Regulatory Institutional Distance and MNCs' Subsidiary Performance: Climbing up Vs. Climbing Down the Institutional Ladder

We investigate the possibility of regulatory institutional distance exerting an asymmetric effect on multinational corporations' (MNCs') subsidiary performance depending on the direction of institutional distance. We use the term ‘institutional ladder’ to differentiate between upward distance, referred to as when the subsidiary is operating in a relatively stronger institutional environment than its parent-firm's home country, and downward distance for vice versa. Combining institutional theory with organisational imprinting and learning perspectives, we argue that the implications of regulatory institutional distance on subsidiary performance are relatively more positive (or less negative) when MNCs are climbing down the institutional ladder as compared to when MNCs are climbing up the institutional ladder. We also argue that subsidiary ownership strategy – i.e. the choice of a wholly owned subsidiary (WOS) versus joint venture (JV) – moderates the above-mentioned implications of institutional distance on subsidiary performance. We test these hypotheses based on a panel data-set of 1936 foreign subsidiaries representing 70 host countries and 66 home countries and spanning the 12-year period: 2002–2013.     

A new look at clustering coefficients with generalization to weighted and multi-faction networks

In this paper we propose a new method for studying local and global clustering in networks employing random walk pairs. The method is intuitive and directly generalizes standard local and global clustering coefficients to weighted networks and networks containing nodes of multiple types. In the case of two-mode networks the values obtained for commonly considered social networks are in sharp contrast to those obtained, for instance, by the method of Opsahl (2013), and provide a different viewpoint for clustering. The approach is also applicable in questions related to the general study of segregation and homophily. Applications to existent data sets are considered.     

Leader-member exchange and organizational citizenship behaviors: Contextual effects of leader power distance and group task interdependence

In this paper we explore the context of the relationship between leader-member exchange and organizational citizenship behaviors (OCB). We maintain that workgroup leader's power distance and the extent of task interdependence in the group exert cross-level effects on the LMX-OCB relationship. We assert that leader power distance attenuates the relationship between LMX and OCB, and this effect is stronger in workgroups with high degree of task interdependence. Results of hierarchical linear modeling analysis of data gathered from 245 employees nested in 54 workgroups supported our hypotheses. LMX-OCB relationship was weaker in workgroups led by high power distance leaders. Further, the three-way cross-level interaction between LMX, leader power distance and group task interdependence demonstrated that the tendency for LMX to have a stronger positive effect on OCB when leader power distance was low rather than high was more pronounced in high task interdependence teams.     

The sociolinguistics of late modern publics

This issue examines struggles over public discursive power in late modern society, understanding that late modern publics are characterized by a destabilization of formerly unmarked public authorities, in other words, an unsettling of standardized “voices from nowhere” (Gal & Woolard, 2001). The contributions to the issue illustrate traditional social and academic elites’ discursive reactions to such developments. In the introduction, we outline different theoretical frameworks of modern and late‐modern publics, identify factors that contribute to a destabilization of modern certainties of social public order, and argue that a weakening of traditional public norms not only implies emancipation but also, as the contributions to the issue demonstrate, may bring along new forms of public dominance. For the positioning of contemporary sociolinguistic theory and practice, we conclude that it is the crucial task of the current public moment to critically self‐engage with our own relations with, and ideologies of, the public. Dieses Themenheft befragt Strukturen öffentlicher Diskursmacht in spätmoderner Gesellschaft und zeigt auf, dass spätmoderne Öffentlichkeit durch eine Destabilisierung von vormals unmarkierten Autoritäten ist, in anderen Worten, von standardisierten “voices from nowhere” (Gal & Woolard, 2001). Die Beiträge illustrieren Reaktionen traditioneller sozialer und akademischer Eliten hierauf. In dieser Einleitung skizzieren wir verschiedene theoretische Zugänge zu moderner und spätmoderner Öffentlichkeit, identifizieren Faktoren, die zu einer Destabilisierung von sozialen Gewissheiten der Moderne beitragen und legen dar, dass eine Schwächung traditioneller öffentlichen Normen nicht nur soziale Emanzipation impliziert sondern, wie die Beiträge zu diesem Heft zeigen, auch neue Formen öffentlicher Dominanz hervorbringt. In Bezug auf zeitgenössische soziolinguistische Theorie und Praxis schlussfolgern wir daraus, dass es im aktuellen öffentlichen Kontext eine zentrale Aufgabe der Soziolinguistik ist, sich kritisch mit den eigenen Beziehungen zu und Ideologien von Öffentlichkeit befassen. Das Themenheft soll zu dieser Auseinandersetzung beitragen.     

