Over the last decades the use of technology has drastically increased and its influence on services has been rising constantly (Meuter et al., 2005; Bitner et al., 2010; Rust and Huang, 2014). The digital revolution has paved the way for new predictive service concepts that are linked to the contents of this dissertation. Despite the many studies that have been conducted (e.g., Allmendinger and Lombreglia, 2005; Hubert et al., 2019; Kabadayi et al., 2019; Kashef et al.,2021; Klein et al., 2018; Timeus et al., 2020) and the amount of literature on this subject (e.g., Rehse et al., 2016; Pena-Rios et al., 2018; Paschou et al., 2018), there are still many gaps in the current status of its research. The industry is constantly introducing new phraseology to create unique selling propositions, such as service 4.0 in the automotive sector, which has not yet been scientifically defined. Against this backdrop, the first step of this dissertation was to define the wording “service 4.0” in the automotive context and to compare it with the fairly more common wording of “smart service”. By analysing interviews with knowledgeable respondents, the first out of four research papers describe the characterising components of service 4.0 and demands a unification of the wordings service 4.0 and smart services. Therefore, the further studies and associated papers use the expression 'smart services'. Additionally, the first study gives an overview of what practitioners expect of this kind of service in the automotive context.
However, the development and implementation of new services require knowledge about customers’ needs and expectations to establish the services successfully. This leads to the question, what do customers actually expect of a predictive service in the automotive sector or a car workshop? Research paper II followed these thoughts and analysed interviews and a group discussion with consumers of different ages, genders, levels of education and origins in Germany. Based on the expectations, it introduced five categories of consumers’ and provides an overview of obstacles to the acceptance of smart services. The results of the qualitative studies reveal that many of the obstacles and expectations are concerned with data safety and trust. Furthermore, the results show that perceived transparency seems to influence trust.
While the results of research paper II show the different influencing factors of trust in connection with the acceptance of smart services, research paper III tries to develop a new framework that reflects these relations. To do so, a quantitative study was conducted based on a sample of more than 1,000 consumers’ who answered the questionnaire. Based on the Technology Acceptance Model, the developed framework explains the connection between perceived transparency, privacy risks, perceived security, perceived control and initial trust. Furthermore, the results help to better understand the variance of perceived usefulness by employing the construct of initial trust. Moreover, the construct of perceived firm transparency has a strong influence on initial trust.
The final research paper employed a qualitative research design to describe in detail the obstacles to the acceptance of smart services. It explored two main obstacle categories and one subcategory that describe why customers reject smart services and what their concerns are. Finally, research paper IV used an experiment to explore whether video clips can be used to increase the perceived firm transparency and control. The results of the empirical study show, that video clips seem to increase the perceived firm transparency and control. Therefore, the combined results of research papers III and IV could be a powerful tool for practitioners enabling them to increase initial trust and acceptance of smart services through the use of video clips. This article presents an overview the conducted studies and summarizes the results. Furthermore, it summarizes the underlying theories and builds a theoretical framework.
All in all, this dissertation deepens the understanding of the acceptance of smart services using the example of the automotive sector, and the results should be valuable from a theoretical as well as from a practical point of view.:Summary I
Overview of Research Papers III
Table of Contents IV
Table of Figures VI
Table of Tables VII
Acronyms and Abbreviations VIII
Preface of the Author IX
PART A: Introductory Overview of Dissertation 1
1. Introduction 2
2. Relevance of the Research Topic and Identification of Research Deficits 4
3. Theoretical and Conceptual Background 6
3.1 Future Services 6
3.2 Smart Service Research 9
3.3 Diffusion of Innovations Theory 10
3.4 Theory of Reasoned Action 12
3.5 Technology Acceptance Model 13
3.6 Theoretical Framework and Literature Overview of Initial Trust 20
4. Research Design 23
4.1 Qualitative Sample 23
4.1.1 Data Collection 23
4.1.2 Sample Details 24
4.1.3 Data Validation 26
4.2 Quantitative Sample 26
4.2.1 Data Collection 26
4.2.2 Sample Details 29
4.2.3 Data Validation 31
5 Summary of Research Papers 33
5.1 Summary of Research Paper I 34
5.2 Summary of Research Paper II 36
5.3 Summary of Research Paper III 38
5.4 Summary of Research Paper IV 42
6 Amalgamation of Studies and Results 44
7 Implications for Research and Practice 48
7.1 Theoretical Implications 48
7.2 Recommendations for Further Research 49
7.3 Practical Implications 50
8 Conclusion 52
9 References 54
PART B: Research Papers XI
Research Paper I XII
Research Paper II XXI
Research Paper III XXXIII
Research Paper IV LXI
PART C: Annexes
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:79964 |
| Date | 20 July 2022 |
| Creators | Hädecke, Kenneth |
| Contributors | Zanger, Cornelia, Leischnig, Alexander, Technische Universität Chemnitz, Universität St.Gallen |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English, German |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 10.1007/978-3-658-37344-3, 978-3-658-37343-6, 978-3-658-37344-3, 10.1007/978-3-658-37384-9, 978-3-658-37383-2, 978-3-658-37384-9 |
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