E-commerce Supply Chain Research Articles

Logistics mode selection and information sharing in a cross-border e-commerce supply chain with competition

Selecting an appropriate logistics mode is crucial for overseas suppliers (OSs) who enter new markets through the cross-border e-commerce platform (CEP), but it is challenging because OSs are unfamiliar with the local markets. Thus motivated, we aim at a supply chain where an OS sells its product through a CEP that holds demand information advantages, and the OS faces competition from the domestic supplier (DS). By constructing a multi-stage game model, we study the OS's logistics mode selection between direct-mail and bonded-warehouse, which has different logistics costs and inventory risks. Moreover, the influence of the CEP's information sharing decision on the logistics mode selection is investigated. Our results show that with information sharing, the OS always selects the bonded-warehouse logistics mode; while without information sharing, the OS makes a choice between direct-mail and bonded-warehouse mode according to the tax rate and market fluctuation. Particularly, under a high tax rate, with the increase in market fluctuation, the uninformed OS not only needs to adjust the logistics mode choice but also change the inventory strategy. We also reveal that information sharing could lead to the OS changing the logistics mode from direct-mail to bonded-warehouse, and then cause fierce competition between the OS and DS. Therefore, sharing information does not always benefit the CEP. Under certain conditions, it is more beneficial for the OS to choose the direct-mail mode when the information is shared, as doing so can help chain members escape the prisoner's dilemma and thus lead to a “win-win-win” outcome.

E-Commerce Supply Chain Optimization with the MOORA Method and Certainty Factor

This study analyzes supply chain optimization on e-commerce platforms by applying the MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) and Certainty Factor methods. The aim of this research is to gain in-depth insights into the relative performance of e-commerce platforms in the context of predefined criteria and sub-criteria. The research methodology consists of six stages, including data collection, selection of criteria and sub-criteria, application of Certainty Factor, selection of case studies, relative analysis using MOORA, and certainty level analysis using Certainty Factor. The results of the analysis show that these two methods provide valuable insights regarding the performance of e-commerce platforms. The MOORA method provides a relatively strong rating, while the Certainty Factor provides an additional dimension by considering the level of certainty regarding the factors that affect performance. From a comparison of the results of the two methods, platforms such as Tokopedia.com and Shopee consistently rank well in both analyses. The implication of this research is that the e-commerce platform has greater development potential in supply chain optimization efforts. Overall, the integration of the MOORA and Certainty Factor methods has succeeded in providing more detailed and comprehensive insights into supply chain optimization on e-commerce platforms. This research provides guidance for stakeholders in making more informed and directed decisions regarding supply chain optimization strategies in e-commerce platforms

Profit Coordination and Optimization of Agricultural Product Brand Promotion Lead by Farmer Cooperative Organizations

In the e-commerce supply chain of agricultural products, there are three parties: farmer cooperative organizations, e-commerce platforms, and consumers. This study aims to investigate how to coordinate farmer cooperative organizations and e-commerce platforms to maximize the overall profits of the supply chains of agricultural products. Based on the Stackelberg game theory, this paper constructs a two-level supply chain decision-making model led by farmers’ cooperatives and followed by e-commerce platforms. It discusses two supply chain decision-making models (decentralized and centralized) with decision variables (selling price and promotion effort). The results show that the overall profit of the supply chain under centralized decision making is higher than the overall profit under decentralized decision making. In order to achieve the coordination of agricultural product sales price and brand promotion efforts and achieve win-win cooperation, this paper puts forward two coordination schemes: (1) coordinating revenue sharing, cost sharing, and wholesale price discounts and (2) coordinating the wholesale price. These two contract coordination schemes are verified by example analysis. Finally, the following strategies are recommended, including strengthening the investment in brand promotion and contract management.

