Knowledge that Transforms

In recent years, instances of organizations failing to maintain digital confidentiality performance have greatly increased in frequency and monetary damage. While the global sourcing of activities in the development of digital assets is widespread, very little is known about how location‐related factors may affect confidentiality outcomes. Addressing this, we empirically investigate two factors with rich theoretical bases and logical linkages to confidentiality: industrial agglomeration and national property rights protections. We conduct a large‐scale, empirical study at the product level of analysis, and treat the confidentiality of a digital product as a performance outcome that is affected by the locations of the two key organizational entities involved in the product's development. We leverage modern, web‐crawling methods to harvest secondary data from a major, illicit distribution channel for these products and combine these data with other secondary data involving legitimate commerce to derive a secondary measure of confidentiality performance. We find robust results, and demonstrate practical significance of our findings through scenario analyses based on actual data from our sample.

In consulting, finance, and other service industries, customers represent a revenue stream, and must be acquired and retained over time. In this paper, we study the resource allocation problem of a profit maximizing service firm that dynamically allocates its resources toward acquiring new clients and retaining unsatisfied existing ones. The interaction between acquisition and retention in our model is reflected in the cash constraint on total expected spending on acquisition and retention in each period. We formulate this problem as a dynamic program in which the firm makes decisions in both acquisition and retention after observing the current size of its customer base and receiving information about customers in danger of attrition, and we characterize the structure of the optimal acquisition and retention strategy. We show that when the firm's customer base size is relatively low, the firm should spend heavily on acquisition and try to retain every unhappy customer. However, as its customer base grows, the firm should gradually shift its emphasis from acquisition to retention, and it should also aim to strike a balance between acquisition and retention while spending its available resources. Finally, when the customer base is large enough, it may be optimal for the firm to begin spending less in both acquisition and retention. We also extend our analysis to situations where acquisition or retention success rate, as a function of resources allocation, is uncertain and show that the optimal acquisition and retention policy can be surprisingly complex. However, we develop an effective heuristic for that case. This paper aims to provide service managers some analytical principles and effective guidelines on resource allocation between these two significant activities based on their firm's customer base size.

The management of remanufacturing inventory system is often challenged by mismatched supply (i.e., returned units, called cores) and demand. Typically, the demand for remanufactured units is high and exceeds the supply early in a product's lifetime, and drops below the supply late in the lifetime. This supply–demand imbalance motivates us to study a switching strategy to facilitate the decision‐making process. This strategy deploys a push mode at the early stage of a product's lifetime, which remanufactures scarce cores to stock to responsively satisfy the high demand, and switches to a pull mode as the product approaches obsolescence to accurately match the low demand with supply. In addition, the strategy further simplifies the decision‐making process by ignoring the impact of leftover cores at the end of each decision period. We show that the optimal policy of the switching strategy possesses a simple, multi‐dimensional base‐stock structure, which aims to remanufacture units from the i best‐quality categories up to the i th state‐independent base‐stock level. An extensive numerical study shows that the switching strategy delivers close‐to‐optimal and robust performance: the strategy only incurs an average profit loss of 1.21% and a maximum of 2.27%, compared with the optimal one. The numerical study also shows when a pure push or pull strategy, a special case of the switching strategy, delivers good performance. The study offers the managerial insight that firms can use simple, easy‐to‐implement strategies to efficiently manage the remanufacturing inventory system.

Firms producing complementary goods often strategically form groups and jointly sell their products to better coordinate their decisions. For consumer durables, decisions about such collaboration might be complicated due to two factors. Because of their durability and presence of used goods markets, such products engender “future” price competition between new and used goods. On the other hand, consumers of such products might be forward‐looking and patient, both of which affect their purchasing behavior. In this study, we study how the above product and consumer characteristics interact to affect the group selling decisions of complementary firms. We do so through a two‐period model consisting of a value chain with two upstream manufacturers and a downstream retailer. When consumers are relatively impatient and reluctant to wait to buy later, group selling by manufacturers will take place only when the end product is relatively perishable, that is, product durability is low. However, if consumers are patient, that is, willing to wait, collaboration happens only when the end product is quite durable; for relatively perishable products the manufacturers sell their products separately. We also comment on how our results are affected by factors like manufacturers directly selling to end consumers or there being multiple opportunities to decide whether or not to use group selling strategy.

