Assessment of Ecological Risks at Former Landfill Site Using TRIAD Procedure and Multicriteria Analysis

Old industrial landfills are important sources of environmental contamination in Europe, including Finland. In this study, we demonstrated the combination of TRIAD procedure, multicriteria decision analysis (MCDA), and statistical Monte Carlo analysis for assessing the risks to terrestrial biota in a former landfill site contaminated by petroleum hydrocarbons (PHCs) and metals. First, we generated hazard quotients by dividing the concentrations of metals and PHCs in soil by the corresponding risk‐based ecological benchmarks. Then we conducted ecotoxicity tests using five plant species, earthworms, and potworms, and determined the abundance and diversity of soil invertebrates from additional samples. We aggregated the results in accordance to the methods used in the TRIAD procedure, conducted rating of the assessment methods based on their performance in terms of specific criteria, and weighted the criteria using two alternative weighting techniques to produce performance scores for each method. We faced problems in using the TRIAD procedure, for example, the results from the animal counts had to be excluded from the calculation of integrated risk estimates (IREs) because our reference soil sample showed the lowest biodiversity and abundance of soil animals. In addition, hormesis hampered the use of the results from the ecotoxicity tests. The final probabilistic IREs imply significant risks at all sampling locations. Although linking MCDA with TRIAD provided a useful means to study and consider the performance of the alternative methods in predicting ecological risks, some uncertainties involved still remained outside the quantitative analysis.     

Decision Analysis for Utilizing Hazardous Waste Site Assessments in Real Estate Acquisition

When a buyer needs to purchase commercial or industrial property, the decision of what real estate to purchase should be based on an assessment of the total costs of acquisition. In addition to the direct purchase cost, other possible costs include hazardous waste site assessment studies and clean up costs if the purchased site proves to be contaminated. This paper presents a decision analysis model for determining when and which type of hazardous waste assessment tests should be conducted and how the test output affects the choice of site. The model assumes there are two types of hazardous waste assessment, an historical use review (phase 1 test)and soil and water sampling (phase 2 test). Model inputs include the cost, sensitivity and specificity for each type of test, a site's purchase price, and a priori probability of contamination, along with the clean-up cost for a contaminated site. The analysis uses the results of a data survey of 17 environmental engineering firms in setting values on the model input requirements. The paper also reports on sensitivity analysis with the model for the purpose of providing decision-makers with explicit protocols for test utilization.     

Spatial Variation of Soil Lead in an Urban Community Garden: Implications for Risk‐Based Sampling

Soil lead pollution is a recalcitrant problem in urban areas resulting from a combination of historical residential, industrial, and transportation practices. The emergence of urban gardening movements in postindustrial cities necessitates accurate assessment of soil lead levels to ensure safe gardening. In this study, we examined small‐scale spatial variability of soil lead within a 15 × 30 m urban garden plot established on two adjacent residential lots located in Detroit, Michigan, USA. Eighty samples collected using a variably spaced sampling grid were analyzed for total, fine fraction (less than 250 μm), and bioaccessible soil lead. Measured concentrations varied at sampling scales of 1–10 m and a hot spot exceeding 400 ppm total soil lead was identified in the northwest portion of the site. An interpolated map of total lead was treated as an exhaustive data set, and random sampling was simulated to generate Monte Carlo distributions and evaluate alternative sampling strategies intended to estimate the average soil lead concentration or detect hot spots. Increasing the number of individual samples decreases the probability of overlooking the hot spot (type II error). However, the practice of compositing and averaging samples decreased the probability of overestimating the mean concentration (type I error) at the expense of increasing the chance for type II error. The results reported here suggest a need to reconsider U.S. Environmental Protection Agency sampling objectives and consequent guidelines for reclaimed city lots where soil lead distributions are expected to be nonuniform.     

Strict Uncertainty: A Criterion for Moderately Pessimistic Decision Makers*

This paper proposes a decision rule to rank actions under strict uncertainty, the available information being limited to the states of nature, the set of alternative rows, and the consequence of choosing every row if a given state occurs. This rule is suitable to moderately pessimistic individuals and social groups, these agents being neither maximax nor maximin decision makers but people who assume that the best outcome from the action will not occur. For these decision makers the paper shows the existence of a consistent weight system in which one and only one weight is attached to each state of the world under plausible conditions of domination. Most of the traditional axioms are satisfied by the proposed ranking approach. In the frame of disappointment (measured by ranges of column dispersion), the meaning of some controversial postulates used in the literature is explained. The proposed criterion is a departure from Laplace's (1825) rule and from the remaining standard criteria. Only in the special case of equal column dispersion do both Laplace's rule and the proposed weights lead to the same solution.     

