一种对等网络P2P信任模型研究

P2P和传统的模式相比较,P2P显得更加灵活、快捷、方便。针对P2P对等网络模型存在不足进行了改进,网络规模不断扩大,复杂性不断增加,利用信任模型的计算,对文件共享、仿真实验证明,信任模型具有很好的可信任性和有效性,该模型对恶意节点具有很好的隔离作用,降低了风险。     

互联网虚假信息研究概述

由于互联网的普遍性、匿名性以及竞争的激烈性,越来越多的网络用户通过虚假信息以混淆视听、恶意诋毁竞争对手和蓄意扰乱社会秩序。本文通过论述互联网虚假信息的研究现状,结合相关研究理论和方法,探索互联网虚假信息的研究方向。     

A network approach to work-family conflict

Most human behaviours, including those instrumental for reducing Work–Family Conflict (WFC), take place in the context of social relationships. However, the role of social networks in an individual's WFC goal pursuit process has not received sufficient attention, as most current research is dominated by an agentic perspective that argues that individuals possess the capabilities to change the demands and resources associated with their roles freely. We believe that the reality faced by many workers is more composite, as the various work and family stakeholders present in an individual's network can create significant constraints and opportunities that are capable of inhibiting or enhancing their agency. In this paper, we aim to examine how the ecosystem of network relationships in an individual’ social network can influence his or her overall capability to minimise WFC. Building on insights from dynamic network theory, a recently introduced framework in the social network literature, we propose a conceptual model that explains the specific roles that work and family stakeholders (i.e., supporters, preventers, resistors, reactors, negators, interactants, or observers) can assume with respect to goal strivers' attempts to manage WFC. Building on prior work-family and social network research, we illustrate how two characteristics of the network in which an individual is embedded (i.e., centrality and density) can shape the magnitude of social network influence on WFC. Implications for theory and practice are also discussed.     

Identification of peer effects through social networks

We provide new results regarding the identification of peer effects. We consider an extended version of the linear-in-means model where interactions are structured through a social network. We assume that correlated unobservables are either absent, or treated as network fixed effects. We provide easy-to-check necessary and sufficient conditions for identification. We show that endogenous and exogenous effects are generally identified under network interaction, although identification may fail for some particular structures. We use data from the Add Health survey to provide an empirical application of our results on the consumption of recreational services (e.g., participation in artistic, sports and social activities) by secondary school students. Monte Carlo simulations calibrated on this application provide an analysis of the effects of some crucial characteristics of a network (i.e., density, intransitivity) on the estimates of peer effects. Our approach generalizes a number of previous results due to Manski [Manski, C., 1993. Identification of endogenous social effects: The reflection problem. Review of Economic Studies 60 (3), 531–542], Moffitt [Moffitt, R., 2001. Policy interventions low-level equilibria, and social interactions. In: Durlauf, Steven, Young, Peyton (Eds.), Social Dynamics. MIT Press] and Lee [Lee, L.F., 2007. Identification and estimation of econometric models with group interactions, contextual factors and fixed effects. Journal of Econometrics 140 (2), 333–374].     

The motifs of risk transmission in multivariate time series: Application to commodity prices

In this article we propose to exploit topological information embedded in forecast error variance decomposition derived from large Bayesian vector autoregressive models (VAR) to study network connectedness and risk transmission of multivariate time series observations. Firstly, we design a robust link classification procedure based on shortest paths, so to identify salient directional spillovers in a high-dimensional framework. Secondly, we study recurrent and statistically significant sub-graphs, i.e. network motifs, on the induced network backbone by means of null models which account for local node heterogeneity. The methodology is applied to analyze spillover networks of a set of global commodity prices. We demonstrate that spillovers become key drivers of the system variance during commodity price bubbles and bursts, giving raise to complex triadic structures which do not manifest during normal business periods. By accounting for local node connectivity, we observe a departure from the null models due to the high participation of Crude Oil, Food and Beverages and Raw Materials in complex recurrent sub-graphs.     

