基于UIE-GT-KANO框架的手机产品需求分析

樊宇, 范保国, 陈进东, 詹敏, 任敏慧

包装工程(设计栏目) ›› 2025, Vol. 46 ›› Issue (18) : 288-299.

PDF(1924 KB)
PDF(1924 KB)
包装工程(设计栏目) ›› 2025, Vol. 46 ›› Issue (18) : 288-299. DOI: 10.19554/j.cnki.1001-3563.2025.18.026
工业设计

基于UIE-GT-KANO框架的手机产品需求分析

  • 樊宇1,2,*, 范保国1, 陈进东1, 詹敏3, 任敏慧4
作者信息 +

Demand Analysis of Mobile Phone Products Based on UIE-GT-KANO Framework

  • FAN Yu1,2,*, FAN Baoguo1, CHEN Jindong1, ZHAN Min3, REN Minhui4
Author information +
文章历史 +

摘要

目的 旨在解决企业在消费市场中准确把握用户需求的问题,并通过优化产品和服务来提升品牌形象。方法 提出了一种融合方面级情感分析、扎根理论和Kano模型的需求分析框架。首先利用通用信息抽取模型(UIE)对手机用户评论提取出方面词和情感倾向;其次结合扎根理论对提取出的方面词进行分析和编码,挖掘用户需求的深层结构;最后运用Kano模型开展用户需求多维度分析。结果 用户对于手机产品的主要需求维度可以分为产品设计与感知、产品性能与技术、品牌与市场服务,不同市场类型下用户需求存在明显差异。结论 随着产品价位提升,用户需求更倾向于精神层面的满足,包括设计与美学、购买体验与服务质量等方面。产品的设计与感知、品牌市场与服务范畴成为用户期望或魅力需求,对用户满意度有显著影响。同时,性能与技术需求虽为必备,但在用户感知中提升空间有限。厂商要在市场中扩大占有率需要在保证手机产品的性能技术提升的同时,在产品的设计与感知、品牌市场与服务中寻找巧思。

Abstract

The work aims to solve the problem of enterprises accurately grasping the needs of users in the consumer market and enhance the brand image by optimizing products and services. A requirement analysis framework integrating aspect-based sentiment analysis, Grounded Theory and Kano model was proposed. Firstly, the Universal Information Extraction (UIE) model was employed to extract aspect terms and emotional tendencies from mobile phone user comments. Subsequently, the extracted terms were analyzed and coded in conjunction with Grounded Theory (GT) to uncover the deep structure of user demands. Finally, the Kano model was used to carry out multi-dimensional analysis of user demands. The main demand dimensions of users for mobile phone products were divided into product design and perception, product performance and technology, brand and market service. There were obvious differences in user demands under different market types. With the increase of product price, user demands are more inclined to meet the spiritual aspects, including design and aesthetics, purchase experience and service quality, etc. Product design and perception, brand market and service category have become users' expectations or charm demands, having a significant impact on user satisfaction. At the same time, although the performance and technical requirements are necessary, there is limited room for improvement in user perception. In order to expand the market share, manufacturers need to ensure the performance and technology improvement of mobile phone products, while seeking ingenuity in product design and perception, brand market and service.

关键词

情感分析 / 在线评论 / 需求分析 / 通用信息抽取 / 扎根理论

Key words

sentiment analysis / online reviews / demand analysis / universal information extraction (UIE) / Grounded theory (GT)

引用本文

导出引用1
樊宇, 范保国, 陈进东, 詹敏, 任敏慧. 基于UIE-GT-KANO框架的手机产品需求分析[J]. 包装工程. 2025, 46(18): 288-299 https://doi.org/10.19554/j.cnki.1001-3563.2025.18.026
FAN Yu, FAN Baoguo, CHEN Jindong, ZHAN Min, REN Minhui. Demand Analysis of Mobile Phone Products Based on UIE-GT-KANO Framework[J]. Packaging Engineering. 2025, 46(18): 288-299 https://doi.org/10.19554/j.cnki.1001-3563.2025.18.026
中图分类号: TB472   

