Innovating for cash

Despite companies' almost fanatical worship of innovation, most new products don't generate money. That's because executives don't realize that the approach they take to commercializing a new product is as important as the innovation itself. Different approaches can generate very different levels of profit. Companies tend to favor one of three different innovation approaches, each with its own investment profile, profitability pattern, risk profile, and skill requirements. Most organizations are instinctively integrators: They manage all the steps needed to take a product to market themselves. Organizations can also choose to be orchestrators: They focus on some parts of the commercialization process and depend on partners to manage the rest. And finally, companies can be licensers: They sell or license a new product or idea to another organization that handles the commercialization process. Different innovations require different approaches. Selecting the most suitable approach, the authors' research found, often yields two or three times the profits of the least optimal approach. Yet companies tend to rely only on the mode most familiar to them. Executives would do better to take several different factors into account before deciding which tack to take, including the industry they're trying to enter, the specific characteristics of the innovation, and the risks involved in taking the product to market. By doing so, companies can match the approach to the opportunity and reap the maximum profit. Choosing the wrong approach, like Polaroid did, for example, can lead to the failure of both the product and the company. Optimizing their approaches, as Whirlpool has done, helps ensure that companies' innovations make money.     

Is Race an Important Factor in Bank–Customer Preferences? The Case of Mortgage Lending

This paper tests whether there is a preference by borrowers and lenders of a particular ethnic or racial group that may predispose them to borrow and lend from each other. Using a narrow geographic area called zip code clusters, this paper groups minority-owned and non-minority-owned banks to allow for a homogenous applicant pool from which both borrower and lender preferences can be determined. This study compares Asian-owned, black-owned and Hispanic-owned banks versus white-owned banks that are located in the same zip code and adjacent zip codes. The results show that borrowing preferences exist between all applicant groups and banks from the same racial classification. In addition, some cross-racial borrowing preferences exist. The results show that across sample lending preferences exist for both black and white applicants with black-owned banks and white applicants with white-owned banks that are located in the same area as Asian-owned banks. Also, the results of the within sample lending preference model shows that white-owned banks have a preference for white applicants, at the expense of Hispanic applicants and both white-owned and Asian-owned banks exhibit a preference for Asian applicants.     

The hard side of change management

Everyone agrees that managing change is tough, but few can agree on how to do it. Most experts are obsessed with "soft" issues, such as culture and motivation, but, say the authors, focusing on these issues alone won't bring about change. Companies also need to consider the hard factors-like the time it takes to complete a change initiative, the number of people required to execute it, and so forth. When the authors studied change initiatives at 225 companies, they found a consistent correlation between the outcomes of change programs (success versus failure) and four hard factors, which they called DICE: project duration, particularly the time between project reviews; integrity of performance, or the capabilities of project teams; the level of commitment of senior executives and staff; and the additional effort required of employees directly affected by the change. The DICE framework is a simple formula for calculating how well a company is implementing, or will be able to implement, its change initiatives. The framework comprises a set of simple questions that help executives score their projects on each of the four factors; the lower the score, the more likely the project will succeed. Companies can use DICE assessments to force conversations a bout projects, to gauge whether projects are on track or in trouble, and to manage project portfolios. The authors have used these four factors to predict the outcomes and guide the execution of more than 1,000 change management programs worldwide. Not only has the correlation held, but no other factors (or combination of factors) have predicted outcomes as successfully.     

What makes the stock market jump? An analysis of political risk on Hong Kong stock returns

This paper employs a components-jump volatility filter to investigate the possible market impact of political risk. The filter operates by identifying jump return dates, which are then associated with political events, allowing us to measure the market return and volatility effects of political announcements. Our empirical results show that political developments in Hong Kong have a significant impact on its market volatility and return. The results have some interesting implications for option pricing and political risk management.     

The market for residential real estate brokerage services: Costs of production and economies of scale

Although the market for real estate brokerage services has been the subject of intense scrutiny for many years, little empirical evidence has been forthcoming regarding the performance of this market. This paper employs a translog cost function to model the underlying production function for the residential real estate brokerage industry. The results indicate that, except for very large firms, modest economies of scale persist throughout almost the entire range of output. Our results also indicate that while average firm size is increasing, many real estate firms are too small to take full advantage of the cost reductions possible with a larger scale of operation. Equally important, large firms do not command a competitive advantage over smaller firms, as fer as unit costs are concerned.     

The income elasticity of household energy demand: a quantile regression analysis

This article examines variation in the income elasticity of household energy demand across the energy expenditure distribution using expenditure data from the five most recent Household Budget Surveys (HBSs) in Ireland: the 1987, 1994/1995, 1999/2000, 2004/2005 and 2009/2010 HBS. The analysis uses a two-stage instrumental variable quantile regression approach and is based on each HBS cross section, as well as the overall pooled observations. The estimated elasticities are compared across low- and high-energy-consumption scenarios and to a benchmark elasticity estimated using two-stage least squares. The results provide evidence that there is significant variation in the income elasticities across the energy expenditure distribution and that care must be taken when using the constant mean elasticity for policy purposes. More specifically, any examination of the future impact of a change in income support policy measures on energy consumption should recognize the substantial context-dependent variation in the income elasticity.