@article{AbramovaWagnerOltetal.2022, author = {Abramova, Olga and Wagner, Amina and Olt, Christian M. and Buxmann, Peter}, title = {One for all, all for one}, series = {International Journal of Information Management}, volume = {64}, journal = {International Journal of Information Management}, publisher = {Elsevier}, address = {Kidlington}, issn = {0268-4012}, doi = {10.1016/j.ijinfomgt.2022.102473}, pages = {1 -- 16}, year = {2022}, abstract = {We propose a conceptual model of acceptance of contact tracing apps based on the privacy calculus perspective. Moving beyond the duality of personal benefits and privacy risks, we theorize that users hold social considerations (i.e., social benefits and risks) that underlie their acceptance decisions. To test our propositions, we chose the context of COVID-19 contact tracing apps and conducted a qualitative pre-study and longitudinal quantitative main study with 589 participants from Germany and Switzerland. Our findings confirm the prominence of individual privacy calculus in explaining intention to use and actual behavior. While privacy risks are a significant determinant of intention to use, social risks (operationalized as fear of mass surveillance) have a notably stronger impact. Our mediation analysis suggests that social risks represent the underlying mechanism behind the observed negative link between individual privacy risks and contact tracing apps' acceptance. Furthermore, we find a substantial intention-behavior gap.}, language = {en} } @masterthesis{Beel2022, type = {Bachelor Thesis}, author = {Beel, Leon}, title = {Teilen von Wissen im Offboarding in der {\"o}ffentlichen Verwaltung Deutschlands}, issn = {2190-4561}, doi = {10.25932/publishup-56210}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-562108}, school = {Universit{\"a}t Potsdam}, pages = {IV, 44}, year = {2022}, abstract = {Die vorliegende Arbeit untersucht, inwiefern extrapersonale Einflussfaktoren das Verhalten der Wissensteilung im Offboarding in der {\"o}ffentlichen Verwaltung Deutschlands beeinflussen. Hier besteht eine Forschungsl{\"u}cke, die es insbesondere vor dem Hintergrund einer nahenden Pensionierungswelle und der daraus resultierenden Gefahr eines massiven Wissensverlusts zu schließen gilt. Zu diesem Zweck werden unterschiedliche Analyseebenen verkn{\"u}pft, Einflussfaktoren aus der Literatur herausgearbeitet und in die Theorie des geplanten Verhaltens eingebunden. Anschließend werden Hypothesen formuliert, wie extrapersonale Einflussfaktoren, die sich aus der Verwaltung als organisationalen Kontext und dem Prozess des Offboarding ergeben, das Verhalten der Wissensteilung f{\"o}rdern oder hemmen. Die Testung der Hypothesen erfolgt durch die Erhebung und Auswertung qualitativer Interviewdaten. Daraus resultierende Erkenntnisse verdeutlichen, dass die anstehende Pensionierungswelle in der deutschen Verwaltung eine st{\"a}rkere Ausrichtung des organisationalen Wissensmanagements auf den Prozess des Offboarding und dessen Gestaltung erfordert, um Wissensverluste zu reduzieren.}, language = {de} } @misc{BenlianWienerCrametal.2022, author = {Benlian, Alexander and Wiener, Martin and Cram, W. Alec and Krasnova, Hanna and Maedche, Alexander and Mohlmann, Mareike and Recker, Jan and Remus, Ulrich}, title = {Algorithmic management}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe}, number = {6}, issn = {2363-7005}, doi = {10.25932/publishup-60711}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-607112}, pages = {17}, year = {2022}, language = {en} } @article{BenlianWienerCrametal.2022, author = {Benlian, Alexander and Wiener, Martin and Cram, W. Alec and Krasnova, Hanna and Maedche, Alexander and Mohlmann, Mareike and Recker, Jan and Remus, Ulrich}, title = {Algorithmic management}, series = {Business and information systems engineering}, volume = {64}, journal = {Business and information systems engineering}, number = {6}, publisher = {Springer Gabler}, address = {Wiesbaden}, issn = {2363-7005}, doi = {10.1007/s12599-022-00764-w}, pages = {825 -- 839}, year = {2022}, language = {en} } @article{BoschSmimou2022, author = {Bosch, David and Smimou, Kamal}, title = {Traders' motivation and hedging pressure in commodity futures markets}, series = {Research in international business and finance}, volume = {59}, journal = {Research in international business and finance}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0275-5319}, doi = {10.1016/j.ribaf.2021.101529}, pages = {34}, year = {2022}, abstract = {This study seeks to explain the major drivers of trading activity in commodity futures markets and gage the effect of trading activity on commodity prices. Rather than concentrating on a specific commodity subgroup or a particular type of commodity traders, we provide an extensive overview of the behavior across all market participants and their influence on commodity prices by using a broad set of commodity futures contracts. Although commodity futures returns show co-movement with financial fundamentals (U.S. dollar index, equity, and bond markets), based on the Disaggregated Commitment of Traders Report (DCOT), this relationship cannot be attributed to trading activity. Pricing in commodity markets can be predominantly attributed to hedgers and influential speculators (money managers), whereas small speculators (nonreportable traders) are crucial to some soft commodity futures similar to dealers in metals commodity futures. Furthermore, we find limited cases where inventory changes exert a sizable influence on position changes of DCOT traders.}, 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{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} } @article{BrueckKnauerSchwering2022, author = {Br{\"u}ck, Christian and Knauer, Thorsten and Schwering, Anja}, title = {Disclosure of value-based performance measures}, series = {Accounting and business research}, volume = {53}, journal = {Accounting and business research}, number = {6}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {0001-4788}, doi = {10.1080/00014788.2022.2062585}, pages = {671 -- 698}, year = {2022}, abstract = {We examine the determinants of the disclosure of value-based (VB) performance measures in Germany. We argue that firms are more likely to disclose VB performance measures when information asymmetry is greater, as greater information asymmetry means firms have a greater need to credibly signal a shareholder value orientation. Using a hand-collected dataset of German listed firms covering 1,528 firm-years from 2004 to 2011, we demonstrate that firms are more likely to disclose a VB performance measure if the free float is larger than the blocking minority and also, when firms are large, if they have high foreign sales to total sales ratios and are not cross-listed internationally. Our results indicate that German firms use VB performance measures to improve investor communication and to substantiate their shareholder value orientation. Our results should be interpreted against a background of increased shareholder value orientation and sophisticated cost accounting in German firms.}, 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} } @book{DeekenHinzKlitschetal.2022, author = {Deeken, Johannes and Hinz, Carsten and Klitsch, Constantin and L{\"o}ffler, Robert and Penning, Isabelle and Richter, Christin and Sch{\"a}fer, David}, title = {\#Wirtschaft - Nordrhein-Westfalen}, number = {7/8}, editor = {Kirchner, Vera}, publisher = {Buchner}, address = {Bamberg}, isbn = {978-3-661-82252-5}, pages = {192}, year = {2022}, language = {de} }