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We consider a platform which provides probabilistic forecasts to a customer using some algorithm. We introduce a concept of miscalibration, which measures the discrepancy between the forecast and the truth. We characterize the platform's optimal equilibrium when it incurs some cost for miscalibration, and show how this equilibrium depends on the miscalibration cost: when the miscalibration cost is low, the platform uses more distant forecasts and the customer is less responsive to the platform's forecast; when the miscalibration cost is high, the platform can achieve its commitment payoff in an equilibrium, and the only extensive-form rationalizable strategy of the platform is its strategy in the commitment solution. Our results show that miscalibration cost is a proxy for the degree of the platform's commitment power, and thus provide a microfoundation for the commitment solution.

This research evaluates e-commerce platforms (ECP) amid the COVID-19 pandemic and investigates the relationship between usability and user experience (UX) and e-commerce platforms performance (ECPP) by testing online customer's interactions with online retailers. Exploratory and confirmatory factor analyses assessed the research constructs' dimensions, dimensionality, validity, and composite reliability, while structural path analysis tested the hypothesized model relationships. The empirical results indicate that six usability dimensional attributes are strategically significant antecedents to UX and ECPP: navigation, information architecture, value of content, satisfaction, aesthetics, and consistency and functionality. An integrated framework of usability and UX is recommended for retailers running their businesses on digital platforms. This research investigates usability, UX, and ECPP through understanding digital marketing frameworks in e-commerce stores in the COVID-19 context, shedding light on the strategic role of usability attributes and how they affect UX digital performance.

In order to study whether e-commerce platforms carry out service cooperation after settlement in-depth, this paper focuses on service selection strategic analysis for agent channels on some self-operated e-commerce platforms settled in hybrid e-commerce platforms. We present multi-leader-follower models in two different scenarios with the platforms as leaders and the manufacturers as followers and give some numerical experiments to analyze the impacts of service selection strategies for self-operated platforms on all supply chain members. Our finding shows that if the service cost efficiency is moderate or low, the self-operated platform prefers to provide its service for the agent; otherwise, its selection mainly depends on the unit product service fee. In addition, fierce service competition and high unit service fee are unfavorable to all members, while high service cost efficiency may hurt both the platform and the manufacturer.

This paper focuses on the settlement selection strategic analysis for self-operated e-commerce platforms on hybrid e-commerce platforms under market competition. Taking factors such as the market share, price competition, commission, and customer loyalty into account, a multi-leader–follower game model with the platforms as leaders and the manufacturers as followers is established. Then, we solve the model with the help of some mathematical techniques and describe some numerical experiments to analyze settlement strategies for the self-operated platforms and their impact on other members in the network. The numerical results reveal the following revelations: a lower commission rate is more suitable for the self-operated platforms; once the commission rates are determined, the self-operated platforms prefer to settle in the hybrid platforms under lower medium price competition; when the price competition is fierce, as customer loyalty increases, the self-operated platforms should settle with a low market share; if the self-operated platforms settle in the hybrid platforms, then a higher price competition is advantageous for all members and can facilitate supply chain coordination.

We examine the interaction effects of linguistic style and verification of online reviews in terms of their valence on purchase intention for search and experiential products. We adopt the cue utilization framework to examine the interplay between the extrinsic cues of online reviews—content style (general versus specific), verified purchase (VP) badge (present versus absent), and valence (positive versus negative)—in two product categories—search product (tablet) and experiential product (trip package)—using an experimental design. The findings of the frequentist and Bayesian analyses show that valence supersedes other attributes’ impacts on purchase intention in both product categories. Variations in the content style of the reviews have minor influences on purchase intention. The presence of a VP badge on a review has a negligible influence on purchase intention across both product categories. Valence-content style and valence-VP badge interactions significantly affect purchase intention. Based on these findings, implications are discussed.

Online e-commerce platforms, such as Amazon and Taobao, connect thousands of sellers and consumers every day. In this work, we study how such platforms should rank products displayed to consumers and utilize the top and most salient slots. We present a model that considers consumers’ search costs and the externalities sellers impose on each other. This model allows us to study a multiobjective optimization, whose objective includes consumer and seller surplus as well as the sales revenue, and derive the optimal ranking decision. In addition, we propose a surplus-ordered ranking mechanism for selling some of the top slots. This mechanism is motivated in part by Amazon’s sponsored search program. We show that the Vickrey–Clarke–Groves mechanism would not be applicable to our setting and propose a new mechanism. This mechanism is near optimal, performing significantly better than those that do not incentivize sellers to reveal their private information regarding each consumer purchase, such as their profit. Moreover, we generalize our model to settings in which platforms can provide partial information about the products and facilitate the consumer search and show the robustness of our findings. This paper was accepted by David Simchi-Levi, operations management.