Risk Perception of Heavy Metal Soil Contamination and Attitudes toward Decontamination Strategies

Contaminated soils are a common environmental risk all over the world. One major source of risk is heavy metal soil contamination caused by industrial emissions. This quasiexperimental study investigated the perception of these risks by exposed and nonexposed people, their attitudes toward bioremediation methods using hyperaccumulating plants, and the influence of long-term aspects of sustainability on the acceptance of bioremediation methods. Major findings were that people living in a contaminated area perceived the risk of the heavy metal soil contamination as higher than the general risk of contamination. Second, a factor analysis showed that the factors dread, control, and catastrophic potential were relevant for the perception and valuation of low-dose environmental risks such as the contamination of the investigated area. In addition, a cluster analysis showed that the risk of heavy metal soil contamination was perceived as similar to that of oil contamination, ozone layer, preservatives and genetic technology. It was perceived indifferently with regard to dread. The uncontrollability of heavy metal soil contamination was estimated as medium, and its catastrophic potential as low. Third, exposed and nonexposed participants preferred bioremediation methods to classical methods (e.g., excavation and chemical treatment of the soil), because they perceived the environmental and esthetical performance of the bioremediation as important criteria. Sustainability or precautionary issues, such as the prevention of harm for future generations, were highly correlated with the acceptance of the use of bioremediation methods in people's residential areas.     

A Framework for the Analysis of Error in Conjunctive,Multi-Criteria,Satisficing Decision Processes*

This paper examines the impact of certain types of error on ad hoc, unstructured decision making that incorporates a satisficing strategy in a multi-criteria context using the conjunctive rule. The impacts of error in evaluation and of error in minimal or satisficing levels are systematically modelled for each of the decision criteria. Error functions, analytical expressions, and procedures are developed to obtain information such as the likelihood of correct decision making in the presence of evaluation and minimal criteria level error. These are applied to a specific research design, which is then analyzed. This highlights certain features of decision making in a satisficing context, such as the importance of keeping the number of decision criteria to a minimum. The results yield various insights, some of which confirm information obtained from previous analyses. A major advantage of the framework presented is that it can provide quantitative measurements which support ideas previously couched in qualitative terms only. Although the framework is applied in the context of decision making that uses the conjunctive rule in the case of multiple criteria, other satisficing strategies can be accommodated as well.     

Dimensions of Market Attractiveness: Competitively Interactive Spatial Models*

This paper presents a normative, multidisciplinary approach for evaluating market entry strategies with concern for the effects of spatial assumptions on performance expectations. An assessment framework is linked to a series of models that show the value of adding spatial and competitive perspectives to typical baseline conceptualizations of market opportunity. Criteria for assessing market attractiveness are discussed with special concern for the problems of field service firms whose market boundaries are not limited by fixed facility locations. The problem is conceptualized as the managerial decision to locate a new brokerage office in a highly competitive regional market area. Realistic constraints are established by focusing the market entry decision through aggregate data from secondary sources that are readily available to an outsider who had not been active in the geographic markets considered. A simple model based on market potential is progressively enhanced with spatially adjusted measures of market attractiveness and competitive resistance. Empirical tests highlight the impact of alternative model formulations and choice criteria on the decision-making process.     

How can we ascertain,understand and interpret the performance level of a production system? A visual method: 'The plan of preferences'

The general context of this study is the parameterizing of the production system. The aim is to regulate the physical flow according to objectives, usually expressed in terms of performance indicator values. Performance control requires mastery of the consequences of the choices made. It then becomes essential to be able to articulate the potential effects of the various decisions. The existing approaches to solving this problem all imply the use of means of simulation capable of assessing the value of the performance indicators for each configuration of the action parameters. Taking this assumption as a basis, and focusing on the user, a multiple criteria approach is developed towards the understanding and schematization of the behaviour of a given system. The particularity of this approach lies in combining both data analysis and user expertise. The instrumentation approach uses tools for data analysis and assistance in decision making to achieve an original visualization of the structure of performance levels in a plan, called the plan of preferences .     

Resource Distribution in Multiple Attacks with Imperfect Detection of the Attack Outcome

This article extends the previous research of consecutive attacks strategy by assuming that an attacker observes the outcome of each attack imperfectly. With given probabilities it may wrongly identify a destroyed target as undestroyed, and wrongly identify an undestroyed target as destroyed. The outcome of each attack is determined by a contest success function that depends on the amount of resources allocated by the defender and the attacker to each attack. The article suggests a probabilistic model of the multiple attacks and analyzes how the target destruction probability and the attacker's relative resource expenditure are impacted by the two probabilities of incorrect observation, the attacker's and defender's resource ratio, the contest intensity, the number of attacks, and the resource distribution across attacks. We analyze how the attacker chooses the number of attacks, the attack stopping rule, and the optimal resource distribution across attacks to maximize its utility.     