Optimization of Digital Marketing Strategies for Agricultural Product Circulation in the E-commerce Supply Chain

Optimization of Digital Marketing Strategies for Agricultural Product Circulation in the E-commerce Supply Chain

Retracted: Risk Prevention of E-Commerce Supply Chain Financial Market Based on High-Performance Computing

Retracted: Risk Prevention of E-Commerce Supply Chain Financial Market Based on High-Performance Computing

Digital Marketing Strategies for E-commerce Supply Chain Risk Management Based on Big Data Analysis and Predictive Modeling

Digital Marketing Strategies for E-commerce Supply Chain Risk Management Based on Big Data Analysis and Predictive Modeling

Optimization of Cross-border E-commerce Supply Chain based on Fuzzy Control Algorithm in Digital Marketing

Optimization of Cross-border E-commerce Supply Chain based on Fuzzy Control Algorithm in Digital Marketing

Q-commerce or E-commerce? A systematic state of the art on comparative last-mile logistics greenhouse gas emissions literature review

PurposeThe purpose of this study is to systematically review available state-of-the-art literature on comparative studies on Quick Commerce (Q-commerce) and E-commerce and their greenhouse gas (GHG) emissions.Design/methodology/approachThe literature survey methodology is based on the funneling approach of Kitchenham (2004), where results are obtained according to inclusion and exclusion criteria. The literature review methodology used for this study covers the period from 2016 to 2022. The areas considered for the survey are operations, logistics and supply chain network design for the distribution of goods in e-business. After deciding on the criteria, a total of 140 articles were extracted from 9 journal articles that study e-commerce and environmental emissions.FindingsThe result of this study reveals that GHG emissions from both modes of shopping depend on various parameters such as speed of delivery, last-mile depot locations, logistics and vehicle efficiency, customers’ order patterns and average basket size. Furthermore, the findings also highlight the difference between Q-commerce and E-commerce supply chain networks.Research limitations/implicationsThis study only accounts for GHG emissions from logistics activities, but there are other sources of GHG emissions in the overall supply chain that are not taken into consideration. Supply chain/business analysts in Q-commerce companies might refer the findings from this study to measure GHG emissions from their operations.Originality/valueThis is the first study in the Q-commerce field that uses a structured approach to find relevant literature from the years 2016 to 2022 and focuses on GHG emission measurement.

Return freight strategies and selling formats in e-commerce supply chain: The perspective of consumer fairness concerns and online shopping returns

Returns and consumer fairness concerns put a huge pressure on manufacturers who sell their products online. The optimal selling format and return freight strategy become particularly important for manufacturers in an e-commerce supply chain. Therefore, we build game models for the following scenarios under different selling formats: the seller bearing the return freight costs or the return-freight insurance premiums, consumers buying insurance for themselves, and no one buying insurance. By comparing the optimal solutions of the game models under reselling and agency formats, several conclusions are derived. In the agency format, if the return-freight insurance premium is higher than a particular threshold, then the optimal strategy of the manufacturer is to decrease the selling price to encourage consumers to purchase the insurance, otherwise, the manufacturer should purchase the insurance. As the level of consumer fairness concerns and platform commission rates increase, the manufacturer should gradually move from the agency to reselling format. In the reselling format, if the return-freight insurance premium is lower than a particular threshold, then consumers will purchase insurance and this will make the platform more profitable, and conversely, the platform should bear the return freight costs.

The Risks and Countermeasures of Supply Chain Financing on E-Commerce Platforms

With the popularization of the Internet, e-commerce business has developed rapidly in recent years, and the scale of online transactions is growing day by day. In order to meet the funding needs of enterprises on the platform supply chain and assist the platform's development, e-commerce platform supply chain financing has become one of the important financing methods. But this model will inevitably face more dimensional risks, which will have an impact on financing efficiency. In order to minimize risks and ensure the smooth and efficient development of this model, this article explores the supply chain financing model of e-commerce platforms, and explores and summarizes the existing risks of e-commerce supply chain financing from multiple perspectives. And propose preventive measures from multiple dimensions to address risks. In order to provide reference for improving the supply chain financing of e-commerce platforms, provide more assistance for enterprise financing, and provide certain reference and inspiration for enterprises interested in developing such businesses.

