Information Acquisition and Voluntary Disclosure in an Export‐Processing System

We study a strategic information management problem in the export‐processing trade, where the buyer controls the raw material input and sales and the producer is responsible for production. The production is vulnerable to random yield risk. The producer can exert a costly effort to acquire the private yield rate information and discretionarily share it with the buyer. We develop a sequential Bayesian game model that captures three key features of the system—endogenous information endowment, voluntary disclosure, and ex post information sharing—a significant departure from the literature. The optimal disclosure strategy is driven by the trade‐off between the gains from Pareto efficiency improvement and self‐interested overproduction. It is specified by two thresholds on yield rate: only the middle‐yield producers (with yield rate between these two thresholds) share private information to improve supply‐demand match; the low‐ and high‐yield producers withhold information to extract excess input from the buyer. The buyer in response penalizes nondisclosure with reduced input and rewards information sharing with a larger order. This strategic interaction is further exacerbated by the double marginalization effect from decentralization, resulting in severe efficiency loss. We examine the effectiveness of three corrective mechanisms—vertical integration, mandatory disclosure, and production restriction—and reveal the costs of information suppressive effect and overinvestment incentive and the benefit from concessions on the processing fee. Our study endogenizes the asymmetric supply risk and provides the first attempt to rationalize the strategic interactions of informational and operational incentives in the export‐processing system.     

Managing Supply Chain Execution: Monitoring Timeliness and Correctness via Individualized Trace Data

Improvements in information technologies provide new opportunities to control and improve business processes based on real‐time performance data. A class of data we call individualized trace data (ITD) identifies the real‐time status of individual entities as they move through execution processes, such as an individual product passing through a supply chain or a uniquely identified mortgage application going through an approval process. We develop a mathematical framework which we call the State‐Identity‐Time (SIT) Framework to represent and manipulate ITD at multiple levels of aggregation for different managerial purposes. Using this framework, we design a pair of generic quality measures—timeliness and correctness—for the progress of entities through a supply chain. The timeliness and correctness metrics provide behavioral visibility that can help managers to grasp the dynamics of supply chain behavior that is distinct from asset visibility such as inventory. We develop special quality control methods using this framework to address the issue of overreaction that is common among managers faced with a large volume of fast‐changing data. The SIT structure and its associated methods inform managers on if, when, and where to react. We illustrate our approach using simulations based on real RFID data from a Walmart RFID pilot project.     

Using a Familiar Risk Comparison Within a Risk Ladder to Improve Risk Understanding by Low Numerates: A Study of Visual Attention

Previous experimental research provides evidence that a familiar risk comparison within a risk ladder is understood by low‐ and high‐numerate individuals. It especially helps low numerates to better evaluate risk. In the present study, an eye tracker was used to capture individuals’ visual attention to a familiar risk comparison, such as the risk associated with smoking. Two parameters of information processing—efficiency and level—were derived from visual attention. A random sample of participants from the general population (N= 68) interpreted a given risk level with the help of the risk ladder. Numeracy was negatively correlated with overall visual attention on the risk ladder (r_s=?0.28, p= 0.01), indicating that the lower the numeracy, the more the time spent looking at the whole risk ladder. Numeracy was positively correlated with the efficiency of processing relevant frequency (r_s= 0.34, p < 0.001) and relevant textual information (r_s= 0.34, p < 0.001), but not with the efficiency of processing relevant comparative information and numerical information. There was a significant negative correlation between numeracy and the level of processing of relevant comparative risk information (r_s=?0.21, p < 0.01), indicating that low numerates processed the comparative risk information more deeply than the high numerates. There was no correlation between numeracy and perceived risk. These results add to previous experimental research, indicating that the smoking risk comparison was crucial for low numerates to evaluate and understand risk. Furthermore, the eye‐tracker method is promising for studying information processing and improving risk communication formats.     

