Bayesian regression with multivariate linear splines

We present a Bayesian analysis of a piecewise linear model constructed by using basis functions which generalizes the univariate linear spline to higher dimensions. Prior distributions are adopted on both the number and the locations of the splines, which leads to a model averaging approach to prediction with predictive distributions that take into account model uncertainty. Conditioning on the data produces a Bayes local linear model with distributions on both predictions and local linear parameters. The method is spatially adaptive and covariate selection is achieved by using splines of lower dimension than the data.     

Estimation and Confidence Intervals for Clock Offset in Networks with Bivariate Exponential Delays

There is a large and increasing literature on statistical modeling-based estimation of the offset between two clocks. Recent work has focused on the construction of confidence intervals for offset. However, in most of this work it has been assumed that the network delays that occur during the synchronization process are independent. The network delays are often modeled as independent exponential random variables. Thus, we introduce the use of a bivariate exponential distribution to capture the anticipated correlation between the network delays and derive a maximum likelihood estimator and a confidence interval procedure for the offset parameter. We then illustrate how use of the independent model for network delays can lead to improper inference about the offset parameter.     

Optimal Dynamic Pricing of Perishable Items by a Monopolist Facing Strategic Consumers

We introduce a dynamic pricing model for a monopolistic company selling a perishable product to a finite population of strategic consumers (customers who are aware that pricing is dynamic and may time their purchases strategically). This problem is modeled as a stochastic dynamic game in which the company's objective is to maximize total expected revenues, and each customer maximizes the expected present value of utility. We prove the existence of a unique subgame‐perfect equilibrium pricing policy, provide equilibrium optimality conditions for both customer and seller, and prove monotonicity results for special cases. We demonstrate through numerical examples that a company that ignores strategic consumer behavior may receive much lower total revenues than one that uses the strategic equilibrium pricing policy. We also show that, when the initial capacity is a decision variable, it can be used together with the appropriate pricing policy to effectively reduce the impact of strategic consumer behavior. The proposed model is computationally tractable for problems of realistic size.     

Enterprise Resource Planning (ERP) Competence Constructs: Two‐Stage Multi‐Item Scale Development and Validation*

This paper defines and operationalizes eight ERP competence constructs. We define ERP competence as a portfolio of managerial, technical and organizational skills and expertise posited as antecedents to improved business performance occurring after an ERP system is operational and functionally stable. To improve responses to changes in markets and products, manufacturers are increasingly adopting ERP systems. However, anecdotal accounts indicate that the realization of ERP's potential benefits is rare. Because of its pervasive influence on manufacturing and business performance, the need for scientifically developed and tested multi‐item scales pertaining to ERP competence is highly relevant to manufacturing strategy research. We follow a two‐stage normative process of scale development. First, we identify a portfolio of eight generic constructs that are hypothesized to be associated with successful ERP adoption. Each construct is then operationalized as a multi‐item measurement scale by applying a manual item sorting technique iteratively to independent panels of expert judges until tentative reliability and validity is established. Second, we further refine and validate the multi‐item scales using survey data from 79 North American manufacturing users of ERP systems.