Validating a short version of the Suicide Intent Scale in China

As Beck's Suicide Intent Scale (SIS) gains popularity in various areas in the world, we are not sure whether the scale is an optimal measure of suicide intent in the Chinese culture. This study is to provide evidence to support the use of the Chinese shortened version of SIS (C-SIS) in Chinese societies. The data were from applying the C-SIS in a psychological autopsy (PA) study of 66 suicides in Dalian, China. Reliability and validity tests were performed on the C-SIS data. Internal consistency analysis showed excellent correlation coefficients for all items but one. Inter-rater reliability tests showed statistically significant correlations between each pair of informants for each item and for the total scores. Criterion validity analysis demonstrated a relatively high correlation between the scores on the Hamilton Depression Rating Scale (HAM-D) and C-SIS. Factor analysis produced three factors accounting for 66.77% of the total variance. The study suggested that C-SIS should be an appropriate instrument for detecting and measuring suicide intent in Chinese societies.     

A quasi-human algorithm for the two dimensional rectangular strip packing problem: in memory of Prof. Wenqi Huang

This paper presents a quasi-human algorithm for the rectangular strip packing problem without guillotine constraint. The basic version of the algorithm works according to seven heuristic selection rules, which are designed to select a corner-occupying action. The strengthened version of the algorithm adopts a branching scheme in which the basic version of the algorithm is applied in a heuristic series of parallel branches. Computational tests carried on eight sets of well-known benchmark instances show that the algorithm is efficient for approximately solving the problem. In comparison with the best algorithms in the literature, the algorithm performs better for zero-waste instances and large scale non-zero-waste instances.     

Best-worst multi-criteria decision-making method

In this paper, a new method, called best-worst method (BWM) is proposed to solve multi-criteria decision-making (MCDM) problems. In an MCDM problem, a number of alternatives are evaluated with respect to a number of criteria in order to select the best alternative(s). According to BWM, the best (e.g. most desirable, most important) and the worst (e.g. least desirable, least important) criteria are identified first by the decision-maker. Pairwise comparisons are then conducted between each of these two criteria (best and worst) and the other criteria. A maximin problem is then formulated and solved to determine the weights of different criteria. The weights of the alternatives with respect to different criteria are obtained using the same process. The final scores of the alternatives are derived by aggregating the weights from different sets of criteria and alternatives, based on which the best alternative is selected. A consistency ratio is proposed for the BWM to check the reliability of the comparisons. To illustrate the proposed method and evaluate its performance, we used some numerical examples and a real-word decision-making problem (mobile phone selection). For the purpose of comparison, we chose AHP (analytic hierarchy process), which is also a pairwise comparison-based method. Statistical results show that BWM performs significantly better than AHP with respect to the consistency ratio, and the other evaluation criteria: minimum violation, total deviation, and conformity. The salient features of the proposed method, compared to the existing MCDM methods, are: (1) it requires less comparison data; (2) it leads to more consistent comparisons, which means that it produces more reliable results.     

A decision tree approach for selecting between demand based,reorder, and JIT/kanban methods for material procurement

In designing mechanisms for the procurement of raw materials, a manager is often faced with the task of selecting from a variety of possible methods. Since the performance of these methods is a function of the environment in which they are implemented, it is the responsibility of the manager to select the method best suited for a particular application. In this paper we present a methodology for assisting managers in the selection process. Specifically, three classes of procurement methods are considered, these are: demand based, reorder, and JIT methods. The selection methodology is structured as a decision tree, which considers the annual usage value, lead time ratio, holding cost, vendor location, vendor delivery performance, and material supply value. Each factor is evaluated on a three level scale, and on the basis of these evaluations the tree makes a selection. The application of the methodology is illustrated via some examples.     

