Corporate foresight for the semiconductor downstream in the Post-Moore Era combining scenario analysis and TPP model: A TSMC case study

• Main Authors: Paul Lawrence Osmond, 歐保羅
• Other Authors: Chih-Hung Hsieh
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/y38a8g

碩士 === 元智大學 === 經營管理碩士班(國際企業學程) === 107 === With the area scaling of CMOS semiconductors reaching its physical limits, the entire electronics industry is facing the inevitable end of Moore’s Law. TSMC is currently one of just three semiconductor manufacturers, along with Intel and Samsung, that continue to push the physical limits at the leading edge of semiconductor technology development. At present, it is expected that TSMC will develop 1 nanometer technology around the year 2027, but beyond this time, there is great uncertainty as to the future development of semiconductor technologies and, in turn, the development of the electronic devices and emerging technologies which rely on semiconductors. Artificial intelligence (AI), the Internet of things (IoT), blockchain including cryptocurrency mining, and automotive electronics in autonomous vehicles have been identified as possible growth drivers for the semiconductor industry over the next decade. Given the technology uncertainty associated with the end of Moore’s Law and uncertainty surrounding market demand, the commercial success of these emerging technologies is uncertain. The current case study utilizes scenario analysis to develop four plausible scenarios based on the key uncertainties facing TSMC in the year 2030. These key uncertainties include; 1) the presence, or lack thereof, of a manufacturing breakthrough in semiconductor manufacturing, and 2) the strength of the market for semiconductor products. Given the resulting four scenarios, a Technology Portfolio Planning (TPP) Delphi survey was administered for each scenario in which internal and external experts to TSMC assessed the importance and risk of the identified emerging technologies in the year 2030. The findings of the study are four-fold. The first finding: Scenario 1 (Digital Utopia) which combines a strong technology market with a technological breakthrough in semiconductor manufacturing has the most Premier Approach technologies and is the best-case scenario for TSMC. On the contrary, scenario 4 (Digital Desert) lacks a semiconductor breakthrough and envisions a weak downstream market and is the worst-case scenario for TSMC. The second finding: Artificial narrow intelligence (ANI), artificial general intelligence (AGI), collaborative-aware Internet of things (IoT), and public blockchain are reliant on a technology breakthrough to achieve their full market potential. Identity-related IoT and Ubiquitous IoT including smart city applications rely on a strong market for widespread adoption. Information-aggregation IoT and automotive electronics are both technology-driven and market-driven and will require a technology breakthrough and a strong market to achieve their greatest potential. The third finding: Automotive electronics have the highest average importance across the four scenarios and ANI provides the lowest level of risk among the emerging technologies analyzed. The fourth finding: A modified TPP model which integrates equilibrium lines in the original TPP model can describe investment group projects in a more detailed manner and is better at identifying managerial implications between various strategic investment opportunities. Finally, based on the results of the analysis, TSMC and other players in the ICT industry can be better prepared to deal with uncertain, but plausible future scenarios in the Post-Moore Era.