@inproceedings{54025,
  abstract     = {{Excellent Information Systems (IS) bachelor or master student theses have the potential to inform the
scientific community about interesting findings about IS phenomena. However, transforming such
theses into scientific working papers is not only time-consuming for the student and the supervisor, but
also purely voluntary. Part of the problem is that few IS faculties offer any structured course for the
transformation process as part of their curriculum. This significantly reduces the proportion of
outstanding theses that are developed into working papers and, ultimately, into publications, resulting
in a loss of knowledge for the broader IS community. To address this structural deficit, we aim to
develop and implement a credit course and open educational resources (e.g., course schedule, slides,
videos) that support students in developing their theses into publishable scientific research papers. This
approach not only enriches the scientific discourse but also presents a research-oriented educational
disruption for the IS community.}},
  author       = {{Althaus, Maike and Hansmeier, Philipp}},
  booktitle    = {{Proceedings of the Thirty-Second European Conference on Information Systems (ECIS 2024)}},
  keywords     = {{Student Thesis, Scientific Publishing, Course Implementation}},
  location     = {{Paphos, Cyprus}},
  title        = {{{The Imperative of Revival Strategies through Digital Transformation in the Cultural Sector - A Taxonomy Approach}}},
  year         = {{2024}},
}

@inproceedings{33490,
  abstract     = {{Algorithmic fairness in Information Systems (IS) is a concept that aims to mitigate systematic discrimination and bias in automated decision-making. However, previous research argued that different fairness criteria are often incompatible. In hiring, AI is used to assess and rank applicants according to their fit for vacant positions. However, various types of bias also exist for AI-based algorithms (e.g., using biased historical data). To reduce AI’s bias and thereby unfair treatment, we conducted a systematic literature review to identify suitable strategies for the context of hiring. We identified nine fundamental articles in this context and extracted four types of approaches to address unfairness in AI, namely pre-process, in-process, post-process, and feature selection. Based on our findings, we (a) derived a research agenda for future studies and (b) proposed strategies for practitioners who design and develop AIs for hiring purposes.}},
  author       = {{Rieskamp, Jonas and Hofeditz, Lennart and Mirbabaie, Milad and Stieglitz, Stefan}},
  booktitle    = {{Proceedings of the Annual Hawaii International Conference on System Sciences (HICSS)}},
  keywords     = {{fairness in AI, SLR, hiring, AI implementation, AI-based algorithms}},
  title        = {{{Approaches to Improve Fairness when Deploying AI-based Algorithms in Hiring – Using a Systematic Literature Review to Guide Future Research}}},
  year         = {{2023}},
}

@article{35732,
  abstract     = {{While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.}},
  author       = {{Bartelheimer, Christian and zur Heiden, Philipp and Lüttenberg, Hedda and Beverungen, Daniel}},
  issn         = {{1019-6781}},
  journal      = {{Electronic Markets}},
  keywords     = {{Platform, Text mining, Machine learning, Data communications, Interpretive research, Systems design and implementation}},
  pages        = {{375--396}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Systematizing the lexicon of platforms in information systems: a data-driven study}}},
  doi          = {{10.1007/s12525-022-00530-6}},
  volume       = {{32}},
  year         = {{2022}},
}

@inproceedings{8538,
  abstract     = {{This paper explores Finnish, German and Swedish older adults’ perceptions of a future welfare service with increased use of welfare technologies, specifically care robots. The issues are the rapid digitalization and development of health and welfare technology, which presently is mainly technology driven (not need or user driven), and the demographic challenge. The aim of the study was to explore older adults’ perception of the future use of welfare technology or care robots. A qualitative approach with focus group discussions was employed, followed by thematic analysis. The results are presented in four overall themes: the impact on daily life for older adults and professional caregivers, codes of practice and terms of use, dissemination of information and knowledge, and conditions for successful implementation. There were significant differences in the informants’ attitudes toward and knowledge about care robots. However, the informants’ attitudes appeared to change during the focus groups and in general, became more positive. Authentic needs, which care robots could support, refer to independence, safety and security, and the ability to manage or ease daily life or working life. The results suggest that older adults, after receiving relevant information, were open to the idea of being supported by care robots in their daily lives.}},
  author       = {{Johansson-Pajala, Rose-Marie and Thommes, Kirsten and Hoppe, Julia Amelie and Tuisku, Outi and Hennala, Lea and Pekkarinen, Satu and  Melkas, Helinä and Gustafsson, Christine }},
  booktitle    = {{HCII 2019}},
  editor       = {{Zhou, Jia and Salvendy, Gavriel}},
  isbn         = {{978-3-030-22011-2}},
  keywords     = {{Care robots, Older adults, Implementation, Information, Perceptions, Welfare technology}},
  location     = {{Orlando}},
  pages        = {{212--227}},
  publisher    = {{Springer}},
  title        = {{{Improved Knowledge Changes the Mindset: Older Adults’ Perceptions of Care Robots}}},
  doi          = {{10.1007/978-3-030-22012-9_16}},
  volume       = {{11592}},
  year         = {{2019}},
}

@inproceedings{10676,
  author       = {{Ho, Nam and Kaufmann, Paul and Platzner, Marco}},
  booktitle    = {{2017 International Conference on Field Programmable Technology (ICFPT)}},
  keywords     = {{Linux, cache storage, microprocessor chips, multiprocessing systems, LEON3-Linux based multicore processor, MiBench suite, block sizes, cache adaptation, evolvable caches, memory-to-cache-index mapping function, processor caches, reconfigurable cache mapping optimization, reconfigurable hardware technology, replacement strategies, standard Linux OS, time a complete hardware implementation, Hardware, Indexes, Linux, Measurement, Multicore processing, Optimization, Training}},
  pages        = {{215--218}},
  title        = {{{Evolvable caches: Optimization of reconfigurable cache mappings for a LEON3/Linux-based multi-core processor}}},
  doi          = {{10.1109/FPT.2017.8280144}},
  year         = {{2017}},
}