Method for product selection considering consumer’s expectations and online reviews

Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ming-Yang Li ◽  
Xiao-Jie Zhao ◽  
Lei Zhang ◽  
Xin Ye ◽  
Bo Li
Keyword(s):  
Value Function ◽  
New Product ◽  
Online Reviews ◽  
Analysis Method ◽  
Purchasing Decisions ◽  
Product Attributes ◽  
Product Selection ◽  
Content Type ◽  
Perceived Values ◽  
The Value Function

Purpose In recent years, the updating speed of products has been significantly accelerated, which not only provides diversified styles for consumers to select from but also makes consumers face selection problems sometimes. In addition, a large number of online reviews for products emerge on many e-commerce websites and influence consumers’ purchasing decisions. The purpose of this study is to propose a method for product selection considering consumer’s expectations and online reviews to support consumers’ purchasing decisions. Design/methodology/approach The product attributes are divided into two categories, i.e. demand attributes and word-of-mouth (WOM) attributes. For the demand attributes, for which the consumers can give specific quantified expectations, the value function of prospect theory is used to determine the consumer’s perceived values to the alternative products according to consumers’ expectations for these attributes and products’ specifications. For the WOM attributes, for which the consumers cannot give specific quantified expectations, the sentiment analysis method is used to identify the sentiment strengths for these attributes in the online reviews, and then the consumer’s perceived values to the alternative products are determined. On this basis, the product selection methods for single consumers and group consumers are given respectively. Findings Finally, taking the data of JD.com (https://www.jd.com/) as an example, the practicability and rationality of the method proposed in this paper is validated. Originality/value First, a new product selection problem considering consumer’s expectations and online reviews is extracted. Second, the product attributes are considered more comprehensively and are classified into two main categories. Third, the bounded rationality of the consumers in the decision-making process is described more reasonably. Fourth, the sentiment dictionaries for each WOM attribute are constructed and the algorithm step of identifying the sentiment strengths is designed, which can help to identify the sentiment strengths in the online reviews more accurately. Fifth, the situation that a group plans to purchase the same products and the members have inconsistent expectations for the product attributes is considered.

Mining numerical measure of consumers’ product evaluation expressed in words based on latent Dirichlet allocation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ziang Wang ◽  
Feng Yang
Keyword(s):  
Latent Dirichlet Allocation ◽  
Product Evaluation ◽  
Online Reviews ◽  
Product Evaluations ◽  
Product Attributes ◽  
Data Set ◽  
Content Type ◽  
Face To Face ◽  
Online Retailers ◽  
Dirichlet Allocation

Purpose It has always been a hot topic for online retailers to obtain consumers’ product evaluations from massive online reviews. In the process of online shopping, there is no face-to-face interaction between online retailers and customers. After collecting online reviews left by customers, online retailers are eager to acquire answers to some questions. For example, which product attributes will attract consumers? Or which step brings a better experience to consumers during the process of shopping? This paper aims to associate the latent Dirichlet allocation (LDA) model with the consumers’ attitude and provides a method to calculate the numerical measure of consumers’ product evaluation expressed in each word. Design/methodology/approach First, all possible pairs of reviews are organized as a document to build the corpus. After that, latent topics of the traditional LDA model noted as the standard LDA model, are separated into shared and differential topics. Then, the authors associate the model with consumers’ attitudes toward each review which is distinguished as positive review and non-positive review. The product evaluation reflected in consumers’ binary attitude is expanded to each word that appeared in the corpus. Finally, a variational optimization is introduced to calculate parameters mentioned in the expanded LDA model. Findings The experiment’s result illustrates that the LDA model in the research noted as an expanded LDA model, can successfully assign sufficient probability with words related to products attributes or consumers’ product evaluation. Compared with the standard LDA model, the expanded model intended to assign higher probability with words, which have a higher ranking within each topic. Besides, the expanded model also has higher precision on the prediction set, which shows that breaking down the topics into two categories fits better on the data set than the standard LDA model. The product evaluation of each word is calculated by the expanded model and depicted at the end of the experiment. Originality/value This research provides a new method to calculate consumers’ product evaluation from reviews in the level of words. Words may be used to describe product attributes or consumers’ experiences in reviews. Assigning words with numerical measures can analyze consumers’ products evaluation quantitatively. Besides, words are labeled themselves, they can also be ranked if a numerical measure is given. Online retailers can benefit from the result for label choosing, advertising or product recommendation.

