Supervisors and their response to poor performance: A study of disciplinary decision making

This study examines how first-level supervisors make disciplinary decisions when faced with a performance problem. Using a policy-capturing design, subjects (supervisors from a nonunion financial services organization) were asked to make disciplinary decisions about cases that varied in terms of six different factors: magnitude of the performance decrement, documented warning, waiver, tenure, past performance, and the manner of the employee. The impact of these factors was examined in order to gain insight into the degree to which key social and institutional norms impact disciplinary decisions and, in turn, generate nascent rights for employees. The findings are suggestive as to the relative importance of these norms within the sample as a whole as well as for individual managers within the sample. The implications for our understanding of the role of nascent rights within disciplinary systems are discussed.     

Analysis of treatment response data from eligibility designs

In this paper, we develop and compare two alternative approaches for calculating the effect of the actual intake when treatments are randomized, but compliance with the assignment in the treatment arm is less than perfect for reasons that are correlated with the outcome. The approaches are based on different identification assumptions about these unobserved confounders. In the first approach, which stems from [Sommer, A., Zeger, S., 1991. On estimating efficacy in clinical trials. Statistics in Medicine 10, 45–52], the unobserved confounders are modeled by a discrete indicator variable that represents subject-type, defined in terms of the potential intake in the face of each possible assignment. In the second approach, confounding is modeled without reference to subject-type in the spirit of the Roy model. Because the two models are non-nested, and model comparison and assessment of the approaches in a real data setting is one of our central goals, we formulate the discussion from a Bayesian perspective, comparing the two models in terms of marginal likelihoods and Bayes factors, and in terms of inferences about the treatment effects. The latter we calculate from a predictive perspective in a way that is different from that in the literature, where typically only a point summary of that effect is calculated. Our real data analysis focuses on the JOBS II eligibility trial that was implemented to test the effectiveness of a job search seminar in decreasing the negative mental health effects commonly associated with job loss. We provide a comparative analysis of the data from the two approaches with prior distributions that are both reasonable in the context of the data and comparable across the model specifications. We show that the approaches can lead to different evaluations of the treatment.     

A note on the robustness of Box-Behnken designs to the unavailability of data

Box-Behnken designs and central composite designs are efficient designs for fitting second order polynomials to response surfaces, because they use relatively small numbers of observations to estimate the parameters. In this paper we investigate the robustness of Box-Behnken designs to the unavailability of observations, in the sense of finding t _max , the maximum number of arbitrary rows in the design matrix that can be removed and still leave all of the parameters of interest estimable. The results are compared to the known results for the central composite designs found in MacEachern, Notz, Whittinghill & Zhu (1995). The blocked Box-Behnken designs are equally as robust as those that are not blocked. Received December 1997     

The new IMF approach to capital account management and its blind spots: lessons from Brazil and South Korea

As emerging economies experience a boom in capital inflows, governments are increasingly concerned about their downsides. Even the IMF (International Monetary Fund), long a stalwart proponent of financial liberalization, has engaged in a new debate on capital flow management. Drawing lessons from empirical case studies on Brazil and South Korea, this paper finds that the new IMF framework remains insufficient in two main aspects. First, by defining ‘capital flow management measures’ (CFMs) as a temporary instrument embedded in an overall strategy of financial opening, the organization insists on the general advantages of financial liberalization, which poses serious limits to emerging economies’ policy space. Second, the Fund keeps on stressing a separation of prudential financial regulation, which should be permanent, and temporary CFMs. Yet, the case studies presented here show that, especially for emerging markets with rather open and sophisticated domestic financial markets, both types of measures are interdependent and overlapping. Additionally, we demonstrate the relevance of a third type of regulation, lying on foreign exchange (FX) derivatives instruments, which may also be required to effectively manage foreign investors’ portfolio reallocations and their impact.     

