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Improving customer satisfaction in proactive service design

Author

Listed:
  • Annette Wenninger

    (University of Bayreuth)

  • Daniel Rau

    (University of Augsburg)

  • Maximilian Röglinger

    (University of Bayreuth)

Abstract

As an emergent variant of digital and smart services, proactive services (PAS) do not wait for customers to make the first move, but proactively participate in customers’ lives and make decisions on their behalf. Due to their novelty, the literature on PAS is in its infancy. Specifically, there is a lack of guidance on designing PAS to meet customer needs. Hence, we examined how customers assess specific features of PAS and whether their assessments differ according to personality traits. To this end, we conducted an online survey via the crowdsourcing platform Prolific, which yielded 259 valid responses. We used a methodological combination of the Kano model, self-stated importance method, and the Five Factor model. Our results reveal that, at the moment, customers do not value features of PAS related to autonomy and that customers engage in paradoxical behavior when assessing the use of personal data. These results allow for a more precise classification and prioritization of the features of PAS tuned to a customer’s most prevalent personality trait.

Suggested Citation

  • Annette Wenninger & Daniel Rau & Maximilian Röglinger, 2022. "Improving customer satisfaction in proactive service design," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1399-1418, September.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:3:d:10.1007_s12525-022-00565-9
    DOI: 10.1007/s12525-022-00565-9
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    Cited by:

    1. Osadci-Baciu Ana-Maria & Zbuchea Alexandra, 2023. "Beyond the Manuscript: Unraveling Author-Publisher Dynamics," Culture. Society. Economy. Politics, Sciendo, vol. 3(2), pages 62-80, December.
    2. Rainer Alt, 2022. "Electronic Markets on platform culture," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1019-1031, September.
    3. Pascal Fechner & Fabian König & Jannik Lockl & Maximilian Röglinger, 2024. "How Artificial Intelligence Challenges Tailorable Technology Design," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(3), pages 357-376, June.
    4. Goutier, Marc & Diebel, Christopher & Adam, Martin & Benlian, Alexander, 2024. "Proactive and Reactive Help from Intelligent Agents in Identity-Relevant Tasks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 142985, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

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    More about this item

    Keywords

    Customer satisfaction; Kano model; Proactive services; Personality traits; Service design;
    All these keywords.

    JEL classification:

    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General
    • L80 - Industrial Organization - - Industry Studies: Services - - - General
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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