Classifying travellers’ requirements from online reviews: an improved Kano model

Zhao, Meng; Liu, Mengjiao; Xu, Chang; Zhang, Chenxi

doi:10.1108/ijchm-06-2022-0726

Cited by 14 publications

(4 citation statements)

References 67 publications

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“…Additionally, we introduced utility-based KANO mapping rules to classify consumer preferences for product attributes. Compared to broad preference categorizations like the two-factor and four-factor theories, the KANO model provides a more detailed attribute classification and has been widely applied in consumer preference analysis studies (e.g., Oh et al [52] and Zhao et al [50]). However, these studies only capture the influence of a single attribute on consumer satisfaction evaluation decisions.…”

Section: Discussionmentioning

confidence: 99%

“…Qi et al [49] applied the joint analysis method and the KANO model to classify the attributes of laptop computers and obtain product improvement strategies. Zhao et al [50] developed a strength-frequency KANO (SF-KANO) model, which considered the interaction between strength and frequency, to classify the demands expressed by different travelers in online reviews with the goal of maximizing traveler satisfaction at the lowest cost. Jiang and Li [51] proposed a method based on multi-dimensional sentiment analysis and the KANO model to quantify customer satisfaction by mining customer demand data from online reviews.…”

Section: User Preferencesmentioning

confidence: 99%

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A Two-Stage Nonlinear User Satisfaction Decision Model Based on Online Review Mining: Considering Non-Compensatory and Compensatory Stages

Li,

Zhu,

Zhang

et al. 2024

JTAER

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Mining user satisfaction decision stages from online reviews is helpful for understanding user preferences and conducting user-centered product improvements. Therefore, this study develops a two-stage nonlinear user satisfaction decision model (USDM). First, we use word2vec technology and lexicon-based sentiment analysis to mine the sentiment polarity of each product attribute in the reviews. Then, we develop KANO mapping rules using utility functions to classify consumer preferences based on attribute importance. Based on this, a two-stage nonlinear USDM is developed to describe post-purchase evaluation behavior. In the first non-compensatory stage, consumers determine their initial satisfaction level based on the performance of basic attributes. If the performance of these attributes is poor, it is almost impossible for users to be satisfied. In the compensatory stage, the performance of the remaining attributes collectively affects final satisfaction through participation in user utility calculation. With the use of reviews from JD.com, we develop a genetic algorithm to determine feasible solutions for the USDM and verify its validity and robustness. The USDM is proven to be effective in predicting user satisfaction compared to other classic models and machine learning algorithms. This study provides a universal pattern for user satisfaction decisions and extends the study on preference analysis.

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Section: Discussionmentioning

confidence: 99%

Section: User Preferencesmentioning

confidence: 99%

A Two-Stage Nonlinear User Satisfaction Decision Model Based on Online Review Mining: Considering Non-Compensatory and Compensatory Stages

Li,

Zhu,

Zhang

et al. 2024

JTAER

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“…To bridge the aforementioned gaps in the nonlinear quantification of the quality–satisfaction relationship in OFD services, this study aims to synthesize existing evidence on OFD service qualities and establish a systematic evaluation to quantitatively characterize their effects on consumer’s satisfaction in a nonlinear manner. The Kano model is adopted (Kano et al ., 1984), as it is one of the most established quality models widely applied by both practitioners and researchers (He et al ., 2023; Zhao et al ., 2023). As depicted in Figure 2, the model abandons a strictly linear view of the impact of service quality on consumer’s satisfaction by categorizing service attributes into attractive (A), one-dimensional (O), must-be (M), indifferent (I) and reverse (R) with distinct patterns.…”

Section: Introductionmentioning

confidence: 99%

Unveiling consumers’ nonlinear evaluation of service performances in online food delivery: a quantitative Kano analysis

