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Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
Service, big data, machine learning
In this short paper, we discuss the impact of data analytics in services and delineate future research directions for the field. After illustrating how data analytics are transforming different service sectors, we consider the provision of data analysis as a service in its own right. We discuss how the very nature of data and certain features of the machine learning method give rise to new issues and pitfalls for the management of these services, which delineates as many future research directions. We also discuss the co-production of services by humans and machines, and call for more research on responsible data analytics services to tackle some of the most pressing ethical issues in our societies.
Copyright © 2020, INFORMS
ISSN (Online)
2164-3970
Journal Article
Operations Research
Saed Alizamir, Francis de Véricourt, Peng Sun
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
Sequential decision making, time pressure, information search, Bayesian inference
Arrow et al. (1949) introduced the first sequential search problem, “where at each stage the options available are to stop and take a definite action or to continue sampling for more information." We study how time pressure in the form of task accumulation may affect this decision problem. To that end, we consider a search problem where the decision maker (DM) faces a stream of random decision tasks to be treated one at a time, and accumulate when not attended to. We formulate the problem of managing this form of pressure as a Partially Observable Markov Decision Process, and characterize the corresponding optimal policy. We find that the DM needs to alleviate this pressure very differently depending on how the search on the current task has unfolded thus far. As the search progresses, the DM is less and less willing to sustain high levels of workloads in the beginning and end of the search, but actually increases the maximum workload she is willing to handle in the middle of the process. The DM manages this workload by first making a priori decisions to release some accumulated tasks, and later by aborting the current search and deciding based on her updated belief. This novel search strategy critically depends on the DM's prior belief about the tasks, and stems, in part, from an effect related to the decision ambivalence. These findings are robust to various extensions of our basic set-up.
© 2019, INFORMS
Journal Article
Management Science 66 (10): 4359–4919
2018 POMS HOCM Best Paper Award
Saed Alizamir, Francis de Véricourt, Shouqiang Wang (2020)
Subject(s)
Health and environment; Management sciences, decision sciences and quantitative methods
Keyword(s)
Information design, Bayesian persuasion game, dynamic programming, statistical decision, global health, disaster management
The World Health Organization seeks effective ways to alert its member states about global pandemics. Motivated by this challenge, we study a public agency’s problem of designing warning policies to mitigate potential disasters that occur with advance notice. The agency privately receives early information about recurring harmful events and issues warnings to induce an uninformed stakeholder to take preemptive actions. The agency’s decision to issue a warning critically depends on its reputation, which we define as the stake- holder’s belief regarding the accuracy of the agency’s information. The agency faces then a trade-off between eliciting a proper response today and maintaining its reputation in order to elicit responses to future events.
We formulate this problem as a dynamic Bayesian persuasion game, which we solve in closed form. We find that the agency sometimes strategically misrepresents its advance information about a current threat in order to cultivate its future reputation. When its reputation is sufficiently low, the agency downplays the risk and actually downplays more as its reputation improves. By contrast, when its reputation is high, the agency sometimes exaggerates the threat and exaggerates more as its reputation deteriorates. Only when its reputation is moderate does the agency send warning messages that fully disclose its private information.
Our study suggests a plausible and novel rationale for some of the false alarms or omissions observed in practice. We further test the robustness of our findings to imperfect advance information, disasters without advance notice, and heterogeneous receivers.
Copyright © 2020, INFORMS
Volume
66
Journal Pages
4359–4919
Journal Article
Management Science 65 (11): 4951–5448
Francis de Véricourt, Denis Gromb (2019)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
Capacity investment, optimal contracts, capital diversion, financial constraints, newsvendor model, moral hazard
We study a firm's capacity choice under demand uncertainty given it must finance this investment externally.
