Next Article in Journal
Model to Measure the Readiness of University Testing Laboratories to Fulfill ISO/IEC 17025 Requirements (A Case Study)
Next Article in Special Issue
Operational Decision Model with Carbon Cap Allocation and Carbon Trading Price
Previous Article in Journal
Servitization: A Model for the Transformation of Products into Services through a Utility-Driven Approach
Article Menu

Export Article

Open AccessArticle
J. Open Innov. Technol. Mark. Complex. 2019, 5(1), 1; https://doi.org/10.3390/joitmc5010001

Patterns of Learning in Dynamic Technological System Lifecycles—What Automotive Managers Can Learn from the Aerospace Industry?

Economics of Innovation, University of Hohenheim, 70599 Stuttgart, Germany
*
Author to whom correspondence should be addressed.
Received: 26 October 2018 / Revised: 15 December 2018 / Accepted: 21 December 2018 / Published: 28 December 2018
(This article belongs to the Special Issue Technology Driven Innovation, Research Management and Policy Making)
  |  
PDF [1589 KB, uploaded 28 December 2018]
  |     |  

Abstract

Not only with respect to the common overlaps within the market of urban air mobility, but also in terms of their requirement profile with regard to the systemic core, all mobility industries are converging. This article focuses on the required patterns of learning in order to cope with these changes, and what automotive managers can learn from the aerospace industry in this context. As organizational learning is the central parameter of economic evolution, and technology develops over trajectory shifts, companies are, at the very least, cyclically forced to learn ambidextrously, or are squeezed out of the market. They have to act and react as complex adaptive systems in their changing environment. Especially in these dynamics, ambidextrous learning is identified to be a conditio sine qua non for organizational success. Especially the combination of efficiency-oriented internal exploitation with an explorative and external-oriented open innovation network turns out to be a superior strategy. By combining patent data, patent citation analysis and data on the European Framework Programs, we show that there are temporal differences, i.e., position of the product in the product, technique, technology, and industry life cycle. Furthermore, we draw a conclusion dependent on the systemic product character, which enforces different learning requirements concerning supply chain position and, as an overarching conclusion, we identify product structure to be decisive for how organizational learning should be styled. View Full-Text
Keywords: ambidexterity; technological learning; open innovation; complex product systems; technological evolution; industry evolution; knowledge evolution; industry convergence; automotive; aerospace ambidexterity; technological learning; open innovation; complex product systems; technological evolution; industry evolution; knowledge evolution; industry convergence; automotive; aerospace
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Guffarth, D.; Knappe, M. Patterns of Learning in Dynamic Technological System Lifecycles—What Automotive Managers Can Learn from the Aerospace Industry? J. Open Innov. Technol. Mark. Complex. 2019, 5, 1.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
J. Open Innov. Technol. Mark. Complex. EISSN 2199-8531 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top