scholarly journals Online shopping green product quality supervision strategy with consumer feedback and collusion behavior

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0229471 ◽  
Author(s):  
Hui He ◽  
Lilong Zhu
Keyword(s):  
Product Quality ◽  
Online Shopping ◽  
Green Product ◽  
Consumer Feedback

scholarly journals Green Product Quality Supervision Strategy in Online Shopping With Consumer Evaluation and Complaint

2021 ◽  
Vol 9 ◽  
Author(s):  
Hui He ◽  
Siyi Zhang ◽  
Lilong Zhu
Keyword(s):  
Product Quality ◽  
Online Shopping ◽  
Evolutionary Game ◽  
Third Party ◽  
Evolutionary Stable Strategy ◽  
Game Model ◽  
Green Product ◽  
High Quality ◽  
Stable Strategy ◽  
Strategy Combination

Green consumption is an important foundation for achieving stable and long-term economic development goals. With the rapid development of e-commerce and people’s widespread attention to sustainability, more and more consumers purchase green products online. Therefore, we consider consumer feedback mechanisms including evaluation and complaint and construct an evolutionary game model of green product quality supervision with the participation of governmental supervision department, third-party e-commerce platform, online seller and consumer, which analyzes the four parties’ evolutionary stable strategies. To verify the theoretical results, we conduct a numerical simulation by Matlab 2020b. Moreover, we study the conditions that make evolutionary stable strategy combination exist based on Lyapunov’s First Method. And we find that when consumer chooses complaint, (0, 0, 1) is likely to become an only evolutionary stable strategy combination. At this time, the online seller chooses to provide high-quality green product, third-party e-commerce platform chooses not to strengthen inspection, and governmental supervision department chooses to strictly supervise. Conversely, when the consumer chooses no complaint, (1, 0, 0) and (0, 0, 1) may become an evolutionary stable strategy combination. At this time, the online seller cannot be stable in providing high-quality green product. What’s more, governmental supervision department increases the penalty, which can incentivize a third-party e-commerce platform to strengthen inspection. Third-party e-commerce platform increases the reward and can promote online seller to provide high-quality green product. On the one hand, this paper enriches the theoretical basis of online shopping green product quality supervision. On the other hand, compared with existing literature, it extends the main body of the evolutionary game to four paries and broadens the application scope of the game model. In addition, it has put forward feasible suggestions for the government supervision department to strengthen the quality supervision, and provided decision-making support for the third-party e-commerce platform to assume the responsibility of quality inspection.

scholarly journals PENGARUH PERSEPSI KUALITAS PRODUK, PENGALAMAN BELANJA ONLINE, DAN AKSES INFORMASI TERHADAP NIAT BELI ULANG ( Studi Pada Pembelian Online Sepatu Sepak Bola Merek Specs Di Kota Denpasar)

2019 ◽  
Vol 8 (4) ◽  
pp. 2524
Author(s):  
Wayan Sudangga Aditya ◽  
Made Jatra
Keyword(s):  
Product Quality ◽  
Purchase Intention ◽  
Online Shopping ◽  
Product Information ◽  
Information Access ◽  
Repurchase Intention ◽  
Repurchase Intentions ◽  
Shopping Experience ◽  
Influence Perceptions ◽  
Positive Effect

This study aims to explain the influence perceptions of product quality, online shopping experience, and access to information on repurchase intentions. This research was conducted in Denpasar involving 100 respondents. To obtain data, this study used questionnaires, observation and interviews. Data analysis techniques used multiple linear regression. The results of this study state that product quality, online shopping experience, and information access have a significant positive effect on repurchase intention. Specs management should provide detailed information on each product, information that’s always updated, carefully re-examine the goods sent. that consumers are interested in repurchasing and not getting the wrong information. Keyword: perception of product quality, online shopping experience, infromation access, purchase intention

scholarly journals E-Commerce Product Classification using Lexical Based Hybrid Feature Extraction and SVM

2019 ◽  
Vol 9 (1) ◽  
pp. 1885-1891 ◽  
Keyword(s):  
Feature Extraction ◽  
Product Quality ◽  
Extraction Method ◽  
Online Shopping ◽  
Support Vector ◽  
Classification Methods ◽  
Feature Extraction Method ◽  
Product Classification ◽  
Hybrid Feature Extraction ◽  
Product Ratings

