Relationship between technological improvement and innovation diffusion: an empirical test

Woo, JongRoul; Magee, Christopher L.

doi:10.1080/09537325.2021.1901875

Cited by 7 publications

(8 citation statements)

References 51 publications

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“…The first telematics systems were launched in the early 1990s and are now standard components on most new vehicles sold. It is hard not to notice that electrification technologies improve slowly and have slower adoption rates while automated/ autonomous and connectivity-related technologies are improving faster and also have higher adoption rates, This relationship between improvement rates and adoption supports the conclusion byWoo and Magee (2018) suggesting that technologies improving at a faster rate have a faster adoption rate especially during their infancy.CHAPTER 5: CONCLUSIONSThis work reviews past work on technological forecasting and decision making and builds on new research to introduce a systematic approach to technological decision-making. We describe the development of a new web-based technology search tool and apply the methodology to a case study of the automotive industry.…”

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confidence: 61%

“…Identifying a technology "just" when it's about to take-off in the S-curve model of diffusion and investing significantly in product development, marketing/ sales at that time, can allow a firm to gain market share quickly and establish a "dominant design" (Benson & Magee, 2018). In addition, there is evidence that faster improving technologies are also adopted at a faster rate during their infancy (Woo & Magee, 2018). This can allow for more accurate estimates of expected sales during the infancy of a technology and can provide a guide for creating realistic technology development and sales roadmaps.…”

Section: Figure 1 Technology Improvement and Diffusionmentioning

confidence: 99%

“…Prior research has demonstrated that there is a high correlation between a technology's improvement rates and its adoption, especially during its infancy-from 0-10% adoption and from 10-30% adoption (Woo & Magee, 2018). This is also the period of greatest uncertainly.…”

Section: Predicting Cross-over Points and Creating Realistic Technology Development And Sales Roadmapsmentioning

confidence: 99%

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Technological Improvement Rate Estimates for All Technologies: Use of Patent Data and an Extended Domain Description

2020

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Complex and highly interdependent socio-technical systems are necessary for sustaining, governing, entertaining and nourishing human society. Such systems fulfill their objectives by incorporating everimproving technologies. A systematic understanding of technology and the pace of technical change is thus critical for policymakers and stakeholders to make well-informed decisions and avoid costly mistakes and omissions. This work reviews past work on technological forecasting and decision making and builds on new research to introduce a systematic approach to technological decision-making. This document describes why information about technology improvement rates matters to technological decision-making, the theoretical framework for doing so, a repeatable methodology and an online system making available this capability to stakeholders. Despite and somewhat because of the complexity of the "whole" socio-technical system, the regularity of constant annual performance improvement is a very strong empirical fact with substantial theoretical underpinning. This regularity lies at the heart of integrating objective data into overall decision processes concerning items affected by the timing of technological change. The methodology uses a broad, easy to use, database of the rates of technological change that covers almost all technologies. We do this by using prior work (accomplished as part of the effort that enabled this thesis) establishing a correspondence of 97.14% of all patents within the entire US patent system to a set of 1757 technology domains and estimating their rates of improvements.We describe the development of a new web-based technology search tool and apply the methodology to a case study of the automotive industry. We believe these results herald a new era of data-driven technological decision-making. Using this new framework and the tool, stakeholders can make timely and "good enough" technology forecasts available without requiring extensive modelling initiatives.

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confidence: 61%

Section: Figure 1 Technology Improvement and Diffusionmentioning

confidence: 99%

Section: Predicting Cross-over Points and Creating Realistic Technology Development And Sales Roadmapsmentioning

confidence: 99%

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Technological Improvement Rate Estimates for All Technologies: Use of Patent Data and an Extended Domain Description

2020

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“…Despite the positive increase, there is a reduction in both the log gross margin and farm productivity of the very high-level users. This was expected since the effect of innovation on competitiveness at the latter stage is tempered by saturation effects hence the decrease (Woo & Magee, 2017) in the competitive level of the agrienterprises.…”

Section: Mean Potential Outcome Across the Treatment Effectsmentioning

confidence: 99%

Effects of Production and Market Innovations on the Level of Competitiveness of Sorghum Small Scale Agrienterprises

Judith¹,

Gathungu²,

Ayuya³

et al. 2021

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Agricultural innovations are keys to economic growth, income stability as well as nutritional enhancement particularly in marginal areas since they are well-adapted to poor or unpredictable agro-ecological conditions. Innovation is a critical player that is seen to bring competitiveness, increase productivity and efficiency to agrienterprises. Despite that, there is limited empirical evidence on whether the uptake of the innovations has on sorghum competitiveness in small scale farm level agriprenuers in most ASALs of Eastern Kenya. This study examines the effect of production and market innovation on the competitiveness of sorghum agriprenuers, using primary data collected in 2019 from a total of 384 randomly selected small scale agrienterprises. A multivalued treatment effect model was applied to determine the role of innovation on the competitiveness of sorghum enterprises. Farm productivity and gross margin analysis were used to measure the competitiveness of the agrientreprises. The results indicated that gross margin and farm productivity of sorghum agrienterprises increase with an increase in the number of innovations used. These innovations include the uses of improved sorghum seeds, conservation agriculture, and group marketing. But also, there was a decrease in both gross margin and productivity for the agrienterprises with the highest number of innovations in the farm at saturation level. The results implied that the kind and the number of innovations employed in agrienterprises development are critical in its profitability and productivity. Therefore, interventions targeting usage of innovations in sorghum agrienterprises should be sensitized to integrate different innovations on product, process, and market in enhancing competitiveness.

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“…Foster [26] posited the theory of S-curves and suggested that technologies evolve along successive S-curves. The latter has become the canonical representations of the technology's life cycle [37,64]. Traditional researches mainly focus on one performance dimension (e.g., high or low) to consider the smooth substitution between two technologies [32,55].…”

Section: Literature On Technology Diffusion and Adoptionmentioning

confidence: 99%

Adoption time of a maturing disruptive technology in a duopoly market

Sun

Lin

2021

RAIRO-Oper. Res.

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New disruptive technologies invalidate the traditional competition dimension in continuous innovation and reconstruct the competitive landscape. These technologies leave a management gap in the adoption of new technologies by competing companies. Accordingly, this research establishes a duopoly game model based on horizontal and vertical differentiations for technology competition problems with asymmetric features. Competition between firms and technologies are investigated simultaneously. We find that a profit increase from new technologies is typically eliminated by the increased technology competition. Thus, firms with competitive advantages in the old market may be late in adopting new technologies, and the competition will further delay the adoption process. We then introduce a preemption strategy for adopting disruptive technologies, and test it in both current established competition and threat competition from the entrants. Results show that leading companies may hesitate in deterring new entrants for fear of losing the leadership in the current competition. At last, we provide a time strategy that can help the market leader maintain a leadership position with minimal losses. Our research has contributed to the studies of both the interpretation of the “innovator's dilemma” and the direction of technology adoption research under multi-dimensional technologies and multiple competitors.

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Relationship between technological improvement and innovation diffusion: an empirical test

Cited by 7 publications

References 51 publications

Technological Improvement Rate Estimates for All Technologies: Use of Patent Data and an Extended Domain Description

Technological Improvement Rate Estimates for All Technologies: Use of Patent Data and an Extended Domain Description

Effects of Production and Market Innovations on the Level of Competitiveness of Sorghum Small Scale Agrienterprises

Adoption time of a maturing disruptive technology in a duopoly market

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