Distributed intervention: networked content moderation in anonymous mobile spaces

Given recent public focus on the use of digital tools to engage in discrimination and harassment, online platforms have come under increasing scrutiny to address online incivility. Many of these efforts have been critiqued for relying too heavily on technical tools or burdening individuals with the responsibility for reporting inappropriate actions. This research examines practices of digital bystander intervention on the anonymous localized mobile app Yik Yak. Through an analysis of the firsthand experiences of college students in the United States, this research identifies and investigates practices of networked intervention—that is, strategies of content moderation where success relies on collective action. Rooted in a general uncertainty and skepticism regarding reporting tools provided by the platform, findings suggest a preference for intervention practices that depend on distributed responsibility and networked activity. Taking inspiration from research on college bathroom graffiti—a parallel discursive environment—this paper employs the feminist theory of relational autonomy to explore the possibilities and limitations of networked intervention to cultivate individual and collective empowerment.     

Integrating Behavioral Science with Human Factors to Address Process Safety

ABSTRACT

Applying the science of human factors to eliminate error across all aspects of process design, management, operation, and maintenance has been a focus in the process safety area for many years. Human error has been attributed as a major cause of many high profile catastrophic accidents around the world. These accidents have resulted in national and international attention, which has led to a focus on improving organizational capabilities, systems, and in many cases, governmental regulations around human factors. This article provides a review of the field of human factors highlighting various topics in the literature, and introduces governmental regulatory bodies currently engaging organizations in a scientific approach to human factors. Finally, the need for integrating behavioral science methodologies with human factors is addressed. This is done with specific focus on how Organizational Behavior Management methodologies can work in concert with human factors to optimize process safety.     

Engaging with Comparative Risk Appraisals: Public Views on Policy Priorities for Environmental Risk Governance

Communicating the rationale for allocating resources to manage policy priorities and their risks is challenging. Here, we demonstrate that environmental risks have diverse attributes and locales in their effects that may drive disproportionate responses among citizens. When 2,065 survey participants deployed summary information and their own understanding to assess 12 policy‐level environmental risks singularly, their assessment differed from a prior expert assessment. However, participants provided rankings similar to those of experts when these same 12 risks were considered as a group, allowing comparison between the different risks. Following this, when individuals were shown the prior expert assessment of this portfolio, they expressed a moderate level of confidence with the combined expert analysis. These are important findings for the comprehension of policy risks that may be subject to augmentation by climate change, their representation alongside other threats within national risk assessments, and interpretations of agency for public risk management by citizens and others.     

Supply Chain Strategies and International Tax Arbitrage

What motivates the geographic footprint of the supply chains that multinational firms (MNFs) deploy? Traditional research in the operations and supply chain management literature tends to recommend locations primarily based on differentials in production costs and the ramifications of physical distance ignoring the role of taxation. MNFs that strategically position parts of their supply chains in low‐tax locations can allocate the profits across the divisions to improve post‐tax profits. For the profit allocation to be defensible to tax authorities, the divisional operations must possess real decision authority and bear meaningful risks. Generally speaking, the greater the transfer of risk and control, the larger the allowable allocation of profit. These transfers may also create inefficiencies due to misalignment of business goals and attitudes toward risk. We model these trade‐offs in the context of placing in a low‐tax region a subsidiary that oversees product distribution (as a limited risk distributor commissionnaire, limited risk distributor, or fully fledged distributor). Our analysis demonstrates that the MNF's preferences regarding the operating structures are not necessarily an obvious ordering based on the amount of risk and decision authority transferred to the division in the low‐tax jurisdiction. We derive and analyze threshold values of the performance parameters that describe the main trade‐offs involved in selecting an operating structure. We find some of the optimal decisions to exhibit interesting non‐monotone behavior. For instance, profits can increase when the tax rate in the low‐tax jurisdiction increases. Numerical analysis shows that the Limited‐Risk Distributor structure is rarely optimal and quantifies when each alternative dominates it.     

