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1.
Data-driven innovation has received increasing attention, which explores big data technologies to gain more insights and advantages for product design. In user experience (UX) based design innovation, user-generated data and archived design documents are two valuable resources for various design activities such as identifying opportunities and generating design ideas. However, these two resources are usually isolated in different systems. Additionally, design information typically represented based on functional aspects is limited for UX-oriented design. To facilitate experience-oriented design activities, we propose a twin data-driven approach to integrate UX data and archived design documents. In particular, we aim to extract UX concepts from product reviews and design concepts from patents respectively and to discover associations between the extracted concepts. First, a UX-integrated design information representation model is proposed to associate capabilities with key elements of UX at the concept, category, and aspect levels of information. Based on this model, a twin data-driven approach is developed to bridge experience information and design information. It contains three steps: experience aspect identification using an attention-based LSTM (Long short-term memory) network, design information categorization based on topic clustering using BERT (Bidirectional Encoder Representations from Transformers) and LAD (Latent Dirichlet allocation) model, and experience needs and design information integration by leveraging word embedding techniques to measure concept similarity. A case study using healthcare-related experience and design information has demonstrated the feasibility and effectiveness of this approach.  相似文献   

2.
[目的/意义]实现海量产品评论数据的快速分析,帮助产品设计人员高效地获取用户需求,在新产品设计的决策中提供参考。[方法/过程]在特征提取和情感分析的基础上,构造了包括"词+词性+词干+位置+依存关系"等节点特征的条件随机场模型,按照"产品特征、谁、在何种情境下、遇到了什么问题"4个要素,以描述手机屏幕和电池的负面评论为例,从产品评论中提取用例。[结果/结论]模型评估和实证研究表明,所构造的模型可以有效地从评论文本中识别产品特征、使用主体、使用情景和遇到的问题,从而快速构造用例,获取用户需求。  相似文献   

3.
Customers commonly share opinions and experiences about products via the internet by means of social media and networking sites. The generated textual data is often analysed by means of Sentiment Analysis (SA) as means to assess customer opinions on product features more efficiently than through surveys. To enable a more objective product target setting, the impact of product feature performance changes on customer satisfaction is essential. Kano et al. (1984) presented a survey-based model to classify product features based on their impact on customer satisfaction to aid designers in their product target setting. Approaches extending the Kano model rely on customer surveys as input data. In addition, existing studies classifying extracted product features from textual data (e.g. product reviews) rarely provide a clear separation in terms of Kano categories. Thus, the impact of identified product features on customer satisfaction remains unknown to product designers. This paper presents a methodology for autonomously classifying extracted aspects from textual data into Kano categories. For verification purposes, two examples using coffee machine and smartphone user reviews are presented. Results indicate that the proposed methodology efficiently provides product designers with insightful customer information through the proposed aspect categorization.  相似文献   

4.
杨楠 《科研管理》2021,42(5):87-93
伴随着社会化媒体的普及,企业日益注重虚拟品牌社区的建设,借此向顾客展示产品独特价值,以期形成良好的口碑传播效应。通过采用扎根理论研究方法,搜集社区评论信息作为经验资料,并进行编码分析,提炼出互动体验、社区归属感以及品牌定位等范畴,阐释了顾客参与价值共创与品牌形象塑造的关系。研究表明,产品价值共创包括价值认知以及用户需求等核心要素,且有利于形成良好的品牌文化,而品牌形象的塑造则依赖于创新产品及建构以用户价值交互为基础的生态圈,顾客参与价值共创有助于品牌形象的塑造,企业应围绕产品创新打造虚拟品牌社区,强化顾客互动体验,并建立完善的信息沟通机制,引导顾客积极参与价值共创。  相似文献   

5.
李贺  曹阳  沈旺  李叶叶  涂敏 《情报科学》2021,39(8):3-11
【目的/意义】目前,越来越多的消费者参与在线评论进行信息交互和需求表达。从丰富的在线产品评论中 识别并分析用户需求有助于企业有针对性地提升产品及服务质量,从而推动企业可持续发展。【方法/过程】本文利 用LDA模型对在线手机评论进行评论主题及产品特征挖掘,有效识别用户需求要素。基于Kano模型设置用户需 求调查问卷,结合用户满意指数分析各项需求对用户满意度的影响,确定各类用户需求重要度和供给优先级顺 序。【结果/结论】本文将24项用户需求要素划分为6项高魅力型需求、8项低魅力型需求、3项高期望型需求、3项高 必备型需求、2项低必备型需求、2项无差异型需求,进一步提出企业产品管理的优化策略。【创新/局限】本文利用文 本挖掘方法对真实的在线评论进行用户需求分析,有效克服传统用户需求调查方法中存在的需求来源滞后及可靠 性不足等问题。此外,本文所选产品的品牌相同,后续研究可向多平台及多品牌的产品需求分析进行改进和深化。  相似文献   

