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The purpose of this paper is to analyze the optimal competition or cooperation decision between technology service platforms and governments in the context of fierce competition within urban agglomerations.

Based on the cooperation and competition game model, this study builds a two-level model for government and technology service platforms considering three cases: perfect competition, platform cooperation and government-led cooperation.

By analyzing the optimal strategies of the government and a platform in three cases, the research shows that choosing appropriate cooperation in a competitive situation is beneficial to both the government and the platform. Government-led cooperation is conducive to increasing social welfare. From the perspective of the platforms, if they actively seek cooperation, they can obtain higher subsidies and profits. The more intense the competition is, the higher the profits and social welfare generated from the platforms' active cooperation.

The contribution of this study relates to the development of technology service platforms in urban agglomerations. As local governments and platforms continuously undertake decision-making processes, this study constructs quantitative models to analyze the advantages and disadvantages of competition and cooperation. It is worth noting that relying on government subsidies to maintain the sustainable development of technology service platforms is not a long-term solution. Government subsidies play a vital role in the initial development of technology service platforms. The analysis results are in line with Guo et al. (2016), Jung and Feng (2020) and Li (2021) conclusions. Furthermore, long-term government subsidies will make platforms dependent on these subsidies. These are the contributions to the scientific literature.

Instead of focusing on vertical relationships, this study emphasizes the horizontal cooperation and competition relationship between platforms and local governments in an urban agglomeration. Thus, the vertical effects of government subsidies on platforms can be investigated. Another innovation is the social welfare policy goal, which is an important index for the development of urban agglomerations.

The study aims to analyze factors impacting firms’ success and persistence in a digital platform competition using the structure-conduct-performance (SCP) framework. The study also includes real-life cases that are beneficial to academicians and practitioners to understand and develop strategies for success and persistence during uncertainty.

A literature review to identify the factors that impact success and persistence in a digital platform competition was conducted following Webster and Watson (2002). Findings were integrated into a SCP framework to examine and understand the identified factors’ relational impact.

While analyzing factors under the SCP framework, all factors were divided into three categories: those impacting positively, those impacting negatively and those with ambiguous impact on the success and persistence in digital platform competition. Digital platform firms can exploit the positively impacting factors to increase market share by being distinctive from other digital platform firms and becoming dominant by withstanding competition. On the other hand, negatively impacting factors increase barriers to entry, intensify competition and reduce the distinctiveness of digital platform firms. Lastly, a few factors may have either a positive or a negative impact depending upon the particular characteristics of the firm/industry.

The study opens the scope for future research on empirically testing the developed conceptual framework and relationships by developing propositions to posit the possible impact of these factors on digital platforms’ success and persistence.

The study contributed to the existing literature by using SCP framework to analyze the factors affecting firm’s success and persistence in a digital platform competition. Also, the study has discussed the relational impact of factors rather than their impact in isolation.

The European Union’s Digital Markets Act (DMA) calls for far-reaching changes to the way economic activity will occur in EU digital markets. Before its remedies are imposed, it is critical to assess their impacts on individual markets, the digital sector, and the overall European economy. The European Commission (EC) released an Impact Assessment in support of the DMA that purports to evaluate it using cost/benefit analysis.

An economic evaluation of the DMA should consider its full impacts on dynamic competition. The Impact Assessment neither assesses the DMA's impact on dynamic competition in the digital economy nor evaluates the impacts of specific DMA prohibitions and obligations. Instead, it considers benefits in general and largely ignores costs. We study its benefit assessments and find they are based on highly inappropriate methodologies and assumptions. A cost/benefit study using inappropriate methodologies and largely ignoring costs cannot provide a sound policy assessment.

Instead of promoting dynamic competition between platforms, the DMA will likely reinforce existing market structures, ossify market boundaries, and stunt European innovation. The DMA is likely to chill R&D by encouraging free riding on the investments of others, which discourages making those investments. Avoiding harm to innovation is critical because innovation delivers large, positive spillover benefits, driving increases in productivity, employment, wages, and prosperity.

The DMA prioritizes static over dynamic competition, with the potential to harm the European economy. Given this, the Impact Assessment does not demonstrate that the DMA will be beneficial overall, and its implementation must be carefully tailored to alleviate or lessen its potential to harm Europe’s economic performance.

