Technology trajectory mapping using data envelopment analysis: the ex ante use of disruptive innovation theory on flat panel technologies

Abstract

In this paper, we propose a technology trajectory mapping approach using data envelopment analysis (DEA) that can scrutinize technology progress patterns from multidimensional perspectives. Literature reviews on technology trajectory mappings have revealed that it is imperative to identify key performance measures that can represent different value propositions and then apply them to the investigation of technology systems in order to capture indications of the future disruption. The proposed approach provides a flexibility not only to take multiple characteristics of technology systems into account, but also to deal with various trade-offs among technology attributes by imposing weight restrictions in the DEA model. The application of this approach to the flat panel technologies is provided to give a strategic insight for the players involved.

It takes two to tango: technological and non-technological factors of Industry 4.0 implementation in manufacturing firms

“…This absorptive capacity resides in prior knowledge or memories of organizations and becomes accumulated through organizational life. Such knowledge helps firms to adapt their behaviour to changes along existing technological trajectories (i.e., in case of incremental innovations), but may fall short to optimum in the case of radical technological changes which require shifts in the organization’s overall behaviours and developments or those which necessitate the acquisition of new sets of knowledge and skills unrelated to previous ones (Ritala and Hurmelinna-Laukkanen 2013 ; Lim and Anderson 2016 ).…”

“…Contributions within technology acceptance literature argue that the decision of organizations to interact with specific technology and their ability to benefit from the use of these systems is dependent on perceived usefulness and ease of use (Lim and Anderson 2016 ). We argue that this perception will be diminished in situations where organizations come in contact with novel technologies unrelated to their accumulated technological knowledge.…”

Assessment of Regulatory Requirements on Technological Changes: The Increasing Dominance of Downsized Turbo/Super-Charged Engines Over Naturally Aspirated Engines

“…The local RoC (δ T j ) is the weighted average of changes observed in the adjacent technology frontiers; in (5), the numerator indicates the weighted sum of the relevant changes observed from outperformed technologies that have set DMU j as a benchmark, while the denominator indicates the accumulated contribution of DMU j to the expansion of the corresponding frontier facet. See more discussions on the computational details in [21], [22], [33] and relevant recent applications in [19], [23], [32], [34]. occurred with a facelift, hence the dataset included total 1,206 engines with 4, 6, or 8 cylinders after filtering out vehicles equipped with duplicated engines.…”

Model-based approaches for technology planning and roadmapping: Technology forecasting and game-theoretic modeling

“…This approach was validated successfully in application to performance prediction for microprocessors (Anderson et al, 2002), computer display projectors (Iamratanakul et al, 2005), jet fighter aircrafts (Inman et al, 2006), wireless networks (Anderson et al, 2008), passenger airplanes technologies (Lamb et al, 2010) and electric vehicles (Jahromi et al, 2013). In Lim and Anderson (2016) the evolution paths of the flat panels technologies were built, and results discussed through the lens of Disruptive Innovation Theory. DEA models assume of convex production sets.…”