The Microeconomics of Efficient Group Behavior: Identification1

Consider a group consisting of S members facing a common budget constraint p'ξ=1: any demand vector belonging to the budget set can be (privately or publicly) consumed by the members. Although the intragroup decision process is not known, it is assumed to generate Pareto‐efficient outcomes; neither individual consumptions nor intragroup transfers are observable. The paper analyzes when, to what extent, and under which conditions it is possible to recover the underlying structure—individual preferences and the decision process—from the group's aggregate behavior. We show that the general version of the model is not identified. However, a simple exclusion assumption (whereby each member does not consume at least one good) is sufficient to guarantee generic identifiability of the welfare‐relevant structural concepts.     

New Service Development Competence and Performance: An Empirical Investigation in Retail Banking

What can service firms do to improve their ability to offer new services? In this paper we argue that new service development success results from building a competence in the management of service development resources and routines. We conceptualize new service development competence as a multidimensional, second‐order latent construct that is represented by a system of four interrelated and complementary dimensions: (1) formalized new service development processes, (2) market acuity, (3) new service development strategy, and (4) information technology use and experience. We hypothesize that the growth of new service development competence is related to improved new service development performance. Using structural equations modeling, we analyze survey data from 166 retail banks and report three key empirical findings. First, we show that the four hypothesized dimensions are statistically significant in defining new service development competence. Second, contrary to conventional wisdom in new product development, we find that formalized processes play a lesser role in the success of new service development compared with the other three dimensions. Instead, market acuity—which captures the firm's ability to see the competitive environment clearly and to anticipate and respond to customers' evolving needs and wants—was the most important new service development competence indicator. Finally, we demonstrate the positive effect of new service development competence on new service development performance and show that new service development competence is also significantly related to business‐level performance. Together, our empirical results suggest that complementary benefits arise from the adoption of a more holistic approach to the management of new service development at the program level.     

How Anxiety Leads to Suboptimal Decisions Under Risky Choice Situations

The current research proposes that situationally activated anxiety—whether incidental or integral—impairs decision making. In particular, we theorize that anxiety drives decisionmakers to more heavily emphasize subjective anecdotal information in their decision making, at the expense of more factual statistical information—a deleterious heuristic called the anecdotal bias. Four studies provide consistent support for this assertion. Studies 1A and 1B feature field experiments that demonstrate the role of incidental anxiety in enhancing the anecdotal bias in a choice context. Study 2 builds on these findings, manipulating individuals’ incidental anxiety and showing how this affects the anecdotal bias in the context of message evaluations. Study 2 also provides direct evidence that only high‐arousal negative emotions such as anxiety/worry enhance the anecdotal bias, not just any negative emotion (e.g., sadness). While the first three studies examine how incidental anxiety impacts choice, the last study demonstrates the effect of integral anxiety on decision making, manipulating anxiety by intensifying participants’ perceived risk. Our results show that—consistent with findings from our first three studies—the anecdotal bias is enhanced when anxiety is heightened by individuals’ perception of risk.     

Multiple Conceptualizations of Small Business Web Use and Benefit*

Small businesses play an important role in the U.S. economy and there is anecdotal evidence that use of the Web is beneficial to such businesses. There is, however, little systematic analysis of the conditions that lead to successful use of and thereby benefits from the Web for small businesses. Based on the innovation adoption, organizations, and information systems (IS) implementation literature, we identify a set of variables that are related to adoption, use, and benefits of information technology (IT), with particular emphasis on small businesses. These variables are reflective of an organization's contextual characteristics, its IT infrastructure, Web use, and Web benefits. Since the extant research does not suggest a single theoretical model for Web use and benefits in the context of small businesses, we adopt a modeling approach and explore the relationships between “context‐IT‐use‐benefit” (CIUB) through three models—partial‐mediator, reduced partial‐mediator, and mediator. These models posit that the extent of Web use by small businesses and the associated benefits are driven by organizations’ contextual characteristics and their IT infrastructure. They differ in the endogeneity/exogeneity of the extent of IT sophistication, and in the direct/mediated effects of organizational context. We examine whether the relationships between variables identified in the literature hold within the context of these models using two samples of small businesses with national coverage, including various sizes, and representing several industry sectors. The results show that the evidence for patterns of relationships is similar across the two independent samples for two of these models. We highlight the relationships within the reduced partial‐mediator and mediator models for which conclusive evidence are given by both samples. Implications for small business managers and providers of Web‐based technologies are discussed.     

