Abstract
The existing approaches to identification of emerging technologies create a prominent opportunity for technology convergence and market growth potential. However, existing approaches either suffer from the time lag issue or have yet to explorethe assessment’s uncertainty and ambiguity. Based on a total of 14 years of mergers and acquisitions (M&A) activity data in the Health Care sector, the complex patterns between growth velocity and accelerating of M&A activities are analyzed with two quantitative indicators (Promising Index and Promising Index Sharpe Ratio) to identify emerging technological opportunities. The proposed integrative approach offers a mean to resolve the time lag issue, deal with market trend irregularity, and manage expectations of investors for emerging technology and industry. Specifically, this study aims to (i) provide a decision support system integrating M&A activity information for strategic investment planning and (ii) identify promising technologies in the Healthcare sector to manage the irregularities of market trend and investment outcome. This study is one of the first research that employs a prior data-based approach to delineate emerging technologies by analyzing the growth momentum properties of specific industry areas based on the M&A activity data.
Highlights
As the global competitive environment continues to change and become more complex, there is a growing awareness of the need to improve long-term sustainability as well as short-term performance with its own technology and information system requirements [1,2]
This study focuses on resolving the time lag issue by proposing a new methodology that recommends emerging technologies and industries based on mergers and acquisitions (M&A) activity information
This study proposes an integration of a Promising Index Sharpe Ratio (PISR) that can be computed as a quick performance measure for each investment policy
Summary
As the global competitive environment continues to change and become more complex, there is a growing awareness of the need to improve long-term sustainability as well as short-term performance with its own technology and information system requirements [1,2]. If firms fail to predict and respond to changing technology trends in a fast-paced industrial environment, they will experience uncertainty related to the technology success and suffer from an inefficient return on investment. They will experience difficulties in securing a sustainable competitive advantage in a highly competitive environment [3]. Existing methodologies effectively help to identify the most recent technological trends and discover hidden patterns in information on authors, inventors, affiliations, recent research, and patents [5] These results often include a time lag issues [13,14,15,16].
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