Maximizing Consumer Surplus Research Articles

Game theoretic operation optimization of photovoltaic storage charging station considering uncertainty and carbon trading

With the advancement of energy conservation and emission reduction efforts, the orderly charging of electric vehicles and the operation of photovoltaic-storage-charging stations associated with electric vehicles have become increasingly important topics. This study constructs an optimization model for the operation of stations under the synergy of electricity and carbon markets from a game theory perspective. Firstly, Latin hypercube sampling and Monte Carlo sampling are employed to handle the uncertainties in photovoltaic output and the stochastic nature of electric vehicles charging. Secondly, a ladder-type carbon trading mechanism is introduced, and a charging optimization model based on Stackelberg game theory is developed to describe the benefit interaction between charging stations and electric vehicles users. In this model, the upper level represents the charging station operator aiming to maximize joint electricity and carbon revenue while minimizing load fluctuations, whereas the lower level represents electric vehicles users aiming to maximize consumer surplus. Finally, a genetic algorithm nested with mixed-integer linear programming is used to solve the optimization model. The simulation results validate the model's effectiveness and superiority. The results indicate that, compared to centralized optimization methods, the Stackelberg game mechanism can increase consumer surplus by 119.40 %, reduce carbon emissions by 217.92 %, and achieve a win-win situation for both parties. Compared to a fixed carbon trading value, the ladder-type carbon trading mechanism can reduce carbon emissions by 23.84 % and smooth load fluctuations.

On-Demand, Long-Term, or Hybrid? An Economic Analysis of Optimal Rental Models on Sharing Platforms

This study examines three rental models—long-term, on-demand, and hybrid—in the sharing economy and evaluates their impacts on social welfare and consumer surplus. Our analysis reveals the significance of consumers’ setup and transaction costs in determining the optimal rental-model for platforms. We find that the relative setup cost and the relative transaction cost between owners and renters play a crucial role in shaping the equilibrium market price and optimality of the three rental models, whereas the total costs determine the equilibrium transaction volume and sustainability of the three models, with high costs posing barriers to the viability of on-demand and hybrid models. In practice, platforms can maximize consumer surplus by selecting an optimal rental model that narrows the gap in setup costs between renters and owners. Policymakers should implement favorable policies or subsidies to balance consumers’ participation incentives on both sides of the market, leading to mutually beneficial social outcomes.

Conditional Rebates and Intel: A Step Backwards by any Standard?

Abstract This paper considers the law on conditional rebates. It sets out the changes introduced by the Court of Justice of the European Union (CJEU) Intel decision and how these have been applied in the General Court Intel Renv case. It is explained that the changes are part of a broader move to bring EU competition law in line with a Consumer Welfare Standard (CWS). An analysis of the new test then reveals that it is flawed for five reasons: the new test ignores the fact that low prices and exclusion are separable. The test incorporates the As-Efficient Competitor test, which only protects firms with low costs, not those that are more competitive as a whole. The test introduces a new standard of harm, which means that the law no longer prevents the restriction of competition, but rather prevents making it impossible for a firm with the same costs as the dominant undertaking to compete, which is a different standard. The new standard diminishes the deterrent effect of the law. Finally, compared with the original test, the CJEU test fails to maximize consumer surplus (despite that being the aim of the CWS). Therefore, there is no reason to retain the test and it is recommended that it is reversed.

Legal and ownership unbundling in the Turkish natural gas market: A comparative analysis

This study introduces a theoretical framework for the Turkish natural gas market based on the principles of game theory and industrial organization. It investigates the effects of the legal and ownership unbundling on consumer surplus, social welfare, and competition. The model considers a mixed oligopoly with a transmission system operator (TSO), a state-owned incumbent, and a private firm. The state-owned incumbent is assumed to maximize consumer surplus and its own profit, while the private firm is assumed to be profit-maximizing. Additionally, the state-owned incumbent is assumed to be less efficient than the private firm. The game consists of three stages. In the first two stages, the state-owned incumbent and the private firm sequentially choose contract sizes in the upstream market. In the last stage, a contract size-restricted Cournot game is played. The findings of the study suggest that legal unbundling appears to offer greater advantages for consumer surplus and social welfare compared to ownership unbundling, particularly when considering key factors such as third-party access, non-tariff discrimination, and import liberalization. The results indicate that adopting the role of a Stackelberg follower by the state-owned incumbent in the upstream market is advantageous in terms of consumer surplus, social welfare, and competition under both unbundling approaches.

