Electronic Commerce Research最新文献

The consumer’s demand for certain products must be grown through frequent promotion. Also, maintaining the green level of the products can catch customers’ attention. The demand can be boosted by lowering the selling price per unit quantity. These essential issues should be considered while modelling the demand function for a production-retail scenario. The production of commodities cannot be error-free. A small part of the production may be imperfect, and the rate of the imperfect output must be increased as time forwards. The production cost increases as the advertisement frequency, maintenance of green level advances, and time forwards. The inventory carrying cost per unit product also hikes with time. This paper presents a comprehensive inventory optimization model, including the mentioned issues in its hypotheses. The result shows that the average profit is significantly sensitive to the selling price and production cost per unit. The resultant managerial insights after solving the proposed model are as follows. First, the average profit increases with the selling price hike and frequent advertisement. Second, the green level cannot increase average profit, though it causes surplus demand, because maintaining green levels of items incurs additional costs. Third, accumulating defective items during production diminishes average profit as the sellable products are lowered.

Despite the widespread adoption of electronic coupons as a promotion tool for attracting customers and increasing operating revenue, there are few empirical studies that focus on the impact of promotion design under smart retail circumstance. How do consumers handle dazzling coupon information? Which coupon distribution method best encourages consumers to redeem coupons? To answer those questions, we collected promotion data from 24 Chinese chain retailers for this paper and matched that design data to the corresponding retail performance data. Our unique data set allows us to reveal the relationship between promotion design and retail operating performance. Our analyses show that promotion depth and width both have significant positive effects on coupon redemption. Unlike quick response (QR) code coupons, location-based coupons, feed ad coupons and payment gift coupons all exert negative effects on coupon redemption. Among retailers, specialty stores have a lower coupon redemption ratio than supermarkets, while the coupon redemption ratio of convenience stores shows no difference from that of supermarkets. In addition, retailer reputation has a positive effect on coupon redemption. We also investigate the moderating effect of retail format and retailer reputation for further discussion.

Platforms play an essential role in the modern economy. At the same time, due to advances in artificial intelligence (AI), algorithms are becoming more widely used for pricing and other business functions. Previous literature examined algorithmic pricing, but not in the context of network effects and platforms. Moreover, platform competition literature has not considered how algorithms may affect competition. We study the performance of AI pricing algorithms (Q-learning and Particle Swarm Optimization) and naïve algorithms (price-matching) under platform competition. We find that algorithms set an optimal price structure that internalizes network effects. However, no algorithm is always the best because profitability depends on the type of competing algorithms and market characteristics, such as differentiation and network effects. Additionally, algorithms learn autonomously when an equilibrium is unstable and avoid it. When algorithm adoption is an endogenous strategic decision, several algorithms can be adopted in equilibrium; we characterize the conditions for the various outcomes and show that the equilibrium and platform profits are sensitive to algorithm design changes. Overall, our research suggests that AI algorithms can be effective in the presence of network effects, and platforms are likely to adopt a variety of algorithms. Lastly, we reflect on the business value of AI and identify opportunities for future research at the intersection of AI algorithms and platforms.

Abstract

The study’s main purpose is to examine the impact of cross-border e-commerce factors such as e-taxation, e-trade policy, distance, gross domestic product, international restriction, antidumping and countervailing duties on exports of goods and services. This study provides a new perspective on cross-border e-commerce activities in Belt and Road countries of Asia using panel data econometric methodologies from 2000 to 2022. It contributes to our understanding of the role of cross-border e-commerce factors in improving the exports of goods and services in the Belt and Road countries of Asia. The panel data is also analysed by CD, CIPS, FMOLS, DOLS, and PMG-ARDL tests. This research has significant theoretical implications. As Belts and road countries increase spending on digital infrastructure and push for more international trade, cross-border e-commerce will likely become an increasingly important factor in their economies’ growth and participation in the international community. However, as per the findings of this study, all the factors statistically significantly impact exports of goods and services. The success of the Belt and Road program largely depends on the expansion and improvement of cross-border e-commerce in the region.

Abstract

Despite the rapid advancement of online shopping, the challenge of asymmetric information, particularly within the realm of agricultural products, poses a hurdle to sustaining consistent customer engagement in e-commerce. Drawing upon governance theory and the cue congruence effect, the research aims to construct a comprehensive theoretical framework that encompasses platforms, providers, and customers. The primary objective is to empirically examine how platform governance can facilitate the presentation of valuable systems through signaling, review clues, and their significant moderating effects. Through an analysis of transaction data from China’s online rice market, employing both two-stage least square and three-stage least square models, the study reveals that robust signals and reputation can lead to increased prices and sales for high-quality products. Additionally, the study identifies the presence of congruence: prices appear to amplify the influence of signaling and reviews, while congruence between video displays and signals yields a negative impact. This research offers theoretical insights for future study and practical recommendations for policymakers and e-commence participants.

