Ride-Hailing Platforms: Competition and Autonomous Vehicles

Author(s):  
Auyon Siddiq ◽  
Terry A. Taylor

Problem definition: Ride-hailing platforms, which are currently struggling with profitability, view autonomous vehicles (AVs) as important to their long-term profitability and prospects. Are competing platforms helped or harmed by platforms’ obtaining access to AVs? Are the humans who participate on the platforms—driver-workers and rider-consumers (hereafter, agents)—collectively helped or harmed by the platforms’ access to AVs? How do the conditions under which access to AVs reduces platform profits, agent welfare, and social welfare depend on the AV ownership structure (i.e., whether platforms or individuals own AVs)? Academic/practical relevance: AVs have the potential to transform the economics of ride-hailing, with welfare consequences for platforms, agents, and society. Methodology: We employ a game-theoretic model that captures platforms’ price, wage, and AV fleet size decisions. Results: We characterize necessary and sufficient conditions under which platforms’ access to AVs reduces platform profit, agent welfare, and social welfare. The structural effect of access to AVs on agent welfare is robust regardless of AV ownership; agent welfare decreases if and only if the AV cost is high. In contrast, the structural effect of access to AVs on platform profit depends on who owns AVs. The necessary and sufficient condition under which access to AVs decreases platform profit is high AV cost under platform-owned AVs and low AV cost under individually owned AVs. Similarly, the structural effect of access to AVs on social welfare depends on who owns AVs. Access to individually owned AVs increases social welfare; in contrast, access to platform-owned AVs decreases social welfare—if and only if the AV cost is high. Managerial implications: Our results provide guidance to platforms, labor and consumer advocates, and governmental entities regarding regulatory and public policy decisions affecting the ease with which platforms obtain access to AVs.

Author(s):  
Tianqin Shi ◽  
Nicholas C. Petruzzi ◽  
Dilip Chhajed

Problem definition: The eco-toxicity arising from unused pharmaceuticals has regulators advocating the benign design concept of “green pharmacy,” but high research and development expenses can be prohibitive. We therefore examine the impacts of two regulatory mechanisms, patent extension and take-back regulation, on inducing drug manufacturers to go green. Academic/practical relevance: One incentive suggested by the European Environmental Agency is a patent extension for a company that redesigns its already patented pharmaceutical to be more environmentally friendly. This incentive can encourage both the development of degradable drugs and the disclosure of technical information. Yet, it is unclear how effective the extension would be in inducing green pharmacy and in maximizing social welfare. Methodology: We develop a game-theoretic model in which an innovative company collects monopoly profits for a patented pharmaceutical but faces competition from a generic rival after the patent expires. A social-welfare-maximizing regulator is the Stackelberg leader. The regulator leads by offering a patent extension to the innovative company while also imposing take-back regulation on the pharmaceutical industry. Then the two-profit maximizing companies respond by setting drug prices and choosing whether to invest in green pharmacy. Results: The regulator’s optimal patent extension offer can induce green pharmacy but only if the offer exceeds a threshold length that depends on the degree of product differentiation present in the pharmaceutical industry. The regulator’s correspondingly optimal take-back regulation generally prescribes a required collection rate that decreases as its optimal patent extension offer increases, and vice versa. Managerial implications: By isolating green pharmacy as a potential target to address pharmaceutical eco-toxicity at its source, the regulatory policy that we consider, which combines the incentive inherent in earning a patent extension on the one hand with the penalty inherent in complying with take-back regulation on the other hand, serves as a useful starting point for policymakers to optimally balance economic welfare considerations with environmental stewardship considerations.


