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    <publisherName>IGI Global</publisherName>
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    <publishedDate>2025-08-07</publishedDate>
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    <title language="eng">ChatGPT in the Working World: A Qualitative Study</title>
    <abstract language="eng">The authors investigated how ChatGPT transforms workplace tasks by analyzing qualitative survey responses from 78 U.S. professionals in the fields of software, marketing, and academia. This study addresses a gap in understanding the malleability of generative artificial intelligence in diverse professional contexts, a need underscored by ChatGPT’s rapid adoption and mixed impact on work practices. Using a qualitative survey deployed via a validated platform, the authors collected open-ended responses about tasks, challenges, and opportunities. Responses were inductively coded to compare domain-specific applications. The findings show that although ChatGPT is widely used across sectors for tasks such as content creation, research, and idea generation, certain tasks—such as coding in software, strategic communication in marketing, and knowledge acquisition in academia—diverge. The results emphasize the importance of context-sensitive integration strategies and bottom-up adoption approaches to maximize the benefits of artificial intelligence while mitigating risks.</abstract>
    <parentTitle language="eng">Information Resources Management Journal (IRMJ)</parentTitle>
    <identifier type="doi">10.4018/IRMJ.386593</identifier>
    <enrichment key="Reviewstatus">Begutachtet/Reviewed</enrichment>
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    <licence>Creative Commons - CC BY-SA - Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International</licence>
    <author>Pedro Schötteler Libera</author>
    <author>Volker Bilgram</author>
    <author>Sebastian Schötteler</author>
    <author>Jan Mammen</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Generative AI</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Technology Adoption</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Human-AI Interaction</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Organizational Malleability</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Qualitative Research</value>
    </subject>
    <collection role="institutes" number="">Fakultät Maschinenbau und Versorgungstechnik</collection>
    <collection role="institutes" number="">Fakultät Betriebswirtschaft</collection>
    <collection role="Forschungsschwerpunkt" number="5">Digitalisierung &amp; Künstliche Intelligenz</collection>
    <collection role="Forschungsschwerpunkt" number="7">Soziale &amp; ökonomische Transformation</collection>
  </doc>
  <doc>
    <id>2873</id>
    <completedYear>2024</completedYear>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>909</pageFirst>
    <pageLast>925</pageLast>
    <pageNumber>17</pageNumber>
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    <issue>5</issue>
    <volume>29</volume>
    <type>article</type>
    <publisherName>Emerald</publisherName>
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    <publishedDate>2024-07-25</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">The German Supply Chain Due Diligence Act: impacts on sustainable supply chain management from a stakeholder perspective</title>
    <abstract language="eng">Purpose&#13;
The German Supply Chain Due Diligence Act (GSCDDA), as a comprehensive regulation for due diligence in supply chains, will exert profound pressure on companies’ sustainable supply chain management (SSCM). This study aims to examine the affected stakeholders’ polarizing expectations stemming from the GSCDDA, the resulting impacts on SSCM and how these findings compare with theoretical SSCM developments.&#13;
&#13;
&#13;
Design/methodology/approach&#13;
From 5,490 GSCDDA posts on X (formerly “Twitter”), the authors extracted 556 qualitative posts illustrating the GSCDDA discourse and analyzed them from a stakeholder perspective. The posts were classified according to the dimensions of stakeholder groups and expectations (i.e. challenges and opportunities). The authors then synthesized the posts across these dimensions and compared the identified expectations with the SSCM literature.&#13;
&#13;
&#13;
Findings&#13;
Seven stakeholder groups were identified, along with nine challenges (e.g. legal flaws) and four opportunities (e.g. increased transparency). The synthesis of both components revealed highly discussed and conflicting expectations. The theoretical SSCM developments partly differ from the discourse, indicating discernible gaps between theory and practice&#13;
&#13;
&#13;
Practical implications&#13;
Identifying key stakeholder groups supports building synergies between GSCDDA implementers and stakeholders to tackle their challenges and reinforce opportunities.&#13;
&#13;
&#13;
Originality/value&#13;
Due to the growing prevalence of supply chain due diligence regulations, it is essential to consider the legal implications for SSCM. This study explores the link between due diligence concepts and SSCM, and to the best of the authors’ knowledge, this is the first study to analyze how legal pressure shapes stakeholders’ expectations on companies’ SSCM.</abstract>
