Smoothed empirical likelihood confidence intervals for the relative distribution with left‐truncated and right‐censored data

The study of differences among groups is an interesting statistical topic in many applied fields. It is very common in this context to have data that are subject to mechanisms of loss of information, such as censoring and truncation. In the setting of a two‐sample problem with data subject to left truncation and right censoring, we develop an empirical likelihood method to do inference for the relative distribution. We obtain a nonparametric generalization of Wilks' theorem and construct nonparametric pointwise confidence intervals for the relative distribution. Finally, we analyse the coverage probability and length of these confidence intervals through a simulation study and illustrate their use with a real data set on gastric cancer. The Canadian Journal of Statistics 38: 453–473; 2010 © 2010 Statistical Society of Canada     

Citizen Support for Hospital Privatization: A Hierarchical Cross-National Analysis

The movement for a new public management (NPM) holds that citizens will put aside partisan and ideological differences to support more efficient service delivery. Focusing on hospital privatization, a multi-national sample is utilized to investigate this assertion. Generalized hierarchical linear modeling (GHLM) is employed as the method of statistical analysis. The findings with regard to privatizing hospitals reveal that citizens develop their policy position by reference to a combination of symbolic political variables, service demand, self-interest, information levels, and political efficacy. The results cast doubt on the assertion that partisan differences will be set aside as citizens consider privatization reforms.

Fisher's Information for Discretely Sampled Lévy Processes

This paper studies the asymptotic behavior of Fisher's information for a Lévy process discretely sampled at an increasing frequency. As a result, we derive the optimal rates of convergence of efficient estimators of the different parameters of the process and show that the rates are often nonstandard and differ across parameters. We also show that it is possible to distinguish the continuous part of the process from its jumps part, and even different types of jumps from one another.     

A Risk-Benefit Analysis of French High Fish Consumption: A QALY Approach

The health risk and the nutritional benefit of a food are usually assessed separately. Toxicologists recommend limiting the consumption of certain fish because of methylmercury; while nutritionists recommend eating more oily fish because of omega 3. A common evaluation is imperative to provide coherent recommendations. In order to evaluate the risks along with the benefits related to fish consumption, a common metric based on the quality-adjusted life year (QALY) method has been used. The impact of a theoretical change from a medium n-3 PUFAs intake to a high intake is studied, in terms of the cardiovascular system (CHD mortality, stroke mortality and morbidity) and on fetal neuronal development (IQ loss or gain). This application can be considered as a sensitive analysis of the model used and looks at the impact of changing the dose-response relationships between cardiovascular diseases and n-3 PUFAs intakes. Results show that increasing fish consumption may have a beneficial impact on health. However, the confidence interval of the overall estimation has a negative lower bound, which means that this increase in fish consumption may have a negative impact due to MeHg contamination. Some limits of the QALY approach are identified. The first concerns determination of the dose-response relationships. The second concerns the economic origins of the approach and of individual preferences. Finally, since only one beneficial aspect and one risk element were studied, consideration should be given to how other beneficial and risk components may be integrated in the model.     

The Emergence of Service Science: Toward Systematic Service Innovations to Accelerate Co‐Creation of Value

The current growth of the service sector in global economies is unparalleled in human history—by scale and speed of labor migration. Even large manufacturing firms are seeing dramatic shifts in percent revenue derived from services. The need for service innovations to fuel further economic growth and to raise the quality and productivity levels of services has never been greater. Services are moving to center stage in the global arena, especially knowledge‐intensive business services aimed at business performance transformation. One challenge to systematic service innovation is the interdisciplinary nature of service, integrating technology, business, social, and client (demand) innovations. This paper describes the emergence of service science, a new interdisciplinary area of study that aims to address the challenge of becoming more systematic about innovating in service.     

The Dynamics of Research Alliances: Examining the Effect of Alliance Experience and Partner Characteristics on the Speed of Alliance Entry in the Biotech Industry

Few studies have moved beyond the dyadic level of an ongoing alliance and examined factors contributing to the success of entering a series of alliances. In this paper we expect biotechnology firms over time to learn from their alliance experience and to develop general alliance capabilities. Specifically, we expect the speed with which they enter into new research alliances, e.g. their alliance formation rate, to be affected by capabilities built up in prior alliances as well as by characteristics of their partners. We use longitudinal event history data for the complete population of US biotechnology firms for 1973–1999 to test four hypotheses about factors affecting the rate of new alliance formation. Our analysis suggests that the speed of entering research alliances is affected by prior experience of the focal firm, but not by partner characteristics. Our findings provide evidence that biotech firms learn how to learn more effectively from multiple research alliances; however, this effect is generalized and not tied to specific characteristics of the alliance partner.     

Drivers and Enablers That Foster Environmental Management Capabilities in Small‐ and Medium‐Sized Suppliers in Supply Chains

The limited capabilities and resources available within many small‐ and medium‐sized enterprises frequently hamper an effective response to environmental pressures, which in turn hurts large buying firms (i.e., customers). Using a case study method with multiple suppliers of two large buying firms, we mapped factors that initiated and improved environmental capabilities in small‐ and medium‐sized enterprises over time. Through several specific mechanisms, buyers' green supply chain management initiated and then enabled the improvement of suppliers' environmental capabilities. Independent of buyers, internal championing of environmental concerns also provided an impetus for small‐ and medium‐sized enterprise suppliers to acquire resources outside the supply chain. Thus, synergistic linkages emerged in supportive buyer‐supplier relationships, resource acquisition, and capability development. When these findings are combined with earlier research on larger suppliers, an integrative framework emerges that provides direction for suppliers, buyers, and public agencies seeking to improve environmental performance.     

Value of Sharing Production Yield Information in a Serial Supply Chain

New developments in corporate information technology such as enterprise resource planning systems have significantly increased the flow of information among members of supply chains. However, the benefits of sharing information can vary depending on the supply chain structure and its operational characteristics. Most of the existing research has studied the impact of sharing downstream information (e.g., a manufacturer sharing information with its suppliers). We evaluate the benefits of sharing upstream yield information (e.g., a supplier sharing information with the manufacturer) in a two‐stage serial supply chain in which the supplier has multiple internal processes and is faced with uncertain output due to yield losses. We are interested in determining when the sharing of the supplier's information is most beneficial to the manufacturer. After proposing an order‐up‐to type heuristic policy, we perform a detailed computational study and observe that this information is most beneficial when the supplier's yield variance is high and when end‐customer demand variance is low. We also find that the manufacturer's backorder‐to‐holding cost ratio has little, if any, impact on the usefulness of information.