Author(s):  
Opher Baron ◽  
Oded Berman ◽  
Mehdi Nourinejad

Problem definition: Autonomous vehicles (AVs) are predicted to enter the consumer market in less than a decade. There is currently no consensus on whether their presence will have a positive impact on users and society. The skeptics of automation foresee increased congestion, whereas the advocates envision smoother traffic with shorter travel times. We study the automation controversy and advise policymakers on how and when to promote AVs. Academic/practical relevance: The AV technology is advancing rapidly and there is a need to study its impact on social welfare and the likelihood of its adoption by the public. Methodology: We use supply-demand theory to find the equilibrium number of trips for autonomous and regular households. We develop a simulation model of peer-to-peer AV sharing. We compare the socially optimal level of automation with the selfish adoption patterns where households independently choose their vehicle type. Results: We establish that the optimal social welfare is influenced by: (i) the network connectivity, that is, the ability of the infrastructure to serve AVs, (ii) the additional comfort provided by AVs that allows passengers to engage in other productive activities instead of driving, and (iii) the AV sharing patterns that reduce ownership costs, but create empty vehicle trips that increase congestion. Managerial implications: We investigate the impact of AVs in a case study of Toronto and show that partial automation maximizes social welfare. We show that the comfort of AVs may add traffic that compromises social welfare. Moreover, although traffic increases with automation, travel times may decrease because of significant improvements in traffic flow caused by AV connectivity in the network.


Sensors ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 297
Author(s):  
Ali Marzoughi ◽  
Andrey V. Savkin

We study problems of intercepting single and multiple invasive intruders on a boundary of a planar region by employing a team of autonomous unmanned surface vehicles. First, the problem of intercepting a single intruder has been studied and then the proposed strategy has been applied to intercepting multiple intruders on the region boundary. Based on the proposed decentralised motion control algorithm and decision making strategy, each autonomous vehicle intercepts any intruder, which tends to leave the region by detecting the most vulnerable point of the boundary. An efficient and simple mathematical rules based control algorithm for navigating the autonomous vehicles on the boundary of the see region is developed. The proposed algorithm is computationally simple and easily implementable in real life intruder interception applications. In this paper, we obtain necessary and sufficient conditions for the existence of a real-time solution to the considered problem of intruder interception. The effectiveness of the proposed method is confirmed by computer simulations with both single and multiple intruders.


Author(s):  
Nick Arnosti ◽  
Ramesh Johari ◽  
Yash Kanoria

Problem definition: Participants in matching markets face search and screening costs when seeking a match. We study how platform design can reduce the effort required to find a suitable partner. Practical/academic relevance: The success of matching platforms requires designs that minimize search effort and facilitate efficient market clearing. Methodology: We study a game-theoretic model in which “applicants” and “employers” pay costs to search and screen. An important feature of our model is that both sides may waste effort: Some applications are never screened, and employers screen applicants who may have already matched. We prove existence and uniqueness of equilibrium and characterize welfare for participants on both sides of the market. Results: We identify that the market operates in one of two regimes: It is either screening-limited or application-limited. In screening-limited markets, employer welfare is low, and some employers choose not to participate. This occurs when application costs are low and there are enough employers that most applicants match, implying that many screened applicants are unavailable. In application-limited markets, applicants face a “tragedy of the commons” and send many applications that are never read. The resulting inefficiency is worst when there is a shortage of employers. We show that simple interventions—such as limiting the number of applications that an individual can send, making it more costly to apply, or setting an appropriate market-wide wage—can significantly improve the welfare of agents on one or both sides of the market. Managerial implications: Our results suggest that platforms cannot focus exclusively on attracting participants and making it easy to contact potential match partners. A good user experience requires that participants not waste effort considering possibilities that are unlikely to be available. The operational interventions we study alleviate congestion by ensuring that potential match partners are likely to be available.


Author(s):  
Ming Hu ◽  
Yun Zhou

Problem definition: We consider an intermediary’s problem of dynamically matching demand and supply of heterogeneous types in a periodic-review fashion. Specifically, there are two disjoint sets of demand and supply types, and a reward for each possible matching of a demand type and a supply type. In each period, demand and supply of various types arrive in random quantities. The platform decides on the optimal matching policy to maximize the expected total discounted rewards, given that unmatched demand and supply may incur waiting or holding costs, and will be fully or partially carried over to the next period. Academic/practical relevance: The problem is crucial to many intermediaries who manage matchings centrally in a sharing economy. Methodology: We formulate the problem as a dynamic program. We explore the structural properties of the optimal policy and propose heuristic policies. Results: We provide sufficient conditions on matching rewards such that the optimal matching policy follows a priority hierarchy among possible matching pairs. We show that those conditions are satisfied by vertically and unidirectionally horizontally differentiated types, for which quality and distance determine priority, respectively. Managerial implications: The priority property simplifies the matching decision within a period, and the trade-off reduces to a choice between matching in the current period and that in the future. Then the optimal matching policy has a match-down-to structure when considering a specific pair of demand and supply types in the priority hierarchy.


