Now showing 1 - 10 of 45
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Stolpersteine auf dem Weg zum Kunden

, Herhausen, Dennis , Schögel, Marcus

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Believe the Hype? Herausforderungen und Herangehensweisen an das „Metaverse"

2022-11-04 , Schögel, Marcus , Grellmann, Laura-Eve , Lienhard, Severin Dominic , Herhausen, Dennis

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Capturing Value in the Internet of Things

2020-01 , Wortmann, Felix , Herhausen, Dennis , Bilgeri, Dominik , Weinberger, Markus , Fleisch, Elgar

The Internet of Things (loT) promises to deliver enormous business value. More specifically, loT solutions disrupt existing business models by opening up novel service opportunities. In order to help companies understand the opportunities and challenges of this development, we shed light on different loT revenue models. Based on an inductive case study approach, we identify nine direct and indirect revenue patterns. The different types of revenue patterns all use loT-enabled services to create value for customers; the extent and the monetization of services, however, vary.

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The interplay between employee and firm customer orientation: Substitution effect and the contingency role of performance-related rewards

2018-07-04 , Herhausen, Dennis , De Luca, Luigi , Weibel, Michael

This paper identifies and explains a potential tension between a firm’s emphasis on customer orientation (CO) and the extent to which employees value CO as a success factor for individual performance. Based on self-determination theory and CO implementation research, we propose that firm CO may represent both autonomous and controlled motivations for CO, but that employees’ CO is more strongly linked to individual performance when employees experience solely autonomous motivation. Hence, we expect a substitution effect whereby the link between employees’ CO and their performance is weaker when firm CO is high. Furthermore, we examine a boundary condition for the previous hypothesis and propose that performance-contingent rewards have a positive effect on the internalization of the extrinsic motivation stemming from firm CO. Two multilevel studies with 979 employees and 201 top management team members from 132 firms support our hypotheses. Against previous research, our findings offer a new perspective on the effectiveness of CO initiatives, propose employees’ motivational states as the theoretical explanation for the heterogeneity in the link between employee CO and performance, and reappraise the role of performance-contingent rewards in CO research. We provide managerial implications for the effective implementation of customer-oriented initiatives within firms.

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Generative AI Tools in Customer Service - Beyond the Hype of "Prompt Engineering"

2023-06 , Thedda Deecke , Dr. Sina Wulfmeyer , Marcus Schögel , Marcus Schögel , Dennis Herhausen

The adoption of artificial assistant tools (AAT) powered by generative artificial intelligence and large language models to support frontline employees (FLEs) opens up promising new use cases while also introducing changing skillset requirements and new challenges (e.g., in compliance and data security). In this paper, the authors explore AAT implementation in a customer contact center, drawing conclusions from a qualitative study of practical use cases, necessary FLE skills and data security requirements and solutions. Recommendations are provided for implementing AATs using the GPT-3.5 Turbo API.

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Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods

2022 , van Giffen, Benjamin , Herhausen, Dennis , Fahse, Tobias

Over the last decade, the importance of machine learning increased dramatically in business and marketing. However, when machine learning is used for decision-making, bias rooted in unrepresentative datasets, inadequate models, weak algorithm designs, or human stereotypes can lead to low performance and unfair decisions, resulting in financial, social, and reputational losses. This paper offers a systematic, interdisciplinary literature review of machine learning biases as well as methods to avoid and mitigate these biases. We identified eight distinct machine learning biases, summarized these biases in the cross-industry standard process for data mining to account for all phases of machine learning projects, and outline twenty-four mitigation methods. We further contextualize these biases in a real-world case study and illustrate adequate mitigation strategies. These insights synthesize the literature on machine learning biases in a concise manner and point to the importance of human judgment for machine learning algorithms.

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One size doesn't fit all: How construal fit determines the effectiveness of organizational brand communication

2019 , Herhausen, Dennis , Henkel, Sven , Kipfelsberger, Petra

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Start with why: The transfer of work meaningfulness from leaders to followers and the role of dyadic tenure

2022-06-22 , Kipfelsberger, Petra , Raes, Anneloes , Herhausen, Dennis , Kark, Ronit , Bruch, Heike

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Perspektiven für Face-Recognition im Data-Driven-Marketing

2020 , Reinhold, Michael , Herhausen, Dennis , Pahl, Maximilian Niklas , Wulf, Jochen

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The Impact of Customer Contact on Collective Human Energy in Firms

2019-07-02 , Kipfelsberger, Petra , Bruch, Heike , Herhausen, Dennis

This paper investigates how and when a firm’s level of customer contact influences the collective organizational energy. For this purpose, we bridge the literature on collective human energy at work with the job impact framework and organizational sensemaking processes and argue that a firm’s level of customer contact is positively linked to the collective organizational energy because a high level of customer contact might make the experience of prosocial impact across the firm more likely. However, as prior research at the individual level has indicated that customers could also deplete employees’ energy, we introduce transformational leadership climate as a novel contingency factor for this linkage at the organizational level. We propose that a medium to high transformational leadership climate is necessary to derive positive meaning from customer contact, while firms with a low transformational leadership climate do not get energized by customer contact. We tested the proposed moderated mediation model with multilevel modeling and a multi-source dataset comprising 9,094 employees and 75 key informants in 75 firms. The results support our hypotheses and offer important theoretical contributions for research on collective human energy in organizations and its interplay with customers.