A novel product recommendation model consolidating price, trust and online reviews

Kybernetes ◽  
2019 ◽  
Vol 48 (6) ◽  
pp. 1355-1372 ◽  
Author(s):  
Ying Huang ◽  
Nu-nu Wang ◽  
Hongyu Zhang ◽  
Jianqiang Wang
Keyword(s):  
Search Engines ◽  
Distance Measure ◽  
Fuzzy Theory ◽  
Online Reviews ◽  
Purchasing Decisions ◽  
Neutrosophic Sets ◽  
Content Type ◽  
Product Recommendation ◽  
Proposed Model

Purpose The purpose of this paper is to propose a model for product recommendation to improve the accuracy of recommendation based on the current search engines used in e-commerce platforms like Tmall.com. Design/methodology/approach First, the proposed model comprehensively considers price, trust and online reviews, which all represent critical factors in consumers’ purchasing decisions. Second, the model introduces the quantization methods for these criteria incorporating fuzzy theory. Third, the model uses a distance measure between two single valued neutrosophic sets based on the prioritized average operator to consolidate the influences of positive, neutral and negative comments. Finally, the model uses multi-criteria decision-making methods to integrate the influences of price, trust and online reviews on purchasing decisions to generate recommendations. Findings To demonstrate the feasibility and efficiency of the proposed model, a case study is conducted based on Tmall.com. The results of case study indicate that the recommendations of our model perform better than those of current search engines of Tmall.com. The proposed model can significantly improve the accuracy of product recommendations based on search engines. Originality/value The product recommendation method can meet the critical challenge from the search engines on e-commerce platforms. In addition, the proposed method could be used in practice to develop a new application for e-commerce platforms.

scholarly journals Users’ Sentiment Analysis of Shopping Websites Based on Online Reviews

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Xiaohong Wang ◽  
Shuang Dong
Keyword(s):  
Sentiment Analysis ◽  
Text Analysis ◽  
Online Shopping ◽  
Rapid Development ◽  
Online Reviews ◽  
Analysis Method ◽  
Purchasing Decisions ◽  
Emotional Words ◽  
Fine Grained ◽  
The Relationship

AbstractWith the rapid development of online shopping, how to explore the value of online reviews, so as to give full play to their role in potential users’ purchasing decisions. Based on text mining and quantitative analysis, this paper studies the sentiment analysis of online reviews on B2C shopping website. The main attributes of commodity or service are extracted based on the order of word frequency in the online reviews. Text analysis method is used to judge the relationship between attributes of commodity or service and its emotional words. The fine-grained sentimental polarity and intensity of attributes are identified to analyze users’ concerns and preferences. The research shows that users pay more attention to the configuration and after-sales service of mobile, and have a positive sentimental orientation to most of attributes, especially unlocking function, hand feeling attribute and logistics service; and have a neutral sentimental orientation towards the attributes of battery and memory, and a negative sentimental orientation towards the membrane of mobile phone. The results can provide a reference for consumers to make purchasing decisions, for enterprises to improve product quality, and for shopping platform to optimize service.

scholarly journals A Method of Product Selection Based on Online Reviews

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Xia Liang ◽  
Jie Guo ◽  
Yan Sun ◽  
Xiaoxiao Liu
Keyword(s):  
Sentiment Analysis ◽  
Rapid Development ◽  
Online Reviews ◽  
Product Attributes ◽  
Product Selection ◽  
Inverse Document Frequency ◽  
Roulette Wheel Selection ◽  
Document Frequency ◽  
Criteria Importance

With the rapid development of information technology and market economy, global e-commerce platform develops rapidly. Recently, online reviews are widely available on e-commerce platforms to express customers’ experience of products. When ranking alternative products based on online reviews, how to make full use of the information in online reviews to represent the sentiment analysis results of online reviews is an important prerequisite for decision analysis. To this end, we propose a method for measuring the time utility and support utility of online reviews. Then a method for representing the sentiment analysis results of online reviews in the form of linguistic distribution is proposed. In addition, in view of the attributes and their weights being unknown, we propose a method for extracting product attributes from online reviews by using the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm; and the objective weights of attributes are determined through the Criteria Importance through Intercriteria Correlation (CRITIC) method. Additionally, in order to highlight the differences between the alternatives, the roulette wheel selection algorithm is first used to randomly select product attributes. Then the alternative products can be ranked by the extended Multi-Attributive Border Approximation area Comparison (MABAC) method with mixed information. Finally, we illustrate the applicability of the proposed method through a case study of selecting a 5G mobile phone and simulation experiment.

