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.     

Risk Ranking for Foodborne Microbial Hazards in New Zealand: Burden of Disease Estimates

Priority setting for food safety management at a national level requires risks to be ranked according to defined criteria. In this study, two approaches (disability‐adjusted life years (DALYs) and cost of illness (COI)) were used to generate estimates of the burden of disease for certain potentially foodborne diseases (campylobacteriosis, salmonellosis, listeriosis (invasive, perinatal, and nonperinatal), infection with Shiga toxin‐producing Escherichia coli (STEC), yersiniosis, and norovirus infection) and their sequelae in New Zealand. A modified Delphi approach was used to estimate the food‐attributable proportion for these diseases. The two approaches gave a similar ranking for the selected diseases, with campylobacteriosis and its sequelae accounting for the greatest proportion of the overall burden of disease by far.     

INDIVIDUAL ITEM FORECASTING MODEL EVALUATION*

A computer simulation experiment was conducted to evaluate and compare seven individual item forecasting models across five different demand patterns. Results indicate the best model varies depending upon the demand pattern, the time period forecast, the noise level of the demand pattern, and to a lesser extent the measure of forecast error. Across all demand patterns, exponential double smoothing was best for the long run forecast and at least second best for the short run regardless of noise level in the demand patterns. Analysis of models within a demand pattern yielded, in most cases, several models as ranking equally well. The adaptive model developed here did not perform as well as some other models. For example, it ranked no better than third on a step function demand pattern.     

Promotion according to who or what you know: managers' and workers' perception of factors influencing promotion

This paper presents partial findings of research examining the perceptions of managers and workers regarding promotions in the Israeli high-tech industry. A questionnaire containing a series of factors related to promotion was conducted with 95 workers and 36 managers in an international high-tech corporation's subsidiary located in Israel. The initial findings indicated a high degree of consent between workers and managers that the most important factor influencing promotion was success in projects. While workers and managers gave similar rankings for the most and least important factors influencing promotions, there were substantial differences in the ranking of the other factors. Among managers, education and multidisciplinary knowledge were ranked second and third, whereas among workers, politics and pressure on the supervisor were ranked second and third. The findings are discussed in terms of HRD in the organization.     

A Deliberative Method for Ranking Risks (I): Overview and Test Bed Development

Risk ranking offers a potentially powerful means for gathering public input to help set risk-management priorities. In most rankings conducted to date, the categories and attributes used to describe the risks have varied widely, the materials and procedures have not been designed to facilitate comparisons among risks on all important attributes, and the validity and reproducibility of the resulting rankings have not been assessed. To address these needs, a risk-ranking method was developed in which risk experts define and categorize the risks to be ranked, identify the relevant risk attributes, and characterize the risks in a set of standardized risk summary sheets, which are then used by lay or other groups in structured ranking exercises. To evaluate this method, a test bed involving 22 health and safety risks in a fictitious middle school was created. This article provides an overview of the risk-ranking method and describes the challenges faced in designing the middle school test bed. A companion article in this issue reports on the validity of the ranking procedures and the level of agreement among risk managers regarding ranking of risks and attributes.     

A New Approach to the Group Ranking Problem: Finding Consensus Ordered Segments from Users’ Preference Data

The group ranking problem involves constructing coherent aggregated results from users’ preference data. The goal of most group ranking problems is to generate an ordered list of all items that represents the user consensus. There are, however, two weaknesses to this approach. First, a complete list of ranked items is always output even when there is no consensus or only a slight consensus. Second, due to similarity of performance, in many practical situations, it is very difficult to differentiate whether one item is really better than another within a set. These weaknesses have motivated us to apply the clustering concept to the group ranking problem, to output an ordered list of segments containing a set of similarly preferred items, called consensus ordered segments. The advantages of our approach are that (i) the list of segments is based on the users’ consensuses, (ii) the items with similar preferences are grouped together in the same segment, and (iii) the relationships between items can be easily seen. An algorithm is developed to construct the consensus of the ordered segments from the users’ total ranking data. Finally, the experimental results indicate that the proposed method is computationally efficient, and can effectively identify consensus ordered segments.     

超效率DEA模型的模糊扩展

在输入、输出数据为模糊数而效率值为准确值的模糊DEA模型中,会出现有两个以上有效单元,从而无法对所有决策单元进行全排序的情形。本文利用模糊数的基于α-截集的比较规则,建立了模糊条件下的超效率DEA模型,有效地解决了模糊决策单元的全排序问题。文末给出了一个实例。     

A data envelopment analysis approach for ranking journals

We create a data envelopment analysis (DEA) model to rank business journals, using data from the Thomson Reuters Journal Citation Reports^® (JCR). As opposed to previous models that ranked journals in only one field and mostly relied on survey data, this model is used to rank 358 business journals from five different JCR categories according to such citation-based factors as the number of articles, the number of citations, impact factor, five-year impact factor, immediacy index, eigenfactor score, and article influence score. We compute relative efficiencies of the journals and thereby create plausible journal rankings that largely, but not completely, corroborate three widely used business publication journal ranking lists. In addition, we show how the different characteristics of the JCR data impact the DEA ranking model. Finally, we identify journals that are not on the business publication lists but consistently perform very well relative to those benchmark journals, and should possibly be included in the business publication ranking lists. We also identify journals whose inclusion in widely used business publication rankings cannot be justified by our methodology.     

