A computerized system to monitor resilience indicators in organizations

The concepts developed by resilience engineering allow the understanding and monitoring the functioning of organizations and, particularly, to map the role of human activities, in success or in failure, enabling a better comprehension about how people make decisions in unexpected situations. The capture of information about human activities in the various organization levels gives managers a deeper real-time understanding of what is influencing the people performance, providing awareness of the factors that influence positively or negatively the organizational goals initially projected. The monitoring is important because the correct functioning of complex systems depends on the knowledge that people have to perform their activities and how the system environment provides tools that actually support the human performance. Therefore, organizations should look forward through precursors in operating signals to identify possible problems or solutions in the structure of tasks and activities, safety, quality, schedule, rework, and maintenance. We apply the concepts of resilience engineering to understand the organization by the analysis of cognitive tasks and activities. The aim is the development of a computerized system to monitor human activities to produce indicators to access system resilience. The validation of the approach was made in a real organization and the results show the successful applicability of the system. Based on findings obtained after the experiment of the system in a real organization, and managers and workers opinions, it was possible to show that the use of system provided an anticipated (real-time) perception about how activities are effectively being performed, allowing managers and workers to make decisions more consistent with daily problems, and also to anticipate solutions to cope with unexpected situations.     

Comparison of decapod communities across an urban-forest land use gradient in Puerto Rican streams

Urbanization influences a range of factors related to stream health, including the hydrologic regime, water quality, and riparian conditions that lead to negative effects on terrestrial and aquatic ecosystems. However, impacts on freshwater decapods from urbanization of tropical streams have not been reported. We hypothesized that changes in decapod communities in watersheds with different levels of urbanization are related to changes in physical stream habitats caused by different land uses and their effects on water discharge. The impacts of land use on the physico-chemical characteristics of streams and freshwater decapod communities were evaluated in three watersheds characterized by low, moderate and high-intensities of urbanization in Puerto Rico. For the low and moderately developed urban watersheds, decapod species richness ranged from 10 to 11 species; the highly urbanized watershed only had 4 species. Macrobrachium faustinum and Xiphocaris elongata were the most ubiquitously species and were found in all watersheds. Multivariable analysis of physical characteristics and densities of the decapod families resulted in one axis that explained 80 % of the total variation among the watersheds and was correlated with stream discharge. The effect of discharge is likely a result of frequent high flows that sustain habitats with high concentrations of dissolved oxygen and low concentrations of pollutants. An increase in physico-chemical parameters were observed from the LUW to the HUW. These results indicate that the decapod communities were most likely influenced by land use and environmental conditions that affected erosional aspects related to water discharge and water quality in the highly impacted watersheds.     

HEAPING‐INDUCED BIAS IN REGRESSION‐DISCONTINUITY DESIGNS

This study uses Monte Carlo simulations to demonstrate that regression‐discontinuity designs arrive at biased estimates when attributes related to outcomes predict heaping in the running variable. After showing that our usual diagnostics may not be well suited to identifying this type of problem, we provide alternatives, and then discuss the usefulness of different approaches to addressing the bias. We then consider these issues in multiple non‐simulated environments. (JEL C21, C14, I12)     

Credit at the Corner Store: An Analysis of Resource Exchange among Detroit‐Area Urban Poor

This ethnographic study examines how and why Detroit‐area credit‐constrained members of the urban poor relied on owners/employees of corner convenience stores, known as “party stores,” for accessing short‐term, interest‐free informal credit services. Findings indicate that informal credit at party stores functioned as a low‐ or no‐cost alternative to formal credit and high‐cost fringe banking services such as payday loans, both of which were inaccessible and/or cost prohibitive for informants. These data contribute empirically to a growing body of research on “credit invisibility” by exploring these populations' use of informal credit mechanisms. Findings also make a theoretical contribution by highlighting the importance of resource exchange networks through which members of the urban poor build strong yet disposable social ties in order to respond to economic shocks, combat food insufficiency, and survive economic destitution.     

Individual Therapy for Couple Problems: Perspectives and Pitfalls

Despite the demonstrated efficacy of conjoint couple therapy, many clients seeking help for couple problems ultimately find themselves in individual therapy for these concerns. Individual therapy for couple problems (ITCP) may evolve from a partner's refusal of conjoint therapy or from the treatment format preferences of either the client or therapist. Having acknowledged the role of partner refusals, we offer some perspectives about the idiosyncratic personal factors and professional background factors that may lead therapists to provide ITCP and discuss the significant pitfalls in its practice. We emphasize five central areas of concern in the ongoing practice of ITCP: structural constraints on change; therapist side‐taking and the therapeutic alliance; inaccurate assessments based on individual client reports; therapeutic focus; and ethical issues relevant to both attending and nonattending partners. We conclude by urging that this very important but largely neglected topic be paid greater attention in psychotherapy research, training and continuing education.     

