Richard Burke

Statistical Control Charts Based on a Geometric Distribution

In some production processes and administrative processes, the occurrence of certain events is best described by a geometric distribution. Control charts are developed for the total number of events and for the average number of events in a fixed number..

PROCESS CAPABILITY INDICES: NOW AND IN THE FUTURE

An overview is provided on the use of process capability indices to measure the ability of a process to manufacture conforming product. After this overview, three characteristics of process capability indices are discussed. It is shown that alternative ..

THE EFFECT OF INSPECTOR ERRORS ON THE TRUE FRACTION NON-CONFORMING: AN INDUSTRIAL EXPERIMENT

This article describes the effect of Type I and Type II inspector errors on the true fraction nonconforming. Estimates of these errors from previous studies for different types of products and production processes are summarized. A procedure is outlined..

Direct Foreign Manufacturing Investment Decisions for China

AbstractA firms foreign direct manufacturing investment (FDMI) vehicle choice is a difficult one. Scholars and practitioners alike differ over the best vehicle of entry into foreign markets. The traditional wisdom suggests the formation of an equity joint venture, a choice that reflects the advice offered by the ancient Chinese proverb, “It is a fool who does not hire a guide when entering a foreign land.” Recently, a wave of agreement has washed over scholars and practitioners, who are now promoting the wholly owned foreign subsidiary as the preferred vehicle for entering foreign markets. This article examines 74 FDMI decisions made by manufacturing firms entering the Peoples Republic of China. Examination of these data suggests a revised FDMI decision framework based on an individual firms technology, investment size, market scope, new-product development strategy, and government regulation.

Progressive random sampling: a multiperiod estimation technique with applications

A number of applications, including claims made under Federal social welfare programs, require retrospective sampling over multiple time periods. A common characteristic of such samples is that population members could appear in multiple time periods. When this occurs, and when the marginal cost of obtaining multiperiod information is minimum for a member appearing in the sample of the period being actively sampled, then a method which is herein called progressive random sampling (PRS) may be applied. The proposed method serves to either improve sampling estimates or reduce sample sizes, as demonstrated by two example applications.

Progressive Random Sampling With Stratification

A number of applications, including claims made under federal social welfare programs, requires retrospective sampling over multiple time periods. A common characteristic of such samples is that population members could appear in multiple time periods. When this occurs, and when the marginal cost of obtaining multiperiod information is minimum for a member appearing in the sample of the period being actively sampled, the progressive random sampling (PRS) method developed by the authors earlier can be applied. This paper enhances the progressive random sampling method by combining it with stratification schemes; the resultant stratified progressive random sampling (SPRS) technique is shown to provide significant improvement over traditional sampling techniques whenever stratification is appropriate. An empirical example based on a data transformation of a real-world application is provided to illustrate the practical application of the technique.

Biostatistics: the hidden path to life science innovation

This exploratory paper investigates the infrastructure for life-science-based new product development. The practice of biostatistics has long been seen as a crucial element of the regulatory process for approving the release of new drugs and medical devices, but the authors hypothesize that it serves a larger role in the new product development process in pharmaceutical and biotechnology firms. To this end, they focus on the management of Biostatistics and related know how such as data mining in the discovery, testing, and commercialization of new products. Their results are drawn from a number of in-depth case studies of biostatistical practices in a variety of firms engaged in life-science product development. The findings point to the importance of biostatistics in providing both technical and strategic information. To the extent that Biostatistics is managed as a learning system, it is critical for building core capability and enabling resource configurations that create value.

Awakening the dragon's breath: biostatistics, competency and competition in the pharmaceutical industry

Innovations in chemistry and biology have generated multiple products and built significant revenue streams in the pharmaceutical industry. However, the complex and multi-disciplinary process of drug discovery and drug development makes it difficult to identify specific core competencies within a company. There is a need to better identify and manage sources of innovation that lead to new markets as ever-increasing investments in R&D have recently been accompanied by mediocre success in new product introduction. Additionally, outsourcing of clinical research and even early-stage discovery research continues to increase, creating a need to better define core competencies for strategic management decisions in pharmaceutical innovation In this context, we investigated the possible role that biostatistics -a key competence-could play in innovation in the drug development process. A sampling of case interviews from biostatisticians and executives in the pharma industry indicate that biostatisticians do contribute to innovation in the drug development process. Data gathered from contract research companies in the pharma industry suggests that outsourcing practices in the pharmaceutical industry increasingly include the outsourcing of biostatistics capabilities. We conclude that pharmaceutical companies should consider directing their management and outsourcing practices to retain and gain novel innovation through biostatistics.

Stratified progressive random sampling [welfare claims processing]

A number of applications, including claims made under Federal social welfare programs, require retrospective sampling over multiple time periods. A common characteristic of such samples is that population members could appear in multiple time periods. When this occurs, and when the marginal cost of obtaining multi-period information is minimum for a member appearing in the sample of the period being actively sampled, the progressive random sampling method developed by the authors earlier (1998) can be applied. This paper enhances the progressive random sampling method by combining it with stratification schemes; the resultant stratified progressive random sampling technique is shown to provide significant improvement over traditional sampling techniques whenever stratification is appropriate.

Developing technological entrepreneurship in China

In this paper, the authors discuss findings from an on-going research effort by a multi-disciplinary team from Rensselaer Polytechnic Institute, in collaboration with faculty and students from Tianjin University. The on-going goal of the research is to analyze how and why foreign firms enter the PRC and document how business practices are changing in the PRC. Part of their initiative is to study managerial and technical entrepreneurship as it is developing in China. For this paper, they have categorized the evolution of the Chinese economy into five epochs. These epochs are useful for analyzing the interaction between technological development and entrepreneurial initiative.