An analytic network process approach for the election of green marketable products

2015 ◽  
Vol 22 (6) ◽  
pp. 994-1018 ◽  
Author(s):  
Ratapol Wudhikarn ◽  
Nopasit Chakpitak ◽  
Gilles Neubert
Keyword(s):  
Environmentally Friendly ◽  
New Product ◽  
Analytic Network Process ◽  
Green Product ◽  
Manufacturing Companies ◽  
Quality Cost ◽  
Product Selection ◽  
Content Type ◽  
Selection Processes ◽  
Network Process

Purpose – In this study, an optimal green product is selected from three newly developed ecological products and a non-environmentally friendly product. An analytic network process (ANP), used widely for multi-criteria decision making (MCDM), is applied to account for the tradeoff issues among the criteria (quality, cost and green issue) in the new green product selection processes. The paper aims to discuss these issues. Design/methodology/approach – This paper focuses on current social and consumer requirements. New product selection processes consider three major perspectives, i.e., quality, cost and environment, as criteria. The following two main methods are applied to respond to this multi-disciplinary issue: the eight quality dimensions proposed by Garvin are used to manage the quality issue, and a life cycle costing (LCC) method is applied for consideration of the cost and green issue. Therefore, the dependency issue among the criteria is considered, using a suitably selected method, the ANP method, and all the methods are applied to a real business, which produces roof tiles, for the delivery of a new optimal green product. Findings – An optimal environmentally friendly product does not overcome the existing toxic product of the focused company. The environmental performance is necessarily balanced by the quality and cost capabilities. Research limitations/implications – This paper focuses on the new product selection of roof tile products. The criteria or measuring indicators may be dissimilar, and cannot be applied to other products. Practical implications – The proposed approach can be applied to other manufacturing companies or services to allow decision makers to make better determinations for a comprehensive dependency problem. The managers can apply the proposed model to benchmark the considered products as well as to find the weaknesses of products. Originality/value – This method considers the relationship among quality, cost and environment for newly developed green products. The method produces better results than former MCDM studies which did not account for the dependency issue among the criteria.

Much too new to eat it? Customer value and its impact on consumer-product relationship in the context of novel food products

2017 ◽  
Vol 26 (6) ◽  
pp. 616-630 ◽  
Author(s):  
Toula Perrea ◽  
Athanasios Krystallis ◽  
Charlotte Engelgreen ◽  
Polymeros Chrysochou
Keyword(s):  
Customer Value ◽  
New Product ◽  
Consumer Attitudes ◽  
Product Evaluation ◽  
Consumer Product ◽  
Product Evaluations ◽  
Product Attributes ◽  
Content Type ◽  
Novel Food ◽  
Trade Offs

Purpose The paper aims to address the issue of how customer value is created in the context of novel food products and how customer value influences product evaluation. Design/methodology/approach The study proposes a model formed by a series of causal relations among value (i.e. functional, social, hedonic, altruistic values) and cost perceptions (i.e. price, effort, evaluation costs, performance and product safety), their trade-offs (i.e. overall customer value) and product evaluation outcomes (i.e. satisfaction, trust). Findings Despite doubts about certain search (information), credence (safety) and experience (taste) attributes, perceptions about product quality, likeability and ethical image predominantly formulate customer value, indicating novel products’ potential to be evaluated positively by consumers. Research limitations/implications The proposed model advances knowledge in the context of product innovation. Contrary to past research that focuses on consumer attitudes towards a manufacturing technology and individual technology-specific risks and benefits, the customer value approach refers to novel product-related consumer attitudes conceptualized as overall customer value; the latter results from product-related value-cost trade-offs, leading towards specific consumer–product evaluations. Practical implications The customer value approach refers to the value from the adoption of a new product that underlies a relevant set of product attributes (e.g. quality, image, sustainability, price, convenience, taste, safety, etc.) Focusing on product attributes that generate gain – loss perceptions impactful on consumer – product evaluations is highly relevant for product managers concerned with new product development. Originality/value The originality of this work lies in the successful contextualization and testing of an inclusive model that comprises both emotional and rational components, operational at the product level, to generate substantial insights on the widely unexplored interplay between consumer – perceived customer value and the generation of consumer – product evaluation outcomes.