Sharing profits with investors causes governance problems affecting both capacity and demand: the firm may “steal" capital, which reduces effective capacity, and \shirk" on market-development, which reduces demand. We adopt an optimal contracting approach whereby the firm optimizes among feasible financial claims derived endogenously. We characterize its optimal financing and capacity choices. First, debt financing is optimal: it minimizes the incentives to both divert and shirk. Second, the firm underinvests (overinvests) if the effort problem is mild (severe) enough relative to the diversion problem. Thus, a worsening of the same governance problem can lead to over- or underinvestment depending on circumstances. Third, we find that the diversion and shirking problems interact in their impact on capacity investment. In particular, if the shirking problem is mild enough, the more severe the diversion problem, the less the firm invests. However, if the shirking problem is severe enough, the effect of diversion is reversed: the more severe the diversion problem, the more the firm invests.
Copyright © 2019, INFORMS
Volume
65
Journal Pages
4951–5448
Journal Article
Management Science 65 (3): 955–1453
Tian Chan, Francis de Véricourt, Omar Besbes (2019)
Subject(s)
Product and operations management
Keyword(s)
Health care, contracting, fine balance matching, service value chain
Maintenance service plans (MSPs) are contracts for the provision of maintenance by a service provider to an equipment operator. These plans can have different payment structures and risk allocations, which induce various types of incentives for agents in the service chain. How do such structures affect service performance and service chain value? We provide an empirical answer to this question by using a unique panel data covering the sales and service records of more than 700 diagnostic body scanners. We exploit the presence of a standard warranty period and employ a matching approach to isolate the incentive effects of MSPs from the confounding effects of endogenous contract selection. We find that moving the equipment operator from a basic, pay-per-service plan to a fixed-fee, full-protection plan not only reduces reliability but also increases equipment service costs. Furthermore, that increase is driven by both the operator and the service provider. Our results indicate that incentive effects arising from MSPs leads to losses in service chain value, and we provide the first evidence that a basic pay-per-service plan—under which risk of equipment failure is borne by the operator—can improve performance and reduce costs.
Copyright © 2019, INFORMS
Volume
65
Journal Pages
955–1453
Journal Article
Manufacturing and Service Operations Management 20 (1): 85–96
Special Issue on Interface of Finance, Operations, and Risk Management (Winter 2018)
Francis de Véricourt, Denis Gromb (2018)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
Capacity, optimal contracts, financial constraints, newsvendor model
We study the capacity choice problem of a firm, whose access to capital is hampered by financial frictions, i.e., moral hazard. The firm optimizes both its capacity investment under demand uncertainty and its sourcing of funds from a competitive investor. Ours is the first study of this problem to adopt an optimal contracting approach: feasible sources of funds are derived endogenously from fundamentals and include standard financial claims (debt, equity, convertible debt, etc.). Thus, in contrast to most of the literature on financing capacity investments, our results are robust to a change of financial contract. We characterize the optimal capacity level under optimal financing. First, we find conditions under which a feasible financial contract exists that achieves first-best. When no such contract exists, we find that under optimal financing, the choice of capacity sometimes exceeds strictly the efficient level. Further, the firm invests more when its cash is low, and in some cases less when the project’s unit revenue is high. These results run counter to the newsvendor logic and standard finance arguments. We also show that our main results hold in the case of a strategic monopolist investor, and such an investor may invest more than a competitive one.
