Pub Date : 2023-12-18DOI: 10.1007/s00287-023-01556-6
Patric Hammler, Nicolas Riesterer, Torsten Braun
The operation of inventory systems plays an important role in the success of manufacturing companies, making it a highly relevant domain for optimization. In particular, the domain lends itself to being approached via Deep Reinforcement Learning (DRL) models due to it requiring sequential reorder decisions based on uncertainty to minimize cost. In this paper, we evaluate state-of-the-art optimization approaches to determine whether Deep Reinforcement Learning can be applied to the multi-echelon inventory optimization (MEIO) framework in a practically feasible manner to generate fully dynamic reorder policies. We investigate how it performs in comparison to an optimized static reorder policy, how robust it is when it comes to structural changes in the environment, and whether the use of DRL is safe in terms of risk in real-world applications. Our results show promising performance for DRL with potential for improvement in terms of minimizing risky behavior.
{"title":"Fully dynamic reorder policies with deep reinforcement learning for multi-echelon inventory management","authors":"Patric Hammler, Nicolas Riesterer, Torsten Braun","doi":"10.1007/s00287-023-01556-6","DOIUrl":"https://doi.org/10.1007/s00287-023-01556-6","url":null,"abstract":"<p>The operation of inventory systems plays an important role in the success of manufacturing companies, making it a highly relevant domain for optimization. In particular, the domain lends itself to being approached via Deep Reinforcement Learning (DRL) models due to it requiring sequential reorder decisions based on uncertainty to minimize cost. In this paper, we evaluate state-of-the-art optimization approaches to determine whether Deep Reinforcement Learning can be applied to the multi-echelon inventory optimization (MEIO) framework in a practically feasible manner to generate fully dynamic reorder policies. We investigate how it performs in comparison to an optimized static reorder policy, how robust it is when it comes to structural changes in the environment, and whether the use of DRL is safe in terms of risk in real-world applications. Our results show promising performance for DRL with potential for improvement in terms of minimizing risky behavior.</p>","PeriodicalId":39769,"journal":{"name":"Informatik-Spektrum","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140888179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-21DOI: 10.1007/s00287-023-01553-9
René Riedl, Thomas Fischer, Martin Reuter
Digital stress is a form of stress caused by the use and ubiquity of digital technologies. More and more scientists and practitioners are interested in the phenomenon of digital stress, its causes (e.g., constant smartphone accessibility, unreliable and unstable systems, information overload), and its consequences (e.g., negative health effects, dissatisfaction, or reduced performance and productivity). In an article published in Frontiers in Psychology (12:607598), we introduced the English version of the Digital Stressors Scale (DSS). This is a psychometrically evaluated self-report questionnaire for measuring digital stress in the workplace. In the current paper, we present a short version of this original questionnaire. The original questionnaire consists of 50 questions (items), whereas the short version presented here contains 30 questions. In accordance with the original questionnaire, the entire digital stress experienced by an individual in the workplace is based on 10 stress categories, with each category being assessed with three questions in the short version. Academics can use the questionnaire to quantify digital stress and its 10 dimensions for reliable and valid measurement within the context of scientific research. Practitioners benefit from using this assessment tool to measure the digital stress perceived by employees in the organizational environment. This is a precondition for implementing effective coping strategies.
