Improving sourcing decisions in NPD projects: Monetary quantification of points of difference

During new product development (NPD), firms make critical design and sourcing decisions that determine the new product's cost, performance, competitive position, and profitability. The purchase price of materials and components for the new product provides only part of the picture for design and sourcing decisions. All-encompassing analyses of cost and performance, such as total cost of ownership, are extraordinarily difficult to implement because they are demanding in terms of time, data and cooperation. We study monetary quantification of points of difference, which enables an NPD team to base its decisions instead on more focused, strategically-pertinent analyses of costs and performance. We propose a substantive model of its antecedents and consequences. We then test this model with data from matched samples of 144 project leaders and 144 cost analysts who participated in the same NPD projects. Using structural equation modeling, we also test hypothesized differences in perspectives between project leaders and cost analysts. Results demonstrate the pivotal role of monetary quantification of points of difference among the sourcing alternatives being considered, especially for cost analysts. Results also demonstrate that Decision Justification to senior management drives the NPD team's decision-making process. Finally, monetary quantification of points of difference leads to Uncertainty Reduction, which is found to be the primary antecedent of the judged success of applying analysis of cost and performance.     

Religion and cooperation in a public goods experiment

We test whether religion affects adult subjects' decisions in a repeated public goods experiment. Contribution levels are not influenced by religious affiliation or participation. However, the decline with repetition is smaller among religious subjects, suggesting that religion may sustain cooperation.     

Use-Value Assessment Tax Expenditures in Urban Areas

Use-value assessment is the practice of valuing land for property tax purposes in its current use, rather than at its full market value. This practice is widespread in the U.S. and is intended to reduce the property tax burden on agricultural land near urban areas and slow the pace of land development. We examine the foregone property tax revenue, or tax expenditure, due to use-value assessment. Data sets for two case studies are employed in empirical estimation of spatial models of the difference between market value and use value, providing the analytic basis for estimates of tax expenditures.     

The US Housing Market: Asset Pricing Forecasts Using Time Varying Coefficients

The US housing market has experienced significant cyclical volatility over the last twenty-five years due to major structural changes and economic fluctuations. In addition, the housing market is generally considered to be weak form inefficient. Houses are relatively illiquid, exceptionally heterogeneous, and are associated with large transactions costs. As such, past research has shown that it is possible to predict, at least partially, the time path of housing prices. The ability to predict housing prices is important such that investors can make better asset allocation decisions, including the pricing and underwriting of mortgages. Most of the prior studies examining the US housing market have employed constant coefficient approaches to forecast house price movements. However, this approach is not optimal as an examination of data reveals substantial sub-sample parameter instability. To account for the parameter instability, we employ alternative estimation methodologies where the estimated parameters are allowed to vary over time. The results provide strong empirical evidence in favor of utilizing the rolling Generalized Autoregressive Conditional Heteroskedastic (GARCH) Model and the Kalman Filter with an Autoregressive Presentation (KAR) for the parameters time variation. Lastly, we provide out-of-sample forecasts and demonstrate the precision of our approach.     

REACTIONS TO REGULATION OF ACCOUNTING FOR GOODWILL

Regulations designed to achieve “uniformity in practice” in Australian firms' reporting of goodwill were first adopted in 1985 with the introduction of AAS18. Because of the requirement to amortise purchased goodwill, a number of firms either did not comply or took evasive actions to mitigate the effects of the standard. This paper documents and explains the pre-regulation cross-sectional variation in accounting practices. Reactions to the set of regulations introduced between 1985 and 1989 are then described and explained through a longitudinal study of accounting policy choice. We develop hypotheses which explain why the goodwill accounting rules reversed relations between the accounting methods adopted by firms and both the earnings effect of compliance and the market value of the firm's goodwill. The results are confirmatory.     

Timestyles: Role factor influences on the convergence and divergence of couples' complementary and substitute activity patterns

Using a role theory framework, this research focuses on convergence and divergence in complementary and substitute activities for husbands and wives. Hypotheses on the effects of children and wife's employment were assessed for a national sample of married men reporting on their and their wives' activities for a typical weekday and Saturday. Role factors are shown to have a significant impact on timestyles and the specific activities emerging as substitutes and complements.     

Capitalizing on capabilities

By making the most of organizational capabilities--employees' collective skills and fields of expertise--you can dramatically improve your company's market value. Although there is no magic list of proficiencies that every organization needs in order to succeed, the authors identify 11 intangible assets that well-managed companies tend to have: talent, speed, shared mind-set and coherent brand identity, accountability, collaboration, learning, leadership, customer connectivity, strategic unity, innovation, and efficiency. Such companies typically excel in only three of these capabilities while maintaining industry parity in the other areas. Organizations that fall below the norm in any of the 11 are likely candidates for dysfunction and competitive disadvantage. So you can determine how your company fares in these categories (or others, if the generic list doesn't suit your needs), the authors explain how to conduct a "capabilities audit," describing in particular the experiences and findings of two companies that recently performed such audits. In addition to highlighting which intangible assets are most important given the organization's history and strategy, this exercise will gauge how well your company delivers on its capabilities and will guide you in developing an action plan for improvement. A capabilities audit can work for an entire organization, a business unit, or a region--indeed, for any part of a company that has a strategy to generate financial or customer-related results. It enables executives to assess overall company strengths and weaknesses, senior leaders to define strategy, midlevel managers to execute strategy, and frontline leaders to achieve tactical results. In short, it helps turn intangible assets into concrete strengths.     

SUBJECTIVE DISTRIBUTIONS AS ECONOMETRIC RESPONSE DATA

Analysis of actual observations of response processes is a routine procedure in applied econometrics but methods of dealing with purely subjective probability distributions as response 'data' have seemingly not hitherto been worked out. The models and methods developed here go some way to filling this void. They are illustrated by using information from a cross-sectional study of sixty Nepalese small-scale farmers. Means and variances of subjective probability distributions for rice paddy yields under different technologies are related to controlled inputs, such as fertiliser levels, and to relevant socio-economic aspects of farmers themselves, such as technological knowledge and farm size.