Gilvan "Gil" C Souza

Areas of Expertise

Operations Management, Supply Chain Management, Closed-Loop Supply Chains, Circular Economy, Sustainable Operations, Remanufacturing, Reverse Logistics

Academic Degrees

• PhD, University of North Carolina, 2000
• MBA, Clemson University, 1995
• BS, ITA (Brazil), 1990

Professional Experience

• Indiana University, 2015-present: Professor
• Indiana University, 2009-2015, Associate Professor
• University of Maryland, 2006-2009, Associate Professor
• University of Maryland, 2000-2006, Assistant Professor
• Georgia Institute of Technology, 2007, Visiting Associate Professor
• Volkswagen of Brazil, 1991-1994, 1995-1996, Product Development Engineer

Awards, Honors & Certificates

• 2014 Research Award, Kelley School of Business
• Wickham Skinner Early Career Research Award, POMS 2004
• 2004 Krowe Teaching Award, for excellence in the MBA program, Smith School, University of Maryland

Selected Publications

• Raz, Gal, and Gilvan C. Souza (2018), “Recycling as a Strategic Supply Source,” Production and Operations Management, 27(5): 902-916.
• James Abbey, Rainer Kleber, Gilvan C. Souza, and Guido Voigt (2017), "The Role of Perceived Quality Risk in Pricing Remanufactured Products," Production and Operations Management, 26(1): 100-115.
• Shanshan Hu, Gilvan C. Souza, Mark E. Ferguson, and Wenbin Wang (2015), "Capacity Investment in Renewable Energy Technology with Supply Intermittency: Data Granularity Matters!" Manufacturing & Service Operations Management, 17(4): 480-494.

Abstract We study an organization’s one-time capacity investment in a renewable energy-producing technology with supply intermittency and net metering compensation. The renewable technology can be coupled with conventional technologies to form a capacity portfolio that is used to meet stochastic demand for energy. The technologies have different initial investments and operating costs, and the operating costs follow different stochastic processes. We show how to reduce this problem to a single-period decision problem and how to estimate the joint distribution of the stochastic factors using historical data. Importantly, we show that data granularity for renewable yield and electricity demand at a fine level, such as hourly, matters: Without energy storage, coarse data that does not reflect the intermittency of renewable generation may lead to an overinvestment in renewable capacity. We obtain solutions that are simple to compute, intuitive, and provide managers with a framework for evaluating the trade-offs of investing in renewable and  conventional technologies. We illustrate our model using two case studies: one for investing in a solar rooftop system for a bank branch and another for investing in a solar thermal system for water heating in a hotel, along with a conventional natural gas heating system.

• Cattani, Kyle, Gilvan C. Souza, and Shengqi Ye (2014). "Shelf Loathing: Cross Docking at an Online Retailer,"Production and Operations Management, 23(5), 893-906.

Abstract Online customers expect to wait, sometimes for a delay of many days. At the fulfillment center, there might be an opportunity to fill customer orders earlier than the due date through a cross-docking transaction: rather than picking the item from inventory, the item moves directly from the receiving to the shipping dock, saving shelving and picking transactions. While cross docking reduces shelving and picking costs, it risks changing customer expectations for how soon a product will be delivered. Given customer order arrivals random in quantity and due dates, random replenishment arrivals, and costs (or benefits) for shipping a product early, we characterize the optimal decision as to whether to cross dock a replenishment item to fulfill demand that is not immediately due or to wait to (hopefully) cross dock in later periods. With multiple demands and due dates, the cross-docking decision depends on the number of unfulfilled demands in each period across the horizon, the number of units that have just arrived (available for cross docking), picking and shelving costs, and the delay cost (or benefit). We formulate the problem as a Markov decision process, determine the structure of the optimal policy, and propose a well-performing heuristic.

• Guo, S., G. Aydin, and G. C. Souza (2014), “Dismantle or Remanufacture?” European Journal of Operational Research, 233(3), 580-583.