Currently, small and medium-sized enterprises (SMEs) have been the mainstay of technological innovation. Given the paucity of financial support, equity crowdfunding has become a popular way for SMEs to obtain project funds in recent years. Based on all successful crowdfunding projects on Seedrs, an equity crowdfunding platform, we delved into the impact of the content not displayed on project’s presentation page, particularly past fundraising experiences, on fundraising performance. Additionally, we empirically explored the influence of three dimensions, namely whether there was past fundraising experience, the number of past fundraising experience(s), and the amount of the last fundraising, on the fundraising ratio and the number of investors. The research results indicate that (1) the fundraising ratio is not significantly related to whether there was past fundraising experience and the number of past fundraising experience(s), but positively related to the amount of the last fundraising; (2) the number of investors is not significantly related to whether there was past fundraising experience, but positively related to the number of past fundraising experience(s) and negatively related to the amount of the last fundraising. Theoretically, we explored the relations between the information not displayed and fundraising performance from the perspective of past fundraising experience, supplementing and enriching the related research. Practically, we revealed the information searching behaviors of investors and guided the crowdfunding platforms in the information display.

This study empirically analyzes the impacts of e-commerce adoption by Chinese agri-food companies on their financial performance, with a nationwide dataset of Chinese agri-food companies. Results show that, on average, the adoption of e-commerce can significantly improve the financial performance of Chinese agri-food companies by 20%. The impacts of e-commerce adoption on financial performance are heterogeneous regarding enterprise scale, industry type, enterprise ownership, enterprise location, and enterprise maturity. In light of these findings, this study discusses the suggestions to encourage e-commerce adoption and improve the financial performance of companies from the perspectives of business operators and policymakers.

The proliferation of mobile devices has made mobile shopping extremely popular among the digital natives. Due to the multitasking nature of mobile devices, users are often disturbed by various interruptions, such as incoming calls, SMSs and APP notifications. Prior studies suggest that interruptions likely affect users’ shopping experience and decision-making, but they find inconclusive results regarding how interruptions influence users’ behavior. Based on the flow theory and prior research on human–computer interaction, this study focuses on the interplay between the design of interruptions and human–computer interaction mode, and examines the effects of interruptions on users’ decision efficiency in a mobile shopping context. Three laboratory experiments were conducted to verify the research hypotheses. The results show that interruptions improve users’ decision efficiency and satisfaction when their content is irrelevant to users’ shopping task. When the content of interruptions is relevant to users’ shopping task, the interruptions reduce users’ decision efficiency. Furthermore, the interruptions reduce (improve) users’ decision efficiency when users browsed the mobile interface in a horizontal (vertical) manner. In general, this study makes one of the early attempts to investigate the effects of interruptions on users’ mobile shopping behavior and provides practical guidance for practitioners to design effective mobile marketing campaigns.

Recently, global environmental and political changes have heightened the risk of supply chain disruptions. To bolster the risk resilience of the supply chain, this paper delves into its robustness structure using complex network theory. Firstly, a network of automotive suppliers is established to analyze its structural characteristics. Notably, the network degree distribution manifests a power-law distribution, highlighting an intricate interplay of mutual cooperation within cohesive communities. Subsequently, the paper performs simulation analyses under scenarios involving both random and deliberate attacks on the automotive supply chain network. The focus is on assessing the network efficiency, the size of the largest connected subgraph, and the variations in three distinct module structures. The results indicate that the automotive supply network exhibits good robustness under random attacks but relatively weak robustness under deliberate attacks. Additionally, a hub-like structure demonstrates significant robustness in the automotive supply chain network, showing optimal risk resistance even in the scenario of deliberate attacks. Therefore, when constructing network connections in the automotive supply chain, it is advisable to focus on establishing hub-like connections with upstream and downstream partners, while also preventing both internal and external risks of deliberate attacks, thereby enhancing the overall robustness of the entire supply chain network. These findings provide insights into risk mitigation in terms of network construction for automotive supply chain management and optimization.

FinTechs have gained an important place in the financial sector with their dynamic and customer-oriented structures and innovative approaches and business models. In recent years, the competition between actors in the financial sector has intensified. In a rapidly developing sector, where competition is intense and challenging, efficiency is a very important performance indicator for fintechs. This study aims to measure and examine the efficiency performance of FinTech companies. Data Envelopment Analysis was used for efficiency measurement. By establishing a two-stage data envelopment analysis model, "profitability", "marketability" and "overall process" efficiencies of fintechs were measured and analyzed. Efficiency of FinTechs operating in eight different sub-sectors was measured for the period of 2010–2019. The results show that, fintechs’ profitability efficiency performances are higher than their marketability efficiency performances. Besides, efficiency performance of the fintech companies differs on the basis of sub-sectors. This paper is a pioneer study in efficiency measurement of FinTechs.