Serguei Netessine Research Articles

Introduction to the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management

AboutSectionsRequest Access ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to Section HomeManufacturing & Service Operations ManagementVol. 24, No. 6 Introduction to the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations ManagementSerguei Netessine , Christopher Tang , Michael Toffel Serguei Netessine , Christopher Tang , Michael Toffel Published Online:7 Oct 2022https://doi.org/10.1287/msom.2022.1155"Introduction to the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management." Manufacturing & Service Operations Management, 24(6), pp. 2797–2798 Back to Top Next FiguresReferencesRelatedInformation Volume 24, Issue 6November-December 2022Pages 2797-3306, C2 Article Information Metrics Information Received:September 14, 2022Accepted:September 14, 2022Published Online:October 07, 2022 Copyright © 2022, INFORMSCite asSerguei Netessine, Christopher Tang, Michael Toffel (2022) Introduction to the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management. Manufacturing & Service Operations Management 24(6):2797-2798. https://doi.org/10.1287/msom.2022.1155 PDF download

Leadership and Productivity: A Study of U.S. Automobile Assembly Plants

We examine the effect of plant managers on productivity using unique matched manager-plant panel data on U.S. auto-assembly plants during 1993–2007. Our econometric approach is two-pronged. Our first approach relies on using the panel nature of our data to measure variation in productivity due to managerial influence. We estimate the interquartile range of the effect of individual plant managers on average hours-per-vehicle to be about 30%. Further, we find that plant managers’ experience with the models that are in production ameliorates the negative impact of new model introductions on productivity. We also observe evidence that managers’ plant-specific tenure has a positive impact on productivity. In our second approach, we use high-frequency time-series data, along with structural-break tests and machine-learning methodologies, to predict variation in production using plant-manager switches. We find that a plant manager’s identity is predictive of changes in both the mean and variance of production, further highlighting their channels of managerial influence. These findings are robust to narrowing the sample to focus on retirements as an exogenous source of managerial switches. This paper was accepted by Serguei Netessine, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.4427 .

Competition in Congested Service Networks with Application to Air Traffic Control Provision in Europe

We analyze congested network-based markets and their impact on competition, equilibrium charges and efficiency. Several strategies are explored including price caps, mergers and investments in new technologies. We find that congested networks served by collaborating (serial) and competing (parallel) firms may lead to excessive prices. Additionally, oligopolists may only serve captive demand, leading to inefficiently low flows. Perhaps surprisingly, permitting a firm with market power to horizontally integrate with a competitor may improve efficiency. We also show that price caps in congested networks are ineffective due to their failure to signal the existence of scarce resources. Instead, partial vertical integration may prove beneficial by creating incentives to expand capacity through technology adoption, provided the price cap regime is dropped. The model is subsequently illustrated with a case study of air traffic control provision in Western Europe, in which it is shown that substantial changes in the regulation are required in order to create a more cost efficient sector with increased capacity. This paper was accepted by Serguei Netessine, operations management.

The Impact of Decision Rights on Innovation Sharing

Although innovation sharing between a buyer and a supplier—a common practice in the automotive industry—can increase the efficiency and total profit of a supply chain, suppliers are often reluctant to do so. Sharing innovations would leave the supplier in a vulnerable position if the buyer were to exploit the information (e.g., by resharing the supplier’s innovation with competing suppliers). Anecdotal evidence from automotive suppliers tells us that the nature of a supplier-buyer relationship for the most part depends on who (e.g., a short-run-focused procurement manager or a long-term-focused engineer) manages the relationship. In this paper, we examine how the allocation of decision rights to short-run- and long-run-focused employees affects collaboration between the firms. To accomplish this, we model a relationship between a supplier and a buyer where the buyer is a dual decision maker, consisting of long-run- and/or short-run-focused employees. We characterize the equilibrium of this model and show that the frequency of collaborative outcomes is lowest when the procurement manager has full control and highest when the engineer has full control or in a setup where employees can unilaterally enforce collaboration. A laboratory experiment confirms that collaborations occur more frequently when a manager with a long-term focus is in charge of or actively involved in decision making. Depending on how joint control is structured, joint control can help or hurt collaboration: Collaboration is highest when employees can unilaterally enforce it, whereas the random joint-control case results in collaboration that is as low as in the procurement manager control case. This paper was accepted by Serguei Netessine, operations management. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2021.4230 .