This study investigates the value of inventory sharing in the presence of spot and forward markets. We consider a multi‐period setting where two firms process a common commodity to meet stochastic demands. They can buy and sell the commodity through both the spot and forward markets. They can also share the commodity if one has leftover inventory while the other has excess demand. We first characterize the equilibrium strategies of the two firms. Our analysis reveals that in such a context, the value of inventory sharing is low when the forward price is directly used to value the sharing transactions. We then develop a structured trans‐shipment price scheme that uses a linear combination of the spot and forward prices. We show that this method can substantially increase the value of inventory sharing. Our analysis also reveals that in the presence of liquid spot and forward markets, the value of inventory sharing mainly results from the difference of the transaction costs, and it increases if the market in which firms operate becomes more competitive.

We study an inventory management mechanism that uses two stochastic programs (SPs), the customary one‐period assemble‐to‐order (ATO) model and its relaxation, to conceive control policies for dynamic ATO systems. We introduce a class of ATO systems, those that possess what we call a “chained BOM.” We prove that having a chained BOM is a sufficient condition for both SPs to be [Formula: see text] convex in the first‐stage decision variables. We show by examples the necessity of the condition. For ATO systems with a chained BOM, our result implies that the optimal integer solutions of the SPs can be found efficiently, and thus expedites the calculation of control parameters. The M system is a representative chained BOM system with two components and three products. We show that in this special case, the SPs can be solved as a one‐stage optimization problem. The allocation policy can also be reduced to simple, intuitive instructions, of which there are four distinct sets, one for each of four different parameter regions. We highlight the need for component reservation in one of these four regions. Our numerical studies demonstrate that achieving asymptotic optimality represents a significant advantage of the SP‐based approach over alternative approaches. Our numerical comparisons also show that outside of the asymptotic regime, the SP‐based approach has a commanding lead over the alternative policies. Our findings indicate that the SP‐based approach is a promising inventory management strategy that warrants further development for more general systems and practical implementations.

We study the provision of collaborative services under online reviews, where the service outcome depends on the effort of both the service provider and the client. The provider decides not only her own effort but also the client's, at least to some extent. The client gives the review based on his net utility upon service completion. We develop a signal‐jamming model in which the provider's inherent capability or type is unobservable, and the market infers the provider type through observable signals such as the service outcome, the client review, or both. We show that compared to the benchmark case when the service outcome is observed as a signal, the client review generally leads to less effort of both the provider and the client. The review hence tends to sacrifice the service effectiveness in favor of the efficiency of the client's effort input. Nevertheless, when clients incorporate private information about the provider type into their reviews, service providers are better motivated to devote effort. Interestingly, we find the provider's effort choices may be either strategic complements or substitutes. With a reasonable level of informativeness, online reviews could lead to favorable performance in service effectiveness, client effort efficiency, and provider type distinguishability. Surprisingly, we demonstrate that when both the review and the outcome are available, the provider may lack sufficient incentive to devote effort, resulting in inferior distinguishability of provider types. It thus illustrates that richer information may not necessarily generate favorable strategic outcomes.

We examine the value of price commitment in a non‐profit organization using individual‐level purchases over a series of concert performances. To decide on a pricing policy, the performing arts organization must be able to accurately measure when each ticket will be sold and what type of audience will purchase the tickets for each performance. We use a competing hazards framework to model the timing of ticket purchases when customer segments differ in their valuations and arrival times. We show that the customer purchase likelihoods change based on the prices observed earlier in the season. Hence, price commitment can aid in improving sales, revenues, and customer visits. In particular, we show that price commitment to a decreasing monotone discount policy can improve the revenues in the range 2.1%–6.7% per concert.

We examine the link between network neutrality (NN) and content innovation on the Internet by comparing the impact of NN and packet discrimination (PD) regimes on content innovation. We do this in the context of a two‐sided market model that simultaneously considers content provider (CP) and consumer decisions concerning market entry and participation while taking into account consumers’ response to network congestion. We find that content innovation flourishes under NN to a greater degree than under PD due to two effects we uncover: the generation of what we call a pro bono innovation zone in which CPs are able to enter the market without contributing to network provider profits; and the cross‐side congestion effect, a negative network externality wherein higher broadband market coverage levels result in greater congestion for CPs, and increased content results in greater congestion for consumers, taking into account consumers’ strategic response to network congestion. These results have important implications for current public policy debates regarding the Federal Communications Commission's Open Internet Rules.