過去之大多文獻資料指出，技術的發展會對經濟成長造成影響，一項新的技術被採用，可能成為某種新興的商品或服務，進而影響總體經濟的發展。過去的研究大多將重點放在技術發展與其對經濟影響的線性關係中，然而技術和經濟之間，不應該是單純的線性關係，而是存在策略、政策、知識、法規等適應與選擇性的中介效果作用其中，使技術複雜性能夠透過這些中介效果，更有效的對經濟複雜性產生影響。因此本文首先探討在技術發展的不同年代中，技術複雜性、經濟複雜性、適應與選擇性之間的關聯性，並探討影響技術複雜性作用在經濟複雜性的中介效果是否存在，以及其關係是否會因為年代不同而有所差異，並希望可以透過回顧過去技術發展歷史，去驗證本研究的假說是否成立。本研究跳脫以往認為技術發展和經濟之間為線性關係的認知，關注兩者之間的中介效果，並量化研究方法為基礎，由經濟複雜性及中介效果，推演出技術發展及擴散的框架，後續透過質性的個案研究法，透過分析中介效果顯著的30年間的技術發展歷史，找出技術發展的過程中，影響不同技術發展的中介效果具體的存在事實，驗證量化研究下推演出的框架存在，並發現技術發展過程背後，一些相同及相異的軌跡。

Literature has widely recognized the significant impact of technological development on economic growth. However, previous studies are mainly focused on the linear relationship between technological development and its impact on economies. This paper argued the relationship between the technology and economy should not treated as a simple linear relationship. Instead, it involves mediating effects such as strategies, policies, knowledge, regulations, and other mediating factors. These mediating factors enable the technological complexity and indirectly exerted moderate effect (strengthen or weaken) on the economy complexity. Therefore, this study aims to explore the relationship between and amongst technological complexity and economic complexity, and examine how the adaption and selection of mediating factors influenced their relationships across five decades from 1970s to 2010s. This study provides significant managerial and policy implications and advance our understanding for the interaction between technological and economic development. This study deviates from the traditional linear relationship between technological advancements and economic growth, and instead emphasizes the mediating effects that exist between the two. Utilizing a quantified research method that considers economic complexity and these mediating factors, a framework for technology development and diffusion is established. Through qualitative case studies that analyze the history of technology development over a 30-year period, the specific mediating effects that influence various technology developments are identified. The derived framework is then validated, revealing both common and unique trajectories behind the process of technology development.

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