen bei der Umsetzung von Gesetzen zum Schutz von Privatsph{\"a}re, (2) der Faktoren, die die Bereitschaft der Kunden zur Weitergabe pers{\"o}nlicher Daten beeinflussen, (3) der Rolle des Datenschutzes f{\"u}r das digitale Unternehmertum und (4) der interdisziplin{\"a}ren wissenschaftlichen Bedeutung, deren Entwicklung und Zusammenh{\"a}nge zu erlangen.},
  language  = {en}
}
@phdthesis{Panzer2024,
  author    = {Panzer, Marcel},
  title     = {Design of a hyper-heuristics based control framework for modular production systems},
  doi       = {10.25932/publishup-63300},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-633006},
  school      = {Universit{\"a}t Potsdam},
  pages     = {vi, 334},
  year      = {2024},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Haase2023,
  author    = {Haase, Jennifer},
  title     = {Creative intensive processes},
  doi       = {10.25932/publishup-59388},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-593886},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 346},
  year      = {2023},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Baum2023,
  author    = {Baum, Katharina},
  title     = {Social networking sites},
  school      = {Universit{\"a}t Potsdam},
  pages     = {281},
  year      = {2023},
  language  = {en}
}
@phdthesis{Brenner2022,
  author    = {Brenner, Andri Caspar},
  title     = {Sustainable urban growth},
  doi       = {10.25932/publishup-55522},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-555223},
  school      = {Universit{\"a}t Potsdam},
  pages     = {231},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Gleiss2022,
  author    = {Gleiß, Alexander},
  title     = {Case Studies on Digital Transformation},
  doi       = {10.25932/publishup-54615},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-546159},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 198},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Boeken2022,
  author    = {B{\"o}ken, Bj{\"o}rn},
  title     = {Improving prediction accuracy using dynamic information},
  doi       = {10.25932/publishup-58512},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-585125},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 160},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Gandhi2022,
  author    = {Gandhi, Nilima},
  title     = {Visionary leadership and job satisfaction},
  doi       = {10.25932/publishup-57269},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-572691},
  school      = {Universit{\"a}t Potsdam},
  pages     = {154},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Dehnert2022,
  author    = {Dehnert, Maik},
  title     = {Studies on the Digital Transformation of Incumbent Organizations},
  doi       = {10.25932/publishup-54832},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-548324},
  school      = {Universit{\"a}t Potsdam},
  pages     = {339},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Brinkmann2022,
  author    = {Brinkmann, Maik},
  title     = {Towards a joint public service delivery? The effects of blockchain on the relationship of public administrations with external stakeholders},
  doi       = {10.25932/publishup-56449},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-564499},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 126, CCLXVIII},
  year      = {2022},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{HannesVincent2022,
  author    = {Hannes-Vincent, Krause},
  title     = {Social networking site use and well-being - a nuanced understanding of a complex relationship},
  school      = {Universit{\"a}t Potsdam},
  year      = {2022},
  abstract  = {Social Networking Sites (SNSs) are ubiquitous and attract an enormous chair of the digital population. Their functionalities allow users to connect and interact with others and weave complex social networks in which social information is continuously disseminated between users. Besides the social value SNSs are generating, they likewise attract companies and allow for new forms of marketing, thereby creating considerable economic value alike. However, as SNSs grew in popularity, so did concerns about the impact of their use on social interactions in general and the well-being of individual users in particular. While existing scientific evidence points to both risk as well as benefits of SNS use, research still lacks a profound understanding of which aspects of SNSs enable an impact on well-being and which psychological processes on the part of the users underly and explain this relationship. Therefore, this thesis is dedicated to an in-depth exploration of the relationship between SNS use and well-being and aims to answer how SNS use can impact well-being. Primarily, it focuses on the unique technological features that characterize SNSs and enable potential well- being alterations and on specific psychological processes on the part of the users, underlying and explaining the relationship. For this purpose, the thesis first introduces the concept of well- being. It continues by presenting SNSs' unique technological features, divided into specifics of the content disseminated on SNSs and the network structure of SNSs. Further, the thesis introduces three classes of psychological processes assumed most relevant for the relationship between SNSs and well-being: other-focused, self-focused, and contrastive processes.. It is assumed that the course and quality of these common processes change in the SNS context and that a complex interplay between the unique features of SNSs and these processes determines how SNSs may ultimately affect users' well-being - both in positive and negative ways. The dissertation comprises seven research articles, each of which focusses on a particular set of SNS characteristics, their interplay with one or more of the proposed psychological processes, and ultimately the resulting effects on user well-being or its key resilience and risk factors. The seven