The Economics of Public Beta Testing

A growing number of software firms now rely on public beta testing to improve the quality of their products before commercial release. While the benefits resulting from improved software reliability are well recognized, some important market‐related benefits have not been studied. Through word‐of‐mouth, public beta testers can accelerate the diffusion of a software product after its release. Additionally, because of network effects, public beta testers can increase users’ valuation of a product. In this study, we consider both reliability‐related and market‐related benefits, and develop models to determine the optimal number of public beta testers and the optimal duration of testing. Our analyses show that public beta testing can be profitable even if word‐of‐mouth and network effects are the only benefits. Furthermore, when both benefits are considered, there is significant “economies of scope”—the net profit increases at a faster rate when both word‐of‐mouth and network effects are significant than when only one benefit is present. Finally, our sensitivity analyses demonstrate that public beta testing remains highly valuable to software firms over a wide range of testing and market conditions. In particular, firms will realize greater profits when recruiting public beta testers who are interested in the software but unable to afford it.     

Branch‐and‐Price Methods for Prescribing Profitable Upgrades of High‐Technology Products with Stochastic Demands*

This paper develops a model that can be used as a decision support aid, helping manufacturers make profitable decisions in upgrading the features of a family of high‐technology products over its life cycle. The model integrates various organizations in the enterprise: product design, marketing, manufacturing, production planning, and supply chain management. Customer demand is assumed random and this uncertainty is addressed using scenario analysis. A branch‐and‐price (B&P) solution approach is devised to optimize the stochastic problem effectively. Sets of random instances are generated to evaluate the effectiveness of our solution approach in comparison with that of commercial software on the basis of run time. Computational results indicate that our approach outperforms commercial software on all of our test problems and is capable of solving practical problems in reasonable run time. We present several examples to demonstrate how managers can use our models to answer “what if” questions.     

Using Advance Purchase Discount Contracts under Uncertain Information Acquisition Cost

We study the use of advance purchase discount (APD) contracts to incentivize a retailer to share demand information with a dual‐sourcing wholesaler. We analyze such contracts in terms of two practical considerations that are relevant in this context but have been overlooked by previous work that has largely studied the direct offer of APD to customers: the retailer's information acquisition cost and the wholesaler's limited information about that cost. The wholesaler's limited knowledge of the retailer's cost leads to a departure—from the normal “full observability” APD design—that is asymmetric and depends on the extent of unobservability; if the uncertainty is small (resp., large) then the optimal discount is higher (resp., lower) than in the case of full observability. An APD contract that ignores the retailer's cost or the wholesaler's uncertainty about it will yield fewer benefits for the wholesaler and the supply chain. We offer a numerical illustration (calibrated on real industry data) establishing that for a representative product, an APD contract can improve the wholesaler's profit margin by as much as 3.5%.     

When Are Local Incentive Constraints Sufficient?

We study the question of whether local incentive constraints are sufficient to imply full incentive compatibility in a variety of mechanism design settings, allowing for probabilistic mechanisms. We give a unified approach that covers both continuous and discrete type spaces. On many common preference domains—including any convex domain of cardinal or ordinal preferences, single‐peaked ordinal preferences, and successive single‐crossing ordinal preferences—local incentive compatibility (suitably defined) implies full incentive compatibility. On domains of cardinal preferences that satisfy a strong nonconvexity condition, local incentive compatibility is not sufficient. Our sufficiency results hold for dominant‐strategy and Bayesian Nash solution concepts, and allow for some interdependence in preferences.     

