Maximizing Revenue Through Two‐Dimensional Shelf‐Space Allocation

We consider the problem of optimally allocating contiguous rectangular presentation spaces in order to maximize revenues. Such problems are encountered in the arrangement of products in retail shelf‐space and in the design of feature advertising displays or webpages. Specifically, we allow (i) the shape of a product's presentation to have a vertical as well as a horizontal component and (ii) displays to extend across multiple shelves for in‐store presentations. Since the vertical location of the shelf on which a product is displayed affects its sales, each vertical location is assigned its own effectiveness with regard to revenue generation. The problem of maximizing the total weighted revenue of a display is strongly NP‐hard. Therefore, we decompose it into two subproblems. The first consists of allocating products to different cabinets. In the second, within each cabinet, each product's units are arranged in a contiguous rectangle and assigned a location. These subproblems are solved using an innovative approach that uses a combination of integer programming and an algorithm for the maximum‐weight independent set problem. Based on computational studies on both real‐world and simulated data, we demonstrate the efficiency and effectiveness of our approach. Specifically, the revenue generated by this scheme is within 1% of the optimum for actual data and within 5% for simulated data.     

SOVEREIGN DEBT SUSTAINABILITY IN ADVANCED ECONOMIES

We develop a measure of maximum sustainable government debt for advanced economies. How much investors are willing to lend to a country's government depends on the country's expected primary surplus, the level and volatility of its rate of growth, and how much debt the government expects to be able to raise in the future for the purpose of servicing the debt it seeks to raise today. We provide a simple formula that computes a country's maximum sustainable debt (MSD) as a function of four easy‐to‐estimate parameters. We further compute a country's theoretical probability of default (PD) as a function of its debt‐to‐GDP ratio. We finally calibrate our measures for 23 OECD countries and test the relation between sovereign yield spreads and our theoretical PD at prevailing debt levels. We find it to be strongly statistically significant.     

Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals

This paper studies nonparametric estimation of conditional moment restrictions in which the generalized residual functions can be nonsmooth in the unknown functions of endogenous variables. This is a nonparametric nonlinear instrumental variables (IV) problem. We propose a class of penalized sieve minimum distance (PSMD) estimators, which are minimizers of a penalized empirical minimum distance criterion over a collection of sieve spaces that are dense in the infinite‐dimensional function parameter space. Some of the PSMD procedures use slowly growing finite‐dimensional sieves with flexible penalties or without any penalty; others use large dimensional sieves with lower semicompact and/or convex penalties. We establish their consistency and the convergence rates in Banach space norms (such as a sup‐norm or a root mean squared norm), allowing for possibly noncompact infinite‐dimensional parameter spaces. For both mildly and severely ill‐posed nonlinear inverse problems, our convergence rates in Hilbert space norms (such as a root mean squared norm) achieve the known minimax optimal rate for the nonparametric mean IV regression. We illustrate the theory with a nonparametric additive quantile IV regression. We present a simulation study and an empirical application of estimating nonparametric quantile IV Engel curves.     

The Influence of Service Orientation on B2B e‐Service Capabilities: An Empirical Investigation

E‐Services, or the company's portfolio of service offerings available to its customers through the Internet, are an emerging area of interest to operations management. Yet little is known about the operations and capabilities needed for provision of business‐to‐business (B2B) e‐services. This paper aims to make a contribution toward closing this gap. First, we develop a new construct of B2B e‐service capability, a term that captures a generic set of five interrelated and complementary dimensions: (1) e‐service recovery, (2) e‐customization, (3) ease of navigation, (4) service portfolio comprehensiveness, and (5) information richness. These combined operational abilities are associated with B2B service delivery, including its portal design, technology architecture, and mix of product and service offerings. They are posited to be necessary for delivering effective B2B e‐services. We also argue that, both service orientation (SO) and customer receptivity to technology, influence B2B e‐service capability. We empirically test a path model using structural equation modeling on a sample of 181 businesses that have deployed B2B e‐services. We find that the influence of SO on performance is not direct but rather mediated by the e‐service capability, a finding that holds for both goods producers and service providers. We suggest that a firm's SO may mitigate industrial customers' resistance toward conducting business online.     