Vote or not? How various information cues affect helpfulness voting of online reviews

2020 ◽  
Vol 44 (4) ◽  
pp. 787-803 ◽  
Author(s):  
Weihua Deng ◽  
Ming Yi ◽  
Yingying Lu
Keyword(s):  
Online Reviews ◽  
Word Count ◽  
Product Attributes ◽  
Information Process ◽  
Content Type ◽  
Information Cues ◽  
Cumulative Voting ◽  
Two Stages ◽  
Textual Content ◽  
Product Ratings

PurposeThe helpfulness vote is a type of aggregate user representation that, by measuring the quality of an online review based on certain criteria, can allow readers to find helpful reviews more quickly. Although widely applied in practice, the effectiveness of the voting mechanism is unsatisfactory. This paper uses the heuristic–systematic model and the theory of dynamics of reviews to shed light on the effect of various information cues (product ratings, word count and product attributes in the textual content of reviews) on online reviews’ aggregative voting process. It proposes a conceptual model of seven empirically tested hypotheses.Design/methodology/approachA dataset of user-generated online hotel reviews (n = 6,099) was automatically extracted from Ctrip.com. In order to measure the variable of product attributes as a systematic cue, the paper uses Chinese word segmentation, a part-of-speech tag and word frequency statistics to analyze online textual content. To verify the seven hypotheses, SPSS 17.0 was used to perform multiple linear regression.FindingsThe results show that the aggregative process of helpfulness voting can be divided into two stages, initial and cumulative voting, depending on whether voting is affected by the previous votes. Heuristic (product ratings, word count) and systematic cues (product attributes in the textual content) respectively exert a greater impact on the two stages. Furthermore, the interaction of heuristic and systematic cues plays an important role in both stages, with a stronger impact on the cumulative voting stage and a weaker one on the initial stage.Practical implicationsThis paper’s findings can be used to explore improvements to helpfulness voting by aligning it with an individual’s information process strategy, such as by providing more explicating heuristic cues, developing different methods of presenting relevant cues to promote the voting decision at different stages, and specifying the cognitive mechanisms when designing the functions and features of helpfulness voting.Originality/valueThis study explores the aggregative process of helpfulness votes, drawing on the study of the dynamics of online reviews for the first time. It also contributes to the understanding of the influence of various information cues on the process from an information process perspective.

Designing health promoting foods for the ageing population: a qualitative approach

2015 ◽  
Vol 117 (12) ◽  
pp. 3003-3023 ◽  
Author(s):  
Orla Collins ◽  
Joe Bogue
Keyword(s):  
Product Design ◽  
Tacit Knowledge ◽  
Food Industry ◽  
New Product ◽  
Knowledge Generation ◽  
Ageing Population ◽  
Product Attributes ◽  
Content Type ◽  
Design Attributes ◽  
Health Promoting

Purpose – The purpose of this paper is to gather stakeholder tacit knowledge to design new product concepts with optimal product attributes for new health promoting food products for the ageing population. Design/methodology/approach – This research employed a qualitative research method. A total of 16 in-depth interviews were carried out to identify key product design attributes. These attributes were used to design health promoting foods for the ageing population. Findings – Age-related conditions affect and alter the design of health promoting foods targeted at the ageing population. Providing the ageing consumer segment with access to health promoting foods facilitates positive ageing intervention. The integration of affordability and convenience elements into ageing food design attributes is important for product acceptance. The multi-level demands and heterogeneity of ageing consumers result in the need for a variety of nutritionally tailored food formats. A dairy-based beverage was considered to be the optimal product concept for the ageing population. Research limitations/implications – The inclusion of stakeholders from the food industry could result in levels of food industry bias. The sample size of stakeholders was limited to 16 participants. One interview guide was used throughout all interviews to ensure consistency levels. A more flexible instrument may have captured more specific stakeholder information. Practical implications – During the early stages of the new product development process, a market-oriented research methodology can help to optimise product design in terms of product attributes that drive consumer acceptance. Originality/value – This paper provides important insights into the significance of stakeholder tacit knowledge generation throughout the need identification stage of the NPD process. Specifically this paper provides stakeholder tacit knowledge on the optimal design of health promoting foods for the ageing population. This knowledge has the ability to provide market-oriented information on health promoting food concepts which can be valuable for food manufacturers to maximise NPD performance, create value and develop competitive advantage within their marketplace. Finally, design templates of health promoting foods for the ageing population are of high strategic importance to food manufacturers, governments, health professionals and medical professionals.

