Mining online reviews with a Kansei-integrated Kano model for innovative product design

Jin, Jian; Jia, Danping; Chen, Kejia

doi:10.1080/00207543.2021.1949641

Cited by 54 publications

(31 citation statements)

References 69 publications

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“…With technology advancements and the abundance of online reviews, novel approaches in data processing for categorization have emerged, addressing specific areas of interest within the Kano model. For example, Park and Jeon (2022) utilized Bi-directional Encoder Representations from Transformers (BERT) and Shapley Additive eXplanation (SHAP), while Joung and Kim (2021) employed neural networks, and Jin et al. (2021) integrated Kansei emotions extraction.…”

Section: The Relevance Of Student Support and Servicesmentioning

confidence: 99%

Enucleating the student support and services needs in higher education: the application of Kano analysis as a strategic tool

Tejero-Dakay,

Lozano,

Ferolin

2024

IJEM

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PurposeThis paper aims to help higher education institutions (HEIs) develop a better understanding of student support and services needs, thereby enabling them to allocate limited resources for initiatives that effectively improve student experience.Design/methodology/approachAn assessment framework following the Kano analysis is developed to categorize student service features based on customer satisfaction and need fulfillment. The framework is used at a local university, using 23 service features listed as minimum requirements by the national regulatory body for education. Analysis of the satisfaction survey results and prioritization are based on quality indices derived from a factor of importance and the satisfaction gap. A survey was conducted for two academic years to generate a comparison of results.FindingsOf the list mandated as minimum requirements for HEIs, the study revealed that no features were regarded as “must-be,” eight as performing, 14 as attractive and one as indifferent by the students. As these results were disaggregated per year level, the natural decay of delight as in the Kano theory was exhibited as there were less attractive features for students who have been in the university longest. After a full-year academic cycle, results compared to the baseline figures seemed to reveal of impact of the achievement of performance targets by the units rendering specific activities on client satisfaction.Research limitations/implicationsFurther rounds of the study are needed to build up more data sets on the relationship between objective performance and satisfaction level for performing features, mindful that this categorization is also bound to change along the way.Practical implicationsAs HEIs in the Philippines journey towards the establishment of their own respective internal quality assurance systems, this study provides a practical approach for institutions to transform a mere list of student services for compliance into a strategic tool to enhance the student experience.Originality/valueIn the context of continuous quality improvement, the study presents how the qualitative Kano model, along with simple quantitative tools in the methodology, can be utilized not only in the planning stage of service design but also in closing the planning, doing, checking and acting (PDCA) cycle and opening the quality improvement spiral.

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Section: The Relevance Of Student Support and Servicesmentioning

confidence: 99%

Enucleating the student support and services needs in higher education: the application of Kano analysis as a strategic tool

Tejero-Dakay,

Lozano,

Ferolin

2024

IJEM

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“…Moreover, Calheiros et al applied LDA for a requirement analysis of eco-hotel reviews. While some methodologies have incorporated simple natural language processing techniques like dependency syntax analysis [7] and WordNet [5,25], these approaches have only partly mitigated LDA's limitations concerning short texts laden with long-tail and low-frequency terms, rendering the extraction of coherent and interpretable topics as a persisting challenge. With the rapid evolution of neural network technology, deep-learning-based methodologies for acquiring user requirement attributes have progressively become more mainstream.…”

Section: Related Workmentioning

confidence: 99%

“…Nevertheless, these manually collected words might not fully represent the entire spectrum of user emotions. Efforts by Wang et al [25] to expand upon sensory words through the WordNet hierarchy, and explorations by Jin et al [7] into the relationships between emotional and sensory words in reviews using word2vec underscore the persisting challenges, such as the difficulty in aligning sensory words with specific contexts and their variable emotional polarities across different scenarios. Moreover, the task of updating and assessing uncollected sensory words remains formidable.…”

Section: Related Workmentioning

confidence: 99%

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A PTM-Based Framework for Enhanced User Requirement Classification in Product Design

Zhang,

Dou,

et al. 2024

Electronics

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Accurately identifying and classifying customer requirements is crucial for successful product design. However, traditional methods for requirement classification, such as Kano models based on questionnaires, can be time-consuming and may not capture all requirements accurately. Analyzing large volumes of user reviews using simple natural language processing techniques can also result in accuracy issues. To address these challenges, we propose a framework that combines pre-trained models (PTMs), Kano models, and the sentiment analysis technique. Our approach integrates an LDA-K-Means model enhanced by PTM ERNIE for pinpointing product feature topics within user reviews. Then, a sentiment analysis is performed using the fine-tuned PTM SKEP to assess user satisfaction with features. Finally, the Kano model is applied to perform requirement classification. We evaluate our framework quantitatively, demonstrating its superior performance compared to the baseline models. Our sentiment analysis model also outperforms the other baseline models. Moreover, a case study on smartphones illustrates the effectiveness of our framework. This research results suggest that leveraging a suitable PTM can better address the problem of requirement classification in user review analyses, leading to improved product design.

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“…Previous studies proposed ways to use sentiment analysis to augment user-centric models and design techniques [16][17][18][19]. The extraction of customer opinions to support product design has also gained considerable attention from researchers [10,20,21].…”

Section: Problem Statementmentioning

confidence: 99%

A Generic Graph-Based Method for Flexible Aspect-Opinion Analysis of Complex Product Customer Feedback

Kpiebaareh

Agyemang

et al. 2022

Information

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Product design experts depend on online customer reviews as a source of insight to improve product design. Previous works used aspect-based sentiment analysis to extract insight from product reviews. However, their approaches for requirements elicitation are less flexible than traditional tools such as interviews and surveys. They require costly data labeling or pre-labeled datasets, lack domain knowledge integration, and focus more on sentiment classification than flexible aspect-opinion analysis. Related works lack effective mechanisms for probing the customer feedback of complex configurable products. This study proposes a generic graph-based opinion mining and analysis method for product design improvement. First, a customer feedback data preprocessing and annotation pipeline that can incorporate designer-specified domain knowledge is proposed. Second, an intuitive opinion-aware labeled property graph data model is designed to ingest preprocessed feedback data and perform ad hoc opinion analysis. Applying the generic model to a real-world dataset demonstrates superior functionality and flexibility compared to related works. A wider range of analyses is supported in a single model without repeating data preprocessing and modeling. Specifically, the proposed method supports regular and comparative aspect-opinion analysis, aspect satisfaction/influence ranking, opinion trend extraction, and targeted aspect-opinion summarization.

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Mining online reviews with a Kansei-integrated Kano model for innovative product design

Cited by 54 publications

References 69 publications

Enucleating the student support and services needs in higher education: the application of Kano analysis as a strategic tool

Enucleating the student support and services needs in higher education: the application of Kano analysis as a strategic tool

A PTM-Based Framework for Enhanced User Requirement Classification in Product Design

A Generic Graph-Based Method for Flexible Aspect-Opinion Analysis of Complex Product Customer Feedback

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