Monopoly Versioning of Information Goods When Consumers Have Group Tastes

Large sunk costs of development, negligible costs of reproduction, and distribution resulting in economies of scale distinguish information goods from physical goods. Versioning is a way firms may take advantage of these properties. However, in a baseline model where consumers differ in their tastes for quality, an information goods monopolist only offers one version, and this differs from what we observe in practice. We explore formulations that add features to the baseline model that result in a monopolist offering multiple versions. We examine versioning where consumers differ in individual tastes for quality, and groups of consumers that share the same group taste are delineated by segments of individual tastes. We find that if groups have mutually exclusive characteristics—a horizontal dimension—that they value relative to the shared characteristics, then versioning is optimal. Consequently, any horizontal differentiation in product line design favors versioning. In addition, when group tastes are hierarchical such that higher taste groups value characteristics that lower taste groups value but not vice versa—a vertical dimension—as long as the valuations of the higher and adjacent lower taste group are sufficiently close, then versioning is also optimal. Our conditions, which also help determine how many versions are optimal, are based on exogenously defined parameters so that it is feasible to check them in practice.     

Supply Chain Strategies for Perishable Products: The Case of Fresh Produce

This paper examines supply chain design strategies for a specific type of perishable product—fresh produce—using melons and sweet corn as examples. Melons and other types of produce reach their peak value at the time of harvest; product value deteriorates exponentially post‐harvest until the product is cooled to dampen the deterioration. Using the product's marginal value of time (MVT), the rate at which the product loses value over time in the supply chain, we show that the appropriate model to minimize lost value in the supply chain is a hybrid of a responsive model from post‐harvest to cooling, followed by an efficient model in the remainder of the chain. We also show that these two segments of the supply chain are only loosely linked, implying that little coordination is required across the chain to achieve value maximization. The models we develop also provide insights into the use of a product's MVT to develop supply chain strategies for other perishable products.     

Strategic supply network planning with vendor selection under consideration of risk and demand uncertainty

We present a stochastic version of a three-layer supply network planning problem that includes the selection of vendors that must be equipped with company-specific tools. The configuration of a supply network must be determined by using demand forecasts for a long planning horizon to meet a given service level. The risk induced by the uncertain demand is explicitly considered by incorporating the conditional value at risk. The objective is to maximize the weighted sum of the expected net present value of discounted cash flows and the conditional value at risk. This would lead to a non-linear model formulation that is approximated by a mixed-integer linear model. This approximation is realized by a piecewise linearization of the expected backlogs and physical inventory as non-linear functions of cumulative production quantities. A two-stage stochastic programming approach is proposed. Our numerical analysis of generic test instances indicates that solving the linearized model formulation yields a robust and stable supply network configuration when demand is uncertain.     

COMPUTER GRAPHICS AS DECISION AIDS: DIRECTIONS FOR RESEARCH*

Computer-generated graphics are becoming increasingly available to decision makers. Despite claims on the part of vendors that the use of graphics will improve decision speed and quality over traditional methods of data display, the available evidence is far from supportive. Initial studies show graphics to be no more effective in communicating information than tables. Correct interpretation of graphical displays appears to require training, which most users lack. Furthermore, there is evidence that those features that make a graph visually attractive—such as color, design complexity, and realism—may actually detract from accurate comprehension. This paper summarizes the literature dealing with the human use of graphics, develops several propositions based on persistent trends in the literature, and suggests directions for future research.     

Fusion Product Planning: A Market Offering Perspective*

Devices that integrate multiple functions together are popular in consumer electronic markets. We describe these multifunction devices as fusion products as they fuse together products that traditionally stand alone in the marketplace. In this article, we investigate the manufacturer's fusion product planning decision, adopting a market offering perspective that allows us to address the design and product portfolio decisions simultaneously. The general approach adopted is to develop and analyze a profit‐maximizing model for a single firm that integrates product substitution effects in identifying an optimal market offering. In the general model, we demonstrate that the product design and portfolio decisions are analytically difficult to characterize because the number of possible portfolios can be extremely large. The managerial insight from a stylized all‐in‐one model and numerical analysis is that the manufacturer should, in most cases, select only a subset of fusion and single‐function products to satisfy the market's multidimension needs. This may explain why the function compositions available in certain product markets are limited. In particular, one of the key factors driving the product portfolio decision is the margin associated with the fusion products. If a single all‐in‐one fusion product has relatively high margins, then this product likely dominates the product portfolio. Also, the congruency of the constituent single‐function products is an important factor. When substitution effects are relatively high (i.e., the product set is more congruent), a portfolio containing a smaller number of products is more likely to be optimal.     