基于犹豫直觉模糊语言集均值-标准差偏好距离的多属性决策研究

在犹豫直觉模糊语言集和语言尺度函数的基础上定义了均值-标准差偏好的Hamming距离，并提出了基于犹豫直觉模糊语言集距离TOPSIS和TODIM的多属性决策方法，进一步利用这两种方法对实例问题建筑商的招标方案进行排序，并讨论了偏好参数对排序结果的灵敏度分析。为验证上述方法的有效性，与已有方法对同一实例的排序结果进行了比较分析。     

基于Mo-RVIKOR的混合多属性决策方法

针对复杂性和不确定性多属性决策问题，考虑定量和定性融合的属性形式，提出了模块化随机多准则妥协解排序法（Modular Random VlseKriterijumska Opti-mizacija I Kompromisno Resenje，Mo-RVIKOR），该方法无需将信息统一，就能处理多种信息形式存在的多属性决策问题。采用精确数、随机变量处理定量评价信息，用概率语义术语集处理定性评价信息；通过改进离差最大化法确定属性权重；根据Mo-RVIKOR对决策对象进行排序；最后以某公司C2B定制化服务质量评测项目为例，验证了所提方法的有效性。     

基于混合加权距离的毕达哥拉斯模糊TOPSIS多属性决策方法研究

针对决策信息为毕达哥拉斯模糊集的多属性决策问题，提出了一种基于混合加权测度的TOPSIS决策方法。在分析了现有距离测度方法不足的基础上，首先给出了一种新的毕达哥拉斯模糊距离测度——毕达哥拉斯模糊有序加权距离（PFOWD），并研究了该测度权重的确定方法；在PFOWD基础上，进一步提出了毕达哥拉斯模糊混合加权距离（PFHWD），同时探讨了其特征和与现有毕达哥拉斯模糊测度的关系；最后提出了一种基于PFHWD测度的毕达哥拉斯模糊TOPSIS多属性方法，并用实例验证了方法的有效性和可行性。     

Compensation or competition: Bias in immigrants' access to active labour market measures

Whether participation in active labour market programmes (ALMPs) pushes individuals back into employment depends on the programme's characteristics. On the basis of encompassing registry data that allow us to control for usually unobserved employability, we find evidence of a systematic access bias whereby jobcentre caseworkers in Switzerland assign unemployed persons to activation measures based on a competition logic that is mainly driven by an economic rationale and the jobcentre's performance evaluation. This practice seems problematic because it results in an overrepresentation of immigrants in measures with little efficacy rather than in measures that could compensate for employability disadvantages. Conversely, Swiss citizens are more likely to enter beneficial human-capital-intensive measures. It is plausible that this discrepancy in programme participation amplifies the general labour market disadvantages of immigrants.     

Comparing Possibly Misspecified Forecasts

Abstract

Recent work has emphasized the importance of evaluating estimates of a statistical functional (such as a conditional mean, quantile, or distribution) using a loss function that is consistent for the functional of interest, of which there is an infinite number. If forecasters all use correctly specified models free from estimation error, and if the information sets of competing forecasters are nested, then the ranking induced by a single consistent loss function is sufficient for the ranking by any consistent loss function. This article shows, via analytical results and realistic simulation-based analyses, that the presence of misspecified models, parameter estimation error, or nonnested information sets, leads generally to sensitivity to the choice of (consistent) loss function. Thus, rather than merely specifying the target functional, which narrows the set of relevant loss functions only to the class of loss functions consistent for that functional, forecast consumers or survey designers should specify the single specific loss function that will be used to evaluate forecasts. An application to survey forecasts of U.S. inflation illustrates the results.     

基于交叉效率DEA与群体共识的区间乘性语言偏好关系群决策

针对区间乘性语言偏好关系群决策问题，提出了一种基于交叉效率DEA和群体共识的群决策方法。首先，提出乘性语言偏好关系导出函数的定义，并构建产出导向的DEA模型，证明了一致性乘性语言偏好关系的DEA效率得分与排序向量之间存在比例关系。在此基础上，建立基于理想值的交叉效率DEA模型，提出乘性语言偏好关系的通用排序方法。同时，基于群体共识建立目标规划模型来计算各语言偏好关系的权重系数。最后，利用Monte Carlo随机模拟的方法对群体语言偏好空间进行统计分析，得到群决策期望排序向量及其可信度。算例分析表明本文方法能够有效的避免信息损失，具有较强的适用性和较高的可信度。