Strategic selling agreement and information management under leakage in an e-commerce supply chain

Nowadays, numerous manufacturers sell products through both an online e-tailer and an offline retailer. The e-tailer can use its rich sales data to predict the demand information and thus has the information advantage. This study develops a game-theoretic model to study the e-tailer’s selling agreement selection and information sharing policy in this multi-channel supply chain. The reselling agreement is adopted by offline retailer, while the reselling or the agency selling agreement can be prepared by the online e-tailer. Our analysis shows that the e-tailer’s information sharing strategy are quite different under these two agreements. That is, the e-tailer has an incentive to share information with the manufacturer voluntarily in the agency selling agreement whereas sharing information hurts the e-tailer in the reselling agreement. Interestingly, under an agency selling agreement, information sharing can make the manufacturer, the offline retailer, and the e-tailer becomes better than the non-information sharing scenario (i.e., Pareto-improvement). However, the reselling e-tailer only shares information with the manufacturer by virtue of information sharing contracting and the all-win outcomes are achieved if the demand uncertainty is high and the competition between the e-tailer and retailer is moderate. Furthermore, the interaction between the large commission rate and the less demand uncertainty drive the e-tailer to adopt the agency selling agreement; otherwise, the reselling agreement is the best choice for the e-tailer. Finally, we demonstrate that, when the e-tailer shares information with the manufacturer, the competing offline retailer always becomes better off due to the information leakage effect.

Dynamic quality management of live streaming e-commerce supply chain considering streamer type

The study aims to analyze the impact of top streamers and ordinary streamers on the quality decision of live streaming e-commerce supply chains. A differential game model is constructed to explore the theoretical conditions for optimizing the trajectory of live streaming product quality under the two types of streamers. The research findings suggest that multiple factors influence the quality decision of the live-streaming supply chain and are not directly related to the streamer types. The level of supply chain quality decision in the situation of the top streamer is higher only when their influence is greater than a certain threshold. Revenue is a key factor that influences the quality improvement and product quality superiority of manufacturers, and only when the profit efficiency of manufacturers under the two types of streamers is higher than the threshold can the live streaming product quality trajectory be optimized over time. The study also identifies that the advantage of the quality decision of the ordinary streamer is in the initial period or when the commission rate of the top streamer is high. In such cases, the ordinary streamer should take the initiative to improve the quality inspection technology, reduce the quality inspection cost, and break the monopoly of the top streamer. However, when the top streamer is in the development period or its commission rate is low, it becomes a disadvantageous area for the quality decision of the ordinary streamer, and thus, a conservative strategy should be adopted. In conclusion, the study provides insights for live streaming e-commerce supply chains to make effective quality decisions under different streamer types and their characteristics.

Information sharing under agency selling in an e-commerce supply chain with competing OEMs

Information sharing under agency selling in an e-commerce supply chain with competing OEMs

Supply chain resource scheduling optimization of e-commerce enterprises in international trade based on mobile edge computing.

The cross-border e-commerce supply chain network (CBESCN) has extensive geographical coverage, trade barriers and complexity of cross-border logistics issues, which makes its construction and development face many challenges. This article focuses on solving the operation optimisation problem of CBESCN under the background of the Internet of Things. A genetic algorithm constructed and solved the resource scheduling model of the supply chain of e-commerce enterprises in international trade. In addition, the mobile edge computing (MEC) optimisation scheme based on partial computation unloading is involved. The initial offload ratio is set and supply chain resources are allocated, then the remaining computing resources are distributed according to the server's computing power. Finally, the offload is optimised according to the resource allocation. The experimental results show that time delay and cost adjustment strategies can improve the CBE supply chain's comprehensive ability. The supply chain optimisation scheme proposed in this article can effectively use supply chain resources according to the requirements of computing tasks to reduce the total delay of task execution and the consumption of node computing.

A Hybrid Modelling Framework for E-Commerce Supply Chain Simulation: Complex Adaptive Systems Perspective

A Hybrid Modelling Framework for E-Commerce Supply Chain Simulation: Complex Adaptive Systems Perspective

Pricing Decisions and Coordination in E-Commerce Supply Chain with Wholesale Price Contract Considering Focus Preferences

