Electronic Commerce Research最新文献

Given the nascent understanding of user perceptions toward digital nudges in e-commerce, our study examines key factors: perceived usefulness, ease of use, trust, and privacy risks. Via an online experiment of 273 participants, we examined the influence of digital nudging interventions – social norms, defaults, and scarcity warnings – against a control group. Employing descriptive and inferential statistics, notable trust variations were found between default and scarcity warning groups versus controls. To assess these findings, we interviewed 11 information systems and psychology experts. This research enriches our understanding of digital nudges in e-commerce and provides design insights. Theoretical implications span from providing propositions in order to enhance user involvement, conducting narrative accompanying research, analyzing diverse time points of nudging. Practical implications focus on emphasizing to users their choice autonomy and the highlighting that defaults and scarcity warnings are designed to mitigate inherent heuristics and biases for combining nudging with boosting elements.

Abstract

Food delivery platforms increase their revenue by charging the restaurants a commission fee for using their service. This study aims to understand the restaurant’s behaviour when they face competition from other restaurants while in a contract with the food delivery platform. We compare the behaviour of the restaurant when they face no competition to their behaviour when there is competition. Specifically, we analyse the impact of competition on the commission rate and the marketing level. Both the online and offline demand for the restaurant is considered to be stochastic. We find that the platform benefits when the restaurants compete. Our study suggests the platform to decide the required marketing index for the restaurant based on their unserved online demand and commission fee, and the restaurants to fix the commission rate based on their unserved offline demand and the marketing index required to meet their capacity.

The primary task of urban managers is to build a digital, green, and intelligent urban grid. Based on the current situation of China’s digital city construction, combined with the experience of Internet of Things city construction at home and abroad, this paper proposes a digital city construction mode suitable for China’s current Internet of Things and sensor technology. On this basis, the main dimensions of the economic elements of the digital city are summarized and the system model of the digital city is constructed using the co-word analysis method. Finally, the economic model of the digital city system is analyzed with a case combined with the discussion of the digital city system theory. The experimental results show that the digital city-integrated public platform has achieved the goal of giving priority to information services, supplemented by data management services in the form of Web services. Urban economic cycle development has good usability.

Inspired by the diversity of content provision and the importance of traffic revenue in media market, this paper investigates the pricing and advertising decisions for a media platform considering traffic revenue under three content provision strategies: single paid-content-without-ads strategy, single free-content-with-ads strategy, and hybrid content strategy. The optimal solutions among different content provision strategies are compared and analyzed, thereby guiding the media platform and consumers in choosing the best content provision mode, while also providing some valuable insights for the media platform in its decision-making. In presence of traffic revenue, findings show that the hybrid content provision strategy can achieve a win–win situation for the media platform and consumers, in terms of platform profit, consumer surplus, and decision-making speed, whereas the single paid or free content provision strategy cannot achieve such a situation. We also surprisingly find that the media content with higher quality fails in creating more welfare for consumers, when the traffic revenue sensitivity coefficient and the free content’s quality discount factor are high. Numerical experiments verify the theoretical results. We also study two model extensions of endogenous content quality and platforms competition, and find that the major findings of the base model are robust.

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.