Understanding information propagation on online social tagging systems: a case study on Flickr

Online social networking services (SNS) have been regarded as one of the most powerful online communication channels to propagate information to other users. It means that the online social networking services are providing users with efficient features (e.g., searching, managing and visualizing new information). It is important for many online collaborative applications to understand how the information can be propagated via such social media. Thus, we want to focus on a social tagging system (e.g., Flickr) where users can easily exchange resources as well as their tags. In this paper, given a certain tag, a social pulse can be established by counting (i) the number of users and (ii) the number of resources over time. More importantly, we assume that information can be propagated by (iii) inducibility from other tags by comparing social pulses. To conduct experimentation, a tag-based searching system (called Tagoole) has been implemented to collect a dataset from Flickr.     

The role of buyers justice in achieving socially sustainable global supply chains: A perspective of apparel suppliers and their workers

The absence of an effective public model (e.g., government regulations and law enforcement) in developing countries has driven clothing brands and retailers to rely on a private voluntary formal model (e.g., compliance and collaboration approaches) to manage suppliers' internal social issues (e.g., poor working conditions). However, this model has been recently criticised for falling short in addressing these issues as it overlooks their main root causes. In this study, we suggest that suppliers' internal social issues can be driven by buyers' unfair practices, and therefore, we propose and examine that buyers' justice can ensure suppliers' internal social performance. We further postulate and investigate that addressing these issues would result in advantages for buyers beyond traditional performance outcomes in the form of reduced supply operational risk. Based on a census of the 117 suppliers comprising the ready-made garment industry in a Middle Eastern country (Jordan), we received survey responses from 97 suppliers and their shop floor workers. The analysis revealed that only buyer’s distributive and procedural justice, but not interactional justice, are positively related to suppliers' internal social performance. We also found evidence that improving suppliers' internal social performance can diminish supply operational risk. This study contributes to the extant research by empirically investigating a new approach to handle the increase in suppliers' internal social issues in a developing country context. It also does by capturing suppliers' internal social performance from the workers' perspective and highlighting the role of improved suppliers' internal social performance on mitigating supply operational risk.     

Understanding information exchange in healthcare operations: Evidence from hospitals and patients

Coordination – or the information exchange among physicians and hospital staff – is necessary for desirable patient outcomes in healthcare delivery. However, coordination is difficult because healthcare delivery processes are information intensive, complex and require interactions of hospitals with autonomous physicians working in multiple operational systems (i.e. multiple hospitals). We examine how three important variables distinctive of the healthcare operations context – use of IT for dissemination of test results (ITDR) (i.e. electronic health records systems) by physicians and hospital staff, social interaction ties among them, and physician employment – influence information exchange and patient perceptions of their care. Drawing from the literature on process inter-dependencies and coordination, vertical integration and social exchange, we develop and test research hypotheses linking ITDR, social interaction ties and physician employment to information exchange relationship, and information exchange relationship to provider–patient communication. Using a paired sample of primary survey data and secondary archival data from CMS HCAHPS for 173 hospitals in the USA, we find that increased information exchange relationship drives provider–patient communication, and increased social interaction ties drives information exchange relationship. Social interaction ties fully mediates the relationship between ITDR and information exchange relationship. Physician employment amplifies the link between ITDR and social interaction ties, but does not have an effect on the link between ITDR and information exchange. We do not find a direct relationship between ITDR, and information exchange relationship or provider–patient communication.     

Contagion of network products in small-world networks

We formulate a model in which agents embedded in an exogenous social network decide whether to adopt a new network product or not. In the theoretical part of the paper, we characterize the stochastically stable equilibria for complete networks and cycles. For an arbitrary network structure, we develop a novel graph decomposition method to characterize the set of recurrent communication states, which is a superset of stochastically stable equilibria of the adoption game presented in our model. In the simulation part, we study the contagion process of a network product in small-world networks that systematically represent social networks. We simulate a generalization of the Morris (Rev Econ Stud 67(1):57–78, 2000) Contagion model that can explain the chasm between early adopters and early majority. Our numerical analysis shows that the failure of a new network product is less likely in a highly cliquish network. In addition, the contagion process reaches to steady state faster in random networks than in highly cliquish networks. It turns out that marketers should work with mixed marketing strategies, which will result in a full contagion of a network product and faster contagion rates with a higher probability.