A NOTE ON OPTIMAL PORTFOLIO SELECTION UNDER STABLE PARETIAN DISTRIBUTIONS*

Elton, Gruber, and Padberg's [2] [3] ranking procedure and Kwan's [6] nonranking procedure for optimal portfolio selection lead to the same solution. This is because of a particular functional property of the cutoff rate for security performance. In this note, the robustness of that functional property is demonstrated the normality of security returns assumed in the above studies is relaxed to encompass the general family of stable Paretian distributions. The proof here is an important step toward portfolio analysis using some multiindex models when securities cannot be ranked.     

Important Strategic and Tactical Manufacturing Issues in the 1990s*

This paper reports the identification and ranking of major manufacturing issues that American manufacturing managers and academics must focus on and resolve in the 1990s to be competitive on a global basis. Vice-presidents of manufacturing from over 75 companies across the United States were asked in a Delphi study to rank the key strategic and tactical issues facing American manufacturing in the next three to five years. Based on three rounds of a Delphi study, quality management, manufacturing strategy, and process technology emerged as the top ranked strategic issues. The top ranked tactical issues were quality control, manufacturing planning and control systems, and work force supervision. These issues were valid across diverse industry groups, since the industrial and educational background of the respondents was shown to have no impact on the final consensus rankings and opinions reported in this paper. Factor analysis of the responses by the panel revealed that certain issues tend to be consistently viewed together, and were interpreted accordingly to provide insights into the ranking of issues. Apart from building a consensus among experts on key manufacturing issues of present and future importance, this study can also be helpful for setting future academic research and pedagogical priorities for the field of production and operations management.     

COMPARISON OF CONSENSUS METHODS FOR PRIORITY RANKING PROBLEMS

Various consensus methods proposed for ranking problems yield controversial rankings and/or tied rankings which are vulnerable to considerable dispute. These include Borda-Kendall (BK) and minimum-variance (MV) methods. This paper compares three continuous (ratio-scale) consensus scoring methods with BK and MV ranking methods. One method, termed GM, is an eigenvector scaling of the geometric-mean consensus matrix. GM allows for (1) paired-comparison voting inputs (as opposed to all-at-once ranking), (2) pick-the-winner preference voting, and (3) ratio-scale preference voting. GM is relatively simple to calculate on small computers or calculators, and merging of “close” candidates into tied rankings can be achieved by using an e-threshold tie rule discussed in this paper. The GM method thus can be used for paired-comparison voting to calculate both a ratio-scaled consensus index (based on a consensus eigenvector) and a ranking of candidates that allows for ties between “close” candidates. Eigenvalue analysis is used as a means of evaluating voter inconsistencies.     

Exploring the Utility of Preference Assessments in Organizational Behavior Management

The present study compared two variations of stimulus preference assessments: a survey in which direct service employees ranked their preferences for a variety of items, and a multiple stimulus preference assessment without replacement (MSWO), in which textual stimuli were used to represent the actual items. Results obtained for four participants revealed identical preference hierarchies across each type of stimulus preference assessment for one participant, with three participants demonstrating variations in their preference hierarchies during the MSWO when compared with the ranking survey.     

A Scale of Risk

This article proposes a conceptual framework for ranking the relative gravity of diverse risks. This framework identifies the moral considerations that should inform the evaluation and comparison of diverse risks. A common definition of risk includes two dimensions: the probability of occurrence and the associated consequences of a set of hazardous scenarios. This article first expands this definition to include a third dimension: the source of a risk. The source of a risk refers to the agents involved in the creation or maintenance of a risk and captures a central moral concern about risks. Then, a scale of risk is proposed to categorize risks along a multidimensional ranking, based on a comparative evaluation of the consequences, probability, and source of a given risk. A risk is ranked higher on the scale the larger the consequences, the greater the probability, and the more morally culpable the source. The information from the proposed comparative evaluation of risks can inform the selection of priorities for risk mitigation.     

A Process for Incorporating Comparative Risk into Environmental Policymaking in Louisiana

The goal of Louisiana's 1990–1991 comparative risk project, also called the Louisiana Environmental Action Plan (LEAP), was to incorporate risk assessment into state environmental planning and policymaking. Scientists, government officials, and citizens were brought together to estimate the relative risk to human health, natural resources, and quality of life posed by 33 selected environmental issues. The issues were then ranked according to their relative estimated risks. It was hoped that this ranking of "comparative risks" would enable state policymakers to target the most important environmental problems and allocate scarce public resources more rationally and efficiently. As a result of the project, the governor issued an Executive Order forming a permanent Public Advisory Committee to continue this type of comparative risk assessment in Louisiana.     

