Social (Dis)Approval and Collective Action Participation: Re‐evaluating the Positive Linearity Thesis

Survey‐based studies on collective action generally assume that social approval of participation in collective action has a positive and linear effect on actual participation. However, this assumption has not yet been subjected to a genuine empirical evaluation. This article investigates the positive linearity thesis, using survey data on participation and non‐participation in a street demonstration in The Hague in 2011. Statistical analyses provide evidence in support of a curvilinear relation between social approval and participation—an increased rate of participation in case of both approval and disapproval by peers. We discuss two processes underlying the observed relation: one pertaining to rebelliousness and the other regarding political awareness. The article generally illustrates the need for further empirical research on social influence and participation in collective action.     

Never easy to say “sorry”: Exploring the interplay of crisis involvement,brand image,and message appeal in developing effective corporate apologies

This study examines how the interplay among crisis involvement, brand image, and message appeal impacts the effectiveness of an apology in the context of a corporate crisis. To determine apology effectiveness, a 2 (crisis involvement: high vs. low) × 2 (brand image: symbolic vs. functional) × 2 (message appeal type: emotional vs. informational) experimental design was employed. The results demonstrate that the three-way interaction is significant, especially in the low-crisis involvement condition. The study concludes with a discussion of theoretical and practical implications and directions for future research.     

Introduction to the Special Section Value Development from Middle Childhood to Early Adulthood—New Insights from Longitudinal and Genetically Informed Research

Research into values at an early age has only started recently, although it has expanded quickly and dynamically in the past years. The purpose of this article is twofold: First, it provides an introduction to a special section that aims to help fill the gap in value development research. The special section brings together four new longitudinal and genetically informed studies of value development from the beginning of middle childhood through early adulthood. Second, this article reviews recent research from this special section and beyond, aiming to provide new directions to the field. With new methods for assessing children's values and an increased awareness of the role of values in children's and adolescents' development, the field now seems ripe for an in‐depth investigation. Our review of empirical evidence shows that, as is the case with adults, children's values are organized based on compatibilities and conflicts in their underlying motivations. Values show some consistency across situations, as well as stability across time. This longitudinal stability tends to increase with age, although mean changes are also observed. These patterns of change seem to be compatible with Schwartz's (1992) theory of values (e.g., if the importance of openness to change values increases, the importance of conservation values decreases). The contributions of culture, family, peers, significant life events, and individual characteristics to values are discussed, as well as the development of values as guides for behavior.     

Time‐Space Distanciation: An Interdisciplinary Account of How Culture Shapes the Implicit and Explicit Psychology of Time and Space

The growing body of research on temporal and spatial experience lacks a comprehensive theoretical approach. Drawing on Giddens’ framework, we present time‐space distanciation (TSD) as a construct for theorizing the relations between culture, time, and space. TSD in a culture may be understood as the extent to which (1) time and space are abstracted as separate dimensions and (2) activities are extended and organized across time and space. After providing a historical account of its development, we outline a multi‐level conceptualization of TSD supported by research on cultural differences in the experience of time and space. We impact this conceptualization by examining two ethnographic case studies. We conclude by highlighting future research directions. TSD is an integrative, interdisciplinary, multi level construct with the potential to guide the burgeoning social science of time and space.     

Marginal zero-inflated regression models for count data

Data sets with excess zeroes are frequently analyzed in many disciplines. A common framework used to analyze such data is the zero-inflated (ZI) regression model. It mixes a degenerate distribution with point mass at zero with a non-degenerate distribution. The estimates from ZI models quantify the effects of covariates on the means of latent random variables, which are often not the quantities of primary interest. Recently, marginal zero-inflated Poisson (MZIP; Long et al. [A marginalized zero-inflated Poisson regression model with overall exposure effects. Stat. Med. 33 (2014), pp. 5151–5165]) and negative binomial (MZINB; Preisser et al., 2016) models have been introduced that model the mean response directly. These models yield covariate effects that have simple interpretations that are, for many applications, more appealing than those available from ZI regression. This paper outlines a general framework for marginal zero-inflated models where the latent distribution is a member of the exponential dispersion family, focusing on common distributions for count data. In particular, our discussion includes the marginal zero-inflated binomial (MZIB) model, which has not been discussed previously. The details of maximum likelihood estimation via the EM algorithm are presented and the properties of the estimators as well as Wald and likelihood ratio-based inference are examined via simulation. Two examples presented illustrate the advantages of MZIP, MZINB, and MZIB models for practical data analysis.     

Evaluating the causal economic impacts of transport investments: evidence from the Madrid–Barcelona high speed rail corridor

This paper evaluates economic impacts arising from the introduction of high-speed rail (HSR) between Madrid and Barcelona. Using difference-in-differences estimation we estimate an average treatment effect for provinces with stops on the HSR line of 2.4% for economic output, 3.3% for numbers of firms, and 1.1% for labour productivity. We complement our DID results with a synthetic control analysis for Lleida and Tarragona, two provinces that we argue were assigned HSR stations largely due to their incidental location. We find that both the number of firms and labour productivity are substantially higher in these provinces than in their synthetic counterparts.     

The elites’ collective subjectivities of the history of ethnic politics in Malaysia

ABSTRACT

Malaysia is one of the multi-ethnic, multi-cultural and multi-religious countries in Southeast Asia. Due to the pluralistic nature of Malaysia, it has a political structure based on ethnic politics. The ethnic preferential policies affected most domains of this country. The objective of this article is to examine the origin and background of ethnic politics in Malaysia. Findings of this study indicate that, ethnic politics originated during the British colonial period, it became a tool used by the Barisan Nasional for the legitimacy of regime. Moreover, ethnic politics in Malaysia today is intertwined with religion. Besides, there is the dilemma of the choice between the interest of certain ethnic group and national interests. However, with the opposition coalition Pakatan Harapan won the election in 9th May, UMNO-led BN lost power and interrupted its 61 years control, which leaves us an interesting topic to think about the future of Malaysian ethnic politics.     

Reversible jump Markov chain Monte Carlo algorithms for Bayesian variable selection in logistic mixed models

In this article, to reduce computational load in performing Bayesian variable selection, we used a variant of reversible jump Markov chain Monte Carlo methods, and the Holmes and Held (HH) algorithm, to sample model index variables in logistic mixed models involving a large number of explanatory variables. Furthermore, we proposed a simple proposal distribution for model index variables, and used a simulation study and real example to compare the performance of the HH algorithm with our proposed and existing proposal distributions. The results show that the HH algorithm with our proposed proposal distribution is a computationally efficient and reliable selection method.     

Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.