    <parentTitle language="eng">Supply Chain Management: An International Journal</parentTitle>
    <identifier type="issn">1359-8546</identifier>
    <identifier type="doi">10.1108/SCM-01-2024-0058</identifier>
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This study aims to examine the affected stakeholders\u2019 polarizing expectations stemming from the GSCDDA, the resulting impacts on SSCM and how these findings compare with theoretical SSCM developments.&lt;\/jats:p&gt;\n&lt;\/jats:sec&gt;\n&lt;jats:sec&gt;\n&lt;jats:title content-type=\"abstract-subheading\"&gt;Design\/methodology\/approach&lt;\/jats:title&gt;\n&lt;jats:p&gt;From 5,490 GSCDDA posts on X (formerly \u201cTwitter\u201d), the authors extracted 556 qualitative posts illustrating the GSCDDA discourse and analyzed them from a stakeholder perspective. The posts were classified according to the dimensions of stakeholder groups and expectations (i.e. challenges and opportunities). The authors then synthesized the posts across these dimensions and compared the identified expectations with the SSCM literature.&lt;\/jats:p&gt;\n&lt;\/jats:sec&gt;\n&lt;jats:sec&gt;\n&lt;jats:title content-type=\"abstract-subheading\"&gt;Findings&lt;\/jats:title&gt;\n&lt;jats:p&gt;Seven stakeholder groups were identified, along with nine challenges (e.g. legal flaws) and four opportunities (e.g. increased transparency). The synthesis of both components revealed highly discussed and conflicting expectations. 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    <author>Sebastian Schötteler</author>
    <author>Florian J. Meier</author>
    <author>Eva Gengler</author>
    <author>Sven Laumer</author>
    <collection role="institutes" number="">Fakultät Informatik</collection>
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    <title language="eng">Analysis of Politicians’ Tweets to Explore Political Communication with Social Network Analysis</title>
    <abstract language="eng">This paper illustrates the practical application of cluster analysis, social network analysis, sentiment analysis, and topic analysis in a case study on Twitter data. These techniques provide insights into the public communication patterns between German Members of Parliament (MPs) on Twitter around the time of the 2021 federal election. The question of this work was to determine whether a potential shift in communication towards the inaugurated “Ampel” coalition, made up of the parties SPD, Greens, and FDP, can be derived from Twitter interactions. Twitter data were collected and separated into two time slots: before and after the election. In distinct scenarios, mention, retweet, and reply interactions are&#13;
first considered together and then separately. In these scenarios,the Girvan-Newman Algorithm detects clusters of MPs dependent on the interactions observed. Then, the average inbreeding homophily and other network metrics of the pre- and post-election area are compared. An additional scenario focuses on intra- and inter-party sentiments conveyed within tweet texts. In a fourth scenario, MPs are grouped according to&#13;
their party affiliation, the average inbreeding homophily values of parties, and potential coalitions. A topic analysis handled relevant discussion topics between the successful coalition parties. Changes in communication behavior at these two different time slots are visible. The communication clusters of those MPs differ mostly before and after the election. The average sentiment of the parties towards each other changed positively, although no significant tendency could be derived&#13;
regarding later coalition formations. A determination of the density of the network for the topics also indicates that the importance of the individual topics before and after the formation of the government has a consistent relevance.</abstract>
    <parentTitle language="eng">International Journal On Advances in Networks and Services</parentTitle>
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    <author>Bernhard Schiffer</author>
    <author>David Wolfharth</author>
    <author>Tim Groß</author>
    <author>Thomas Kreidl</author>
    <author>Fabian Model</author>
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      <language>eng</language>
      <type>uncontrolled</type>
      <value>Cluster Analysis; Microblog; Network Metrics; Sentiment Analysis; Social Network Analysis; Topic Analysis</value>
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    <publisherName>University of Zagreb, Faculty of Economics &amp; Business</publisherName>
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    <title language="eng">JUDGED BY ITS COVER: UNDERSTANDING THE FORMATION OF BOOK TESTIMONIAL NETWORKS</title>