Post-consensus analysis of group decision making processes by means of a graph theoretic and an association rules mining approach

It is assumed that a group of experts is tasked to evaluate (rank) a finite set of alternatives during a group decision making (GDM) session. The GDM session may go through a number of iterations (stages) to reach a consensus. At each iteration at least one of the experts changes his/her ranking of some of the alternatives. The session terminates when a consensus has been reached or no expert is willing to alter his/her ranking. In the latter case a compromised consensus is somehow determined. It is also assumed that a data recording mechanism exists that keeps log files with information on each session and the iterations involved at each session. Such logs describe how each individual expert has ranked the alternatives at each iteration of each session. It is also assumed that there is a supervisory authority of this GDM process. This authority wishes to analyze the log files to extract any actionable insights. An approach based on some graph theoretic and the mining of association rules is proposed to identify any dynamics that may exist in the way the experts make ranking decisions. Such analysis may reveal unknown, but potentially useful information, on the way the experts make decisions and also on the way the experts may interact with each other. Knowing such relationships may be pivotal on the way the groups of experts need to be formed and operate during the GDM sessions. Some experimental results based on synthetic data are described and analyzed in terms of the proposed approaches.     

Factors influencing a firm’s decision to conduct remanufacturing: evidence from the Thai automotive parts industry

This paper aims to investigate the key factors influencing the decision-making process of firms in conducting remanufacturing activities, using the Thai automotive parts as a case study. Our results show that on average, business feasibility is the most influential determinant driving the decision-making of firms, followed by areas of the firm’s strategic factors, and policy factors. In terms of individual factors, product maturity is ranked first as the most important factor for a firm to engage in remanufacturing activities, followed by financial aspects, availability of skilled workers and technical aspects. Policies related to trade, intellectual property rights and the environment are identified as the least crucial factors in affecting the decisions of firms. Characteristics of firms and products matter in ranking the factors influencing a firm’s decision to conduct remanufacturing.     

基于概率权重函数和随机占优准则的开放式基金评级

传统的开放式基金评级方法存在两个缺陷,首先是忽视了现实中投资者是如何做决策的,假定投资者对利益和损失的主观态度相同;其次是忽略了现实的样本性质,假定随机收益的样本达到渐近正态的规模。通过期望效用的高阶泰勒序列展开建立超额收益的高阶矩和效用函数的关系,以高阶矩为约束条件估计样本的经验概率,再对经验概率进行决策权重调整。在此基础上,通过扩展夏普比和应用随机占优准则进行基金评级,并对645种开放式基金进行了案例分析。     

政府投资项目代建人选择评价模型研究

基于对国内试点地区政府部门与代建单位的调研,提出由代建人实力与业绩、代建项目组织管理水平、代建管理大纲、代建管理目标及保证措施、代建管理费用5个一级指标、13个二级指标构成的代建人选择评价指标体系,采用Likert 5点法对指标进行综合评分。在此基础上,运用模糊熵的方法,以条件熵度量各项评价指标的相对重要性,采用双基点法确定出代建人的优劣顺序,避免了依赖主观判断进行评分的弊端,提高了政府在代建人选择过程中的客观性和准确性。最后,通过项目实例验证了该模型的有效性。     

Classification of Listeria monocytogenes Persistence in Retail Delicatessen Environments Using Expert Elicitation and Machine Learning

Increasing evidence suggests that persistence of Listeria monocytogenes in food processing plants has been the underlying cause of a number of human listeriosis outbreaks. This study extracts criteria used by food safety experts in determining bacterial persistence in the environment, using retail delicatessen operations as a model. Using the Delphi method, we conducted an expert elicitation with 10 food safety experts from academia, industry, and government to classify L. monocytogenes persistence based on environmental sampling results collected over six months for 30 retail delicatessen stores. The results were modeled using variations of random forest, support vector machine, logistic regression, and linear regression; variable importance values of random forest and support vector machine models were consolidated to rank important variables in the experts’ classifications. The duration of subtype isolation ranked most important across all expert categories. Sampling site category also ranked high in importance and validation errors doubled when this covariate was removed. Support vector machine and random forest models successfully classified the data with average validation errors of 3.1% and 2.2% (n = 144), respectively. Our findings indicate that (i) the frequency of isolations over time and sampling site information are critical factors for experts determining subtype persistence, (ii) food safety experts from different sectors may not use the same criteria in determining persistence, and (iii) machine learning models have potential for future use in environmental surveillance and risk management programs. Future work is necessary to validate the accuracy of expert and machine classification against biological measurement of L. monocytogenes persistence.     

Chainwise Paired Comparisons

The pairwise comparison technique is a building block of the Analytic Hierarchy Process (AHP), which has been popularly used for multicriteria decision analysis. This paper develops a shortcut technique in which only n paired comparisons forming a closed chain are needed for n decision elements. Together with the development of a simple and intuitive measure of (inconsistency, this technique derives the relative weights of decision elements via easy step-by-step calculations on a spreadsheet format. Its performance has been tested on Saaty's wealth of nations example. It is important to notice that ranking and weights yielded from this alternative technique are identical to Harker's incomplete pairwise comparison solution for the same chain orientation for the example tested.