A Framework for Estimating Benefits of Using Auctions in Revenue Management*

We develop a stochastic model to explore the benefits of incorporating auctions in revenue management. To the best of our knowledge the extant literature on modeling in revenue management has not considered auctions. We consider three models, namely, a traditional fixed price (non‐auction) model, a pure auction model, and a hybrid auction model and evaluate their revenue performance under a variety of conditions. The hybrid approach outperforms the other two in all 24 scenarios and yields an average revenue increase of 16.1% over the next best. A surprise finding is that there is no significant difference between the performance of the fixed price and pure auction approaches. A sensitivity analysis reveals that the relative superiority of the hybrid revenue management strategy is reasonably robust.     

The Individually Responsible and Rational Decision Approach to Economic Lot Sizes for One Vendor and Many Purchasers

Banerjee's [2] joint economic lot size (JELS) model, along with related works by Monahan [12] and Lal and Staelin [10], represents one approach to minimizing the total inventory carrying and ordering costs of a vendor and his purchaser(s). Noting that JELS philosophy requires a coordinated system and that its practical implementation is problematic, we present an alternative approach to the same problem: the individually responsible and rational decision (IRRD) approach. The IRRD approach is consistent with a free enterprise system and easy to implement. In order to show that the IRRD approach is also more economical than the JELS approach, we first build a more refined JELS model for the case of one vendor and many identical purchasers. Drawing on earlier criticisms of specific JELS models, our refinement relaxes the lot-for-lot assumption commonly used by JELS scholars. To be comparable with earlier works, we retain the assumption of deterministic conditions and demonstrate the economic advantages of IRRD over JELS through a numerical example. An algebraic proof of IRRD's superiority over JELS is offered in the more general and realistic case of a vendor dealing with K nonidentical purchasers with reasonably predictable annual demand but uncertain order quantities and timings.     

The influence of CEO equity incentives on licensing

In a study of life science firms, we find that, in accordance with predictions drawn from agency theory and behavioral agency theory, CEO stock ownership is negatively associated with licensing while CEO stock options are positively associated with licensing. Furthermore, by combining theoretical insights from the capabilities literature with both agency theory and behavioral agency theory, we predict that a key measure of capabilities in the licensing context—a firm's alliance experience—significantly influences the ways in which CEO equity incentives impact licensing. More specifically, we find that, in accordance with our theoretical predictions, alliance experience positively (negatively) moderates the relationship between CEO stock ownership (CEO stock options) and licensing. Our study contributes to the wider literature on the determinants of licensing by examining whether licensing is sensitive to CEO equity incentives. We also extend the capabilities literature on licensing by examining the contrasting influences of a firm's alliance experience on the relationship between CEO equity incentives and licensing. Our findings also inform behavioral agency-based research on the effects of equity incentives by highlighting the usefulness of a capabilities perspective in augmenting our understanding of the behavioral role of CEO equity incentives.     

Generalizing the Announced Price Increase Problem*

This paper generalizes the announced price increase problem to consider a variety of practical concerns arising out of applications ranging from foreign exchange fluctuations to upper limits on the purchase of discounted supermarket items. These include limitations on the amount that can be purchased at the old price and/or on the length of the grace period, within which buyers may take advantage of this lower price. These constraints give rise to 16 possible situations. For each situation purchasing and inventory decision rules are developed. A numerical example is discussed to highlight the main features of the models.     

Determining Optimal Selling Price and Lot Size When the Supplier Offers All-Unit Quantity Discounts*

This paper is concerned with finding the optimal price and lot size for a retailer purchasing a product for which the supplier offers all-unit quantity discounts. Demand for the product is assumed to be a decreasing function of price, and a procedure is developed for finding the optimal price and lot size for a class of demand functions. The procedure then is applied to two common demand functions: (1) the constant price-elasticity function, and (2) the linear demand function.     

Consignment or wholesale: Retailer and supplier preferences and incentives for compromise

We consider two independently managed parties, a retailer and a supplier, that are considering either a wholesale or a consignment contract to produce and market a single good. Both parties have an interest in reaching an agreement, but their first choice of contract type are generally not the same. We define the strength of retailer and supplier preferences for their respective choices of contract type as the ratio of their expected profits for their first choice of contract type over that for the alternative contract type. We study how uncontrollable factors as well as controllable factors affect the strength of retailer and supplier contract preferences. We develop incentive payments that can potentially be used to increase the likelihood of success in negotiating an agreement.     

