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Jin Chen
School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China

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Journal article
Published: 21 July 2021 in Sustainability
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Small and medium enterprises (SMEs) play an important role in promoting the national economy and providing employment opportunities. E-commerce platforms may facilitate transactions between these enterprises. However, transactions on the e-commerce platform are non-face-to-face, strongly virtual, and variable, resulting in SMEs often facing moral hazards and opportunistic behaviors. Blockchain is a distributed ledger consisting of an encryption algorithm, consensus mechanism, and smart contracts, having the characteristics of authenticity, security, transparency, and unforgeability. Thus, the problems faced by SMEs can be resolved by combining e-commerce platforms and blockchain technology. In this study, we first provide a conceptual framework for blockchain-supported e-commerce platforms for SMEs. Second, based on this conceptual framework, we build a total business architecture. Finally, we propose three key applications to illustrate how the platform facilitates SMEs in solving financing and trading problems. This study provides significant guidance for the operation and management of blockchain-supported e-commerce platforms for these enterprises.

ACS Style

Ji Jiang; Jin Chen. Framework of Blockchain-Supported E-Commerce Platform for Small and Medium Enterprises. Sustainability 2021, 13, 8158 .

AMA Style

Ji Jiang, Jin Chen. Framework of Blockchain-Supported E-Commerce Platform for Small and Medium Enterprises. Sustainability. 2021; 13 (15):8158.

Chicago/Turabian Style

Ji Jiang; Jin Chen. 2021. "Framework of Blockchain-Supported E-Commerce Platform for Small and Medium Enterprises." Sustainability 13, no. 15: 8158.

Journal article
Published: 27 May 2021 in Sustainability
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As a disruptive tool, blockchain technology can eradicate the product-counterfeiting problem in supply chains. However, a blockchain-supported platform charges an operating fee to legitimate manufacturers and retailers for product traceability and authentication. In this study, we employ enterprise profit-driven analytical models using Stackelberg equilibrium theory and highlight the values of blockchain-supported e-commerce platforms in addressing the product-counterfeiting problem. To measure the actual benefits of blockchain technology, we compare the profits of all agents in two different supply chains, traditional and blockchain-supported. Results show that the application of blockchain technology is not always beneficial to manufacturers, retailers, and customers. However, when the manufacturing cost of a legitimate manufacturer is sufficiently high, the manufacturer generates more profits using blockchain technology. Further, for a price-sensitive market, a retailer tends to trade in a blockchain-supported e-commerce platform if the retailer’s qualification in the platform is lower than that in a traditional supply chain, and the manufacturing cost of the counterfeit manufacturer in the platform is higher than that in a traditional supply chain.

ACS Style

Ji Jiang; Jin Chen. Managing the Product-Counterfeiting Problem with a Blockchain-Supported E-Commerce Platform. Sustainability 2021, 13, 6016 .

AMA Style

Ji Jiang, Jin Chen. Managing the Product-Counterfeiting Problem with a Blockchain-Supported E-Commerce Platform. Sustainability. 2021; 13 (11):6016.

Chicago/Turabian Style

Ji Jiang; Jin Chen. 2021. "Managing the Product-Counterfeiting Problem with a Blockchain-Supported E-Commerce Platform." Sustainability 13, no. 11: 6016.

Journal article
Published: 09 September 2019 in Sustainability
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As a typical application of fintech, the robo-advisor has increasingly gained attention over the last decade. However, most research regarding the robo-advisor has focused on its development issues such as performance improvement and regulation, while limited research has paid attention to trust. This research extends the literature by investigating the trust influencing mechanism of robo-advisors by a mixed method approach. Specifically, we identified six salient trust influencing factors by qualitative interviews and proposed the research model based on trust transfer theory. This model was tested via a survey of 230 investors. Our study finds the significant influencing role of supervisory control and validates the relationships among trust influencing factors, trust in technologies, trust in vendor and trust in robo-advisor. Moreover, several differences between junior investors and senior investors are also found in our research. This study examines trust transfer theory in the new context of the robo-advisor and contributes to further development of this increasingly utilized service.

ACS Style

Xusen Cheng; Fei Guo; Jin Chen; Kejiang Li; Yihui Zhang; Peng Gao. Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach. Sustainability 2019, 11, 4917 .

AMA Style

Xusen Cheng, Fei Guo, Jin Chen, Kejiang Li, Yihui Zhang, Peng Gao. Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach. Sustainability. 2019; 11 (18):4917.

Chicago/Turabian Style

Xusen Cheng; Fei Guo; Jin Chen; Kejiang Li; Yihui Zhang; Peng Gao. 2019. "Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach." Sustainability 11, no. 18: 4917.

Journal article
Published: 01 April 2019 in Sustainability
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Predicted price-to-book value ratios (P/BV) are widely used for the valuation of listed common stocks. However, with the application of automated trading system (ATS), the existing indicators that are applied in the method are losing their effectiveness in the Chinese market. Combining qualitative research with the text mining method, this study explores and validates those ignored factors to improve the accuracy of the stock valuation. On the basis of the principal of the existing valuation method, we clarify the scope of the factors that affects the P/BV ratio prediction. Through semi-structured interviews that are designed with six first-level factors which are taken from the literature, we then excavate some second-level factors. After that, with three corpuses including samples form Sina.com.cn, Xueqiu.com, and CSDN.net, four first-level factors and thirteen second-level factors have been verified step by step through the Latent Dirichlet Allocation (LDA) model. In the process, two other new factors and three sub-factors are also found. Furthermore, based on the factor correlation that was found in a data analysis, a factor relationship model was built. The results can be used in a stock valuation in future work as the basis of the indicator system for the prediction of P/BV ratio.

ACS Style

Xusen Cheng; Danya Huang; Jin Chen; Xiangsong Meng; Chengyao Li. An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading. Sustainability 2019, 11, 1938 .

AMA Style

Xusen Cheng, Danya Huang, Jin Chen, Xiangsong Meng, Chengyao Li. An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading. Sustainability. 2019; 11 (7):1938.

Chicago/Turabian Style

Xusen Cheng; Danya Huang; Jin Chen; Xiangsong Meng; Chengyao Li. 2019. "An Investigation on Factors Affecting Stock Valuation Using Text Mining for Automated Trading." Sustainability 11, no. 7: 1938.