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The Effect of Asset Ownership on Project Selection: Evidence from 1970's Television
No full textExisting theoretical and empirical work on contracting highlights the efficiency gains possible from optimizing asset ownership when projects span firm boundaries. However, in settings where firms are able to choose among heterogenous projects, asset ownership can also determine which projects are selected for execution. Using a regulatory shock to the US broadcast television industry, this study finds restricting television network ownership over television shows altered the types of shows commissioned by the networks. This result extends prior theoretical and empirical work on contracting by showing asset ownership not only determines the efficiency of outcomes given a project but also can change the relative attractiveness of different projects. The relationship between asset ownership and project selection is especially important in innovation contexts where project selection has a cumulative effect by changing the marginal returns to future projects; an industry’s contracting environment can therefore be a driver of the direction of innovation
Do Investors Care About Corporate Externalities? Experimental Evidence
No full textWe measure how shareholders value a firm's ethical actions via an experiment. Our findings are threefold. First, the "selfish investor hypothesis'' is strongly rejected. Participants are willing to pay 1 on a charity is valued $.9 less than a similar company with no externality. The scaling of non-pecuniary preferences is linear: doubling the size of a social externality doubles its impact on willingness to pay. Second, the data show that whether investors are pivotal or not with regard to the ethical actions of the firm does not affect their willingness to pay. Third, when participants make investment decisions on behalf of a third party (delegation), their generosity level remains similar. Our results appear to be compatible with a utility model where non-pecuniary benefits are conditional on stock holding
The Impact of Overconfidence and Ambiguity Attitude on Market Entry
No full textWe study the behavioral drivers of market entry. An experiment allows us to disentangle the impact on entry across different types of markets of two key behavioral mechanisms: overconfidence and attitude toward ambiguity. We theorize and show that the causal effect of overconfidence on entry is limited to skill-based markets and does not appear in those that are chance based. Moreover, we also find that, independent of confidence levels, individuals exhibit ambiguity-seeking behavior when the result of the competition depends on their skills, which in turn leads to higher levels of entry. This preference for ambiguity can thus explain results that have previously been attributed to overconfidence. Our results challenge existing literature that has inferred overconfidence from differential entry levels across types of markets
Sciences en Marche.L'expérience entrepreneuriale d'un mouvement social
No full textInternational audienc
Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach
No full textInternational audienceDynamic pricing of new products has been extensively studied in monopolistic and oligopolistic markets. But, the optimal control and differential game tools used to investigate the pricing behavior on markets with a finite number of firms are not well-suited to model competitive markets with an infinity of firms. Using a mean-field games approach, this paper examines dynamic pricing policies in competitive markets, where no firm exerts market power. The theoretical setting is based on a diffusion modeì a la Bass. We prove both the existence and the uniqueness of a mean-field game equilibrium, and we investigate mean tendencies and firms dispersion in the market. Numerical simulations show that the competitive market splits into two separate groups of firms depending on their production experience. The two groups differ in price and profit. Thus, high prices and profits do not have to signal anticompetitive practices, stimulating the debate on market regulation
Rational vs Byzantine Players in Consensus-based Blockchains
No full textInternational audienceWe analyze from the game theory point of view Consensus-basedblockchains when participants exhibit rational or Byzantine be-havior. Our work is the first to model the Byzantine-consensusbased blockchains as a committee coordination game. Our firstcontribution is to offer a game-theoretical methodology to an-alyze equilibrium interactions between Byzantine and rationalcommittee members in Consensus-based blockchains. Byzantineparticipants seek to inflict maximum damage to the system, whilerational participants best-respond to maximize their expectednet gains. Our second contribution is to derive conditions underwhich consensus properties are satisfied or not in equilibrium.When the number of votes required for a decision is lower thanthe proportion of Byzantine participants, invalid blocks are ac-cepted in equilibrium. When the number of votes needed is large,equilibrium can involve coordination failures, in which no blockis ever accepted. However, when the cost of accepting invalidblocks is large, there exists an equilibrium in which blocks areaccepted if and only if they are valid
