@phdthesis{Adam2024, author = {Adam, Jan P.}, title = {Top-Management-Support und die Digitalisierung von Verwaltungsleistungen}, doi = {10.25932/publishup-64713}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-647132}, school = {Universit{\"a}t Potsdam}, pages = {xii, 250}, year = {2024}, abstract = {Digitalization is a key component of current administrative reforms. Despite its high importance and long-standing efforts, the balance of administrative digitalization in Germany remains ambivalent. This study investigates the influencing factors on the implementation of digitalization projects in public administration, with a special focus on the role of top management support. This study focuses on three successful digitalization projects from the German Online Access Act (OZG) and analyzes, using problem-centered expert interviews, the influencing factors on the implementation of OZG projects and the role of management in this process. The analysis is theoretically grounded and based on the approach of bounded rationality and the economic theory of bureaucracy. The results suggest that the identified influencing factors affect the reusability and maturity level of administrative services differently and can be interpreted as consequences of bounded rationality in the human problem-solving process. Managers influence the bounded rationality of operational actors by implementing appropriate strategies in the support of their implementation tasks. This includes providing resources, contributing their expertise, making information accessible, changing decision-making pathways, and contributing to conflict resolution. The study provides valuable insights into actual management practices and derives recommendations for the implementation of public digitalization projects and the management of public administrations. This study makes an important contribution to understanding the influence of management in digitalization. It also underscores the need for further research in this area to better understand the practices and challenges of administrative digitalization and to effectively address them.}, language = {de} } @inproceedings{TeichmannUllrichKotarskietal.2021, author = {Teichmann, Malte and Ullrich, Andr{\´e} and Kotarski, David and Gronau, Norbert}, title = {Facing the demographic change}, series = {SSRN eLibrary / Social Science Research Network}, booktitle = {SSRN eLibrary / Social Science Research Network}, publisher = {Social Science Electronic Publ.}, address = {[Erscheinungsort nicht ermittelbar]}, issn = {1556-5068}, doi = {10.2139/ssrn.3858716}, pages = {6}, year = {2021}, abstract = {Digitization and demographic change are enormous challenges for companies. Learning factories as innovative learning places can help prepare older employees for the digital change but must be designed and configured based on their specific learning requirements. To date, however, there are no particular recommendations to ensure effective age-appropriate training of bluecollar workers in learning factories. Therefore, based on a literature review, design characteristics and attributes of learning factories and learning requirements of older employees are presented. Furthermore, didactical recommendations for realizing age-appropriate learning designs in learning factories and a conceptualized scenario are outlined by synthesizing the findings.}, language = {en} } @incollection{Borck2023, author = {Borck, Rainald}, title = {Energy policies, agglomeration, and pollution}, series = {Handbook of labor, human resources and population economics}, booktitle = {Handbook of labor, human resources and population economics}, editor = {Zimmermann, Klaus F.}, publisher = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-57365-6}, doi = {10.1007/978-3-319-57365-6_421-1}, pages = {15}, year = {2023}, abstract = {This chapter reviews the interplay of agglomeration and pollution as well as the effect of energy policies on pollution in an urban context. It starts by describing the effect of agglomeration on pollution. While this effect is theoretically ambiguous, empirical research tends to find that larger cities are more polluted, but per capita emissions fall with city size. The chapter discusses the implications for optimal city size. Conversely, urban pollution tends to discourage agglomeration if larger cities are more exposed to pollution. The chapter then considers various energy policies and their effect on urban pollution. Specifically, it looks at the effects of energy and transport policies as well as urban policies such as zoning.}, language = {en} } @misc{SandbergAlnoorTiberius2022, author = {Sandberg, Helene and Alnoor, Alhamzah and Tiberius, Victor}, title = {Environmental, social, and governance ratings and financial performance}, 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 = {4}, issn = {1867-5808}, doi = {10.25932/publishup-60880}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-608807}, pages = {21}, year = {2022}, abstract = {Long-term value creation is expected not only to be concerned with maximizing shareholder value but also includes the impact on other stakeholders and the environment. Environmental, social, and governance (ESG) issues are therefore gaining increasing importance, in line with the growing demand for corporate sustainability. ESG ratings foster the comparison of companies with respect to their sustainable practices. This study aims to investigate how