6.
Fast development of IT and ICT facilitate customers to post a large volume of their concerns and expectation online, which are widely accepted to be a valuable resource for product designers. However, it is found that only a small number of small and medium-sized enterprises (SMEs) have capabilities to leverage customer online insights for design innovation, which often demonstrate a significant share in national economies growth. To discover the beneath reasons regarding the barrier that prevent them to make effective utilization, in this study, as a concrete example, manufacturing SMEs in the South Wales and Greater Manchester industrial areas of the UK are focused and their potential motivations for using and knowledge of big data-based customer analytics are investigated. An exploratory survey was conducted in terms of the type of customer data they have, the storage approaches, the volume of customer data, etc. Next, a carefully devised exploratory study was undertaken to understand how SMEs perceive the relations between customer data and product design, how about their expectations from big customer data analytics and what really challenges SMEs to exploit the value of big customer data. Besides, a demonstration platform is developed to present SMEs an automatic process of analysing customer online reviews and the capacity on customer insights acquisition and strategic decision making. Finally, findings from two focus groups indicate the different managerial and technical considerations required for SMEs considering implementing big data and customer analytics. This study encourages SMEs to welcome big customer data and suggests that a cloud-based approach may be the most appropriate way of giving access to big data analytics techniques.  相似文献   

7.
在线商品评论对产品销量影响研究   总被引:3,自引:0,他引:3  
李健 《现代情报》2012,32(1):164-167
作为一种新型的口碑传播方式,在线产品评论成为了消费者和商家了解产品质量和服务的最为重要的信息来源。在线产品评论哪些因素影响到消费者的购买决策,对产品的销量产生多大的影响已经成为人们关注的重要问题。通过对在线手机评论研究发现,"在线评论数量"、"商品的关注度"对在线手机销量有显著性影响,更为重要的是我们发现"评论的时效性"和"顾客认为评论的有用率"对手机的销量也有非常重要的显著性影响,而"评论的正负情感倾向性"等对产品的销量无明显影响。  相似文献   

8.
邢云菲  曹高辉  陶然 《情报科学》2021,39(9):101-109
【目的/意义】网络用户在线评论是用户对某产品或服务机构体验感知的反馈,对网络用户在线评论的文 本挖掘是情报分析的重要内容。【方法/过程】为了更有效从海量网络用户在线评论文本中挖掘用户感兴趣的信息, 本研究爬取TripAdvisor网站四大城市的酒店用户在线评论,基于主题图谱理论和文本聚类算法构建网络用户在线 评论的聚类模型,通过图谱可视化揭示不同地区酒店用户观点差异,并分析不同图谱的社会网络特征。【结果/结 论】研究发现酒店用户最关注的是服务,其次是酒店的环境和位置。本研究能够快速挖掘酒店用户关注内容,对帮 助酒店管理者了解用户住宿需求并以此提高用户满意度具有重要价值。【创新/局限】本文结合主题图谱和文本挖 掘技术构建酒店用户在线评论主题图谱,在大数据文本主题聚类上显示出优越性。但本文仅分析TripAdvisor网站 四个城市中部分酒店的用户在线评论,数据面覆盖不够广泛。  相似文献   

9.
基于中文网络客户评论的消费者行为分析方法   总被引:2,自引:0,他引:2  
邱云飞  王雪  邵良杉 《现代情报》2012,32(1):8-11,15
网络上针对商品的评论中含有消费者的消费习惯、消费体验和消费偏好等颇有价值的信息,这为观察和分析消费者的行为提供了很好的资料。文中设计了一个网络环境下的消费者行为分析方法。首先,在收集的客户评论中提取产品特征、消费者信息和消费者对具体产品特征的情感倾向;其次,按消费者信息进行消费者群体划分,进而探讨不同消费群体对不同产品的喜好。企业可通过该方法及时获取消费人群对产品的反馈数据并制定正确的市场营销策略。  相似文献   

