Stable matching problems with exchange restrictions

We study variants of classical stable matching problems in which there is an additional requirement for a stable matching, namely that there should not be two participants who would prefer to exchange partners. The problem is motivated by the experience of real-world medical matching schemes that use stable matchings, where cases have arisen in which two participants discovered that each of them would prefer the other’s allocation, a situation that is seen as unfair. Our main result is that the problem of deciding whether an instance of the classical stable marriage problem admits a stable matching, with the additional property that no two men would prefer to exchange partners, is NP-complete. This implies a similar result for more general problems, such as the hospitals/residents problem, the many-to-one extension of stable marriage. Unlike previous NP-hardness results for variants of stable marriage, the proof exploits the powerful algebraic structure underlying the set of all stable matchings. In practical matching schemes, however, applicants’ preference lists are typically of short fixed length, and we describe a linear time algorithm for the problem in the special case where all of the men’s preference lists are of length ≤3.     

Firm-level correlates of emergent green supply chain management practices in the Chinese context

Greening the supply chain is increasingly a concern for many business enterprises and a challenge for logistics management in the 21st century. Of particular concern is how to arouse organizational environmental awareness and put environmental activities into practice in the logistics activities of their supply chains. This paper investigates the correlation of two major factors, organizational learning and management support, with the extent of adoption of green supply chain management (GSCM) practices in Chinese manufacturing firms, where their inbound and outbound logistics activities are potential polluters to the environment. Organizational and operational learning was derived from the firm's experience with programs such as total quality management and environmental management systems. Management support included support for GSCM ideas and practices from top and middle-level management and cooperation across organizational functions. We find significant positive relationships between organizational learning mechanisms, organizational support and the adoption of GSCM practices, after controlling for a number of other influences including regulations, marketing, supplier, cost pressures, industry levels of the relevant practice and organizational size. Implications of our findings on logistics management are discussed.     

Eliciting Risk and Time Preferences

We design experiments to jointly elicit risk and time preferences for the adult Danish population. Since subjects are generally risk averse, we find that joint elicitation provides estimates of discount rates that are significantly lower than those found in previous studies and more in line with what would be considered as a priori reasonable rates. The statistical specification relies on a theoretical framework that involves a latent trade‐off between long‐run optimization and short‐run temptation. Estimation of this specification is undertaken using structural, maximum likelihood methods. Our main results based on exponential discounting are robust to alternative specifications such as hyperbolic discounting. These results have direct implications for attempts to elicit time preferences, as well as debates over the appropriate domain of the utility function when characterizing risk aversion and time consistency.     

Lack of reciprocity among Dutch teachers: Validation of reciprocity indices and their relation to stress and well-being

This research presents the results of two related studies on the convergent and construct validity of three measures of reciprocity in exchange relationships at work. In Study 1, 71 Dutch teachers were interviewed about their specific investments and outcomes in the exchange relationships with their students, colleagues and school. ANOVA revealed that they reported significantly more investments than outcomes, and that the number of reported investments and outcomes mentioned varied as a function of the type of exchange relationship. Building on these results, multi-item scales were created to assess reciprocity at a detailed level for each of the three exchange relationships. Study 2 validated these specific reciprocity measures by relating them to two global assessments of reciprocity (convergent validity) as well as to measures of job stress and well-being (construct validity). LISREL-analysis of data obtained from a further sample of 224 teachers revealed that for each type of exchange relationship there were significant, consistent and meaningful relationships among the three reciprocity measures. Further, hierarchical regression analysis showed that the reciprocity measures were differentially related to job stressors and measures of well-being. Implications are discussed.     

Job stress, job strain, and psychological withdrawal among Dutch university staff: towards a dualprocess model for the effects of occupational stress

This study examined the antecedents of job strain (emotional exhaustion, health complaints) and withdrawal behaviour (e.g. lowered organizational commitment) among a cross-sectional sample of 131 academic staff members of the law department of a large Dutch university. Conservation of resources theory (Hobfoll, 1989) provided the theoretical background for this study. Strains and withdrawal behaviours were expected to be most prominent among those who reported having few resources and/or who reported high job demands. Structural equation modelling revealed that this was indeed the case. As predicted, differential patterns of effects emerged for job demands and job resources. Analysis of the effects of four job-specific stressors revealed that especially the structural aspects of a staff member's teaching task (e.g. the number of students in their classes) contributed strongly to perceived job demands. Theoretical and practical implications of the study are discussed.     

