Artikel
A contextualized acceptance model for proactive smart services
Thanks to digital technologies, information about customer needs and contexts is becoming accessible ever more easily and service providers are more closely connected to customers. This development enables services to act on behalf of customers and to proactively initiate the customer interactions. Such services are so-called proactive smart services (PASS) and are a subgroup of smart services. Research suggests that service providers often face the challenge to gain customers' acceptance of innovative services. In response to this call for action and the change in customer interaction, which can have far-reaching consequences in the lives of customers, we examined the antecedents that explain customers' acceptance of PASS using a contextualized approach. Hence, we identified PASS-specific antecedents, developed a contextualized acceptance model (UTAUT2-PASS) while drawing from general acceptance theory, and validated it empirically. A comparison of our contextualized model with UTAUT2 as an established yet uncontextualized model confirmed the outperformance of our contextualized model. Our findings advance the academic understanding of PASS and help service providers design PASS for customer acceptance.
- Language
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Englisch
- Bibliographic citation
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Journal: Schmalenbach Journal of Business Research (SBUR) ; ISSN: 2366-6153 ; Volume: 74 ; Year: 2022 ; Issue: 3 ; Pages: 345-387
- Classification
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Management
- Subject
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Contextualization
Factor Analysis
Proactive Smart Services
Technology Acceptance
- Event
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Geistige Schöpfung
- (who)
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Graf-Drasch, Valerie
Röglinger, Maximilian
Wenninger, Annette
Hosseini, Sabiölla
- Event
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Veröffentlichung
- (who)
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Springer
- (where)
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Heidelberg
- (when)
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2022
- DOI
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doi:10.1007/s41471-022-00139-7
- Handle
- Last update
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10.03.2025, 11:42 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Graf-Drasch, Valerie
- Röglinger, Maximilian
- Wenninger, Annette
- Hosseini, Sabiölla
- Springer
Time of origin
- 2022
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