Urbanization is not associated with increased abundance or decreased richness of terrestrial animals - dissecting the literature through meta-analysis

The widely accepted consensus is that urbanization increases abundance but reduces species richness of animals. This assumption is the premise for empirical tests and theoretical explanations. We studied the association of urbanization with abundance and species richness of different animal taxa in 20 and 26 published articles reporting abundances and richness, respectively via meta-analysis. Because some articles had multiple estimates, we analyzed 40 and 58 estimates of abundance and richness, respectively. Contrary to conventional wisdom, the overall abundance of terrestrial animals was not higher in urban areas, but instead actually lower, while we failed to confirm the conventional thinking of lower species richness with urbanization. These findings cannot, however, be generalized across all cities and animal species, as conflicting differences were reported among geographical regions, animal taxa. Our results question the conventional wisdom that urbanization generally increases abundances while reducing species richness, and highlights the variability of urbanization effects on diversity among taxa and geographic regions.     

Model-Robust Design of Conjoint Choice Experiments

Within the context of choice experimental designs, most authors have proposed designs for the multinomial logit model under the assumption that only the main effects matter. Very little attention has been paid to designs for attribute interaction models. In this article, three types of Bayesian D-optimal designs for the multinomial logit model are studied: main-effects designs, interaction-effects designs, and composite designs. Simulation studies are used to show that in situations where a researcher is not sure whether or not attribute interaction effects are present, it is best to take into account interactions in the design stage. In particular, it is shown that a composite design constructed by including an interaction-effects model and a main-effects model in the design criterion is most robust against misspecification of the underlying model when it comes to making precise predictions.     

All in the Family: How Do Social Capital and Material Wellbeing Affect Relational Wellbeing?

We use a unique dataset from Italy to investigate the impact of socioeconomic characteristics and social capital on family wellbeing and satisfaction. We assess wellbeing using four dimensions of satisfaction with family life: satisfaction with decision making processes, with relationships with partner and children, and with time spent with children. Social capital is measured through information about membership in organizations, trust, and interactions with others. We find that while socioeconomic characteristics in general do not have strong effects on family wellbeing, social capital matters for family life satisfaction.

     

Agency Problems and Airport Security: Quantitative and Qualitative Evidence on the Impact of Security Training

We analyze the issue of agency costs in aviation security by combining results from a quantitative economic model with a qualitative study based on semi‐structured interviews. Our model extends previous principal‐agent models by combining the traditional fixed and varying monetary responses to physical and cognitive effort with nonmonetary welfare and potentially transferable value of employees' own human capital. To provide empirical evidence for the tradeoffs identified in the quantitative model, we have undertaken an extensive interview process with regulators, airport managers, security personnel, and those tasked with training security personnel from an airport operating in a relatively high‐risk state, Turkey. Our results indicate that the effectiveness of additional training depends on the mix of “transferable skills” and “emotional” buy‐in of the security agents. Principals need to identify on which side of a critical tipping point their agents are to ensure that additional training, with attached expectations of the burden of work, aligns the incentives of employees with the principals' own objectives.     

The Interpretation of Clinical Trials of Immediate Versus Delayed Therapy

Prospective, randomised clinical comparisons with a control group are the ideal way to evaluate the effectiveness of a new therapy. However if the new therapy is already available, then it may be unethical to refuse patients this treatment indefinitely. In some trials, patients randomised to the control group receive placebo until their condition deteriorates, and are then switched to the new therapy. Patients randomised to the experimental group receive the new treatment immediately. An analysis following the intention-to-treat principle will be a valid comparison of the two treatment policies actually used. However, such an analysis will underestimate the effect of immediate therapy relative to completely untreated controls, and in particular a negative conclusion should not be interpreted to mean that the therapy is ineffective.In this paper we introduce a parametric approach, which models the dependence between the survival time and the time of switching to the new treatment. This is used first to illustrate the lack of power of the intention-to-treat analysis for evaluating the therapy relative to a pure control. More speculatively, an alternative method of analysis based on our model is presented. We illustrate the issues with data from a prospective randomised study, in which one group of HIV-positive patients received zidovudine immediately after randomisation while control patients were switched to zidovudine only when their condition deteriorated.     

Adjusting for Network Size and Composition Effects in Exponential-Family Random Graph Models

Exponential-family random graph models (ERGMs) provide a principled way to model and simulate features common in human social networks, such as propensities for homophily and friend-of-a-friend triad closure. We show that, without adjustment, ERGMs preserve density as network size increases. Density invariance is often not appropriate for social networks. We suggest a simple modification based on an offset which instead preserves the mean degree and accommodates changes in network composition asymptotically. We demonstrate that this approach allows ERGMs to be applied to the important situation of egocentrically sampled data. We analyze data from the National Health and Social Life Survey (NHSLS).     

Resilience in Business and Management Research: A Review of Influential Publications and a Research Agenda

This paper identifies the development of and gaps in knowledge in business and management research on resilience, based on a systematic review of influential publications among 339 papers, books and book chapters published between 1977 and 2014. Analyzing these records shows that resilience research has developed into five research streams, or lines of enquiry, which view resilience as (1) organizational responses to external threats, (2) organizational reliability, (3) employee strengths, (4) the adaptability of business models or (5) design principles that reduce supply chain vulnerabilities and disruptions. A review of the five streams suggests three key findings: First, resilience has been conceptualized quite differently across studies, meaning that the different research streams have developed their own definitions, theories and understandings of resilience. Second, conceptual similarities and differences among these streams have not yet been explored, nor have insights been gleaned about any possible generalizable principles for developing resilience. Third, resilience has been operationalized quite differently, with few insights into the empirics for detecting resilience to future adversity (or the absence thereof). This paper outlines emerging research trends and pathways for future research, highlighting opportunities to integrate and expand on existing knowledge, as well as avenues for further investigation of resilience in business and management studies.     

Tackling Climate Change Through Social Change: A Comparative Analysis

In recent years there has been a widespread perception of climate change as a growing threat to security, both at the individual level and at the international level. This increased attention is mainly due to scientific research, which indicates that climate change is a process already underway, with observable facts and potentially serious consequences. Moreover, according to some scholars, even the immediate implementation of stringent mitigation measures—i.e. reducing greenhouse gas emissions—would not contain the effects of climate change in coming decades, making it necessary to combine the efforts of mitigation policies targeted for the prevention of major threats. Are there any chances for climate stabilization to be sustainable with the economic growth required under a capitalist system? On the one hand, climate environmentalists raise concerns about the risks associated with global warming. On the other hand, leading economists’ main concern is to foster economic growth, thus, a trade off is advocated. In fact, policy-makers are unlikely to impose a burden on the economic growth of their own country in order to meet the targets imposed by the international climate change agreements. This work intends to identify and suggest a framework for climate policies, with the aim to maximize social consensus, through an integration of the issues raised by both disputing fields. A proposed solution is to take into consideration an additional GDP driver, the so-called human capital that would allow a social change.