The attempt to establish a common European framework for core platforms' duties and responsibilities toward other actors in the digital environment is at the core of the recent scholarly debate surrounding the Digital Markets Act (DMA) proposal. In particular, the everlasting juxtaposition between the “data power” – as emerging from recent cases (Section 2) – that dominant tech companies enjoy and the concept of consumer sovereignty (Section 3) lies at the core of the proposal's attempt to identify digital core platforms as market gatekeepers. Accordingly, this chapter critically investigates the divide between power imbalance and consumer sovereignty in light of the architecture designed by the DMA, with a specific focus on its effectiveness in identifying gatekeepers' power drivers (Section 4). After highlighting the main critical aspects of the pertinent rules, opportunities for fruitful developments are then identified through the reframing of some of the notions considered in the proposal, and namely the role of “lock-in” effects and “data accumulation” (Section 5). Lastly, this chapter suggests that the DMA advancements – while desirable – are bound to be fragmentary in the absence of a wider appraisal of the nature of data power imbalance dynamics in the modern digital markets (Section 6).

The purpose of this study is to explore the coopetition relationships between platform owners and complementors in complementary product markets. Drawing on the coopetition theory, the authors examined the evolutionary trends of the coopetition relationships between platform owners and complementors and explore the main influence factors.

The authors used Lotka–Volterra model to analyze the coopetition relationship between platform owners and complementors, including the evolutionary trends as well as the results. Considering the feasibility of sample data collection, simulation is used to verify the effects of different factors on the evolution of coopetition relationships.

The results show that there are four possible results of the competition in the complementary products market. That comprises “winner-take-all for platform owners,” “winner-take-all for complementors,” “stable competitive coexistence” and “unstable competitive coexistence,” where “stable competitive coexistence” is the optimal evolutionary state. Moreover, the results of competitive evolution are determined by innovation subjects’ interaction parameters. However, the natural growth rate, the initial market benefits of the two innovators and the overall benefits of the complementary product markets influence the time to reach a steady state.

The study provides new insights into the entry of platform owners into complementary markets, and the findings highlight the fact that in complementary product markets, platform owners and complementors should seek “competitive coexistence” rather than “winner-takes-all.” Moreover, the authors also enrich the coopetition theory by revealing the core factors that influence the evolution of coopetition relationships, which further enhance the analysis of the evolutionary process of coopetition relationships.

This study aims to provide insights into Airbnb’s exit from the China market, specifically from the perspective of platform competition.

Based on the understanding of the evolution and competition of peer-to-peer (P2P) accommodation market in China and the double-edged network effects, this viewpoint article provides an in-depth discussion on Airbnb’s withdrawal from the China market.

This viewpoint paper contends that Airbnb faced increasing challenges in establishing unique competitive advantages against local rivals, who demonstrate a capacity for innovation and maintaining loyal customers in adapting to the market evolution. Consequently, this may inhibit Airbnb from attracting the mainstream market and lead Airbnb into a negative spiral, exacerbated by indirect network effects.

This study offers insights into the failure of an internationalisation process, drawing from an analysis of the competitive environment and the competition strategies of P2P accommodation platforms in China. These findings have practical implications for the implementation of international business strategies in P2P accommodation.

本观点文章旨在基于平台竞争的视角对爱彼迎退出中国的现象进行阐释

基于对中国共享住宿/民宿市场的演变和竞争、双边网络效应的理解, 本文对爱彼迎退出中国进行了深入探讨。

本文提出, 爱彼迎在建立独特竞争优势以应对本地竞争对手方面面临日益严峻的挑战, 因为本地竞争者在适应市场变化方面展现出突出的创新和留客的能力。这可能会阻碍爱彼迎吸引主流市场, 并导致其跌入由间接网络效应加剧的恶性循环中。

基于对中国共享住宿平台的竞争环境和策略的分析, 本文洞悉了一个国际化失败的案例。本文的发现对于共享住宿的国际化策略实施具有实践意义。

Este artículo de opinión pretende aportar ideas sobre la salida de Airbnb del mercado chino, concretamente desde la perspectiva de la competencia entre plataformas.

Basándonos en la comprensión de la evolución y la competencia del mercado de alojamientos P2P en China, así como en los “efectos de red de doble filo”, este artículo de opinión ofrece una discusión en profundidad sobre la retirada de Airbnb del mercado chino.

