The Research on Innovation Diffusion: An Assessment

Today innovation can be so radical and futuristic that common models of innovation diffusion might not be enough. The success of an innovation relies on the functional features of the new product, but also on how consumers shape the meaning of that innovation. Consumer Culture Theory (CCT) can help managers by focusing on the cultural determinants of consumer behaviour. The work provides a preliminary analysis of how consumers elaborate the cultural platform that will determine the degree of success of the upcoming innovation Google Glass.

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Reverse Innovation in Emerging Market -Innovation Diffusion Model and A Case Study of China-

Korean-Chinese Social Science Studies ◽

10.36527/kcsss.18.1.7 ◽

2020 ◽

Vol 18 (1) ◽

pp. 171-198

Author(s):

Yongkyun Chung

Keyword(s):

Innovation Diffusion ◽

Diffusion Model ◽

Emerging Market ◽

Reverse Innovation

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'Classic' Representations about Innovation Diffusion

SSRN Electronic Journal ◽

10.2139/ssrn.3481092 ◽

2019 ◽

Author(s):

Lazat Spankulova

Keyword(s):

Innovation Diffusion

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Promoting Electric Vehicle Cell Innovation Diffusion Considering Patent Licensing Strategy: A Combination of Evolutionary Game and Optimization Algorithm Approach

World Electric Vehicle Journal ◽

10.3390/wevj12030095 ◽

2021 ◽

Vol 12 (3) ◽

pp. 95

Author(s):

Weiwei Sun ◽

Zheng Zhang

Keyword(s):

Electric Vehicle ◽

Innovation Diffusion ◽

Diffusion Model ◽

Optimization Algorithm ◽

Evolutionary Game ◽

Patent Holder ◽

Patent Licensing ◽

Object Function ◽

Patent License ◽

Fierce Competition

Electric vehicle cell industry is an emerging area with fierce competition on technical innovation, in which the patent holder can choose different innovation diffusion options to maximize the return; however, the strategy is unclear in certain scenarios. We tried to explain the question of how to maximize the patent holder’s return by appropriate patent license strategy to promote EV cell innovation diffusion, when competition and patent licensing relationship exist in the supply chain. A multistage and multichannel diffusion model of EV cell comprising the patent holder, EV cell producer and EV producers is developed; the evolutionary game is analyzed considering the competition among same stage players and patent licensing relationship among different stage players; and an optimization algorithm is introduced to find the maximum weighted object function of the patent holder. We established the multistage and multichannel diffusion model and found a nonlinear complex relationship between patent holder object function and the key factors including patent royalty pricing and innovation advantage coefficient; in addition, an optimization algorithm is developed based on adopters’ decision-making related with competition and patent licensing.

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Macro Patterns and Trends of U.S. Consumer Technological Innovation Diffusion Rates

Systems ◽

10.3390/systems9010016 ◽

2021 ◽

Vol 9 (1) ◽

pp. 16

Author(s):

Albert Joseph Parvin ◽

Mario G. Beruvides

Keyword(s):

Innovation Diffusion ◽

Technological Innovation ◽

Research Effort ◽

Decision Makers ◽

Macro Level ◽

Technological Innovations ◽

Exploratory Data ◽

Diffusion Rates ◽

Technological Innovation Diffusion ◽

Aid Decision

Macro-level trends and patterns are commonly used in business, science, finance, and engineering to provide insights and estimates to assist decision-makers. In this research effort, macro-level trends and patterns were explored on the diffusion rates of technological innovations, a component of a sorely under-studied question in technology assessment: When should a technological innovation be abandoned? A quantitative exploratory data analysis (EDA)-based approach was employed to examine diffusion market data of 42 U.S. consumer technological innovations from the early 1900s to the 2010s to extract general macro-level knowledge on technological innovation diffusion rates. A goal of this effort is to grow diffusion rate knowledge to enable the development of general macro-based forecasting tools. Such tools would aid decision-makers in making informed and proactive decisions on when to abandon a technological innovation. This research offers several significant contributions to the macro-level understanding of the boundaries and likelihood of achieving a range of technological innovation diffusion rates. These contributions include the determination that the frequency of diffusion rates are positively skewed when ordered from slowest to fastest, and the identification and ranking of probability density functions that best represent the rates of technological innovation diffusion.

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Tracking innovation diffusion: AI analysis of large-scale patent data towards an agenda for further research

Technological Forecasting and Social Change ◽

10.1016/j.techfore.2020.120524 ◽

2021 ◽

Vol 165 ◽

pp. 120524

Author(s):

Ashkan Fredström ◽

Joakim Wincent ◽

David Sjödin ◽

Pejvak Oghazi ◽

Vinit Parida

Keyword(s):

Innovation Diffusion ◽

Large Scale ◽

Patent Data

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The drivers of innovation diffusion in agriculture: evidence from Italian census data

Journal on Chain and Network Science ◽

10.3920/jcns2014.x009 ◽

2014 ◽

Vol 14 (3) ◽

pp. 231-245 ◽

Cited By ~ 7

Author(s):

G. Avolio ◽

E. Blasi ◽

C. Cicatiello ◽

S. Franco

Keyword(s):

Innovation Diffusion ◽

Diffusion Of Innovations ◽

Agricultural Sector ◽

Census Data ◽

Structural Features ◽

Three Dimensions ◽

Local Expenditure ◽

Diffusion Dynamics ◽

Italian Provinces ◽

Market Opportunities

Innovation is a key issue in the discussion about the links between agriculture, food production and sustainability. Indeed, the creation, adoption and exploitation of innovations can interact with all three dimensions of sustainability – environment, society and economy. Despite the increasing support for innovation practices in the agrifood sector from institutions and public policies, innovation in this sector has spread quite slowly. Indeed, the diffusion of innovations strongly depends on the social, institutional and productive system behind the technological/structural features of the farms. The analysis of the drivers underpinning the innovation diffusion dynamics in agriculture is therefore a very interesting topic for studies in this domain. This paper aims to provide a map of the diffusion of innovations in the Italian agricultural sector, highlighting differences and territorial specificities. We try to explain the drivers and factors influencing such specificities, drawing from data on the agricultural sector as well as information on the institutional and regulatory framework. Data on the diffusion of product, process, organizational and marketing innovations in agriculture have been gathered for the 110 Italian provinces, drawing from the 2010 Agricultural Census survey. Maps of the diffusion of the different types of innovations have then been constructed and analysed. Results show that the diffusion of the different innovation types is not uniform within the country. Some are typical to specific areas where productive or market opportunities occur. Others are not territorial-specific but are linked to the features of the single farms. The influence of the regulatory context also seems to play a significant role. By analysing the local expenditure in rural development intervention, we analyses how the synergies among the productive and institutional systems may act as a driver for innovation diffusion in agriculture.

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