Knowledge that Transforms

“Gray markets” are unauthorized channels that distribute a branded product without the manufacturer's permission. Since gray markets are not officially sanctioned by the manufacturer, their existence is assumed to hurt the manufacturer. Yet manufacturers sometimes tolerate or even encourage gray market activities. We investigate the incentives of a manufacturer and its authorized retailer to engage in (or tolerate) gray markets. The firms need to consider the trade‐off between the positive effects of a gray market (price discrimination and cost savings) and the negative effects (cannibalization of sales and a loss in consumer valuation). Generally, gray markets can be categorized into two types: (i) a “local gray market,” where a retailer diverts products to unauthorized sellers operating in the same region as the retailer; and, (ii) “bootlegging,” where the retailer diverts products to unauthorized sellers in another market where the manufacturer sells through a direct channel. We characterize the equilibrium in each type of gray market and identify conditions under which the retailer will divert products to the gray market. Incentive problems are more complicated when the retailer bootlegs and, in this case, we show that conflicting incentives may lead to the emergence of a gray market where both the manufacturer's and retailer's profits decrease.

In developing countries, governments, non‐governmental organizations, and social entrepreneurs are disseminating agricultural information to farmers to improve their welfare. However, instead of having direct access to the information, farmers usually acquire information from local social networks, and, thus, they may have very different information channels. We establish a general framework that accommodates highly asymmetric information structures to study farmers' information management and utilization problems. In our model, a bipartite graph describes which subset of signals is accessible to a farmer. We characterize a unique Bayesian Nash equilibrium and express farmers' strategies and expected profits in closed form. We discuss properties of this equilibrium and show that asymmetric information structures can lead to various novel results. For example, a farmer may produce more (less) when observing a pessimistic (optimistic) signal, may benefit from the improvement of a signal she cannot observe, may want to share her signal with others, and may become worse off when another farmer releases a signal to her. We conduct comprehensive studies on the equilibrium in the “weak signal limit,” where signals are subject to substantial noise. We examine the government's optimal information allocation in this limit when its goal is to maximize farmers' total profits or the social welfare. To improve farmers' total profits, the government should provide all its information to (and only to) one farmer. We establish an index to determine which farmer should get the information. In contrast, to maximize the social welfare, the government should provide all its information to all farmers.

Firms are increasingly outsourcing information security operations to managed security service providers (MSSPs). Cost reduction and quality (security) improvement are often mentioned as motives for outsourcing information security, and these are also the frequently cited reasons for outsourcing traditional information technology (IT) functions, such as software development and maintenance. In this study, we present a different explanation—one based on interdependent risks and competitive externalities associated with IT security—for firms' decisions to outsource security. We show that in the absence of competitive externalities and interdependent risks, a firm will outsource security if and only if the MSSP offers a quality advantage over in‐house operations, which is consistent with the conventional explanation for security outsourcing. However, when security risks are interdependent and breaches impose competitive externalities, although firms still have stronger incentive to outsource security if the MSSP offers a higher quality in terms of preventing breaches than in‐house management, a quality advantage of MSSP over in‐house management is neither a prerequisite for a firm to outsource security nor a guarantee that a firm will. In addition to MSSP quality, the type of externality (positive or negative), the degree of externality, whether outsourcing increases or decreases risk interdependency, and the breach characteristics determine firms' sourcing decisions. When security breaches impose a positive externality, the incentive to outsource is enhanced if the MSSP decreases the risk interdependency and diminished if the MSSP increases this interdependency. A negative externality has the opposite effect on firms' incentives to outsource. A high demand spillover to a competitor, together with a high loss in industry demand because of a security breach, enhances these incentives to outsource security operations when the externality is negative. Finally, we extend our base model in several dimensions and show that our main results regarding the impact of interdependent risks and competitive externalities on sourcing decisions are robust and generalizable to different specifications.