     

Water disclosure and firm risk: Empirical evidence from highly water‐sensitive industries in China

In this paper, we examine the relationship between water disclosure and firm risk. Specifically, based upon a panel dataset of 334 Chinese listed firms operating in highly water‐sensitive industries during 2010–2015, we use regression models to analyze the relationships between water disclosure and three types of firm risk (i.e., total risk, systematic risk, and idiosyncratic risk) and the moderating effects of media coverage on these relationships. Our empirical results show that (a) although there are no significant relationships between water disclosure and total risk and idiosyncratic risk, there is a significant negative relationship between water disclosure and systematic risk; (b) negative media coverage weakens the negative relationship between water disclosure and systematic risk, whereas nonnegative media coverage reinforces this negative relationship. Our cornerstone study examines the effect of a specific type of environmental disclosure (i.e., water disclosure) on firm risk, and our empirical findings are different from previous studies, which examined the effects of overall corporate social responsibility (CSR) disclosure on firm risk. We analyze the causes of the differences in detail. With this study, we make theoretical, empirical, and managerial contributions to CSR disclosure–firm risk research in business ethics literature.     

Incentivizing resilience in financial networks

When banks extend loans to each other, they generate a negative externality in the form of systemic risk. They create a network of interbank exposures by which they expose other banks to potential insolvency cascades. In this paper, we show how a regulator can use information about the financial network to devise a transaction-specific tax based on a network centrality measure that captures systemic importance. Since different transactions have different impact on creating systemic risk, they are taxed differently. We call this tax a systemic risk tax (SRT). We use an equilibrium concept inspired by the matching markets literature to show analytically that this SRT induces a unique equilibrium matching of lenders and borrowers that is systemic-risk efficient, i.e. it minimizes systemic risk given a certain transaction volume. On the other hand, we show that without this SRT multiple equilibrium matchings exist, which are generally inefficient. This allows the regulator to effectively stimulate a ‘rewiring’ of the equilibrium interbank network so as to make it more resilient to insolvency cascades, without sacrificing transaction volume. Moreover, we show that a standard financial transaction tax (e.g. a Tobin-like tax) has no impact on reshaping the equilibrium financial network because it taxes all transactions indiscriminately. A Tobin-like tax is indeed shown to have a limited effect on reducing systemic risk while it decreases transaction volume.     

The method of leader's overthrow in networks based on Shapley value

Quantitative methods for leaders' detection and overthrow are useful tools for decision-making in many real-life social networks. In the given research, we present algorithms that detect and overthrow the most influential node to the weaker leadership positions following the greedy method in terms of structural modifications. We employ the concept of Shapley value from the area of cooperative game theory to measure a node's leadership and to develop the leader's overthrow algorithms. Specifically, we introduce a quantitative approach to analyze prospective structural modifications in social networks to make the initially identified network leader less influential. The resulting mechanism is based on the symbiosis of game-theoretic and algorithmic concepts. It presents a useful tool for the technical analysis of the primary structural data in the initial steps of multifaceted quantitative network analysis where the raw data (i.e., linkages) is frequently the only knowledge about interrelations in social networks.     

Cross-industry asset allocation with the spatial interaction on multiple risk transmission channels

Taking into consideration the real link and information risk transmission channels, we used a spatial econometric approach to construct an economic distance-based spatial weight matrix, which can capture the spatial interaction across industries, and built a return estimation model with spatial interaction using the matrix. On this basis, we derived the covariance matrix and constructed the cross-industry asset allocation model. The empirical results showed that 1) the spatial interaction has a strong explanatory power to return and integrating the spatial interaction on multiple risk transmission channels can improve the effectiveness of the return estimation model; 2) the covariance matrix includes unsystematic risk (idiosyncratic risk) and systematic risk (market risk and cross-industry spillover risk); 3) the asset allocation model with spatial interaction can improve the performance of the portfolio and provide a valuable reference for investors' risk management and investment decision.     

