@article{20212,
  abstract     = {{Ideational impact refers to the uptake of a paper's ideas and concepts by subsequent research. It is defined in stark contrast to total citation impact, a measure predominantly used in research evaluation that assumes that all citations are equal. Understanding ideational impact is critical for evaluating research impact and understanding how scientific disciplines build a cumulative tradition. Research has only recently developed automated citation classification techniques to distinguish between different types of citations and generally does not emphasize the conceptual content of the citations and its ideational impact. To address this problem, we develop Deep Content-enriched Ideational Impact Classification (Deep-CENIC) as the first automated approach for ideational impact classification to support researchers' literature search practices. We evaluate Deep-CENIC on 1,256 papers citing 24 information systems review articles from the IT business value domain. We show that Deep-CENIC significantly outperforms state-of-the-art benchmark models. We contribute to information systems research by operationalizing the concept of ideational impact, designing a recommender system for academic papers based on deep learning techniques, and empirically exploring the ideational impact of the IT business value domain.
}},
  author       = {{Prester, Julian and Wagner, Gerit and Schryen, Guido and Hassan, Nik Rushdi}},
  journal      = {{Decision Support Systems}},
  keywords     = {{Ideational impact, citation classification, academic recommender systems, natural language processing, deep learning, cumulative tradition}},
  number       = {{January}},
  title        = {{{Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach}}},
  volume       = {{140}},
  year         = {{2021}},
}

@article{20844,
  abstract     = {{Review papers are essential for knowledge development in IS. While some are cited twice a day, others accumulate single digit citations over a decade. The magnitude of these differences prompts us to analyze what distinguishes those reviews that have proven to be integral to scientific progress from those that might be considered less impactful. Our results highlight differences between reviews aimed at describing, understanding, explaining, and theory testing. Beyond the control variables, they demonstrate the importance of methodological transparency and the development of research agendas. These insights inform all stakeholders involved in the development and publication of review papers.}},
  author       = {{Wagner, Gerit and Prester, Julian and Roche, Maria and Schryen, Guido and Benlian, Alexander and Paré, Guy and Templier, Mathieu}},
  journal      = {{Information & Management}},
  keywords     = {{Literature review, review papers, scientometric, scientific impact, citation analysis}},
  number       = {{3}},
  title        = {{{Which Factors Affect the Scientific Impact of Review Papers in IS Research? A Scientometric Study}}},
  volume       = {{58}},
  year         = {{2021}},
}

@inproceedings{24280,
  abstract     = {{Challenges in decisions on technical changes are the lack of knowledge about the expected impact and change propagation. Currently, no literature study contains a systematic differentiation and evaluation of existing approaches, which is a prerequisite for practitioners to select a suitable approach. This research aims at defining differentiation criteria as well as generally applicable requirements for evaluation. A four-step approach is used: systematic literature review on approaches for impact analysis of engineering changes (1), categorization and prioritization of approaches based on reoccuring elements (2), derivation of context specific requirements for evaluation (3), and evaluation of approaches (4). The result indicates existing potential of object-oriented modeling approaches.}},
  author       = {{Gräßler, Iris and Wiechel, Dominik}},
  booktitle    = {{DS 111: Proceedings of the 32nd Symposium Design for X}},
  editor       = {{Krause, Dieter and Paetzold, Kristin and Wartzack, Sandro}},
  keywords     = {{Engineering Change Management, Impact Analysis, Engineering  Changes, Model-based Systems Engineering, Product Developmen}},
  location     = {{Tutzing}},
  title        = {{{Systematische Bewertung von Auswirkungsanalysen des Engineering Change Managements}}},
  doi          = {{10.35199/dfx2021.12}},
  year         = {{2021}},
}

@techreport{17019,
  abstract     = {{The scientific impact of research papers is multi-dimensional and can be determined quantitatively by means of citation analysis and qualitatively by means of content analysis. Accounting for the widely acknowledged limitations of pure citation analysis, we adopt a knowledge-based perspective on scientific impact to develop a methodology for content-based citation analysis which allows determining how papers have enabled knowledge development in subsequent research (knowledge impact). As knowledge development differs between research genres, we develop a new knowledgebased citation analysis methodology for the genre of standalone literature reviews (LRs). We apply the suggested methodology to the IS business value domain by manually coding 22 LRs and 1,228 citing papers (CPs) and show that the results challenge the assumption that citations indicate knowledge impact. We derive implications for distinguishing knowledge impact from citation impact in the LR genre. Finally, we develop recommendations for authors of LRs, scientific evaluation committees and editorial boards of journals how to apply and benefit from the suggested methodology, and we discuss its efficiency and automatization.}},
  author       = {{Schryen, Guido and Wagner, Gerit and Benlian, Alexander}},
  keywords     = {{Scientific impact, knowledge impact, content-based citation analysis, methodology}},
  title        = {{{Distinguishing Knowledge Impact from Citation Impact: A Methodology for Analysing Knowledge Impact for the Literature Review Genre}}},
  year         = {{2020}},
}

@article{9575,
  abstract     = {{Many ultrasonic processes are based on the mechanical contact of oscillating parts. Within ultrasonic machining (drilling, milling, grinding) micro impacts lead to abrasion at the processed workpiece and hopefully do not damage the tool. In ultrasonic motors ideally neither part gets worn. Thus the appropriate design of contact partners as well as their kinematics is a substantial task during the development of such devices. A first step to optimize contact mechanics is to understand their behavior and dependencies on parameter variations, such as vibration amplitude and pre-stress of the impacting parts. For a detailed understanding models validated with convincing experimental data from measurements are absolutely essential. This paper focuses on simple vibro-impact experiments which can be used as benchmark data for future models. The setup of the experiment and first experimental investigations are described in detail.}},
  author       = {{Twiefel, Jens and Potthast, Christian and Mracek, Maik and Hemsel, Tobias and Sattel, Thomas and Wallaschek, Jörg}},
  issn         = {{1385-3449}},
  journal      = {{Journal of Electroceramics}},
  keywords     = {{Contact measurements, Vibro-impact, Ultrasonic application}},
  number       = {{3-4}},
  pages        = {{209--214}},
  publisher    = {{Springer US}},
  title        = {{{Fundamental experiments as benchmark problems for modeling ultrasonic micro-impact processes}}},
  doi          = {{10.1007/s10832-007-9169-4}},
  volume       = {{20}},
  year         = {{2008}},
}