The impact of period effects on dose level contrasts in alternating cross‐over designs for first‐time‐in‐human studies

For first‐time‐in‐human studies with small molecules alternating cross‐over designs are often employed and at study end are analyzed using linear models. We discuss the impact of including a period effect in the model on the precision with which dose level contrasts can be estimated and quantify the bias of least squares estimators if a period effect is inherent in the data that is not accounted for in the model. We also propose two alternative designs that allow a more precise estimation of dose level contrasts compared with the standard design when period effects are included in the model. Copyright © 2010 John Wiley & Sons, Ltd.     

Supporting collaboration in humanitarian supply chains – insights from a design science project

Abstract

The growing number of large-scale relief operations and humanitarian aid initiatives is stretching the resources – financial, material and human – of humanitarian actors to their limits. Challenges to collaborate both within international humanitarian organizations, and among their direct and indirect supply chain partners often contribute to the inefficient use of resources, or ineffective operations. In this research, we discuss collaboration in humanitarian supply chains, and analyze causes of their dysfunctional operations. Furthermore, we develop an experiential learning approach that can sensitize humanitarian supply chain actors to causes of information distortion. The simulation approach was implemented in the field and instructional design cycles yielded insights into how staff apply their learnings under the specific conditions of humanitarian relief work.     

Out-migration from and return migration to Puerto Rico after Hurricane Maria: evidence from the consumer credit panel

Population and Environment - In this research brief, we contribute to a much-needed, initial, and growing inventory of data on Puerto Rican migration after Hurricane Maria. Using data from the...     

Leveraging global sources of knowledge for business model innovation

This article explores the concept of leveraging global knowledge for business model innovation, whereby knowledge is transferred across space and firm boundaries for the reconfiguration of an incumbent firm's business model. Considering the implications of an ever-increasing fragmentation of global value chains and the associated dispersion of global knowledge sources, we propose that supply chain partners at foreign locations can provide valuable knowledge that incumbents can leverage to change their business model. Integrating insights from global supply chain, business model, and organizational learning literature, we theorize and empirically test how different organizational capabilities enable firms to acquire knowledge from foreign partners, integrate external with internal knowledge, transform knowledge through experimentation, and finally apply global knowledge in the form of business model innovation. We conclude with suggestions for future research.     

The ambivalent effect of complexity on firm performance: A study of the global service provider industry

Prior literature is ambivalent about whether organizational complexity has positive or negative effects on firm performance. Using rich data on global service providers, we explore this ambivalence by disentangling performance consequences of different types of organizational complexity. We show that complexity arising from the coordination of different services and operations negatively influences profit margins through increased coordination costs, whereas complexity coming from the sophistication of particular services may positively influence margins through informational advantages. We also investigate the moderating effects of process commoditization and client-specific investments. Our findings point to critical performance dilemmas facing global service providers in a highly competitive industry, and they help better differentiate performance effects of complexity at different organizational levels.     

The social conditions of cumulation

Unlike philosophy, a sociological theory of cumulation cannot legislate the logical or metaphysical criteria which make cumulation in science universally possible. Instead, sociology must explain under which structural conditions cumulation events are more likely to occur than different varieties of change. Organizationally, cumulation events are rational myths, which tend to surface on ritual and ceremonial frontstages directed at concerned and skeptical outsiders. Historically, cumulation presupposes the retrospective closure and coherent periodization of episodes. Structurally, cumulation tends to occur when the intellectual and design spaces of a network or specialty are highly focussed on narrow and isolated dimensions of performance. Technically, much as in natural evolution, cumulative advances are more likely when experimental controls allow for restrictive tinkering on machines and machine-like devices. Cumulation is local, not global; it occurs in the short, not the long, run, and prefers non-turbulent environments.     

什么是村落?

依据1991~1993的十个村庄的研究,我们区分出来三种制度类型,每一种在界定作为地方的村庄上都大有不同。每一种又造就了不同的领导类型,尽管它们相互可能都是一致的。这些村庄类型的变化是巨大的,并且每一个都处在变化的过程中。     

Ideal football culture: A cultural take on self‐determination theory

This paper discusses cultural psychology and psychological training in football (soccer). Self‐Determination Theory (SDT; Deci & Ryan, 1980) has shown to be pragmatically successful in sport and suggests that being regulated by autonomous forms of motivation leads to better psychological outcomes. Cultural psychologists would be tempted to dismiss SDT because it is predicated on an a‐cultural approach to mind. It is possible to nurture a stronger and more effective team culture by reframing SDT in a cultural direction. As such, this paper outlines a cultural approach that reconceptualizes SDT in a way that retains the latter's pragmatic value while not approaching mind in a self‐contained individualist manner.     

Optimal replacement strategies in network infrastructures under quality penalties

As a consequence of liberalization, electric utilities have developed different asset management strategies with the aim of reducing total maintenance costs by prolonging replacement cycles. A cost-minimizing network operator has to optimize the trade-off between costs for early replacement and quality penalties he faces in the case of outages (due to a resulting higher number of failures). The basic purpose of this paper is to identify the optimal decisions for a network operator under output-based quality regulation and to determine the main drivers for his decisions. In order to derive general insights, an analytical framework is chosen for this paper. This work builds on the foundations of optimal maintenance and replacement strategies as developed across Operations Research, Production Economics and Engineering Production Theory. As main results we are able to analytically derive optimal replacement strategies for network components depending on the characteristics of their failure distributions linked to the equipment’s cost, respective replacement cost, and quality penalties.     

Empirical Processes in Survey Sampling with (Conditional) Poisson Designs

It is the main purpose of this paper to study the asymptotics of certain variants of the empirical process in the context of survey data. Precisely, Functional Central Limit Theorems are established under usual conditions when the sample is drawn from a Poisson or a rejective sampling design. The framework we develop encompasses sampling designs with non‐uniform first order inclusion probabilities, which can be chosen so as to optimize estimation accuracy. Applications to Hadamard differentiable functionals are considered.