Get more for less? Experimental evidence on repeated decision making under non-monotone incentives

Summary  This paper presents experimental results of a benchmark study to analyze the incentive effects of non-monotone pay schemes. An incentive compatible contract that does not award the highest pay to the highest possible output combination was tested in a neutral, framing, and two framing-with-principal settings, respectively. The results confirm the model in a statistically significant way. Principals select the non-monotone contract over a monotone contract that would give them ex ante a lower expected surplus. Agents predominantly select the income-maximizing strategy, i.e. select the effort level that should be implemented by the contract. Given the widespread view that non-monotone output-contingent incentives are not plausible labor contracts, it seems worthwile to extend the experimental study to include aspects which are common in labor relations, such as an option to quit for the employee and repeated interaction between employer and employee. This would help answer the question whether theoretically optimal non-monotone contracts may be used as labor contracts. The author acknowledges insightful comments by Jeannette Brosig, Alexis Kunz, Thomas Riechmann, Dirk Sliwka, Joachim Weimann and two anonymous referees. Financial support by MaxLab is gratefully acknowledged. Any remaining errors are my own.     

Using review articles to address societal grand challenges

We introduce a special issue of International Journal of Management Reviews that demonstrates how to use review articles to address societal grand challenges—complex, large-scale issues facing humankind, such as climate change, inequality and poverty. First, we argue that review articles possess unique features that make them particularly useful for addressing societal grand challenges. Second, we discuss three distinct but related roles of review articles in addressing societal grand challenges: (1) advancing theoretical knowledge; (2) advancing methodological knowledge; and (3) advancing practical knowledge. We conclude by providing future directions to enhance contributions of review articles for addressing societal grand challenges further by: (a) spanning disciplinary boundaries; (b) engaging practitioners; and (c) using alternative review approaches.     

Adaptive Tactical Pricing in Multi‐Agent Supply Chain Markets Using Economic Regimes

In today's complex and dynamic supply chain markets, information systems are essential for effective supply chain management. Complex decision making processes on strategic, tactical, and operational levels require substantial timely support in order to contribute to organizations' agility. Consequently, there is a need for sophisticated dynamic product pricing mechanisms that can adapt quickly to changing market conditions and competitors' strategies. We propose a two‐layered machine learning approach to compute tactical pricing decisions in real time. The first layer estimates prevailing economic conditions—economic regimes—identifying and predicting current and future market conditions. In the second layer, we train a neural network for each regime to estimate price distributions in real time using available information. The neural networks compute offer acceptance probabilities from a tactical perspective to meet desired sales quotas. We validate our approach in the trading agent competition for supply chain management. When competing against the world's leading agents, the performance of our system significantly improves compared to using only economic regimes to predict prices. Profits increase significantly even though the prices and sales volume do not change significantly. Instead, tactical pricing results in a more efficient sales strategy by reducing both finished goods and components inventory costs.     

A Probabilistic Dealing Strategy

A probabilistic dealing strategy is proposed which allows all premium brands in an established market to earn nonnegative profits without cooperation. Following the strategy, brands take turns attracting deal-responsive customers. Relative to a reactive competitive strategy, the proposed strategy improves the positions of all premium brands. With use of the strategy, average deal sizes are positively related to a brand's market share, the proportion of quality conscious customers, the proportion of informed customers, the span of regular prices in a market, and the range of customers' acceptable prices.     

TOTAL SETUP LOT SIZING WITH QUANTITY DISCOUNTS*

Often, order quantity decisions are made by purchasers facing a price schedule of quantity discounts. Traditional solution procedures have consisted of the evaluation of total cost at numerous price-break points in search of the lowest total cost. This approach is tedious and not particularly informative, especially when one is faced with lengthy schedules. This paper presents a total setup lot-sizing model that reduces the computations required to find the least-total-cost quantity, given parameters from a supplier's price schedule. The parameters are first obtained by simple regression (graphical or computer) and in themselves can provide valuable insight for the purchaser's decision making. A total setup lot-sizing model is next developed to define a “critical interval” that contains the solution. The model and algorithm are tested under a variety of conditions. Their application offers the decision maker a convenient alternative to determine the best quantity to order from a tendered price schedule.     

Trial or No Trial: Supplying Costly Signals to Improve Profits*

Many software and video game firms offer free trials with limited content to help buyers assess the likely value of the goods that they may purchase. This article examines fundamental issues related to the incentives and risks for a monopoly by providing a trial. Assuming that a seller can control the mix of components in a trial, we introduce a new mechanism for buyers’ inference of using a trial. We find that a trial may enable the seller to segment the market and charge a higher price to high‐valuation buyers, but can also cause a decline in demand. Moreover, the seller forfeits partial value of a full product through providing a free trial, so the benefit is offset by this cannibalization loss. In addition to the size and content of a trial, the distribution of buyers’ prior belief also affects a trial's ability to convey information. We show that a trial can provide more information if the prior belief is more concentrated in the tails of the distribution.     