Delegating Innovation Projects with Deadline: Committed vs. Flexible Stopping

In many contexts such as product design and development, advertising, and scouting for technical solutions, clients seek the expertise of external providers to generate innovative solutions for their business problems. Because innovation projects are beset with uncertainty, they often require multiple iterations of ideation and evaluation. Although some clients make a commitment to take the first feasible solution from the provider, other clients retain the flexibility to seek more solutions until they decide to stop the project. Which of these policies is the better way to delegate an innovation project? To answer this question, we develop game-theoretic models that capture two salient aspects of delegated innovation projects: a deadline for the project and dynamic effort adjustment by the provider. We show that the flexible stopping policy, despite its intuitive appeal, may not always benefit the client. Specifically, the committed stopping policy is optimal when the provider is highly capable of generating solutions and when the client’s cost of evaluating solutions is in an intermediate range. In such situations, the committed stopping policy provides a stronger incentive to the provider to exert costly effort early on, which improves the quality of initial solutions. Considering endogenous payments, we show that the committed policy not only mitigates the provider’s tendency to postpone effort but also does so with a smaller payment. This paper was accepted by Serguei Netessine, operations management.

A Structural Estimation Approach to Study Agent Attrition

Worker attrition is a costly and operationally disruptive challenge throughout the world. Although large bodies of research have documented drivers of attrition and the operational consequences of attrition, managers still lack an integrated approach to understanding attrition and making decisions to address it on a forward-going basis. To fill this need, we build a structural model that both captures the firm’s decision to terminate a worker’s employment (involuntary attrition) and uses an optimal stopping problem process to model a worker’s decision to leave the firm (voluntary attrition). We then estimate the parameters of the model and conduct counterfactual analyses on the population of 1,118 agents serving one client over 3 years for an Indian business process management company. Our model reveals a number of interesting findings. We find that supervisors have a strong impact on whether employees stay because they reshape the way that agents make their decisions. We also find that the impact of supervisors on agent attrition is more significant than the impact of salary. For example, increasing salary by 20% decreases the total attrition level by 5%. However, if agents were managed by the best supervisors, among those that manage similar agents, the attrition rate decreases by 10%. Altogether, our paper contributes to the burgeoning literature on people operations and managerial practice. This paper was accepted by Serguei Netessine, operations management.

Service Design for a Holistic Customer Experience: A Process Framework

Modern service design practices conceptualize services as multistep processes. At each step, customers derive an uncertain value, which depends on a functional benefit and a subjective experience. The latter may depend on experiences realized at previous steps. Service designs determine the provider effort at each step given that customers prefer less-variable experiences, and enable a holistic perspective of the overall experience. We quantify two factors that shape service designs: the type of steps ((i) routine steps, where effort increases the functional benefit and decreases the experience variability, and (ii) nonroutine steps, where effort increases the functional benefit at the expense of higher variability) and a holistic coupling factor (at each step, the design is determined not only by experience realizations at predecessor steps but also by how it can shape subsequent experiences). The optimal efforts depend on the combination of these two factors, giving rise to actionable design rules. For a positive coupling factor, step type homogeneity leads to “spread the effort” designs (complementary efforts), whereas a negative coupling factor suggests focusing the effort on a few key steps at the expense of the rest of the service (substitutable efforts). Step type heterogeneity reverses these recommendations. Moreover, when the customer experience unfolds according to a nonstationary process with serial correlation, the effort at each step is determined by an impact zone defined by the steps surrounding the focal service step. Stronger correlation always induces higher effort, whereas weaker correlation may induce less effort in services with heterogeneous step types.This paper was accepted by Serguei Netessine, operations management.

