A systematic approached to building a technology delivery system model for an emerging technology: illustrated for ‘Big Data & analytics’

Ying Huang, Ying Guo, Alan L. Porter, Jan Youtie, Douglas Robinson, Donghua Zhu

[Abstract] Addressing important relationships in the process of sociotechnical change associated with compkex technologies becomes a thorny problem for policy-makers both in government and industry. The notion of a technology delivery system (TDS) was employed by the National Academy of Engineering to represent the complex processes by which knowledge in natural and social sciences is deliberately applied to achieve desired outputs of consumer amenities and to address societal problems. Drawing on this definition, TDS can provide analytical value, if it is well-constructed. However, recent trends toward faster and more customized technologies that involve co-creation between provider and consumer have the potential to dramatically change traditional TDS conceptualizations.

Based on a previous research framework, this paper explores empirical insights from different type of documents (e.g., policy reports, funding proposals, scientific articles and patent assignment information) to contribute to an enriched TDS model for the case of Big Data. We present a systematic approach to building a TDS model that includes four phases: (1) Identify macroeconomics and policy environment, including market competition, financial investment, industrial policy, etc.; (2) Figure out key public and private institutions who play an important roles in the delivery of applications deriving from the target technology along the supply chain; (3) Address the core technical complements and their owners, and then trace the intera