© 2017, INFORMS
Volume
20
Journal Pages
85–96
Journal Article
Operations Research 64 (2): 371–389
2018 INFORMS ENRE Best Paper Award Environment and Sustainability
Shouqiang Wang, Peng Sun, Francis de Véricourt (2016)
Subject(s)
Management sciences, decision sciences and quantitative methods; Product and operations management
Keyword(s)
Dynamic mechanism design, optimal control, asymmetric information, environmental regulation, voluntary disclosure
This paper studies the design of voluntary disclosure regulations for a firm that faces a stochastic environmental hazard. The occurrence of such a hazard is known only to the firm. The regulator, if finding a hazard, collects a fine and mandates the firm to perform costly remediation that reduces the environmental damage. The regulator may inspect the firm at any time to uncover the hazard. However, because inspections are costly, the regulator also offers a reward to the firm for voluntarily disclosing the hazard. The reward corresponds to either a subsidy or a reduced fine, depending on whether it is positive or negative. Thus, the regulator needs to dynamically determine the reward and inspection policy that minimizes expected societal cost in the long run. We model this problem as a dynamic adverse selection problem with costly state verification in continuous time. Despite the complexity and generality of this setup, we show that the optimal regulation policy follows a very simple cyclic structure, which we fully characterize in closed form. Specifically, the regulator runs scheduled inspections periodically. After each inspection, the reward level decreases over time until a subsequent inspection takes place. If a hazard is not revealed, the reward level is reset to a high level, restarting the cycle. In contrast to the reward level, the mandated remediation level is constant over time. Nonetheless, when subsidies are not allowed in the industry, we show that the regulator should dynamically adjust this remediation level, which then acts as a substitute for a subsidy. Our analysis further reveals that optimal inspection frequency increases not only when the inspection accuracy decreases, but also when the penalty for not disclosing the hazard increases.
© 2016 INFORMS
Volume
64
Journal Pages
371–389
Journal Article
American Economic Review 106 (2): 316–358
Published as NBER Working Paper No. 19849 under the title Productivity response to a contract change
2016 KfW Research Prize for Excellence
Subject(s)
Economics, politics and business environment
Keyword(s)
Labor contracts, incentives, behavioral economics, plantations
JEL Code(s)
D82, D86, J33, J41, J43, O13, Q12
We study a contract change for tea pluckers on an Indian plantation, with a higher government-stipulated baseline wage. Incentive piece rates were lowered or kept unchanged. Yet, in the following month, output increased by 20 to 80 percent. This response contradicts the standard model and several variants, is only partly explicable by greater supervision, and appears to be "behavioral." But in subsequent months, the increase is comprehensively reversed. Though not an unequivocal indictment of "behavioral" models, these findings suggest that nonstandard responses may be ephemeral, and should ideally be tracked over an extended period of time.
Copyright © 2016 by the American Economic Association.
Volume
106
Journal Pages
316–358
Journal Article
Operations Research 64 (1): 52–66
Saed Alizamir, Francis de Véricourt, Peng Sun (2016)
Subject(s)
Management sciences, decision sciences and quantitative methods; Product and operations management
Keyword(s)
Technology diffusion, government incentive policies, renewable energy technology, feed-in tariff, learning-by-doing, dynamic programming
Feed-in-tariff (FIT) policies aim at driving down the cost of renewable energies by fostering learning and accelerating the diffusion of green technologies. Under FIT mechanisms, governments purchase green energy at tariffs that are set above market price. The success or failure of FIT policies, in turn, critically depend on how these tariffs are determined and adjusted over time. This paper provides insights into designing cost-efficient and socially-optimal FIT programs. Our modeling framework captures key market dynamics as well as investors' strategic behavior. In this framework, we establish that the current practice of maintaining constant profitability is theoretically rarely optimal. By contrast, we characterize a no-delay region in the problem's parameters, such that profitability should strictly decrease over time if the diffusion and learning rates belong to this region. In this case, investors never strategically postpone their investment to a later period. When the diffusion and learning rates fall outside the region, profitability should increase at least temporarily over some time periods and strategic delays occur. The presence of strategic delays, however, makes the practical problem of computing optimal FIT schedules very difficult. To address this issue, the regulator may focus on policies that disincentivize investors to postpone their investment. With this additional constraint, a constant profitability policy is optimal if and only if the diffusion and learning rates fall outside the no-delay region. This provides partial justifications for current FIT implementations.