Practical Methods for Meeting Remediation Goals at Hazardous Waste Sites

Risk-based cleanup goals or preliminary remediation goals (PRGs) are established at hazardous waste sites when contaminant concentrations in air, soil, surface water, or groundwater exceed specified acceptable risk levels. When derived in accordance with the Environmental Protection Agency's risk assessment guidance, the PRG is intended to represent the average contaminant concentration within an exposure unit area that is left on the site following remediation. The PRG, however, frequently has been used inconsistently at Superfund sites with a number of remediation decisions using the PRG as a not-to-exceed concentration (NTEC). Such misapplications could result in overly conservative and unnecessarily costly remedial actions. The PRG should be applied in remedial actions in the same manner in which it was generated. Statistical methods, such as Bower's Confidence Response Goal, and mathematical methods such as "iterative removal of hot spots," are available to assist in the development of NTECs that ensure the average postremediation contaminant concentration is at or below the PRG. These NTECs can provide the risk manager with a more practical cleanup goal. In addition, an acute PRG can be developed to ensure that contaminant concentrations left on-site following remediation are not so high as to pose an acute or short-term health risk if excessive exposure to small areas of the site should occur. A case study demonstrates cost savings of five to ten times associated with the more scientifically sound use of the PRG as a postremediation site average, and development of a separate NTEC and acute PRG based on the methods referenced in this article.     

Property Loss Estimation for Wind and Earthquake Perils

This article describes the development of a generic loss assessment methodology, which is applicable to earthquake and windstorm perils worldwide. The latest information regarding hazard estimation is first integrated with the parameters that best describe the intensity of the action of both windstorms and earthquakes on building structures, for events with defined average return periods or recurrence intervals. The subsequent evaluation of building vulnerability (damageability) under the action of both earthquake and windstorm loadings utilizes information on damage and loss from past events, along with an assessment of the key building properties (including age and quality of design and construction), to assess information about the ability of buildings to withstand such loadings and hence to assign a building type to the particular risk or portfolio of risks. This predicted damage information is then translated into risk-specific mathematical vulnerability functions, which enable numerical evaluation of the probability of building damage arising at various defined levels. By assigning cost factors to the defined damage levels, the associated computation of total loss at a given level of hazard may be achieved. This developed methodology is universal in the sense that it may be applied successfully to buildings situated in a variety of earthquake and windstorm environments, ranging from very low to extreme levels of hazard. As a loss prediction tool, it enables accurate estimation of losses from potential scenario events linked to defined return periods and, hence, can greatly assist risk assessment and planning.     

Customized clinical case management for chronically ill patients. Health system sees remarkable results with teams of case managers,physicians, patients

Securing excellent care and positive outcomes for seriously ill, high-risk patients requires extraordinary measures. A health system in Georgia is experiencing strong results by taking a team approach to health care with case managers, physicians and patients working together.     

Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data

Access management, which systematically limits opportunities for egress and ingress of vehicles to highway lanes, is critical to protect trillions of dollars of current investment in transportation. This article addresses allocating resources for access management with incomplete and partially relevant data on crash rates, travel speeds, and other factors. While access management can be effective to avoid crashes, reduce travel times, and increase route capacities, the literature suggests a need for performance metrics to guide investments in resource allocation across large corridor networks and several time horizons. In this article, we describe a quantitative decision model to support an access management program via risk‐cost‐benefit analysis under data uncertainties from diverse sources of data and expertise. The approach quantifies potential benefits, including safety improvement and travel time savings, and costs of access management through functional relationships of input parameters including crash rates, corridor access point densities, and traffic volumes. Parameter uncertainties, which vary across locales and experts, are addressed via numerical interval analyses. This approach is demonstrated at several geographic scales across 7,000 kilometers of highways in a geographic region and several subregions. The demonstration prioritizes route segments that would benefit from risk management, including (i) additional data or elicitation, (ii) right‐of‐way purchases, (iii) restriction or closing of access points, (iv) new alignments, (v) developer proffers, and (vi) etc. The approach ought to be of wide interest to analysts, planners, policymakers, and stakeholders who rely on heterogeneous data and expertise for risk management.