Commodity anti-counterfeiting decision in e-commerce trade based on machine learning and Internet of Things

Chin, Shih-Hsien; Lu, Chun-Wei; Ho, Ping-Tsan; Shiao, Yung-Fu; Wu, Tai

doi:10.1016/j.csi.2020.103504

Cited by 21 publications

(10 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This way is relatively balanced and is the most commonly used way at present, such as outsourcing of technology development department, outsourcing of hardware facilities (such as hosting) and outsourcing of electronic settlement business, etc. (Chin et al, 2021) 3 E-commerce enterprises pay attention to project management and operation and maintenance personnel training. In the implementation and development process of B2C blockchain transaction payment system, the internal team of enterprises pay attention to good project management to ensure quality and progress.…”

Section: The B2b Trading Mechanism Under the Blockchain Technologymentioning

confidence: 99%

Research on model mechanism of B2B transaction based on delivery means of blockchain

Zhou¹,

Zhou²,

Zhao³

2022

IJTPM

View full text Add to dashboard Cite

The security of customer information, business information and payment information pool is a problem in the process of transaction payment under traditional B2B e-commerce mode. To solve this security problem, a B2B e-commerce transaction payment mode based on block chain technology is constructed. This study integrates the technical characteristics of decentralisation in blockchain algorithm, point-to-point distributed computing network, distributed storage of data and security and credibility of data encryption into the system architecture of B2B e-commerce transaction payment, and explores the feasibility of blockchain payment model architecture from the perspective of demand and supply of system products, then a secure payment model mechanism based on blockchain technology is constructed, which provides an effective model architecture solution to solve the problems of payment security and information security in the traditional B2B e-commerce transaction payment system.

show abstract

Section: The B2b Trading Mechanism Under the Blockchain Technologymentioning

confidence: 99%

Research on model mechanism of B2B transaction based on delivery means of blockchain

Zhou¹,

Zhou²,

Zhao³

2022

IJTPM

View full text Add to dashboard Cite

show abstract

“…In response to the proliferation of counterfeit products in ecommerce markets, Meraviglia [18] considers an innovative product monitoring approach to combat counterfeiting by controlling the entire production and distribution chain. Chin et al [25] studied the decision problem of counterfeit goods in e-commerce transactions based on machine learning and IoT, and proposed anti-counterfeiting system ideas and methods from the perspectives of machine learning, IoT anti-counterfeiting sharing and anti-counterfeiting penalties. However, the traditional product anti-counterfeiting technology is difficult to realize the open and transparent information of production and sales chain, which leads to the product anti-counterfeiting cannot be truly realized [14], [40].…”

Section: B Blockchain Anti-counterfeiting Traceabilitymentioning

confidence: 99%

“…On the other hand, e-commerce platforms use their own advantages, based on a large number of consumer transactions and behavior data, based on data-driven analysis of marketing activities, consumer demographic insights, advertising precision targeting and other data marketing services across the chain, that is, data-driven marketing (DDM), can also stimulate demand [21], [22]. In addition, counterfeit products seriously harm the interests of brands and consumers [23], [24], [25], damage the reputation of the entire consumer market, and are not conducive to the sustainable development of the market, product anti-counterfeiting has been pushed to the forefront of the times [14], [26], and the blockchain anticounterfeiting traceability system was born [1], [27]. The product anti-counterfeiting traceability based on blockchain technology can realize the full traceability of products through the combination of its unique distributed ledger record characteristics and technologies such as Internet of Things [28], [29], including the information collection records of product sources, raw material source traceability, production and processing links, logistics information, anticounterfeiting authentication, etc., realizing one code for one thing [15].…”

Section: Introductionmentioning

confidence: 99%

Optimized Combination of e-commerce Platform Sales Model and Blockchain Anti-Counterfeit Traceability Service Strategy

