Prior evaluations are frequently challenged and need to be revised. We propose that an important determinant of such revisions is the degree to which the challenge provides an opportunity to compare the target against a competitor. Whenever a challenge offers an opportunity, the information contained in the challene will carry a disproportionate weight in the revised judgments. We call this proposition the comparison-revision hypothesis.
This paper introduces a class of state dependent jump (SDJ) models in which the arrival intensity and jump sizes depend on a given set of state variables, including lagged jumps. With this model, we investigate the structure of jumps to U.S. equity indices, concentrating on the predictability of jumps times if found for all of the indices considered: Standard and Poor's 500 and Mid-Cap, the Russell 1000, 2000, and 3000 indices, the Wilshire 5000 and the Nasdaq 100 (NDX).
Research extending over twenty years in behavioral decision theory has led to the development of two important research streams--mental accounting and reason-based choice. This paper explores recent research on the role of mental accounting and reason-based choice in the construction of consumer preferences. Evidence suggests that the principles of mental accounting often regulate the purchase and consumption of luxuries and that reasons may play an important part in this process.
Affective states of the same valence may have distinct, yet predictable, influences on decision processes. Results from three experiments show that, in gambling decisions, as well as in jobselection decisions, sad individuals are biased in favor of highrisk/high-reward options, whereas anxious individuals are biased in favor of low-risk/low-reward options. We argue that these biases occur because anxiety and sadness convey distinct types of information to the decision-maker and prime different goals.
Stochastic Economic Lot Scheduling Problems (ELSPs) involve settings where several items need to be produced in a common facility with limited capacity, under significant uncertainty regarding demands, unit production times, setup times, or combinations thereof. We consider systems where some products are made-to-stock while another product line is made-to-order. We present a rich and effective class of strategies for which a variety of cost and performance measures can be evaluated and optimized efficiently by analytical methods.
We examine the ability of a dynamic asset-pricing model to explain the returns on G7-country stock market indices. We extend Campbell's (1996) asset-pricing model to investigate international equity returns. We also utilize and evaluate recent evidence on the predictability of stock returns. We find some evidence for the role of hedging demands in explaining stock returns and compare the predictions of the dynamic model to those from the static CAPM. Both models fail in their predictions of average returns on portfolios of high book-to-market stocks across countries.
This paper deals with Markov decision processes with a countable state space. We demonstrate that a single, relatively simple condition suffices to guarantee that the value-iteration method converges and that an optimal policy can be computed via this method, once the existence of a solution to the average cost optimality equation has been established via any of the many available sets of existence conditions.
Marketers all over the world agree that the Internet will have a major impact on the way firms do business. What changes will exactly occur, however, is hard to predict as the Internet is in a phase of rapid growth and constant change. Patterns are difficult to isolate, especially since despite its explosive growth, today, the Net is still in its infancy, only being available to a small proportion of people. In spite of this general lack of reliable patterns, one consensus among managers seems to be that the Internet is likely to intensify price competition.