Muslims’ social inclusion and exclusion in France,Québec,and Canada: does national context matter?*

This article compares the social experiences of Muslim minorities in three contexts – France, Québec, and English Canada – each reflecting a different approach to immigrant integration. France’s republican model emphasises cultural assimilation and the exclusion of religion from the public sphere; Canada’s multicultural model advocates official recognition of minority cultures; Québec shares Canada’s tradition of large-scale permanent immigration but embodies a unique intercultural discourse of integration, in some ways resembling France. We compare the social experiences of Muslim and non-Muslim minorities in these three settings using the French ‘Trajectories and Origins’ survey (2009) and the Canadian ‘Ethnic Diversity Survey’ (2002) data on reports of discrimination, friendship networks, social trust, voluntarism, and national identity. We find the Muslim/non-Muslim gap in social inclusion is significant in all three settings and results from ethnic, cultural, or racial differences, more than religion. In assessing immigrants’ social inclusion, we suggest consideration be given to: (i) the reality of ‘national models’ in the community, (ii) a tendency for minorities to locate in more accepting segments of mainstream society, and (iii) the limited impact of policies based on national models.     

A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding

Floods are a natural hazard evolving in space and time according to meteorological and river basin dynamics, so that a single flood event can affect different regions over the event duration. This physical mechanism introduces spatio‐temporal relationships between flood records and losses at different locations over a given time window that should be taken into account for an effective assessment of the collective flood risk. However, since extreme floods are rare events, the limited number of historical records usually prevents a reliable frequency analysis. To overcome this limit, we move from the analysis of extreme events to the modeling of continuous stream flow records preserving spatio‐temporal correlation structures of the entire process, and making a more efficient use of the information provided by continuous flow records. The approach is based on the dynamic copula framework, which allows for splitting the modeling of spatio‐temporal properties by coupling suitable time series models accounting for temporal dynamics, and multivariate distributions describing spatial dependence. The model is applied to 490 stream flow sequences recorded across 10 of the largest river basins in central and eastern Europe (Danube, Rhine, Elbe, Oder, Waser, Meuse, Rhone, Seine, Loire, and Garonne). Using available proxy data to quantify local flood exposure and vulnerability, we show that the temporal dependence exerts a key role in reproducing interannual persistence, and thus magnitude and frequency of annual proxy flood losses aggregated at a basin‐wide scale, while copulas allow the preservation of the spatial dependence of losses at weekly and annual time scales.     

A reference activity model for smart factory design and improvement

Smart manufacturing systems (SMSs) are envisioned to contain highly automated and IT-driven production systems. To address the complexity that arises in such systems, a standard and holistic model for describing its activities and their interrelationships is needed. This paper introduces a factory design and improvement (FDI) activity model and illustrates a case study of FDI in an electromechanical component factory. In essence, FDI is a reference activity model that encompasses a range of manufacturing system activities for designing and improving a factory during its initial development and also its operational phases. The FDI model shows not only the dependency between activities and manufacturing control levels but also the pieces of information and software functions each activity relies on. We envision that the availability of these pieces of information in digital form to integrate across the software functions will increase the agility of factory design and improvement projects. Therefore, our future work lies in contributing to standards for exchanging such information.     

Data-driven operations management: organisational implications of the digital transformation in industrial practice

Abstract

The ongoing digital transformation on industry has so far mostly been studied from the perspective of cyber-physical systems solutions as drivers of change. In this paper, we turn the focus to the changes in data management resulting from the introduction of new digital technologies in industry. So far, data processing activities in operations management have usually been organised according to the existing business structures inside and in-between companies. With increasing importance of Big Data in the context of the digital transformation, the opposite will be the case: business structures will evolve based on the potential to develop value streams offered on the basis of new data processing solutions. Based on a review of the extant literature, we identify the general different fields of action for operations management related to data processing. In particular, we explore the impact of Big Data on industrial operations and its organisational implications.     