© 2015 INFORMS
Volume
64
Journal Pages
52–66
Journal Article
Manufacturing and Service Operations Management 16 (1): 119–132
Liu Yang, Francis de Véricourt, Peng Sun (2014)
Subject(s)
Product and operations management
Keyword(s)
Waiting time competition; benchmark effect; loss aversion; queues; game theory
We consider a duopoly where firms compete on waiting times in the presence of an industry benchmark. The demand captured by a firm depends on the gap between the firm's offer and the benchmark. We refer to the benchmark effect as the impact of this gap on demand. The formation of the benchmark is endogenous and depends on both firms' choices. When the benchmark is equal to the shorter of the two offered delays, we characterize the unique Pareto optimal Nash equilibrium. Our analysis reveals a stickiness effect in which firms equate their delays at the equilibrium when the benchmark effect is sufficiently strong. When the benchmark corresponds to a weighted average of the two offered delays, we show the existence of a pure Nash equilibrium. In this case, we reveal a reversal effect, in which the market leader, i.e., the firm that offers a shorter delay, becomes the follower when the benchmark effect is sufficiently strong. In both cases, we show that customers' equilibrium waiting times are shorter with the benchmark effect than without it. Our models also capture customers' loss aversion, which, in our setting, states that demand is more sensitive to the gap between the delay and the benchmark when the delay is longer than the benchmark (loss) than when it is shorter (gain). We characterize the impact of this loss aversion on the equilibrium in both settings. Finally, we show numerically that the stickiness and reversal effects still exist when firms also compete on price.
© 2014 INFORMS
Volume
16
Journal Pages
119–132
Journal Article
Management Science 59 (1): 157–171
Saed Alizamir, Francis de Véricourt, Peng Sun (2013)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
service operations, queueing theory, dynamic programming, decision making, information search, Bayes' rule
In diagnostic services, agents typically need to weigh the benefit of running an additional test and improving the accuracy of diagnosis against the cost of delaying the provision of services to others. Our paper analyzes how to dynamically manage this accuracy/congestion trade-off. To that end, we study an elementary congested system facing an arriving stream of customers. The diagnostic process consists of a search problem in which the service provider conducts a sequence of imperfect tests to determine the customer's type. We find that the agent should continue to perform the diagnosis as long as her current belief that the customer is of a given type falls into an interval that depends on the congestion level as well as the number of performed tests thus far. This search interval should shrink as congestion intensifies and as the number of performed tests increases if additional conditions hold. Our study reveals that, contrary to diagnostic services without congestion, the base rate (i.e., the prior probability of the customer type) has an effect on the agent's search strategy. In particular, the optimal search interval shrinks when customer types are more ambiguous a priori, i.e., as the base rate approaches the value at which the agent is indifferent between types. Finally, because of congestion effects, the agent should sometimes diagnose the customer as being of a given type, even if test results indicate otherwise. All these insights disappear in the absence of congestion.
© 2013 INFORMS
This publication was a finalist of the 2016 Service SIG Best Paper Competition.
Volume
59
Journal Pages
157–171
Journal Article
Journal of Operations Management 31 (1/2): 86–92
Francis de Véricourt, Kriti Jain, J. Neil Bearden, Allan Filipowicz (2013)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
newsvendor, risk aversion, gender difference, behavioral operations
We present results from two experiments that reveal significant gender differences in ordering behavior in the newsvendor problem. In high margin settings, males tend to order more than females, and they also tend to achieve higher profits. There are no gender differences in low margin settings. We show that the observed gender differences are partially driven by (or mediated by) gender differences in risk appetite. Males tend to prefer taking greater risk than women, and this leads them to order more in the newsvendor problem (in high margin settings). We show that the risk-ordering relationship is related to financial risk attitudes but not to social risk attitudes, and also that the effect is not driven by gender differences in affect, a likely alternative explanation for the results.