参考文献

[1] 孙冰, 沈瑞. 基于在线评论的产品需求偏好判别与客户细分——以智能手机为例[J]. 中国管理科学, 2023, 31(3): 217-227.
SUN B, SHEN R.Online Reviews for Product Demand Preference Discrimination and Customer Segmentation: A Case Study of the Smart Phone Data[J]. Chinese Journal of Management Science, 2023, 31(3): 217-227. https://link.cnki.net/doi/10.16381/j.cnki.issn1003-207x.2020.0164
[2] WANG Z B, WAN M Y, CUI X H, et al.Personalized Recommendation Algorithm Based on Product Reviews[J]. Journal of Electronic Commerce in Organizations, 2018, 16(3): 22-38.
[3] WANG W X, FENG Y, DAI W Q.Topic Analysis of Online Reviews for Two Competitive Products Using Latent Dirichlet Allocation[J]. Electronic Commerce Research and Applications, 2018, 29: 142-156.
[4] FAN Z P, CHE Y J, CHEN Z Y.Product Sales Forecasting Using Online Reviews and Historical Sales Data: A Method Combining the Bass Model and Sentiment Analysis[J]. Journal of Business Research, 2017, 74: 90-100.
[5] JEONG B, YOON J, LEE J M.Social Media Mining for Product Planning: A Product Opportunity Mining Approach Based on Topic Modeling and Sentiment Analysis[J]. International Journal of Information Management, 2019, 48: 280-290.
[6] 赵宇晴, 阮平南, 刘晓燕, 等. 基于在线评论的用户满意度评价研究[J]. 管理评论, 2020, 32(3): 179-189.
ZHAO Y Q, RUAN P N, LIU X Y, et al.Study on User Satisfaction Evaluation Based on Online Comment[J]. Management Review, 2020, 32(3): 179-189.
[7] 尤天慧, 陶玲玲, 袁媛. 基于在线评论的顾客满意度评估方法[J]. 运筹与管理, 2023, 32(12): 144-150.
YOU T H, TAO L L, YUAN Y.Evaluation Method of Customer Satisfaction Based on Online Reviews[J]. Operations Research and Management Science, 2023, 32(12): 144-150.
[8] 楚东晓, 王雯露, 穆勤远. 基于LDA和语义网络的产品感知价值维度研究[J]. 包装工程, 2023, 44(S1): 47-55.
CHU D X, WANG W L, MU Q Y.Research on Product Perceived Value Dimension Based on LDA and Semantic Network[J]. Packaging Engineering, 2023, 44(S1): 47-55.
[9] 朱韦光. 基于在线评论的智能手机需求偏好判别及客户细分模型构建研究[J]. 计算机时代, 2023(9): 132-135.
ZHU W G.Research on the Construction of Smart Phone Demand Preference Discrimination Model Based on Online Review[J]. Computer Era, 2023(9): 132-135.
[10] 鞠海龙, 彭珺. 基于评论挖掘的用户购买行为因果事理图谱分析[J]. 情报科学, 2021, 39(10): 170-177.
JU H L, PENG J.Mining Competitive Intelligence Based on Event Logic Graph[J]. Information Science, 2021, 39(10): 170-177.
[11] 李永海. 一种使用在线评论信息的商品购买决策分析方法[J]. 运筹与管理, 2018, 27(2): 32-37.
LI Y H.A Decision Analysis Method for Product Purchase Based on Online Review Information[J]. Operations Research and Management Science, 2018, 27(2): 32-37.
[12] 赵玉峰, 赵一凡, 范宪伟. 着力化解青年就业的结构性矛盾——基于全国5万份青年就业调查问卷[J]. 宏观经济管理, 2024(9): 39-48.
ZHAO Y F, ZHAO Y F, FAN X W.To Address the Structural Contradiction between Youth Employment Expectations and Realities—As Highlighted in a Nationwide Survey of 50, 000 Youth Employment Questionnaires[J]. Macroeconomic Management, 2024(9): 39-48.