A Consistency Test for AHP Decision Makers

Saaty's analytic hierarchy process assessed attribute importance by soliciting decision makers' (DM) importance ratios to compute weights. Saaty suggested a decision rule for accepting DM judgments based on a consistency measure derived from the DM's importance ratios. This paper investigates the distribution of random inconsistency and decision rule implications. Stricter consistency requirements for three- and four-attribute criteria matrices are suggested.     

On tie breaking in competitive location under binary customer behavior

Ties in customer facility choice may occur when the customer selects the facility with maximum utility to be served. In the location literature ties in maximum utility are broken by assigning a fixed proportion of the customer demand to the facilities with maximum utility which are owned by the entering firm. This tie breaking rule does not take into account the number of tied facilities of both the entering firm and its competitors. In this paper we introduce a more realistic tie breaking rule which assigns a variable proportion of customer demand to the entering firm depending on the number of tied facilities. We present a general framework in which optimal locations for the old and the new tie breaking rules can be obtained through Integer Linear Programming formulations of the corresponding location models. The optimal locations are obtained for the old tie breaking rule for different values of the fixed proportion and a comparison with the results obtained for the new tie breaking rule is drawn with data of Spanish municipalities in a variety of scenarios. Finally, some conclusions are presented.     

Risk-Based Environmental Remediation: Bayesian Monte Carlo Analysis and the Expected Value of Sample Information

A methodology that simulates outcomes from future data collection programs, utilizes Bayesian Monte Carlo analysis to predict the resulting reduction in uncertainty in an environmental fate-and-transport model, and estimates the expected value of this reduction in uncertainty to a risk-based environmental remediation decision is illustrated considering polychlorinated biphenyl (PCB) sediment contamination and uptake by winter flounder in New Bedford Harbor, MA. The expected value of sample information (EVSI), the difference between the expected loss of the optimal decision based on the prior uncertainty analysis and the expected loss of the optimal decision from an updated information state, is calculated for several sampling plan. For the illustrative application we have posed, the EVSI for a sampling plan of two data points is $9.4 million, for five data points is $10.4 million, and for ten data points is $11.5 million. The EVSI for sampling plans involving larger numbers of data points is bounded by the expected value of perfect information, $15.6 million. A sensitivity analysis is conducted to examine the effect of selected model structure and parametric assumptions on the optimal decision and the EVSI. The optimal decision (total area to be dredged) is sensitive to the assumption of linearity between PCB sediment concentration and flounder PCB body burden and to the assumed relationship between area dredged and the harbor-wide average sediment PCB concentration; these assumptions also have a moderate impact on the computed EVSI. The EVSI is most sensitive to the unit cost of remediation and rather insensitive to the penalty cost associated with under-remediation.     

A multiobjective retail service location model for fastfood restaurants

Traditionally, most existing retail location models largely ignore the behavioral aspect of locational strategies. On the other hand, a few of the existing behavioral models of retail store choice are aspatial at best. This paper designs a multiobjective retail location decision model which not only considers the behavioral and spatial aspects of location scenarios, but also takes advantage of systematic sequential decision process. The model has been applied to solve ‘real-world-like’ fastfood restaurant location problems which were based on the actual data.     

Hiding your criteria will never work

In this era of managed care, the message has been that the health care industry has provided inappropriate or inefficient care, causing the ruination of medicine and ultimately of the U.S. economy. Published research data on small area analysis have demonstrated marked differences in utilization rates for the same surgical procedure in various locations. Researchers and others have logically surmised that criteria used by providers in recommending these procedures have also varied from location to location. Correction, therefore, will require attention to the establishment of logical and defensible criteria.     

The weakness of strong ties: Sampling bias,social ties,and nepotism in family business succession

Decision-making is a complex cognitive activity filled with bias. Leader decision-making is unique because it occurs in a social context. We examine how biases resulting from social network dynamics complicate leaders' decision-making. In particular, we focus on a specific case of leader cognition: nepotism in the succession decisions in the context of family businesses. Succession often leads to a decline in performance because leaders frequently choose family members as their successor, a form of nepotism. We show that even when a leader can overcome individual decision biases, a bias in sampling resulting from families' strong ties can still allow a leader to wrongly conclude that family members are better qualified than external candidates when the opposite is true. We demonstrate this phenomenon using simulation modeling and explore solutions to family business succession planning.     