With permission of Elsevier
Volume
31
Journal Pages
86–92
Journal Article
Operations Research 59 (6): 1320–1331
Francis de Véricourt, Otis B. Jennings (2011)
Subject(s)
Management sciences, decision sciences and quantitative methods; Product and operations management
Keyword(s)
queueing system, health care, public policy, nursing, staffing, many-server limit theorems
In this paper, we present a closed queueing model to determine efficient nurse staffing policies. We explicitly model the workload experienced by s nurses within a single medical unit with n homogeneous patients as a closed M/M/s//n queueing system, where each patient alternates between requiring assistance and not. The performance of the medical unit is based on the probability of excessive delay, the relative frequency with which the delay between the onset of patient neediness and the provision of care from a nurse exceeds a given time threshold. Using new many-server asymptotic results, we find that effective staffing policies should deviate from threshold-specific nurse-to-patient ratios by factors that take into account the total number of patients present in the unit. In particular, our staffing rule significantly differs from California Bill AB 394, legislation that mandates fixed nurse-to-patient staffing ratios. Simulations show that our results are robust to delay-dependent service times, generally distributed service times, and nonhomogeneous patients, i.e., those with different acuity levels.
© 2011 INFORMS
Volume
59
Journal Pages
1320–1331
Journal Article
IIE Transactions 41 (12): 1096–1109
Jean-Philippe Gayon, Francis de Véricourt, Fikri Karaesmen (2009)
Subject(s)
Product and operations management
Keyword(s)
Inventory rationing, optimal control, queuing theory
Volume
41
Journal Pages
1096–1109
Journal Article
Manufacturing and Service Operations Management 11 (1): 128–143
2011 INFORMS Best Paper Award
Jean-Philippe Gayon, Saif Benjaafar, Francis de Véricourt (2009)
Subject(s)
Product and operations management
Keyword(s)
advance demand information, production-inventory systems, inventory rationing, make-to-stock
We consider a make-to-stock supplier that operates a production facility with limited capacity. The supplier receives orders from customers belonging to several demand classes. Some of the customer classes share advance demand information with the supplier by announcing their orders ahead of their due date. However, this advance demand information is not perfect because the customer may decide to order prior to or later than the expected due date or may decide to cancel the order altogether. Customer classes vary in their demand rates, expected due dates, cancellation probabilities, and shortage costs. The supplier must decide when to produce and, whenever an order becomes due, whether or not to satisfy it from on-hand inventory. Hence, the supplier is faced with a joint production-control and inventory-allocation problem. We formulate the problem as a Markov decision process and characterize the structure of the optimal policy. We show that the optimal production policy is a state-dependent base-stock policy with a base-stock level that is nondecreasing in the number of announced orders. We show that the optimal inventory-allocation policy is a state-dependent multilevel rationing policy, with the rationing level for each class nondecreasing in the number of announced orders (regardless of whether the class provides advance information). From numerical results, we obtain several insights into the value of advance demand information for both supplier and customers.
© 2009 INFORMS
Volume
11
Journal Pages
128–143
Journal Article
Mathematical Biosciences 222 (1): 1–20
Shouqiang Wang, Francis de Véricourt, Peng Sun (2009)
Subject(s)
Product and operations management
Keyword(s)
epidemic control, game theory, optimization
This paper examines how two countries would allocate resources at the onset of an epidemic when they seek to protect their own populations by minimizing the total number of infectives over the entire time horizon. We model this situation as a game between selfish countries, where players strategically allocate their resources in order to minimize the total number of infected individuals in their respective populations during the epidemic. We study this problem when the initial number of infectives is very small, which greatly simplifies the analysis. We show in this framework that selfish countries always allocate their resources so as to bring the effective reproduction ratio below one and avoid a major outbreak. When a major outbreak is avoidable, we further identify the necessary and sufficient conditions under which the individual allocation decisions of selfish countries match the decision that a central planner would make in order to minimize the total number of infectives in the whole population (without distinguishing between countries).