Managing Supplier Social and Environmental Impacts with Voluntary Versus Mandatory Disclosure to Investors

A buying firm might in the future incur costs associated with a supplier’s carbon dioxide emissions, safety violations, or other social or environmental impacts. Learning about a supplier’s impacts requires costly effort, but it is necessary (and sometimes sufficient) to reduce those impacts. The capital market valuation of a buying firm reflects investors’ estimate of future costs associated with a supplier’s impacts, as well as any costs that the buying firm incurs in order to learn about and reduce a supplier’s impacts. This paper analyzes a game theoretic model in which a manager—with the objective of maximizing the capital market valuation of the buying firm—decides whether to learn about a supplier’s impacts, how much cost to incur to reduce the supplier’s impacts, and whether to disclose the supplier’s impacts to investors. The investors have rational expectations (e.g., that a manager might withhold bad news about the supplier’s impacts) and value the buying firm accordingly. The paper considers a mandate to disclose information learned about a supplier’s impacts. The paper shows that the disclosure mandate deters learning and thus, under plausible conditions, results in higher expected impacts. The disclosure mandate can result in lower expected impacts only if buying firms face moderately high future costs associated with suppliers’ impacts. In contrast, a disclosure mandate always increases a buying firm’s expected discounted profit and capital market valuation. A disclosure mandate can induce cooperation among buying firms with a shared supplier, yet result in higher expected impacts by the supplier. When a buying firm has alternative suppliers, the disclosure mandate favors commitment to a supplier to facilitate learning about that supplier’s impacts (instead of searching for a lower-impact supplier). This paper was accepted by Serguei Netessine, operations management.

Equity Contracts and Incentive Design in Start-Up Teams

Entrepreneurial teams assign equity positions in their start-ups using a term sheet that details equity splits and the conditions for being granted those splits. The design of equity split agreements has attracted considerable attention in the entrepreneurial community, with no convergence on a single preferred contract form. This paper experimentally examines the effectiveness of different contractual arrangements, focusing in particular on the effects of contract form and contracting timing on founder effort and on the value of the venture. Our results suggest that performance improves with the incentive strength of the contract, but they question the conventional logic that this effect is causal. Instead, we suggest a novel causal sequence. Rather than the contract form being the primitive and the behavior the derived consequence, our results suggest the reverse. The differences in contract performance are driven primarily by the sorting of high contributors into nonequal contracts and of low contributors into equal contracts; that is, equal contracts are bad for team performance not because of their incentive strength but because of the founder types that adopt them. Taken together, these results suggest that both investors and founders should pay as much (or more) attention to personality type as they do to contract form. This paper was accepted by Serguei Netessine, operations management.

Trust in Procurement Interactions

When complex procurement projects are conducted, it is often not possible to write complete contracts. As a consequence, the relationship between buyer and supplier is important for the success of the project. In this paper we investigate the claim that auctions in procurement can be detrimental for the buyer–supplier relationship, which is in line with the observation that reverse auctions are less frequently conducted if projects are complex. A poor relationship can result in a decrease in trust on the part of the buyer during the sourcing process and an increase in the supplier’s opportunistic behavior following sourcing. We consider a setting in which the winning supplier decides on the level of quality to provide to the buyer, and we compare a standard reverse auction and a buyer-determined reverse auction, both analytically and in the laboratory. We find that the buyer-determined reverse auction can perform better than the standard reverse auction from both the buyer’s and the suppliers’ perspective. In a buyer-determined reverse auction, it may be optimal for the buyer to select the supplier who submitted a higher bid, which may in turn induce this supplier to deliver higher quality. Standard auctions, however, yield lower prices but reduce cooperation. The degree of trust, as reflected by a larger number of transactions and a higher average efficiency of trade, is significantly higher in buyer-determined reverse auctions. Theoretical reasoning based on other-regarding preferences organizes our data well. This paper was accepted by Serguei Netessine, operations management.

