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講座預(yù)告 | APP的溢出效應(yīng)測量:基于因果圖算法

天津大學(xué)管理與經(jīng)濟(jì)學(xué)部
2019-01-03 16:39 瀏覽量: 3359
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and APP promotional strategies for APP platform managers and APP developers.圖文編輯 / 宇文慧 天津大學(xué)管理與經(jīng)濟(jì)學(xué)部 tjucome...

講 座 預(yù) 告APP的溢出效應(yīng)測量:基于因果圖算法How Mega is the Mega?Measuring the Spillover Effects of WeChat by Machine Learning and Econometrics25樓C區(qū)4121月9日(周三)9:30-11:30主講人:竇一凡復(fù)旦大學(xué)管理學(xué)院信息管理與信息系統(tǒng)系副教授。2007年畢業(yè)于清華大學(xué)經(jīng)管學(xué)院,獲管理學(xué)學(xué)士學(xué)位;2012年畢業(yè)于清華大學(xué)經(jīng)管學(xué)院管理科學(xué)工程專業(yè),獲管理學(xué)博士學(xué)位。竇一凡的主要研究興趣是與信息產(chǎn)品相關(guān)的經(jīng)濟(jì)學(xué)問題,如信息產(chǎn)品的定價(jià)策略、平臺(tái)模式的定價(jià)和協(xié)調(diào)問題等。竇一凡的研究工作先后發(fā)表Information System Research、European Journal of Operational Research、管理科學(xué)學(xué)報(bào)等國內(nèi)外知名學(xué)術(shù)期刊上,并入選ESI高被引論文。竇一凡曾獲得Management Science的優(yōu)秀reviewer服務(wù)獎(jiǎng),并于2018年獲得國家自然科學(xué)基金優(yōu)秀青年基金項(xiàng)目資助。講座摘要WeChat, an instant messaging APP, is considered a mega APP due to its dominance in terms of use among Chinese smartphone users. Little is known, however, about its externality in the broader APP market. This work estimates the spillover effects of WeChat on the other Top-50 most frequently used APPs in China, using users’ weekly APP usage data. Given the challenge of determining causal inference from observational data, we apply a graphical model and an econometric method to estimate the spillover effects in two steps: (1) we determine the causal structure by estimating a partially ancestral diagram, using a Fast Causal Inference (FCI) algorithm; and (2) given the causal structure, we find a valid adjustment set and estimate the causal effects by an econometric model with the adjustment set for controlling non-causal effects. Our findings show that the spillover effects of WeChat are limited; in fact, only two other APPs, Tencent News and Taobao, receive positive spillover effects from WeChat. In addition, we show that, if researchers fail to account for the causal structure that is determined from the graphical model, it is easy to fall into the trap of confounding bias and selection bias when estimating causal effects. The findings generate managerial implications in terms of APP usage patterns, strategic management of mega APPs on an APP platform, and APP promotional strategies for APP platform managers and APP developers.圖文編輯 / 宇文慧
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