Strategy

Companies need tools and models that accurately describe and forecast the diffusion process of new products. Most tools for predicting the diffusion of an innovation, given early data, use aggregate models (such as the Bass model) that capture the impact of advertising and word-of-mouth on adoption. Because of their aggregate nature, however, (i.e., these models treat each month or each year as one observation), they are often unable to produce reliable predictions early in the diffusion process, when such predictions would be most helpful (e.g., in order to adjust the launch campaign).

Since its first publication, Michael J. Mauboussin's popular guide to wise investing has been translated into eight languages and has been named best business book by BusinessWeek and best economics book by Strategy+Business. Now updated to reflect current research and expanded to include new chapters on investment philosophy, psychology, and strategy and science as they pertain to money management, this volume is more than ever the best chance to know more than the average investor.

Consider an economy in which the underlying security returns follow a linear factor model with constant coeffcients. While portfolios that invest in these securities will, in general, have a linear factor structure, it will be one with time-varying coeffcients. However, under certain assumptions regarding the portfolio's investment strategy, it is possible to estimate these time-varying alphas and betas.

Competing organizations are often defined by their niche overlap or structural equivalence in resource dependence, but the very structure that defines competitors can also identify cooperators. There is a fine line between competition and cooperation, but current theories give insufficient guidance as to which will take place and also contribute to the belief that cooperation between competitors is illegitimate. We show that the legitimacy of these practices, as well the evaluation of their welfare implications, are context bound.

Our results are broadly consistent with the predictions of a benign view of the role of investment banks in advising acquisition targets. Fees to investment banks are correlated with attributes of transactions and target firms in ways that make sense if banks are being paid for processing information. The more contingent (and, therefore, risky) the fees, the higher they tend to be, all else held constant. Variation in acquisition premia also can be explained by fundamental deal attributes.

In this paper, we examine the pattern of correlation among consumer price sensitivities for customer purchase incidence decisions across complementary product categories. We use a hierarchical Bayesian multivariate probit model to uncover this pattern. We estimated this model using purchase incidence data for six categories involving three pairs of complementary products.

In many services (e.g., the wireless service industry), consumers choose a service plan according to their expected consumption. In such situations, consumers experience two forms of uncertainty. First, they may be uncertain about the quality of their service provider and can learn about it after repeated use of the service. Second, they may be uncertain about their own usage of minutes and learn about it after observing their actual consumption.

We match Big Mac prices with prices of its ingredients as a unique prism to study real exchange rates (RERs). This approach has several advantages. First, the levels of the Big Mac RER can be measured meaningfully. Second, as the exact composition of a Big Mac is known, the contributions of its tradable and non-tradable components can be estimated relatively precisely. Third, the dynamics of the RER can be studied in a setting free of several biases inherent in CPI-based RERs. Finally, a large cross-country dimension allows us to overturn the Engel result on what drives RERs.