Opportunism in Capital Budget Recommendations: The Effects of Past Performance and Its Attributions*

This study uses an experiment to examine the separate and combined effects of managers' loss aversion and their causal attributions about their divisions' performance on tendencies to make goal‐incongruent capital budget recommendations. We find that managers' recommendations are biased by their loss aversion. In particular, managers of high‐performing divisions are more likely than managers of low‐performing divisions to propose investments that maximize their division's short‐term profits at the expense of the firm's long‐term value. We also find that managers' recommendations are biased by their causal attributions. In particular, managers are more likely to propose investments that maximize their division's short‐term profits at the expense of the firm's long‐term value when they attribute their division's performance to external causes (e.g., task difficulty or luck) rather than to internal causes (e.g., managerial ability or effort). Further, the effects of causal attributions are greater for managers of high‐performing divisions than for managers of low‐performing divisions. The study's findings are important because loss aversion and causal attributions are often manifested in firms. Thus, they may bias managers' decisions, which in turn may be detrimental to the firms' long‐term value.     

Competing on Time: An Integrated Framework to Optimize Dynamic Time‐to‐Market and Production Decisions

This study develops a comprehensive framework to optimize new product introduction timing and subsequent production decisions faced by a component supplier. Prior to market entry, the supplier performs process design activities, which improve manufacturing yield and the chances of getting qualified for the customer's product. However, a long delay in market entry allows competitors to enter the market and pass the customer's qualification process before the supplier, reducing the supplier's share of the customer's business. After entering the market and if qualified, the supplier also needs to decide how much to produce for a finite planning horizon by considering several factors such as manufacturing yield and stochastic demand, both of which depend on the earlier time‐to‐market decision. To capture this dependency, we develop a sequential, nested, two‐stage decision framework to optimize the time‐to‐market and production decisions in relation to each other. We show that the supplier's optimal market entry and qualification timing decision need to be revised in real time based on the number of qualified competitors at the time of market‐entry decision. We establish the optimality of a threshold policy. Following this policy, at the beginning of each decision epoch, the supplier should optimally stop preparing for qualification and decide whether to enter the market if her order among qualified competitors exceeds a predetermined threshold. We also prove that the supplier's optimal production policy is a state‐dependent, base‐stock policy, which depends on the time‐to‐market and qualification decisions. The proposed framework also enables a firm to quantify how market conditions (such as price and competitor entry behavior) and operating conditions (such as the rate of learning and inventory/production‐related costs) affect time‐to‐market strategy and post‐entry production decisions.     

Technology Choice and Capacity Portfolios under Emissions Regulation

We study the impact of emissions tax and emissions cap‐and‐trade regulation on a firm's technology choice and capacity decisions. We show that emissions price uncertainty under cap‐and‐trade results in greater expected profit than a constant emissions price under an emissions tax, which contradicts popular arguments that the greater uncertainty under cap‐and‐trade will erode value. We further show that two operational drivers underlie this result: (i) the firm's option not to operate, which effectively right‐censors the uncertain emissions price; and (ii) dispatch flexibility, which is the firm's ability to first deploy its most profitable capacity given the realized emissions price. In addition to these managerial insights, we also explore policy implications: the effect of emissions price level, and the effect of investment and production subsidies. Through an illustrative example, we show that production subsidies of higher investment and production cost technologies (such as carbon capture and storage technologies) have no effect on the firm's optimal total capacity when firms own a portfolio of both clean and dirty technologies, but that investment subsidies of these technologies increase the firm's total capacity, conditionally increasing expected emissions. A subsidy of a lower production cost technology, on the other hand, has no effect on the firm's optimal total capacity in multi‐technology portfolios, regardless of whether the subsidy is a production or investment subsidy.     

Marketing as an Investment in Shareholder Value

We present resource‐based and capability‐based arguments of marketing investment intensity to offer a strategic view of marketing as an investment in shareholder value. We find that marketing investment intensity has a U‐shaped quadratic effect on shareholder value creation (Tobin's q) that calls for marketing investment to be protected and increased, not surrendered. We show how marketing investments interact with investments in R&D, human capital and operations to reveal how strategic co‐investments can alter the shareholder value of marketing. Finally, we show how competitive intensity and failings in the firm's investment productivity (its ability to convert investment expenditure into sales) point to malaise in the firm's own strategic architecture as a fault for perceived poor returns from marketing investments. Our findings suggest that marketing investment should not be scapegoated when its contributions to shareholder value are not as expected. When invested in strategically and in combination with other investments, marketing can unlock exciting improvements in shareholder value.     

