Showing papers in "Management Science in 2020"
TL;DR: The authors combine machine learning and operations research and management science (OR/MS) in developing a framework, along with specific methods, for using data to prescribe optimal decisi, for optimal decision making.
Abstract: We combine ideas from machine learning (ML) and operations research and management science (OR/MS) in developing a framework, along with specific methods, for using data to prescribe optimal decisi...
370 citations
TL;DR: A theory is developed that shows signaling a firm’s fundamental quality to lenders through inventory transactions to be more efficient—it leads to less costly ope...
Abstract: We develop a theory that shows signaling a firm’s fundamental quality (e.g., its operational capabilities) to lenders through inventory transactions to be more efficient—it leads to less costly ope...
230 citations
TL;DR: One prominent intervention involves attaching warnings to headlines of news stories that have been disputed by third-party fact-checkers as mentioned in this paper, which can be seen as an attempt to combat political misinformation.
Abstract: What can be done to combat political misinformation? One prominent intervention involves attaching warnings to headlines of news stories that have been disputed by third-party fact-checkers. Here w...
185 citations
TL;DR: It is found that entrepreneurs who behave like scientists perform better, are more likely to pivot to a different idea, and are not morelikely to drop out than the control group in the early stages of the startup.
Abstract: A classical approach to collecting and elaborating information to make entrepreneurial decisions combines search heuristics, such as trial and error, effectuation, and confirmatory search. This pap...
168 citations
TL;DR: It is found that the inclusion of a moral appeal or a sentence that increases the perceived probability of detection in a letter from the tax authorities almost doubled the average self-reported foreign income.
Abstract: We report from a large-scale randomized field experiment conducted on a unique sample of more than 15,000 taxpayers in Norway who were likely to have misreported their foreign income. By randomly m...
121 citations
TL;DR: In this article, the authors explore ways to reduce discrimination using online reputability, and find that widespread discrimination by hosts against guests of certain races in online marketplaces is widespread.
Abstract: Recent research has found widespread discrimination by hosts against guests of certain races in online marketplaces. In this paper, we explore ways to reduce such discrimination using online reputa...
116 citations
TL;DR: This work presents a new distributionally robust optimization model called robust stochastic optimization (RSO), which unifies both scenario-tree-based Stochastic linear optimization and distributionally strong linear optimization in a single model.
Abstract: We present a new distributionally robust optimization model called robust stochastic optimization (RSO), which unifies both scenario-tree-based stochastic linear optimization and distributionally r...
104 citations
TL;DR: Regulating on-demand ride-hailing services (e.g., Uber and DiDi) requires a balance of multiple competing objectives: encouraging innovative business models, sustaining traditional indian taxi services, and sustaining traditional taxi services.
Abstract: Regulating on-demand ride-hailing services (e.g., Uber and DiDi) requires a balance of multiple competing objectives: encouraging innovative business models (e.g., DiDi), sustaining traditional ind...
102 citations
TL;DR: This paper developed a model in which reward-based crowdfunding enables firms to obtain a reliable proof of concept early in their production cycle: they learn about total demand from a limited sample of target consumers preordering a new product.
Abstract: We develop a model in which reward-based crowdfunding enables firms to obtain a reliable proof of concept early in their production cycle: they learn about total demand from a limited sample of target consumers preordering a new product. Learning from the crowdfunding sample creates a valuable real option because firms invest only if updated expectations about total demand are sufficiently high. This is particularly valuable for firms facing a high degree of uncertainty about consumer preferences, such as developers of innovative consumer products. Learning also enables firms to overcome moral hazard. The higher the funds raised, the lower the firms’ incentives to divert them, provided third-party platforms limit the sample size by restricting campaign length. Although the probability of campaign success decreases with sample size, the expected funds raised are maximized at an intermediate sample size. Our results are consistent with stylized facts and lead to new empirical implications.
97 citations
TL;DR: With the growing popularity of corporate social responsibility (CSR), critics point out that firms tend to focus on salient CSR activities while slacking off on the unobservable ones, using CSR as a smokescreen for poor corporate governance.
Abstract: With the growing popularity of corporate social responsibility (CSR), critics point out that firms tend to focus on salient CSR activities while slacking off on the unobservable ones, using CSR as ...
96 citations
TL;DR: In this paper, the authors estimate the impact of two different types of bike-share systems in Paris, London, Chicago, and New York, and show that two of them are significantly worse than one another.
Abstract: The cities of Paris, London, Chicago, and New York (among many others) have set up bike-share systems to facilitate the use of bicycles for urban commuting. This paper estimates the impact of two f...
TL;DR: This work examines the relationship between data analytics capabilities and innovation using detailed firm-level data and first utilizes a survey to capture two types of firm practice.
Abstract: We examine the relationship between data analytics capabilities and innovation using detailed firm-level data. To measure innovation, we first utilize a survey to capture two types of firm practice...
TL;DR: This work studies the pricing and return policy decisions of an omnichannel retailer serving customers who differ in how they realize their uncertain valuation for a product—by inspecting in store before pu...
Abstract: We study the pricing and return policy decisions of an omnichannel retailer serving customers who differ in how they realize their uncertain valuation for a product—by inspecting in store before pu...
TL;DR: This paper identifies empirically which reference point in the literature is most likely to be related to behavior and explains how reference dependence is explained.
Abstract: Although reference dependence plays a central role in explaining behavior, little is known about the way that reference points are selected. This paper identifies empirically which reference point people use in decision under risk. We assume a comprehensive reference-dependent model that nests the main reference-dependent theories, including prospect theory, and that allows for isolating the reference point rule from other behavioral parameters. Our experiment involved high stakes with payoffs up to a week's salary. We used an optimal design to select the choices in the experiment and Bayesian hierarchical modeling for estimation. The most common reference points were the status quo and a security level (the maximum of the minimal outcomes of the prospects in a choice). We found little support for the use of expectations-based reference points.