TRANSFER-PRICING AND OUTPUT DECISIONS: THE DYNAMIC INTERACTION

This paper is concerned with the dynamic interactions between output and transferprice decisions in a three-country model for a multinational firm when profits taxation and ad valorem tariffs are applied simultaneously. A numerical example is used to illustrate that the three-country model modifies considerably conclusions reached in the traditional two-country, two-goods framework.     

Decentralization in Linear Programming Models

This paper proposes a decomposition of a linear programming problem based on the structure of the optimal basis matrix. If this matrix contains a zero matrix of appropriate dimensions, the problem may be decomposed into a price-setting problem and a quantity-setting problem. This decomposition is valid for a set of coefficients of the problem to be determined by parametric programming. It can be applied to problems with common constraints or common variables. An application to dairy production planning is discussed and a comparison with the Dantzig-Wolfe decomposition principle is given.     

Using Asset Prices to Measure the Persistence of the Marginal Utility of Wealth

We derive a lower bound for the volatility of the permanent component of investors' marginal utility of wealth or, more generally, asset pricing kernels. The bound is based on return properties of long‐term zero‐coupon bonds, risk‐free bonds, and other risky securities. We find the permanent component of the pricing kernel to be very volatile; its volatility is about at least as large as the volatility of the stochastic discount factor. A related measure for the transitory component suggest it to be considerably less important. We also show that, for many cases where the pricing kernel is a function of consumption, innovations to consumption need to have permanent effects.     

A Generalized Framework for Quantity Discount Pricing Schedules

The use of price to influence a buyer's purchasing behavior and thus improve supply chain coordination has received considerable attention. The vendor and buyer are independent economic entities, each maximizing its own profit. We consider the case of a buyer with fixed annual demand, independent of cost. The vendor's objective is to set a price schedule that encourages the buyer to raise its order quantity, increasing the vendor's profits. We present a unified treatment of the problem, categorize different variations, and provide a common solution procedure for all cases.     

Dynamic Pricing and Lead‐Time Policies for Make‐to‐Order Systems*

Make‐to‐order firms use different approaches for managing their lead‐times and pricing in the face of changing market conditions. A particular firm's approach may be largely dictated by environmental constraints. For example, it makes little sense to carefully manage lead‐time if its effect on demand is muted, as it can be in situations where leadtime is difficult for the market to gauge or requires investment to estimate. Similarly, it can be impractical to change capacity and price. However, environmental constraints are likely to become less of an issue in the future with the expanding e‐business infrastructure, and this trend raises questions into how to manage effectively the marketing mix of price and lead‐time in a more “friction‐free” setting. We study a simple model of a make‐to‐order firm, and we examine policies for adjusting price and capacity in response to periodic and unpredictable shifts in how the market values price and lead‐time. Our analysis suggests that maintaining a fixed capacity while using lead‐time and/or price to absorb changes in the market will be most attractive when stability in throughput and profit are highly valued, but in volatile markets, this stability comes at a cost of low profits. From a pure profit maximization perspective, it is best to strive for a short and consistent lead‐times by adjusting both capacity and price in response to market changes.     

A UNIFIED APPROACH TO THE PRICE-BREAK ECONOMIC ORDER QUANTITY (EOQ) PROBLEM*

In many developing countries where supply is limited, a premium rather than a discounted price is paid for buying in larger amounts. In order for management science/operations research solutions to be relevant to developing economies, such realities need to be explicitly recognized and any decisions evaluated from that perspective. To illustrate this point, a typical inventory-purchasing problem is solved. In the process, formulae are developed that introduce simultaneous price and quantity sensitivity into the inventory equation. A systematic procedure is suggested to locate the optimal order quantity for a given schedule of discounts or premiums.     

Optimal Digital Rights Management with Uncertain Piracy

Many firms that sell digital copies of copyrighted materials online face a common dilemma: the use of digital rights management (DRM) to impede pirates can impose restrictions on legitimate use. We introduce a two‐period model in which the use of DRM in the first period affects the probability that a consumer finds a pirated copy in the second period; the threat of legal action reduces consumers’ consumption of pirated copies; and firms choose whether to sell, and at what prices, either strongly or weakly DRM‐protected products, or both. Furthermore, we incorporate the role of uncertainty concerning future levels of piracy. Using a two‐period model with uncertainty, we investigate a firm's optimal DRM strategies and present the optimal pricing strategy as well as product launch strategy under different market conditions. We find that one important characteristic of the optimal strategy is that it is optimal to maintain the same product line configuration strategy for both periods. We also characterize the conditions under which each strategy is optimal.