[13] MARTÍNEZ-MIRANDA J, PÉREZ-ESPINOSA H, ESPINOSA-CURIEL I, et al. Age-Based Differences in Preferences and Affective Reactions towards a Robot’s Personality during Interaction[J]. Computers in Human Behavior, 2018, 84: 245-257.
[14] ZHAO P L, HOU L L, WU O.Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-Level Sentiment Classification[J]. Knowledge- Based Systems, 2020, 193: 105443.
[15] COLÓN-RUIZ C, SEGURA-BEDMAR I. Comparing Deep Learning Architectures for Sentiment Analysis on Drug Reviews[J]. Journal of Biomedical Informatics, 2020, 110: 103539.
[16] 翟夏普, 安源, 龙艺璇. 本体和深度学习融合的在线评论细粒度情感分析[J]. 北京邮电大学学报, 2023, 46(5): 125-131.
ZHAI X P, AN Y, LONG Y X.Fine-Grained Emotion Analysis of Online Comments Based on the Fusion of Ontology and Deep Learning[J]. Journal of Beijing University of Posts and Telecommunications, 2023, 46(5): 125-131.
[17] MIAO Y L, CHENG W F, JI Y C, et al.Aspect-Based Sentiment Analysis in Chinese Based on Mobile Reviews for BiLSTM-CRF[J]. Journal of Intelligent & Fuzzy Systems, 40(5): 8697-8707.
[18] MA K, TAN Y J, TIAN M, et al.Extraction of Temporal Information from Social Media Messages Using the BERT Model[J]. Earth Science Informatics, 2022, 15(1): 573-584.
[19] 王秀红, 高敏. 基于BERT-LDA的关键技术识别方法及其实证研究——以农业机器人为例[J]. 图书情报工作, 2021, 65(22): 114-125.
WANG X H, GAO M.The Key Technology Identification Method Based on BERT-LDA and Its Empirical Research: A Case Study of Agricultural Robots[J]. Library and Information Service, 2021, 65(22): 114-125.
[20] 杨德清, 张静, 郭伟, 等. 基于在线产品社区的动态用户需求Kano模型构建研究[J]. 机械设计, 2018, 35(3): 12-19.
YANG D Q, ZHANG J, GUO W, et al.Research on Dynamic Kano Model Construction of Customer Requirements Based on Online Product Community[J]. Journal of Machine Design, 2018, 35(3): 12-19.
[21] 王雪, 董庆兴, 张斌. 面向在线评论的用户需求分析框架与实证研究——基于KANO模型[J]. 情报理论与实践, 2022, 45(2): 160-167.
WANG X, DONG Q X, ZHANG B.Analytical Framework and Empirical Study of User Needs for Online Reviews Based on KANO Model[J]. Information Studies (Theory & Application), 2022, 45(2): 160-167.
[22] 黄琳, 王丽亚, 明新国. 基于改进的LDA模型的产品服务需求识别[J]. 工业工程与管理, 2023, 28(1): 42-50.
HUANG L, WANG L Y, MING X G.Product Service Requirement Identification Based on Modified-LDA Model[J]. Industrial Engineering and Management, 2023, 28(1): 42-50.
[23] 卫军朝, 张怡琳. 基于Kano模型的科学数据重用需求优先序确定[J]. 图书馆杂志, 2024, 43(10): 16-28.
WEI J C, ZHANG Y L.Determination of Priority Requirements for Reuse Scientific Data Based on Kano Model[J]. Library Journal, 2024, 43(10): 16-28.
[24] 孟文, 韩玉启, 何林. 基于模糊Kano模型的顾客服务需求分类方法[J]. 技术经济, 2014, 33(6): 54-58.
MENG W, HAN Y Q, HE L.Classification Method of Customer's Service Requirement Based on Fuzzy Kano Model[J]. Technology Economics, 2014, 33(6): 54-58.
