Bringing Closure to the Plotting Position Controversy

In this article, it is explicitly demonstrated that the probability of non exceedance of the mth value in n order ranked events equals m/(n + 1). Consequently, the plotting position in the extreme value analysis should be considered not as an estimate, but to be equal to m/(n + 1), regardless of the parent distribution and the application. The many other suggested plotting formulas and numerical methods to determine them should thus be abandoned. The article is intended to mark the end of the century-long controversial discussion on the plotting positions.     

Best linear unbiased and invariant estimation in location-scale families based on double-ranked set sampling

Abstract

In this article, we propose the best linear unbiased estimators (BLUEs) and best linear invariant estimators (BLIEs) for the unknown parameters of location-scale family of distributions based on double-ranked set sampling (DRSS) using perfect and imperfect rankings. These estimators are then compared with the BLUEs and BLIEs based on ranked set sampling (RSS). It is shown that under perfect ranking, the proposed estimators are uniformly better than the BLUEs and BLIEs obtained via RSS. We also propose the best linear unbiased quantile (BLUQ) and the best linear invariant quantile (BLIQ) estimators for normal distribution under DRSS. It is observed that the proposed quantile estimators are more efficient than the BLUQ and BLIQ estimators based on RSS for both perfect and imperfect orderings.     

Augmenting the Deliberative Method for Ranking Risks

The Department of Homeland Security (DHS) characterized and prioritized the physical cross‐border threats and hazards to the nation stemming from terrorism, market‐driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top‐ranked and bottom‐ranked risks, let alone deciding what the stand‐out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand‐out risks to help prioritize further analysis.     

Robust Ordinal Regression and Stochastic Multiobjective Acceptability Analysis in multiple criteria hierarchy process for the Choquet integral preference model

The paper deals with two important issues of Multiple Criteria Decision Aiding: interaction between criteria and hierarchical structure of criteria. To handle interactions, we apply the Choquet integral as a preference model, and to handle the hierarchy of criteria, we apply the recently proposed methodology called Multiple Criteria Hierarchy Process. In addition to dealing with the above issues, we suppose that the preference information provided by the Decision Maker is indirect and has the form of pairwise comparisons of criteria with respect to their importance and pairwise preference comparisons of some pairs of alternatives with respect to some criteria. In consequence, many instances of the Choquet integral are usually compatible with this preference information. These instances are identified and exploited by Robust Ordinal Regression and Stochastic Multiobjective Acceptability Analysis. To illustrate the whole approach, we show its application to a real world decision problem concerning the ranking of universities for a hypothetical Decision Maker.     

Modification and simplification of thurstone scaling method,and its demonstration with a crime seriousness assessment

The paper aims to improve the Thurstone scaling method by reducing the workload of data collection and simplifying the procedures of application. It proposes a hierarchical structure for organizing items that are to be scaled. Instead of making paired comparisons, the respondents would be asked to rank the items. The ranks of the items would then be transformed into paired comparisons. Workload of data collection can hence be greatly reduced. As an alternative to Thurstone model, the use of three models, i.e., linear, exponential and information, to compute serious scores is also demonstrated.     

“单方索取”还是“相互需要”——代际同住中的需求组合与亲子选择

基于2018年中国老年社会追踪调查的数据,本文深入挖掘老年人与成年子女的同住需求组合类型,并分析其中子女的性别和排行两个维度的同住机制。研究发现,在中国,代际互惠的合作型同住占据首要地位,代际重心下移和浓厚的互惠色彩是当今代际同住的主流, 城乡之间代际互惠的逻辑存在差异。从代际同住机制看,特别是在农村,儿子依旧是同住选择偏好的对象,但女儿在代际同住中更有可能承担赡养的责任;农村地区排行靠后的子女在代际同住中更有可能得到父母的帮扶,也更有可能承担赡养的责任。     

Knowledge dissemination in operations management: Published perceptions versus academic reality

The channels for knowledge generation and dissemination in the business disciplines are many: presenting research at conferences, writing books, distributing working papers, offering insights in society newsletters, giving invited talks, publishing studies in academic journals, and many other venues, including even blogs and perhaps Facebook^®. But the most important venue is probably published research in “top-level” academic journals. In the discipline of Operations Management, many studies and lists have been published that attempt to determine which of these journals are supposedly the “top” according to either citation analyses, the opinion of recognized experts, author affiliations, bibliometric studies, and other approaches. These lists may then, in turn, be used in different degrees to evaluate research. However, what really counts is what the academic institutions actually use for guidance in evaluating faculty research. Based on a new source of ranking data from AACSB-accredited schools, we compare published journal-ranking studies against that of academe to determine the degree to which the studies reflect academic “reality”. We present rankings of OM journals based on this new source of data and on an aggregate of the stream of published studies, and evaluate their consistency.