We consider a revenue management problem wherein the seller is endowed with a single type resource with a finite capacity and the resource can be repeatedly used to serve customers. There are multiple classes of customers arriving according to a multi‐class Poisson process. Each customer, upon arrival, submits a service request that specifies his service start time and end time. Our model allows customer advanced reservation times and services times in each class to be arbitrarily distributed and correlated. Upon arrival of each customer, the seller must instantaneously decide whether to accept this customer's service request. A customer whose request is denied leaves the system. A customer whose request is accepted is allocated with a specific item of the resource at his service start time. The resource unit occupied by a customer becomes available to other customers after serving this customer. The seller aims to design an admission control policy that maximizes her expected long‐run average revenue. We propose a policy called the ε‐ perturbation class selection policy ( ε‐CSP), based on the optimal solution in the fluid setting wherein customers are infinitesimal and customer arrival processes are deterministic, under the restriction that the seller can utilize at most (1 − ε) of her capacity for any ε ∈ (0, 1). We prove that the ε‐CSP is near‐optimal. More precisely, we develop an upper bound of the performance loss of the ε‐CSP relative to the seller's optimal revenue, and show that it converges to zero with a square‐root convergence rate in the asymptotic regime wherein the arrival rates and the capacity grow up proportionally and the capacity buffer level ε decays to zero.

In this article, we study the electricity time‐of‐use (TOU) tariff for an electricity company with stochastic demand. The electricity company offers the flat rate (FR) and TOU tariffs to customers. Under the FR tariff, the customer pays a flat price for electricity consumption in both the peak and non‐peak periods. Under the TOU tariff, the customer pays a high price for electricity consumption in the peak period and a low price for electricity consumption in the non‐peak period. The electricity company uses two technologies, namely the base‐load and peak‐load technologies, to generate electricity. We derive the optimal capacity investment and pricing decisions for the electricity company. Furthermore, we use real data from a case study to validate the results and derive insights for implementing the TOU tariff. We show that in almost all the cases, the electricity company needs less capacity for both technologies under the TOU tariff than under the FR tariff, even though the expected demand in the non‐peak period increases. In addition, except for some extreme cases, there is essentially no signicant reduction in the total demand of the two periods, although the TOU tariff can reduce the demand in the peak period. Under the price‐cap regulation, the customer may pay a lower price on average under the TOU tariff than under the FR tariff. We conduct an extensive numerical study to assess the impacts of the model parameters on the optimal solutions and the robustness of the analytical results, and generate managerial implications of the research findings.

In recent years, an increasing number of brick‐and‐mortar retailers have entered into the new brick‐and‐click era. Within this context, when a manufacturer presents a new product offering to a retailer, the ultimate decision is often made by the retailer regarding (1) whether to carry the new product, and (2) the channel outlet the product will be carried in (i.e., in‐store only, online‐exclusive, or brick‐and‐click). In response to this trend, we examine how a manufacturer may use product design to influence a dual‐channel retailer's outlet designation decision. This is the first study to investigate a manufacturer's optimal product design strategy when a brick‐and‐mortar retailer expands online. We demonstrate that, to induce the retailer to carry a new product both offline and online, it may not always be optimal for the manufacturer to enhance product quality (compared with when the retailer only operates offline). With the online store addition, the retailer may also be incentivized to adjust his participation criterion to a level less than what is determined by his outside option.

