scholarly journals Integrating Hedonic Quality for User Experience Modelling

2021 ◽  
Author(s):  
Yanzhang Tong ◽  
Yan Liang ◽  
Ying Liu ◽  
Yulia Hicks ◽  
Irena Spasic
Keyword(s):  
Product Design ◽  
User Experience ◽  
User Interaction ◽  
Word List ◽  
Quality Factors ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Design Activities ◽  
Customer Review ◽  
Hedonic Quality

Abstract Research on user experience (UX) has attracted much attention from designers. Additionally, hedonic quality can help designers understand user interaction (such as attractive, original and innovative) when they experience a product. Realising the user’s interaction state is a significant step for designers to optimise product design and service. Previous UX modelling lacks exploration in user interaction state. Also, the lack of user interaction state factor will reduce the accuracy of the UX modelling. In this paper, we explore the interaction value of online customer review and introduce a new approach to integrating hedonic quality for UX modelling. Firstly, extracting word list from online customer review; Secondly, hedonic quality words are extracted from the word list and added as a hedonic quality part to UX modelling; Thirdly, we compared the analysis result with our previous study for the conclusion. This research combines hedonic quality with UX modelling to enrich modelling in the field of UX for the first time. The proposed data collection method is superior to the traditional collection methods in hedonic quality studies. Extracting hedonic quality factors from online customer reviews can in-depth provide reflections for designers to improve their product design. Furthermore, it also explored the valuable relationship between UX and online customer reviews to provide proactive thinking in user strategy and design activities.

Automated Keyword Filtering in LDA for Identifying Product Attributes from Online Reviews

2020 ◽  
pp. 1-10
Author(s):  
Junegak Joung ◽  
Harrison M. Kim
Keyword(s):  
Product Design ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Online Reviews ◽  
Previous Method ◽  
Product Attributes ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Dirichlet Allocation

Abstract Identifying product attributes from the perspective of a customer is essential to measure the satisfaction, importance, and Kano category of each product attribute for product design. This paper proposes automated keyword filtering to identify product attributes from online customer reviews based on latent Dirichlet allocation. The preprocessing for latent Dirichlet allocation is important because it affects the results of topic modeling; however, previous research performed latent Dirichlet allocation either without removing noise keywords or by manually eliminating them. The proposed method improves the preprocessing for latent Dirichlet allocation by conducting automated filtering to remove the noise keywords that are not related to the product. A case study of Android smartphones is performed to validate the proposed method. The performance of the latent Dirichlet allocation by the proposed method is compared to that of a previous method, and according to the latent Dirichlet allocation results, the former exhibits a higher performance than the latter.

The Effect of Online Customer Review and Promotion through E-Trust on the Purchase Decision of Bukalapakin Medan City

2021 ◽  
Vol 8 (8) ◽  
pp. 236-243
Author(s):  
Rimna Regina ◽  
Endang Sulistya Rini ◽  
Beby Karina Fawzeea Sembiring
Keyword(s):  
Sampling Method ◽  
Customer Behavior ◽  
Purchase Decision ◽  
Purchasing Decisions ◽  
Consumer Decisions ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Technological Developments ◽  
Customer Review ◽  
Online Shops

Technological developments have made a shift in customer behavior from purchasing through an offline shop to purchasing through an online shop or through e-commerce. People tend to use technology to support their needs. The development of e-commerce sites is increasingly intense with many e-commerce sites competing with each other to attract the attention of sellers and buyers. Currently in Indonesia, the online shop trend is on the rise. Many new online shops have started to appear, adding to the list of old online shops that have already been in this e-commerce business. One of the e-commerce sites originating from within the country, including Bukalapak. Bukalapak is a marketplace that was founded by Ahmad Zaky in 2010. Consumer decisions in making purchases at Bukalapak are influenced by several factors, namely online customer reviews, promotions and e-trust. The purpose of this study was to analyze the influence of online customer reviews and promotions through e-trust on Bukalapak's purchasing decisions in Medan City. The type of this research is associative research and the population in this study is Bukalapak users in Medan City whose number is unknown. The sampling method used is accidental sampling. Data analysis was carried out through PLS-SEM using the SmartPLS program. The results show that online customer reviews, promotions and e-trust directly have a positive and significant impact on Bukalapak's purchasing decisions in Medan City. then indirectly online customer review has a positive and significant effect on purchasing decisions through e-trust and promotions through e-trust have a positive and significant impact on Bukalapak's purchasing decisions in Medan City. Keywords: Online Customer Review, Promotion, e-Trust, Purchase Decision.