Content Length Limit: How Does It Matter for a Consumer-to-Consumer Media Platform?

Our study is inspired by the rapid growth of consumer-to-consumer (C2C) media platforms such as TikTok. There are three key findings. First, we show that when content pieces on the platform are longer, viewers set a higher standard of match value in selecting content to view, leading to a lower click-through rate of contributed content on the platform. This finding suggests that a tight limit on content length increases click-through rate. Second, we show that extended content length on the platform first enhances platform performance but then hurts its performance, following an inverted U-shape curve. This pattern holds true for short-term performance measured by viewer traffic and total viewing time, as well as for long-term performance measured by total consumer surplus. This finding suggests the existence of an optimal content length. Third, we find that the optimal content length maximizing viewer traffic is smaller than the one maximizing total viewing time, which is further smaller than the one maximizing consumer surplus. As such, a platform that switches the strategic focus from short-term advertising revenue to long-term growth will benefit from extending the content length limit.

Multi-Dimensional Screening: Buyer-Optimal Learning and Informational Robustness

Abstract A monopolist seller of multiple goods screens a buyer whose type vector is initially unknown to both but drawn from a commonly known prior distribution. The seller chooses a mechanism to maximize her worst-case profits against all possible signals from which the buyer can learn about his values for the goods. We show that it is robustly optimal for the seller to bundle goods with identical demands (these are goods that can be permuted without changing the buyer’s prior type distribution). Consequently, pure bundling is robustly optimal for exchangeable prior distributions. For exchangeable priors, pure bundling is also optimal for the seller in the information environment (with the reverse timing) where an information designer, with the objective of maximizing consumer surplus, first selects a signal for the buyer, and then the seller chooses an optimal mechanism in response. We derive a formal relationship between the seller’s problem in both information environments.

When can auctions maximize post-auction welfare?

I study auctions in which firms bid for licenses that reduce their marginal costs in a post-auction downstream market. When there are three or more firms, I show that the Vickrey–Clarke–Groves (VCG) auction maximizes consumer surplus in dominant strategies if and only if it maximizes producer surplus in dominant strategies. With two firms, the effect on consumer surplus is ambiguous. When the VCG auction does not maximize consumer surplus, I show that consumer surplus can be maximized by adding caps, i.e., restricting the number of licenses a bidder can win. This might lower producer surplus.

Information Disclosure and Promotion Policy Design for Platforms

We consider a platform facilitating trade between sellers and buyers with the objective of maximizing consumer surplus. Even though in many such marketplaces, prices are set by revenue-maximizing sellers, platforms can influence prices through (i) price-dependent promotion policies that can increase demand for a product by featuring it in a prominent position on the web page and (ii) the information revealed to sellers about the value of being promoted. Identifying effective joint information design and promotion policies is a challenging dynamic problem as sellers can sequentially learn the promotion value from sales observations and update prices accordingly. We introduce the notion of confounding promotion policies, which are designed to prevent a Bayesian seller from learning the promotion value (at the expense of the short-run loss of diverting some consumers from the best product offering). Leveraging these policies, we characterize the maximum long-run average consumer surplus that is achievable through joint information design and promotion policies when the seller sets prices myopically. We then construct a Bayesian Nash equilibrium, in which the seller’s best response to the platform’s optimal policy is to price myopically in every period. Moreover, the equilibrium we identify is platform optimal within the class of horizon-maximin equilibria, in which strategies are not predicated on precise knowledge of the horizon length and are designed to maximize payoff over the worst-case horizon. Our analysis allows one to identify practical long-run average optimal platform policies in a broad range of demand models. This paper was accepted by David Simchi-Levi, revenue management and market analytics. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4677 .

