可持续供应链管理实践对企业绩效的影响:基于中国的实证研究

本文基于我国172家企业的问卷调查数据,运用结构方程模型,对企业可持续供应链管理实践及其对绩效的影响进行实证分析。结果表明,企业实现内部可持续管理能够对企业管理供应商的行为有着显著的影响;同时,企业管理供应商的行为作为企业外部管理实践对企业的绩效有着显著的正向影响;在企业绩效中,环境绩效和社会绩效对经济绩效有着显著的正向影响,企业的外部管理实践能够通过环境绩效和社会绩效的提高实现最终经济绩效的明显增加。     

The cultural Red King effect

Why do minority groups tend to be discriminated against when it comes to situations of bargaining and resource division? In this article, I explore an explanation for this disadvantage that appeals solely to the dynamics of social interaction between minority and majority groups—the cultural Red King effect (Bruner, 2017). As I show, in agent-based models of bargaining between groups, the minority group will tend to get less as a direct result of the fact that they frequently interact with majority group members, while majority group members meet them only rarely. This effect is strengthened by certain psychological phenomenon—risk aversion and in-group preference—is robust on network models, and is strengthened in cases where preexisting norms are discriminatory. I will also discuss how this effect unifies previous results on the impacts of institutional memory on bargaining between groups.     

Forecasting the integration of immigrants

In this research, we develop and introduce a theoretical and mathematical forecasting framework of immigrant integration using immigrant density as a single driver. First, we introduce the integration concepts we aim at forecasting. Thereafter, we introduce a theoretical and mathematical model of the relationship between integration and immigrant density. Based on this model, we develop a methodological forecasting framework. We test the framework using immigrant integration data from Spain. We produce the forecasts, and conduct the proper evaluation of them. Finally, we conclude with a brief discussion of the wider implications of our results.     

Compressing strongly connected subgroups in social networks: An entropy-based approach

To detect and study cohesive subgroups of actors is a main objective in social network analysis. What are the respective relations inside such groups and what separates them from the outside. Entropy-based analysis of network structures is an up-and-coming approach. It turns out to be a powerful instrument to detect certain forms of cohesive subgroups and to compress them to superactors without loss of information about their embeddedness in the net: Compressing strongly connected subgroups leaves the whole net’s and the (super-)actors’ information theoretical indices unchanged; i.e., such compression is information-invariant. The actual article relates on the reduction of networks with hundreds of actors. All entropy-based calculations are realized in an expert system shell.     

A Bayesian record linkage model incorporating relational data

In this article, we introduce a novel Bayesian approach for linking multiple social networks in order to discover the same real world person having different accounts across networks. In particular, we develop a latent model that allows us to jointly characterize the network and linkage structures relying on both relational and profile data. In contrast to other existing approaches in the machine learning literature, our Bayesian implementation naturally provides uncertainty quantification via posterior probabilities for the linkage structure itself or any function of it. Our findings clearly suggest that our methodology can produce accurate point estimates of the linkage structure even in the absence of profile information, and also, in an identity resolution setting, our results confirm that including relational data into the matching process improves the linkage accuracy. We illustrate our methodology using real data from popular social networks such as Twitter , Facebook , and YouTube .     