10.
王莉 《科研管理》2019,40(7):182-191
通过虚拟顾客参与平台(Virtual Customer Environments, VCE)来吸引顾客参与创新、利用顾客大数据、创建顾客中心型组织成为企业的重要策略,但VCE的运行机制并未得到理论界的足够重视。本文以VCE功能为主线,将VCE分为信息展示、需求收集和深度互动三个子平台。基于刺激-机体-反应模型,分析每个子平台的运行机制。具体而言,IT环境和市场环境的发展构成VCE的运行基础,企业和顾客之间的交互关系构成VCE的运行动因,企业吸引行为和顾客参与行为构成VCE的运行过程。进一步运用内容分析法,本文检验了中国500强企业网站中VCE子平台的运行,实证研究结果支持理论模型所提出的运行机制。但同时也发现,大多数中国500强企业尚未充分构建需求收集和深度互动这两个子平台,表现为在实际运行中未能有效吸引顾客参与。本研究不仅推动了VCE理论的发展,对顾客参与理论进行了拓展,并且有助于指导企业完善VCE平台的构建,从信息技术的角度塑造顾客导向型组织,提升创新绩效。  相似文献   

11.
With the rapid development of information technology, customers not only shop online—they also post reviews on social media. This user-generated content (UGC) can be useful to understand customers’ shopping experiences and influence future customers’ purchase intentions. Therefore, business intelligence and analytics are increasingly being advocated as a way to analyze customers’ UGC in social media and support firms’ marketing activities. However, because of its open structure, UGC such as customer reviews can be difficult to analyze, and firms find it challenging to harness UGC. To fill this gap, this study aims to examine customer satisfaction and dissatisfaction toward attributes of hotel products and services based on online customer textual reviews. Using a text mining approach, latent semantic analysis (LSA), we identify the key attributes driving customer satisfaction and dissatisfaction toward hotel products and service attributes. Additionally, using a regression approach, we examine the effects of travel purposes, hotel types, star level, and editor recommendations on customers’ perceptions of attributes of hotel products and services. This study bridges customer online textual reviews with customers’ perceptions to help business managers better understand customers’ needs through UGC.  相似文献   

12.
吉顺权  周毅 《现代情报》2015,35(6):114-121
在总结用户评论相关研究的基础上,提出关联规则理论在用户评论挖掘中的作用,包括可以用来挖掘产品的优劣势特征及其程度大小,以及挖掘影响产品整体评价的关键特征。提出了基于产品特征关联规则数据挖掘的企业竞争情报应用模型,包含确定用户评论情报源及其采集、数据预处理及其产品特征提取、数据结构化处理及其关联规则分析和产品优劣势特征及其关键特征的对比分析四个模块。最后通过实验论证了这一模型的价值。  相似文献   

13.
严建援  张丽  张蕾 《情报科学》2012,(5):713-716,719
从在线评论文本内容的视角出发,通过中国大型B2C电子商务网站的221个有效样本的实证分析,研究了在线评论内容对评论有用性的影响。研究发现,评论深度越深、越客观、传达越多产品实物与网站描述是否相符以及产品特性的信息,则评论有用性越高;而评论内容中表述越多的个人喜好和感受反而评论有用性越低;评论传达的情感强度与评论有用性关系不显著。  相似文献   

14.
The research on users as a source of innovation has been coming into blossom and the studies about the effect of users’ lead userness on their innovation-related activities are drawing more and more attention from both academic and business circles. However, there have been few empirical studies exploring the relationship between users’ lead userness and their innovation-related knowledge sharing behavior in the context of online user community and the mediating effects of users’ social capital and their perceived behavioral control on this relationship. By empirically analyzing the 140 data collected from an online user community that is used as an important source of innovation for a company with the structural equation modeling analysis through the partial least squares method, this study reveals that users’ lead userness has a positive relationship with their innovation-related knowledge sharing in the online user community and users’ social capital and perceived behavioral control jointly and fully mediate this positive relationship. Based on the new findings, this study is expected to provide useful implications which can contribute to widening and deepening the research stream about the effect of users’ lead userness on their innovation-related knowledge sharing in the online user community.  相似文献   

15.
This paper extracted discrete emotions from online reviews based on an emotion classification approach, and examined the differential effects of three discrete emotions (anger, fear, sadness) on perceived review helpfulness. We empirically tested the hypotheses by analyzing the “verified purchase” reviews on Amazon.com. The findings of this study extend the previous research by suggesting that product type moderates the effects of emotions on perceived review helpfulness. Anger embedded in a customer review exerts a greater negative impact on perceived review helpfulness for experience goods than for search goods. Fear embedded in a review is identified as an important emotional cue to positively affect the perceived review helpfulness with more persuasive messages. As the level of sadness embedded in a review increases, perceived review helpfulness decreases. These findings contribute to a better understanding of the important role of emotions embedded in reviews on the perceived review helpfulness. This study also provides practical insights related to the presentation of online reviews and gives suggestions for consumers regarding how to select and write a helpful review.  相似文献   

