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The model of pay-for-knowledge incentivizes individuals with financial rewards for sharing their expertise, facilitating a transactional exchange between knowledge providers (sellers) and seekers (buyers). While this model is effective in promoting paid contributions, its influence on free knowledge exchanges remains ambiguous, creating uncertainty about its overall impact on platform knowledge ecosystems. This study aims to explore the mechanim of how knowledge payment influences free knowledge contribution. Based on relational signaling theory, this study posits that a buyer’s payment for knowledge acts as a positive relational signal in the buyer–seller relationship and examines how the signaling effect varies across different social contexts through attribution theory.

This paper empirically tests the hypotheses by analyzing a data set comprising 630 instances from 359 unique knowledge sellers on Zhihu, a prominent knowledge-sharing platform in China. This paper use zero-inflated negative binomial models to conduct this analysis.

The findings reveal that when buyers pay for knowledge, this action positively influences sellers to contribute knowledge for free. However, the strength of this influence is moderated by the platform’s social functions: appreciation feedback tends to weaken this effect, while social network ties enhance it.

Prior research has predominantly focused on the financial incentives of pay-for-knowledge and its spillover effects on unpaid users’ activities. This study shifts the focus to the social dimensions of pay-for-knowledge, arguing that buyer-initiated knowledge payments signal buyers’ commitment to foster reciprocal relationships with sellers. It expands the literature on the relationship between knowledge payment and contribution, moving beyond financial incentives to include social factors, thus enriching our understanding of the interplay between paid and free knowledge activities. Additionally, the empirical evidence supports the efficacy of pay-for-knowledge in promoting both free and paid contributions within knowledge-sharing platforms.

Drawing on the principal-agent theoretical perspective, we assert that sellers’ opportunism is acknowledged as an essential component that could determine the quality of the relationship between buyers (principals) and sellers (agents). The primary aim of this research is to investigate the influence of seller behavior vs outcome-based reputation and seller’s perceived freedom on opportunistic behavior in the Chinese e-commerce platform context.

The data collected from 436 e-commerce platform sellers were analyzed and interpreted using structural equation modeling.

The results indicate that both behavior-based and outcome-based reputations positively impact sellers’ perceived freedom but negatively impact their opportunism. Additionally, while perceived freedom of objectives reduces opportunism, freedom of action increases it. The study also highlights the significant moderating roles of prevention mechanisms and ethical ideology.

This study extends the principal-agent perspective by integrating the seller’s reputation as a potential source of preventing sellers from behaving opportunistically on e-commerce platforms.

The integration of e-commerce platforms and artificial intelligence (AI) into the marketing channel ecosystem is challenging the explanatory capacity of traditional channel power theories, indicating a significant yet unaddressed research gap concerning the impact of these digital entities and AI on channel power exercise dynamics. This study adopts a contingency perspective to critically revisit how e-commerce platforms exercise channel power and the ensuing effects on channel conflicts. The purpose of this study is to extend the boundaries of traditional channel power theories, enhancing their relevance in today’s digital marketplace.

Building on channel power theories, the authors developed a framework tested with survey data collected from 262 sellers. This framework incorporates three key contingent variables: inter-platform competition, AI capabilities and platform value co-creation. Regression analysis was used to perform the analyses.

This study finds that intense inter-platform competition mitigates the (positive) negative relationship between platform channel power and the exercise of (non-) coercive power. Moreover, a platform’s AI capabilities and value co-creation activities diminish the potential for channel conflicts induced by the exercise of coercive power. AI capabilities can also strengthen the negative relationship between the exercise of non-coercive power and channel conflicts.

This study contributes to the advancement of traditional channel power theories by integrating contemporary digital elements like AI and platform dynamics. This study provides theoretical and practical insights on navigating channel power in modern marketing environments, offering strategic guidelines for optimizing channel relationships.

In social marketplaces, follower ego networks are integral social capital assets for online sellers. While previous research has underscored the positive impact of the follower number on seller performance, little attention has been given to the structure of follower networks and their value implications. This research investigates two structural properties of follower networks—network centralization and density—and examines their main and contingent effects on sellers’ sales performance.

A 13-month panel dataset of 1,150 sellers in Etsy, a social marketplace for handmade and vintage products, was collected and analyzed. A fixed effects model was adopted to validate the hypotheses on the main effect of centralization and density, as well as the moderating effects of two store attributes: store age and product diversification.

We find that both network centralization and density negatively impact sellers’ sales performance, and these effects vary across store age and product diversification levels. Specifically, the negative effect of network centralization is less pronounced for older stores than young ones, whereas the negative effect of density is more severe for stores with high product diversification.

This research contributes to social commerce research by highlighting the significance of network structure, alongside network size, in assessing the value of followers and offers practical guidance for sellers in social marketplaces seeking to optimize their follower networks.

In response to the intense competition in the platform economy, e-commerce platforms are actively introducing value-added services to maintain their competitiveness. However, how effective these value-added services are in fulfilling this purpose remains unclear. This paper explores how value-added services can enhance e-commerce platform competitiveness, measured by both user scale and reputation, considering the effect of network externalities.

A bilateral e-commerce platform with potential high-quality sellers and low-quality sellers on one side and potential buyers on the other side was chosen as research setting. Game theory models are constructed to simultaneously consider the behaviors of all actors (including sellers, buyers and the platform).

