The Predictive Power of Internet-Based Product Concept Testing Using Visual Depiction and Animation

One critical step in new product development is selecting from among multiple possible product concepts the one that the firm will carry forward into the marketplace. There is a need for low‐cost, parallel testing of the appeal of new product concepts, the results of which closely mirror ultimate market performance. In this article, the authors first describe an Internet‐based product concept testing method they developed that incorporates virtual prototypes of new product concepts, substituting them for physical prototypes. The method can be used with either static representations of the products or with dynamic representations that demonstrate how the product works through a simulated video clip of its operation. The objective of this method is to allow design teams to select the best of several new concepts within a product category with which to proceed, without having to develop physical prototypes. The authors then provide a rigorous test of both virtual prototype methods against tests using both physical prototypes and attribute‐only (i.e., no visuals), full‐profile conjoint analysis. Nine concepts compete against two actual products in the tests. Market shares from the test using the physical prototypes are defined as the “actual” market shares. Predicted market shares for the attribute‐only, full‐profile conjoint analysis and each of the two virtual prototype methods are compared to those obtained for the physical prototypes. Both static and animated virtual prototype tests produced market shares that closely mirrored those obtained with the physical products, outperforming the set of predictions across the full range of products produced in the attribute‐only conjoint analysis. Interestingly, the attribute‐only conjoint analysis identified the top three products, in correct order. It was unable to differentiate performance below these top three products. Furthermore, it predicted market shares for the top three products to be well below those achieved using physical prototypes. As virtual prototypes cost considerably less to build and test than their physical counterparts, design teams using Internet‐based product concept research may be able to afford to explore a much larger number of concepts. Virtual prototypes and the testing methods associated with them may help reduce the uncertainty and cost of new product introductions by allowing more ideas to be concept tested in parallel with target consumers.     

American depositary receipts: An analysis of international stock price movements

With significant increases in private capital flows across the globe, there has been a rise in the US listing of foreign stocks as American depositary receipts (ADRs). In this study, we employ cointegration techniques and estimate error-correction (EC) models to examine the degree of integration between US and three foreign equity markets. We find that ADRs are cointegrated with ordinary shares trading in the UK, Japan, and Germany, which implies that for long-term investors, they are a substitute for ordinary shares. Our analysis of the dynamic relationships between ADRs and foreign equities suggest that both markets contribute information pertinent to portfolio valuation. However, the foreign markets are found to be the more important source of information.     

The virtual customer

Communication and information technologies are adding new capabilities for rapid and inexpensive customer input to all stages of the product development (PD) process. In this article we review six web‐based methods of customer input as examples of the improved Internet capabilities of communication, conceptualization, and computation. For each method we give examples of user‐interfaces, initial applications, and validity tests. We critique the applicability of the methods for use in the various stages of PD and discuss how they complement existing methods. For example, during the fuzzy front end of PD the information pump enables customers to interact with each other in a web‐based game that provides incentives for truth‐telling and thinking hard, thus providing new ways for customers to verbalize the product features that are important to them. Fast polyhedral adaptive conjoint estimation enables PD teams to screen larger numbers of product features inexpensively to identify and measure the importance of the most promising features for further development. Meanwhile, interactive web‐based conjoint analysis interfaces are moving this proven set of methods to the web while exploiting new capabilities to present products, features, product use, and marketing elements in streaming multimedia representations. User design exploits the interactivity of the web to enable users to design their own virtual products thus enabling the PD team to understand complex feature interactions and enabling customers to learn their own preferences for new products. These methods can be valuable for identifying opportunities, improving the design and engineering of products, and testing ideas and concepts much earlier in the process when less time and money is at risk. As products move toward pretesting and testing, virtual concept testing on the web enables PD teams to test concepts without actually building the product. Further, by combining virtual concepts and the ability of customers to interact with one another in a stock‐market‐like game, securities trading of concepts provides a novel way to identify winning concepts. Prototypes of all six methods are available and have been tested with real products and real customers. These tests demonstrate reliability for web‐based conjoint analysis, polyhedral methods, virtual concept testing, and stock‐market‐like trading; external validity for web‐based conjoint analysis and polyhedral methods; and consistency for web‐based conjoint analysis versus user design. We report on these tests, commercial applications, and other evaluations. © 2002 Elsevier Science Inc. All rights reserved.     

Volatility Spillovers and the Risk-Return Relation Between Stock and Foreign Exchange Markets in Brazil

We examine the evidence of mean and volatility spillovers between stock and foreign exchange markets in Brazil with multivariate GARCH models and nonlinear Granger causality tests. We also use a multivariate GARCH-in-mean model to assess the relationship between risk and return in these markets. The results indicate that the stock market leads the foreign exchange market in price formation and that nonlinear Granger causalities from the exchange market to the stock market do occur. Part of these nonlinear causalities are explained by volatility spillovers. We show that exchange rate volatility affects not only stock market volatility but also stock returns.     