With permission of Elsevier
Volume
222
Journal Pages
1–20
Journal Article
Operations Research 57 (6): 1320–1332
Peng Sun, Liu Yang, Francis de Véricourt (2009)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
epidemic control, influenza, Reed-Frost model, supermodular games
Recent epidemiologic studies have suggested that the prophylactic use of antiviral drugs or imperfect vaccines could slow down the spread of an influenza epidemic. Since drug stockpiles are presently scattered in different countries, the outbreak of an epidemic gives rise to a game in which each country must make decisions about how best to allocate its own stockpile in order to protect its population. We develop a two-period multivariate Reed-Frost model to represent the spread of the epidemic within and across countries at its onset. Our model captures three critical sources of uncertainty: the number of initial infections, the spread of the disease, and drug efficacy. We show that for small between-country infection rates, the underlying game is supermodular and that a unique Pareto optimal Nash equilibrium exists. In this equilibrium, some countries give up all their drugs to protect the population where the epidemic first appeared, while all others keep their stockpiles for themselves. Further, we identify sufficient conditions under which the optimal solution of a central planner (such as the World Health Organization) constitutes a Pareto improvement over the decentralized equilibrium, suggesting that countries could agree on an allocation scheme which would benefitt everyone. By contrast, when the central planner's solution does not constitute a Pareto improvement, minimizing the total number of infected persons globally requires some countries to sacrifice part of their own population, which raises intriguing ethical issues. Preliminary numerical studies also indicate that similar results hold for the duration of the pandemic, with the difference that countries seem willing to give up their drug stockpiles for more sets of parameters than in the two-period case.
© 2009 INFORMS
Volume
57
Journal Pages
1320–1332
Journal Article
Operations Research 57 (5): 1114–1128
Francis de Véricourt, Miguel Sousa Lobo (2009)
Subject(s)
Product and operations management
Keyword(s)
capacity allocation, revenue management, dynamic pricing, nonprofit
Nonprofit firms sometimes engage in for-profit activities for the purpose of generating revenue to subsidize their mission activities. The organization is then confronted with a consumption versus investment trade-off, where investment corresponds to providing capacity for revenue customers, and consumption corresponds to serving mission customers. Exemplary of this approach are the Aravind Eye Hospitals in India, where profitable paying hospitals are used to subsidize care at free hospitals. We model this problem as a multiperiod stochastic dynamic program. In each period, the organization must decide how much of the current assets should be invested in revenue-customer service capacity, and at what price the service should be sold. We provide sufficient conditions under which the optimal capacity and pricing decisions are of threshold type. Similar results are derived when the selling price is fixed, but the banking of assets from one period to the next is allowed. We compare the performance of the optimal threshold policy with heuristics that may be more appealing to managers of nonprofit organizations, and we assess the value of banking and of dynamic pricing through numerical experiments.
© 2009 INFORMS
Volume
57
Journal Pages
1114–1128
Journal Article
Operations Research 56 (3): 562–575
Fernando Bernstein, Francis de Véricourt (2008)
Subject(s)
Product and operations management
Keyword(s)
facilities/equipment planning capacity expansion, games noncooperative, inventory/production multi-item, queues priority
We consider a market with two suppliers and a set of buyers in search of procurement contracts with one of the suppliers. In particular, each buyer needs to process a certain volume of work, and each supplier's ability to process the customers' requests is constrained by a production capacity. The procurement contracts include guarantees that the products will be available when needed, and the buyers select a supplier based on their service delivery offers. The suppliers are modeled as make-to-stock queues and compete for the buyers' business. The main objective of this paper is to determine how the procurement contracts are established between buyers and suppliers. Because each buyer selects a single supplier to establish the sourcing relationship, the game fails to have a pure-strategy Nash equilibrium. Instead, an equilibrium is defined as the limit equilibrium of some discrete action games.