Abstract In this paper we study a firm''s disposition decision for returned end-of-use products, which can either be remanufactured and sold, or dismantled into parts that can be reused. We formulate this problem as a multi-period stochastic dynamic program, and find the structure of the optimal policy, which consists of monotonic switching curves. Specifically, if it is optimal to remanufacture in a given period and for given inventory levels, then it is also optimal to remanufacture when the inventory of part(s) is higher or the inventory of remanufactured product is lower.

• Atasu, Atalay, and Gilvan C. Souza (2013), “How Does Product Recovery Affect Quality Choice?”Production and Operations Management, 22:4, 991–1010, July–August.
• Wang, W., M. Ferguson, S. Hu, and G. C. Souza (2013). "Dynamic Capacity Investment with Two Competing Technologies," Manufacturing & Service Operations Management, 15(4), 616-629.

Abstract With the recent focus on sustainability, firms making adjustments to their production or distribution capacity levels often have the option of investing in newer technologies with lower carbon footprints and/or energy consumption. These more sustainable technologies typically require a higher upfront investment but have lower operating (fuel or energy) costs. What complicates this decision is the fact that the projected dollar savings from the more sustainable technologies fluctuate considerably due to uncertainty in fuel prices and the total capacity may not be utilized at 100% because of fluctuations in the demand for the product. We consider the firm''s capacity adjustments over time given a portfolio of technology options when the demand and the fuel costs are stochastic and possibly dependent. Our model also allows for usage-based capacity deterioration. We provide the analytical structure of the optimal policy, which assigns different control limits for investing, staying put, and disinvesting in the capacities of the competing technology choices for each realization of demand and fuel costs at each period. We also present an application of our model to the problem of designing a delivery truck fleet for a beverage distributor.

• Abbey, James, V. Daniel Guide, Jr., and Gilvan C. Souza (2013), “Delayed Differentiation for Multiple Lifecycle Products.” Production and Operations Management, Vol. 22, No. 3, pp. 588–602.
• Souza, Gilvan C., (2012), Sustainable Operations and Closed-Loop Supply Chains, Business Expert Press, New York, NY.
• Ferguson, M. and G. Souza (eds.) (2010), Closed-Loop Supply Chains: New Developments to Improve the Sustainability of Business Practices, Boca Ratton, FL: CRC Press.
• Ferguson, Mark, V. Daniel Guide, Jr., Eylem Koca, and Gilvan C. Souza (2009), “The Value of Quality Grading in Remanufacturing,” Production and Operations Management, Vol. 18, No. 3, pp. 300-314.

Abstract In this paper we consider a tactical production-planning problem for remanufacturing when returns have different quality levels. Remanufacturing cost increases as the quality level decreases, and any unused returns may be salvaged at a value that increases with their quality level. Decision variables include the amount to remanufacture each period for each return quality level and the amount of inventory to carry over for future periods for both returns (unremanufactured), and finished remanufactured products. Our model is grounded with data collected at Pitney-Bowes from their mailing systems remanufacturing operations. We derive some analytic properties for the optimal solution in the general case, and provide a simple greedy heuristic to computing the optimal solution in the case of deterministic returns and demand. Under mild assumptions, we find that the firm always remanufactures the exact demand in each period. We also study the value of a nominal quality-grading system in planning production. Based on common industry parameters, we analyze, via a numerical study, the increase in profits observed by the firm if it maintains separate inventories for each quality grade. The results show that a grading system increases profit by an average of 4% over a wide range of parameter values commonly found in the remanufacturing industry; this number increases as the returns volume increases. We also numerically explore the case where there are capacity constraints and find the average improvement of a grading system remains around 4%.

• Guide, V. Daniel, Jr., Gilvan C. Souza, Luk Van Wassenhove, and Joseph D. Blackburn (2006), "Time Value of Commercial Product Returns," Management Science, Vol. 52, No. 8, pp. 1200-1214.

Abstract Manufacturers and their distributors must cope with an increased flow of returned products from their customers. The value of commercial product returns, which we define as products returned for any reason within 90 days of sale, now exceeds $100 billion annually in the United States. Although the reverse supply chain of returned products represents a sizeable flow of potentially recoverable assets, only a relatively small fraction of the value is currently extracted by manufacturers; a large proportion of the product value erodes away because of long processing delays. Thus, there are significant opportunities to build competitive advantage from making the appropriate reverse supply chain design choices. In this paper, we present a network flow with delay models that includes the marginal value of time to identify the drivers of reverse supply chain design. We illustrate our approach with specific examples from two companies in different industries and then examine how industry clockspeed generally affects the choice between an efficient and a responsive returns network.