ESG ratings impact financial performance in the European food industry. Ordinary least squares regression is applied to analyze the relation between ESG ratings and financial performance over a 4-year period from 2017 to 2020. The profitability measures Return on Assets (ROA) and Return on Equity (ROE) are employed as financial performance measures, while ESG ratings are obtained from the database CSRHub. Results show that higher ESG ratings are associated with better financial performance. Although the effect is modest in the present study, the findings support previous results that ESG ratings are positively related to financial performance. Nonetheless, they also highlight that ESG ratings strongly converge to the mean, which depicts the need to reassess whether ESG ratings are able to measure actual ESG behavior.}, language = {en} } @inproceedings{VladovaUllrichBenderetal.2021, author = {Vladova, Gergana and Ullrich, Andr{\´e} and Bender, Benedict and Gronau, Norbert}, title = {Yes, we can (?)}, series = {Technology and innovation in learning, teaching and education : second international conference, TECH-EDU 2020, Vila Real, Portugal, December 2-4, 2020 : proceedings}, booktitle = {Technology and innovation in learning, teaching and education : second international conference, TECH-EDU 2020, Vila Real, Portugal, December 2-4, 2020 : proceedings}, editor = {Reis, Ars{\´e}nio and Barroso, Jo{\~a}o and Lopes, J. Bernardino and Mikropoulos, Tassos and Fan, Chih-Wen}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-73987-4}, doi = {10.1007/978-3-030-73988-1_17}, pages = {225 -- 235}, year = {2021}, abstract = {The COVID-19 crisis has caused an extreme situation for higher education institutions around the world, where exclusively virtual teaching and learning has become obligatory rather than an additional supporting feature. This has created opportunities to explore the potential and limitations of virtual learning formats. This paper presents four theses on virtual classroom teaching and learning that are discussed critically. We use existing theoretical insights extended by empirical evidence from a survey of more than 850 students on acceptance, expectations, and attitudes regarding the positive and negative aspects of virtual teaching. The survey responses were gathered from students at different universities during the first completely digital semester (Spring-Summer 2020) in Germany. We discuss similarities and differences between the subjects being studied and highlight the advantages and disadvantages of virtual teaching and learning. Against the background of existing theory and the gathered data, we emphasize the importance of social interaction, the combination of different learning formats, and thus context-sensitive hybrid learning as the learning form of the future.}, language = {en} } @article{SandbergAlnoorTiberius2022, author = {Sandberg, Helene and Alnoor, Alhamzah and Tiberius, Victor}, title = {Environmental, social, and governance ratings and financial performance}, series = {Business strategy and the environment}, volume = {32}, journal = {Business strategy and the environment}, number = {4}, publisher = {Wiley}, address = {New York}, issn = {0964-4733}, doi = {10.1002/bse.3259}, pages = {2471 -- 2489}, year = {2022}, abstract = {Long-term value creation is expected not only to be concerned with maximizing shareholder value but also includes the impact on other stakeholders and the environment. Environmental, social, and governance (ESG) issues are therefore gaining increasing importance, in line with the growing demand for corporate sustainability. ESG ratings foster the comparison of companies with respect to their sustainable practices. This study aims to investigate how ESG ratings impact financial performance in the European food industry. Ordinary least squares regression is applied to analyze the relation between ESG ratings and financial performance over a 4-year period from 2017 to 2020. The profitability measures Return on Assets (ROA) and Return on Equity (ROE) are employed as financial performance measures, while ESG ratings are obtained from the database CSRHub. Results show that higher ESG ratings are associated with better financial performance. Although the effect is modest in the present study, the findings support previous results that ESG ratings are positively related to financial performance. Nonetheless, they also highlight that ESG ratings strongly converge to the mean, which depicts the need to reassess whether ESG ratings are able to measure actual ESG behavior.}, language = {en} } @article{StieglitzMirbabaieDeubeletal.2023, author = {Stieglitz, Stefan and Mirbabaie, Milad and Deubel, Annika and Braun, Lea-Marie and Kissmer, Tobias}, title = {The potential of digital nudging to bridge the gap between environmental attitude and behavior in the usage of smart home applications}, series = {International Journal of Information Management}, volume = {72}, journal = {International Journal of Information Management}, publisher = {Elsevier}, address = {Oxford}, issn = {0268-4012}, doi = {10.1016/j.ijinfomgt.2023.102665}, year = {2023}, abstract = {Despite energy efficiency measures, global energy demand has gradually increased due to global economic growth and changes in consumer behavior. Even if people are aware of the problem and want to change their energy consumption, they have difficulty acting on their attitudes. This is called the