Cooperative innovation through a talent management pool: A qualitative study on coopetition in healthcare

In recent years, the Dutch healthcare sector has been confronted with increased competition. Not only are financial resources scarce, Dutch hospitals also need to compete with other hospitals in the same geographic area to attract and retain talented employees due to considerable labour shortages. However, four hospitals operating in the same region are cooperating to cope with these shortages by developing a joint Talent Management Pool. ‘Coopetiton’ is a concept used for simultaneous cooperation and competition. In this paper, a case study is performed in order to enhance our understanding of coopetition. Among other things, the findings suggest that perceptions of organizational actors on competition differ and might hinder cooperative innovation with competitors, while perceived shared problems and resource constraints stimulate coopetition. We reflect on the current coopetition literature in light of the research findings, which have implications for future research on this topic.     

Finding and Implementing Energy Efficiency Projects in Industrial Facilities

This study addresses the challenges of finding and implementing profitable energy efficiency (EE) projects, a critical foundation for sustainable operations. We focus on manufacturing enterprises, but many of our findings apply also to the back office of service operations. Our starting point is that, in nearly every industrial enterprise, there are many profitable EE projects that could be implemented but are not. An oft‐cited hindrance to implementation is the lack of an internal management framework in which to find, value, and execute these projects. Using a conceptual approach, we rely on proven sustainable operations tools to develop such a framework. We identify three major value drivers of EE projects: savings intensity, “green” image, and project complexity. We then describe a framework for understanding the context of EE projects in industry, with an underlying analytic foundation in optimal portfolio analysis. A case study of a large manufacturing site is used to illustrate emerging best practices—based on Kaizen management principles—for integrating EE project management with operations, engineering, and strategy.     

Quantitative Risk Assessment of the New York State Operated West Valley Radioactive Waste Disposal Area

This article is based on a quantitative risk assessment (QRA) that was performed on a radioactive waste disposal area within the Western New York Nuclear Service Center in western New York State. The QRA results were instrumental in the decision by the New York State Energy Research and Development Authority to support a strategy of in‐place management of the disposal area for another decade. The QRA methodology adopted for this first of a kind application was a scenario‐based approach in the framework of the triplet definition of risk (scenarios, likelihoods, consequences). The measure of risk is the frequency of occurrence of different levels of radiation dose to humans at prescribed locations. The risk from each scenario is determined by (1) the frequency of disruptive events or natural processes that cause a release of radioactive materials from the disposal area; (2) the physical form, quantity, and radionuclide content of the material that is released during each scenario; (3) distribution, dilution, and deposition of the released materials throughout the environment surrounding the disposal area; and (4) public exposure to the distributed material and the accumulated radiation dose from that exposure. The risks of the individual scenarios are assembled into a representation of the risk from the disposal area. In addition to quantifying the total risk to the public, the analysis ranks the importance of each contributing scenario, which facilitates taking corrective actions and implementing effective risk management. Perhaps most importantly, quantification of the uncertainties is an intrinsic part of the risk results. This approach to safety analysis has demonstrated many advantages of applying QRA principles to assessing the risk of facilities involving hazardous materials.     

Leadership ambiguity in universities and K–12 schools and the limits of contemporary leadership theory

This paper explores the differences in context, assumptions, and behavior of leaders both in modern American universities and in elementary and high schools. The paper's main section examines the utility of five leadership theories (situational, charismatic, transformational, path–goal, and leader–member exchange [LMX]) in explaining leader behavior in each educational sector. We show that while each theory has some merit, none adequately incorporates the larger internal and external “system” pressures on leaders whose institutions are undergoing changes. The paper concludes with a recommendation for a reformulation of the leadership dilemmas in education that sets the five theories in a broader, systemic conceptual framework.     

Symbolic interaction theory and the cognitively disabled: A neglected dimension

Symbolic interactionists have by and large not explored how individuals with mental illnesses—specifically, delusional misidentification syndromes—are able to exercise the cognitive factors necessary for successful interaction. Such factors include: recognition of self and others, situated interpretation, inferring others’ cognitive and emotional states, anticipating what others might say or do, empathizing, maintaining a cogent belief system, etc. What needs to be addressed is how the mentally ill manage—and fail to manage—these cognitively-informed activities as they slip more and more into cognitive and existential chaos, and the associated loss of meaningful dialogue with self and others. Clinical accounts of the cognitively dysfunctional could widen and deepen our understanding of cognition, belief states, self, and self-other relations, central concepts for symbolic interactionists. Accordingly, this paper is as much a critique of symbolic interactionism as a contribution to a humanistic social psychology.     

Markov Chain Monte Carlo in small worlds

As the number of applications for Markov Chain Monte Carlo (MCMC) grows, the power of these methods as well as their shortcomings become more apparent. While MCMC yields an almost automatic way to sample a space according to some distribution, its implementations often fall short of this task as they may lead to chains which converge too slowly or get trapped within one mode of a multi-modal space. Moreover, it may be difficult to determine if a chain is only sampling a certain area of the space or if it has indeed reached stationarity. In this paper, we show how a simple modification of the proposal mechanism results in faster convergence of the chain and helps to circumvent the problems described above. This mechanism, which is based on an idea from the field of “small-world” networks, amounts to adding occasional “wild” proposals to any local proposal scheme. We demonstrate through both theory and extensive simulations, that these new proposal distributions can greatly outperform the traditional local proposals when it comes to exploring complex heterogenous spaces and multi-modal distributions. Our method can easily be applied to most, if not all, problems involving MCMC and unlike many other remedies which improve the performance of MCMC it preserves the simplicity of the underlying algorithm.