The shifting value of federal deposit insurance: Implications for reform

This research examines the relationship between the value of federal deposit insurance and bank size. We conclude that the value of deposit insurance has often been greater for the largest bank-holding companies since 1981. This differential is consistent with the notion that largest banks have greater ability to circumvent regulatory and/or market discipline. The source of this differential appears to be due to holding less capital rather than greater asset risk. Insurance costs net of the value of deposit insurance are also relatively lower for the largest banks and have become more so since 1981. These results suggest that recent proposals to improve the deposit insurance system should be evaluated based on their ability to effect even-handed discipline throughout the banking industry to eliminate and forestall further creation of this large institution bias.     

Integration of technical and value issues in air quality policy formation: A case study

This paper deals with the problem of air quality policy making in urban areas where the automobile is the major source of air pollution. A quantitative method for integrating technical and social value issues is outlined and applied to air quality policy formation in Denver, Colorado. The implications of this study for quantitative analysis in policy analysis in general are discussed.The study centers on decisions to be made now for managing the future air quality in the Denver metropolitan region. At the time of the study Denver was in violation of the National Ambient Air Quality Standards for two gaseous pollutants—carbon monoxide and ozone. Three elements of the study are described—structural analysis, quantitative analysis and contextual analysis.The conclusions of the study are: (1) Under 1977 Clean Air Act standards, strategies intended to reduce emissions from automobiles will assure attainment of ambient standards in Denver by approx. 1990. The impacts of these strategies upon the valued dimensions of health effects, cost and lifestyle appear acceptable. The acceptability of adding regulations to accomplish an earlier date of attainment, such as transportation controls, could not be resolved. (2) If federal emissions standards are relaxed, Denver cannot meet ambient standards without making difficult tradeoffs among health effects, economic factors, and citizens' mobility and convenience. (3) Continued increase in the use of diesel automobiles will substantially worsen Denver's “brown cloud” problem. Our analysis also indicates that a “do nothing” option was not acceptable. The choice of a strategy for reducing particulates from diesels involves tradeoffs among health, haze and cost.     

STRUCTURAL CHANGES IN RETURN-GENERATING MODELS AROUND TENDER OFFERS: A NOTE

This note investigates the role of changes in the parameters of return-generating models in explaining the pattern of abnormal returns accruing to target and bidding firms around tender-offer announcements. Employing a varyingparameter modeling approach the study finds lower abnormal returns to target firms and increased abnormal returns to bidding firms, relative to standard approaches. However, use of this approach fails to refute the common findings that mean abnormal returns are large for target firms and negligible for bidding firms.     

Pricing of non-redundant derivatives in a complete market

We consider a complete financial market with primitive assets and derivatives on these primitive assets. Nevertheless, the derivative assets are non-redundant in the market, in the sense that the market is complete,only with their existence. In such a framework, we derive an equilibrium restriction on the admissible prices of derivative assets. The equilibrium condition imposes a well-ordering principle restricting the set of probability measures that qualify as candidate equivalent martingale measures. This restriction is preference free and applies whenever the utility functions belong to the general class of Von-Neumann Morgenstern functions. We provide numerical examples that show the applicability of the restriction for the computation of option prices.We are indebted to the editor Marti Subrahmanyam and two anonymous referees for very constructive comments. We have also benefitted from conversations with Nour Meddahi. We would like to thank seminar participants at Université de Montréal, Washington University, HEC Montréal, Ecole Polytechnique de Tunisie, Institut Henri Poincaré, Trento Mathematical Finance Conference (1997), Aspet (FIQUAM) Conference (1998) as well as the participants at the Quantitative Methods of Finance Conference, Australia, 1997.This author gratefully acknowledges the financial support of INQUIRE-Europe.     

New Product Development 2.0: Preference Markets—How Scalable Securities Markets Identify Winning Product Concepts and Attributes*

Preference markets address the need for scalable, fast, and engaging market research in new product development. The Web 2.0 paradigm, in which users contribute numerous ideas that may lead to new products, requires new methods of screening those ideas for their marketability, and preference markets offer just such a mechanism. For faster new product development decisions, a flexible prioritization methodology is implemented for product features and concepts, one that scales up in the number of testable alternatives, limited only by the number of participants. New product preferences for concepts, attributes, and attribute levels are measured by trading stocks whose prices are based upon share of choice of new products and features. A conceptual model of scalable preference markets is developed and tested experimentally. Benefits of the methodology are found to include speed (less than one hour per trading experiment), scalability (question capacity grows linearly in the number of traders), flexibility (features and concepts can be tested simultaneously), and respondent enthusiasm for the method.