M&SOM Review

In recent years, carsharing has been widely adopted as a means of sustainable transportation. Cities around the world have launched numerous carshare initiatives hoping to relieve their urban transportation problems. Carshare service providers, such as Zipcar, Car2Go, and DriveNow—in partnership with leading automobile manufacturers such as Toyota, Daimler, and BMW—have undergone rapid growth and expansion. In the United States alone, it is estimated that over 1.3 million individual users participated in the sharing of 20,000 vehicles through different carshare services as of July 2015 (EcoPlan Association 2015).

CarShare lot

In spite of its widespread success, carsharing brings forth significant challenges to operations management. In particular, service providers must optimize their fleet management to maximize profit while maintaining high quality of service. Fleet management is concerned with decisions such as the acquisition of vehicle fleet and parking spaces and the allocation of fleet to service zones. The complexity of fleet management is even more pronounced with the recent introduction of one-way services. Traditional carshare services typically require the vehicles be returned to the same location from which they were originally rented. To address growing user demand for one-way rentals, carshare service providers have launched different types of one-way services, e.g., Car2go’s innovative free-floating system and Zipcar’s ONE>WAY programs. Providing one-way service leads to additional operational challenges, of which the most significant one is to deal with the imbalances caused by one-way rentals. Since vehicles no longer need to be returned to the same location where they were first rented, the service provider must therefore reposition vehicles to restore a proper fleet allocation for continuing service. Determining the quantity, origin, and destination of repositioning in each time period is also a complex problem.

Because of its importance, fleet management in carshare systems has received a lot of attention from industries. Toyota, for example, has devised an IT system to help its customers manage their carsharing fleet (Toyota Europe Newsroom 2013). Miveo, a carshare solutions provider in Europe, recently won a prestigious industry leadership award for their fleet management products (Frost & Sullivan 2016). However, optimal fleet allocation and repositioning remains a difficult and challenging problem to solve, especially under uncertain demand.

One way to tackle this problem is by using stochastic programming with two stages of decision making. In the first stage, the acquisition of vehicles and parking spaces/permits is determined. In the second stage, based on the first-stage decisions, the movement of vehicles is optimized on a spatial-temporal network. Each arc of this network represents a vehicle activity across certain time periods and geographic locations, such as fulfilling a rental trip, being repositioned to a different location, and remaining idled at the same location. The amount of flow along each arc represents the number of vehicles having the corresponding activity, which is constrained by random rental demand or parking capacity, and each unit of flow generates corresponding rental revenue or repositioning/idling cost. The first-stage decisions are then carefully chosen so as to minimize the expected total cost and quality of service penalty net expected revenue. This requires solving a mathematical optimization model with a large number of variables, which grows exponentially with the number of service zones, operating periods, and demand scenarios used to represent uncertainty. Even with state-of-the-art commercial optimization packages, it is still hard to solve this problem with practical scale within a reasonable amount of time. To speed up the process, decomposition methods enhanced with a procedure known as cutting plane are used to eliminate irrelevant decisions without affecting the final optimal solution.

Equipped with a mathematical programming model for the carshare system and a solution algorithm that can efficiently optimize the decisions, service providers can now solve their fleet management problem. Various analyses were conducted using carshare demand data from the Boston–Cambridge area. Comparing the optimal fleet allocation with the demand, one can see that the optimal proportion of vehicles assigned to each location is not necessarily similar to the proportion of demand originating from each location. This shows that the carshare fleet management is indeed a complex problem for which intuitive solutions may not perform well. Of particular interest is the impact of one-way services on the profitability and quality of service of carshare systems. Contradictory to what many would expect, results show that if growth in one-way demand is exogenous, e.g., from natural market penetration, then it is not necessarily detrimental to either profitability or service quality. With sufficient price differentiation (for example, Zipcar charges $12 per hour in its ONE>WAY program compared to $7.75 per hour in round trip rentals) and effective vehicle repositioning, more one-way rentals can actually increase profit while reducing the number of unfulfilled rental trips/hours. On the other hand, if growth in one-way demand is endogenous, e.g., as a result of users’ strategic response to pricing, then it will result in lower profit. By implementing the fleet allocation model periodically, real-time vehicle repositioning decisions can be obtained. One concern regarding repositioning is that service providers may not have enough capacity to rebalance the fleet. Results show that in order to gain most of the benefit from repositioning, only a small proportion of the fleet needs to be repositioned simultaneously, suggesting that repositioning capacity may not be as restrictive as many would expect.

In summary, with the help of efficient modeling and solution methods, mathematical optimization models can be used to optimize carshare service providers’ strategic planning decisions and real-time tactical decisions. Analysis results show that the challenges brought by one-way rentals can be well managed by sufficient price differentiation and effective vehicle repositioning and the restriction from limited repositioning capacity is not significant. Carshare service providers can be more confident in providing flexible one-way services.

 

References

Lu M, Chen Z, Shen, S (2018) Optimizing the profitability and quality of service in carshare systems under demand uncertainty. Manufacturing Service Operations Management 20(2):162–180.

EcoPlan Association (2015) One thousand world cities where you can carshare this morning. Accessed June 30, 2016, https://worldstreets.wordpress.com/2009/07/15/one-thousand-cities-where-you-can-carshare-this-morning/.

Frost & Sullivan (2016) Frost & Sullivan lauds Miveo’s end-to-end solutions for carsharing operators in the European market. Accessed June 30, 2016, https://ww2.frost.com/news/press-releases/frost-sullivan-lauds-miveos-end-end-solutions-carsharing-operators-european-market/.

Toyota Europe Newsroom (2013) City of Grenoble, Grenoble-Alpes Métropole, Cité lib, EDF, Toyota Motor Corporation to launch ultra-compact urban EV car-sharing project. (March 4), http://newsroom.toyota.eu/city-of-grenoble-grenoble-alpes-mtropole-cit-lib-edf-toyota-motor-corporation-to-launch-ultra-compact-urban-ev-car-sharing-project/.

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The Problem of Capacity Investment in Supply Chains

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Let us first read a story written and posted on the thekrazycouponlady.com:

Like many Krazy Coupon Ladies, I consider myself a smart and savvy shopper, but I'll be the first to admit that sometimes my emotions get the best of me. I saw a beautiful cashmere sweater at one of my favorite shops last week for 30% off; it even came in petite sizes—it was too perfect. I thought I had an amazing deal. It was still more than I would normally spend, but I went against my gut and bought it anyway. The next day I got an email that they were now all 40% off—just my luck! Thankfully, while I was online I came across their price adjustment policy and got an additional $10 credited back to my card. Since I had such good luck with this, I thought I'd share a few other fabulous price adjustment policies so hopefully you can save more money and stress less this season! (The Krazy Coupon Lady 2016; emphasis added)

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