Taxi-hailing platforms:Inform or Assign drivers?

Online platforms for matching supply and demand, as part of the sharing economy, are becoming increasingly important in practice and have seen a steep increase in academic interest. Especially in the taxi/travel industry, platforms such as Uber, Lyft, and Didi Chuxing have become major players. Some of these platforms, including Didi Chuxing, operate two matching systems: Inform, where multiple drivers receive ride details and the first to respond is selected; and Assign, where the platform assigns the driver nearest to the customer. The Inform system allows drivers to select their destinations, but the Assign system minimizes driver-customer distances. This research is the first to explore: (i) how a platform should allocate customer requests to the two systems and set the maximum matching radius (i.e., customer-driver distance), with the objective to minimize the overall average waiting times for customers; and (ii) how taxi drivers select a system, depending on their varying degrees of preference for certain destinations. Using approximate queuing analysis, we derive the optimal decisions for the platform and drivers. These are applied to real-world data from Didi Chuxing, revealing the following managerial insights. The optimal radius is 1-3 kilometers, and is lower during rush hour. For most considered settings, it is optimal to allocate relatively few rides to the Inform system. Most interestingly, if destination selection becomes more important to the average driver, then the platform should not always allocate more requests to the Inform system. Although this may seem counterintuitive, allocating too many orders to that system would result in many drivers opting for it, leading to very high waiting times in the Assign system. (c) 2020 Elsevier Ltd. All rights reserved

Managing demand uncertainty: probabilistic selling versus inventory substitution

Demand variability is prevailing in the current rapidly changing business environment, which makes it difficult for a retailer that sells multiple substitutable products to determine the optimal inventory. To combat demand uncertainty, both strategies of inventory substitution and probabilistic selling can be used. Although the two strategies differ in operation, we believe that they share a common feature in combating demand uncertainty by encouraging some customers to give up some specific demand for the product to enable demand substitution. It is interesting to explore which strategy is more advantageous to the retailer. We endogenize the inventory decision and demonstrate the efficiency of probabilistic selling through demand substitution. Then we analyze some special cases without cannibalization, and computationally evaluate the profitability and inventory decisions of the two strategies in a more general case to generate managerial insights. The results show that the retailer should adjust inventory decisions depending on products' substitution possibility. The interesting computational result is that probabilistic selling is more profitable with relatively lower product similarity and higher price-sensitive customers, while inventory substitution outperforms probabilistic selling with higher product similarity. Higher demand uncertainty will increase the profitability advantage of probabilistic selling over inventory substitution.Peer ReviewedPostprint (author's final draft

Effects of introducing low-cost high-speed rail on air-rail competition:Modelling and numerical analysis for Paris-Marseille

Given the trend of railway liberalization in Europe and Asia, we explore the effects of introducing low-cost high-speed rail as an answer to the railway reform on air-rail competition. In particular, by proposing a vertically differentiated model, we first derive the optimal pricing policies as well as the corresponding profits and market shares for low-cost high-speed rail (LCR), full-service high-speed rail (FSR) and air transport (Air). We do so for two types of LCR entrants, namely the incumbent owned entrant (to the FSR company) and the independently owned entrants. For both situations, we prove analytically that introducing LCR leads to reduced FSR and Air fares as well as to reduced Air traffic. The fare and traffic reductions increase with the passenger's time value and with the LCR travel time, while they decrease with the Air unit seat cost. Moreover, all LCR effects are stronger for an independently operated LCR. We apply our model to the Paris-Marseille route, based on data collected from publicly available sources. It is found that introducing an independently owned (incumbent owned) LCR on this route leads to 39% (33%) less air traffic, 20% (14%) less FSR traffic and a 37% (29%) increase in total rail traffic. Furthermore, this comes with increases of 2% (8%) in combined railway profit and 6% (5%) in total social welfare. These results support the decision of French policy makers to have LCR and FSR operated by the same company, as it comes with much higher combined railway profits and almost the same welfare increase as independently owned LCR. Further sensitivity analyses suggest that most LCR passengers would otherwise have traveled by FSR or Air, although LCR also attracts new passengers. In addition, offering a low-cost alternative is more effective if passengers value time more highly. Implications in terms of methodology and industry are provided.</p

Modeling the Potential for Aviation Liberalization in Central Asia - Market analysis and implications for the Belt and Road initiative

