Contributions in Merlin

Building on the enactment perspective and past work on the self-fulfilling prophecy, this paper explores how organizational decline can be enacted through self-fulfilling prophecies of decline. We present two self-fulfilling prophecy-based models of organizational decline, one in which decline is enacted unintentionally through the predictions of an organization's managers, and a second in which decline is enacted unintentionally through the predictions of external constituencies. We articulate propositions that capture the dynamics of each model and that are intended as a platform for future empirical research. We also discuss the implications of our theoretical framework for future theory development on the causes of organizational decline, and offer suggestions for managers who wish to avoid organizational decline.

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The financial industry puts the Basle Committee under strain to align regulatory capital with economic capital. This could be reached by allowing more flexibility in the choice of risk measure for regulatory reporting. Markus Leippold and Paolo Vanini show that if banks could use the theoretically more sound risk measure of Expected Shortfall, the three cheers of Stahl (1997) would be reduced to exactly half as many cheers. This would substantially decrease the regulatory capital in most cases. There is no dispute on the necessity of regulating the financial industry. Ideally, a regulation aims at maintaining and improving the safety of the financial industry. At the root of every regulation framework lies the basic idea of calculating a capital reserve as a function of the firm’s total capital and its risk. While the calculation of the firm’s capital is tedious but feasible, the measurement of risk is a difficult task. Consequently, regulators advocate normative and simplified rules applicable to all financial institutions.

This paper analyzes a capacity-planning and pricing problem of a monopolist facing uncertain demand. The model incorporates .soft. and .hard. capacity constraints (soft constraints can be relaxed at a cost while hard constraints cannot be relaxed) and demand uncertainty. The firm receives additional demand information within the planning horizon. The solution to the planning problem depends crucially on what is known about demand at the time of the capacity decision as well as the pricing decision. Historical acquisition costs of capacity are relevant for pricing whenever the same information is available for capacity planning and pricing. However, when the firm receives additional demand information before making the pricing decision, only marginal cost is relevant for pricing. Different types of capacity constraints, i.e., soft vs. hard, affect how much capacity the firm obtains, but not how the firm sets prices.

This paper discusses standardization of information and communications technologies. Standardization has become a domain of firm strategizing with information and communication technology standards being increasingly created through semi-open alliances. The paper analyzes the strategic logic of such standardization alliances based on an in-depth case study of the Bluetooth initiative. Similar to other successful standards described in the standardization literature, Bluetooth has been rapidly adopted by a large number of companies. The author argues that at least part of the success is due to the structure and design of the standardization alliance that promoted Bluetooth.

We analyze a unique data set on multiunit auctions, which contains the actual demand schedules of the bidders as well as the auctionawards in over 400 Swedish Treasury auctions. First, we document that bidders vary their prices, bid dispersion, and the quantity demanded in response to increased uncertainty at the time of bidding. Second,we find that bid shading can be explained by a winner 19s curse 13driven model in which each bidder submits only one bid, despite the fact that the bidders in our data set use much richer bidding strategies.

An Introduction to Wavelets and Other Filtering Methods in Finance and Economics presents a unified view of filtering techniques with a special focus on wavelet analysis in finance and economics. It emphasizes the methods and explanations of the theory that underlies them. It also concentrates on exactly what wavelet analysis (and filtering methods in general) can reveal about a time series. It offers testing issues which can be performed with wavelets in conjunction with the multi-resolution analysis. The descriptive focus of the book avoids proofs and provides easy access to a wide spectrum of parametric and nonparametric filtering methods. Examples and empirical applications will show readers the capabilities, advantages, and disadvantages of each method.

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