INSTRUCTING OPERATIONS DESIGN: AN EXPERIENTIAL APPROACH

Teaching an operations design course has major pedagogical challenges. (1) The design topics—output, process, facility, and work design—are necessarily taught sequentially, yet the decisions are integrative. (2) Instruction must be generic to service or product producers. (3) Discussing output design is difficult since students typically have had no exposure to the “product language” of engineering graphics. (4) No text is available which examines in sufficient depth all the operations design decisions. (5) Cases necessarily depict historical situations—process technologies and economic data—while operations managers must plan future directions for their productive systems. (6) While the commercial world contains fresh information and data, students are inexperienced in obtaining knowledge from the real world. (7) While the course presents an operations management perspective, students must recognize the information, data, and cooperation necessary from the other functional areas to successfully complete the operations design. To help overcome these seven pedagogical challenges, the students in the undergraduate and graduate operation design courses complete a comprehensive feasibility study for a new product or service and the entire productive system.     

Dynamic Simulation as an Approach to Understanding Hurricane Risk Response: Insights from the Stormview Lab

This article investigates the use of dynamic laboratory simulations as a tool for studying decisions to prepare for hurricane threats. A prototype web‐based simulation named Stormview is described that allows individuals to experience the approach of a hurricane in a computer‐based environment. In Stormview participants can gather storm information through various media, hear the opinions of neighbors, and indicate intentions to take protective action. We illustrate how the ability to exert experimental control over the information viewed by participants can be used to provide insights into decision making that would be difficult to gain from field studies, such as how preparedness decisions are affected by the nature of news coverage of prior storms, how a storm's movement is depicted in graphics, and the content of word‐of‐mouth communications. Data from an initial application involving a sample of Florida residents reveal a number of unexpected findings about hurricane risk response. Participants who viewed forecast graphics, which contained track lines depicting the most likely path of the storm, for example, had higher levels of preparation than those who saw graphics that showed only uncertainty cones—even among those living far from the predicted center path. Similarly, the participants who were most likely to express worry about an approaching storm and fastest to undertake preparatory action were those who, ironically, had never experienced one. Finally, external validity is evidenced by a close rank‐order correspondence between patterns of information use revealed in the lab and that found in previous cross‐sectional field studies.     

Dynamic Supply Risk Management with Signal‐Based Forecast,Multi‐Sourcing,and Discretionary Selling

We examine the critical role of advance supply signals—such as suppliers’ financial health and production viability—in dynamic supply risk management. The firm operates an inventory system with multiple demand classes and multiple suppliers. The sales are discretionary and the suppliers are susceptible to both systematic and operational risks. We develop a hierarchical Markov model that captures the essential features of advance supply signals, and integrate it with procurement and selling decisions. We characterize the optimal procurement and selling policy, and the strategic relationship between signal‐based forecast, multi‐sourcing, and discretionary selling. We show that higher demand heterogeneity may reduce the value of discretionary selling, and that the mean value‐based forecast may outperform the stationary distribution‐based forecast. This work advances our understanding on when and how to use advance supply signals in dynamic risk management. Future supply risk erodes profitability but enhances the marginal value of current inventory. A signal of future supply shortage raises both base stock and demand rationing levels, thereby boosting the current production and tightening the current sales. Signal‐based dynamic forecast effectively guides the firm's procurement and selling decisions. Its value critically depends on supply volatility and scarcity. Ignoring advance supply signals can result in misleading recommendations and severe losses. Signal‐based dynamic supply forecast should be used when: (a) supply uncertainty is substantial, (b) supply‐demand ratio is moderate, (c) forecast precision is high, and (d) supplier heterogeneity is high.     

What Defines Us as Professionals in the Field of Risk Analysis?

In a recent issue of Risk Analysis, the then‐President of the Society for Risk Analysis (SRA), Pamela Williams, has some interesting reflections about the risk analysis field. She states that the ability and desire to tackle difficult problems using a risk analytical approach is what uniquely defines us as professionals in the field of risk analysis. The point of departure for her discussion is interviews with the plenary speakers of the 2014 SRA Annual Meeting, who addressed two divisive topics: hydraulic fracking and marijuana use. She points to several themes that invite contributions from the field of risk analysis, including: Has the full spectrum of potential risks and benefits been identified and weighted, and what are the risk tradeoffs or countervailing risks? Inspired by Williams's reflections, and by analyzing the issues raised in the interviews, this article seeks to clarify what our field is really providing. A main conclusion of the article is that it is essential to acknowledge that professionals in the field of risk analysis merely support the tackling of such problems, and that their genuine competence—that which distinguishes them from other professionals—lies in the risk analytical approach itself.     