Residential grid storage technology battles: a multi-criteria analysis using BWM

This article focuses on the battle for dominance between various battery technologies in the residential grid storage market (< 10?KWh) in the context of residential energy systems and the related home energy management systems. We focus on five major battery technologies that are available in the market (lithium-based batteries, lead-based batteries, flow batteries, nickel-based batteries, and sodium-based batteries). Based on a literature review and expert interviews, we study the factors for technology success in the residential grid storage market. By applying the best worst method (BWM), we assign the relative importance to the factors and predict which technology will have the highest chance of achieving success. We compare this to the technology that now has the highest market share and conclude that BWM is a useful method to indicate technology dominance in this market.     

Revealing Differences in Willingness to Pay due to the Dimensionality of Stated Choice Designs: An Initial Assessment

Stated choice (SC) methods are now a widely accepted data paradigm in the study of the choice responses of agents. Their popularity has spawned an industry of applications in fields as diverse as transportation, environmental science, health economics and policy, marketing, political science and econometrics. With rare exception, empirical studies have used a single SC design, in which the numbers of attributes, alternatives, choice sets, attribute levels and ranges have been fixed across the entire design. As a consequence the opportunity to investigate the influence of design dimensionality on behavioural response has been denied. Accumulated wisdom has promoted a large number of positions on what design features are specifically challenging for respondents; and although a number of studies have assessed the influence of subsets of design dimensions, there exists no single study (that we are aware of) that has systematically varied all of the main dimensions of SC experiments. This paper reports some initial findings on what influences, in aggregate, specific design configurations have on the mean willingness to pay for specific attributes using a Design of Designs (DoD) SC experiment in which the ‘attributes’ of the design are the design dimensions themselves. The design dimensions that are varied are the number of choice sets presented, the number of alternatives in each choice set, the number of attributes per alternative, the number of levels of each attribute and the range of attribute levels. The empirical evidence, using a sample of respondents in Sydney choosing amongst trip attribute bundles for their car commuting trip, suggests that, within the boundaries of design dimensionality investigated, mean estimates of WTP for travel time savings in the aggregate cover a range that is appropriate for reporting a global mean and a set of meaningful values for sensitivity testing in project appraisal and demand prediction. When these aggregated mean estimates are conditioned on all design dimensions we do not find any systematic differences due to specific design dimensions; however when each design dimension is assessed without controlling for the other dimensions we find evidence to support differences in aggregate mean WTP attributable to the number of attributes per alternative and the number of alternatives in a choice set. Research funded under the Australian Research Council Large Grants Scheme, Grant A00103962.     

浅谈传统图形与现代标志设计的结合

我国传统图形艺术源远流长,其代表着中国几千年的文化内涵,将传统图形与现代标志设计相结合,成为设计的一个新启示和新创意。本文分别从传统图形的溯源,意义以及在现代标志设计中的应用等方面进行阐述。     

Polygonal designs with blocks of size k≤10

The use of polygonal designs is motivated by the desire to avoid the selection of contiguous units in a sample from an ordered finite population. However very little is known about polygonal designs that have block size 5 or more. We present new polygonal designs with blocks of sizes 5 through 10, including the first designs with block sizes 9 and 10. For block sizes 5 through 7, we identify, with one possible exception, all values for the number of varieties for which a polygonal design exists. Received January 2001     

A stochastic characterization of Loewner optimality design criterion in linear models

In this paper we present a new stochastic characterization of the Loewner optimality design criterion. The result is obtained by proving a generalization to the well known corollary of Anderson's theorem. Certain connections between the Loewner optimality and the stochastic distance optimality design criterion are showed. We also present applications and generalizations of the main result. Received: 9 August 2000     

Efficiencies of Rounded Optimal Approximate Designs for Small Samples

Optimal exact designs are notoriously hard to study and only a few of them are known for polynomial models. Using recently obtained optimal exact designs (I mhof , 1997), we show that the efficiency of the frequently used rounded optimal approximate designs can be sensitive if the sample size is small. For some criteria, the efficiency of the rounded optimal approximate design can vary by as much as 25% when the sample size is changed by one unit. The paper also discusses lower efficiency bounds and shows that they are sometimes the best possible bounds for the rounded optimal approximate designs.