Data Envelopment Analysis of Financial Strategy Efficiency in the Global Semiconductor Industry (2015-2024)
Ollonqvist, Joonas (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025120533088
https://urn.fi/URN:NBN:fi:amk-2025120533088
Tiivistelmä
This master’s thesis is a scientific research study, conducted without a commissioner, that examines how leading semiconductor companies convert strategic investments into operating performance. The objective is to explain cross-company differences in efficiency in the global semiconductor industry using the Resource-Based View (RBV) and its extensions as the theoretical framework.
A quantitative, non-experimental and longitudinal research design is applied, using panel data of company-year observations from fiscal years 2015–2024 and audited annual reports as secondary data. Operating efficiency is benchmarked with an output-oriented, variable-returns-to-scale Data Envelopment Analysis (DEA), complemented with descriptive and inferential statistical checks. Connections to working life are ensured by focusing on capital allocation and strategic positioning decisions in a capital-intensive, innovation-driven industry.
The analysis reveals a right-skewed efficiency distribution and a concentrated frontier in which a small subset of companies repeatedly acts as peers for others. Scale efficiency patterns indicate where performance gaps reflect scale misfit rather than process or capability weaknesses. Descriptive associations between DEA efficiency scores and profitability indicators suggest that more efficient companies tend to achieve stronger financial outcomes within the sample. The results provide a systematic, theory-informed benchmark for comparing resource utilization and efficiency trajectories across semiconductor value chain roles.
Managerial implications highlight how companies can identify scale versus process gaps, learn from best-performing peers and strengthen investment governance. Sustained efficiency leadership emerges as dependent on continuous resource orchestration and alignment within semiconductor ecosystems. The study outlines theoretical contributions and avenues for further research.
A quantitative, non-experimental and longitudinal research design is applied, using panel data of company-year observations from fiscal years 2015–2024 and audited annual reports as secondary data. Operating efficiency is benchmarked with an output-oriented, variable-returns-to-scale Data Envelopment Analysis (DEA), complemented with descriptive and inferential statistical checks. Connections to working life are ensured by focusing on capital allocation and strategic positioning decisions in a capital-intensive, innovation-driven industry.
The analysis reveals a right-skewed efficiency distribution and a concentrated frontier in which a small subset of companies repeatedly acts as peers for others. Scale efficiency patterns indicate where performance gaps reflect scale misfit rather than process or capability weaknesses. Descriptive associations between DEA efficiency scores and profitability indicators suggest that more efficient companies tend to achieve stronger financial outcomes within the sample. The results provide a systematic, theory-informed benchmark for comparing resource utilization and efficiency trajectories across semiconductor value chain roles.
Managerial implications highlight how companies can identify scale versus process gaps, learn from best-performing peers and strengthen investment governance. Sustained efficiency leadership emerges as dependent on continuous resource orchestration and alignment within semiconductor ecosystems. The study outlines theoretical contributions and avenues for further research.