Route vs. Segment: An Experiment on Real‐Time Travel Information in Congestible Networks

We report the results of an experimental study of route choice in congestible networks with a common origin and common destination. In one condition, in each round of play network users independently committed themselves at the origin to a three‐segment route; in the other condition, they chose route segments sequentially at each network junction upon receiving en route information. At the end of each round, players received ex‐post complete information about the distribution of the route choices. Although the complexity of the network defies analysis by common users, traffic patterns in both conditions converged rapidly to the equilibrium solution. We account for the observed results by a Markov adaptive learning model postulating regret minimization and inertia. We find that subjects' learning behavior was similar across conditions, except that they exhibited more inertia in the condition with en route information.     

Long‐Term Contracting: The Role of Private Information in Dynamic Supply Risk Management

We examine the critical role of evolving private information in managing supply risk. The problem features a dyadic channel where a dominant buyer operates a multiperiod inventory system with lost sales and fixed cost. He replenishes from a supplier, whose private state of production is vulnerable to random shocks and evolves dynamically over time. We characterize the optimal inventory policy with a simple semi‐stationary structure; it distorts order quantity for limiting information rent only in the initial period; the optimal payment compensates for production cost in every period but concedes real information rent only in the initial period. These properties allow us to derive an easy‐to‐implement revenue‐sharing contract that facilitates ex ante strategic planning and ex post dynamic execution. This work advances our understanding on when and how to use private information in dynamic risk management.     

LYING ABOUT WHAT YOU KNOW OR ABOUT WHAT YOU DO?

We compare communication about private information to communication about actions in a one‐shot 2‐person public good game with private information. The informed player, who knows the exact return from contributing and whose contribution is unobserved, can send a message about the return or her contribution. Theoretically, messages can elicit the uninformed player's contribution, and allow the informed player to free‐ride. The exact language used is not expected to matter. Experimentally, however, we find that free‐ride depends on the language: the informed player free‐rides less—and thereby lies less frequently—when she talks about her contribution than when she talks about the return. Further experimental evidence indicates that it is the promise component in messages about the contribution that leads to less free‐ride and less lying.     

Product Design and Supply Chain Coordination Under Extended Producer Responsibility

Extended Producer Responsibility (EPR) legislation focuses on the life‐cycle environmental performance of products and has significant implications for management theory and practice. In this paper, we examine the influence of EPR policy parameters on product design and coordination incentives in a durable product supply chain. We model a manufacturer supplying a remanufacturable product to a customer over multiple periods. The manufacturer invests in two design attributes of the product that impact costs incurred by the supply chain—performance, which affects the environmental impact of the product during use, and remanufacturability, which affects the environmental impact post‐use. Consistent with the goals of EPR policies, the manufacturer and the customer are required to share the environmental costs incurred over the product's life cycle. The customer has a continuing need for the services of the product and optimizes between the costs of product replacement and the costs incurred during use. We demonstrate how charges during use and post‐use can be used as levers to encourage environmentally favorable product design. We analyze the impact of supply chain coordination on design choices and profit and discuss contracts that can be used to achieve coordination, both under symmetric and asymmetric information about customer attributes.     