{"title":"Measuring digital stress in the workplace context","authors":"René Riedl, Thomas Fischer, Martin Reuter","doi":"10.1007/s00287-023-01553-9","DOIUrl":"https://doi.org/10.1007/s00287-023-01553-9","url":null,"abstract":"<p>Digital stress is a form of stress caused by the use and ubiquity of digital technologies. More and more scientists and practitioners are interested in the phenomenon of digital stress, its causes (e.g., constant smartphone accessibility, unreliable and unstable systems, information overload), and its consequences (e.g., negative health effects, dissatisfaction, or reduced performance and productivity). In an article published in <i>Frontiers in Psychology</i> (12:607598), we introduced the English version of the Digital Stressors Scale (DSS). This is a psychometrically evaluated self-report questionnaire for measuring digital stress in the workplace. In the current paper, we present a short version of this original questionnaire. The original questionnaire consists of 50 questions (items), whereas the short version presented here contains 30 questions. In accordance with the original questionnaire, the entire digital stress experienced by an individual in the workplace is based on 10 stress categories, with each category being assessed with three questions in the short version. Academics can use the questionnaire to quantify digital stress and its 10 dimensions for reliable and valid measurement within the context of scientific research. Practitioners benefit from using this assessment tool to measure the digital stress perceived by employees in the organizational environment. This is a precondition for implementing effective coping strategies.</p>","PeriodicalId":39769,"journal":{"name":"Informatik-Spektrum","volume":"5 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138503947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1007/s00287-023-01549-5
Paul Theurich, Josepha Witt, Sebastian Richter
Abstract Facing the increasing annual cybersecurity costs, threat modelling (TM) is a method to consider security as early as possible in the software development life cycle (SDLC). Thereby, TM helps to identify and address security-related design flaws in information systems. As the original TM approach is based on sequential development, it is not aligned with today’s predominantly agile environments. This results in several challenges. However, TM’s implementation in an agile development approach lacks the recommendations on how to tackle these challenges. Therefore, we assess the state-of-the-art of TM challenges and practices in agile environments by conducting a literature review covering 220 papers. Thereby, we identify nine categories of challenges and six categories of practices. We propose a valuable artefact for practitioners by mapping challenges and practices to the agile SDLC and by creating a matrix highlighting how the practices address the challenges of TM in an agile environment.
{"title":"Practices and challenges of threat modelling in agile environments","authors":"Paul Theurich, Josepha Witt, Sebastian Richter","doi":"10.1007/s00287-023-01549-5","DOIUrl":"https://doi.org/10.1007/s00287-023-01549-5","url":null,"abstract":"Abstract Facing the increasing annual cybersecurity costs, threat modelling (TM) is a method to consider security as early as possible in the software development life cycle (SDLC). Thereby, TM helps to identify and address security-related design flaws in information systems. As the original TM approach is based on sequential development, it is not aligned with today’s predominantly agile environments. This results in several challenges. However, TM’s implementation in an agile development approach lacks the recommendations on how to tackle these challenges. Therefore, we assess the state-of-the-art of TM challenges and practices in agile environments by conducting a literature review covering 220 papers. Thereby, we identify nine categories of challenges and six categories of practices. We propose a valuable artefact for practitioners by mapping challenges and practices to the agile SDLC and by creating a matrix highlighting how the practices address the challenges of TM in an agile environment.","PeriodicalId":39769,"journal":{"name":"Informatik-Spektrum","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135004355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1007/s00287-023-01547-7
Sophie Hundertmark, Nils Hafner, Edy Portmann
Zusammenfassung Automatisierung mithilfe von Conversational AIs ist in der Finanzwelt keine Seltenheit mehr. Banken und Versicherungen stehen vor der großen Herausforderung, trotz Automatisierung ein möglichst individuelles Kundenerlebnis zu bieten. Character Computing ist eine Methode, die aufzeigt wie Conversational AIs zur Steigerung der Customer Experience jedes einzelnen Nutzers, gestaltet werden sollten. Mithilfe von Character Computing sollen sich Conversational AIs individuell auf die Wünsche des einzelnen Kunden anpassen können. Doch Character Computing allein reicht nicht aus, wie die Ergebnisse dieses Experiments zeigen. Das Paper zeigt, wie mithilfe von Experimenten Regeln für die Anwendung von Character Computing erstellt werden können. Es wird aber auch gezeigt, wie andere Methoden, wie beispielsweise die Conversational Theory oder mehrdimensionale Fuzzy Classifications, integriert werden müssten.