On the one hand, to increase the seller scale, basic services play a substituting role in determining the effect of value-added services. On the other hand, to increase the buyer scale and improve platform reputation, basic services play a fundamental role in determining the effect of value-added services. Furthermore, the higher the loss rate of the product value, the bigger the room for providing value-added services. With increasing loss rate of the product value, participating buyers who are attracted by value-added services are the fastest growing indicators; this indicates that the most significant effect of value-added services is its increase in the buyer scale.

Basic services determine the lower limit of platform competitiveness, while value-added services set the upper limit. The results of this paper can instruct different types of platforms to enhance their competitiveness in different ways.

(1) While previous studies on how to enhance platform competitiveness only considered scale or reputation separately, this paper applies a new perspective of platform competitiveness, namely the improvement of both the seller scale/buyer scale and platform reputation. (2) According to the characteristics of bilateral platforms, game theory models are constructed to explore how value-added services can enhance platform competitiveness considering both positive and negative network externalities. (3) The existing literature studies basic services and value-added services in a fragmented state; this paper contributes to research on value-added services by considering the mutual effect between basic and value-added services.

This study examines the inverted U-shaped relationship between a live-streaming seller’s disclosure of two-sided product information and consumers’ trust in the seller and product. It also explores the interaction between these two types of information disclosure and their impact on purchase intention in the live-streaming sales context.

An e-questionnaire survey was conducted in China, followed by multiple regression and structural equation modeling analyses.

The disclosure of both negative and positive product information is positively correlated with consumers’ trust in the seller or product but does not directly affect their purchase intention. Negative information disclosure neither enhances nor diminishes the positive impact of disclosing positive information on consumer trust.

Live-streaming sellers (i.e. retailers or manufacturers) should disclose both positive and negative product information to form consumers’ trust toward them (or products) and enhance sales.

Live-streaming sellers often worry about the negative effects of excessive promotions or disclosure of positive or negative product information. However, these negative effects were not statistically significant.

Since some researchers have found nonlinear effects of two-sided product information in other contexts, this study is the first to focus on the impact of live-streaming sellers’ disclosure of two-sided product information on consumers’ trust in the live-streaming sales context rather than on the information per se.

In online exchange platforms' sponsored search advertising, the array of product quality signals within a keyword search results list plays a crucial role in shaping buyers' purchasing decisions. This research seeks to explore the impact of various quality signals – namely, ranking position, seller reputation and product price – on ad clicks. Additionally, it examines the role of keyword attributes, such as specificity and popularity, in modulating the effects of these quality signals on advertising clicks.

A total of 5,763 effective data points were collected from a leading B2B electronic platform company, and we employed negative binomial regression with Heckman correction methods to test the hypotheses.

The results indicate that in online exchange platforms, search ad clicks are significantly and positively affected by displayed signals such as ranking position, seller reputation and product price information. Notably, a U-shaped relationship emerges between product price and ad clicks. Furthermore, keyword specificity and popularity distinctly moderate the impact of these displayed signals on ad clicks within online exchange platforms.

This paper addresses the gap in existing research on search advertising by methodically analyzing the impact of various signals displayed in search results and how keyword attributes moderate ad clicks, all through a signaling theory lens.

Although African markets have incorporated various selling practices originating from the West, there are still some selling practices that are indigenous to the African people and are widely practised by sellers across the continent. This chapter is an attempt at documenting those indigenous practices with the aim of providing managers, educators and policymakers of the continent with a reference document on what these indigenous selling practices are, how sellers invoke them in the course of transactions and the cultural values that guide these practices. Primary data were gathered from three countries representing western, eastern and southern Africa through observations, field surveys and in-depth and key informant interviews while literature was sourced for secondary data. The chapter identified street selling, haggling and credit-based selling as the major indigenous selling practices found among sellers in Africa. The cultural values that guide selling in the continent include respect, trustworthiness and kindness. The chapter displayed a framework to explain the subject matter and made some practical suggestions that are relevant for managers, educators and policymakers.

This paper studies product adoption as modeled by Katz and Shapiro (1986) in an experimental setting. Two sellers offer competing, incompatible technologies and two groups of buyers make purchase decisions sequentially in a two-stage game of complete information. Value to a buyer from purchasing a technology depends on the total number of buyers of that technology (installed base). There is mixed evidence that the results are qualitatively consistent with equilibrium predictions laid out in theory. Buyers of technology display behavior close to equilibrium predictions. However, the sellers in the laboratory do not exploit their installed bases significantly.

For two-sided platforms, the utility of users on one side of the platform depends in part on the number of users on the other side of the platform, a phenomenon called indirect network externalities. With the rapid development of two-sided platform and the popularity of platform membership, more and more two-sided platforms have launched joint membership through horizontal cooperation in order to take advantage of indirect network externalities to increase platform profits.

Our study explores the optimal bundling strategy for platform memberships under horizontal cooperation considering indirect network externalities. The main purpose of our study is to obtain the optimal pricing under different strategies (pure component, pure bundling, and mixed bundling) and contrast different strategies under different indirect network externalities.

Results suggest that the platform's optimal pricing for consumers and sellers depends on the indirect network externalities. Interestingly, the higher the indirect network externalities from consumers, the higher the price of the platform charges to sellers, and the platform might even subsidize sellers. Besides, when there are equal proportions of different types of consumers in the market, indirect network externalities that are too high, too low, or heavily lopsided may discourage the platforms from bundling their memberships. When the composition of consumers changes, the optimal strategy will also change. Our results can be employed in practical applications of bundling, which can help the platform increase profits.