Co-Occurrence and Cyclical Growth Law Analysis of User Innovation Knowledge Map Based on Temporal-Weighted Network

The construction of user innovation knowledge map can clearly describe the co-occurrence relationship among innovative knowledge points. Different types of weighted knowledge map models have been applied by enterprises to promote their innovative knowledge development. Moreover, the temporal-weighted user innovation knowledge map can reveal the hidden hot knowledge network model accurately and reflect the general evolution law of the hot topic of innovation knowledge in a certain period. In this paper, we proposed a method based on a knowledge network for constructing the temporal-weighted user innovation knowledge map. In order to model the temporal-weighted co-occurrence relationship among knowledge points, we assigned different weights to the knowledge points at different periods. Then, we carried out centrality analysis and core subgroup analysis for knowledge points through using a time-dynamic analysis method to explore the dynamic laws. Based on that, we proposed the periodical growth rule of user innovation hotspots. It was convenient to predict the hot spots of innovation and grasp the pace of innovation. Besides, we conducted an empirical study of the “Arduino” community, which is the most professional electronic enthusiast community in China. We applied the established model to explore the sensitivity and accuracy of the knowledge map after adding the temporal factor to the user innovation knowledge map, and we found out the evolution process of co-occurrence relationship between user innovation knowledge points. Finally, we concluded that it takes time to ultimately establish a core-edge innovation knowledge model to represent specific innovation fields. More importantly, the development of hotspots of innovative knowledge presented the general growth cycle of the four stages: the initial stage, the explosive development stage, the mature stage, and the recession stage. Discovery of this law has a major impact on the company’s trending of the future “frontier research” field and the entry choice of innovation.

[1]  Yan Gao.  A Study on the Knowledge Mapping of Organizational Change Based on Keyword Co-Occurrence , 2018 .

[2]  D. Doloreux,et al.  Knowledge-Intensive Business Services (KIBS) Use and User Innovation: High-Order Services, Geographic Hierarchies and Internet Use in Quebec's Manufacturing Sector , 2015 .

[3]  Suihuai Yu,et al.  A user requirement driven framework for collaborative design knowledge management , 2017, Adv. Eng. Informatics.

[4]  Marylène Gagné.  A model of knowledge‐sharing motivation , 2009 .

[5]  Juho Salminen,et al.  Facilitating user driven innovation trough a Living Lab , 2010, 2010 IEEE International Technology Management Conference (ICE).

[6]  Lars Frederiksen,et al.  The Core and Cosmopolitans: A Relational View of Innovation in User Communities , 2012, Organ. Sci..

[7]  Cornelius Herstatt,et al.  The Dynamics Of User Innovation: Drivers And Impediments Of Innovation Activities , 2008 .

[8]  Yong Tan,et al.  Social Networks and the Diffusion of User-Generated Content: Evidence from YouTube , 2012, Inf. Syst. Res..

[9]  Simon Rodan,et al.  Knowledge Networks, Collaboration Networks, and Exploratory Innovation , 2014 .

[10]  D. Baglieri,et al.  Collaborative innovation in tourism: managing virtual communities , 2009 .

[11]  Yu-Wen Huang,et al.  Mapping knowledge structure by keyword co-occurrence and social network analysis: Evidence from Library Hi Tech between 2006 and 2017 , 2018, Libr. Hi Tech.

[12]  Frank W. Geels,et al.  The dynamics of sustainable innovation journeys , 2008, Technol. Anal. Strateg. Manag..

[13]  Jina Kang,et al.  HOW DO FIRMS SOURCE EXTERNAL KNOWLEDGE FOR INNOVATION? ANALYSING EFFECTS OF DIFFERENT KNOWLEDGE SOURCING METHODS , 2009 .

[14]  Yoshiteru Nakamori,et al.  Connecting informal networks to management of tacit knowledge , 2010 .

[15]  Jeroen P.J. de Jong,et al.  Innovation lessons from 3-D printing , 2013 .

[16]  Eric von Hippel,et al.  Foreword: Progress in research on user innovation , 2015 .

[17]  W. Dolfsma,et al.  Social networks for innovation and new product development , 2016 .

[18]  Y.-Y. Liu,et al.  The fundamental advantages of temporal networks , 2016, Science.

[19]  R. Hartmann,et al.  Policies to promote user innovation: Makerspaces and clinician innovation in Swedish hospitals , 2018 .

[20]  E. Hippel,et al.  Users as Service Innovators: The Case of Banking Services , 2011 .

[21]  Kristof Coussement,et al.  Multi-label classification of member participation in online innovation communities , 2018, Eur. J. Oper. Res..

[22]  Jeonghwan Jeon,et al.  Monitoring patterns of open innovation using the patent-based brokerage analysis , 2019, Technological Forecasting and Social Change.

[23]  J. West,et al.  Managing Distributed Innovation: Strategic Utilization of Open and User Innovation , 2012 .

[24]  Samer Faraj,et al.  Network Exchange Patterns in Online Communities , 2011, Organ. Sci..

[25]  A. Petruzzelli,et al.  Mapping innovation dynamics in the Internet of Things domain: Evidence from patent analysis , 2017, Technological Forecasting and Social Change.

[26]  Qi Luo.  User-Oriented Service Design and Innovation , 2011, 2011 International Conference of Information Technology, Computer Engineering and Management Sciences.

[27]  John Darlington,et al.  Co-creation and user innovation , 2015 .

[28]  L. Freeman.  Centrality in social networks conceptual clarification , 1978 .

[29]  Junfeng Yang,et al.  Strategies for Smooth and Effective Cross-Cultural Online Collaborative Learning , 2014, J. Educ. Technol. Soc..

[30]  L. Reisch,et al.  Sustainable user innovation from a policy perspective: a systematic literature review , 2016 .

[31]  Pei-Chun Lee,et al.  Mapping knowledge structure by keyword co-occurrence: a first look at journal papers in Technology Foresight , 2010, Scientometrics.

[32]  Martin Meyer,et al.  Innovation intermediaries and collaboration: Knowledge–based practices and internal value creation , 2018 .

[33]  Carliss Y. Baldwin,et al.  Modeling a Paradigm Shift: From Producer Innovation to User and Open Collaborative Innovation , 2010, Organ. Sci..