Using Emotions in Usability

2007 ◽  
Vol 51 (17) ◽  
pp. 1044-1049 ◽  
Author(s):  
Roberto K. Champney ◽  
Kay M. Stanney
Keyword(s):  
Product Design ◽  
User Experience ◽  
Evaluation Criteria ◽  
User Interaction ◽  
Emotional Reactions ◽  
Usability Evaluation ◽  
Emotional Impact ◽  
Human System

Emotions are evermore present in discussions of product design and are becoming part of a usability practitioner's repertoire of evaluation criteria. Nonetheless, emotions in design are far more than simply using satisfaction and frustration as criteria, noting how pleasant or unpleasant a product is, or listing a number of emotions elicited during an evaluation. Evaluating the emotional impact of a user interaction as part of a usability evaluation requires that emotions be adequately assessed and, most importantly, interpreted to identify their source. This article aims to present a method and process of Emotional Profiling to show how emotions may be utilized to aid usability professionals in further understanding the emotional reactions to human-system interactions, thereby identifying factors that enhance or detract from the user experience.

scholarly journals Analisis komparatif online customer review dan survey customer review marketing mix

2020 ◽  
Vol 15 (3) ◽  
pp. 138-148
Author(s):  
Hilmy Mu’nis ◽  
Rita Komaladewi
Keyword(s):  
Marketing Mix ◽  
Culinary Tourism ◽  
Customer Reviews ◽  
Spider Web ◽  
Online Customer Reviews ◽  
Online Assessments ◽  
Survey Results ◽  
Online Tracking ◽  
Customer Review ◽  
The City

The purpose of this study is to compare between online customer review and customer review survey also to see the performance mapping of culinary tourism in Bandung using 4A marketing mix namely acceptability, affordability, accessibility and awareness with comparative and descriptive methods. This study uses Mann Whitney on SPSS and Spider Web Chart. Online tracking on Google Review and survey questionnaire are used as a measurement to get 100 customer review online assessments and 125 customer review survey assessments. Based on research results there is a difference between marketing mix 4A online customer results Google review and marketing mix 4A customer review survey results. This is marked from the 3 sub-variables used in this study, namely acceptability (taste, portion, aroma), affordability (price, price: taste, price: portion) and accessibility (atmosphere, cleanliness, service), there are differences in the results of the assessment in sub accessibility variable (atmosphere and service). Then, the results of mapping the performance of culinary tourism in the city of Bandung both online customer reviews and customer surveys have good performance for sub-variables acceptability (taste, portion, aroma) and affordability (price, price: taste, price: portion) but need improvement in the sub accessibility variables (suansana, cleanliness, service).

scholarly journals Definition of customer requirements in big data using word vectors and affinity propagation clustering

2021 ◽  
pp. 095440892110017
Author(s):  
Yanlin Shi ◽  
Qingjin Peng
Keyword(s):  
Big Data ◽  
Product Design ◽  
Affinity Propagation ◽  
Product Reviews ◽  
Customer Requirements ◽  
Parts Of Speech ◽  
Customer Reviews ◽  
Affinity Propagation Clustering ◽  
Online Customer Reviews ◽  
Definition Of

Customer requirements (CRs) have a significant impact on product design. The existing methods of defining CRs, such as customer surveys and expert evaluations, are time-consuming, inaccurate and subjective. This paper proposes an automatic CRs definition method based on online customer product reviews using the big data analysis. Word vectors are defined using a continuous bag of words (CBOW) model. Online customer reviews are searched by a crawling method and filtered by the parts of speech and frequency of words. Filtered words are then clustered into groups by an affinity propagation (AP) clustering method based on trained word vectors. Exemplars in each clustering group are finally used to define CRs. The proposed method is verified by case studies of defining CRs for product design. Results show that the proposed method has better performance to determine CRs compared to existing CRs definition methods.