    <abstract language="eng">Testimonials, short promotional statements often written by notable authors or critics, are a crucial marketing tool in the publishing industry, contributing to a book’s market success. This study investigates the formation of ties in testimonial networks, focusing on both network-endogenous factors (reciprocity, transitivity and preferential attachment) and exogenous factors tied to social homophily, such as shared publisher, genre and gender. A network of 575 authors was constructed from testimonials in fiction books published between 2020 and 2024 and analyzed using Exponential Random Graph Models (ERGM). The results reveal strong effects of reciprocity, transitivity, and homophily, particularly with respect to publisher and genre. Reciprocity appears to play a key role in testimonial exchanges, suggesting that authors who provide testimonials are significantly more likely to receive testimonials in return. Authors are likely to form connections through shared relationships. However, the network does not exhibit significant inequality in tie distribution, indicating that preferential attachment is not a dominant mechanism. The results strongly confirm that shared attributes, especially publisher and genre, significantly influence testimonial formation, with publisher-based homophily being the most impactful. This reflects the role of publishers in orchestrating testimonial exchanges, as they may actively encourage authors within their networks to provide testimonials for one another. These findings offer insights into the structural dynamics of testimonial networks and provide practical implications for emerging authors seeking to establish connections in the competitive publishing market. The strong evidence for reciprocity underscores the im- portance of actively engaging in the testimonial exchange process. The lack of evidence for preferential attachment is a promising finding for emerging authors, as it suggests they are not disadvantaged by having fewer initial connections.</abstract>
    <parentTitle language="eng">Proceedings of FEB Zagreb 16th International Odyssey Conference on Economics and Business</parentTitle>
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    <author>Jan Domanski</author>
    <author>Jonas Reif</author>
    <author>Lea Schaab</author>
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      <value>Social Network Analysis, Testimonials, Book Market, ERGM</value>
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    <title language="eng">Agile learning: Use of Eduscrum in higher education</title>
    <abstract language="eng">Eduscrum is a methodology that applies agile project management principles to the field of education. The Scrum methodology is an established approach in software development, where iterative product development is carried out by a small development team in work cycles. Originally, Scrum was an agile framework that originated in software development but has since been adapted to various industries,&#13;
including education. The idea behind Eduscrum is to apply agile project management principles to education, aiming to be more flexible in addressing the needs of learners, fostering collaboration, and enabling continuous feedback. Eduscrum organizes the learning process into sprints, which are time-boxed periods typically lasting one to four weeks. During each sprint, students and teachers work collaboratively to achieve specific learning objectives. Scrum defines roles which are sometimes difficult&#13;
to adapt to the educational context. The role of the product owner is often taken on by the teacher, who defines the learning goals and prioritizes the content. The Scrum master moderates the learning process, removes obstacles, and ensures that the Scrum framework is followed effectively. Students take on the role of the development team. Regular meetings, often referred to as "stand-ups" or "Scrum meetings,"are held to discuss progress and challenges. These meetings provide a platform for students and teachers to collaborate, share insights, and identify any impediments. The Scrum process includes artifacts, like a backlog to prioritize tasks and charts which track the progress of the sprints. One of the key principles of Eduscrum is flexibility. It allows for adjustments based on student needs, enabling a dynamic and responsive learning environment. Eduscrum promotes regular feedback loops between students and&#13;
teachers, fostering a culture of continuous improvement. Collaboration is a central theme in Eduscrum. Students work together on projects, share ideas, and contribute to the overall learning experience. The paper describes how the methodology is used in a master’s level class for computer science. Content of the course subject is social network analysis. The students work together in small groups. They perform together a self-chosen project and write a research paper together. Every process step is accompanied by the professor and an assistant, in accordance with Eduscrum. Each project group gets constant feedback. The students are guided step by step through the whole process. In the course evaluation, the students state their high learning outcomes, but they find that the projects are a lot of work.</abstract>
    <parentTitle language="eng">Education and New Developments 2024 – Volume 2</parentTitle>
    <identifier type="doi">10.36315/2024v2end034</identifier>
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    <author>Heidi Schuhbauer</author>
    <author>Patricia Brockmann</author>
    <author>Sebastian Schötteler</author>
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      <value>Agile learning, Eduscrum, higher education, science education, social network analysis</value>
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