A Balancing Act of Regulating On-Demand Ride Services

Regulating on-demand ride-hailing services (e.g., Uber and DiDi) requires a balance of multiple competing objectives: encouraging innovative business models (e.g., DiDi), sustaining traditional industries (e.g., taxi), creating new jobs, and reducing traffic congestion. This study is motivated by a regulatory policy implemented by the Chinese government in 2017 and a similar policy approved by the New York City Council in 2018 that regulate the “maximum” number of registered Uber/DiDi drivers. We examine the impact of these policies on the welfare of different stakeholders (i.e., consumers, taxi drivers, on-demand ride service company, and independent drivers). By analyzing a two-period dynamic game that involves these stakeholders, we find that, without government intervention, the on-demand ride service platform can drive the traditional taxi industry out of the market under certain conditions. Relative to no regulations and a complete ban policy, a carefully designed regulatory policy can strike a better balance of multiple competing objectives. Finally, if a government can reform the taxi industry by adjusting the taxi fare, then lowering the taxi fare instead of imposing a strict policy toward on-demand ride services can improve the total social welfare. This paper was accepted by Serguei Netessine, operations management.

Manufacturers’ Competition and Cooperation in Sustainability: Stable Recycling Alliances

Rather than organizing disposal of consumer-generated waste themselves, many states and countries have passed legislation that makes producers responsible for the proper disposal (i.e., recycling) of the products that they bring to the market. We study the stability of producers’ strategies emerging under such legislation. In our paper, the producers compete with multiple differentiated products in consumer markets but may consider cooperating when recycling those products to benefit from economies of scale. Products made by different producers or sold in different markets might still be considered for joint recycling. Our main questions are when and whether firm-based recycling strategies (i.e., separately recycling products falling under same brand) or market-based recycling strategies (i.e., separately recycling products falling in the same product category) emerge as stable outcomes. To that end, we analyze a series of simple producer-market configurations. We first look at an asymmetric market model with two producers making three products in two markets, and then, we look at a symmetric market model with two producers competing with four products in two markets. Our results show that, with intense market competition and differentiated market sizes, producers may recycle their products on their own without cooperating with others. In some instances, they can add a product from their competitor to their recycling mix. Because these outcomes are never socially optimal, they may reduce social welfare and require government intervention. Otherwise, with less intense competition or more equitable market shares, all-inclusive (market-based) recycling is the most common stable outcome with high (low) scale economies, and the firms’ independent choices might lead to social optima.This paper was accepted by Serguei Netessine, operations management.

High-Performance Practice Processes

Despite their idiosyncrasies, motor and cognitive learning and endurance sports training have in common that they involve repeated practice. While considerable research has been devoted to the effect of practice on performance, little is known about optimal practice strategies. In this paper, we model the practice process for both skill acquisition and retention, and optimize its profile to maximize performance on a predefined date. For skill acquisition, we find that the optimal process involves multiple phases of practice increase and decrease, yielding U-shaped effort consistent with the principle of distributing practice, and that the transitions between phases are smoother for skills that are easily forgotten (e.g., cognitive skills) than for those that are easily retained (e.g., continuous motor skills). In particular for the latter, an extended period of rest should precede an ultimate high-intensity stress. For skill retention, the optimal practice strategy consists of cycles of either constant effort (for skills that are easily forgotten) or pulsed effort (for skills that are easily retained) consistent with the principle of alternating stress and rest. Our parametric model thus indicates when commonly used high-performance practice strategies are indeed optimal. This paper was accepted by Serguei Netessine, operations management.

Oversight and Efficiency in Public Projects: A Regression Discontinuity Analysis

In the United States, 42% of public infrastructure projects report delays or cost overruns. To mitigate this problem, regulators scrutinize project operations. We study the effect of oversight on delays and overruns with 262,857 projects spanning 71 federal agencies and 54,739 contractors. We identify our results using a federal bylaw: if the project’s budget is above a cutoff, procurement officers actively oversee the contractor’s operations; otherwise, most operational checks are waived. We find that oversight increases delays by 6.1%–13.8% and overruns by 1.4%–1.6%. We also show that oversight is most obstructive when the contractor has no experience in public projects, is paid with a fixed-fee contract with performance-based incentives, or performs a labor-intensive task. Oversight is least obstructive—or even beneficial—when the contractor is experienced, paid with a time-and-materials contract, or conducts a machine-intensive task. This paper was accepted by Serguei Netessine, operations management.