[25] LU Y J, LIU Q, DAI D, et al.Unified Structure Generation for Universal Information Extraction[C]//Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Dublin: USAACL, 2022: 5755-5772.
[26] 陈向明. 扎根理论的思路和方法[J]. 教育研究与实验, 1999(4): 58-63.
CHEN X M.Grounded Theory: Its Train of Thought and Methods[J]. Educational Research and Experiment, 1999(4): 58-63.
[27] 缪秀梅, 陈烨天, 米传民. 基于ISM和在线评论的汤山温泉顾客满意度研究[J]. 中国管理科学, 2019, 27(7): 186-194.
MIAO X M, CHEN Y T, MI C M.Study on Consumer Satisfaction of Tangshan Hot Springs Based on ISM and Online Reviews[J]. Chinese Journal of Management Science, 2019, 27(7): 186-194.
[28] 张新兴, 杨志刚, 郑永田. 基于在线评论文本的游客感知图书馆形象研究——以携程旅行网为例[J]. 图书与情报, 2023(6): 98-107.
ZHANG X X, YANG Z G, ZHENG Y T.Research on the Visitor Perceived Image of Library Based on Online Comment Text—A Case Study of Ctrip[J]. Library & Information, 2023(6): 98-107.
[29] 刘清堂, 尹兴翰, 吴林静, 等. 基于学习者评论数据挖掘的MOOC课程质量影响因素研究[J]. 远程教育杂志, 2023, 41(1): 80-90.
LIU Q T, YIN X H, WU L J, et al.Research on the Influencing Factors of MOOC Course Quality Based on Learner Review Data Mining[J]. Journal of Distance Education, 2023, 41(1): 80-90.
[30] 杨益兴, 吴刚, 陈兰芳, 等. 基于LDA主题模型的多阶段生鲜消费者需求研究——以京东为例[J]. 管理案例研究与评论, 2024, 17(1): 105-122.
YANG Y X, WU G, CHEN L F, et al.Research on Multi-Stage Fresh Consumer Demands Based on LDA Topic Model: A Case of JingDong[J]. Journal of Management Case Studies, 2024, 17(1): 105-122.
[31] 李贺, 曹阳, 沈旺, 等. 基于LDA主题识别与Kano模型分析的用户需求研究[J]. 情报科学, 2021, 39(8): 3-11.
LI H, CAO Y, SHEN W, et al.User Demand Based on LDA Subject Identification and Kano Model Analysis[J]. Information Science, 2021, 39(8): 3-11.
[32] 杨程, 谭昆, 俞春阳. 基于评论大数据的手机产品改进[J]. 计算机集成制造系统, 2020, 26(11): 3074-3083.
YANG C, TAN K, YU C Y.Mobil Phone Product Improvement Based on Big Data of Comment[J]. Computer Integrated Manufacturing Systems, 2020, 26(11): 3074-3083.
[33] 陈思为. 基于在线弹幕及评论的手机用户需求研究[D]. 成都: 西南财经大学, 2023.
CHEN S W.Research on the Demand of Mobile Phone Users Based on Online Barrage and Comments[D]. Chengdu: Southwestern University of Finance and Economics, 2023.
[34] 黄静薇. 基于在线评论的手机产品用户需求分析方法研究[D]. 广州: 华南理工大学, 2022.
HUANG J W.Research on User Demand Analysis Method of Mobile Phone Products Based on Online Comments[D]. Guangzhou: South China University of Technology, 2022.
[35] 许强. 基于在线评论的用户需求研究——以小米10手机为例[D]. 北京: 首都经济贸易大学, 2021.
XU Q.Research on User Demand Based on Online Comments—Taking Xiaomi 10 Mobile Phone as an Example[D]. Beijing: Capital University of Economics and Business, 2021.
[36] 张振刚, 罗泰晔. 基于在线评论数据挖掘和Kano模型的产品需求分析[J]. 管理评论, 2022, 34(11): 109-117.
ZHANG Z G, LUO T Y.Product Demand Analysis Based on Online Review Data Mining and Kano Model[J]. Management Review, 2022, 34(11): 109-117.

基金

国家重点研发计划课题(2019YFB1405303); 科技部国家重点研发计划项目(2022YFC3302402)

PDF(1924 KB)

Accesses

Citation

Detail

段落导航
相关文章

/