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?智能總結(jié)信息管理與電子商務(wù)研究前沿系列 TITLE: What is the Value of Free Players and Free Goodies in Online Video Games? An ...

信息管理與電子商務(wù)研究前沿系列
TITLE:
What is the Value of Free Players and Free Goodies in Online Video Games? An Empirical Study of Microtransactions
ABSTRACT:
Massively multiplayer online (MMO) games usually adopt free-to-play business model, in which companies earn profits from gamers' in-game purchases (commonly known as microtransactions). We develop a structural model of a player's simultaneous choices of the hours and money spent on playing the game with unobserved player heterogeneity in the opportunity cost of time, price sensitivity, and taste of the game, and with social interactions within the gaming community. Using player-level panel data, we show the identification and propose a novel estimation method. Our estimates show that without the participation of free players, the average in-game expenditure among paid players will drop by 58% in our specific MMO game. We propose and evaluate a counterfactual reward program, in which players will be rewarded virtual goods for free after playing the game for certain hours. The counterfactual analysis shows the optimal generosity of the reward program.
TIME:2021/07/26, 9:30-11:00a.m.(GMT+8)ZOOM:ID: 89028614402
密碼:123456
SPEAKER:

車(chē)海是加州大學(xué)河濱分校Gary Anderson商學(xué)院的市場(chǎng)營(yíng)銷(xiāo)學(xué)副教授。在加入加州大學(xué)河濱分校之前,車(chē)教授是印第安納大學(xué)凱利商學(xué)院的副教授,并曾在加州大學(xué)伯克利分校和南加州大學(xué)任教。車(chē)教授教授本科,全日制和兼職MBA課程以及博士課程。他的主要研究領(lǐng)域包括數(shù)據(jù)驅(qū)動(dòng)營(yíng)銷(xiāo),實(shí)證模型和行為經(jīng)濟(jì)學(xué)。他在頂級(jí)學(xué)術(shù)期刊上發(fā)表了十余篇研究論文,其中包括Marketing Science, Journal of Marketing Research, Quantitative Marketing Economics, and Production and Operations Management。車(chē)教授于2009年被授予為市場(chǎng)營(yíng)銷(xiāo)科學(xué)研究所的青年學(xué)者,并獲得加州大學(xué)總部頒發(fā)的教學(xué)獎(jiǎng)和亞洲營(yíng)銷(xiāo)學(xué)會(huì)的最佳論文獎(jiǎng)。

運(yùn)籌優(yōu)化與運(yùn)營(yíng)管理研究前沿系列
TITLE:
Saddle points and Nash equilibria
ABSTRACT:
A saddle point is a pair of solutions that solves min-max and max-min optimization simultaneously. A Nash equilibrium is a set of strategies for a group of players such that each player's strategy is optimal when the other players' strategies are the given ones. A saddle point is the Nash equilibrium for a zero sum game of two players. This talk discusses how to find saddle points and Nash equilibria for problems that are given by polynomials. We formulate efficient polynomial optimization and apply the Moment-SOS relaxations to solve it. Under some genericity assumptions, we show that the method can find a saddle point (or Nash equilibrium), or show that it can detect nonexistence if they do not exist. This is joint work with Zi Yang, Guangming Zhou and Xindong Tang.
TIME:2021/07/27, 9:00-11:00a.m.(GMT+8)Tecent Meeting:ID:262356720
密碼:123456
SPEAKER:

聶家旺,加利福尼亞大學(xué)圣地亞哥分校教授。主要從事多項(xiàng)式優(yōu)化、半正定規(guī)劃、張量計(jì)算、矩問(wèn)題、鞍點(diǎn)問(wèn)題、Nash均衡問(wèn)題等相關(guān)領(lǐng)域的研究。他曾先后獲得國(guó)際數(shù)學(xué)規(guī)劃學(xué)會(huì)Tucker Prize Finalist, 美國(guó)NSF Career獎(jiǎng),INFORMS青年優(yōu)化學(xué)者獎(jiǎng), SIAM應(yīng)用線(xiàn)性代數(shù)最佳論文獎(jiǎng)。他目前擔(dān)任學(xué)術(shù)刊物《中國(guó)運(yùn)籌學(xué)會(huì)會(huì)刊》,《優(yōu)化計(jì)算及應(yīng)用》,《運(yùn)籌數(shù)學(xué)》,《SIAM矩陣分析及應(yīng)用》等雜志的編委。

運(yùn)籌優(yōu)化與運(yùn)營(yíng)管理研究前沿系列
TITLE:
Screening with Limited Information: The Minimax Theorem and A Geometric Approach
ABSTRACT:
Consider a seller seeking a selling mechanism to maximize the worst-case revenue obtained from a buyer whose valuation distribution lies in a certain ambiguity set. For a generic convex ambiguity set, we show via the minimax theorem that strong duality holds between the problem of finding the optimal robust mechanism and a minimax pricing problem where the adversary first chooses a worst-case distribution and then the seller decides the best posted price mechanism. This observation connects prior literature that separately studies the primal (robust mechanism design) and problems related to the dual (e.g., robust pricing, buyer-optimal pricing and personalized pricing). We further provide a geometric approach to analytically solving the minimax pricing problem (as well as the robust pricing problem) for several important ambiguity sets such as the ones with mean and various dispersion measures, and with the Wasserstein metric. The solutions are then used to construct the optimal robust mechanism and to compare with the solutions to the robust pricing problem.
TIME:2021/07/30, 9:30-11:30a.m.(GMT+8)Tecent Meeting:ID:241224661
密碼:123456
SPEAKER:


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