TY - JOUR
T1 - An approach to identify emergent topics of technological convergence
T2 - A case study for 3D printing
AU - Wang, Zhinan
AU - Porter, Alan L.
AU - Wang, Xuefeng
AU - Carley, Stephen
N1 - Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2019/9
Y1 - 2019/9
N2 - Technological Convergence (TC) reflects developmental processes that overlap different technological fields. It holds promise to yield outcomes that exceed the sum of its subparts. Measuring emergence for a TC environment can inform innovation management. This paper suggests a novel approach to identify Emergent Topics (ETopics) of the TC environment within a target technology domain using patent information. A non-TC environment is constructed as a comparison group. First, TC is operationalized as a co-classification of a given patent into multiple 4-digit IPC codes (≥2-IPC). We take a set of patents and parse those into three sub-datasets based on the number of IPC codes assigned 1-IPC (Non-TC), 2-IPC and ≥3-IPC. Second, a method is applied to identify emergent terms (ETs) and calculate emergence score for each term in each sub-dataset. Finally, we cluster those ETs using Principal Components Analysis (PCA) to generate a factor map with ETopics. A convergent domain – 3D printing – is selected to present the illustrative results. Results affirm that for 3D printing, emergent topics in TC patents are distinctly different from those in non-TC patents. The number of ETs in the TC environment is increasing annually.
AB - Technological Convergence (TC) reflects developmental processes that overlap different technological fields. It holds promise to yield outcomes that exceed the sum of its subparts. Measuring emergence for a TC environment can inform innovation management. This paper suggests a novel approach to identify Emergent Topics (ETopics) of the TC environment within a target technology domain using patent information. A non-TC environment is constructed as a comparison group. First, TC is operationalized as a co-classification of a given patent into multiple 4-digit IPC codes (≥2-IPC). We take a set of patents and parse those into three sub-datasets based on the number of IPC codes assigned 1-IPC (Non-TC), 2-IPC and ≥3-IPC. Second, a method is applied to identify emergent terms (ETs) and calculate emergence score for each term in each sub-dataset. Finally, we cluster those ETs using Principal Components Analysis (PCA) to generate a factor map with ETopics. A convergent domain – 3D printing – is selected to present the illustrative results. Results affirm that for 3D printing, emergent topics in TC patents are distinctly different from those in non-TC patents. The number of ETs in the TC environment is increasing annually.
KW - 3D printing
KW - Emergent Terms (ETs)
KW - Emergent Topics (ETopics)
KW - International Patent Classification (IPC)
KW - Technological Convergence (TC)
UR - http://www.scopus.com/inward/record.url?scp=85059200792&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2018.12.015
DO - 10.1016/j.techfore.2018.12.015
M3 - Article
AN - SCOPUS:85059200792
SN - 0040-1625
VL - 146
SP - 723
EP - 732
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
ER -