Ma,

Limierta,

Teo

et al. 2023

BFJ

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PurposeThe study proposes an evaluation model that allows quantitative characterization of the effects of service quality on consumer’s satisfaction for online food delivery (OFD) services in a nonlinear manner. As such, the authors endeavor to bridge the research-to-practice gaps whereby the effect magnitudes and nonlinear patterns of service quality have been overlooked in the current literature.Design/methodology/approach The quantitative Kano method is adopted. A Kano questionnaire was first developed by synthesizing and operationalizing existing evidence on OFD service qualities. The questionnaire solicited consumers’ evaluations of 21 OFD service attributes, and it was distributed to an online panel in Singapore. With 580 valid responses, the functions that quantitatively depict effects of each attribute on consumer’s satisfaction were subsequently derived.Findings The results reveal that among Singaporean consumers, food quality, reliability of delivery, responsiveness of customer support, ease-of-use of digital interfaces and promotions are pivotal attributes contributing to above-average satisfaction improvement across all performance levels. Meanwhile, delivery riders’ attitudes and real-time tracking functions emerge as substantial contributors to satisfaction at high-performance levels.Practical implications The findings provide crucial insights for OFD practitioners in Singapore in resource prioritization and service optimization. This study demonstrated the importance of streamlining customer support services and focusing on the utilitarian aspects of OFD services. Moreover, these results can be employed in advanced service improvement procedures, providing a roadmap for future OFD service enhancements.Originality/value This study pioneers the development of a quantitative quality evaluation model in the OFD context. With the established quantitative Kano model, the study addresses the omission of effect magnitudes and nonlinear patterns of service quality. It highlights the transition from a binary “does it affect satisfaction” to a more nuanced “how much does it affect satisfaction” approach, offering a robust understanding of consumer’s satisfaction dynamics.

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“…Pai, Yeh, and Tang (2018) also employed the Kano model in the restaurant industry chain to classify service quality attributes but only limited to several attributes of the marketing mix (product, place, people, process, and physical evidence). In the research of Zhao, Liu, Xu, and Zhang (2023), the Kano model was utilized to classify traveler needs consisting of 13 attributes; the results were beneficial for hoteliers and could improve hotel service.…”

Section: Introductionmentioning

confidence: 99%

Korean Restaurants’ Consumer Needs Based on Marketing Mix Through the Kano Model

Zavira

Ismoyowati

Yuliando

2023

J AGRIB RURAL DEV RES

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A proliferation of Korean restaurants in Yogyakarta can be seen over the past few years, each with its unique concept. However, a survey on Google Star Rating suggests that not all of these restaurants are sustainable. The significant discrepancy between expectations and actual satisfaction of consumers is likely a contributing factor. Moreover, intense competition exists between these restaurants. This study aims to identify which aspects of marketing—such as product, price, place, promotion, people, process, and physical evidence—influence Korean restaurants’ consumer needs. Using the Kano model, consumer satisfaction was analyzed by classifying consumer needs into attractive, must-be, one-dimensional, indifferent, reverse, or questionable categories. Purposive and snowball sampling methods were employed to select 100 respondents to complete a questionnaire. The results unveiled that four of the seven marketing mix attributes needed by Korean restaurants’ consumers fell into the one-dimensional category. The features consisted of physical evidence (clean dining room), people (clean and tidy employee appearance), product (good taste), and process (timely service). Furthermore, the attributes of unique offers (D1); fast service (F2); menu information, ingredients, how to cook it (E3); and affordable food prices (B1) contributed to greater consumer satisfaction. These attributes boosted consumer satisfaction by 80%, 79.8%, 74.5%, and 73.7%, respectively.

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Classifying travellers’ requirements from online reviews: an improved Kano model

Cited by 14 publications

References 67 publications

A Two-Stage Nonlinear User Satisfaction Decision Model Based on Online Review Mining: Considering Non-Compensatory and Compensatory Stages

A Two-Stage Nonlinear User Satisfaction Decision Model Based on Online Review Mining: Considering Non-Compensatory and Compensatory Stages

Unveiling consumers’ nonlinear evaluation of service performances in online food delivery: a quantitative Kano analysis

Korean Restaurants’ Consumer Needs Based on Marketing Mix Through the Kano Model

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