• Ferguson, Mark, V. Daniel Guide, Jr., and Gilvan C. Souza (2006), “Supply Chain Coordination for False Failure Returns,” Manufacturing & Service Operations Management, Vol. 8, No. 4, pp. 376-393.

Abstract False failure returns are products that are returned by consumers to retailers with no functional or cosmetic defect. The cost of a false failure return includes the processing actions of testing, refurbishing (if necessary), repackaging, the loss in value during the time the product spends in the reverse supply chain (a time that can exceed several months for many firms), and the loss in revenue because the product is sold at a discounted price. This cost is significant and is incurred primarily by the manufacturer. Reducing false failure returns, however, requires effort primarily from the retailer, for example informing consumers about the exact product that best fits their needs. We address the problem of reducing false failure returns via supply chain coordination methods. Specifically, we propose a target rebate contract that pays the retailer a specific dollar amount per each unit of false failure returns below a target. This target rebate provides an incentive to the retailer to increase her effort, thus decreasing the number of false failures and (potentially) increasing net sales. We show that this contract is Pareto improving in the majority of cases. Our results also indicate that the profit improvement to both parties, and the supply chain, is substantial.

• Souza, Gilvan C., Barry L. Bayus, and Harvey M. Wagner (2004), "New-Product Strategy and Industry Clockspeed," Management Science, Vol. 50, No. 4, April, pp. 537-549.

Abstract We study how industry clockspeed, internal firm factors, such as product development, production, and inventory costs, and competitive factors determine a firm''s optimal new-product introduction timing and product-quality decisions. We explicitly model market demand uncertainty, a firm''s internal cost structure, and competition, using an infinite-horizon Markov decision process. Based on a large-scale numerical analysis, we find that more frequent new-product introductions are optimal under faster clockspeed conditions. In addition, we find that a firm''s optimal product-quality decision is governed by a firm''s relative costs of introducing new products with incremental versus more substantial improvements. We show that a time-pacing product introduction strategy results in a production policy with a simple base-stock form and performs well relative to the optimal policy. Our results thus provide analytical support for the managerial belief that industry clockspeed and time to market are closely related.

• Blackburn, Joseph, V. Daniel Guide, Jr., Gilvan C. Souza, and Luk Van Wassenhove (2004), "Reverse Supply Chains for Commercial Returns," California Management Review, Vol. 46, No. 2, pp. 6-22.

Abstract The flow of product returns is becoming a significant concern for manufacturers. Typically, these returns have been viewed as a nuisance, resulting in reverse supply chains that are designed to minimize costs. These minimum cost reverse supply chains often do not consider product return speed. The longer it takes to retrieve a returned product, the lower the chances that there are financially attractive reuse options. Unlike forward supply chains, design strategies for reverse supply chains are unexplored and largely undocumented. The most influential product characteristic for reverse supply chain design is the marginal value of time. Responsive reverse supply chains are the appropriate choice when the marginal value of time for products is high, and efficient reverse supply chains are the proper choice when the marginal value of time for products is low. Product returns and their reverse supply chains represent a potential value stream and deserve as much attention as forward supply chains.

• Cattani, Kyle and Givlan C. Souza (2002), "Inventory Rationing and Shipment Flexibility Alternatives for Direct Market Firms," Production and Operations Management, Vol. 11, No. 4, pp. 441-457.

Abstract This paper investigates inventory-rationing policies of interest to firms operating in a direct market channel. We model a single product with two demand classes, where one class requests a lower order fulfillment lead time but pays a higher price. Demand for each class follows a Poisson process. Inventory is fed by a production system with exponentially distributed build times. We study rationing policies in which the firm either blocks or backlogs orders for the lower priority customers when inventory drops below a certain level. We compare the performance of these rationing policies with a pure first-come, first-serve policy under various scenarios for customer response to delay: lost sales, backlog, and a combination of lost sales and backlog.