Feng Li

Dr. Feng Li

orcid

Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 July 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
LZLi Zhou
Li Zhou
JWJingjing Wang
Jingjing Wang
FLFeng Li
Feng Li
YXYan Xu
Yan Xu
Jie ZhaoJie Zhao
Jie Zhao
Jiafu SuJiafu Su
Jiafu Su
In recent years, with the booming development of the B2C cross-border e-commerce industry, the supply chain of B2C cross-border e-commerce faces many potential risk factors, which must be prevented. To solve this problem, this paper studies the supply chain risk factors of B2C cross-border e-commerce and puts forward avoidance strategies. First, the fitness network model of a dual local world is constructed by combining the fitness model with the local world model. Then, the fitness network model of the dual local world is verified by the risk dynamics simulation model to fit the actual network situation. On this basis, the SIRS virus transmission model is constructed to simulate the risk transmission of the B2C cross-border e-commerce supply chain, and the evaluation index system of the supply chain risk immunity ability and external risk intensity are established according to the supply chain risk immunity ability and external risk intensity. AHP is used to calculate the factors that have the greatest influence on supply chain risk immunity and external risk intensity. The results show that: from the point of view of the enterprise’s own risk immunity, it is more necessary to ensure the stability of the company’s capital and to establish a perfect risk monitoring and coping mechanism to avoid risks. From the perspective of enterprise external risk intensity, the risk should be avoided from two aspects of transaction security and logistics.

7 February 2022 in Kybernetes
Verified
Journal Article
Closed access
Aijun LiuAijun Liu
Aijun Liu
YYYun Yang
Yun Yang
JMJie Miao
Jie Miao
ZLZengxian Li
Zengxian Li
LHLu Hui
Lu Hui
FLFeng Li
Feng Li
Purpose: The promotion of new energy vehicles (EVs) is an effective way to achieve low carbon emission reduction. This paper aims to investigate the optimal pricing of automotive supply chain members in the context of dual policy implementation while considering consumers' low-carbon preferences.Design/methodology/approach: This article takes manufacturers, retailers and consumers in a main three-level supply chain as the research object. Stackelberg game theory is used as the theoretical guidance. A game model in which the manufacturer is the leader and the retailer is the follower is established. The author also considered the impact of carbon tax policies, subsidy policies and consumer preferences on the results. Furthermore, the author investigates the optimal decision-making problem under the profit maximization model.Findings: Through model solving, it is found that the pricing of EVs is positively correlated with the unit price of carbon and the amount of subsidies. The following conclusions can be obtained by numerical analysis of each parameter. Changes in carbon prices have a greater impact on conventional gasoline vehicles. Based on the numerical analysis of parameter β, it is also found that when the government subsidizes consumers, supply chain members will increase their prices to obtain partial subsidies. Compared with retailers, low-carbon preferences have a greater impact on manufacturers.Research limitations/implications: The new energy automobile industry involves many policies, including tax cuts, tax exemptions and subsidies. The policy environment faced by the members of a supply chain is complex and diverse. Therefore, the analysis in this article is based only on partial policies.Originality/value: The authors innovatively combine the three factors of subsidy policy, carbon tax policy and consumer low-carbon preference, with research on the pricing of EVs. The influence of policy factors and consumer preferences on the pricing of EVs is studied.

21 June 2024 in Asia Pacific Journal of Marketing and Logistics
Verified
Journal Article
Closed access
JXJie Xiong
Jie Xiong
FLFeng Li
Feng Li
Purpose: The rapid development of e-commerce live streaming is inseparable from the important role of live-streamer. However, research exploring the impacts of live-streamers’ characteristics on customer engagement in different types of live streaming rooms remains limited. This study aims to examine the impacts of live-streamers’ characteristics (i.e. expertise, moral reputation, popularity, responsiveness) on consumer engagement in e-commerce live streaming, and verify whether there are differences in the impact of live-streamers’ characteristics on consumer experience for different types of live-streamers. Design/methodology/approach: Data were gathered from 266 Chinese adults who have experience watching e-commerce live streaming. Partial least squares techniques were used to verify the model. Findings: The results show that expertise, moral reputation, popularity, and responsiveness of live-streamers have positive impacts on consumer engagement through perceived trust and perceived pleasure. Moreover, through multi-group analysis, this study found that compared with enterprise live-streamers, the moral reputation of individual live-streamers exerts a stronger effect on consumers’ perceived trust, and the popularity of individual live-streamers exerts a stronger effect on consumers’ perceived pleasure. Compared with individual live-streamers, the responsiveness of enterprise live-streamers exerts a stronger effect on consumers’ perceived pleasure. Originality/value: This study contributes to e-commerce live streaming research by categorizing live-streamers into two types: individual live-streamers and enterprise live-streamers, and verifying the specific difference in the impacts of live-streamers’ characteristics on consumer experience for the two types of live-streamers.

25 August 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
FLFeng Li
Feng Li
WAWenjing Ai
Wenjing Ai
TJTianli Ju
Tianli Ju
With the gradual development of a capital city subcenter, numerous residents gradually move to the subcenter, increasing the demand for fresh food. Thus, an adequate supply of fresh food to the subcenter should be guaranteed, while reducing the logistics costs, maintaining the quality and quantity, complying with sustainable development, and cooperating with the city to complete the food basket logistics and distribution. Accordingly, we propose the optimization of logistics distribution paths for fresh products. After field research, we found that the main fresh product distribution point in the Beijing subcenter is the Baliqiao wholesale market, one of Beijing’s vegetable basket projects, and the main distribution targets are large- and medium-sized markets in the subcenter. We optimize a fresh food distribution path model using minimum total cost and carbon emissions as the objective function according to the layout of the subcenter, and the best path is determined using improved ant colony optimization. The optimization results provide a basis for fresh food distribution in the capital city subcenter. We use scientific methods to analyze the travel routes of vehicles transporting fresh products in the subcenter to obtain the best distribution path for logistics companies, aiming to reduce the waste of resources and pollution to the environment by reducing the overall distribution costs and carbon emissions. Therefore, this type of study can benefit logistics companies and the subcenter population while contributing to sustainable development.

Aijun LiuAijun Liu
Aijun Liu
TLTaoning Liu
Taoning Liu
XJXiaohui Ji
Xiaohui Ji
LHLu Hui
Lu Hui
FLFeng Li
Feng Li
With the concept of sustainability gaining popularity, low-carbon tourism has been widely considered. In this paper, a multicriteria group decision making (MCGDM) process based on an uncertain environment is proposed to study the evaluation problem of low-carbon scenic spots (LSSs). In order to minimize the influence of subjective and objective factors, the traditional Vlse Kriterjumska Optimizacija I Kompromisno Resenje (VIKOR) method is expanded, using the improved best and worst method (IBWM) and Bayes approximation method, based on Dempster-Shafer Theory (B-DST). First, in order to make the evaluation process more professional, a number of evaluation criteria are established as effective systems, followed by the use of triangular intuitionistic fuzzy numbers (TIFNs) to evaluate alternatives of LSSs. Next, according to the evaluation results, the weights of the criteria are determined by the IBWM method, and the weights of the expert panels (Eps) are determined by B-DST. Finally, a weighted averaging algorithm of TIFN is used to integrate the above results to expand the traditional VIKOR and obtain the optimal LSS. The applicability of this method is proven by example calculation. The main conclusions are as follows: tourist facilities and the eco-environment are the two most important factors influencing the choice of LSSs. Meanwhile, the roles of management and participant attitudes in LSS evaluations cannot be ignored.