Many knowledge‐intensive projects such as new product and software design, research, and high technology development have flexible scope and involve co‐production between a client and a vendor. In such projects, it is often challenging to estimate how much progress can be achieved within a certain time window or how much time may be needed to achieve a certain degree of progress, especially because the client and vendor often adjust their efforts as a function of the project's progress, the time until the deadline, and the incentives in place. Effective contracts should therefore be flexible in scope and foster collaboration. In this study, we characterize the collaborative work dynamics of a client and a vendor who are engaged in a multi‐state, multi‐period stochastic project with a finite deadline. We show that when the client can verify the vendor's effort, it is optimal that they both exert high effort in one of two situations: when either not enough progress has been made and the deadline is close (deadline effect), or conversely, when so much progress has been made that the project state is close to a completion state set by the client (milestone effect). Hence, in this case, progress will typically be faster when the project is about to be stopped, due to either reaching the deadline or reaching the client's desired completion state. However, when the client cannot verify the vendor's effort, the vendor is prone to free‐riding. Considering a time‐based contract that pays the vendor a per‐period fee and a fixed completion bonus, we show that the equilibrium completion state is decreasing in the per‐period fee and increasing in the bonus, justifying the use of both incentive mechanisms in practice. Moreover, we show that, under such contracts, some form of milestone effect arises in equilibrium, but the deadline effect does not. Hence, in those cases, early progress will typically lead to early project conclusion at a high state; whereas, slow progress will typically make the project drag until the deadline while still at a low state.

The most salient or peak aspect of a service experience often defines customer perceptions of the service. Across two studies, using the same novel form of a scenario‐based experiment, we investigate the design of peak events in a service sequence by testing how anticipated and surprised peaks influence customer perceptions. Study 1 captures the immediate reactions of participants and Study 2 surveys participants a week later. In both studies, we find a main effect for the temporal peak placement, confirming the positive influence of a strong peak ending. When assessing the peak design strategies of surprise and anticipation, we find in Study 1 that surprise and anticipation moderate the temporal peak placement (e.g., early peak vs. late peak) on overall customer perceptions, with the surprise peak at the end of an experience yielding the strongest effect. In Study 2 we see that the remembered experience of a surprise peak positively affects customer perceptions compared to an anticipated peak regardless of the temporal placement of the peak. We also find that the infusion of a surprise peak ending has a lasting effect that amplifies the peak‐end effect of remembered experiences. Drawing on these findings, we discuss the role of surprise, anticipation, and sequence effects in experience design strategy.

Despite substantial financial aid from international donors for procurement of health products, stockouts of life‐saving drugs related to prevalent infectious diseases are still widespread in Africa. Rigorous research to understand the underlying causes of these stockouts is lacking. To this end, we study the relationship between The Global Fund to Fight AIDS, Tuberculosis and Malaria and its grant recipients. Specifically, we leverage historical fund disbursement and drug procurement data from 2002 to 2013 to build a discrete‐event simulation model predicting the joint impact of procurement and grant disbursement processes on national drug availability for the Global Fund's recipient countries in Africa. This model is validated against cumulative stockout levels inferred from historical grant implementation lengths, and used to evaluate potential high‐level modifications in the disbursement or procurement process. Results show the existence of significant intrinsic stockout risks in most African countries, with particularly high levels in East Africa, due to the unpredictability of fund disbursements and the frequency of grant performance monitoring performed by the Global Fund. Interventions shifting some fund disbursements upfront to protect against disbursement timing uncertainty are predicted to be more effective than others that include regional buffer stocks and bridge financing.

Subsidy programs are widely offered in both developing and developed countries to encourage consumption of products that generate positive social, health, and environmental externalities. We study the effect of subsidies on product consumption under uncertain market demand. To reach a target consumer population, the program sponsor may subsidize a for‐profit or a not‐for‐profit firm on each unit of the product purchased by the firm or on each unit of the sale generated by the firm. We show that subsidy programs provide stronger incentives to a not‐for‐profit firm than to its for‐profit counterpart in inducing a large consumption whenever the sponsor is having a very limited budget or a very generous budget. When subsidizing a not‐for‐profit firm, the sponsor should always choose the purchase subsidy over the sales subsidy because the former can induce a larger consumption than the latter with the same subsidy spending. However, this is not always true when the subsidy program is administered through a for‐profit firm, unless the firm is a price taker in the market or the sponsor has a limited budget. Our analysis leads to new theoretical development of price‐setting newsvendor problem for both the for‐profit and not‐for‐profit operations under subsidy.