Seller marketing capability and brand reputation are central to firm performance and customer behaviors. However, little is known about how these two dimensions matter in the increasingly important domain of e-commerce platforms, where sellers are diverse and brand reputations are challenged. This research examines the effects of marketing capability and brand reputation on key customer purchase journey outcomes on e-commerce platforms, from click to browsing time, purchase, and post-purchase frustration. Using smartphone category data from a leading e-commerce platform, the authors demonstrate the positive and increasing effect of marketing capability on consumer journey outcomes. This research also paints a more nuanced view of brand reputation in e-commerce platform environments and illustrates nuanced U-shaped effects of brand reputation on consumer journey outcomes. These findings provide implications for brands and sellers on e-commerce platforms.

PurposeFood and beverage (F&B) small and medium-sized enterprises (SMEs) must diversify their markets and obtain predictable sources of revenues to withstand difficult and volatile periods such as the post-pandemic geopolitical scenario, recently burdened by the Russian-Ukrainian conflict. On the other hand, another strand of the literature suggests that public procurement could be considered a great source of income, enabling solid contracts, revenues and cash-flow stability. Therefore, this paper aims to explore the role of public procurement, the adoption of e-commerce platforms and their interactions in affecting the exporting performances of SMEs operating in the F&B sector.Design/methodology/approachThe study retrieves data from 2,186 Italian F&B manufacturing SMEs relying on Margò by Cribis database. Therefore, it conducts a structured equational model (SEM) to test the developed hypotheses empirically.FindingsThe findings reveal that digital selling platforms positively affect exports, whereas public procurement negatively affects F&B SMEs exports. Nonetheless, findings underline that the interaction between public procurement and the adoption of digital selling platforms dampens public procurement's negative effects on exports.Originality/valueThis study brings an original contribution to the F&B literature by conducting empirical research on an extensive sample of firms from one of the most influential countries in the F&B vertical, Italy, with officially registered data. More importantly, to the best of the authors' knowledge, this study pioneers the investigation of the relationship between public procurement and e-commerce platforms in affecting F&B SMEs' export performances.

Small and medium-sized businesses (SMEs) are frequently exposed to a variety of difficulties during global epidemic crises like coronavirus (COVID-19), which may even threaten their lives. The purpose of this study explores the influencing factors of Taiwan’s companies between small and medium-sized enterprises and micro-enterprises on the choice of the cross-border e-commerce platform. The findings are defined as taking into account small and medium-sized businesses and microenterprises when choosing cross-border e-commerce through a literature review and an examination of secondary data among the 10 participating businesses through interviews in various regions and business sectors in Taiwan. In this case we used study-based research, which included five small, medium-sized, and micro-enterprises, as well as five cross-border e-commerce projects and the company’s management senior officers. According to the study’s emphasis on the economic, social, technological, and legal aspects of various firms, these factors lead to a variety of decisions regarding the best cross-border e-commerce platform. The case study approach was utilized in this investigation to confirm the consideration of micro-and small-sized businesses that took part in cross-border e-commerce project counseling. This study summarizes five types of enterprises with different capabilities: product enhancement, marketing enhancement, cross-border potential, knowledge-based enhancement, and cross-border start-up. According to the results, it was found that different enterprise capabilities will affect the choice of cross-border e-commerce platforms. These five capabilities also have different types of consideration factors; among them, SMEs pay attention to marketing, pricing, market analysis, culture, customer service, payment, logistics, certification, taxation, etc. In addition to theoretical implications, this research also gives small and medium enterprises and micro-enterprises practice when choosing cross-border e-commerce platform, as well as suggestions for future research.

Based on the intelligent big data method and the cross-border e-commerce logistics service system as the research object, the paper constructs a cross-border e-commerce logistics service system based on mobile Internet. According to the user’s preference, the products matching the user’s preference are obtained through association rule mining, and recommended to the user. The research shows that the digital cross-border e-commerce platform system involved in the paper has good compatibility, and the user preference recommendation algorithm involved in the paper has high accuracy, which meets the needs of users.