Haskayne School of Business Research & Publications

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Browsing Haskayne School of Business Research & Publications by Author "Alp, Osman"

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    Adoption of Electric Trucks in Freight Transportation
    (2019-10-15) Alp, Osman; Tan, Tarkan; Udenio, Maximiliano
    Transportation sector is the largest contributor of global greenhouse gas emissions in the USA. Disruptive technological changes in this sector, such as alternative fuel vehicles, are crucial for emission reduction. We analyze how a cost-minimizing strategic transition plan can be developed for a transportation firm that aims to adopt electric trucks in their fully diesel fleet, over time. We consider the case in which the firm needs to invest in charging infrastructure required to support this transition, as the public charging infrastructure is currently inadequate. The congestion effect at the charging stations, the charging times, and the potential loss of productive driving time due to detours to reach charging stations are explicitly considered. By developing an independence property, we are able to model this problem as a linear integer program without any need to explicitly specify origins and destinations. We illustrate the resulting transition plan with a realistic data set. Our results indicate that a transportation firm that operates with high demand density over a given service region significantly benefits from adoption of electric trucks, while also enjoying substantial carbon emissions savings. High demand density also favors smaller battery capacity with shorter ranges under the optimized charging network capacity, even though larger battery capacity would increase productivity with extended ranges. Our analysis also offers insights for governments and regulators regarding the impact of several influential factors such as carbon cost, content of renewable energy in electricity mix, diesel engine efficiency, and subsidizing the charging infrastructure.
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    Delegation of Stocking Decisions under Asymmetric Demand Information
    (2017-11-22) Sen, Alper; Alp, Osman
    Headquarters of a retailer delegates stocking decisions to store managers at its various stores. Store managers have complete information of the local demand process, whereas headquarters has partial information. The problem is how to incentivize the managers to make stocking decisions that minimizes headquarters' expected overage and underage costs. We investigate performance measurement schemes in which headquarters incite store managers make stocking decisions in headquarters' best interests using their private information. Adopting such schemes helps retailers reduce stock-outs and attain desired service levels across their stores. Headquarters knows that the underlying demand process at a store for a product over a replenishment cycle is one of J possible Wiener demand processes, whereas store manager knows the specific process with certainty. Store manager creates a single order before the cycle. Headquarters use an incentive scheme which is based on the end-of-period leftover inventory and on a stock-out occasion at a pre-specified inspection time {\it before} the end of a period. Headquarters' problem to determine the inspection time and relative importance of stock-outs to leftover stock is formulated as a constrained non-linear optimization problem in a single period setting and a dynamic program in a multi-period setting. The proposed ``early inspection'' scheme leads to perfect alignment under certain conditions. Under more general conditions, it provides a near-perfect alignment and performs strictly better than stock-out inspection at the end. Using historical sales data of a retailer, we show that this scheme can lead to considerable cost reduction. Even though attaining high on-shelf availability is crucial in retail, stock-out related measures are not reflected in store managers' performance scorecards. We prescribe a novel, easy and practical method for headquarters with which they can increase on-shelf-availability by relying on their store managers' private demand information. The proposed method decidedly outperforms the computer aided ordering systems that are commonly used in practice.
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    Store Incentives and Retailer Inventory Performance under Asymmetric Demand Information and Unobservable Lost Sales*
    (2017) Alp, Osman; Sen, Alper
    We study incentive issues in an inventory management setting in which high on-shelf availability is crucial. Headquarters of a retailer delegates inventory replenishment decisions to store managers in its various stores. Store manager has complete information of the local demand process, whereas headquarters has partial information and cannot observe unsatisfied demand. The problem is how to incentivize the manager to make an order quantity decision that minimizes the sum of headquarters’ expected overage and underage costs. We propose two incentive schemes that explicitly incorporate excess inventory and stock-outs into the store manager’s performance measurement.We prove that a perfect alignment of incentives is possible under certain conditions. Interestingly, perfect or near-perfect alignment requires the stock-out inspection before the end of the replenishment cycle. We validate our approach and assumptions on a retailer’s actual data and show that the retailer may improve its profitability by using the proposed incentive scheme.