{"title":"Dialog-Anpassung an den Charakter des Benutzers – Anwendung der Methoden des Charakter Computing","authors":"Sophie Hundertmark, Nils Hafner, Edy Portmann","doi":"10.1007/s00287-023-01547-7","DOIUrl":"https://doi.org/10.1007/s00287-023-01547-7","url":null,"abstract":"Zusammenfassung Automatisierung mithilfe von Conversational AIs ist in der Finanzwelt keine Seltenheit mehr. Banken und Versicherungen stehen vor der großen Herausforderung, trotz Automatisierung ein möglichst individuelles Kundenerlebnis zu bieten. Character Computing ist eine Methode, die aufzeigt wie Conversational AIs zur Steigerung der Customer Experience jedes einzelnen Nutzers, gestaltet werden sollten. Mithilfe von Character Computing sollen sich Conversational AIs individuell auf die Wünsche des einzelnen Kunden anpassen können. Doch Character Computing allein reicht nicht aus, wie die Ergebnisse dieses Experiments zeigen. Das Paper zeigt, wie mithilfe von Experimenten Regeln für die Anwendung von Character Computing erstellt werden können. Es wird aber auch gezeigt, wie andere Methoden, wie beispielsweise die Conversational Theory oder mehrdimensionale Fuzzy Classifications, integriert werden müssten.","PeriodicalId":39769,"journal":{"name":"Informatik-Spektrum","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135003702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1007/s00287-023-01546-8
Marco Barenkamp
{"title":"Einflussnahme großer Sprachmodelle auf die moderne Arbeitswelt","authors":"Marco Barenkamp","doi":"10.1007/s00287-023-01546-8","DOIUrl":"https://doi.org/10.1007/s00287-023-01546-8","url":null,"abstract":"","PeriodicalId":39769,"journal":{"name":"Informatik-Spektrum","volume":"1 1","pages":"185 - 188"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90249156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1007/s00287-023-01548-6
Michael Grebe, Marc Roman Franke, Armin Heinzl
Abstract Artificial intelligence (AI) is one of the most transformative information technologies of our century. Despite high expectations across all industries and corporate functions, companies have difficulties to realize the full potential of AI and struggle to move beyond AI pilots. This article provides empirical evidence from survey data and three case studies to better understand the value drivers of AI. Leading companies specify use cases from a business perspective and leverage domain expertise to tap into value pools by combining technology with human capabilities. They provide fundamental enablers for AI like digital and data platforms, a data-centric organization with solid governance, and a dedicated human resource base to facilitate AI value creation. Moreover, these firms assess the financial and business impact of AI initiatives and reprioritize projects if the expected value does not materialize. Based on these insights, recommendations to better scale and derive value from AI projects will be offered.
{"title":"Artificial intelligence: how leading companies define use cases, scale-up utilization, and realize value","authors":"Michael Grebe, Marc Roman Franke, Armin Heinzl","doi":"10.1007/s00287-023-01548-6","DOIUrl":"https://doi.org/10.1007/s00287-023-01548-6","url":null,"abstract":"Abstract Artificial intelligence (AI) is one of the most transformative information technologies of our century. Despite high expectations across all industries and corporate functions, companies have difficulties to realize the full potential of AI and struggle to move beyond AI pilots. This article provides empirical evidence from survey data and three case studies to better understand the value drivers of AI. Leading companies specify use cases from a business perspective and leverage domain expertise to tap into value pools by combining technology with human capabilities. They provide fundamental enablers for AI like digital and data platforms, a data-centric organization with solid governance, and a dedicated human resource base to facilitate AI value creation. Moreover, these firms assess the financial and business impact of AI initiatives and reprioritize projects if the expected value does not materialize. Based on these insights, recommendations to better scale and derive value from AI projects will be offered.","PeriodicalId":39769,"journal":{"name":"Informatik-Spektrum","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135004353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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