In summary, this chapter provided a detailed description of the dissertation’s research methodology. Quantitative and qualitative case study methodology was employed to illustrate the phenomenon of how businesses deal with the digitalization of processes with respect to overhead costs, the limitations of the current approaches and what the success factors in managing overhead costs successfully are. The sample of participants consisted of 20 purposefully selected individuals. Four data collection methods were employed, namely surveys (quantitative and qualitative), individual interviews (qualitative), critical incidents (qualitative), and focus group (qualitative). The data were challenged with literature, other databases and the emerging findings. Credibility and dependability were addressed by carefully selected strategies, in particular triangulation of sources and methods.
Different qualitative and quantitative methods were used in the dissertation. Table 6 contains the data-sources for the quantitative research, Table 9 gives an overview of the qualitative methods.
Table 9: Overview of qualitative methods for needed information
Research question Information needed Method
1. How does the digitalization of processes impact the management of overhead costs?
Participant’s perceptions of the
2. What are the limitations of the current approaches of the management of overhead costs in respect to methods and tools? If there are limitations, what can be done to overcome them?
3. In general, what are the prerequisites for the successful management of overhead costs?
Table 9 explains – beginning with the research question – what type of information is needed; followed by the chosen method to obtain it. The findings are presented in the next chapter. They are consistent with the above mentioned research methods. A review of the literature was conducted to craft the theoretical foundation for the design and analysis of the dissertation. The analysis enabled the development of the themes consistent with the research questions and the hypotheses. Through a comparison with the literature, interpretations of the findings, and drawing conclusions, the dissertation resulted in recommendations offered for academic institutions, businesses, and further research. The intent was that the dissertation contributes to the understanding for the academic and business community, both current and future, with regards to managing overhead costs. Additionally, it is hoped that the dissertation will be of value to those educators who are responsible for training prospective business leaders and scholars.
CHAPTER 4
PRESENTATION OF FINDINGS
4 Presentation of findings
The following section displays the metadata of the survey. It explains the demographic matrix of the participants, the structure of the enterprises concerning revenue, number of employees, R&D spending, and percentage of service. Later, in Chapter 5, these findings are put in context according to benchmarks outside this study. The numbers provided by self-disclosure were double-checked (and confirmed) by cross-referencing with public information.
Table 10: Demographic matrix of the participants
# Participant
Table 10 shows 20 different participants from seven distinct industries. There are seven females (35% of the sample) and 13 male participants (65% of the sample) between the ages 27 to 54 years old. Joachim (pseudonym, participant code OHM946U) is with 27 years by far the youngest. Nevertheless, when participating in the research he had already 12 years of experience in the automotive parts industry (started as apprentice and worked his way up to cost engineering department manager, attending a master program at university as a part-time student). Another impressive track-record has the oldest participant: Diane (pseudonym, participant code OHM544P) is 54 years old and works in the automotive parts industry as well (skill area manager for the powertrain of battery electrical vehicles). Diane has the second most experience in the field with 22 years; Csaba (pseudonym, participant code OHM444Y) has the most experience with 23 years. One participant, Ute (participant code OHM743V), has only nine years of experience in her field, precisely 9.4 years at the time of the interview. It would apparently contradict the selection criteria of the research sample as defined in Chapter 3.4.
Nevertheless, because of her background in chemical engineering in the beverage industry with assignments in the Netherlands, South Africa, and the United States of America she qualifies for the survey; it brings a useful inter-cultural perspective into the study. At the completion of the dissertation, she was still in her position and therefore had reached the once self-imposed criteria for the length of experience with 10 years. The set-up of the educational background is displayed in the following tree-map:
Figure 15: Educational background of the participants Source: Own research
Figure 15 shows in a tree-map the structure of the various educational backgrounds of the participants stating the highest obtained educational degree or industry training, respectively. Master of Science (with eight individuals) is held by the most participants. The Master’s degrees were earned in the field of business administration, chemical engineering, electrical engineering, industrial engineering, and mechanical engineering. Five participants hold a PhD in various fields, which encompass agile factory layout management, logistics-controlling in supplier relationship management, strategic influencing factors on merger and acquisition transactions, thermal behavior of aeronautic parts in outer space, and total quality management in the service sector. Four Diplomingenieure (Dipl.-Ing.) are part of the panel as well, their background is electrical engineering, industrial engineering, and mechanical engineering. Two Engineers (Ing.) obtained their degree in the higher technical school system in Austria for mechanical engineering. One participant, a technician (OHM467Z) has no formal higher education yet brings in an extensive level of experience in cost management in the aviation industry. Eight of the participants give lectures at local universities; hence understand the academic demands for scientific work.
Applying another tree map, the set-up of the various industries in the study are demonstrated by the following figure. It displays a weakness of the dissertation as the number of different industries is limited.
Figure 16: Represented industries in the dissertation Source: Own research
Figure 16 displays in a tree map of the representation of the seven various industries in the dissertation. Automotive (parts) has the highest number of participants with five, followed by automotive (OEM), beverage, and transportation, logistics with three participants each.
Aviation, chemicals, and steel each have two representatives in the study. In total, they add up to the 20 different enterprises. The structure of the industries becomes important when the results of the multi-case study is compared to larger, multi-national databases.