Decision makers’ behavioral preferences have always been important in coordinating the supply chain. Decision makers need to choose a partner wisely to increase the profitability of the entire supply chain, especially in the competitive e-commerce environment. In this paper, we examine a two-echelon e-commerce supply chain with one retailer and one supplier using the most popular wholesale price contract to facilitate collaboration. Traditional research has shown that the classical expectation model cannot coordinate the supply chain. We apply the focus theory of choice to describe the retailer’s behavior as a follower, and we examine the impact of the retailer’s pricing decisions on the supplier under different focus preferences and the coordination for the entire supply chain. The lower the parameter φ, which represents the degree of positivity, and the higher the parameter κ, which represents the level of confidence, the closer the profit of the whole supply chain is to the coordination result—both are visualized through numerical experiments and images. In the case of φ determination, the lower the κ, the better the supply chain coordination. The finding implies that the retailer may be able to coordinate the supply chain and produce better results than the expectation model when he or she makes choices using a positive evaluation system that includes both higher levels of optimism and lower levels of confidence. The findings of the FTC model can simultaneously offer a theoretical foundation for expanding collaboration among supply chain participants and management insights for decision makers to choose cooperation partners.

Geographical relevance-based multi-period optimization for e-commerce supply chain resilience strategies under disruption risks

With the fierce competition in e-commerce, e-tailers are required to rapid responses to a variety of customised orders with multiple frequencies and strict delivery times. The delay or insufficient supply caused by disruptions might result in lost sales during long-term processes. To address this problem, a two-stage stochastic programming model considering profits, consumer service level (CSL) as well as market priorities is developed to manage long-term disruptions. We analyse multi-period consumer transaction data and formulate geographical relevance (GR) to link each marketplace with historical data in related regions and then prioritise market segments. A GR-based two-stage stochastic programming with multi-period is proposed, which (1) considers both proactive mitigation decisions before disruption and reactive recovery plans after disruption; (2) collaborates three resilience strategies; (3) optimises the e-tailer's profits considering market priorities during long-term disruptions. Using a real case of Chinese e-commerce under the COVID-19 pandemic, it is illustrated (1) the applicability and performance of the proposed GR-based model for multi-period resilience optimisation improving both the CSL and the total profit; (2) the efficiency and robustness of the developed sequential particle swarm optimisation with social structures algorithm. The proposed method could optimise e-tailers' response strategies for managing long-term disruptions in practice.

Performance evaluation model of cross border e-commerce supply chain based on LMBP feedback neural network

Performance evaluation model of cross border e-commerce supply chain based on LMBP feedback neural network

Live streaming e-commerce supply chain decisions considering dominant streamer under agency selling and reselling formats

With the prevalence of live streaming e-commerce in the pandemic, brands and platforms cooperate with streamers to join this emerging e-commerce pattern. In the live streaming e-commerce supply chain composed of brand, third-party self-operated platform and streamers with different power, weak and dominant streamer, this paper investigates how the dominant streamer affects the supply chain decision-making under four scenarios composed of different selling formats and different power. Using a game-theoretic model, we find that the market demand can be enlarged by dominant streamer, and the dominant streamer tends to set lower price and lower marketing effort. Furthermore, the member who has the pricing power can obtain higher profit than the scenario in which they lose the power. And with the deeper of the degree of live streaming channel low price consensus among consumers, the streamers will invest more marketing effort as a compensation. Some managerial implications are showed in this paper.

Fabrizex: creating a technology platform for global supply chains

Subject area Supply Chain Management, Technology, Procurement, Supply Chain Finance Learning outcomes The key learning objectives are as follows: to gain critical insights into e-commerce supply chains of fashion garments; understand the importance of digitization to manage the risks due to supply chain disruptions; evaluate the role of digitization to improve supply chain performance; understand the importance of supply chain finance in maintaining a healthy buyer–supplier relationship; and appreciate the role of supply chain digitization to transform a regional supply chain into a global supply chain. Case overview/synopsis This case highlights the challenges faced by fashion garments industry due to fragmented nature of their supply chains, where the manufacturing base was in the east and most of the consumers in the west. Digitization can create a bridge to integrate these supply chains to drive out their inefficiency, fragility and vulnerability to disruptions. Complexity academic level The case could be discussed in 90 min of an Operations Management, Supply Chain Management and Technology Management class at MBA or Executive MBA level. Supplementary Material Teaching notes are available for educators only. Subject code CSS 9: Operations and Logistics.