scholarly journals Exploiting online customer reviews for product design

2020 ◽  
Vol 909 ◽  
pp. 012080
Author(s):  
Yanti Pasmawati ◽  
Alva Edy Tontowi ◽  
Budi Hartono ◽  
Titis Wijayanto
Keyword(s):  
Product Design ◽  
Customer Reviews ◽  
Online Customer Reviews

Study of E-Commerce Customer Review Capturing Process in the Indian Context

2022 ◽  
pp. 79-93
Author(s):  
Som Sekhar Bhattacharyya ◽  
Asmita Wani
Keyword(s):  
Research Work ◽  
Online Reviews ◽  
Point Of View ◽  
Online Review ◽  
Exploratory Research ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Customer Review ◽  
Depth Interviews ◽  
Potential Customers

Online customer reviews provided by customers on e-commerce sites who had bought the products proved to be a key parameter. New and potential customers at the pre-purchase stage to vet the merits and demerits before buying new products listed on e-commerce sites referred to online customer reviews. However, there have been very few studies that focused on online customer review capturing process. Thus, this research work focused on the review capturing process of e-commerce websites from a customer's point of view to understand the online customer review process. A qualitative exploratory research was carried out. An open-ended semi-structured questionnaire was used to understand customer's stand on the e-commerce review capturing process. In-depth interviews were collected from customers. The data was analyzed thematic content. The study findings indicated what motivated customers to write online reviews, what inhibited them from writing reviews and what were their suggestions for the managers of e-commerce organizations towards designing better online review capturing.

scholarly journals Automatic Identification of Product Usage Contexts from Online Customer Reviews

2019 ◽  
Vol 1 (1) ◽  
pp. 2507-2516
Author(s):  
Dedy Suryadi ◽  
Harrison Kim
Keyword(s):  
Product Design ◽  
Automatic Identification ◽  
Computing Power ◽  
Product Usage ◽  
Customer Reviews ◽  
Customer Preferences ◽  
Context Factors ◽  
Online Customer Reviews ◽  
Product Description ◽  
Usage Context

AbstractThere are three product design contexts that may significantly affect the design of a product and customer preferences towards product attributes, i.e. customer context, market context, and usage context factors. The conventional methods to gather product usage contexts may be costly and time consuming to conduct. As an alternative, this paper aims to automatically identify product usage contexts from publicly available online customer reviews. The proposed methodology consists of Preprocessing, Word Embedding, and Usage Context Clustering stages. The methodology is applied to identify usage contexts from laptop customer reviews, which results in 16 clusters of usage contexts. Furthermore, analyzing the review sentences explains the separation of “playing games” –which is more related to casual gaming, and “gaming rig” –which implies high computing power requirements. Finally, comparing customer review with manufacturer's product description may reveal a discrepancy to be investigated further by product designer, e.g. a customer suggests a laptop for basic use, although the manufacturer's description describes it for heavy use.

scholarly journals PENGARUH ONLINE CUSTOMER REVIEW DAN ONLINE CUSTOMER RATING TERHADAP KEPERCAYAAN KONSUMEN REMAJA KOTA MATARAM PADA PEMBELIAN PRODUK FASHION SHOPEE ONLINE SHOP

2019 ◽  
Vol 19 (1) ◽  
pp. 1
Author(s):  
Taesar Wahyudi
Keyword(s):  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Total Sample ◽  
Multiple Linear Regression Analysis ◽  
Survey Method ◽  
Analysis Tool ◽  
Customer Reviews ◽  
Online Customer Reviews ◽  
Customer Review ◽  
Customer Trust

This study aims to prove and analyze the effect of online customer reviews, online customer ratings on customer trust in online shopping at Shopee. This type of research is correlational research because this study aims to study the differences between two or more variables. The data collection method used is a survey method. The population in this study is the teenagers of the city of Mataram who bought 10-24 years who had bought fashion products online at Shopee. Purposive sampling technique, with a total sample of 120. The distribution of questionnaires using the form of goggles. The data analysis tool used is Multiple Linear Regression Analysis using the SPSS 22 program for Windows. The results of this study indicate that online customer reviews and online customer ratings have a significant positive effect on customer trust   Keywords : Online Customer Review, Online Customer Rating, Customer Trust.

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