Este documento sostiene que Airbnb enfrentó desafíos crecientes para establecer ventajas competitivas únicas frente a sus rivales locales, demostrando estos últimos una capacidad de innovación y del mantenimiento de la lealtad de sus clientes al adaptarse a la evolución del mercado. En consecuencia, esto puede inhibir a Airbnb para atraer al mercado principal y llevar a la empresa a una espiral negativa, exacerbada por efectos de red indirectos.

Este estudio ofrece una visión del fracaso de un proceso de internacionalización, a partir de un análisis del entorno competitivo y de las estrategias de competencia de las plataformas de alojamiento P2P en China. Estos resultados tienen implicaciones prácticas para la aplicación de estrategias empresariales internacionales en los alojamientos P2P.

This paper aims to study the interplay between a risk-averse national brand manufacturer's (NBM) selling mode decision and a risk-neutral e-platform's private brand (PB) introduction decision.

A game theory model is used to solve selling mode decision, that is whether transform the selling mode from the wholesale mode to the marketplace mode, and PB introduction decision, that is, whether introduce the PB.

The results show that for the NBM, under certain condition, the NBM's selling mode decision is not affected by the e-platform's PB introduction decision. High revenue-sharing rate is conducive only when the difference in consumer preference between the PB and the national brand (NB) is small. The NBM's risk aversion will improve the applicability of the marketplace mode. For the e-platform, high PB preference of consumers and risk-averse behavior of the NBM is not conducive to PB introduction. For the supply chain, scenarios that the NB monopolizes the market under the wholesale mode and PB introduction under the marketplace mode should be prevented. PB introduction under the wholesale mode will become the only equilibrium with the increase of risk aversion of the NBM. Finally, the authors extend the scenario that consumers prefer the PB and the e-platform is risk-averse enterprise and find that PB introduction under the wholesale mode is detrimental to the NBM but beneficial to the supply chain. The impact of consumers' PB preference on the e-platform's PB introduction is opposite to the basic model. The impact of the e-platform's risk aversion on game equilibrium is opposite to that of the NBM's risk aversion.

This paper is first to study selling mode decision and PB introduction decision when considering enterprises' risk-averse attitude.

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

For an entrant platform in the on-demand service market, choosing an appropriate employment model is critical. This study explores how the entrant optimally chooses the employment model to achieve better performance and investigates the optimal pricing strategies and wage schemes for both incumbent and entrant platforms.

Based on the Hotelling model, the authors develop a game-theoretic framework to study the incumbent's and entrant's optimal service prices and wage schemes. Moreover, the authors determine the entrant's optimal employment model by comparing the entrant's optimal profits under different market configurations and analytically analyze the impacts of some critical factors on the platforms' decision-making.

This study reveals that the impacts of the unit misfit cost of suppliers or consumers on the pricing strategies and wage schemes vary with different operational efficiencies of platforms. Only when both the service efficiency of contractors and the basic employee benefits are low, entrants should adopt the employee model. Moreover, a lower unit misfit cost of suppliers or consumers makes entrants more likely to choose the contractor model. However, the service efficiency of contractors has nonmonotonic effects on the entrant's decision.

This study focuses on an entrant's decision on the optimal employment model in an on-demand service market, considering the competition between entrants and incumbents on both the supplier and consumer sides, which has not been investigated in the prior literature.

The purpose of the paper is to construct a model that considers video purchase and then identifies the logical relationships implied by the parameters to explore video platform operation mechanisms.

The authors analyzed the video platform system using a mathematical modeling approach and numerical optimization techniques. Through pricing decisions, the authors obtained equilibrium results for the profitability of the video platforms and analyzed the favorable market factors. The authors then extended the model by analyzing the competitive strategies of the two video platforms in the market.

The authors find that advertiser profitability, ad nuisance, video sensitivity and video creator network effects are important factors influencing the pricing strategy of video platforms. During positive market conditions, video platforms tend to lower their prices until they absorb enough users. As market conditions change, the price adjustment strategies of video platforms are affected by parameter changes and inter-parameter relationships.

The study considers the network effects of video creators, which provides a realistic reference for scholars and managers. In addition, the authors consider the bargaining power of platforms when purchasing content. The authors provide a fresh perspective for scholars while filling a gap in the field as video platforms can acquire a portion of the content on the market by setting a purchase price.