Author(s):  
Lifei Sheng ◽  
Christopher Thomas Ryan ◽  
Mahesh Nagarajan ◽  
Yuan Cheng ◽  
Chunyang Tong

Problem definition: Games are the fastest-growing sector of the entertainment industry. Freemium games are the fastest-growing segment within games. The concept behind freemium is to attract large pools of players, many of whom will never spend money on the game. When game publishers cannot earn directly from the pockets of consumers, they employ other revenue-generating content, such as advertising. Players can become irritated by revenue-generating content. A recent innovation is to offer incentives for players to interact with such content, such as clicking an ad or watching a video. These are termed incentivized (incented) actions. We study the optimal deployment of incented actions. Academic/practical relevance: Removing or adding incented actions can essentially be done in real-time. Accordingly, the deployment of incented actions is a tactical, operational question for game designers. Methodology: We model the deployment problem as a Markov decision process (MDP). We study the performance of simple policies, as well as the structure of optimal policies. We use a proprietary data set to calibrate our MDP and derive insights. Results: Cannibalization—the degree to which incented actions distract players from making in-app purchases—is the key parameter for determining how to deploy incented actions. If cannibalization is sufficiently high, it is never optimal to offer incented actions. If cannibalization is sufficiently low, it is always optimal to offer. We find sufficient conditions for the optimality of threshold strategies that offer incented actions to low-engagement users and later remove them once a player is sufficiently engaged. Managerial implications: This research introduces operations management academics to a new class of operational issues in the games industry. Managers in the games industry can gain insights into when incentivized actions can be more or less effective. Game designers can use our MDP model to make data-driven decisions for deploying incented actions.


Author(s):  
Wei Qi ◽  
Mengyi Sha ◽  
Shanling Li

Problem definition: We develop a crossdisciplinary analytics framework to understand citywide mobility-energy synergy. In particular, we investigate the potential of shared autonomous electric vehicles (SAEVs) for improving the self-sufficiency and resilience of solar-powered urban microgrids. Academic/practical relevance: Our work is motivated by the ever-increasing interconnection of energy and mobility service systems at the urban scale. We propose models and analytics to characterize the dynamics of the SAEV-microgrid service systems, which were largely overlooked by the literature on service operations and vehicle-grid integration (VGI) analysis. Methodology: We develop a space-time-energy network representation of SAEVs. Then, we formulate linear program models to incorporate an array of major operational decisions interconnecting the mobility and energy systems. To preventatively ensure microgrid resilience, we also propose an “N − 1” resilience-constrained fleet dispatch problem to cope with microgrid outages. Results: Combining eight data sources of New York City, our results show that 80,000 SAEVs in place of the current ride-sharing mobility assets can improve the microgrid self-sufficiency by 1.45% (benchmarked against the case without grid support) mainly via the spatial transfer of electricity, which complements conventional VGI. Scaling up the SAEV fleet size to 500,000 increases the microgrid self-sufficiency by 8.85% mainly through temporal energy transfer, which substitutes conventional VGI. We also quantify the potential and trade-offs of SAEVs for peak electricity import reduction and ramping mitigation. In addition, microgrid resilience can be enhanced by SAEVs, but the actual resilience level varies by microgrids and by the hour when grid contingency occurs. The SAEV fleet operator can further maintain the resilience of pivotal microgrid areas at their maximum achievable level with no more than a 1% increase in the fleet repositioning trip length. Managerial implications: Our models and findings demonstrate the potential in deepening the integration of urban mobility and energy service systems toward a smart-city future.