Identification and Estimation of Average Partial Effects in “Irregular” Correlated Random Coefficient Panel Data Models

In this paper we study identification and estimation of a correlated random coefficients (CRC) panel data model. The outcome of interest varies linearly with a vector of endogenous regressors. The coefficients on these regressors are heterogenous across units and may covary with them. We consider the average partial effect (APE) of a small change in the regressor vector on the outcome (cf. Chamberlain (1984), Wooldridge (2005a)). Chamberlain (1992) calculated the semiparametric efficiency bound for the APE in our model and proposed a √N‐consistent estimator. Nonsingularity of the APE's information bound, and hence the appropriateness of Chamberlain's (1992) estimator, requires (i) the time dimension of the panel (T) to strictly exceed the number of random coefficients (p) and (ii) strong conditions on the time series properties of the regressor vector. We demonstrate irregular identification of the APE when T = p and for more persistent regressor processes. Our approach exploits the different identifying content of the subpopulations of stayers—or units whose regressor values change little across periods—and movers—or units whose regressor values change substantially across periods. We propose a feasible estimator based on our identification result and characterize its large sample properties. While irregularity precludes our estimator from attaining parametric rates of convergence, its limiting distribution is normal and inference is straightforward to conduct. Standard software may be used to compute point estimates and standard errors. We use our methods to estimate the average elasticity of calorie consumption with respect to total outlay for a sample of poor Nicaraguan households.     

Level‐k Auctions: Can a Nonequilibrium Model of Strategic Thinking Explain the Winner's Curse and Overbidding in Private‐Value Auctions?

This paper proposes a structural nonequilibrium model of initial responses to incomplete‐information games based on “level‐k” thinking, which describes behavior in many experiments with complete‐information games. We derive the model's implications in first‐ and second‐price auctions with general information structures, compare them to equilibrium and Eyster and Rabin's (2005) “cursed equilibrium,” and evaluate the model's potential to explain nonequilibrium bidding in auction experiments. The level‐k model generalizes many insights from equilibrium auction theory. It allows a unified explanation of the winner's curse in common‐value auctions and overbidding in those independent‐private‐value auctions without the uniform value distributions used in most experiments.     

Waiting for News in the Market for Lemons

We study a dynamic setting in which stochastic information (news) about the value of a privately informed seller's asset is gradually revealed to a market of buyers. We construct an equilibrium that involves periods of no trade or market failure. The no‐trade period ends in one of two ways: either enough good news arrives, restoring confidence and markets reopen, or bad news arrives, making buyers more pessimistic and forcing capitulation that is, a partial sell‐off of low‐value assets. Conditions under which the equilibrium is unique are provided. We analyze welfare and efficiency as they depend on the quality of the news. Higher quality news can lead to more inefficient outcomes. Our model encompasses settings with or without a standard static adverse selection problem—in a dynamic setting with sufficiently informative news, reservation values arise endogenously from the option to sell in the future and the two environments have the same equilibrium structure.     

The Concepts of Risk,Safety, and Security: Applications in Everyday Language

The concepts of risk, safety, and security have received substantial academic interest. Several assumptions exist about their nature and relation. Besides academic use, the words risk, safety, and security are frequent in ordinary language, for example, in media reporting. In this article, we analyze the concepts of risk, safety, and security, and their relation, based on empirical observation of their actual everyday use. The “behavioral profiles” of the nouns risk, safety, and security and the adjectives risky, safe, and secure are coded and compared regarding lexical and grammatical contexts. The main findings are: (1) the three nouns risk, safety, and security, and the two adjectives safe and secure, have widespread use in different senses, which will make any attempt to define them in a single unified manner extremely difficult; (2) the relationship between the central risk terms is complex and only partially confirms the distinctions commonly made between the terms in specialized terminology; (3) whereas most attempts to define risk in specialized terminology have taken the term to have a quantitative meaning, nonquantitative meanings dominate in everyday language, and numerical meanings are rare; and (4) the three adjectives safe, secure, and risky are frequently used in comparative form. This speaks against interpretations that would take them as absolute, all‐or‐nothing concepts.     

Multiple Temptations

We use a preference‐over‐menus framework to model a decision maker who is affected by multiple temptations. Our two main axioms on preference—exclusion and inclusion—identify when the agent would want to restrict his choice set and when he would want to expand his choice set. An agent who is tempted would want to restrict his choice set by excluding the normatively worst alternative of that choice set. Simultaneously, he would want to expand his choice set by including a normatively superior alternative. Our representation identifies the agent's normative preference and temptations, and suggests the agent is uncertain which of these temptations will affect him. We provide examples to illustrate how our model improves on those of Gul and Pesendorfer (2001) and Dekel, Lipman, and Rustichini (2009).