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110 With their far-reaching strategic implications transcending IT and business, CNAs can be therefore understood as adjacent to other recent technology trends employing distributive systems, such as artificial intelligence, IoT, or blockchain (Kratzke, 2018). All in all, the research and the resulting model emphasizes the need for an integration of business and IT strategy to exploit the full potential of novel technologies and remain competitive in a digital era.
6.2. Research Quality
To assess the quality of the research, the applied methods of the research will be evaluated through the concepts of reliability, validity, and generalizability.
Predominantly two procedures have been utilized in the research to ensure the reliability of the research. Firstly, full documentation of the collected data is provided in Appendix 3, thus increasing research transparency. Secondly, explicit qualitative analysis via verbatim quotes provides the possibility to establish a “decision-trail”, i.e. evidence that the conclusions made are well-founded based on data (Noble & Smith, 2015). Combined, these procedures increase the likelihood that independent research would arrive at a similar or comparable conclusion with the same data, which ultimately constitutes reliable research (Noble & Smith, 2015; Saunders et al., 2016).
Regarding the validity of the research, the central evaluation criteria are to firstly determine the appropriateness of the applied methods, and secondly the accuracy to which the findings reflect the data (Golafshani, 2003). Firstly, semi-structured interviews proved an adequate method to obtain detail-rich descriptions of the informant’s experiences with CNAs. The research does not perceive it likely that other qualitative means of the query, e.g. questionnaires, would yield the same in-depth understanding of the CNAs. Secondly, the applied iterative processes between theory and data in abductive reasoning, lead to abductive validation (Danermark et al. 2002; Saunders et al, 2016).
The proposed Cloud-Native Strategy Model thus reflects the most accurate description of the strategic implications of CNAs based on theory and data.
The abductive validation is in alignment with the outlined critical realist research philosophy focussing on identifying causality between a phenomenon and its context (Egholm, 2014; Fletcher, 2017). The unveiling of causal relations between the cases and their use of CNAs extends into the question of generalizability from case studies, i.e. how transferable the findings are to other contexts
111 (Noble & Smith, 2015). In a critical realist case study, the aim is not to justify the conclusions to other hypothetical settings. Instead, the critical realist research philosophy perceives case studies as an approach to “provide useful information regarding how the postulated mechanism [CNAs]
operate under a set of contingent conditions [the contexts of Zalando or Adidas] [..].” (Tsang, 2014, p. 180). Therefore, the suggested Cloud-Native Strategy Model may be used by others in its present form to explain the strategic implications of CNAs, or with modifications serve as a basis for further analysis of CNAs in different settings. This depends on the individual assessment of the transferability of the conceptual model (Tsang, 2014).
6.3. Limitations of the Research
Nevertheless, the research comes with limitations. Firstly, cloud-native and CNAs present a relatively novel research domain. Consequently, there exist only few academic definitions related to CNAs to date. The concept employed by the research at hand relies heavily on the results from Kratzke & Quint (2017), who establish a broad definition of CNAs. Thus, it must be noted that while the research focused on this high-level definition of CNAs, more detailed results could have been elaborated by focusing only on the strategic implications of the individual elements of CNAs, such as microservices or container orchestration. Further, the lack of prior research led to the application of research findings originally concerned with cloud computing infrastructure to CNAs to provide a theoretical starting point for the research at hand.
Secondly, the incorporation of data triangulation using quantitative data to compare results would have increased the validity of the research as it reduces measurement error. However, due to the novelty and the lack of comparative numerical measures to date, the application of quantitative research methods to investigate the strategic implications from CNAs remains difficult.
Finally, the sample size of the research constituted a limitation. Although the samples include interviewees with managerial responsibility related to cloud-native initiatives, the overall validity of the findings would be strengthened by a greater interviewee sample size. Yet, the outbreak of the Coronavirus in Europe affected the data collection process, as scheduled interviews had to be postponed indefinitely. Even with persistence, it was not possible to reschedule all interviews to a time that would allow for enough time to process the data before the submission of the research.
112 6.4. Future Research
Despite the limitations of the research presented above, the findings of this thesis provide valuable insights for further research in connection with the strategic implications, impact, and business value of CNAs. Whereas the previous literature in this research domain predominantly took a technological perspective on the implementation of CNAs, this research contributes to the domain by suggesting a multi-faceted model for the implications and impacts of CNAs on the overall business strategy. Thus, it serves as a starting point for further investigation of the topic.
In particular, the limitations of this thesis at hand present concrete subjects that are worth to be addressed by future research. This includes the validation of the proposed model within a more diverse set of case companies and industries. While the maturity of CNAs and its integration in practice will evolve, future research will benefit from more practical experience in this context and subsequently, better access to data.
Moreover, the establishment of a quantitative model to measure the implications and impact of CNAs on the business seems to present an interesting research array. While this seems challenging due to the lack of comparable numerical benchmarks to date, the authors expect the application of quantitative methods to be facilitated in the future due to the growing body of experience and data around CNA implementation.
Additionally, the model of this thesis could be further refined by detailing the strategic implications of specific characteristics of CNAs. Thereby, a more fine-grained understanding of the casualties between the constituents of CNAs and the respective implications could be established, thus enabling more differentiated managerial decisions.
Further, an important leap for the understanding of CNA’s strategic business value presents the establishment of a better understanding of its impact on the overall business performance. Thereby, business and IT stakeholders could be provided with a better understanding of the value mechanisms resulting from CNAs.
Lastly, while this study mainly found beneficial implications of CNAs, future research could address the drawbacks more in-depth. Consequently, firms aiming for a digital transformation with CNAs could gain a more detailed picture of the involved risks to their business strategy.
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