Distance domination in graphs with given minimum and maximum degree

For an integer \(k \ge 1\), a distance k-dominating set of a connected graph G is a set S of vertices of G such that every vertex of V(G) is at distance at most k from some vertex of S. The distance k-domination number \(\gamma _k(G)\) of G is the minimum cardinality of a distance k-dominating set of G. In this paper, we establish an upper bound on the distance k-domination number of a graph in terms of its order, minimum degree and maximum degree. We prove that for \(k \ge 2\), if G is a connected graph with minimum degree \(\delta \ge 2\) and maximum degree \(\Delta \) and of order \(n \ge \Delta + k - 1\), then \(\gamma _k(G) \le \frac{n + \delta - \Delta }{\delta + k - 1}\). This result improves existing known results.     

Introducing the expatriate ‘Entry-Mode’: an exploratory qualitative study of a missing link in global mobility and expatriate management research

ABSTRACT

This article introduces the novel concepts of expatriate ‘entry-modes’, ‘comb-patriates’, and ‘Fourth-Country Nationals’ (FCNs), emerging from an exploratory qualitative investigation of 51 Scandinavian expatriates in Hong Kong. Global mobility research has traditionally been overly focused on the characteristics and background variables of expatriates or accumulated experiences after arrival, and has neglected the phase and mode of entering the new host country. Unveiling new global mobility patterns is significant for multinational enterprises’ (MNE) global talent recruitment, and has implications for training and development. This is due to directing the focus towards the increasing numbers of those individuals who are not expatriating in the conventional linear fashion, such as between an MNE’s headquarter (HQ) and its subsidiaries overseas. The critical stance taken in this article is articulated through a theoretical lens comprising a social constructionist epistemology. Theoretical contributions, future research avenues, as well as managerial relevance and policy implications are also discussed.     

Testing independence based on Bernstein empirical copula and copula density

In this paper we provide three nonparametric tests of independence between continuous random variables based on the Bernstein copula distribution function and the Bernstein copula density function. The first test is constructed based on a Cramér-von Mises divergence-type functional based on the empirical Bernstein copula process. The two other tests are based on the Bernstein copula density and use Cramér-von Mises and Kullback–Leibler divergence-type functionals, respectively. Furthermore, we study the asymptotic null distribution of each of these test statistics. Finally, we consider a Monte Carlo experiment to investigate the performance of our tests. In particular we examine their size and power which we compare with those of the classical nonparametric tests that are based on the empirical distribution function.     

On generalised estimating equations for vector regression

Generalised estimating equations (GEE) for regression problems with vector‐valued responses are examined. When the response vectors are of mixed type (e.g. continuous–binary response pairs), the GEE approach is a semiparametric alternative to full‐likelihood copula methods, and is closely related to Prentice & Zhao's mean‐covariance estimation equations approach. When the response vectors are of the same type (e.g. measurements on left and right eyes), the GEE approach can be viewed as a ‘plug‐in’ to existing methods, such as the vglm function from the state‐of‐the‐art VGAM package in R. In either scenario, the GEE approach offers asymptotically correct inferences on model parameters regardless of whether the working variance–covariance model is correctly or incorrectly specified. The finite‐sample performance of the method is assessed using simulation studies based on a burn injury dataset and a sorbinil eye trial dataset. The method is applied to data analysis examples using the same two datasets, as well as to a trivariate binary dataset on three plant species in the Hunua ranges of Auckland.     

A powerful and efficient algorithm for breaking the links between aliased effects in asymmetric designs

Fractional factorial (FF) designs are no doubt the most widely used designs in experimental investigations due to their efficient use of experimental runs. One price we pay for using FF designs is, clearly, our inability to obtain estimates of some important effects (main effects or second order interactions) that are separate from estimates of other effects (usually higher order interactions). When the estimate of an effect also includes the influence of one or more other effects the effects are said to be aliased. Folding over an FF design is a method for breaking the links between aliased effects in a design. The question is, how do we define the foldover structure for asymmetric FF designs, whether regular or nonregular? How do we choose the optimal foldover plan? How do we use optimal foldover plans to construct combined designs which have better capability of estimating lower order effects? The main objective of the present paper is to provide answers to these questions. Using the new results in this paper as benchmarks, we can implement a powerful and efficient algorithm for finding optimal foldover plans which can be used to break links between aliased effects.