scholarly journals Asymmetric influence of corruption distance on FDI

2018 ◽  
Vol 25 (3) ◽  
pp. 845-858 ◽  
Author(s):  
Birgit Burböck ◽  
Anita Macek ◽  
Edith Podhovnik ◽  
Christian Zirgoi
Keyword(s):  
Loss Aversion ◽  
Value Function ◽  
Industrialized Countries ◽  
Content Type ◽  
Transparency International ◽  
Positive Performance ◽  
Asymmetric Impact ◽  
The Uk ◽  
The Value Function ◽  
Diminishing Sensitivity

Purpose The purpose of this paper is to measure the influence of corruption distance (CD) on foreign direct investment (FDI) with the characteristics of the value function from the Prospect Theory (PT) such as loss aversion and diminishing sensitivity. Design/methodology/approach Data are derived from Transparency International and the Organisation for Economic Co-operation and Development (OECD) and tested on the countries China, Germany, Italy, Japan, Korea, Russia, Spain and the UK and are analysed with a natural log (LN) regression model. Findings The findings indicate a negative asymmetric relationship for China, Germany, Korea, Spain and Russia. This means that negative performance on CD will not have greater impact on FDI outflows than positive performance on CD in the same country. Loss aversion, as well as diminishing sensitivity, as suggested by the PT, cannot be supported with the empirical results. Originality/value Its originality lies in contributing and extending knowledge on CD on FDI in several ways. First, it analyses the data of emerging and industrialized countries, namely, Russia, China, Germany, Italy, Japan, Korea, Spain and the UK. Second, a potential asymmetric impact is explained by the characteristics of the hypothetical value function of the PT. Third, it seeks empirical evidence by applying an econometric model developed to analyse the variables CD and FDI.

Determining manufacturing system changes based on new product specifications

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Casper Schou ◽  
Daniel Grud Hellerup Sørensen ◽  
Chen Li ◽  
Thomas Ditlev Brunø ◽  
Ole Madsen
Keyword(s):  
Product Development ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Solution Space ◽  
New Product ◽  
Academic Learning ◽  
Product Attributes ◽  
Time To Market ◽  
Content Type ◽  
Modelling Approach

Purpose The purpose of this paper is to investigate how necessary changes in a manufacturing system can be determined based on a new product specification. It proposes a formal modelling approach, enhancing the utilization of changeability of a manufacturing system given a set of changes in a product. Design/methodology/approach To develop the proposed modelling approach, a design science research method is used to iteratively frame an issue, develop a solution and evaluate it in a relevant environment. Evaluation is carried out through a case study. Findings A stepwise method is introduced, facilitating the creation of a model describing the relations between product characteristics within a product family and the changeability of a manufacturing system. Limitations of each manufacturing system module are evaluated to determine permittable changes in the product domain. This establishes clear relations between product attributes and manufacturing capabilities. Through this, users receive feedback on which parts of the manufacturing system must change, depending on changes in product attributes. Research limitations/implications Testing has been carried out in an academic learning factory setting. Products and processes are thus less complicated than an industrial setting. The system used for validation is highly modular by design. Practical implications The proposed approach could be used during product development, when determining characteristics and variety of new products, evaluating the consequences of changing the solution space. This implies a shorter time-to-market and lower product costs. Social implications Faster product development and shorter time-to-market would give manufacturers increased agility to track market needs, and ultimately lead to greater fulfilment of customer requirements. Originality/value The current body of literature focus on modelling either products or manufacturing systems. Little literature addresses both, but does not touch on identifying changes within parts of the manufacturing system, nor supports the high changeability proposed in this research.

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