A systematic approach to prioritizing R&amp;D projects based on customer-perceived value using opinion mining

Yoon, Boram; Jeong, Yujin; Lee, Keeeun; Lee, Sungjoo

doi:10.1016/j.technovation.2020.102164

Cited by 20 publications

(9 citation statements)

References 66 publications

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“…The existing research on product perceived quality is remarkable and many efficient methods such as evaluation, quantification, and defect identification have been proposed, but they tend to focus only on the macro-level (e.g. Yoon et al ., 2020; Golara et al ., 2021) or only on the micro-level (e.g. Liu et al ., 2018; Zheng et al ., 2021).…”

Section: Discussionmentioning

confidence: 99%

“…As Web 2.0 applications evolve, social media begins to support communication interactions between consumers (Chong et al ., 2018a, b). Perceived quality embedded in social media data influences consumers' satisfaction (Yoon et al ., 2020). Because the data spread fast and widely, perceived quality can influence sales by positively or negatively affecting the attitudes of potential customers (Singh et al ., 2021; Wang et al ., 2021) and manufacturer performance (Golara et al ., 2021).…”

Section: Related Workmentioning

confidence: 99%

“…However, existing research on perceived quality using social media data has been conducted either at the macro-level (e.g. Yoon et al ., 2020; Golara et al ., 2021) or at the micro-level (e.g. Liu et al ., 2018; Zheng et al ., 2021), with few studies conducting a combination of macro–micro analysis.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic perceived quality analysis using social media data at macro- and micro-levels

Yang

Dang

2023

IMDS

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PurposeThis paper aims to propose a method for dynamic product perceived quality analysis using social media data and to achieve a macro–micro combination analysis. The method enables the prioritization of perceived quality attributes and provides perception causes.Design/methodology/approachTo rationalize the macro–micro combination, ANOVA and multiple linear regression were used to identify the main factors affecting perceived quality which served as the combination basis; by using the combination basis for consumer segmentation, macro-knowledge (i.e. attribute importance and quality category of the attribute) is achieved by term frequency-inverse document frequency (TF-IDF)-based attribute importance calculation and KANO-based attribute classification, which is combined with micro-quality diagnostic information (i.e. perceived quality, perception causes and quality parameters). Further, dynamic perception Importance-Performance Analysis (IPA) is built to present the attribute priority and perception causes.FindingsThe framework was validated by the new energy vehicle (NEV) data of Autohome. The results show that price and purchase purpose are the most influential factors of perceived quality and that dynamic perception IPA can effectively prioritize attributes and mine perception causes.Originality/valueThis is one of the first studies to analyze dynamic perceived quality using social media data, which contributes to the research on perceived quality. The paper also contributes by achieving a combined macro–micro analysis of perceived quality. The method rationalizes the macro–micro combination by identifying the factors influencing perceived quality, which provides ideas for other studies using social media data.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Dynamic perceived quality analysis using social media data at macro- and micro-levels

Yang

Dang

2023

IMDS

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“…In this study, patent analysis of 19 companies leading the eVTOL market established a total technical classification system (Tech-tree) of the eVTOL market and derived detailed technology-specific competitiveness analysis and related component companies through various patent-analysis indicators. While we cannot claim that patent indicators directly represent the R&D performance of a particular company, as patents have been used as a main indicator for measuring R&D activity in many existing studies [35], it is reasonable to say that it does indicate a certain level of R&D activity, as evidenced by quantitative empirical studies that examined the relationship between R&D activities, patents, and corporate market changes [32,36,37].…”

Section: Network Analysismentioning

confidence: 95%

A Study on Finding Partners through Patent Network Analysis of UAM (Urban Air Mobility)

Ryu¹,

Kim

2022

Applied Sciences

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This paper presents an open innovation strategy by identifying the patent impact index and cooperation network through patent analysis for leading companies developing technology in the UAM field. Among companies developing UAM technology, patent analysis was conducted on the leading companies with active patent activities, technology classification was used to match companies by parts, and a technical capability index was utilized to identify the companies. When developing UAM technology in the future, this can help companies seek effective partners to improve competitiveness in technology development. To the best of our knowledge, the work done in this paper is unprecedented, as it suggests methods for patent analysis and verifies them by analyzing the UAM patents with the proposed method.

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“…In addition, a multiple regression model is built. The paper [22] presents an approach for a customer-perceived value investigation using the structural equation model and opinion mining.…”

Section: Introductionmentioning

confidence: 99%

Stacking Machine Learning Model for the Assessment of R&D Product’s Readiness and Method for Its Cost Estimation

et al. 2022

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The modern technology universities have the necessary resource and material base for developing and transferring R&D products. However, the cost estimation process is not formalized. There are many methods of estimating the cost of R&D products’ commercialization processes. However, in some cases, we cannot consider any single technique to be the best one as each of them has advantages and disadvantages. In such conditions, all efforts should be made to use a combination of the estimation techniques to arrive at a better cost and quality estimate. The effectiveness of the valuation of R&D products is of particular importance in today’s economy and due to the need to analyze large data sets prepared for transfer from universities to the business environment. This paper presents the model, two methods, and general information technology for R&D products’ readiness level assessment and R&D products’ cost estimation. The article presents the complex method for determining the cost of R&D products, which will allow: increasing the efficiency of the transfer, commercialization, and market launch of R&D products, and promoting the interaction of all components of the national innovation infrastructure, innovations, etc. The need to consider many different indicators when evaluating R&D products has determined the need to use machine learning algorithms. We have designed a new machine learning-based model for the readiness assessment of R&D products, which is based on the principle of “crowd wisdom” and uses a stacking strategy to integrate machine learning methods. It is experimentally established that the new stacking model based on machine learning algorithms that use random forest as a meta-algorithm provides a minimum of a 1.03 times higher RMSE compared to other ensemble strategies.

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A systematic approach to prioritizing R&D projects based on customer-perceived value using opinion mining

Cited by 20 publications

References 66 publications

Dynamic perceived quality analysis using social media data at macro- and micro-levels

Dynamic perceived quality analysis using social media data at macro- and micro-levels

A Study on Finding Partners through Patent Network Analysis of UAM (Urban Air Mobility)

Stacking Machine Learning Model for the Assessment of R&D Product’s Readiness and Method for Its Cost Estimation

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