articles investigate this relationship using different methodological approaches. Three articles are based on either systematic or narrative literature reviews, one applies an empirical cross-sectional research design, and three articles present an experimental investigation. Thematically, two articles revolve around SNS use's effect on self-esteem. Three articles examine the specific role of the emotion of envy and its potential to establish and perpetuate a well-being-damaging social climate on SNSs. The two last articles of this thesis revolve around the established assumption that active and passive SNS use, as different modalities of SNS use, cause differential effects on users' well-being due to the involvement of different psychological processes. The results of this thesis illustrate different ways how SNSs can affect users' well-being. The results suggest that especially contrastive processes play a decisive role in explaining potential well-being risks for SNS users. Their interplay with certain SNS features seems to foster upward social comparisons and feelings of envy, potentially leading to a complex set of deleterious effects on users' well-being. At the same time, the findings illuminate ways in which SNSs can benefit users and their self-esteem - especially when SNS use promotes self- focused and social-feedback-based other-focused processes. The thesis and their findings illustrate that the relationship between SNSs and well-being is complex. Therefore, a nuanced perspective, taking into consideration both the technological uniqueness of SNSs and the psychological processes they are enabling, is crucial to understand how these technologies affect their users in good and potentially harmful ways. On the one hand, the gathered insights contribute to research, providing novel insights into the complex relationship between SNS use and well-being. On the other hand, the results enable a focused and action-oriented derivation of recommendations for stakeholders such as individual users, policymakers, and platform providers. The findings of this thesis can help them to better combat SNS-related risks and ultimately ensure a healthy and sustainable environment for users - and thus also the economic values of SNSs - in the long term.},
  language  = {en}
}
@phdthesis{Dressen2021,
  author    = {Dreßen, Sebastian},
  title     = {Open innovation for manufacturing technologies},
  doi       = {10.25932/publishup-51438},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-514384},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VIII, 141},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{AbuJarour2021,
  author    = {AbuJarour, Safa'a},
  title     = {Digital inclusion},
  doi       = {10.25932/publishup-51053},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-510535},
  school      = {Universit{\"a}t Potsdam},
  pages     = {217},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Heger2021,
  author    = {Heger, Tobias},
  title     = {Foresight in networks},
  doi       = {10.25932/publishup-50385},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-503851},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XVII, 247},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Graeber2021,
  author    = {Graeber, Daniel},
  title     = {Four essays on the socio-economic causes and consequences of individual health as well as public health crises},
  doi       = {10.25932/publishup-51517},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-515175},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XIV, 249},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Sikkens2021,
  author    = {Sikkens, Reinier},
  title     = {An analysis of cultural entrepreneurship},
  doi       = {10.25932/publishup-50187},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-501879},
  school      = {Universit{\"a}t Potsdam},
  pages     = {325},
  year      = {2021},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{LeueBensch2020,
  author    = {Leue-Bensch, Carina},
  title     = {Supporting the expression of entrepreneurial potential},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XII, 127, XVIII},
  year      = {2020},
  abstract  = {The ability of a company to innovate and to launch innovation is a critical competitive edge to remain competitive in the 21st century. Large organizations therefore increasingly recognize employees as a significant factor and critical source of innovation. Several studies assert the fact that every employee has to offer certain skills and knowledge and can contribute to innovation. Hence, every employee has a certain 'entrepreneurial potential'. This potential can be expressed in the form of entrepreneurial behaviour and can occur in many ways, from monopersonal innovation championing to several small scale contributions, where several individuals team up for innovation. To support entrepreneurial behaviour of their employees, large organizations increasingly rely on Corporate Entrepreneurship. They set up organizational structures and venturing units, offer vehicles and tools to their employees to be more entrepreneurial. The evolvement of new tools and technologies thereby allow for new ways of employee involvement, also allowing for more radical innovation to be developed collaboratively. Yet, many of such offerings fail to achieve the desired outcome. While some employees immediately opt-in for innovation, others do not and their entrepreneurial potential remains untapped. This research explores how large organizations can better support their employees to express their entrepreneurial potential, thus moving from non-entrepreneurial behaviour or not wanting to be involved, to actually expressing entrepreneurial behaviour. The underlying research therefore is two-fold. While focusing on the individual level and the entrepreneurial behaviour of employees, this research also takes the organizational perspective