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HMD Praxis der Wirtschaftsinformatik

, Volume 56, Issue 1, pp 252–267 | Cite as

Ich fühle mit dir! Können empathische virtuelle Assistenten den stationären Einzelhandel unterstützen?

  • Michael MeyerEmail author
  • Timo Strohmann
Schwerpunkt
  • 72 Downloads

Zusammenfassung

In Rahmen dieses Beitrags sollen moderne Informationssysteme wie virtuelle Assistenten auf deren Unterstützungspotentiale im stationären Einzelhandel hin untersucht werden. Dabei wird ein besonderes Augenmerk auf die Kooperationsfähigkeit dieser Systeme gelegt. Eine gute Kooperation zwischen Informationssystem und Händler soll insbesondere durch eine systemseitige emotionale Intelligenz beziehungsweise eine gute Empathie erreicht werden. Dazu werden moderne Ansätze betrachtet, welche das Ziel verfolgen, Emotionen von Informationssystemen messbar und interpretierbar zu machen. Im Zuge dieser Forschungsbemühungen wurden Experteninterviews im stationären Einzelhandel der Stadt Braunschweig durchgeführt, um den Bedarf sowie die Anforderungen an einen empathischen Virtuellen Assistenten abzufragen.

Schlüsselwörter

Digitale Transformation Stationären Einzelhandel Virtuelle Assistenz Emotionen Support-Service 

I Feel for You! Can Empathic Virtual Assistants Support the Stationary Retail?

Abstract

In the context of this contribution, modern information systems such as virtual assistants are to be examined for their support potential in local retail. Special attention is paid to the ability of these systems to cooperate. Good cooperation between the information system and retailers should be achieved in particular through good system-side emotional intelligence or good empathy. For this purpose, current approaches are considered, which aim to make emotions of information systems measurable and interpretable. In the course of these research efforts, expert interviews were conducted in the local retail sector of the city of Braunschweig to determine the needs and requirements for an empathic virtual assistant.