© 2008 INFORMS
Volume
56
Journal Pages
562–575
Journal Article
Management Science 54 (2): 354–368
O. Zeynep Aksin, Francis de Véricourt, Fikri Karaesmen (2008)
Subject(s)
Product and operations management
Keyword(s)
call center, outsourcing, subcontracting, contract choice, capacity investment, pricing
This paper considers a call center outsourcing contract analysis and choice problem faced by a contractor and a service provider. The service provider receives an uncertain call volume over multiple periods and is considering outsourcing all or part of these calls to a contractor. Each call brings in a fixed revenue to the service provider. Answering calls requires having service capacity; thus implicit in the outsourcing decision is a capacity decision. Insufficient capacity implies that calls cannot be answered, which in turn means there will be a revenue loss. Faced with a choice between a volume-based and a capacity-based contract offered by a contractor that has pricing power, the service provider determines optimal capacity levels. The optimal price and capacity of the contractor together with the optimal capacity of the service provider determine optimal profits of each party under the two contracts being considered. This paper characterizes optimal capacity levels and partially characterizes optimal pricing decisions under each contract. The impact of demand variability and the economic parameters on contract choice are explored through numerical examples. It is shown that no contract type is universally preferred and that operating environments as well as cost-revenue structures have an important effect.
© 2008 INFORMS
Volume
54
Journal Pages
354–368
Journal Article
Operations Research 56 (1): 173–187
Francis de Véricourt, Otis B. Jennings (2008)
Subject(s)
Product and operations management
Keyword(s)
diffusion models queues, limit theorems, staffing stochastic model applications, service operation
Motivated by workforce planning problems in health care, professional, warranty, and repair services, we propose modeling service centers that are exclusively dedicated to fixed client constituencies as closed multiserver queueing systems, a framework we refer to as membership services. We provide fluid and diffusion approximations of the number of users within the membership who are requesting service. The approximations are obtained via many-server limit theorems, where the limiting regime assumptions of each theorem correspond to a particular staffing strategy a manager might employ. Accordingly, we propose staffing rules designed to meet a certain desired performance criterion. In particular, when the objective is to minimize the staffing size subject to a constraint on the probability of delay for a service-requesting customer, we suggest staffing rules inspired by the so-called quality- and efficiency-driven (QED), or Halfin-Whitt, limiting regime. Numerical evaluations of our proposed QED scheme indicate that, although justified for large systems, the staffing rule performs well for memberships of all sizes.
© 2008 INFORMS
Volume
56
Journal Pages
173–187
Journal Article
Queueing Systems 52 (3): 189–191
Francis de Véricourt, Yong-Pin Zhou (2006)
Subject(s)
Product and operations management
Keyword(s)
multiple heterogeneous servers, slow server problem
Volume
52
Journal Pages
189–191
Journal Article
Operations Research 53 (6): 968–981
Francis de Véricourt, Yong-Pin Zhou (2005)
Subject(s)
Product and operations management
Keyword(s)
dynamic programming/optimal control, Markov infinite state, probability stochastic model applications, queues Markovian, multichannel
Traditional research on routing in queueing systems usually ignores service quality related factors. In this paper, we analyze the routing problem in a system where customers call back when their problems are not completely resolved by the customer service representatives (CSRs). We introduce the concept of call resolution probability, and we argue that it constitutes a good proxy for call quality. For each call, both the call resolution probability (p) and the average service time (1/µ) are CSR dependent. We use a Markov decision process formulation to obtain analytical results and insights about the optimal routing policy that minimizes the average total time of call resolution, including callbacks. In particular, we provide sufficient conditions under which it is optimal to route to the CSR with the highest call resolution rate (pµ) among those available. We also develop efficient heuristics that can be easily implemented in practice.
© 2006 INFORMS
Volume
53
Journal Pages
968–981
Journal Article
Management Science 50 (10): 1431–1448
Saif Benjaafar, Mohsen ElHafsi, Francis de Véricourt (2004)
Subject(s)
Product and operations management
Keyword(s)
production/inventory systems, queueing systems, generalized assignment problem, multi-item/multifacility systems
We consider the problem of allocating demand arising from multiple products to multiple production facilities with finite capacity and load-dependent lead times. Production facilities can choose to manufacture items either to stock or to order. Products vary in their demand rates, holding and backordering costs, and service-level requirements. We develop models and solution procedures to determine the optimal allocation of demand to facilities and the optimal inventory level for products at each facility. We consider two types of demand allocation, one in which we allow the demand for a product to be split among multiple facilities and the other in which demand from each product must be entirely satisfied by a single facility. We also consider two forms of inventory warehousing, one in which inventory locations are factory based and one in which they are centralized. For each case, we offer a solution procedure to obtain optimal demand allocations and optimal inventory base-stock levels. For systems with multiple customer classes, we also determine optimal inventory rationing levels for each class for each product. We use the models to characterize analytically several properties of the optimal solution. In particular, we highlight eight principles that relate the effects of cost, congestion, inventory pooling, multiple sourcing, customer segmentation, inventory rationing, and process and demand variability.
