Browsing by Subject "behavioral science"
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Publication11th Consumer Barometer of Renewable Energies(Char for Renewable Energy Management, 2021-11-03)
;Beatrice, Petrovich -
Publication2. Opportunities and challenges of utilizing personality traits for personalization in HCI(De Gruyter Oldenbourg, 2019)
;Völkel, S. T. ;Schödel, R. ;Buschek, D. ;Au, Q. ;Bischl, B. ;Bühner, M.Hussmann, H.This chapter discusses main opportunities and challenges of assessing and utilizing personality traits in personalized interactive systems and services. This unique perspective arises from our long-term collaboration on research projects involving three groups on human-computer interaction (HCI), psychology, and statistics. Currently, personalization in HCI is often based on past user behavior, preferences, and interaction context. We argue that personality traits provide a promising additional source of information for personalization, which goes beyond context- and device-specific behavior and preferences. We first give an overview of the well-established Big Five personality trait model from psychology. We then present previous findings on the influence of personality in HCI associated with the benefits and challenges of personalization. These findings include the preference for interactive systems, filtering of information to increase personal relevance, communication behavior, and the impact on trust and acceptance. Moreover, we present first approaches of personality-based recommender systems. We then identify several opportunities and use cases for personality-aware personalization: (i) personal communication between users, (ii) recommendations upon first use, (iii) persuasive technology, (iv) trust and comfort in autonomous vehicles, and (v) empathic intelligent systems. Furthermore, we highlight main challenges. First, we point out technological challenges of personality computing. To benefit from personality awareness, systems need to automatically assess the user’s personality. To create empathic intelligent agents (e. g., voice assistants), a consistent personality has to be synthesized. Second, personality-aware personalization raises questions about user concerns and views, particularly privacy and data control. Another challenge is acceptance and trust in personality-aware systems due to the sensitivity of the data. Moreover, the importance of an accurate mental model for users’ trust in a system was recently underlined by the right for explanations in the EU’s General Data Protection Regulation. Such considerations seem particularly relevant for systems that assess and utilize personality. Finally, we examine methodological requirements such as the need for large sample sizes and appropriate measurements. We conclude with a summary of opportunities and challenges of personality-aware personalization and discuss future research questions.Type: book section -
PublicationA Biased "Radical" or a False Choice?( 2021-03-16)Type: journal articleJournal: Constructivist FoundationsVolume: 16Issue: 3
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PublicationA CPT-based comparison of retirement products( 2021)
;Chen, AnType: journal articleJournal: SSRN Electronic Journal -
PublicationA Framework of Brand Contestation: Toward Brand AntifragilityType: journal articleJournal: Journal of Consumer ResearchVolume: 48Issue: 4DOI: 10.1093/jcr/ucab053
Scopus© Citations 4 -
PublicationA moderated mediation model linking perceived organizational support to volunteer outcomes( 2020)
;Traeger, Charlotte ;Alfes, KerstinType: conference paper -
PublicationA multilevel examination of the relationship between role overload and employee subjective health: The buffering effect of support climates
Scopus© Citations 13 -
PublicationA qualitative Approach to Understand Frontline Employees’ Acceptance of Robots in Retailing( 2022-06)Type: conference paper
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PublicationA Strategy Framework to Boost Conversational AI PerformanceType: journal articleJournal: Marketing Review St. GallenIssue: 4
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PublicationA Tale of Trauma, Friendship, and Personally Relevant ResearchType: journal articleJournal: learning & education
Scopus© Citations 2 -
PublicationA theory of HR co-creationType: journal articleJournal: Human resource management reviewVolume: 31Issue: 4
Scopus© Citations 16 -
PublicationAccommodation, Interpersonal Justice, and the Turnover Intentions of Employees with Disabilities(Taylor & Francis Group, 2021)
;Samosh, Daniel ;Maerz, Addison ;Spitzmuller, MatthiasType: journal articleJournal: The International Journal of Human Resource Management -
PublicationAffects of diverse encounters and understanding their atmospheric attunements( 2021)Janssens, MaddyType: conference paper
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PublicationAge and gender in language, emoji, and emoticon usage in instant messages.Type: journal articleJournal: Computers in Human Behavior
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PublicationAgile Praktiken im Performance Management - Auswahl und Nutzung moderner SteuerungswerkzeugeType: journal articleJournal: Controlling : Zeitschrift für erfolgsorientierte UnternehmenssteuerungVolume: 33Issue: 4
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PublicationAlgorithmic Management: Its Implications for Information Systems Research(ACM, 2023)
;Cameron, Lindsey ;Lamers, Laura ;Meijerink, JeroenMöhlmann, MareikeIn recent years, the topic of algorithmic management has received increasing attention in information systems (IS) research and beyond. As both emerging platform businesses and established companies rely on artificial intelligence and sophisticated software to automate tasks previously done by managers, important organizational, social, and ethical questions emerge. However, a cross-disciplinary approach to algorithmic management that brings together IS perspectives with other (sub-)disciplines such as macro- and micro-organizational behavior, business ethics, and digital sociology is missing, despite its usefulness for IS research. This article engages in cross-disciplinary agenda setting through an in-depth report of a professional development workshop (PDW) entitled “Algorithmic Management: Toward a Cross-Disciplinary Research Agenda” delivered at the 2021 Academy of Management Annual Meeting. Three leading experts (Mareike Möhlmann, Lindsey Cameron, and Laura Lamers) on the topic provide their insights on the current status of algorithmic management research, how their work contributes to this area, where the field is heading in the future, and what important questions should be answered going forward. These accounts are followed up by insights from the breakout group discussions at the PDW that provided further input. Overall, the experts and workshop participants highlighted that future research should examine both the desirable and undesirable outcomes of algorithmic management and should not shy away from posing ethical and normative questions.Type: journal articleJournal: Communications of the Association for Information Systems (CAIS)Volume: 52 -
PublicationAlienation from work: Marxist ideologies and 21st century practiceType: journal articleJournal: International Journal of Human Resource ManagementVolume: 25Issue: 18
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