Apple is a representative company of technological innovation (TI) and management. It has launched new and innovative products since 1977, and many companies and business schools around the world have attempted to learn about the success story of Apple's innovation. However, most previous research works on Apple's innovation have been based on qualitative approaches such as experts' opinions. Such studies offer a subjective point of view. By contrast, in this paper the authors aim to study the TI and forecasting of Apple by analyzing its patent applications, which is an objective approach to examining the innovation of Apple from a technological perspective.
TI is an important issue concerning technology management for companies and governments. To examine Apple's TI, the authors analyze all applied patents and construct analytical models according to three approaches. First, they build statistical models using the time series regression and multiple linear regression methods to create a technology map. Second, they cluster all Apple's patents to find its vacant technology domain. Lastly, they use social network analysis to search for technologies central to Apple's future.
The authors' study shows the technological trends and relations between Apple's technologies. This research finds vacant technology areas and central technologies for Apple's TI.
Using statistical and machine learning methods, the authors analyze all Apple's patents in order to predict the firm's future technologies. This research contributes to examining the TI of Apple. Therefore, the results of the patent analysis can highlight the technological opportunities for Apple's TI.
Traditional TI models have been based on qualitative methods. Previous investigations of Apple's TI have also relied on traditional analytical approaches. In this paper, however, the authors develop a quantitative and objective approach for examining Apple's TI.