Guo¹,

et al. 2021

IEEE Access

View full text Add to dashboard Cite

In the e-commerce market, many e-commerce platforms act as resellers when selling products, and act as agents when selling other products. In the sales process, e-commerce platforms can either build their own blockchain anti-counterfeit traceability platforms or cooperate with third-party blockchain anti-counterfeit traceability platforms. This will generate four scenarios: (a) reseller, building its own platform (RE); (b) reseller, cooperating with a third-party platform (RO); (c) agent, building its own platform (ME); (d) agent, cooperating with a third-party platform (MO). Therefore, this paper constructs a differential game model under four modes to explore the interaction between the choice of sales mode and the choice of anti-counterfeit traceability service strategy. The results show that suppliers' profits are influenced by various aspects. On the one hand, in small-scale markets, the situation in which suppliers can realize higher profits evolves from ME to RO as the wholesale price increases , and in large-scale markets, suppliers are more profitable in the ME mode. On the other hand, with the increase of market scale and the decrease of unit price of anti-counterfeit traceability service of third-party platform, the situation that suppliers can achieve higher profit evolves from RE to RO and then to RE. For e-commerce platform, selfbuilt platform is a better choice. In the small-scale market, as the market size increases, the cost performance of anti-counterfeit traceability service decreases, and the best choice for e-commerce platform evolves from resale to agency sales, and in the large-scale market, the best choice for e-commerce platform is resale.

show abstract

“…As an outcome, the system gives customers better recommendations and owners explanation of chosen products that was recommended. In addition, it is possible to prevent clients from fake and inferior goods with the help of machine learning algorithms (Chin et al, 2021). The conducted model may predict with a high accuracy customers' behavior and prevent the infringing sales.…”

Section: Previous Studies' Overviewmentioning

confidence: 99%

“…It is easy to build a community with this app and connect a team inside it. Also, it gives the company private cloud storage that is much bigger than other apps offer (BigML, 2021).…”

mentioning

confidence: 99%

Data Science and Marketing in E-Commerce Amid COVID-19 Pandemic

Fedirko¹,

Zatonatska²,

Wołowiec³

et al. 2021

ERSJ

View full text Add to dashboard Cite

Purpose:The objective of this study involves the determination of data-driven solutions needed to increase the usability of e-commerce systems and its profitability. Design/Methodology/Approach: In the research implementation process, logic generalization and induction to identify and analyze the most beneficial data science tools in e-commerce. deign of the study is to generalize existing approaches of data science usage in e-commerce, to develop practical recommendations to ensure the competitive advantages of e-commerce market participants and to estimate the cost of technical tools needed to launch the data science project in e-commerce. Findings: The results clearly demonstrate that in 2020 businesses that have e-commerce system were financially successful and in next 3 years online sales will increase rapidly. The simple analytics will not cover the demand of online business and it is needed to implement advanced data-driven decisions now. Practical Implications: The present research provides generalized knowledge on how to launch a data science project in e-commerce and how to choose the best programming and visualization app to ensure the profitability of a project. The scientific paper gives an instruction on the marketing contribution analysis, which is the tool of key importance for online marketplaces. Originality/Value: The main research value drawn from the study is to launch the datadriven models in e-commerce company it is needed to observe the real business need and available data, find the best programming and visualization tools. It was defined that the most beneficial data science solutions are demand forecasting, estimation of the marketing contribution, customers clustering, recommendation system and customers' attitude analysis. The main business need for each e-commerce company is to estimate the contribution of all marketing channels and advertisement formats separately. This issue may be easily handled with a regression modelling, which helps to understand a set of factors influencing sales.

show abstract

Commodity anti-counterfeiting decision in e-commerce trade based on machine learning and Internet of Things

Cited by 21 publications

References 8 publications

Research on model mechanism of B2B transaction based on delivery means of blockchain

Research on model mechanism of B2B transaction based on delivery means of blockchain

Optimized Combination of e-commerce Platform Sales Model and Blockchain Anti-Counterfeit Traceability Service Strategy

Data Science and Marketing in E-Commerce Amid COVID-19 Pandemic

Contact Info

Product

Resources

About