into account in order to identify how non-entrepreneurial behaviour can be stimulated towards entrepreneurial behaviour. Using an empirical qualitative research design based on pragmatism and abduction, data is collected by means of qualitative interviews as well as a longitudinal use case setting. Grounded theory is then applied for analysis and sense making. The main outcome is a theoretical model of why employees are expressing or not expressing their entrepreneurial potential and how non-expression can potentially be triggered towards entrepreneurial behaviour. The results indicate that there is no one-size-fits all model of Corporate Entrepreneurship. This research therefore argues that organizations can achieve higher levels of entrepreneurial behaviour when addressing employees differently. By developing a theoretical model as well as suggestions of how this model can be applied in practice, this research contributes to theory and practice alike. This document closes suggesting future research areas around supporting employees to express their entrepreneurial potential.},
  language  = {en}
}
@phdthesis{Tuebbicke2020,
  author    = {T{\"u}bbicke, Stefan},
  title     = {Essays on start-up subsidies for the unemployed and methods for causal inference},
  doi       = {10.25932/publishup-47793},
  school      = {Universit{\"a}t Potsdam},
  pages     = {191},
  year      = {2020},
  abstract  = {This thesis offers new insights on the effects of Start-Up Subsidies (SUS) for unemployed individuals as a special kind of active labor market program (ALMP) that aims to re-integrate individuals into the labor market via the route of self-employment. Moreover, this thesis contributes to the literature on methods for causal inference when the treatment variable is continuous rather than binary. For example, this is the case when individuals differ in their degree of exposure to a common treatment. The analysis of the effects of SUS focuses on the main current German program called "Gr{\"u}ndungszuschuss" (New Start-Up Subsidy, NSUS) after its reform in 2011. Average Effects on participants' labor market outcomes - as measured by employment and earnings - as well as subjective well-being are estimated mainly based on propensity score matching (PSM) techniques. PSM aims to achieve balance in terms of observed characteristics by matching participants with at least one comparable non-participant in terms of their probability to receive the treatment. This estimation strategy is valid as long as all relevant characteristics that explain selection patterns into treatment are observed and included in the estimation of the propensity score. To make our analysis as credible as possible, we control for a large vector of characteristics as observed through the combination of rich administrative data from the Federal Employment Agency as well as through survey data. Chapters two to four of this thesis puts special emphasis on aspects regarding (the evaluation of) SUS programs that have received no or only limited attention thus far. The first aspect relates to the interplay of institutional details of the program and its effectiveness. So far, relatively little is known about the importance of SUS program features such as the duration of support. Second, there is no experimental benchmark evaluation of SUS available and thus, the reliability of non-experimental estimation techniques such as PSM is of crucial importance as estimates are biased when relevant confounders are omitted from the analysis. Third, there may be potentially detrimental effects of transitioning into (relatively risky) self-employment on subjective well-being among subsidized founders out of unemployment. These were to remain undetected if the analysis would focus exclusively on labor market outcomes of participants. The results indicate positive long-term effects of SUS participation on employment and earnings among participants. These effects are substantially larger than what estimated before the reform, indicating room for improvement in program design via changes in institutional details. Moreover, non-experimental estimates of treatment effects are remarkably robust to hidden confounding. Regarding subjective well-being, this thesis finds a positive long-run impact on job satisfaction and a detrimental effect on satisfaction with social security. The latter appears to be driven by adverse effects on social insurance contributions. In chapter five, a novel automated covariate balancing technique for the estimation of causal effects in the context of continuous treatments is derived and assessed regarding its performance compared to other (automated) balancing techniques. Although binary research designs that only differentiate between participants and non-participants of some treatment remain the most-common case in empirical practice, many applications can be adapted to include continuous treatments as well. Often, this will allow for more meaningful estimates of causal effects in order to further improve the design of programs. In the context of SUS, one may further investigate the effects of the size of monetary support or its duration on participants' labor market outcomes. Both Monte-Carlo investigations and analysis of two well-known datasets suggests superior performance of the proposed Entropy Balancing for continuous treatments (EBCT) compared to other existing estimation strategies.},
  language  = {en}
}
@phdthesis{Henike2019,
  author    = {Henike, Tassilo},
  title     = {Cognition and entrepreneurial business modelling},
  school      = {Universit{\"a}t Potsdam},
  pages     = {150},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}
@phdthesis{Schmeiss2019,
  author    = {Schmeiss, Jessica},
  title     = {Designing value architectures for emerging technologies},
  school      = {Universit{\"a}t Potsdam},
  pages     = {135},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}