See Paper at: ISPRS Int. J. Geo-Inf. 2019, 8(1), 34; https://doi.org/10.3390/ijgi8010034
The topic of technology development and its disruptive effects has been the subject of much debate over the last 20 years with numerous theories at both macro and micro scales offering potential models of technology progression and disruption. I have personally been involved in looking at technology progression (so called horizon scanning) in order to help government agencies decide how to react to the potential challenges and benefits of technology driven disruption. The process at present is typically very manual and involves interviews with industry experts, academics and commentators in the relevant field. In particular it involves pouring over reports, manual internet searches and the generation of best guesses.
A topic of great interest to me is how theories of technology progression may be integrated and whether suitable indicators of this progression and any subsequent disruptive effects might be derived based on the use of big data analytic techniques. Given the magnitude of the economic, social, and political implications of many disruptive technologies, the ability to quantify disruptive change at the earliest possible stage could deliver major returns by reducing uncertainty, assisting public policy intervention, and managing the technology transition through disruption into deployment. However, determining when this stage has been reached is problematic because small random effects in the timing, direction of development, the availability of essential supportive technologies or “platform” technologies, market response or government policy can all result in failure of a technology, its form of adoption or optimality of implementation.
I am undertaking research into this topic at Nottingham University, and if you are interested you can take a look at my first paper, published in the January 2019 Edition of the ISPRS International Journal of Geo Information (see link below). It reviews the various theories and approaches applied to technology progression in particularly those of Arthur and Chrissensen but also looks at work from many other researchers in the field. Lastly it describes a proof of concept experiment to harvest information from the internet and analyse it in terms of identifying technology progression. The diagram shows the experimental framework used to perform an historic analysis of technology progression particularly around the smartphone platform and applications which build on it. Can we track both the underlying technology spread geographically and the resulting disruption (for the latter I chose to look at Uber)?
This sort of geographic spread of technology and the subsequent disruptive effect is particularly relevant to the concept of platform development. We are seeing more and more platforms of all sorts (app stores, crowd funding platforms, social media platforms) which are having a significant magnifying effect on modern life and commerce. The figure shows the progression of Uber over the last ten years, derived from historical sources on the internet which, together with apps like AirBnB is causing significant disruption to ways of working in the relevant industry. The geographic aspect of this is also significant, and the almost viral nature of disruption spread is obvious from the analysis.
If you are interested in this topic, you can download the concept paper here:
ISPRS Int. J. Geo-Inf. 2019, 8(1), 34; https://doi.org/10.3390/ijgi8010034
Please comment if you have any opinion on the issues covered. I’m really interested in feedback.