Measuring exposure to bullying and harassment at work: Validity,factor structure and psychometric properties of the Negative Acts Questionnaire-Revised

Abstract

This study investigates the psychometric properties, factor structure and validity of the revised Negative Acts Questionnaire-Revised (NAQ-R), an instrument designed to measure exposure to bullying in the workplace. By reanalyzing data based on a heterogeneous sample of 5288 UK employees, the results show that the 22-item instrument has a high internal stability, with three underlying factors: personal bullying, work-related bullying and physically intimidating forms of bullying, although the instrument may also be used as a single factor measure. Criterion validity was explored by relating the scores on the NAQ-R to a single-item measure of perceived victimization from bullying, showing high correlations with both the total NAQ-R and scores on the three factors. Targets of bullying scored significantly higher on all 22 items compared to non-targets. The NAQ-R correlated as expected with measures of mental health, psychosocial work environment and leadership, indicating a good construct validity of the instrument. Furthermore, a latent class cluster (LCC) analysis showed that the instrument may be used to differentiate between groups of employees with different levels of exposure to bullying, ranging from infrequent exposure to incivility at work to severe victimization from bullying and harassment. The more commonly used operational criteria can also be used to detect targets of bullying. Hence, the NAQ-R is proposed as a standardized and valid instrument for the measurement of workplace bullying.     

On Determining Specifications and Selections of Alternative Technologies for Airport Checked-Baggage Security Screening

Federal law mandates that every checked bag at all commercial airports be screened by explosive detection systems (EDS), explosive trace detection systems (ETD), or alternative technologies. These technologies serve as critical components of airport security systems that strive to reduce security risks at both national and global levels. To improve the operational efficiency and airport security, emerging image-based technologies have been developed, such as dual-energy X-ray (DX), backscatter X-ray (BX), and multiview tomography (MVT). These technologies differ widely in purchasing cost, maintenance cost, operating cost, processing rate, and accuracy. Based on a mathematical framework that takes into account all these factors, this article investigates two critical issues for operating screening devices: setting specifications for continuous security responses by different technologies; and selecting technology or combination of technologies for efficient 100% baggage screening. For continuous security responses, specifications or thresholds are used for classifying threat items from nonthreat items. By investigating the setting of specifications on system security responses, this article assesses the risk and cost effectiveness of various technologies for both single-device and two-device systems. The findings provide the best selection of image-based technologies for both single-device and two-device systems. Our study suggests that two-device systems outperform single-device systems in terms of both cost effectiveness and accuracy. The model can be readily extended to evaluate risk and cost effectiveness of multiple-device systems for airport checked-baggage security screening.     

Machine learning for multi-criteria inventory classification applied to intermittent demand

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously.

In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems.     

Parametric discounting

A parametric approach to the problem of selection from amongst alternative investment opportunities is considered in a discounted cash flow framework. The approach employs differential cash flows, an uncertain planning horizon and a nested approach to composing cash flow parameters. This promotes consistent treatment of alternative investments, clarifies the effects of uncertainty, avoids some of the defects of internal rate of return and payback period criteria and allows direct comparison of best and next best options as primal and dual versions of the same model. Net present value, internal rate of return, annual average cost or payback period assessments may be selected post analysis. A domestic wall insulation example is used for illustrative purposes. This example is related to the hydroelectric power development decision which gave rise to the approach.     

资源约束下可打断项目组合选择模型研究

首先,本文在已有可打断项目组合选择模型的基础上,引入了消耗性资源和可更新资源约束,构建了一个更符合实际的新模型;其次,为了达到模型简化的目的,本文给出了资金约束的现值表示,并给出了理论证明;最后,利用GAMS对模型进行了算例分析。数值实验结果表明：1）资源约束下的项目打断有时可以给企业带来积极效益,这有别于已有的研究;2）在考虑资源约束的情况下,资源消耗少且同时收益高的项目应优先执行;3）当资源的供给量较少时,资源约束是决定项目选择的关键因素。此外,通过企业实际的案例对数值实验结果进行了验证。     

Bin packing with “Largest In Bottom” constraint: tighter bounds and generalizations

The (online) bin packing problem with LIB constraint is stated as follows: The items arrive one by one, and must be packed into unit capacity bins, but a bigger item cannot be packed into a bin which already contains a smaller item. The number of used bins has to be minimized as usually. We show that the absolute performance bound of algorithm First Fit is not worse than 2+1/6≈2.1666 for the problem, improving the previous best upper bound 2.5. Moreover, if the item sizes do not exceed 1/d, then we improve the previous best result 2+1/d to 2+1/d(d+2), for any d≥2. (Both previously best results are due to Epstein, Nav. Res. Logist. 56(8):780–786, 2009.) Furthermore, we define a problem with the generalized LIB constraint, where some incoming items cannot be packed into the bins of some already packed items. The (in)compatibility of the incoming item with the items already packed becomes known only at the arrival of the actual item, and is given by an undirected graph (and, as usual in case of online graph problems, we can see only that part of the graph what already arrived). We show that 3 is an upper bound for this general problem if some natural transitivity constraint is satisfied.     

