Experimental designs in management and leadership research: Strengths,limitations, and recommendations for improving publishability

Despite the renewed interest in the use of experimental designs in the fields of leadership and management over the past few decades, these designs are still relatively underutilized. Although there are several potential reasons for this, chief among them is misunderstanding the value of these designs. The purpose of this article is to review the role of laboratory, field, and quasi-experimental designs in management and leadership research. We first discuss the primary goals of experimental studies. Next, we examine the characteristics of experimental designs and how to distinguish laboratory, field, and quasi-experiments from one another and from non-experimental studies. Following these discussions, we provide examples of each type of experimental design and discuss their relative strengths and limitations. Finally, we discuss steps that researchers can take to increase the probability of having articles reporting experiments accepted by leadership and management journals.     

A systematic review of executive coaching outcomes: Is it the journey or the destination that matters the most?

In this article, we focus on a specific type of personal and professional development practice -executive coaching- and present the most extensive systematic review of executive coaching outcome studies published in peer-reviewed scholarly journals to date. We focus only on coaching provided by external coaches to organizational members. Our purpose is twofold: First, to present and evaluate how executive coaching outcome studies are designed and researched (particularly regarding methodological rigor and context-sensitivity). Secondly, to provide a comprehensive review of what we know about executive coaching outcomes, what are the contextual drivers that affect coaching interventions and what the current gaps in our understanding of coaching practice. On that basis, we discuss and provide a research agenda that might significantly shift the field. We argue that methodological rigor is as important as context-sensitivity in the design of executive coaching outcome studies. We conclude with a discussion of implications for practice.     

Differential evolutionary algorithm in the construction process of optimal experimental designs

This article shows how a differential evolution algorithm can be used to find statistical designs under several optimality criteria as A, D, and T. The general algorithm of differential evolution is described and then applied on constructing optimal designs for several well-known models and compare them with those already available by other algorithms, in terms of relative efficiency. Moreover, the great effect of population size in the running of this algorithm establishes a precedent in the use of differential evolution algorithms over genetic algorithms.     

Nearly optimal covariate designs—Part I

We propose to discuss at length several examples from standard text books. All of these examples deal with analysis of covariance (ANCOVA) models and related analyses of data. We intend to capitalize on our understanding of optimal covariate designs (OCDs) in different ANCOVA models and re-visit these examples with a view to suggest optimal/nearly optimal designs for estimation of the covariate parameter(s). As we will see, for some examples our task is very much routine but for others, it is indeed a highly non trivial exercise.

?We intent to cover a total of six examples—divided in two parts. This is Part I—dealing with two examples.     

A new extension strategy on three-level factorials under wrap-around L2-discrepancy

Sequential experiment is an indispensable strategy and is applied immensely to various fields of science and engineering. In such experiments, it is desirable that a given design should retain the properties as much as possible when few runs are added to it. The designs based on sequential experiment strategy are called extended designs. In this paper, we have studied theoretical properties of such experimental strategies using uniformity measure. We have also derived a lower bound of extended designs under wrap-around L₂-discrepancy measure. Moreover, we have provided an algorithm to construct uniform (or nearly uniform) extended designs. For ease of understanding, some examples are also presented and a lot of sequential strategies for a 27-run original design are tabulated for practice.     

Construction of circular partially balanced-Repeated measurement designs using cyclic shifts

Repeated measurement designs are widely used in medicine, pharmacology, animal sciences and psychology. These designs balance out the residual effects. The situations where balanced repeated measurements designs require a large number of the subjects, partially-balanced repeated measurements designs should be used. In this paper some infinite series are developed which provide circular partially-balanced repeated measurement designs for p (periods) even. Catalogues of circular partially-balanced repeated measurement designs are also presented for v (treatments) ≤ 100 with p = 5, 7 & 9.     

Maximum expected entropy transformed Latin hypercube designs

Existing projection designs (e.g. maximum projection designs) attempt to achieve good space-filling properties in all projections. However, when using a Gaussian process (GP), model-based design criteria such as the entropy criterion is more appropriate. We employ the entropy criterion averaged over a set of projections, called expected entropy criterion (EEC), to generate projection designs. We show that maximum EEC designs are invariant to monotonic transformations of the response, i.e. they are optimal for a wide class of stochastic process models. We also demonstrate that transformation of each column of a Latin hypercube design (LHD) based on a monotonic function can substantially improve the EEC. Two types of input transformations are considered: a quantile function of a symmetric Beta distribution chosen to optimize the EEC, and a nonparametric transformation corresponding to the quantile function of a symmetric density chosen to optimize the EEC. Numerical studies show that the proposed transformations of the LHD are efficient and effective for building robust maximum EEC designs. These designs give projections with markedly higher entropies and lower maximum prediction variances (MPV''s) at the cost of small increases in average prediction variances (APV''s) compared to state-of-the-art space-filling designs over wide ranges of covariance parameter values.     

试论就业导向下高职高专电脑艺术专业人才的培养

目前,我国将电脑艺术设计广泛地应用于各个艺术设计领域,从工业设计、平面设计、建筑设计、室内设计到影视动画、电脑游戏……等等。由此可见电脑艺术设计专业市场前景甚好。电脑艺术设计专业的人才培养和就业已成为人们关注的焦点。如何来培养电脑艺术设计人才呢？他们的就业又将是一个什么样的处境呢？因此笔者借鉴许多前辈的优秀经验和观点阐述了对电脑艺术设计人才的培养和就业趋向的一些看法。