复杂网络上的意见动力学对谣言传播的影响

通过在SIR(susceptible-infected-recovered)模型中引入抑制者对谣言的辟谣机制研究了在线社交网络上的意见动力学对谣言传播的影响.在这一模型中,节点可以与自身的邻居组成1个群,传播者可以通过该群传播信息,抑制者也可以在此群中对信息发表意见进行辟谣.辟谣机制在降低未知者对于谣言的接受概率的同时也可以促使传播者向抑制者转变.本文采用ER(Erd?s-Rényi)随机网络、无标度网络以及真实的社交网络研究了抑制者的沉默概率对于谣言传播范围的影响.首先发现,谣言传播的过程以传播者的峰值为界可以分为两个阶段,即谣言自由传播的前期以及抑制者和传播者互相制衡的后期;其次,谣言的传播会随着抑制者的沉默概率的增大而突然暴发.在谣言暴发阈值之下,沉默概率的增大不会导致谣言传播范围显著增大,这是由于未知者在感知到谣言并转变为传播者后又迅速转变为抑制者;而当沉默概率达到谣言暴发阈值时,抑制者将不能控制传播者对谣言的传播从而导致抑制者的降低和谣言的暴发;最后,无标度上的谣言自由传播的前期阶段比随机网络持续的时间更短,从而使无标度上的谣言更难以暴发.本文的模型综合考虑了意见动力学和谣言传播的相互作用,更加真实地模拟了真实世界社交网络中的谣言传播过程.为谣言传播的控制和干预提供了一些有用的思路和见解.     

政府奖励对报废汽车回收模式选择的作用机制研究——基于企业社会责任视角

随着我国报废汽车数量的增多,由其造成的交通隐患、环境污染和资源浪费已成为重要社会问题,而如何设计合理可行的回收模式成为解决问题的关键。以制造商主导为前提,提出了基于企业社会责任的报废汽车回收模型,构建了制造商回收、销售商回收和第三方回收模式下的回收流程和数学模型,通过实例对考虑和不考虑企业社会责任两种情况下的回收模型进行了分析,探讨了不同政府奖励下报废汽车回收模式的策略选择。通过研究发现:(1)不论是否考虑企业社会责任,随着政府奖励的增加,制造商最终都会选择由自己进行回收;(2)当考虑企业社会责任时,政府奖励和决策者经济责任偏好都会导致决策的改变,随着政府奖励和赋予经济责任权重的同步增加,制造商的决策由第三方企业回收模式或销售商回收模式变成了制造商回收模式,表明政府奖励和企业社会责任对报废汽车回收模式选择具有显著影响。     

基于FDI收益分成视角的FTA网络演化

本文假定双边自由贸易协定(bilateral free trade agreement,简称FTA)包含着无限制对外直接投资(foreign direct investment,简称FDI),并且通过FDI销售到非FTA伙伴国的收益按照一定比例在母国和东道国之间进行分配。基于Goyal和Joshi^[1],本文构建了FTA网络形成博弈模型。本文发现,FTA网络演化过程分为两个阶段:第一阶段,从空FTA网络到星状FTA网络,存在一条路径使得个体国家福利、世界总福利均改善,在此过程中,国家福利存在不对称性;第二阶段,从星状FTA网络到全连接FTA网络,存在一条路径使得个体国家福利改善,在此过程中,世界总福利不变,国家福利不对称性逐步消除。     

Approximations for interactive Markov chains in discrete and continuous time

A class of models called interactive Markov chains is studied in both discrete and continuous time. These models were introduced by Conlisk and serve as a rich class for sociological modeling, because they allow for interactions among individuals. In discrete time, it is proved that the Markovian processes converge to a deterministic process almost surely as the population size becomes infinite. More importantly, the normalized process is shown to be asymptotically normal with specified mean vector and covariance matrix. In continuous time, the chain is shown to converge weakly to a diffusion process with specified drift and scale terms. The distributional results will allow for the construction of a likelihood function from interactive Markov chain data, so these results will be important for questions of statistical inference. An example from manpower planning is given which indicates the use of this theory in constructing and evaluating control policies for certain social systems.     

Projecting average family size in rural India by the analytic hierarchy process

In this study, cultural, economic as well as certain crucial demographic factors are considered as the determinants for projecting the average family size in rural India. We use the Analytic Hierarchy Process to analyze influences of the factors which enter implicitly in a rural couple's decision‐making to determine the number of children they want to have as time goes by. We did not attempt to make distinctions among the regional differences in rural India. The outcome projected in our analysis compares favorably with the results of other demographic studies.