How industries change

It's fairly obvious: To make intelligent investments within your organization, you need to understand how your whole industry is changing. But such knowledge is not always easy to come by. Companies misread clues and arrive at false conclusions all the time. To truly understand where your industry is headed, you have to take a long-term, high-level look at the context in which you do business, says Boston University professor Anita McGahan. She studied a variety of businesses from a cross section of industries over a ten-year period, examining how industry structure affects business profitability and investor returns. Her research suggests that industries evolve along one of four distinct trajectories--radical, progressive, creative, and intermediating--that set boundaries on what will generate profits in a business. These four trajectories are defined by two types of threats. The first is when new, outside alternatives threaten to weaken or make obsolete core activities that have historically generated profits for an industry. The second is when an industry's core assets--its resources, knowledge, and brand capital--fail to generate value as they once did. Industries undergo radical change when core assets and core activities are both threatened with obsolescence; they experience progressive change when neither are jeopardized. Creative change occurs when core assets are under threat but core activities are stable, and intermediating change happens when core activities are threatened while core assets retain their capacity to create value. If your company's innovation strategy is not aligned with your industry's change trajectory, your plan for achieving returns on invested capital cannot succeed, McGahan says. But if you understand which path you're on, you can determine which strategies will succeed and which will backfire.     

Innovation for Inclusive Growth: Towards a Theoretical Framework and a Research Agenda

Inclusive innovation, which we define as innovation that benefits the disenfranchised, is a process as well as a performance outcome. Consideration of inclusive innovation points to inequalities that may arise in the development and commercialization of innovations, and also acknowledges the inequalities that may occur as a result of value creation and capture. We outline opportunities for the development of theory and empirical research around this construct in the fields of entrepreneurship, strategy, and marketing. We aim for a synthesis in views of inclusive innovation and call for future research that deals directly with value creation and the distributional consequences of innovation.     

How Industries Evolve

Firms can improve their performance by tailoring investments to ride industry trends rather than to fight them. This article sheds light on how. It argues that better corporate performance hinges on understanding how industries evolve and that the main frameworks currently in use (the five forces and the S-curve/product life cycle models) are incomplete for this purpose. Building on an extensive body of fieldwork and statistical research, the author identifies four basic models of industry evolution which she calls 'receptive', 'blockbuster', 'radical organic', and 'intermediating'. Each kind of evolution involves specific kinds of risks, and each carries different implications for the relevance of established capabilities and investment priorities.     

The development of capabilities in new firms

This research explores evidence of corporate capabilities for conducting acquisition and alliance deals in young firms. We hypothesize that investors conjecture about the future based on information about a firm's capabilities. Each successive deal carries intrinsic value, creates experience, generates feedback, and yields information about the firm's underlying capabilities. We evaluate whether stock prices impute expectations that firms will capably pursue particular programs of acquisitions and alliances. The analysis covers how investor responses change across successive deals on the theory that firms with a concentrated program of deals may develop capabilities more intensively than those with programs that involve both acquisitions and alliances. The dataset covers the population of firms that went through an initial public offering (IPO) in the United States between 1988 and 1999. It contains information on all of their post‐IPO acquisitions and alliances, and on how their stock prices changed in response to the announcement of each deal. The results suggest that within the first year after IPO, investors expect firms to execute particular streams of alliances and acquisitions that reflect their unique histories of demonstrated capabilities. We also find evidence that investors cannot fully anticipate deal programs. The findings support a capabilities‐based view of the firm and also show that accurate inference using event‐study methods may require digging deep into the early histories of firms. Copyright © 2009 John Wiley & Sons, Ltd.     

The choice among acquisitions,alliances, and divestitures

This paper investigates how firms choose among acquisitions, alliances, and divestitures when they decide to expand or contract their boundaries. The dataset covers 9276 deals announced and completed by 86 members of the Fortune 100 between 1990 and 2000. Our findings support explanations based on resources, transaction costs, internalization, organizational learning, social embeddedness, asymmetric information, and real options, and suggest that these theories are highly related and complementary. We find less consistent support for theories based on agency costs and asset indivisibilities. The strong role of firm attributes explains in part why firms may pre‐specify whether they will pursue acquisitions, alliances, or divestitures as part of their corporate strategies. Copyright © 2005 John Wiley & Sons, Ltd.     

S&P 500 trading strategies and stock betas

This paper shows that S&P 500 stock betas are overstatedand the non-S&P 500 stock betas are understated becauseof liquidity price effects caused by the S&P 500 tradingstrategies. The daily and weekly betas of stocks added to theS&P 500 index during 1985-1989 increase, on average, by0.211 and 0.130. The difference between monthly betas of otherwisesimilar S&P 500 and non-S&P 500 stocks also equals 0.125during this period. Some of these increases can be explainedby the reduced nonsynchroneity of S&P 500 stock prices,but the remaining increases are explained by the price pressureor excess volatility caused by the S&P 500 trading strategies.I estimate that the price pressures account for 8.5 percentof the total variance of daily returns of a value-weighted portfolioof NYSE/AMEX stocks. The negative own autocorrelations in S&P500 index returns and the negative cross autocorrelations betweenS&P 500 stock returns provide further evidence consistentwith the price pressure hypothesis.     

Government Revenue and Child and Maternal Mortality

Open Economies Review - Most maternal and child deaths result from inadequate access to the critical determinants of health: clean water, sanitation, education and healthcare, which are also among...