Strategic Consumers, Revenue Management, and the Design of Loyalty Programs

We study the interaction between the design of a premium-status loyalty program, revenue management, and strategic consumer behavior. Specifically, we consider a contemporaneous change where firms across several industries switch their loyalty programs from quantity-based toward spending-based designs. This change has been met with fierce opposition from the media and consumers. Building on the microfoundations of strategic, forward-looking, and status-seeking consumer behavior, we endogenize strategic consumer response to firms’ pricing and loyalty program design decisions, and we characterize conditions under which, by coordinating these decisions, firms can benefit from strategic consumer behavior. We further show that by switching to a spending-based design, firms can benefit from strategic behavior even more, under broader conditions, and in a Pareto-improving way. Finally, we also analyze combined designs, which utilize a combination of quantity and/or spending requirements, and show how they can be used to better manage the transition toward spending-based designs, possibly minimizing negative consumer reactions. This paper was accepted by Serguei Netessine, operations management.

Can Yardstick Competition Reduce Waiting Times?

Yardstick competition is a regulatory scheme for local monopolists (e.g., hospitals), where the monopolist’s reimbursement is linked to performance relative to other equivalent monopolists. This regulatory scheme is known to provide cost-reduction incentives and serves as the theoretical underpinning behind the hospital prospective reimbursement system used throughout the developed world. This paper uses a game-theoretic queueing model to investigate how yardstick competition performs in service systems (e.g., hospital emergency departments), where in addition to incentivizing cost reduction the regulator wants to incentivize waiting time reduction. We first show that the form of cost-based yardstick competition used in practice results in inefficiently long waiting times. We then demonstrate how yardstick competition can be appropriately modified to achieve the dual goal of cost and waiting-time reduction. In particular, we show that full efficiency (first-best) can be restored if the regulator makes the providers’ reimbursement contingent on their service rates and is also able to charge a provider-specific “toll” to consumers. More important, if such a toll is not feasible, as may be the case in healthcare, we show that there exists an alternative and particularly simple yardstick-competition scheme, which depends on the average waiting time only, that can significantly improve system efficiency (second-best). This scheme is easier to implement because it does not require the regulator to have detailed knowledge of the queueing discipline. We conclude with a numerical investigation that provides insights on the practical implementation of yardstick competition for hospital emergency departments, and we also present a series of modelling extensions. The e-companion is available at https://doi.org/10.1287/mnsc.2018.3089 . This paper was accepted by Serguei Netessine, operations management.

Supply Chain Contracts That Prevent Information Leakage

This paper determines categories of contracts that facilitate vertical information sharing in a supply chain while precluding horizontal information leakage among competing newsvendors. We consider a supply chain in which retailers replenish inventory from a common supplier to satisfy uncertain demand and are engaged in newsvendor competition. Each retailer has imperfect demand information. Yet one of the retailers (the incumbent) has a more accurate demand forecast than the other (the entrant). Information leakage among such competing retailers precludes vertical information sharing and is often the reason for many retailers to abandon collaborative forecast-sharing initiatives, leading to suboptimized supply chains. We show that whether a contract can prevent information leakage depends on how the inventory risk (i.e., cost of supply–demand mismatch) is allocated among the supplier and retailers in conjunction with the allocation of profits. We categorize contracts according to how they allocate inventory risk among firms when compared with a wholesale‐price contract. This comparison yields four mutually exclusive and collectively exhaustive categories of contracts. A downside-protection contract is one that effectively reduces retailers’ cost of excess inventory by shifting some of their overage cost to the supplier. Examples of such contracts include buy-back and revenue-sharing contracts. An upside-protection contract is one that effectively increases retailers’ cost of inventory shortage by shifting some of the supplier’s underage cost to retailers. Examples of such contracts include penalty and rebate contracts. A two-sided protection contract combines the properties of the previous two categories. A no-protection contract is one that fails to shift firms’ cost of inventory shortage or excess from one to the other. Examples of such contracts include wholesale-price and two-part tariff contracts. We show that no-protection contracts, which are extensively used in practice, cannot prevent information leakage, whereas others may do so. We also show that preventing information leakage could be costly for the supply chain (i.e., low channel efficiency). We conclude by illustrating how our unified framework to study a variety of contracts can enable a firm to determine the best-performing contract (among many) that precludes information leakage while almost coordinating the channel. For example, we show why buy‐back contracts perform significantly better than revenue‐sharing or rebate contracts. This paper was accepted by Serguei Netessine, operations management.