E-retailers and the engagement of delivery workers in urban last-mile delivery for sustainable logistics value creation: Leveraging legitimate concerns under time-based marketing promise
No full textInternational audienceThis paper's research aims to understand how e-retailers can benefit from independent contractors' (delivery drivers') agile engagement under time-based marketing promise (TBMP) to advance sustainable logistics value creation in the urbanised last-mile-delivery (ULMD) environment. Our analysis of independent drivers' narratives (n = 30) reveals that sustainable logistics value can be apprehended through a process in which independent workers are both agenced by their leveraging of technologisation and task autonomy and concerned by the mobilisation of other ULMD stakeholders. They thus can propose novel, creative solutions for e-retailers and city planners towards sustainable logistics value creation
Economic Benefits of Product Recommendations to Consumers: Estimates from a Field Experiment
No full textDo personalized offerings enabled by big data only bring economic benefits to firms but not to consumers? In this paper, we seek to address this question by examining a particular category of personalized offerings provided by algorithmic product recommendation systems. While the economic value of algorithmic product recommendations to firms is mostly understood, their benefits to consumers are not well quantified in the literature. We conduct a randomized field experiment on an apparel retailer’s website in the US to estimate the benefits of recommendations to consumers. We find that recommendations helped consumers discover lower-priced products on the website, which results in a higher probability of product purchase (lower likelihood of failed search efforts) and a lower price of purchased products. Specifically, an additional recommended product page view due to recommendations leads to a 15 percent increase in purchase probability and a 56,631 (3.8 percent of the total sales), two-thirds of which the retailer captured as additional revenue, and the remaining one-third the consumers as price savings
Scaling Human Effort in Idea Screening and Content Evaluation
No full textBrands and advertisers often tap into the crowd to generate ideas for new products and ad creatives by hosting ideation contests. Content evaluators then winnow thousands of submitted ideas before a separate stakeholder, such as a manager or client, decides on a small subset to pursue. We demonstrate the information value of data generated by content evaluators in past contests and propose a proof-of-concept machine learning approach to efficiently surface the best submissions in new contests with less human effort. The approach combines ratings by different evaluators based on their correlation with the past stakeholder choices, controlling for submission characteristics and textual content features. Using field data from a crowdsourcing platform, we demonstrate that the approach improves performance by identifying nonlinear transformations and efficiently reweighting evaluator ratings. Implementing the proposed approach can affect the optimal assignment of internal experts to ideation contests. Two evaluators whose votes were a priori equally correlated with sponsor choices may provide substantially different incremental information to improve the model-based idea ranking. We provide additional support for our findings using simulations based on a product design survey
Privacy Management in Service Systems
No full textWe study customer-centric privacy management in service systems and explore the consequences of extended control over personal information by customers in such systems. Our stylized model of a service environment features a service provider and customers who are strategic in deciding whether to disclose personal information to the service provider – that is, customers' privacy or information disclosure strategy. A customer's service request can be one of two types, which affects service time but is unknown when customers commit to a privacy strategy. The service provider can discriminate among customers, based on their disclosed information, by offering different priorities. Our analysis yields three sets of main insights. First, when given control over their personal data, strategic customers do not always choose to withhold it. We find that control over information gives customers a tool they can use to hedge against the service provider's incentives, which might not be aligned with the interests of customers. Second, a customer's self-centered strategic decision may or may not be aligned with what is best for customers themselves. In fact, giving customers full control over information might backfire by leading to inferior system performance (i.e., longer average wait time) and hurting customers themselves. We demonstrate how a regulator can correct information disclosure inefficiencies through monetary incentives to customers and show that providing such incentives makes economic sense in some scenarios. Finally, the service provider itself can benefit from customers being in control of their personal information by enticing more customers joining the service. Our findings shed light on the market for pricing personal information in the service industry