TL;DR: In this article, the authors consider product delivery as an important service component that influences their shopping decisions on online retail platforms, and they consider delivering products to customers in a timely and reliable manner.
Abstract: Consumers regard product delivery as an important service component that influences their shopping decisions on online retail platforms. Delivering products to customers in a timely and reliable ma...
TL;DR: Market thickness is a key parameter that can make or break a platform’s business model and can offer more opportunities for participants to meet and higher chances that a potential participant will meet.
Abstract: Market thickness is a key parameter that can make or break a platform’s business model. Thicker markets can offer more opportunities for participants to meet and higher chances that a potential mat...
TL;DR: This work considers the problem faced by a firm that receives highly differentiated products in an online fashion and needs to price these products to sell them to its customer base.
Abstract: We consider the problem faced by a firm that receives highly differentiated products in an online fashion. The firm needs to price these products to sell them to its customer base. Products are des...
TL;DR: In this paper, the relation between air pollution and individual investors' trading behavior and performance was examined using unique data on stock trades by 87,504 individuals from 34 cities in China.
Abstract: This paper examines the relation between air pollution and individual investors’ trading behavior and performance. Using unique data on stock trades by 87,504 individuals from 34 cities in China, w...
TL;DR: In this article, the authors study the problem of sharing the revenue from broadcasting sport events among participating players, and provide direct, axiomatic and game-theoretical foundations for two focal rules: the equal-split rule and concede-and-divide.
Abstract: We study the problem of sharing the revenue from broadcasting sport events, among participating players. We provide direct, axiomatic and game-theoretical foundations for two focal rules: the equal-split rule and concede-and-divide. The former allocates the revenues generated from broadcasting each game equally among the participating players in the game. The latter concedes players in each game the revenues generated by their respective fans and divides equally the residual. We also provide an application studying the case of sharing the revenue from broadcasting games in La Liga, the Spanish Football League. We show that hybrid schemes, combining our rules with lower bounds and performance measures, yield close outcomes to the current allocation being implemented by the Spanish National Professional Football League Association.
TL;DR: This work considers dynamic assortment problems with reusable products, in which each arriving customer chooses a product within an offered assortment, uses the product for a random duration of time, and r...
Abstract: We consider dynamic assortment problems with reusable products, in which each arriving customer chooses a product within an offered assortment, uses the product for a random duration of time, and r...
TL;DR: The analysis suggests that the common strategic advice to subsidize one side in order to maximize total profits may be limited or even incorrect when both sides multi-home, which is an important caveat given the increasing prevalence of multi-homing in platform markets.
Abstract: A major result in the study of two-sided platforms is the strategic interdependence between the two sides of the same platform, leading to the implication that a platform can maximize its total pro...
TL;DR: In this paper, the authors discuss the role of accelerators in helping nascent companies reach successful outcomes by providing capital, enabling industry connections, and increasing exposure to investors, however, they do not consider the impact of these connections on the company's performance.
Abstract: Accelerators aim to help nascent companies reach successful outcomes by providing capital, enabling industry connections, and increasing exposure to investors. Critically, however, accelerators als...
TL;DR: A general framework to study the design of spare parts logistics in the presence of three-dimensional (3-D) printing technology is presented.
Abstract: We present a general framework to study the design of spare parts logistics in the presence of three-dimensional (3-D) printing technology. We consider multiple parts facing stochastic demands and ...
TL;DR: This paper presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and therefore expensive process of manually selecting a subset of items to offer to a buyer.
Abstract: Assortment optimization is an important problem that arises in many practical applications such as retailing and online advertising. The fundamental goal is to select a subset of items to offer fro...
TL;DR: In this paper, the compatibility decisions of two competing platform owners that generate profits through both hardware sales and royalties from content sales are studied. And they consider a game-theoretic model in which two...
Abstract: We study compatibility decisions of two competing platform owners that generate profits through both hardware sales and royalties from content sales. We consider a game-theoretic model in which two...
TL;DR: In this paper, the authors investigate whether personal information posted by job candidates on social media sites is sought and used by prospective U.S. employers and create profiles for job candidates.
Abstract: We investigate whether personal information posted by job candidates on social media sites is sought and used by prospective U.S. employers. We create profiles for job candidates on popular social ...
TL;DR: A duopoly model where each firm chooses personalized prices for its targeted consumers, who can be active or passive in identity management is studied, which can lead to lower consumer surplus and lower social welfare.
Abstract: We study a model where each competing firm has a target segment where it has full consumer information and can exercise personalized pricing, and consumers may engage in identity management to bypa...
TL;DR: This paper examines how customer sentiment expressed through social media influences institutional investors’ investment decisions and firm value.
Abstract: This paper examines how customer sentiment expressed through social media influences institutional investors’ investment decisions and firm value. We use psychology theory to classify the emotional...
TL;DR: A family of re-solving heuristics that periodically re-optimize an approximation to the original problem known as the deterministic linear program (DLP), where random customer arrivals are replaced by their expectations are studied.
Abstract: We consider a canonical quantity-based network revenue management problem where a firm accepts or rejects incoming customer requests irrevocably in order to maximize expected revenue given limited ...
TL;DR: The authors empirically examined this question on a crowd-based corporate earnings forecast platform (Estimize) and found that a large group of experts can provide an accurate answer to a question involving quantity estimation.
Abstract: When will a large group provide an accurate answer to a question involving quantity estimation? We empirically examine this question on a crowd-based corporate earnings forecast platform (Estimize....