Mining the R&amp;D innovation performance processes for high-tech firms based on rough set theory

Wang, Chun-Hsien; Chin, Yang-Chieh; Tzeng, Gwo‐Hshiung

doi:10.1016/j.technovation.2009.11.001

Cited by 38 publications

(25 citation statements)

References 53 publications

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“…This overall lack of clarity about abstractions over time and level makes it very difficult to unambiguously describe the technical changes or inventions that contribute to the progress in a technical field, and thus to understand at an actionable level how to utilize the concept of breakthroughs. It is therefore not surprising that lists such as these have been criticized as potential sources of data due to their subjectively selected nature, lack of repeatability and reliance on a priori assumptions (Yu and Hang, 2010;Wang et al, 2010).…”

Section: Methods Of Measuring Technological Changementioning

confidence: 99%

A Framework for Analyzing the Underlying Inventions That Drive Technical Improvements in a Specific Technological Field

Benson

Magee

2012

EMR

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This paper presents a repeatable method to identify, describe and analyze the important inventions in an industry. The method involves qualitative and quantitative methods of analysis of patents to understand the inventions that have contributed to the growth of an industry. We present a process for mapping the inventions by their importance in an attempt to understand the set of inventions that contribute most significantly to the development of an industry. As a demonstration of the method, a set of 2484 patented inventions in the solar PV industry was selected as a case study. The case study results show that the conceptual basis for the method is useful in understanding technological change in an industry. For example, the analysis identifies important PV patents but none that are discontinuously important. These findings support the probable utility of the framework and have some preliminary broader implications to our understanding of technological development.

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Section: Methods Of Measuring Technological Changementioning

confidence: 99%

A Framework for Analyzing the Underlying Inventions That Drive Technical Improvements in a Specific Technological Field

Benson

Magee

2012

EMR

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“…RST can be used to handle quantitative and qualitative attributes simultaneously without requiring a priori information regarding the probability distribution of the data. Many studies have adopted the RST approach to extract rules and patterns from collected data or unclassified information, such as the evaluation of bankruptcy risk [27], business failure prediction [1], travel demand analysis [7], mining stock prices [31], personal investment portfolios [25], accident prevention [32], and R&D performance [29]. The basic concepts of RST are described in the studies by Pawlak [20][21][22][23][24], Ou Yang et al [14], and Wang et al [29].…”

Section: The Basic Concepts Of Rough Setmentioning

confidence: 99%

Improving airline service quality based on rough set theory and flow graphs

Liou

Chuang

Hsu

2015

Journal of Industrial and Production Engineering

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This study differs from previous studies by applying multivariate statistical analysis and multi-criterion decision-making methods to the improvement of service quality. We use the rough set theory (RST) with a flow graph approach to determine customer attitudes regarding service quality, which can assist managers in developing strategies to improve service quality and thus satisfy the needs of customers. A set of rules is derived from a large sample of airline customers, and its predictive ability is evaluated. The flow graph and the cause-and-effect relationship of the decision rules are heavily exploited in service quality characteristics. As compared with the results of other data-mining analyses, our results are encouraging. This study demonstrates that the combination of the RST model and flow graphs assists in identifying the needs of customers, determining their characteristics, and facilitating the development of an improvement strategy.

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“…Association rules defined for the failure types have opened a new dimension for the research on failure of collaboration [13]. The first study on mining the SME innovation by Wang et Al has found some patterns for allocating the R&D resources [14]. Suh & Kim have detailed the R&D collaboration in service industries detected the positive relations of technology and the product or process innovation [15].…”

Section: Fig 2 Publication Timeline On Association Rulesmentioning

confidence: 99%

Intelligent Association Rules for Innovative SME Collaboration

Kayakutlu

Duzdar

Mercier‐Laurent

et al. 2015

IFIP Advances in Information and Communication Technology

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Part 3: Techniques of Artificial Intelligence Supporting Knowledge ManagementInternational audienceSMEs are encouraged to collaborate for research and innovation in order to survive in tough global competition. Even the technology SMEs with high knowledge capital have the fear to collaborate with other SMEs or bigger companies. This study aims to illuminate the preferences in customer, supplier and competitor collaboration within industry or inter industry. A survey is run on more than 110 companies and Machine Learning methods are used to define the association rules that will lead for success

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Mining the R&D innovation performance processes for high-tech firms based on rough set theory

Cited by 38 publications

References 53 publications

A Framework for Analyzing the Underlying Inventions That Drive Technical Improvements in a Specific Technological Field

A Framework for Analyzing the Underlying Inventions That Drive Technical Improvements in a Specific Technological Field

Improving airline service quality based on rough set theory and flow graphs

Intelligent Association Rules for Innovative SME Collaboration

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