The Potential for Cannibalization of New Products Sales by Remanufactured Products*

The potential for cannibalization of new product sales by remanufactured versions of the same product is a central issue in the continuing development of closed‐loop supply chains. Practitioners have no fact‐based information to guide practice at firms and academics have no studies available to use as the basis for assumptions in models. We address the cannibalization issue by using auctions to determine consumers’ willingness to pay (WTP) for both new and remanufactured products. The auctions also allow us to better understand the potential impact of offering new and remanufactured products at the same time, which provides us insights into the potential for new product cannibalization. Our results indicate that, for the consumer and commercial products auctioned, there is a clear difference in WTP) for new and remanufactured goods. For the consumer product, there is scant overlap in bidders between the new and remanufactured products, leading us to conclude that the risk of cannibalization in this case is minimal. For the commercial product, there is evidence of overlap in bidding behavior, exposing the potential for cannibalization.     

Strategic Product/Service Innovations of an Online Firm

We study the incentives that drive an online firm to make various types of innovations in a competitive environment. We develop and use a simplified price competition model between two retailers, one online and one offline. A given fraction of consumers, called the Internet penetration, comparison shop online, independent of their customer type, thereby creating two markets for the offline retailer, a captive market and a competitive market. The online product has the steeper of the two linear utility functions, which means that the customers who buy online in our model are high end. We focus on the competitive region in which both retailers are (strictly) profitable in the competitive market and consider innovations that increase high‐end appeal, low‐end appeal, and/or reduce unit cost. We find that the online firm has a strong incentive to invest in innovations that either reduce unit cost and/or, equivalently, increase the appeal to all consumers equally. Investments of this type are strategic complements: implementing one increases the value of another, so the value of two innovations of this type is more than the sum of the values of each individually. We identify a relative strength measure of the online firm such that, as its high‐end appeal increases and/or its unit cost decreases, we say that the online firm is stronger. This strength measure facilitates drawing an explicit dividing line between strong and weak online firms. If Internet penetration increases, the online firm's profits increase if and only if it is strong. If penetration increases over time, it is possible for a strong firm to turn weak and see its profits decrease and possibly disappear completely. A strong online firm has more opportunity to profit from low‐end innovations than does a weak one, while the opposite is true for high‐end innovations. Interestingly, some innovations may actually decrease the online firm's profits. We discuss the implications of our results for existing and future online innovations.     

Slack free MEA and RDM with comprehensive efficiency measures

This paper extends two directional distance function models, the Multi-directional Efficiency Analysis (MEA) Model and the Range Directional Model (RDM), in order to account for any type of technical inefficiency, i.e. both directional and non-directional inefficiencies. We first focus on the variable returns to scale (VRS) case, because both VRS-MEA and RDM are translation invariant models, which mean that both models are able to deal with negative data. Our main result is the definition of a new comprehensive efficiency measure which is units invariant and translation invariant and covers both models. Secondly, we introduce the RDM model under constant returns to scale (CRS) together with a new comprehensive efficiency measure.     

Hepatitis C psychoeducation curriculum topics generated by group members

ABSTRACT

Educational programs for hepatitis C (HCV) have been created by professionals. There has not been a focus on whether what clients want to know about HCV differs from what providers want patients to know. This study addresses this gap by examining topics selected by participants in an education/support group model. Data were collected as part of a randomized psychoeducation trial for patients with HCV. Topics were systematically generated by the members uniquely for each group. Topics and rank order for each group were generated and a combined variable was created. Twenty-eight different topics were identified across 12 groups. The total number of topics was 102, averaging 8.5 per group. Topics are divided into three separate conceptual groups, members’ personal relationship to HCV, medical aspects of HCV, and unique concerns. A patient-centered approach that addresses the needs of HCV patients first provides an optimal starting point to discuss HCV disease management.     

The Beta Product Distribution with Complex Parameters

The family consisting of the distributions of products of two independent beta variables is extended to include cases where some of the parameters are not positive but negative or complex. This “beta product” distribution is expressible as a Meijer G function. An example (from risk theory) where such a distribution arises is given: an infinite sum of products of independent random variables is shown to have a distribution that is the product convolution of a complex-parameter beta product and an independent exponential. The distribution of the infinite sum is a new explicit solution of the stochastic equation X = (in law) B(X + C). Characterizations of some G distributions are also proved.     

A Nonparametric Synthetic Control Chart Using Sign Statistic

This article presents a synthetic control chart for detection of shifts in the process median. The synthetic chart is a combination of sign chart and conforming run-length chart. The performance evaluation of the proposed chart indicates that the synthetic chart has a higher power of detecting shifts in process median than the Shewhart charts based on sign statistic as well as the classical Shewhart X-bar chart for various symmetric distributions. The improvement is significant for shifts of moderate to large shifts in the median. The robustness studies of the proposed synthetic control chart against outliers indicate that the proposed synthetic control chart is robust against contamination by outliers.     

Tests for Equality of Inflation Parameters of Two Zero-Inflated Power Series Distributions

In this article, we consider two independent zero-inflated power series distributions and provide likelihood ratio test for equality of inflation parameters of the same. As an illustration, testing equality of inflation parameters of two zero inflated Poisson distributions is provided. Further, simulation study to investigate power of likelihood ratio tests has been carried out.     

Confidence Bounds for Multiplicative Comparisons

Statements that are inherently multiplicative have historically been justified using ratios of random variables. Although recent work on ratios has extended the classical theory to produce confidence bounds conditioned on a positive denominator, this current article offers a novel perspective that eliminates the need for such a condition. Although seemingly trivial, this new perspective leads to improved lower confidence bounds to support multiplicative statements. This perspective is also more satisfying as it allows comparisons that are inherently multiplicative in nature to be properly analyzed as such.     

On the Bias of the Maximum Likelihood Estimator for the Two-Parameter Lomax Distribution

The Lomax (Pareto II) distribution has found wide application in a variety of fields. We analyze the second-order bias of the maximum likelihood estimators of its parameters for finite sample sizes, and show that this bias is positive. We derive an analytic bias correction which reduces the percentage bias of these estimators by one or two orders of magnitude, while simultaneously reducing relative mean squared error. Our simulations show that this performance is very similar to that of a parametric bootstrap correction based on a linear bias function. Three examples with actual data illustrate the application of our bias correction.     

Nonparametric Predictive Inference for Ordinal Data

Nonparametric predictive inference (NPI) is a powerful frequentist statistical framework based only on an exchangeability assumption for future and past observations, made possible by the use of lower and upper probabilities. In this article, NPI is presented for ordinal data, which are categorical data with an ordering of the categories. The method uses a latent variable representation of the observations and categories on the real line. Lower and upper probabilities for events involving the next observation are presented, and briefly compared to NPI for non ordered categorical data. As application, the comparison of multiple groups of ordinal data is presented.