About and beyond leading uniqueness and belongingness: A systematic review of inclusive leadership research

The purpose of this systematic review of 107 papers is to address the conceptual confusion about what inclusive leadership (IL) behavior entails and understand the theoretical development of IL. Synthesizing the divergent conceptualizations of inclusive leader behaviors, we propose a multi-level (i.e., employee, team, organizational) model of IL behavior consisting of four dimensions namely, fostering employee's uniqueness (e.g., promoting diversity); strengthening belongingness within a team (e.g., building relationships); showing appreciation (e.g., recognizing efforts and contributions); and supporting organizational efforts (e.g., promoting organizational mission on inclusion). Further, we provide a summary of studied variables as a nomological network in relation to inclusive leadership and an overview of the different theories (e.g., social exchange, intrinsic motivation) supporting the respective relationships and explaining the underlying mechanisms (e.g., reciprocity, motivation). We propose future research to empirically test the multi-level model of IL and examine the predictive value in terms of employee and organizational outcomes.     

Method towards discovering potential opportunity information during cross-organisational business processes using role identification analysis within complex social network

ABSTRACT

The key to discover potential opportunity information in cross-organisation business processes (COBPs) is to identify the primary roles and actors, i.e. how to obtain their associations according to the interactive behaviours within the complex social networks. The information of roles in COBPs is commonly considered important and explicitly related with activities contained in COBPs. In this paper, we define a role as a configurable resource model integrating the capabilities and knowledge required to the qualified actors. Furthermore, we introduce two networks named as role-based interactive behaviour network and handover of work social network to investigate the information on roles. How to build the complex social network mapped on roles from COBPs is also discussed, and an approach to obtain the potential opportunity information is proposed by combining with the significance of roles and actors. The simulation result shows that the primary roles may not completely correspond to the central position in networks, but they are closely associated with more reliable actors.     

Bowling alone but tweeting together: the evolution of human interaction in the social networking era

The objective of this paper is to theoretically analyze how human interaction may evolve in a world characterized by the explosion of online networking and other Web-mediated ways of building and nurturing relationships. The analysis shows that online networking yields a storage mechanism through which any individual contribution—e.g. a blog post, a comment, or a photo—is stored within a particular network and ready for virtual access by each member who connects to the network. When someone provides feedback, for example by commenting on a note, or by replying to a message, the interaction is finalized. These interactions are asynchronous, i.e. they allow individuals to relate in different moments, whenever they have time to. When the social environment is poor of participation opportunities and/or the pressure on time increases (for example due to the need to increase the working time), the stock of information and ties stored in the Internet can help individuals to defend their sociability.     

The uncertainty in extreme risk forecasts from covariate-augmented volatility models

For a GARCH-type volatility model with covariates, we derive asymptotically valid forecast intervals for risk measures, such as the Value-at-Risk or Expected Shortfall. To forecast these, we use estimators from extreme value theory. In the volatility model, we allow for leverage effects and the inclusion of exogenous variables, e.g., volatility indices or high-frequency volatility measures. In simulations, we find coverage of the forecast intervals to be adequate for sufficiently extreme risk levels and sufficiently large samples, which is consistent with theory. Finally, we investigate if covariate information from volatility indices or high-frequency data improves risk forecasts for major US stock indices. While—in our framework—volatility indices appear to be helpful in this regard, intra-day data are not.     

The Role of Information and Influence in Social Networks

A bstract .   This article examines two mechanisms through which social networks are related to job mobility: (1) access to diverse sources of information about job openings and (2) nonredundant sources of influence. Using data on job changing and social networks among television station managers, we assess the extent to which job information and influence variables mediate the relationship between social network structure and getting a better job. Results indicate that there is an association between job mobility and having nonredundant contacts, but our measures of the information and influence mechanisms are not significant mediators. We conclude by reexamining the network-resource model that forms the basis for much of the research on the relationship between social networks and job mobility.     

Forecasting short-term defaults of firms in a commercial network via Bayesian spatial and spatio-temporal methods

To protect financial institutions from unexpected credit losses, during the monitoring phase of granted loans it is of primary importance to foresee any evidence of a contagion of liquidity distress across a network of firms. This term indicates a situation of lack of solvency of a firm (e.g., a customer) that propagates to other firms (e.g, its suppliers), which could consequently face challenges in repaying their own granted loans. In this paper, we look for the evidence of contagion of liquidity distress on an Intesa Sanpaolo proprietary dataset by means of Bayesian spatial and spatio-temporal models. Our results indicate that such models can detect cases of distress not yet apparent from covariate information collected on the firms by instead borrowing information from the network, leading to improved forecasting performance on the prediction of short-term default with respect to state-of-the-art methods.