DOES WHOM YOU KNOW MATTER? UNRAVELING THE INFLUENCE OF PEERS' NETWORK ATTRIBUTES ON ACADEMIC PERFORMANCE

This paper examines how students' network size, distance, prestige, and connections to influential individuals impact academic performance. Larger and closer networks facilitate information exchange, but may also increase distractions that decrease productivity. We resolve this ambiguity using administrative data from a business school that features random assignment of students to multiple overlapping sets of peers, allowing us to calculate degree, closeness, eigenvector, and Katz‐Bonacich centrality for each node. We find that increasing closeness centrality within the network negatively affects student performance measured by grade point average, suggesting that synergy reduction and information processing costs outweigh benefits from greater information access. (JEL I23, L14, L23)     

The Leverage of Protest: Market,Media, and Reputational Disruption in Social Movement Success

How do social movements gain concessions from large corporations? The ability of protests to attain leverage by imposing disruption costs on their targets is widely assumed but less often tested. In this article, we assess the ability of protests to attain concessions by disrupting three broad sources of interest to firm officials: maximizing shareholder value, gaining positive media, and fostering a well-reputed image. In contrast to the body of research on the benefits to movements from shaping media discourses and damaging the reputations of their targets, we find that only market disruption provides protests with leverage. We show this through statistical analyses of an original database of protests against large corporations in the United States over five years, 2005–2009. This study advances social movement and organizational research by demonstrating the ways in which the interests of large corporations provide insurgents with means of attaining leverage over their targets. It also speaks to the broad debate over the importance of disrupting the material versus symbolic interests of movement targets. Our results suggest that when it comes to obtaining concessions from large corporations, it is material disruption and not symbolic disruption that provides movements with leverage.     

Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment

A wide range of uncertainties will be introduced inevitably during the process of performing a safety assessment of engineering systems. The impact of all these uncertainties must be addressed if the analysis is to serve as a tool in the decision-making process. Uncertainties present in the components (input parameters of model or basic events) of model output are propagated to quantify its impact in the final results. There are several methods available in the literature, namely, method of moments, discrete probability analysis, Monte Carlo simulation, fuzzy arithmetic, and Dempster-Shafer theory. All the methods are different in terms of characterizing at the component level and also in propagating to the system level. All these methods have different desirable and undesirable features, making them more or less useful in different situations. In the probabilistic framework, which is most widely used, probability distribution is used to characterize uncertainty. However, in situations in which one cannot specify (1) parameter values for input distributions, (2) precise probability distributions (shape), and (3) dependencies between input parameters, these methods have limitations and are found to be not effective. In order to address some of these limitations, the article presents uncertainty analysis in the context of level-1 probabilistic safety assessment (PSA) based on a probability bounds (PB) approach. PB analysis combines probability theory and interval arithmetic to produce probability boxes (p-boxes), structures that allow the comprehensive propagation through calculation in a rigorous way. A practical case study is also carried out with the developed code based on the PB approach and compared with the two-phase Monte Carlo simulation results.     

STRATEGIC OR NONSTRATEGIC: THE ROLE OF FINANCIAL BENEFIT IN BANKRUPTCY

A partial test for strategic behavior in bankruptcy filing may be formulated by testing whether consumers manipulate their debt and filing decision jointly, or not: that is, testing for endogeneity of financial benefit and the bankruptcy filing decision. Using joint maximum likelihood estimation of an extended discrete choice model, test results are consistent with nonstrategic filing: financial benefit is exogenous to the filing decision. This result is confirmed in two different datasets (Panel Study of Income Dynamics and Survey of Consumer Finances). This result is consistent with an ex ante low net gain from a bankruptcy filing; a type of “rational inattention” to rare events such as bankruptcy. (JEL D12, D14)     

Differences in Retail Inventory Investment Behavior During Macroeconomic Shocks: Role of Service Level

In this article, we analyze how retailers change their inventory investment behavior in response to macroeconomic shocks. We examine if service level, as measured by the ratio of stockout to inventory holding costs, can explain the differences in observed behavior across retailers. We use data on macroeconomic indicators and quarterly filings of US public retailers from 1985 to 2009 to estimate a dynamic model of short‐ and long‐term impact of macroeconomic shocks on inventory investment. Our results show that retailers with a high service level increase their inventory investment significantly more than those with a low service level during expansion shocks. Conversely, retailers with a low service level curtail their inventory investment significantly more than those with a high service level during periods of economic contractions. Thus, we show that the aggregate change in inventory investment documented in prior macroeconomics research is driven by different sets of retailers, as predicted by newsvendor logic. We draw implications of our findings to retailers as well as their suppliers.     

ETHNICITY NOT RACE: A PUBLIC HEALTH PERSPECTIVE

This article presents an argument, from a public health perspective, against the use of the term ‘race’ and for its replacement by the term ‘ethnicity’. Historically, the rise of the race concept in society was dependent on its undeserved status as an objective scientific and biological category and was associated with strategies of exclusion and political domination. Mainstream science played a key role in the rise of the race concept but has since largely abandoned it in face of evidence from population genetics. Similarly, the public health movement has historically been concerned with race/ethnicity as a determinant of unequal health status, but the race term has now all but disappeared from the Australian public health literature, where it has been replaced by the concept of ethnicity. Ethnicity is a complex social variable, with cultural and political dimensions, but no biological dimension. Adopting a public health perspective on ethnicity which recognises the fluid and contested nature of this socio‐political variable, whilst seeking to make explicit its relevance and definitional limits, allows us to dispense with the race concept altogether, since race has no additional explanatory or strategic value above that of ethnicity. The race term is still commonly used, however, in general conversation and in the media. The persistence of the race concept and of racism is difficult to explain but may be related historically to the politics of nationalism, and in modern times to the politics of difference and identity that characterise the modern multicultural nation‐state. Abandoning the terminology of race leaves racism without any logical basis, and may contribute to a process of social change, although it cannot be expected to eliminate the phenomenon of racism.     

Knowledge-Based Risk Assessment Under Uncertainty for Species Invasion

Management of invasive species depends on developing prevention and control strategies through comprehensive risk assessment frameworks that need a thorough analysis of exposure to invasive species. However, accurate exposure analysis of invasive species can be a daunting task because of the inherent uncertainty in invasion processes. Risk assessment of invasive species under uncertainty requires potential integration of expert judgment with empirical information, which often can be incomplete, imprecise, and fragmentary. The representation of knowledge in classical risk models depends on the formulation of a precise probabilistic value or well-defined joint distribution of unknown parameters. However, expert knowledge and judgments are often represented in value-laden terms or preference-ordered criteria. We offer a novel approach to risk assessment by using a dominance-based rough set approach to account for preference order in the domains of attributes in the set of risk classes. The model is illustrated with an example showing how a knowledge-centric risk model can be integrated with the dominance-based principle of rough set to derive minimal covering "if ... , then...," decision rules to reason over a set of possible invasion scenarios. The inconsistency and ambiguity in the data set is modeled using the rough set concept of boundary region adjoining lower and upper approximation of risk classes. Finally, we present an extension of rough set to evidence a theoretic interpretation of risk measures of invasive species in a spatial context. In this approach, the multispecies interactions in an invasion risk are approximated with imprecise probability measures through a combination of spatial neighborhood information of risk estimation in terms of belief and plausibility.