Coût d'opportunité | EPFL Graph Search

Le coût d'opportunité (de l'anglais opportunity cost), également appelé coût d'option, coût alternatif, coût de substitution, coût de renonciation ou encore coût de renoncement désigne la perte des biens auxquels on renonce lorsqu'on procède à un choix, autrement dit lorsqu'on affecte les ressources disponibles à un usage donné au détriment d'autres choix. C'est le coût d'une chose estimé en termes d'opportunités non réalisées, ou encore la valeur de la meilleure autre option non réalisée. Autrement dit : dans une situation où l'on est confronté à plusieurs choix, le coût d'opportunité d'un choix donné est le meilleur gain (gain dans l'absolu, pas par rapport au choix donné) que l'on peut obtenir en choisissant l'un des autres choix. La notion de coût d'opportunité n'introduit donc pas de nouvelle mesure économique par rapport au gain : elle permet en revanche de rendre compte du fait qu'en envisageant un choix, on renonce à d'autres choix qui avaient des gains associés (supérieurs o

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

In this dissertation, I develop theory and evidence to argue that new technologies are central to how firms organize to create and capture value. I use computational methods such as reinforcement learning and probabilistic topic modeling to investigate three topics: the automation of routines, the organization of artificial intelligence (AI), and the evaluation of technology risk. Overall, I argue that new technologies are not a panacea for the firm but require deliberate strategic planning to manage the potential downsides of myopic automation, AI interdependencies, and the disclosure of technology risks.In the first essay, I argue that while automation can increase productivity by reducing the costs of coordinating individuals, the automation of routines can also incur an indirect opportunity cost due to slow adaptation to environmental change. I develop a reinforcement learning simulation to model the impact of automation on the returns from the division of labor in dynamic environments and to show how automation incurs opportunity costs through lost learning and slow adaptation. Moreover, automation can be suboptimal when it brings about myopic behavior, i.e. high returns from the division of labor in the short term, but negative returns in the long term. Given the simulation results, I argue that firms need dynamic routines to simultaneously balance learning and automation. I open-source the simulation platform as OrgSim-RL on GitHub.In the second essay, I argue that a data-driven culture - what I define as a Data Clan - can help to coordinate complex interdependencies between AI components within a firm. I analyze in-depth semi-structured interview data with a hierarchical stochastic block model (hSBM) and hand-coding to find that managers focus primarily on building a strong culture and establishing high-quality data assets when allocating resources to AI initiatives. Given the results, I inductively develop implications for theory and argue that the emergence of a Data Clan can be a governance mechanism to reduce coordination frictions and build a competitive advantage in the age of AI.In the third essay, I argue that investors require a higher initial return to take on more technology risk disclosure during an IPO. I quantify the magnitude of disclosed risk and the risk disclosure topics based on a latent Dirichlet allocation (LDA) topic model of IPO prospectus text and find a return-for-risk association between text-based technology risk disclosure and underpricing. The study also finds evidence that owning granted patents is associated with a lower return-for-risk association, suggesting that intellectual property allows the disclosure of risk without losing the competitive advantage. I open-source the code for quantifying risk disclosure as RiskyData-LDA on GitHub.In summary, this dissertation develops theory and finds evidence across three essays to argue that leveraging new technologies requires deliberate strategic planning to manage potential downsides of new technologies, such as the opportunity costs of automation, coordination costs, and costs associated with raising capital. The results suggest three mitigating solutions: dynamic routines to balance learning and automation, a Data Clan to improve coordination, and disclosure through patents to reduce underpricing.

EPFL2022

Three Essays in Banking and Finance

Damien Olivier Klossner

This thesis develops three models that study the motivation of various agents to take on debt, and the impact that excessive financial leverage can have on social welfare. In the chapter "Short-term Bank Leverage and the Value of Liquid Reserves", the incentive of a bank to take on leverage stems from the fact that its short-term debt provides liquidity benefits to depositors, at the cost of exposing the bank to the risk of runs. In the model, a bank possesses two instruments to manage the risk of runs: its funding policy and the size of its liquid asset holdings, modeled as government bonds. Issuing more debt allows the bank to better capture the liquidity benefits fits priced into deposits but increases illiquidity risk. Holding more bonds makes the bank more robust to withdrawals but it reduces the bank's asset returns. When the supply is scarce, banks are the natural buyers of government bonds. This links the liquidity premium priced into government bonds to the risk of bank runs. In the chapter "Liquidity, Debt Overhang, and Monetary Policy", firms take on bank credit to relax their liquidity constraint and purchase new capital. But taking on debt creates a debt overhang distortion which causes entrepreneurs to pass on protable projects. In the model, entrepreneurs arrange for their financing before they observe the profitability of their investment opportunity. After the latter becomes known, entrepreneurs are liquidity-constrained when investment conditions are favorable, and over-indebted when they are unfavorable. The monetary authority can generate welfare gains by lowering the cost of holding liquidity and, when debt is contracted in nominal terms, by pursuing a counter-cyclical monetary policy. In the chapter "Safe Claim Production and Capital Structure", firms issue debt to satisfy the demand of risk-averse investors for safe claims, at the cost of increasing default risk. In general equilibrium, firms need to be compensated for this service, which can only occur if their debt and equity claims are held and priced by different investor types. This segmentation of the investor base can be sufficient to prevent the existence of a symmetric equilibrium. Instead, only a fraction of firms opt for levered capital structures, and the gain in value obtained by tranching cash flows into debt and equity is offset by the expected cost of default. Changes in aggregate leverage can be divided into variations in extensive (the fraction of levered firms ) and intensive (the leverage ratio of levered firms ) margins. Changes in rm business risk have opposite effects on leverage, depending on whether the risk is of a systematic nature or firm-specific nature.

EPFL2019

Another Hidden Cost of Incentives: The Detrimental Effect on Norm Enforcement

Stephan Meier

Monetary incentives, such as subsidies or bonuses, are often considered as a way to foster contributions to public goods in society and firms. This paper investigates experimentally the effect of private contribution incentives in the presence of a norm enforcement mechanism. Norm enforcement through peer punishment has been shown to be effective in raising contributions by itself. We test whether and how (centrally provided) private incentives interact with (decentralized) punishment, both of which affect subjects’ monetary payoffs. The results of our experiment show that private incentives for contributors can reduce the effectiveness of the norm enforcement mechanism: Free riders are punished less harshly in the treatment with incentives, and as a consequence, average contributions to the public good are no higher than without incentives. This finding ties to and extends previous research on settings in which monetary incentives may fail to have the desired effect.

2010

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

EPFL2022

Three Essays in Banking and Finance

Damien Olivier Klossner

EPFL2019