16.
Ideation is an important phase in the new product development process at which product designers innovate and select novel ideas that can be added as features to an existing product. One way to find novel ideas is to transfer uncommon features of products of other domains and integrate them into the product to be improved. However, before incorporating such targeted features into the product, they need to be evaluated against the customers’ acceptance in social media using sentiment aggregation tools. Despite the many studies in sentiment analysis, mapping the customers’ opinions towards both high-level and technical features of a product extracted from social media to their best corresponding component in that product is still a challenge. Furthermore, none of the existing approaches ascertains the sentiment value of a targeted feature by capturing its dependencies on other features. In this paper, to address these drawbacks, we propose the sentiment aggregation framework for targeted features (SA-TF). SA-TF determines the sentiment of a targeted feature by assisting product designers in the tasks of mapping the features discussed in the reviews to the right product components, sentiment aggregation and considering feature dependencies to determine their polarity. The superiority of the different phases of SA-TF is demonstrated with experiments and comparing it with an existing approach.  相似文献   

17.
Existing approaches to learning path recommendation for online learning communities mainly rely on the individual characteristics of users or the historical records of their learning processes, but pay less attention to the semantics of users’ postings and the context. To facilitate the knowledge understanding and personalized learning of users in online learning communities, it is necessary to conduct a fine-grained analysis of user data to capture their dynamical learning characteristics and potential knowledge levels, so as to recommend appropriate learning paths. In this paper, we propose a fine-grained and multi-context-aware learning path recommendation model for online learning communities based on a knowledge graph. First, we design a multidimensional knowledge graph to solve the problem of monotonous and incomplete entity information presentation of the single layer knowledge graph. Second, we use the topic preference features of users’ postings to determine the starting point of learning paths. We then strengthen the distant relationship of knowledge in the global context using the multidimensional knowledge graph when generating and recommending learning paths. Finally, we build a user background similarity matrix to establish user connections in the local context to recommend users with similar knowledge levels and learning preferences and synchronize their subsequent postings. Experiment results show that the proposed model can recommend appropriate learning paths for users, and the recommended similar users and postings are effective.  相似文献   

18.
[目的/意义] 提出一种基于在线产品评论的竞争情报挖掘框架,为企业改进产品设计和制定竞争策略提供参考。[方法/过程] 利用Word2vec技术构建产品特征词集合,识别用户评论主题特征。然后使用情感分析方法对评论文本进行分类,得到特征维度的评论情感。最后从产品主题特征和情感态度特征两方面进行数据分析,并以可视化结果呈现。[结果/结论] 以汽车行业的评论数据为例进行实验,结果表明该方法能够有效提取产品情报信息,帮助企业有效识别自身品牌及竞争对手的优势和劣势,为大数据环境下的竞争情报挖掘提供方法指导。  相似文献   

19.
Consumers’ software purchase decisions are influenced both by online reviews and by their experiences with free samples provided by firms. This paper empirically investigates the differential effects of online reviews (user and editor ratings) on consumers’ sample downloading behavior, using a dataset drawn from a large software free sampling website CNET.com. Our findings extend the previous research by suggesting that information disclosure levels of free samples (indicated by licenses) moderates the impacts of online reviews on consumers’ sample downloads. For samples that disclose a great level of information, higher user ratings can increase downloads; otherwise, higher user ratings fail to increase downloads. When both user and editor ratings are available to consumers, only user ratings can increase sample downloads. The findings can be explained by consumers’ two-stage information process whereby consumers first refer to online reviews and then determine whether to sample software. This study provides practical implications on the design of information disclosure channel and offers suggestions for firms regarding how to select and apply sample licenses.  相似文献   

20.
Consumers evaluate products through online reviews, in addition to sharing their product experiences. Online reviews affect product marketing, and companies use online reviews to investigate consumer attitudes and perceptions of their products. However, when analyzing a review, it is often the case that specific contexts are not taken into consideration and meaningful information is not obtained from the analysis results. This study suggests a methodology for analyzing reviews in the context of comparing two competing products. In addition, by analyzing the discriminative attributes of competing products, we were able to derive more specific information than an overall product analysis. Analyzing the discriminative attributes in the context of comparing competing products provides clarity on analyzing the strengths and weaknesses of competitive products and provides realistic information that can help the company's management activities. Considering this purpose, this study collected a review of the BB Cream product line in the cosmetics field. The analysis was sequentially carried out in three stages. First, we extracted words that represent discriminative attributes by analyzing the percentage difference of words. Second, different attribute words were classified according to the meaning used in the review by using latent semantic analysis. Finally, the polarity of discriminative attribute words was analyzed using Labeled-LDA. This analysis method can be used as a market research method as it can extract more information than a traditional survey or interview method, and can save cost and time through the automation of the program.  相似文献   

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