An integrative model of leadership behavior

Decades of questionnaire and interview studies have revealed various leadership behaviors observed in successful leaders. However, little is known about the actual behaviors that cause those observations. Given that lay observers are prone to cognitive biases, such as the halo effect, the validity of theories that are exclusively based on observed behaviors is questionable. We thus follow the call of leading scientists in the field and derive a parsimonious model of leadership behavior that is informed by established psychological theories. Building on the taxonomy of Yukl (2012), we propose three task-oriented behavior categories (enhancing understanding, strengthening motivation and facilitating implementation) and three relation-oriented behavior categories (fostering coordination, promoting cooperation and activating resources), each of which is further specified by a number of distinct behaviors. While the task-oriented behaviors are directed towards the accomplishment of shared objectives, the relation-oriented behaviors support this process by increasing the coordinated engagement of the team members. Our model contributes to the advancement of leadership behavior theory by (1) consolidating current taxonomies, (2) sharpening behavioral concepts of leadership behavior, (3) specifying precise relationships between those categories and (4) spurring new hypotheses that can be derived from existing findings in the field of psychology. To test our model as well as the hypotheses derived from this model, we advocate the development of new measurements that overcome the limitations associated with questionnaire and interview studies.     

Generating a smallest binary tree by proper selection of the longest edges to bisect in a unit simplex refinement

In several areas like global optimization using branch-and-bound methods for mixture design, the unit n-simplex is refined by longest edge bisection (LEB). This process provides a binary search tree. For \(n>2\), simplices appearing during the refinement process can have more than one longest edge (LE). The size of the resulting binary tree depends on the specific sequence of bisected longest edges. The questions are how to calculate the size of one of the smallest binary trees generated by LEB and how to find the corresponding sequence of LEs to bisect, which can be represented by a set of LE indices. Algorithms answering these questions are presented here. We focus on sets of LE indices that are repeated at a level of the binary tree. A set of LEs was presented in Aparicio et al. (Informatica 26(1):17–32, 2015), for \(n=3\). An additional question is whether this set is the best one under the so-called \(m_k\)-valid condition.     

An integrated model of national HRD and critical HRD: considering new possibilities for human resource development

Though both National Human Resource Development (NHRD) and Critical Human Resource Development (CHRD) have received an increasing amount of attention, only two published works have used an explicitly critical approach to discuss NHRD norms, policies, and practices. The purpose of this article was to examine and articulate the relationship between NHRD and CHRD and make a case for the importance of that relationship to the field of HRD. We identify some commonalities between NHRD and CHRD, including the shared priorities of context, culture, and empowerment, which provide a strong foundation for future focuses on theory-sharing, global awareness, holistic and socially conscious economic development, negotiated power and performance, and emancipation in HRD research and practice.     

农业企业的盈余操控更为严重吗?——基于中国上市公司的实证研究

采用2007—2014年中国沪深两市A股上市公司数据,研究行业特征和盈利能力对上市公司盈余管理水平的影响,实证分析结果表明:农业上市公司较非农上市公司具有更高的应计盈余管理水平和真实盈余管理水平;上市公司的盈利能力与应计盈余管理水平正相关,而与真实盈余管理水平负相关;较高的盈利能力强化了行业特征对真实盈余管理水平的正向影响,而对应计盈余管理水平则不具有这种影响。该研究不仅证实了农业上市公司较非农上市公司实施了更为严重的盈余操控,还揭示出上市公司的盈利能力对应计盈余管理水平和真实盈余管理水平的影响存在异质性以及盈利能力对行业特征与两种盈余管理水平之间关系的调节作用也存在异质性。     

Estimates of subgroup treatment effects in overall nonsignificant trials: To what extent should we believe in them?

In drug development, it sometimes occurs that a new drug does not demonstrate effectiveness for the full study population but appears to be beneficial in a relevant subgroup. In case the subgroup of interest was not part of a confirmatory testing strategy, the inflation of the overall type I error is substantial and therefore such a subgroup analysis finding can only be seen as exploratory at best. To support such exploratory findings, an appropriate replication of the subgroup finding should be undertaken in a new trial. We should, however, be reasonably confident in the observed treatment effect size to be able to use this estimate in a replication trial in the subpopulation of interest. We were therefore interested in evaluating the bias of the estimate of the subgroup treatment effect, after selection based on significance for the subgroup in an overall “failed” trial. Different scenarios, involving continuous as well as dichotomous outcomes, were investigated via simulation studies. It is shown that the bias associated with subgroup findings in overall nonsignificant clinical trials is on average large and varies substantially across plausible scenarios. This renders the subgroup treatment estimate from the original trial of limited value to design the replication trial. An empirical Bayesian shrinkage method is suggested to minimize this overestimation. The proposed estimator appears to offer either a good or a conservative correction to the observed subgroup treatment effect hence provides a more reliable subgroup treatment effect estimate for adequate planning of future studies.