This study analyzes aviation markets in the five land-locked countries in Central Asia. Panel data spanning from 2007 to 2015 are used to estimate airline entry patterns in origin-destination markets. Econometric estimates for domestic and international markets are subsequently benchmarked, and route groups are paired by alternative matching algorithms so that counter-factual analysis can be conducted. Our investigation suggests that although the Central Asia–China markets are characterized by poor connectivity and high airfares, great benefits could be achieved if more liberal aviation policies such as those proposed by the Belt and Road initiative were introduced. In particular, our counterfactual analysis suggests that if the Central Asia–China markets were regulated and operated in a similar way to the routes between Central Asia and other states, the probability of having aviation services between cities in China and Central Asia would increase by 27%, even by conservative estimates. The number of Chinese destinations could increase by more than 150%. Our study finds strong negative effects of the restrictive regulations on the international aviation markets, and calls for further liberalizations between Central Asia and the region’s major trade partners

Global bifurcation and nodal solutions for homogeneous Kirchhoff type equations

In this paper, we shall study unilateral global bifurcation phenomenon for the following homogeneous Kirchhoff type problem

Global bifurcation and nodal solutions for homogeneous Kirchhoff type equations

In this paper, we shall study unilateral global bifurcation phenomenon for the following homogeneous Kirchhoff type problem \begin{equation*} \begin{cases} -\left(\int_0^1 \left\vert u'\right\vert^2\,dx\right)u''=\lambda u^3+h(x,u,\lambda)&\text{in}\,\, (0,1),\\ u(0)=u(1)=0. \end{cases} \end{equation*} As application of bifurcation result, we shall determine the interval of $\lambda$ in which there exist nodal solutions for the following homogeneous Kirchhoff type problem \begin{equation*} \begin{cases} -\left(\int_0^1 \left\vert u'\right\vert^2\,dx\right) u''=\lambda f(x,u)&\text{in}\,\, (0,1),\\ u(0)=u(1)=0, \end{cases} \end{equation*} where $f$ is asymptotically cubic at zero and infinity. To do this, we also establish a complete characterization of the spectrum of a homogeneous nonlocal eigenvalue problem

Order picking optimization with order assignment and multiple workstations in KIVA warehouses

We consider the problem of allocating orders and racks to multiple stations and sequencing their interlinked processing flows at each station in the robot-assisted KIVA warehouse. The various decisions involved in the problem, which are closely associated and must be solved in real time, are often tackled separately for ease of treatment. However, exploiting the synergy between order assignment and picking station scheduling benefits picking efficiency. We develop a comprehensive mathematical model that takes the synergy into consideration to minimize the total number of rack visits. To solve this intractable problem, we develop an efficient algorithm based on simulated annealing and dynamic programming. Computational studies show that the proposed approach outperforms the rule-based policies used in practice in terms of solution quality. Moreover, the results reveal that ignoring the order assignment policy leads to considerable optimality gaps for real-world-sized instances

Purchase or rent? Optimal pricing for 3D printing capacity sharing platforms

Online sharing platforms have attracted considerable research and management attention across a number of industries, including travel, real estate, and cloud computing. They also have great potential for the 3D printing (3DP) industry, offering users the choice between owning or renting 3DP capacity. For matching supply and demand, capacity pricing is crucial. In this paper we consider two fundamental questions concerning pricing: (i) What is the optimal pricing strategy for a 3DP capacity sharing platform? (ii) How do usage level and printer heterogeneity affect consumers’ choice between in-house printing (owning) and outsourcing (renting)? Using queuing analysis, we derive the structural properties of the solutions to the problems. Furthermore, we conduct numerical studies using real-world data to generate managerial insights from the analytical findings. A key finding is that governments should focus on encouraging technological progress to lower the printers’ prices in order to improve the well-being of the industry. When considering two types of printers, we find that it is more beneficial for the platform if the high capacity printer dominates the market, as the platform then retains the prominent role in “redistributing” the 3DP capacity.</p

Efficient multi-attribute auctions considering supply disruption

Although supply disruption is ubiquitous because of natural or man-made disasters, many firms still use the price-only reverse auction (only the cost is considered) to make purchase decisions. We first study the suppliers’ equilibrium bidding strategies and the buyer’s expected revenue under the first- and second-price price-only reverse auctions when the suppliers are unreliable and have private information on their costs and disruption probabilities. We show that the two auctions are equivalent and not efficient. Then we propose two easily implementable reverse auctions, namely the first-price and second-price format announced penalty reverse auction (APRA), and show that the “revenue equivalence principle” holds, i.e., the two auctions generate the same ex ante expected profit to the buyer. We further show that the two reverse auctions are efficient and “truth telling” is the suppliers’ dominant strategy in the second-price format APRA. We conduct numerical studies to assess the impacts of some parameters on the bidding strategies, the buyer’s profit and social profitPeer ReviewedPostprint (author's final draft