Triple-solution approach for the strip packing problem with two-staged patterns

A triple-solution approach for the rectangular level strip packing problem is presented, where m item types with specified demands are packed in levels into a strip with definite width and infinite height to minimize the occupied height, with the constraint that the items in the same level cannot be placed one on top of the other. The approach contains two phases and considers three types of solutions. In phase one, two types of solutions, obtained respectively from solving residual problems using column generation and from looking ahead, are considered and the best is selected as phase-one solution. In phase two, an integer programming model is solved over the levels generated in phase-one to obtain phase-two solution. Finally the better one of the phase-one and phase-two solutions are selected. Computational results indicate that the approach is effective for both the instances with strongly heterogeneous items and those with weakly heterogeneous items.     

Optimal Acquisition Quantities in Remanufacturing with Condition Uncertainty

The condition of the used products acquired by remanufacturing firms often varies widely. A firm can manage this variation by acquiring a quantity of used items that exceeds demand, enabling it to remanufacture a subset of the acquired items in the best condition. As more excess items are acquired, the firm can increase its selectivity and lower its remanufacturing costs. In this paper, we examine the tradeoff of acquisition and scrapping costs vs. remanufacturing costs when used product condition is widely varying and uncertain. We derive acquisition quantities that minimize total expected costs for several representations of condition variability and remanufacturing cost structures. We find that, when costs are linear, the optimal acquisition quantity has a closed form and increases with the square root of the degree of condition variability. Our models are based on experience with remanufacturers of cell phones and imaging supplies, and application of our results is illustrated using example data from industry.     

A Framework for Facilitating Sourcing and Allocation Decisions for Make‐to‐Order Items

This paper provides a fundamental building block to facilitate sourcing and allocation decisions for make‐to‐order items. We specifically address the buyer's vendor selection problem for make‐to‐order items where the goal is to minimize sourcing and purchasing costs in the presence of fixed costs, shared capacity constraints, and volume‐based discounts for bundles of items. The potential suppliers for make‐to‐order items provide quotes in the form of single sealed bids or participate in a dynamic auction involving open bids. A solution to our problem can be used to determine winning bids amongst the single sealed bids or winners at each stage of a dynamic auction. Due to the computational complexity of this problem, we develop a heuristic procedure based on Lagrangian relaxation technique to solve the problem. The computational results show that the procedure is effective under a variety of scenarios. The average gap across 2,250 problem instances is 4.65%.     

A new EPQ model: integrating lower pricing,rework and reject situations

The economic production quantity (EPQ) is a well-known and commonly used inventory control technique. It has been used for well over 50 years to optimize lot sizes in transportation/production. The standard results are easy to apply but are based on a number of assumptions. A common assumption in the EPQ model is that all units produced are of perfect quality, this will underestimate the actual required quantity. Many researchers have studied the effects after relaxing this assumption on the EPQ model. The previous studies had considered that imperfect quality and defective items are either to be reworked instantaneously and kept in stock or rejected at a cost. The objective of this paper is to provide a framework to integrate lower pricing, rework and reject situations into a single EPQ model. A 100% inspection is performed in order to identify the amount of good quality items, imperfect quality items and defective items in each lot. This model assumes that items of imperfect quality, not necessarily defective, could be used in another production situation or sold to a particular purchaser at a lower price. The electronic and clothing industries give good examples for such situations. A mathematical model is developed and a numerical example is presented to illustrate the solution procedures. It is found that the time factor of when to sell the imperfect items is critical, as this decision will affect the inventory cost and the batch quantities.     

PERFORMANCE OF THE EXPECTED UTILITY METHOD AND TWO OTHER NORMATIVE METHODS IN INSURANCE DECISION MAKING*

In an experiment, thirty-six professional insurance men employed the utility method, the worry method, and the comparison method in two insurance problems to determine the appropriate insurance coverage. It was found that the best act with the utility method almost always was no insurance, whereas the best act with the other two methods tended to be complete insurance. The utility method best act rarely agreed with the subject's actual preferred act, while the comparison method best act usually was the same or almost the same as the actual preferred act. While the worry method suggests that the subjects typically are risk averse, the utility functions obtained tend to show that the subjects typically are not risk averse.     