Author(s):  
Retsef Levi ◽  
Somya Singhvi ◽  
Yanchong Zheng

Problem definition: Price surge of essential commodities despite inventory availability, due to artificial shortage, presents a serious threat to food security in many countries. To protect consumers’ welfare, governments intervene reactively with either (i) cash subsidy, to increase consumers’ purchasing power by directly transferring cash; or (ii) supply allocation, to increase product availability by importing the commodity from foreign markets and selling it at subsidized rates. Academic/practical relevance: This paper develops a new behavioral game-theoretic model to examine the supply chain and market dynamics that engender artificial shortage as well as to analyze the effectiveness of various government interventions in improving consumer welfare. Methodology: We analyze a three-stage dynamic game between the government and the trader. We fully characterize the market equilibrium and the resulting consumer welfare under the base scenario of no government intervention as well as under each of the interventions being studied. Results: The analysis demonstrates the disparate effects of different interventions on artificial shortage; whereas supply allocation schemes often mitigate shortage, cash subsidy can inadvertently aggravate shortage in the market. Furthermore, empirical analysis with actual data on onion prices in India shows that the proposed model explains the data well and provides specific estimates on the implied artificial shortage. A counterfactual analysis quantifies the potential impacts of government interventions on market outcomes. Managerial implications: The analysis shows that reactive government interventions with supply allocation schemes can have a preemptive effect to reduce the trader’s incentive to create artificial shortage. Although cash subsidy schemes have recently gained wide popularity in many countries, we caution governments to carefully consider the strategic responses of different stakeholders in the supply chain when implementing cash subsidy schemes.


Author(s):  
Ricky Roet-Green ◽  
Aditya Shetty

Problem definition: We consider the problem faced by a welfare-maximizing service provider who must make a decision on how to split a fixed quantity of resources between two variants of the service: a standard variant and an expedited variant. The service is mandatory, but customers can choose between the two variants. Choosing the expedited variant requires enrollment that incurs a fixed cost per period. Customers are strategic and have the same cost of waiting but are heterogeneous in the rate at which they use the service. Academic/practical relevance: The option of expedited security at U.S. airports (TSA PreCheck) is an instance where this problem arises. As has been the case with the PreCheck program, providers that offer expedited service may face criticism from customers, with the main concern being that the diversion of resources to expedited services increases wait time for regular customers. This has important policy implications for the provider, especially a government organization such as the TSA. Existing literature has focused on service differentiation as a means to maximize profit or overall social welfare, but its effect on individual customers has received little attention. Methodology: We find customer’s equilibrium decisions for any allocation choice made by the provider. Using the equilibrium result, we solve for the allocation choice that maximizes social welfare. Results: Even when customers behave strategically, an expedited service offered in parallel to a standard service cannot only increase overall welfare, but also do so for each customer individually. We also find that in a scenario where some customers lose out because of the expedited service, improving the efficiency of the expedited service is more effective than decreasing the enrollment cost to help those who are worse off. Managerial implications: The gains from offering expedited service do not have to come at the expense of regular customers. When they do, we provide recommendations for which decision levers are most effective at making the system fair.


Author(s):  
Shiliang Cui ◽  
Kaili Li ◽  
Luyi Yang ◽  
Jinting Wang

Problem definition: “Slugging,” or casual carpooling, refers to the commuting practice of drivers picking up passengers at designated locations and offering them a free ride in order to qualify for high-occupancy vehicle (HOV) lanes. Academic/practical relevance: It is estimated that tens of thousands of daily commuters rely on slugging to go to work in major U.S. cities. As drivers save commute time and passengers ride for free, slugging can be a promising Smart Mobility solution. However, little is known about the welfare, policy, and environmental implications of slugging. Methodology: We develop a stylized model that captures the essence of slugging. We characterize commuters’ equilibrium behavior in the model. Results: We find that slugging indeed makes commuters better off. However, the widely observed free-ride tradition is socially suboptimal. As compared with the social optimum, commuters always underslug in the free-slugging equilibrium when highway travel time is insensitive to slugging activities but may overslug otherwise. The socially optimal outcome can be achieved by allowing pecuniary exchanges between drivers and passengers. Interestingly, passengers may be better off if they pay for a ride than if they do not under free slugging. We also find that although policy initiatives to expand highway capacity or improve public transportation always increase social welfare in the absence of slugging, they may reduce social welfare in areas where free slugging is a major commuting choice. Nevertheless, these unintended consequences would be mitigated by the introduction of pecuniary exchanges. Finally, contrary to conventional wisdom, slugging as a form of carpooling can result in more cars on the road and thus, more carbon emissions. Managerial implications: Our results call upon the slugging community to rethink the free-ride practice. We also caution that slugging benefits commuters possibly to the detriment of the environment.


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