Seller promotion and competition on decentralized two-sided platforms

IF 1.8 Q3 MANAGEMENT
Feng Yang, Jingyi Peng, Zihao Zhang
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引用次数: 0

Abstract

Purpose

This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

Design/methodology/approach

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

Findings

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

Originality/value

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

去中心化双面平台上的卖家推广和竞争
本文旨在探讨竞争条件下分散平台上异质卖家的推广决策,并分析卖家行为如何影响平台利润、卖家收入、买家盈余和社会福利。本文考虑了一个库诺模型,该模型由一个收取佣金的平台和两个具有不同转化率和浏览成本的卖家组成。卖家的推广活动可以增加流量,但也会给卖家带来推广成本。卖家通过权衡这两种效果来决定推广力度。作者还探讨了平台收取固定使用费时的均衡情况。研究结果卖家的利润随着转化率的提高而提高,随着浏览成本的增加而降低。此外,提高平台收取的佣金率会使卖方减少在促销方面的投入。因此,平台必须考虑这种权衡,以确定最佳费率。分析表明,转化率高、浏览成本高的卖家在创造更多总体收入方面发挥着更大的作用。原创性/价值 本文将转换率、买家浏览成本、单位推广成本和平台收费纳入模型,研究分散平台上卖家的推广决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.50
自引率
12.50%
发文量
52
期刊介绍: Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.
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