A multi-period ambulance location and allocation problem in the disaster

To achieve quick response in the disaster, this paper addresses the issue of ambulance location and allocation, as well as the location problem of temporary medical centers. Considering budget and capacity limitations, a multi-period mixed integer programming model is proposed and two hybrid heuristic algorithms are designed to solve this complex problem. The proposed model and algorithm are further verified in a real case study, and the numerical experiments demonstrate the effectiveness of our proposed model. Specifically, we obtain several findings based on the computational results: (1) The best locations of ambulance stations should change in each period because the demand rate changes over time. (2) Involving temporary medical centers is necessary to reduce the average waiting time of injured people. (3) It may not be optimal to allocate ambulances from the nearest ambulance stations because of potentially limited station capacity.

     

An integrated method for cognitive complex multiple experts multiple criteria decision making based on ELECTRE III with weighted Borda rule

The ELECTRE (ELimination Et Choix Traduisant la REalité, in French) is an effective multiple criteria decision making method based on comparative analysis. Among the family of the ELECTRE methods and their extensions, the ELECTRE III is widely used since it can tackle uncertain and imprecise information. The hesitant fuzzy linguistic term set can represent people's perceptions more comprehensively and flexibly than exact numbers especially in cognitive complex decision-making process. In this paper, we develop an integrated method based on the ELECTRE III to handle the cognitive complex multiple experts multiple criteria decision making problems in which the cognitive complex information is represented by hesitant fuzzy linguistic term sets and the outranking relations between alternatives are calculated by a novel score-function-based distance measure between hesitant fuzzy linguistic elements. A combinative weight-determining method involving both subjective and objective opinions of experts is introduced to derive the weights of criteria. After obtaining the ranking of alternatives from each experts’ decision matrix by the distillation algorithm, the weighted Borda rule is implemented to aggregate the rankings of alternatives regarding different experts. Some ordinal consensus measures are introduced to identify the reliability of the final ranking result. An application of hospital ranking in China is provided to validate the efficiency of the proposed method.     

Step-through simulation

This report describes the initial development of the Step-Through variant of Monte Carlo simulation, a new procedure for implementing decision analysis or for training decision makers. Like regular Monte Carlo simulation, it involves sampling possible aftermaths of an initial action, and generating a distribution of outcome values for it. However, the detailed structure and/or assessments of the decision model are elicited as called for in the execution of each trial. It, therefore, permits substantial economy of elicitation if there are few trials. The Step-Through procedure also offers economy of elicitation and calculation over a traditional extensive tree decision-analytic model without requiring simplifications or aggregations in the model's conceptualization. In addition to describing this procedure, this paper presents the results of a preliminary test and evaluation of its viability.     

The Risk Management of Third Parties During Construction in Multifunctional Urban Locations

Buildings above roads, railways, and existing buildings themselves are examples of multifunctional urban locations. The construction stage of those buildings is in general extremely complicated. Safety is one of the critical issues during the construction stage. Because the traffic on the infrastructure must continue during the construction of the building above the infrastructure, falling objects due to construction activities form a major hazard for third parties, i.e., people present on the infrastructure or beneath it, such as car drivers and passengers. This article outlines a systematic approach to conduct quantitative risk assessment (QRA) and risk management of falling elements for third parties during the construction stage of the building above the infrastructure in multifunctional urban locations. In order to set up a QRA model, quantifiable aspects influencing the risk for third parties were determined. Subsequently, the conditional probabilities of these aspects were estimated by historical data or engineering judgment. This was followed by integrating those conditional probabilities, now used as input parameters for the QRA, into a Bayesian network representing the relation and the conditional dependence between the quantified aspects. The outcome of the Bayesian network—the calculation of both the human and financial risk in quantitative terms—is compared with the risk acceptance criteria as far as possible. Furthermore, the effect of some safety measures were analyzed and optimized in relation with decision making. Finally, the possibility of integration of safety measures in the functional and structural building design above the infrastructure are explored.     

A two-phase robot selection procedure

In this paper, a two-phase methodology is proposed for robot selection. In phase 1, data envelopment analysis is used as a means to determine the technically efficient robot alternatives, considering cost and technical performance parameters. Using data envelopment analysis permits us to consider the fact that the performance parameters specified by the vendors are generally unattainable in practice. In the second phase, a fuzzy robot selection algorithm is utilized to rank the technically efficient robots according to both predetermined objective criteria and additional vendor-related subjective criteria. The algorithm is based on calculating fuzzy suitability indices for the technically efficient robot alternatives, and then, ranking the fuzzy indices to select the best robot alternative. A comprehensive example is provided to illustrate the decision procedure. The algorithm proposed in here is also applicable to a broader area of decision problems, e.g. facility site selection, determination of the best CNC machine or flexible manufacturing system among a set of mutually exclusive alternatives.