An Information‐Processing Approach for Evaluating In‐Store Retail Operational Design Strategies

We develop a model to evaluate retail store operational design strategies using an information‐processing perspective of organizational design. We propose that three model constructs pertaining to in‐store shopper task uncertainty—the product mix complexity, the service production complexity, and the product mix changeover—create shopper encounter information requirements (IR). These requirements can be met using specific retail service operational design choices for managing shopper encounters, namely, designing layouts for self‐service (SS) and providing employees with task empowerment (TE). The model is then operationalized using a two‐stage approach to develop new multi‐item, measurement scales. The psychometric properties and predictive validity of the scales and model are then confirmed by using structural equation modeling with survey data from 175 merchandise retail store managers. We find that our model can be generically applied across the retail industry to understand how shopper encounter IR motivate retailer store design choices and can be used to determine whether to design stores for SS or to provide store employees with TE. We then evaluate the efficacy of the studied store design choices on customer delivery satisfaction, and offer some suggestions for future research.     

Closed‐Loop Supply Chains: An Introduction to the Feature Issue (Part 2)

Closed‐loop supply chain management is the design, control and operation of a system to maximize value creation over the entire life‐cycle of a product with dynamic recovery of value from different types and volumes of returns over time. The research in this feature issue furthers our understanding of this rich area and serves as a starting point for another round of research which continues to dig deeper still into relevant industry issues.     

ECONOMICS AND CLIMATE CHANGE: INTEGRATED ASSESSMENT IN A MULTI‐REGION WORLD

This paper develops a model that integrates the climate and the global economy—an integrated assessment model—with which different policy scenarios can be analyzed and compared. The model is a dynamic stochastic general‐equilibrium setup with a continuum of regions. Thus, it is a full stochastic general‐equilibrium version of RICE, Nordhaus’s pioneering multi‐region integrated assessment model. Like RICE, our model features traded fossil fuel but otherwise has no markets across regions—there is no insurance nor any intertemporal trade across them. The extreme form of market incompleteness is not fully realistic but arguably not a bad approximation of reality. Its major advantage is that, along with a set of reasonable assumptions on preferences, technology, and nature, it allows a closed‐form model solution. We use the model to assess the welfare consequences of carbon taxes that differ across as well as within oil‐consuming and ‐producing regions. We show that, surprisingly, only taxes on oil producers can improve the climate: taxes on oil consumers have no effect at all. The calibrated model suggests large differences in views on climate policy across regions.     

IT服务外包项目工期与费用控制的 多属性英氏逆拍卖机制

工期和费用是影响IT服务外包项目成败的两个重要因素,且两者之间呈负相关的关系。在IT服务外包项目执行前,发包方与接包方需要就项目的工期和费用达成一致。通常,发包方并不完全了解外包项目的市场行情,在这种情况下,就需要一种有效的方式使发包方和接包方之间就工期和费用达成一致。本文设计了改进的英氏逆拍卖机制,针对一对多的情况设计了新的拍卖协议;针对工期和费用的多属性情况,引入多属性效用理论解决,设计了相应的效用增加函数。最后通过一个算例来演示所设计的拍卖机制对解决此类决策问题的作用。得出一些结论:所设计机制能够以拍卖方式描述费用和工期管理流程;找到了发包方和接包方的最佳增量效用,并且建议的拍卖协议是发包方和接包方获得双赢结果的机制;从不同大小的案例中可以得到完全一致的结果,这表明设计的拍卖机制的有效性和效用增加函数对协商结果的有效性。     

