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on Industrial Organization |
Issue of 2023‒10‒16
five papers chosen by |
By: | Liang Chen; Yao Luo |
Abstract: | Network effects, i.e., an agent's utility may depend on other agents' choices, appear in many contracting situations. Empirically assessing them faces two challenges: an endogeneity problem in contract choice and a reflection problem in network effects. This paper proposes a nonparametric approach to tackle both challenges by exploiting restriction conditions from both demand and supply sides. We illustrate our methodology in the yellow pages advertising industry. Using advertising purchases and nonlinear price schedules from seven directories in Toronto, we find positive network effects, which account for a substantial portion of the publisher's profit and businesses' surpluses. We finally conduct counterfactuals to assess the overall and distributional welfare effects of the nonlinear pricing scheme relative to an alternative linear pricing scheme with and without network effects. |
Keywords: | Identification, Asymmetric Information, Network Effects, Nonlinear Pricing |
JEL: | L11 L12 L13 |
Date: | 2023–09–25 |
URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-758&r=ind |
By: | Xingchen Xu; Stephanie Lee; Yong Tan |
Abstract: | Recent academic research has extensively examined algorithmic collusion resulting from the utilization of artificial intelligence (AI)-based dynamic pricing algorithms. Nevertheless, e-commerce platforms employ recommendation algorithms to allocate exposure to various products, and this important aspect has been largely overlooked in previous studies on algorithmic collusion. Our study bridges this important gap in the literature and examines how recommendation algorithms can determine the competitive or collusive dynamics of AI-based pricing algorithms. Specifically, two commonly deployed recommendation algorithms are examined: (i) a recommender system that aims to maximize the sellers' total profit (profit-based recommender system) and (ii) a recommender system that aims to maximize the demand for products sold on the platform (demand-based recommender system). We construct a repeated game framework that incorporates both pricing algorithms adopted by sellers and the platform's recommender system. Subsequently, we conduct experiments to observe price dynamics and ascertain the final equilibrium. Experimental results reveal that a profit-based recommender system intensifies algorithmic collusion among sellers due to its congruence with sellers' profit-maximizing objectives. Conversely, a demand-based recommender system fosters price competition among sellers and results in a lower price, owing to its misalignment with sellers' goals. Extended analyses suggest the robustness of our findings in various market scenarios. Overall, we highlight the importance of platforms' recommender systems in delineating the competitive structure of the digital marketplace, providing important insights for market participants and corresponding policymakers. |
Date: | 2023–09 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:2309.14548&r=ind |
By: | Bearzotti, Enia; Polanec, Sašo; Bartolj, Tjaša |
Abstract: | This paper evaluates the impact of varying subsidy sizes and distinct program objectives on firm size and performance. The magnitude of treatment effects increases with subsidy size, although the marginal effects tend to decrease. We also find that treatment effects differ across subsidy programs due to their distinct objectives. Among these, labor-support measures are most effective at supporting employment, capital, and output while being most harmful to productivity. Contrary to theory, subsidies providing incentives for investments have no impact on capital or productivity. The treatment effects tend to decrease over time and are thus temporary. As recipient firms are more likely to receive additional support in the future, the effects of subsidies accumulate giving rise to permanent differences between subsidized and non-subsidized firms. However, the lack of productivity improvements in such firms questions the benefits of repeated supporting measures. |
Keywords: | Subsidies, Firm Growth, Firm Performance, Industrial Policy |
JEL: | H25 L25 L52 |
Date: | 2023–09–06 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:118490&r=ind |
By: | Fakhrabadi, Mahnaz (Dept. of Business and Management Science, Norwegian School of Economics); Sandal, Leif K. (Dept. of Business and Management Science, Norwegian School of Economics) |
Abstract: | The paper investigates a multi-period supply channel facing uncertain and price-history dependent demands and environmental regulations. The knowledge about the demands is limited to its mean and standard deviation in each period, .e., there is incomplete information on the actual distribution. A distributional robust approach is conducted to address incompleteness. The chain is incorporating environmental policies such as pollution constraints and (optimal) corrective taxes. A single contract covers all periods. Numerical examples highlight the benefits of a single contract. |
Keywords: | Dynamic Games; Single Contract; Distributional-Robust Demand; Price-History-Dependent Demand; Pollution Reduction; Sustainability |
JEL: | C61 C62 C63 C72 C73 D81 Q52 |
Date: | 2023–09–22 |
URL: | http://d.repec.org/n?u=RePEc:hhs:nhhfms:2023_013&r=ind |
By: | Dimitrov, Kiril |
Abstract: | This paper reviews basic and emerging research trends on the moonshot phenomenon in the business world. It traces the emergence and development of the nuances for this construct, its relationships with the proclaimed corporate culture and some new attributes of management by objectives. Nevertheless the numerous realizations that the moonshot phenomenon has acquired – as goals, projects, tasks, specific leadership, skill and others, it seems subordinated to certain principles and approaches, constituting the so called moonshot thinking that is also succinctly described. |
Keywords: | moonshot, corporate culture, proclaimed corporate culture, strategic management, exponential organizations |
JEL: | M14 L1 L2 |
Date: | 2023 |
URL: | http://d.repec.org/n?u=RePEc:zbw:esconf:277566&r=ind |