At present, online shopping has become a growing process, in which the profit statistics are posted by familiar ecommerce corporations like Amazon, Flipkart, Snapdeal, etc. However, this kind of online shopping unkindly omits the touch and feel of the products that can be used to estimate the product quality as the main factor while buying the commodities from the shops. The estimation of product quality is more significant during the purchasing of online products. Therefore, many opinion mining and sentiment classification methods were introduced to purchase the best products through online shopping. But, these classification methods haven’t attained the effective product classification with best reviews and ratings. In this paper, we propose a hybrid feature extraction method PCA (Principle Component Analysis) and t-SNE (t-Distributed Stochastic Neighbor Embedding ) with SVM (Support Vector Machine) using lexicon-based method to classify and separate the products from the large set of different products depending on their features, best product ratings and positive reviews. In this process, the online products will be isolated and listed according to their high positive reviews. The data preprocessing is applied to the dataset to get the data accuracy before the execution of feature extraction and classification. The dimensionality reduction and best visualization of large data set are executed by applying the PCA and t-SNE method. The sentiments are also been extracted by this hybrid feature extraction method to acquire the best neighboring product ratings. The polarity of words is discovered using a lexical based approach to extract positive reviews for obtaining the best products. Finally, the SVM is exploited to the classification of products. The performance of the proposed method is estimated with precision, recall, accuracy and complexity that can provide the entire accurateness of the system.

scholarly journals Perception Analysis of Online Shopping: A Case Study of amazon.com

2020 ◽  
Vol 8 (2) ◽  
pp. 53-60
Author(s):  
H Manjula Bai
Keyword(s):  
Product Quality ◽  
Cyber Security ◽  
Consumer Behaviour ◽  
Online Shopping ◽  
The Internet ◽  
Quality Service ◽  
Level Of Satisfaction ◽  
Digital Payments ◽  
Perception Analysis

This paper is designed to study the perception of the consumer about online shopping, to know the optimistic and pessimistic influence of online shopping on the consumers and to study the consumer behaviour towards online shopping. For the study, the researcher has selected 50 respondents who are familiar with Amazon. It particularly focused on the problems or the benefits availed from online shopping. A common problem faced by the customer while shopping online is quality service. The biggest problem while buying things online is that there is no guarantee of product quality, digital payments failure, unclear returns and guarantee policies, cyber security or more precisely the lack of it is a major problem on the internet today All levels of customers were surveyed by using a questionnaire, and the level of satisfaction or dissatisfaction from the online shopping was studied. Finally, the detail information about the benefits they had received was also considered. A small attempt has been made to understand the benefits of online shopping, and also the limitation of online shopping was studied concerning AMAZON. Finally, it attempts to offer suggestions to customers to educate much more about online shopping.

Evaluation of the product quality of the online shopping platform using t-spherical fuzzy preference relations

2021 ◽  
pp. 1-18
Author(s):  
Choonkil Park ◽  
Shahzaib Ashraf ◽  
Noor Rehman ◽  
Saleem Abdullah ◽  
Muhammad Aslam
Keyword(s):  
Decision Making ◽  
Product Quality ◽  
Fuzzy Sets ◽  
Online Shopping ◽  
Score Function ◽  
Decision Makers ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

As a generalization of Pythagorean fuzzy sets and picture fuzzy sets, spherical fuzzy sets provide decision makers more flexible space in expressing their opinions. Preference relations have received widespread acceptance as an efficient tool in representing decision makers’ preference over alternatives in the decision-making process. In this paper, some new preference relations are investigated based on the spherical fuzzy sets. Firstly, the deficiency of the existing operating laws is elaborated in detail and three cases are described to identify the accuracy of the proposed operating laws in the context of t-spherical fuzzy environment. Also, a novel score function is proposed to obtain the consistent value in ranking of the alternatives. The backbone of this research, t-spherical fuzzy preference relation, consistent t-spherical fuzzy preference relations, incomplete t-spherical fuzzy preference relations, consistent incomplete t-spherical fuzzy preference relations, and acceptable incomplete t-spherical fuzzy preference relations are established. Additionally, some ranking and selection algorithms are established using the proposed novel score function and preference relations to tackle the uncertainty in real-life decision-making problems. Finally, evaluation of the product quality of the online shopping platform problem is demonstrated to show the applicability and reliability of proposed technique.