A master–slave game optimal scheduling strategy for park-integrated energy systems based on adjustable robust optimization

As the bridge between power companies and users, the integrated energy system has become one of the carriers of energy reform, energy-saving, and emission reduction. Based on this, a master–slave game bilevel optimization model considering power company–park-integrated energy system (PIES)–user is established. In the upper game, the power company, as the leader, takes the maximization of its interests as the goal to consider and formulate the price of purchasing and selling electricity with the park. As a follower, combined with the fluctuation of electricity price and the electricity demand of its equipment, the park determines the relationship between purchasing and selling electricity with the power company. In the lower-level game, the park becomes the leader, taking into account the energy needs of users and formulating a reasonable price for selling energy. Users, as followers, intend to maximize consumer surplus and adjust their energy demand strategies to achieve the best energy consumption experience. Analyzing the properties of the game, it is verified that there is a unique Nash equilibrium solution in the game model. At the same time, the idea of solving the distribution of the model is adopted, and the equilibrium solution of the model is obtained by using limited information. In addition, the output uncertainty of renewable energy in the park is dealt with by adjustable robust optimization. Finally, aiming at achieving a win–win situation among all stakeholders, the proposed game model is verified to effectively solve the equilibrium strategy problem among the PIES, the power company, and users through simulation analysis of an example.

Joint optimisation of park-and-ride facility locations and alternate traffic restriction scheme under equilibrium flows

Alternate traffic restriction (ATR) schemes manage traffic congestion by prohibiting a proportion of cars from entering a predetermined ATR area during specific time periods. Under the ATR scheme, Park-and-Ride (P&R) often becomes more popular as travelers can park cars at P&R facilities and avoid driving into the ATR area. This paper proposes a multi-objective bi-level model that jointly optimizes the P&R facility locations and the ATR scheme (the ATR areas and the proportion of restricted private cars). The upper-level model minimizes the total travel cost and total emission cost, and maximizes consumer surplus. The lower-level model characterizes the user equilibrium of travel modes and route choices. The non-dominated sorting genetic algorithm is adapted to solve the proposed multi-objective bi-level model, where a gradient project algorithm is used for solving the lower-level model. Numerical studies are conducted to test and illustrate the applicability of the model and algorithms.

A two-sided model of paid peering

Internet users have suffered collateral damage in tussles over paid peering between large ISPs and large content providers. Paid peering is a relationship where two networks exchange traffic with payment, which provides direct access to each other’s customers without having to pay a third party to carry that traffic for them. The issue will arise again when the United States Federal Communications Commission (FCC) considers a new net neutrality order.We first consider the effect of paid peering on broadband prices. We adopt a two-sided market model in which an ISP maximizes profit by setting broadband prices and a paid peering price. We analytically derive the profit-maximizing prices, and show that they satisfy a generalization of the well-known Lerner rule. Our result shows that paid peering fees reduce the premium plan price, increase the video streaming price and the total price for premium tier customers who subscribe to video streaming services; however, the ISP passes on to its customers only a portion of the revenue from paid peering. ISP profit increases but video streaming profit decreases as an ISP moves from settlement-free peering to paid peering price.We next consider the effect of paid peering on consumer surplus. We find that consumer surplus is a uni-modal function of the paid peering fee. The paid peering fee that maximizes consumer surplus depends on elasticities of demand for broadband and for video streaming. However, consumer surplus is maximized when paid peering fees are significantly lower than those that maximize ISP profit. However, it does not follow that settlement-free peering is always the policy that maximizes consumer surplus. The peering price depends critically on the incremental ISP cost per video streaming subscriber; at different costs, it can be negative, zero, or positive.

Consumer search and optimal information

AbstractThis article studies an information design problem in a sequential consumer search environment. Consumers, whose valuation of firms' products is uncertain, observe a noisy signal about the valuation upon being matched with a firm. The goal is to characterize those signal structures that maximize consumer surplus. We show that the consumer‐optimal signal structure can be found within the class of conditional unit‐elastic demand signal distributions. A rich set of properties and comparative statics of the consumer‐optimal signal distributions are also derived.