Communicating Conservation Status: How Different Statistical Assessment Criteria Affect Perceptions of Extinction Risk

Although alternative forms of statistical and verbal information are routinely used to convey species’ extinction risk to policymakers and the public, little is known about their effects on audience information processing and risk perceptions. To address this gap in literature, we report on an experiment that was designed to explore how perceptions of extinction risk differ as a function of five different assessment benchmarks (Criteria A–E) used by scientists to classify species within IUCN Red List risk levels (e.g., Critically Endangered, Vulnerable), as well as the role of key individual differences in these effects (e.g., rational and experiential thinking styles, environmental concern). Despite their normative equivalence within the IUCN classification system, results revealed divergent effects of specific assessment criteria: on average, describing extinction risk in terms of proportional population decline over time (Criterion A) and number of remaining individuals (Criterion D) evoked the highest level of perceived risk, whereas the single‐event probability of a species becoming extinct (Criterion E) engendered the least perceived risk. Furthermore, participants scoring high in rationality (analytic thinking) were less prone to exhibit these biases compared to those low in rationality. Our findings suggest that despite their equivalence in the eyes of scientific experts, IUCN criteria are indeed capable of engendering different levels of risk perception among lay audiences, effects that carry direct and important implications for those tasked with communicating about conservation status to diverse publics.     

Job Satisfaction,Comparison Earnings,and Gender

This paper examines sex differences in job satisfaction by utilizing data from the 1986 UK Social and Economic Life Initiative (SCELI) household survey. It attempts to ascertain the relationship between actual and comparison pay and job satisfaction. Employees were asked on a 0–10 scale how satisfied or dissatisfied they were with their present job. They were also asked to state whether they were equitably, over or underpaid and to say how much pay they thought they deserved. Uniquely, therefore, we are able to analyse the effects of both actual and objective and subjective comparative pay measures on job satisfaction. The paper rejects the view that the higher expressed job satisfaction of women represents an innate difference rather than the results of self‐selection into jobs with highly valued attributes.     

虚拟企业合作伙伴选择三阶段模型及方法研究

虚拟企业是新时代应对激烈竞争、迅速变化的市场环境的主要模式,合作伙伴选择是关系虚拟企业成败的关键环节,该过程非常重要又极其复杂。考虑到已有选择方案的效率低下和可操作性不理想,本文提出三阶段选择模型,并给出每阶段所采用的分析方法,目的是高效合理地获得合作伙伴多目标组合优化问题的最优解。     

顾客满意度测量探讨：量表设计、信度和效度

针对消费者行为研究中,对顾客满意/不满意构念存在单维/双维的讨论,顾客满意度测量常常会得到左偏甚至严重左偏的结果,通过设计量表、收集数据、信度和效度检验以及结构方程模型分析等进行了充分讨论。研究发现:①把顾客满意和不满意当作同一维度的2个极端符合实际情况;②通过适当的量表设计可在一定程度上避免测量结果左偏,以及顾客满意和不满意测量之间存在非对称性。此外,对可靠并有效测量顾客满意度的方法提出改进建议;讨论了研究的实际意义和局限性。     

Personal Values, Beliefs, and Ecological Risk Perception

A mail survey on ecological risk perception was administered in the summer of 2002 to a randomized sample of the lay public and to selected risk professionals at the U.S. Environmental Protection Agency (US EPA). The ranking of 24 ecological risk items, from global climate change to commercial fishing, reveals that the lay public is more concerned about low-probability, high-consequence risks whereas the risk professionals are more concerned about risks that pose long-term, ecosystem-level impacts. To test the explanatory power of the value-belief-norm (VBN) theory for risk perception, respondents were questioned about their personal values, spiritual beliefs, and worldviews. The most consistent predictors of the risk rankings are belief in the new ecological paradigm (NEP) and Schwartz's altruism. The NEP and Schwartz's altruism explain from 19% to 46% of the variance in the risk rankings. Religious beliefs account for less than 6% of the variance and do not show a consistent pattern in predicting risk perception although religious fundamentalists are generally less concerned about the risk items. While not exerting as strong an impact, social-structural variables do have some influence on risk perception. Ethnicities show no effect on the risk scales but the more educated and financially well-off are less concerned about the risk items. Political leanings have no direct influence on risk rankings, but indirectly affect rankings through the NEP. These results reveal that the VBN theory is a plausible explanation for the differences measured in the respondents' perception of ecological risk.