Acquisition and Disclosure of Operational Information*

We study a firm's strategy for acquisition and disclosure of operational information by establishing linkages among information quality, managerial self‐interest, and production planning. We develop a multistage model in which a manager of a publicly traded firm first receives private information about the product demand and then uses it to make production and disclosure decisions. We consider two prevalent disclosure models employed in the accounting literature: all‐or‐nothing and cheap‐talk models. In the all‐or‐nothing model, it is assumed that any disclosure must be truthful, but the manager can strategically withhold information. We show that the manager commits to acquire the value‐added operational information if (i) the managerial self‐interest in the interim share price is low or (ii) the managerial self‐interest in the interim share price is high, but the fixed disclosure cost is either sufficiently low or sufficiently high. We demonstrate that the firm is better off if the production level is observable to the financial market because multidimensional signaling reduces costs. In the cheap‐talk model, we assume that the manager's disclosure may not be truthful. We show that the manager's incentive to acquire value‐added operational information increases along with the penalty cost for misleading investors. Therefore, a high penalty cost for misleading investors can encourage the manager to obtain more precise information, which in turn improves the firm's cash flow.     

Stochastic Optimization for Natural Disaster Asset Prepositioning

A key strategic issue in pre‐disaster planning for humanitarian logistics is the pre‐establishment of adequate capacity and resources that enable efficient relief operations. This paper develops a two‐stage stochastic optimization model to guide the allocation of budget to acquire and position relief assets, decisions that typically need to be made well in advance before a disaster strikes. The optimization focuses on minimizing the expected number of casualties, so our model includes first‐stage decisions to represent the expansion of resources such as warehouses, medical facilities with personnel, ramp spaces, and shelters. Second‐stage decisions concern the logistics of the problem, where allocated resources and contracted transportation assets are deployed to rescue critical population (in need of emergency evacuation), deliver required commodities to stay‐back population, and transport the transfer population displaced by the disaster. Because of the uncertainty of the event's location and severity, these and other parameters are represented as scenarios. Computational results on notional test cases provide guidance on budget allocation and prove the potential benefit of using stochastic optimization.     

Modeling Reputation as a Time‐Series: Evaluating the Risk of Purchase Decisions on eBay*

Reputation systems based on buyer feedback play an important role in today's online markets. In this article, we provide a rigorous methodology to establish a relationship between a seller's feedback history and risk of default. We validate this method against eBay's reputation system, using a dataset of terminated users (Not‐A‐Registered‐User or NARU) and the feedback left for them by buyers. By treating feedback rating data as a function of time, we characterize the tendency of change in seller feedback ratings in order to predict the behavior of a seller. We find that NARU sellers have significantly more negative feedback in their final weeks. Applying functional principal component analysis and classification tree methods, we find that when projecting the feedback data to an appropriate space, NARU and non‐NARU sellers can be distinguished at better than 92% accuracy. We use this to provide a quantitative mechanism for evaluating the risk of trading with a seller who has less than perfect feedback, and offer advice on how much a buyer should offer to pay, given an asking price on a commodity item and a seller's feedback history.     

Knowledge Diversity,Turnover, and Organizational‐Unit Productivity: An Empirical Analysis in a Knowledge‐Intensive Context

We examine the role of knowledge diversity among unit members on an organizational unit's productivity. Utilizing a proprietary data set of corrective maintenance tasks from a large software‐services firm, we investigate the impact of two key within‐unit diversity metrics: interpersonal diversity and intrapersonal diversity. We analyze the independent influence of interpersonal diversity and the interactive influence of interpersonal diversity and intrapersonal diversity on organizational unit's productivity. Finally, we examine how diversity moderates productivity of an organizational unit when employee turnover occurs. Our analysis reveals the following key insights: (a) interpersonal diversity has an inverted U‐shaped effect on organizational unit's productivity; (b) intrapersonal diversity moderates the influence of interpersonal diversity on organizational‐unit productivity; (c) at higher levels of interpersonal diversity, rate of decrease in productivity of the organizational unit due to turnover is higher. We discuss the resulting theoretical and managerial insights associated with these findings.     