Assessment of Recreational and Cultural Ecosystem Services Value of Islands

With the gradual expansion of benefits provided by islands to human wellbeing, it has become increasingly important to quantify the cultural ecosystem service functions of islands. In this study, the zone travel cost method (ZTCM) and individual travel cost method (ITCM) are used to assess the recreational and cultural ecosystem services value of the island region of Changhai County, China, and the recreational value of Xiaochangshan, Dachangshan, and Guanglu Islands based on questionnaire survey data. The results are as follows: (1) The overall recreational and cultural ecosystem services value of Changhai County in 2019 was 533.14 million USD, including a traveling cost of 395.71 million USD and consumer surplus of 137.43 million USD. (2) Further, based on the choice and consumption behaviors of tourists, multiple recreational values of the county were also inferred: the aesthetic experience presented the greatest contribution, while educational knowledge accounted for a lower percentage. (3) The recreational and cultural ecosystem services value 294.16, 60.03, and 143.26 million USD for Xiaochangshan, Dachangshan, and Guanglu Islands, respectively. Based on the findings of this study, future research will focus on the planning and development of Xiaochangshan Island tourism to maximize consumer surplus.

Horizontal mergers under uniform resource constraints

Resource constraints have a vertical influence on a firm's competition and it is important to address the issue of horizontal mergers with scarce resources. This article highlights the effects of uniform resource constraints on horizontal mergers with game theory methods. First, the threshold values for the firms to accept the merger, increasing consumer surplus, and increasing social welfare are presented and compared. Second, the threshold value to merge for consumer surplus maximization is larger than that for profit incentive mergers without resource constraints. Thus, under unbinding resource industries, mergers reduce consumer surplus and it is necessary to implement antitrust. Third, resource constraints deter mergers. Finally, under binding capacity (or resource) constraints, the threshold value for firms to merge is larger than that for the social optimality. Therefore, industries with scare resource should avoid antitrust.

Optimal Government Incentives to Improve the New Technology Adoption: Subsidizing Infrastructure Investment or Usage?

To promote new technology adoption, governments around the world are contemplating different ideas to develop effective subsidy policies. At the new technology infrastructure investment stage, governments can use investment subsidy to reduce the new technology firms' investment cost; at the market stage of promoting the new technology, governments can use usage subsidy to reduce consumers' cost of using the service provided by the new technology firms. In this study, we develop a game-theoretic model to examine the impact of both investment subsidy and usage subsidy on the new technology adoption. We find that both the investment subsidy and usage subsidy can entice the new technology firms to increase the infrastructure investment level so as to further improve the market penetration of the new technology. Next, by also examining the optimal government subsidy policy subject to a budget constraint, we find that the optimal government subsidy policy depends on both the government's objective function and the amount of the budget. Specifically, when the budget is low, both investment subsidy and usage subsidy are equally effective in improving market penetration, consumer surplus, firm profit, and social welfare. However, when the budget is high, it is optimal for the government to offer investment subsidy only to maximize the market penetration of the new technology; while it is optimal for the government to offer usage subsidy only to maximize consumer surplus or social welfare. Our results can serve as guidelines for the government when designing the optimal subsidy programs to achieve different goals associated with new technology promotion.

Price Competition and Platform Design in Two-Sided Networks

The owners of large online platforms, like Airbnb or Amazon Marketplace, are able to affect the probability that a given buyer observes a given seller on their platform. Buyers and sellers therefore interact on a bipartite graph with links between them weighted by the probability of observation. Platform owners are then able to design the network by choosing the observation probabilities. A seller's price is decreasing in their Bonacich centrality. In order to maximize profits, the platform owner connects an entrant to buyers according to a measure of their own centrality in the graph. While a network where buyers observe and trade with all sellers with probability one maximizes consumer surplus, such a network does not necessarily maximize the platform's profit. The platform owner faces a trade-off between increasing observability and reducing competition, which explains why buyers tend not to be able to observe all sellers on online platforms. If sellers are identical, increasing seller prominence for any consumer segment increases competition, and profit is maximized when it is randomized across all sellers.