© 2004 INFORMS
Volume
50
Journal Pages
1431–1448
Subject(s)
Product and operations management
Keyword(s)
ergonomics & human factors, logistics, operations research, plant engineering, production systems, quality control & reliability
Volume
36
Journal Pages
221–236
Journal Article
Queueing Systems 43 (3): 251–266
Michael H. Veatch, Francis de Véricourt (2003)
Subject(s)
Product and operations management
Keyword(s)
make-to-stock queue, hedging points, just-in-time
Volume
43
Journal Pages
251–266
Journal Article
Management Science 48 (11): 1486–1501
Francis de Véricourt, Fikri Karaesmen, Yves Dallery (2002)
Subject(s)
Product and operations management
Keyword(s)
inventory/production stock allocation, stochastic multi-class, queues make-to-stock system
We consider the dynamic scheduling of a two-part-type make-to-stock production system using the model of Wein. Exogenous demand for each part type is met from finished goods inventory; unmet demand is backordered. The control policy determines which part type, if any, to produce at each moment; complete flexibility is assumed. The objective is to minimize average holding and backorder costs. For exponentially distributed interarrival and production times, necessary and sufficient conditions are found for a zero-inventory policy to be optimal. This result indicates the economic and production conditions under which a simple make-to-order control is optimal. Weaker results are given for the case of general production times.
© 2002 INFORMS
Volume
48
Journal Pages
1486–1501
Journal Article
Manufacturing and Service Operations Management 3 (2): 105–121
Francis de Véricourt, Fikri Karaesmen, Yves Dallery (2001)
Subject(s)
Management sciences, decision sciences and quantitative methods
Keyword(s)
inventory/production: optimal policies, stock allocation; queues: make-to-stock system
We consider a manufacturing facility that produces a single item that is demanded by several different classes of customers. The inventory-related cost performance of such a system can be improved by effective allocation of production and inventories. We obtain the optimal parameters for three easily implementable allocation policies. Our results cover the case of linear backorder costs as well as fill-rate constraints. We compare the optimal performance of these control policies to gain insights into the benefits of different production and stock-allocation rules.
© 2001 INFORMS
Volume
3
Journal Pages
105–121
Journal Article
Operations Research 48 (5): 811–819
Francis de Véricourt, Fikri Karaesmen, Yves Dallery (2000)
Subject(s)
Product and operations management
Keyword(s)
production/scheduling, stochastic: multi-item. queues: make-to-stock system. inventory/production: optimal policies
We consider the problem of dynamically allocatingproduction capacity between two products to minimize the average inventory and backorder costs per unit time in a make-to-stock single machine system. Using sample path comparisons and dynamic programming, we give a characterization of the optimal hedging point policy for a certain region of the state space. The characterization is simple enough to lead to easily implementable heuristics and provides a formal justi)cation of some of the earlier heuristics proposed.
© 2000 INFORMS
Volume
48
Journal Pages
811–819
Journal Article
IEEE Transactions on Automatic Control 45 (2): 309–311
Francis de Véricourt, Yves Dallery (2000)
Subject(s)
Product and operations management
Keyword(s)
multiple part type, stochastic scheduling, unreliable manufacturing systems
Volume
45
Journal Pages
309–311
Journal Article
Logistique et Management 7 (1): 57–66
Francis de Véricourt, Yves Dallery (1999)
Subject(s)
Product and operations management
Keyword(s)
product and operations management
Volume
7
Journal Pages
57–66