scholarly journals PENGARUH GREEN PRODUCT QUALITY DAN GREEN PERCEIVED RISK TERHADAP GREEN CUSTOMER SATISFACTION SERTA GREEN CUSTOMER LOYALTY PADA KONSUMEN PERTAMAX/ PERTAMAX PLUS DI KOTA MATARAM

2015 ◽  
Vol 4 (1) ◽  
Author(s):  
Lalu Raditya P.R
Keyword(s):  
Data Analysis ◽  
Customer Satisfaction ◽  
Product Quality ◽  
Customer Loyalty ◽  
Perceived Risk ◽  
Survey Sampling ◽  
Green Product

This research is entitled “The Effect of Green Product Quality and Green PerceivedRisk on Green Customer Satisfaction and Green Customer Loyalty in the Consumerof Pertamax/Pertamax Plus in Mataram”. The background of this research were thefindings of previous researches and some other theories sating that Green ProductQuality, Green Perceived Risk, Green Customer Satisfaction, and Green CustomerLoyalty are inter-related to one another. This research was aimed at determining theeffect of Green Product Quality and Green Perceived Risk on Green CustomerSatisfaction and Green Customer Loyalty in the consumer of Pertamax/PertamaxPlus in Mataram. This research is an associative research. The method of datacollection is survey sampling where the samples were selected through accidentalsampling with 120 respondents. The data were collected through observation,interview, and questionnaire. The method of data analysis is structural equationmodelling analysis with AMOS program. The research showed that all hypothesis inthis research are supported. Thus, it could be concluded that the variables of GreenProduct Quality and Green Perceived Risk affect the Green Customer Loyalty eitherdirectly or indirectly through Green Customer Satisfaction. It is suggested thatPertamina improve the quality of Pertamax as the Green Product, as well as reducethe risk that the consumers of Pertamax may perceive in the environment, withintense communication and socialization.Keywords: Green Product Quality, Green Perceived Risk, Green Customer Satisfaction, GreenCustomer Loyalty, Green Product

FACTORS INFLUENCING CUSTOMER SATISFACTION OF ONLINE SHOPPING IN OMAN – YOUTH PERSPECTIVE

2018 ◽  
Vol 6 (2) ◽  
pp. 64-73 ◽  
Author(s):  
Noura Said Al-Jahwari ◽  
M. Firdouse Rahman Khan ◽  
Ghanya Khamies Al Kalbani ◽  
Shima Said Al Khansouri
Keyword(s):  
Customer Satisfaction ◽  
Product Quality ◽  
Online Shopping ◽  
Chi Square ◽  
Safety Assurance ◽  
Factors Influencing ◽  
Kolmogorov Smirnov ◽  
Chi Square Analysis ◽  
The Impact ◽  
Youth Perspective

Purpose: The objective of the study was to analyze the impact of online customer satisfaction through the product quality, application safety, delivery guarantee, and the offers through online shopping. Design/methodology/approach: For this research, the purposive sampling method was used to collect 120 samples through a questionnaire– from those who are performing online shopping in Oman especially the youth. SPSS was used to analyze the collected data. Chi-square analysis, ANOVA and Kolmogorov-Smirnov ranking analyses were carried out to conclude. Findings: The results of the empirical study reveal that the perceptions of the youth confirming the product quality & service guarantee influenced comfort and satisfaction to the online customers. The study also revealed that the service tangibility concerning the guaranteed package and delivery process along with the lowest price motivated them to go for online shopping repeatedly. Research Implications: The study illustrates through Quality Safety Assurance (QSA) model, the factors viz. Product Quality, Application Safety, Delivery Guarantee, and Offers should be focused to improve the online customer satisfaction, and the best-buy offers are the factors which need more attention to increase the Omani clientele. Social implications: The study throws light on the factors and their important role towards improving customer satisfaction during online shopping and the ways and means to augment the same. Originality/Value: Only a very few have examined the factors influencing thecustomers’ satisfaction of online shopping in Oman, and it is a first-hand study of its kind, and the results will be useful to the online marketers.

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