attitude-behavior gap. To narrow this gap and reduce energy consumption and CO2 emissions, behavioral interventions beyond technological advances must be considered. A promising intervention is nudging, which uses insights from behavioral economics to gently nudge individuals toward more sustainable choices. In this study, we investigate how modifying digital choice architectures with nudges can be used to influence consumer energy conservation behavior in smart home applications (SHAs). We conducted an online experiment with 391 participants to test the effectiveness of the following three digital nudges in an SHA: self-commitment, reminder, and social norm nudge. While the results of a structural equation model indicated no effect on bridging the gap between attitude and behavior, we found the potential to promote energy conservation with two nudge types. Thus, this paper makes substantial contribution to persuasive and information systems-enabled sustainability for a better world in the form of digital nudges for emerging technologies.}, language = {en} } @article{StieglitzMirbabaieDeubeletal.2024, author = {Stieglitz, Stefan and Mirbabaie, Milad and Deubel, Annika and Braun, Lea-Marie and Kissmer, Tobias}, title = {Corrigendum to "The potential of digital nudging to bridge the gap between environmental attitude and behavior in the usage of smart home applications" [International Journal of Information Management 72 (2023) 102665]}, series = {International journal of information management}, volume = {76}, journal = {International journal of information management}, publisher = {Elsevier}, address = {Oxford}, issn = {0268-4012}, doi = {10.1016/j.ijinfomgt.2024.102774}, pages = {2}, year = {2024}, abstract = {We would like to inform the readers and editors of the journal that we have discovered some errors in the references of our paper. These errors were brought to our attention by a reader who noticed some inconsistencies between the citations in the text and the bibliography. Upon further investigation, we realized that our literature management software had mistakenly linked some of the references to wrong or non-existent sources. We apologize for this oversight and assure you that it did not affect the validity or quality of our arguments and results, which were based on the correct sources. Below you find a list of the incorrect references along with their corresponding correct ones. We hope that this correction statement will clarify any confusion or misunderstanding that may have arisen from this mistake. The authors would like to apologise for any inconvenience caused.}, language = {en} } @misc{PanzerBenderGronau2021, author = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert}, title = {Deep reinforcement learning in production planning and control}, 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}, issn = {2701-6277}, doi = {10.25932/publishup-60572}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-605722}, pages = {13}, year = {2021}, abstract = {Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep reinforcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensorand process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.}, language = {en} } @inproceedings{PanzerBenderGronau2021, author = {Panzer, Marcel and Bender, Benedict and Gronau, Norbert}, title = {Deep reinforcement learning in production planning and control}, series = {Proceedings of the Conference on Production Systems and Logistics}, booktitle = {Proceedings of the Conference on Production Systems and Logistics}, publisher = {Institutionelles Repositorium der Leibniz Universit{\"a}t Hannover}, address = {Hannover}, issn = {2701-6277}, doi = {10.15488/11238}, pages = {535 -- 545}, year = {2021}, abstract = {Increasingly fast development cycles and individualized products pose major challenges for today's smart production systems in times of industry 4.0. The systems must be flexible and continuously adapt to changing conditions while still guaranteeing high throughputs and robustness against external disruptions. Deep rein- forcement learning (RL) algorithms, which already reached impressive success with Google DeepMind's AlphaGo, are increasingly transferred to production systems to meet related requirements. Unlike supervised and unsupervised machine learning techniques, deep RL algorithms learn based on recently collected sensor- and process-data in direct interaction with the environment and are able to perform decisions in real-time. As such, deep RL algorithms seem promising given their potential to provide decision support in complex environments, as production systems, and simultaneously adapt to changing circumstances. While different use-cases for deep RL emerged, a structured overview and integration of findings on their application are missing. To address this gap, this contribution provides a systematic literature review of existing deep RL applications in the field of production planning and control as well as production logistics. From a performance perspective, it became evident that deep RL can beat heuristics significantly in their overall performance and provides superior solutions to various industrial use-cases. Nevertheless, safety and reliability concerns must be overcome before the widespread use of deep RL is possible which presumes more intensive testing of deep RL in real world applications besides the already ongoing intensive simulations.}, language = {en} }