CHOICE-CONSTRAINED CONJOINT ANALYSIS

Choice-constrained conjoint analysis (CCCA) is a new method for metric conjoint analysis studies. It computes part-worth utility functions that account for “revealed preference”—those products a respondent actually selects in an independent choice situation. CCCA uses an iterative penalty function estimation procedure that successively modifies initial regressionderived part worths so that respondent choices (either actual or intended) of real brands are predicted as accurately as possible. The paper first describes the motivation and rationale for CCCA and presents the mathematics of the algorithm. As an illustration, it applies the CCCA model and penalty function estimation procedure to a limited set of synthetic data. A second application of the technique is presented that uses data obtained by a major telecommunications firm that used conjoint analysis to examine the importance of several features of residential communication devices. The paper also discusses potential extensions of the CCCA model and the kinds of marketing applications for which it might be useful.     

Commercialization of Platform Technologies: Launch Timing and Versioning Strategy

Many emerging entrepreneurial applications and services connect two or more groups of users over Internet‐based information technologies. Commercial success of such technology products requires astute business practices related to product line design, price discrimination, and launch timing. We examine these issues for a platform firm that serves two markets—labeled as user and developer markets—such that the size of each market positively impacts participation in the other. In addition, our model allows for sequential unfolding of consumer and developer participation, and for uncertainty regarding developer participation. We demonstrate that product versioning is an especially attractive strategy for platform firms, that is, the trade‐off between market size and margins is tilted in the direction of more versions. However, when expanding the product line carries substantial fixed costs (e.g., marketing cost, cost of additional plant, increased distribution cost), then the uncertainty in developer participation adversely impacts the firm's ability to offer multiple versions. We show that for established firms with lower uncertainty about developer participation, the choice is essentially between an expanded or minimal product line. Startups and firms that are entering a new product category are more likely to benefit from a “wait and see” deferred expansion strategy.     

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.     

间接网络效应下的产品扩散——基于复杂网络和计算经济学的研究

借鉴复杂性理论,基于个体交往关系的复杂网络结构,该文采用计算经济学建模方法和行为博弈学习算法对间接网络效应下的产品扩散现象进行建模.在该文模型中,间接网络效应下"软件"数量为厂商策略行动内生决定,并根据用户数量而变化,因此个体的决策和全局变量之间存在双向交互复杂作用.研究结果揭示了个体邻域结构在产品扩散中的影响,直接网络效应和间接网络效应在产品扩散中的区别和产品锁定发生的条件等.结果也较好地解释了产品扩散中的很多现象如不同产品的共存,产品扩散中的"涌现",产品扩散中的路径依赖,产品兼容性的选择以及新旧产品的更新换代等.     

Optimal Software Free Trial Strategy: Limited Version,Time‐locked,or Hybrid?

Limited version, time‐locked, and hybrid are three software free trial strategies employed by software firms to exploit increased installed base and/or reduction of consumers' uncertainty about software quality. We develop an analytical model to examine these three software free trial strategies. We find that the hybrid strategy weakly dominates the limited and time‐locked versions, and the intensity of the network effects is a key factor determining which strategy is optimal.     

Optimal Enhancement and Lifetime of Software Systems: A Control Theoretic Analysis

We develop an optimal control model to maximize the net value provided by a software system over its useful life. The model determines the initial number of features in the system, the level of dynamic enhancement effort, and the lifetime of the system. The various factors affecting these optimal choices are systems characteristics (e.g., complexity, age, quality), user learning, and process maturity. We also consider that there is a time lag between the addition of a feature and the realization of its benefit to users. The basic model is extended to consider the decision of replacing the existing system by a new one.     

Does Higher Transparency Lead to More Search in Online Auctions?

In a controlled field experiment, we examine pairs of auctions for identical items under different conditions. We find that auction design features that are under the control of the auctioneer—including information transparency, number of simultaneous auctions, and the degree of overlap between simultaneous auctions—affect bidder search and choice. Clickstream data show that a significant relationship between information transparency and price dispersion can be linked to search. Specifically, the effect of information transparency on price dispersion is fully mediated by lookup behavior. Combining these findings, we make auction design recommendations regarding the provision of product and value information.