An adaptive biomarker basket design in phase II oncology trials

The phase II basket trial in oncology is a novel design that enables the simultaneous assessment of treatment effects of one anti-cancer targeted agent in multiple cancer types. Biomarkers could potentially associate with the clinical outcomes and re-define clinically meaningful treatment effects. It is therefore natural to develop a biomarker-based basket design to allow the prospective enrichment of the trials with the adaptive selection of the biomarker-positive (BM+) subjects who are most sensitive to the experimental treatment. We propose a two-stage phase II adaptive biomarker basket (ABB) design based on a potential predictive biomarker measured on a continuous scale. At Stage 1, the design incorporates a biomarker cutoff estimation procedure via a hierarchical Bayesian model with biomarker as a covariate (HBMbc). At Stage 2, the design enrolls only BM+ subjects, defined as those with the biomarker values exceeding the biomarker cutoff within each cancer type, and subsequently assesses the early efficacy and/or futility stopping through the pre-defined interim analyses. At the end of the trial, the response rate of all BM+ subjects for each cancer type can guide drug development, while the data from all subjects can be used to further model the relationship between the biomarker value and the clinical outcome for potential future research. The extensive simulation studies show that the ABB design could produce a good estimate of the biomarker cutoff to select BM+ subjects with high accuracy and could outperform the existing phase II basket biomarker cutoff design under various scenarios.     

Likelihood testing populations modeled by autoregressive process subject to the limit of detection in applications to longitudinal biomedical data

Dependent and often incomplete outcomes are commonly found in longitudinal biomedical studies. We develop a likelihood function, which implements the autoregressive process of outcomes, incorporating the limit of detection problem and the probability of drop-out. The proposed approach incorporates the characteristics of the longitudinal data in biomedical research allowing us to carry out powerful tests to detect a difference between study populations in terms of the growth rate and drop-out rate. The formal notation of the likelihood function is developed, making it possible to adapt the proposed method easily for various different scenarios in terms of the number of groups to compare and a variety of growth trend patterns. Useful inferential properties for the proposed method are established, which take advantage of many well-developed theorems regarding the likelihood approach. A broad Monte-Carlo study confirms both the asymptotic results and illustrates good power properties of the proposed method. We apply the proposed method to three data sets obtained from mouse tumor experiments.     

MULTIPLE-CRITERIA DECISION MAKING INCLUDING QUALITATIVE FACTORS: THE POST-MODEL ANALYSIS APPROACH

As a method of solving multiple-criteria decision making problems with a single quantitative objective and multiple qualitative objectives, the post-model analysis (PMA) approach is proposed. The essence of PMA is to support the trade-offs between a quantitative objective and multiple qualitative objectives so that the decision maker can find a perceived most preferred nondominated solution. To this end, the optimal solution of a quantitative model is found first, without regard for qualitative factors. The solution is then evaluated in terms of qualitative objectives. When the initial quantitatively optimal solution is adjusted to allow improvement of qualitative goals, opportunity costs of achieving qualitative goals are incurred. In this process, an expert system and/or graphical display can be used. PMA therefore provides a way to incorporate quantitative models into knowledge-based expert systems.     

Top Management Team Internationalization and Firm-level Internationalization: The Moderating Effects of Home-region Institutional Diversity and Firm Global Focus

The factors that determine firms' levels of internationalization remain a focal area of international business research. Within this research stream, studies building on the upper echelons theory have investigated the influence of the demographic characteristics of the top management team (TMT) on firms' international expansion. However, the literature to date has overlooked the TMT's overall degree of internationalization as a key driver of firm-level internationalization. In our paper, we argue that by having self-selected into careers abroad, foreign TMT members by definition have a higher cognitive tolerance of foreignness than domestic TMT members do. We theorize that foreign TMT members' higher cognitive tolerance for foreignness enhances the overall TMT's level of international attention and international trust, thereby facilitating strategic decisions that favor firm-level internationalization. Additionally, we propose two key contingencies that attenuate this relationship: the institutional diversity of the firm's home region and the firm's global focus. Analysis of Fortune Global 500 firms supports the hypothesized relationship between TMT internationalization and firm-level internationalization, as well as the two moderation effects.