Disentangling the automotive technology structure: a patent co-citation analysis

Abstract

While most technological positioning studies were traditionally addressed by comparing firms technological patents classes and portfolios, only a few of them adopted science mapping patent co-citation techniques and none of these seeks to understand the impact of collective cognition on the technology structure of an entire industry. What is the firms technological positioning landscape within an high collective cognition sector? What is the groups technological positioning evolution? How do technology structures shift according to different economic scenarios? Through a strategic lens we contribute to technology strategy literatures by proposing an invention behavior map of automotive actors at a firm, groups and industry level. From Derwent Innovation Index, about 581,000 patents, 1,309,356 citations and 1,287,594 co-citations relationships between (a) the main 49 firms assignees of 1991–2013 and (b) the main 28 or 34 groups assignees by considering three timespan 1991–1997, 1998–2004, 2005–2013, were collected. Results: (1) most of the companies are located close together, depicting the sector technology structure as highly dense; (2) the market leaders do not coincide with technology production leaders and not necessarily occupy central technological positions; (3) the automotive groups considerably varies in the three timespan in terms of position and composition; (4) the market leaders groups occupy technological remoteness positions during economic growth timespan; (5) the sector technology structure is highly dense during growth, strongly scattered and lacking of technologically center positioned actors after economic decline. Finally, strategic implications supporting central locating or suburb R&D positioning planning and M&As recombinational partners decision making are discussed

Measuring Innovation Quality: A Patent Analysis

“…[38] observed that the communications industry has the highest inventions' generality of applicability in a broad range of technology fields, further making this industry interesting for a more in-depth analysis. [24] suggest that the patent analysis is not useful in all sectors, but it is more applicable to the telecommunications, information technology, pharmaceuticals, biotechnology, chemicals, and automotive [33]. Hence, a patent analysis is particularly suitable for this industry.…”

“…More specifically, innovation scholars have shown a great interest in analyzing patent citation data [7], [8], [9], [33], and [34]. Patent citation analysis is a bibliometric technique that links patents in the same way that the science citations link the papers' references [33], [35], [36], and [37].…”

“…More specifically, innovation scholars have shown a great interest in analyzing patent citation data [7], [8], [9], [33], and [34]. Patent citation analysis is a bibliometric technique that links patents in the same way that the science citations link the papers' references [33], [35], [36], and [37]. Patent citations have been primarily used in three lines of research: as a measure of patent quality [1], [2], [3], [4], [5], [6], [7], [8], [18], [38], as a measure of knowledge flows and spillovers [39], [40], [41], and as a tool for the examination of technology structure [33], [42].…”

Big Data and Technology Evolution in the IoT Industry

“…The technology conceptual structure emerges by linking different concepts (Small, 1999). These links allow us to disentangle the connections not only between items but also between groups, signaling the centrality of items within and between clusters (Noyons, Moed, & Van Raan, 1999;Castriotta & Di Guardo 2016).…”