Information Independence and Common Knowledge

In Bayesian environments with private information, as described by the types of Harsanyi, how can types of agents be (statistically) disassociated from each other and how are such disassociations reflected in the agents' knowledge structure? Conditions studied are (i) subjective independence (the opponents' types are independent conditional on one's own) and (ii) type disassociation under common knowledge (the agents' types are independent, conditional on some common‐knowledge variable). Subjective independence is motivated by its implications in Bayesian games and in studies of equilibrium concepts. We find that a variable that disassociates types is more informative than any common‐knowledge variable. With three or more agents, conditions (i) and (ii) are equivalent. They also imply that any variable which is common knowledge to two agents is common knowledge to all, and imply the existence of a unique common‐knowledge variable that disassociates types, which is the one defined by Aumann.     

The Dynamics of Domestic Gray Markets and Its Impact on Supply Chains

Gray markets are created by unauthorized retailers selling manufacturer's branded products. Similar to international gray markets, domestic gray markets are a growing phenomenon whose impact on supply chains is not clear. We consider a supply chain with one manufacturer and several authorized retailers who face a newsvendor problem and a domestic gray market. While a gray market provides an opportunity for retailers to clear their excess inventory (inventory‐correction effect), it also can be a threat to their demand (demand‐cannibalization effect). We first characterize the emerging equilibrium by assuming an MSRP environment. Comparing a decentralized and centralized system, we show that a wholesale pricing contract is quite efficient in a gray market environment; we explain the underlying mechanism and note some of the operational decisions that could hurt that efficiency. We show that the gray market price determines the degree of both the negative effects of demand‐cannibalization and the positive effects of inventory correction, which in turn determines the net impact of gray markets on the retailer's stocking choice and, ultimately, the manufacturer's profit. We then study the authorized retailers' problem as a price‐setting newsvendor. We observe that the gray market creates price competition between the authorized and unauthorized retailers, causing a drop in the primary market price. However, this price competition can be counteracted by the authorized retailers' stocking decision. Finally, we extend our model to consider the cases where the demand can be correlated across retailers.     

Shareholders' Wealth‐Maximizing Operating Decisions and Risk Management Practices in a Mixed Contracts Economy

This paper establishes a critically important positive role for operations management practices and financial hedging. We show that operations management decisions and financial hedging are intertwined, and we advance a framework that can identify their combined effects on investors' wealth. We show that: (a) firms (publicly traded corporations) will optimally hold adequate riskless working capital (e.g., cash) to minimize the cost of obtaining non‐financial inputs, and the magnitude of this cash holding depends on operating details, and (b) operations management and financial hedging can lower firms' cash requirements, and boost productivity, defined as the wealth created in the firm per dollar of invested capital. Productivity‐enhancing practices—by “freeing up” some of the firm's cash—can maximize the investors' wealth. We show that these results obtain because firms' contracts with many of the providers of non‐financial inputs are not traded, and because investors can invest not just in public corporations but also in businesses “outside the markets” (e.g., proprietorships, partnerships, and private equity).     

Why Competition from a Multi‐Channel E‐Tailer Does Not Always Benefit Consumers*

Empirical studies have delivered mixed conclusions on whether the widely acclaimed assertions of lower electronic retail (e‐tail) prices are true and to what extent these prices impact conventional retail prices, profits, and consumer welfare. For goods that require little in‐person pre‐ or postsales support such as CDs, DVDs, and books, we extend Balasubramanian's e‐tailer‐in‐the‐center, spatial, circular market model to examine the impact of a multichannel e‐tailer's presence on retailers' decisions to relocate, on retail prices and profits, and consumer welfare. We demonstrate several counter‐intuitive results. For example, when the disutility of buying online and shipping costs are relatively low, retailers are better off by not relocating in response to an e‐tailer's entry into the retail channel. In addition, such an entry—a multichannel strategy—may lead to increased retail prices and increased profits across the industry. Finally, consumers can be better off with less channel competition. The underlying message is that inferences regarding prices, profits, and consumer welfare critically depend on specifications of the good, disutility and shipping costs versus transportation costs (or more generally, positioning), and competition.     