Social Learning and the Design of New Experience Goods

Consumers often consult the reviews of their peers before deciding whether to purchase a new experience good; however, their initial quality expectations are typically set by the product’s observable attributes. This paper focuses on the implications of social learning for a monopolist firm’s choice of product design. In our model, the firm’s design choice determines the product’s ex ante expected quality, and designs associated with (stochastically) higher quality incur higher costs of production. Consumers are forward-looking social learners, and may choose to strategically delay their purchase in anticipation of product reviews. In this setting, we find that the firm’s optimal policy differs significantly depending on the level of the ex ante quality uncertainty surrounding the product. In comparison to the case where there is no social learning, we show that (i) when the uncertainty is relatively low, the firm opts for a product of inferior design accompanied by a lower price, while (ii) when the uncertainty is high, the firm chooses a product of superior design accompanied by a higher price; interestingly, we find that the product’s expected quality decreases either in the absolute sense (in the former case), or relative to the product’s price (in the latter case). We further establish that, contrary to conventional knowledge, social learning can have an ex ante negative impact on the firm’s profit, in particular when the consumers are sufficiently forward-looking. Conversely, we find that the presence of social learning tends to be beneficial for the consumers only provided they are sufficiently forward-looking. This paper was accepted by Serguei Netessine, operations management.

Learning and Hierarchies in Service Systems

Motivated by diverse application areas such as healthcare, call centers, and crowdsourcing, we consider the design and operation of service systems that process tasks with types that are ex ante unknown, and employ servers with different skill sets. Our benchmark model involves two types of tasks, Easy and Hard, and servers that are either Junior or Senior in their abilities. The service provider determines a resource allocation policy, i.e., how to assign tasks to servers over time, with the goal of maximizing the system’s long-term throughput. Information about a task’s type can only be obtained while serving it. In particular, the more time a Junior server spends on a task without service completion, the higher her belief that the task is Hard and thus needs to be rerouted to a Senior server. This interplay between service time and task-type uncertainty implies that the system’s resource allocation policy and staffing levels implicitly determine how the provider prioritizes between learning and actually serving. We show that the performance loss due to the uncertainty in task types can be significant and, interestingly, that the system’s stability region is largely dependent on the rate at which information about tasks’ types is generated. Furthermore, we consider endogenizing the servers’ capabilities: assuming that training is costly, we explore the problem of jointly optimizing over the training levels of the system’s server pools, the staffing levels, and the resource allocation policy. We find that among optimal designs there always exists one with a “hierarchical” structure, where all tasks are initially routed to the least skilled servers and then progressively move to more skilled ones, if necessary. Comparative statics indicate that uncertainty in task types leads to significantly higher staffing cost and less specialized server pools. This paper was accepted by Serguei Netessine, operations management.

Assessing the Impact of Service Level When Customer Needs Are Uncertain: An Empirical Investigation of Hospital Step-Down Units

Many service systems have servers with different capabilities and customers with varying needs. One common way this occurs is when servers are hierarchical in their skills or in the level of service they can provide. Much of the literature studying such systems relies on an understanding of the relative costs and benefits associated with serving different customer types by the different levels of service. In this work, we focus on estimating these costs and benefits in a complex healthcare setting where the major differentiation among server types is the intensity of service provided. Step-down units (SDUs) were initially introduced in hospitals to provide an intermediate level of care for semicritically ill patients who are not sick enough to require intensive care but not stable enough to be treated in the general medical/surgical ward. One complicating factor is that the needs of customers is sometimes uncertain—specifically, it is difficult to know a priori which level of care a particular patient needs. Using data from 10 hospitals from a single hospital network, we take a data-driven approach to classify patients based on severity and empirically estimate the clinical and operational outcomes associated with routing these patients to the SDU. Our findings suggest that an SDU may be a cost-effective way to treat patients when used for patients who are post-ICU (intensive care unit). However, the impact of SDU care is more nuanced for patients admitted from the emergency department and may result in increased mortality risk and hospital length of stay for patients who should be treated in the ICU. Our results imply that more study is needed when using SDU care this way. This paper was accepted by Serguei Netessine, operations management.