Impact of Technical Progress on the Relationship Between Competition and Investment

This paper investigates the impact of technical progress on the relationship between competition and investment. Using a model of oligopolistic competition with differentiated products in which firms invest to reduce their marginal cost of production (or to improve quality), I find that technical progress, by increasing the size of innovation, defined as the drop in marginal costs (or the increase in quality) obtained for a given investment amount, increases total investment and decreases the level of competition that maximizes investment in the industry. This feature also holds for consumer surplus and welfare. This means that innovative industries maximize consumer surplus and welfare at a lower level of competitive pressure than do less innovative industries. In the model, competition is measured either by the number of competitors or by the degree of horizontal substitutability between offers. The results hold for both measures, subject to a relatively steady industry specific rate of technological change.

Is Public-Private Partnership Better than Traditional Procurement? An Analysis Under Nash Bargaining

Public-private partnership (PPP) is a form of government procurement where a private entity (firm) provides upfront funding to construct a major public infrastructure project. After the project is completed, the firm collects payments from end consumers who use the project to recoup the construction cost and generate a profit. Due to the enormous expense of infrastructure projects, the government and the firm often entertain intense negotiations on the subject of the construction and compensation details. However, existing literature has not studied the impact of negotiations on the outcome of the final PPP agreement. We solve for the Nash bargaining outcome between the government and the firm under PPP, and compare it to the traditional procurement where the government provides upfront funding for the project from its operating budget. The firm wants to maximize profit while the goal of the government is to maximize social welfare which typically includes consumer surplus and public revenue. We find that when public revenue accounts for a large proportion of the government's objective function, PPP can lead to a win-win situation for the government and the firm, compared to traditional procurement. In contrast, when the government's goal is to mainly maximize consumer surplus, PPP can result in a lose-lose outcome. However, in this case, the government can utilize subsidies (provided to either the firm or the end consumers) to attain a desired bargaining outcome under PPP. Our results are useful for informing policy makers of instances when PPP is better than traditional procurement and when government subsidies should be provided.

When Can Auctions Maximize Post-Auction Welfare?

I study auctions in which firms bid for licenses that reduce their marginal costs in a post-auction downstream market. When there are three or more firms, I show that the Vickrey--Clarke--Groves (VCG) auction maximizes consumer surplus in dominant strategies if and only if it maximizes producer surplus in dominant strategies. With two firms, the effect on consumer surplus is ambiguous. When the VCG auction does not maximize consumer surplus, I show that consumer surplus can be maximized by adding the right caps, i.e., restricting the number of licenses a bidder can win. This might lower producer surplus.

The Effect of Autonomous Vehicles on Consumer Welfare in Ride-Hailing Markets

Ride-hailing and shared-mobility markets, matching drivers with customers via an APP, have been rising in popularity in recent years, while the emergence of Autonomous Vehicles (AVs) promises to revolutionize urban mobility. In this paper, we research the implications for operators, policymakers, and consumer welfare of introducing fleets of autonomous vehicles (AVs) into a ride-hailing system and thus replacing the driver side. Unlike existing research, we propose a comparative model between non-AV and AV mobility markets with single- and dual-demand levels and introduce four market cases (1) with drivers, (2) with AV fleets provided by a for-profit operator, (3) AV fleets provided by a public sector operator maximizing transportation throughput and (4) AV fleets provided by a public sector operator maximizing consumer surplus. By comparing the first and second case we highlight the implications of switching to AVs in today's setting, while the third and fourth cases evaluate the possible welfare benefits of introducing AVs under a public non-profit operator scheme. Through numerical studies, we assess the performance of all market cases in regard to the achieved consumer welfare as subject to the realized number of trips and prices of a system. Our results highlight that a shift from today’s non-AV to an AV system lowers overall consumer welfare. More precisely, we show that privately operated AV systems are less capable to adjust to fluctuations in mobility demand than non-AV systems because of their fixed fleet size of AVs. Further, a public operated AV system with the aim to maximize the number of trips, would not increase overall consumer welfare compared to a privately operated AV system, whereas a public operator maximizing consumer surplus would. However, such a public operator maximizing consumer surplus would only be able to serve a smaller number of trips and thus be limited to being a complementary service within an existing transportation network.