Multiphase experiments in practice: A look back

Multiphase experiments are introduced and an overview of their design and analysis as it is currently practised is given via an account of their development since 1955 and a literature survey. Methods that are available for designing and analysing them are outlined, with an emphasis on making explicit the role of the model in their design. The availability of software and its use is described in detail. Overall, while multiphase designs have been applied in areas such as plant breeding, plant pathology, greenhouse experimentation, product storage, gene expression studies, and sensory evaluation, their deployment has been limited.     

A Bayesian sequential design with binary outcome

Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha‐spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maximum total sample size on critical values. Alpha‐spending functions are compared using power and actual sample size through simulations. Further simulations show that, when total sample size is fixed, the proposed design has greater power than the traditional Bayesian sequential design, which sets equal stopping bounds at all interim analyses. We also find that the proposed design with the new stopping for futility rule results in greater power and can stop earlier with a smaller actual sample size, compared with the traditional stopping rule for futility when all other conditions are held constant. Finally, we apply the proposed method to a real data set and compare the results with traditional designs.     

An access network design problem with end-to-end QoS constraints

In this paper, we present an access network design problem with end-to-end quality of service (QoS) requirement. The problem can be conceptualized as a two-level hierarchical location-allocation problem on the tree topology with nonlinear side constraints. The objective function of the nonlinear mixed integer programming model minimizes the total cost of switch and fiber cable, while satisfying demand within the prescribed level of QoS. By exploiting the inherent structure of the nonlinear QoS constraints, we develop linearization techniques for finding an optimal solution. Also, we devise an effective exact optimal algorithm within the context of disjunctive constraint generation. We present promising computational results that demonstrate the effectiveness of the proposed solution procedure.     

Policy instrument affordances: a framework for analysis

The present study uses the concept of technological efficacy derived from ecological psychology and design studies to offer an alternative way of analyzing how policy instruments affect change. Reasoning from this, the paper outlines a framework for analyzing policy instruments in terms of their affordances. We define affordances as the means through which an instrument exerts influence on its intended target audience. Using this approach, we contend that policy instruments may be analyzed as interfaces that organize social relations and create structures of opportunity and/or restrict possibilities for action. We argue that explicating the pathways through which instruments afford or constrain action is a central task for policy analysis. Our proposed framework of analysis builds on the idea that instruments yield effects by facilitating action and learning. We further contend that the actions that an instrument can facilitate or inhibit are determined by specific affordance modalities of the instrument in conjunction with contingencies of the actor and the policy environment. Examples from research policy are used to illustrate some of these effects.     

Improving Risk Management: From Lame Excuses to Principled Practice

The three classic pillars of risk analysis are risk assessment (how big is the risk and how sure can we be?), risk management (what shall we do about it?), and risk communication (what shall we say about it, to whom, when, and how?). We propose two complements as important parts of these three bases: risk attribution (who or what addressable conditions actually caused an accident or loss?) and learning from experience about risk reduction (what works, and how well?). Failures in complex systems usually evoke blame, often with insufficient attention to root causes of failure, including some aspects of the situation, design decisions, or social norms and culture. Focusing on blame, however, can inhibit effective learning, instead eliciting excuses to deflect attention and perceived culpability. Productive understanding of what went wrong, and how to do better, thus requires moving past recrimination and excuses. This article identifies common blame‐shifting “lame excuses” for poor risk management. These generally contribute little to effective improvements and may leave real risks and preventable causes unaddressed. We propose principles from risk and decision sciences and organizational design to improve results. These start with organizational leadership. More specifically, they include: deliberate testing and learning—especially from near‐misses and accident precursors; careful causal analysis of accidents; risk quantification; candid expression of uncertainties about costs and benefits of risk‐reduction options; optimization of tradeoffs between gathering additional information and immediate action; promotion of safety culture; and mindful allocation of people, responsibilities, and resources to reduce risks. We propose that these principles provide sound foundations for improving successful risk management.     

An Individual Mixed‐Evaluation Method for Career Intervention

Economic issues linked to career counseling are a cause for concern to policy makers in developed countries because they expect career practitioners to provide evidence of the efficiency of career counseling interventions. The aim of this study was to test an individual evaluation method mixing time series (outcomes) and life narrative (processes). The method used 5 items related to 1 client's career decision self‐efficacy and studied the evolution of those items throughout the intervention of 1 career counselor (43 days). Changepoint analysis helped in identifying the changes that have to be taken into account for time series and which are contextualized in the client's verbatim analysis. This mixed method highlighted that the career counselor's intervention increased the client's career decision self‐efficacy. Practitioners could use the methodology proposed in this article to evaluate their interventions. They could also report their practice to clients, employers, and decision makers.     

阻沙率在沙漠公路高大沙丘段防沙体系设计中的应用

在工程防沙设计中，阻沙率和输沙强度均是确定防护类型及其宽度的重要指标。从工程实际出发，结合典型地形特征，运用实测的阻沙率指标，优化沙漠公路高大沙丘段防沙体系的设计，用理论指导实践的同时，并在实践施工中加以较好地运用，从实践效果上，以阻沙率这一风沙物理指标为依据，确定高大沙丘段的防沙设计参数，是符合实际和可行的方法。     

基于模仿创新的产品设计

在当前我国产品设计相对薄弱,企业资金投入不足的情形下,较难自主创新,模仿创新成为产品设计跨越式发展的必经之路。模仿创新相较率先创新具有后发优势,反而能设计出占据市场主导地位和最具经济效益的产品。但模仿创新不是恶劣的伪造,重点在于借鉴改造,从而形成自身风格。     

A comparison of recent nonparametric methods for testing effects in two-by-two factorial designs

The two-way two-levels crossed factorial design is a commonly used design by practitioners at the exploratory phase of industrial experiments. The F-test in the usual linear model for analysis of variance (ANOVA) is a key instrument to assess the impact of each factor and of their interactions on the response variable. However, if assumptions such as normal distribution and homoscedasticity of errors are violated, the conventional wisdom is to resort to nonparametric tests. Nonparametric methods, rank-based as well as permutation, have been a subject of recent investigations to make them effective in testing the hypotheses of interest and to improve their performance in small sample situations. In this study, we assess the performances of some nonparametric methods and, more importantly, we compare their powers. Specifically, we examine three permutation methods (Constrained Synchronized Permutations, Unconstrained Synchronized Permutations and Wald-Type Permutation Test), a rank-based method (Aligned Rank Transform) and a parametric method (ANOVA-Type Test). In the simulations, we generate datasets with different configurations of distribution of errors, variance, factor's effect and number of replicates. The objective is to elicit practical advice and guides to practitioners regarding the sensitivity of the tests in the various configurations, the conditions under which some tests cannot be used, the tradeoff between power and type I error, and the bias of the power on one main factor analysis due to the presence of effect of the other factor. A dataset from an industrial engineering experiment for thermoformed packaging production is used to illustrate the application of the various methods of analysis, taking into account the power of the test suggested by the objective of the experiment.     

古镇旅游资源开发的总体设计思路——以胜芳古镇旅游资源开发为例

以胜芳古镇旅游资源开发为例,通过对古镇旅游资源的分析评价、SWOT分析、古镇旅游发展目标与战略等问题的分析,扼要阐释了古镇旅游资源开发的总体设计思路。