Keywords

Digital tranformation Retail Virtual assistance Emotions Support service 

Literatur

  1. Amit R, Zott C (2001) Value creation in E‑business. Strateg Manage J 22:493–520.  https://doi.org/10.1002/smj.187 CrossRefGoogle Scholar
  2. Bachmann A, Klebsattel C, Schankin A et al (2015) Leveraging smartwatches for unobtrusive mobile ambulatory mood assessment. In: Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers—UbiComp ’15. ACM Press, Osaka, S 1057–1062Google Scholar
  3. Blazquez M (2014) Fashion shopping in multichannel retail: The role of technology in enhancing the customer experience. Int J Electron Commer 18:97–116.  https://doi.org/10.2753/JEC1086-4415180404 CrossRefGoogle Scholar
  4. Brave S, Nass C (2003) Emotion in human-computer interaction. In: Jacko JA, Sears A (Hrsg) The human-computer interaction handbook. Lawrence Erlbaum, Hillsdale, S 81–96Google Scholar
  5. Cabanac M (2002) What is emotion? Behav Processes 60:69–83.  https://doi.org/10.1016/S0376-6357(02)00078-5 CrossRefGoogle Scholar
  6. Faullant R (2007) Psychologische Determinanten der Kundenzufriedenheit: Der Einfluss von Emotionen und Persönlichkeit, 1. Aufl. Dt. Univ.-Verl, WiesbadenGoogle Scholar
  7. Fulcher J (2008) Computational intelligence: An introduction. In: Computational intelligence: A compendium. Springer, Berlin, Heidelberg, S 3–78CrossRefGoogle Scholar
  8. Fulgoni GM (2015) The rise of the digital omnivore: What it means for advertisers, publishers, and app developers. J Advert Res 55:115–119.  https://doi.org/10.2501/JAR-55-2-115-119 CrossRefGoogle Scholar
  9. Guzman AL (2017) Making AI safe for humans: A conversation with Siri. In: Gehl RW, Bakardjieva M (Hrsg) Socialbots and their friends: Digital media and the automation of sociality. Routledge, New York, S 69–85Google Scholar
  10. Hagberg J, Sundstrom M, Egels-Zandén N (2016) The digitalization of retailing: An exploratory framework. Int J Retail Distrib Manage 44:694–712.  https://doi.org/10.1108/IJRDM-09-2015-0140 CrossRefGoogle Scholar
  11. Härtfelder J, Winkelmann A (2016) Opportunities and challenges for local retailing in an environment dominated by mobile Internet devices—literature review and gap analysis. In: Conference Paper: MKWI 2016 – 11. Konferenz Mobilität & Digitalisierung (MMS 2016). ISBN 978-3863601324Google Scholar
  12. Hussain SS, Peter C, Bieber G (2009) Emotion Recognition on the Go: Providing Personalized Services Based on Emotional States. 6Google Scholar
  13. Lakens D (2013) Using a Smartphone to measure heart rate changes during relived happiness and anger. IEEE Trans Affect Comput 4:238–241.  https://doi.org/10.1109/T-AFFC.2013.3 CrossRefGoogle Scholar
  14. Mayer JD, Geher G (1996) Emotional intelligence and the identification of emotion. Intelligence 22:89–113.  https://doi.org/10.1016/S0160-2896(96)90011-2 CrossRefGoogle Scholar
  15. Meschtscherjakov A, Reitberger W, Lankes M, Tscheligi M (2008) Enhanced shopping: A dynamic map in a retail store. In: Proceedings of the 10th international conference on Ubiquitous computing—UbiComp ’08. ACM Press, Seoul, S 336Google Scholar
  16. Morana S, Friemel C, Gnewuch U et al (2017) Interaktion mit smarten Systemen – Aktueller Stand und zukünftige Entwicklungen im Bereich der Nutzerassistenz. Wirtschaftsinform Manag 9:42–51.  https://doi.org/10.1007/s35764-017-0101-7 CrossRefGoogle Scholar
  17. Peter C, Beale R (2008) Affect and emotion in human-computer interaction: From theory to applications, 1. Aufl. Springer, Heidelberg, Berlin, New YorkCrossRefGoogle Scholar
  18. Peter C, Urban B (2012) Emotion in human-computer interaction. In: Dill J, Earnshaw R, Kasik D et al (Hrsg) Expanding the frontiers of visual Analytics and visualization. Springer, London, S 239–262CrossRefGoogle Scholar
  19. Picard RW, Klein J (2002) Computers that recognise and respond to user emotion: Theoretical and practical implications. Interact Comput 14:141–169.  https://doi.org/10.1016/S0953-5438(01)00055-8 CrossRefGoogle Scholar
  20. Reeves B, Nass C (1996) The media equation: How people treat computers, television, and new media like real people and places. The Center for the Study of Language and Information Publications, StanfordGoogle Scholar
  21. Rohm A, Sultan F (2006) An exploratory cross-market study of mobile marketing acceptance. Int J Mob Mark 1:4–12Google Scholar
  22. Rothermund K, Eder A (2011) Allgemeine Psychologie: Motivation und Emotion. VS, WiesbadenCrossRefGoogle Scholar
  23. Russell JA (1980) A circumplex model of affect. J Pers Soc Psychol 39:1161–1178.  https://doi.org/10.1037/h0077714 CrossRefGoogle Scholar
  24. Seeber I, Bittner E, Briggs RO et al (2018) Machines as teammates: A collaboration research agenda. In: Proceedings of the 51st Hawaii International Conference on System Sciences. Waikoloa, HI, USAGoogle Scholar
  25. Siemon D, Becker F, Eckardt L, Robra-Bissantz S (2017) One for all and all for one—towards a framework for collaboration support systems. Educ Inf Technol.  https://doi.org/10.1007/s10639-017-9651-9 Google Scholar
  26. Spaid BI, Flint DJ (2014) The meaning of shopping experiences augmented by mobile Internet devices. J Mark Theory Pract 22:73–90.  https://doi.org/10.2753/MTP1069-6679220105 CrossRefGoogle Scholar
  27. Yurur O, Liu CH, Sheng Z et al (2016) Context-awareness for mobile sensing: A survey and future directions. Ieee Commun Surv Tutorials 18:68–93.  https://doi.org/10.1109/COMST.2014.2381246 CrossRefGoogle Scholar

Copyright information

© Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature 2018

Authors and Affiliations

  1. 1.Lehrstuhl Informationsmanagement, Institut für WirtschaftsinformatikTechnische Universität BraunschweigBraunschweigDeutschland

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