Sourcing Decisions with Competitive Suppliers and Imperfect Information

Manufacturers often must choose between outsourcing and producing internally. This choice is complex and influenced by a variety of factors, including the costs and capabilities of the potential suppliers. In addition, if the manufacturer outsources, he must design the sourcing process. We study the manufacturer's outsourcing decision, with a focus on the impact of the sourcing process on that decision. We consider a setting in which the manufacturer has imperfect information regarding the suppliers' costs and capabilities, and we assume that the manufacturer uses a two‐stage sourcing process. The first stage is the qualification stage, in which the manufacturer seeks to reduce the uncertainty regarding the suppliers' capabilities. The second stage is the supplier selection stage, in which the manufacturer selects among the qualified suppliers on the basis of price. We first characterize the optimal design of the two‐stage process, and then consider the outsourcing decision. We demonstrate several trade‐offs. Vertical integration enables the manufacturer to reduce uncertainty and extract all of the profits of production. However, outsourcing enables the manufacturer to take advantage of the (potentially) lower costs and higher capabilities of the suppliers, particularly if competition between suppliers can be encouraged. We find that the manufacturer is more likely to vertically integrate when the warranty cost and the cost of exerting effort during qualification are large, and when there is significant uncertainty regarding the suppliers' capabilities. The manufacturer is more likely to outsource when the suppliers' costs (capabilities) are low (high), and when the number of suppliers is large.     

Examining the Antecedents and Consequences of CIO Strategic Decision‐Making Authority: An Empirical Study*

Despite the strategic importance of information technology (IT) to contemporary firms, chief information officers (CIO) often still have varying degrees of strategic decision‐making authority. In this study, we apply the theory of managerial discretion to define CIO strategic decision‐making authority and argue that the CIO's level of strategic decision‐making authority directly influences IT's contribution to organization performance. We also draw on the power and politics perspective in the strategic decision‐making literature to identify the direct antecedents to the CIO's strategic decision‐making authority. A theoretical model is presented and empirically tested using survey data collected from a cross‐industry sample of 174 matched pairs of CIOs and top business executives through structural equation modeling. The results suggest that organizational climate, organizational support for IT, the CIO's structural power, the CIO's level of strategic effectiveness, and a strong partnership between the CIO and top management team directly influence the CIO's level of strategic decision‐making authority within the organization. The results also suggest that the CIO's strategic decision‐making authority in the organization directly influences the contribution of IT to firm performance and that effective CIOs have a greater influence on IT's contribution when provided with strategic decision‐making authority.     

Time for space: A narrative review of research on organizational spaces

This paper presents an integrated framework for studying organizational spaces. It suggests that existing research can be classed into three categories: studies of space as distance; studies of space as the materialization of power relations; and studies of space as experience. These approaches are drawn together using Henri Lefebvre's theory of spatial production to argue that an adequate understanding of organizational spaces would investigate how they are practised, planned and imagined. Moreover, an adequate theory of space would account for multiple spatial levels, or scales. To illustrate the potential of the synthetic framework, a reading of three exemplary studies of multiple organizational spaces, from social anthropology and economic geography, is presented. The paper concludes by presenting a research agenda that indicates how data collection and analysis in established fields such as employee relations and international business might become more ‘space sensitive’ by integrating such theorized cross‐scale analysis.     

Panel Size and Overbooking Decisions for Appointment‐Based Services under Patient No‐Shows

Many service systems that work with appointments, particularly those in healthcare, suffer from high no‐show rates. While there are many reasons why patients become no‐shows, empirical studies found that the probability of a patient being a no‐show typically increases with the patient's appointment delay, i.e., the time between the call for the appointment and the appointment date. This paper investigates how demand and capacity control decisions should be made while taking this relationship into account. We use stylized single server queueing models to model the appointments scheduled for a provider, and consider two different problems. In the first problem, the service capacity is fixed and the decision variable is the panel size; in the second problem, both the panel size and the service capacity (i.e., overbooking level) are decision variables. The objective in both cases is to maximize some net reward function, which reduces to system throughput for the first problem. We give partial or complete characterizations for the optimal decisions, and use these characterizations to provide insights into how optimal decisions depend on patient's no‐show behavior in regards to their appointment delay. These insights especially provide guidance to service providers who are already engaged in or considering interventions such as sending reminders in order to decrease no‐show probabilities. We find that in addition to the magnitudes of patient show‐up probabilities, patients' sensitivity to incremental delays is an important determinant of how demand and capacity decisions should be adjusted in response to anticipated changes in patients' no‐show behavior.