Antecedents of board involvement and its consequences on organisational effectiveness in non-profit organisations: a study on European corporate foundations

Journal of Management and Governance - The governance of non-profit organisations is complex, as these organisations are not only intended to create value for third parties but also dependent on...     

Measuring Well-Being Over Time: The Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices

Most of the socio-economic phenomena such as development, well-being, and quality of life have a multidimensional nature and require the definition of a set of individual indicators to be properly assessed. Often, individual indicators are summarized and a composite index is created. One of the main problems in constructing composite indices is the choice of a method which allows time comparisons. In this paper, we consider the Adjusted Mazziotta–Pareto Index, a non-compensatory composite index used by the Italian National Institute of Statistics for measuring “Equitable and Sustainable Well-being” in Italy. An empirical comparison with some traditional non-compensatory indices is presented and an Influence Analysis is, for the first time, performed in order to assess the robustness of the index.     

Does Religiosity Influence Retention Strategies in Nonprofit Organizations?

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Despite the rise of interest in nonprofit organizations’ (NPOs) retention strategies and organizational behaviour...     

A multi-objective coordinate-exchange two-phase local search algorithm for multi-stratum experiments

A multi-stratum design is a useful tool for industrial experimentation, where factors that have levels which are harder to set than others, due to time or cost constraints, are frequently included. The number of different levels of hardness to set defines the number of strata that should be used. The simplest case is the split-plot design, which includes two strata and two sets of factors defined by their level of hardness-to-set. In this paper, we propose a novel computational algorithm which can be used to construct optimal multi-stratum designs for any number of strata and up to six optimality criteria simultaneously. Our algorithm allows the study of the entire Pareto front of the optimization problem and the selection of the designs representing the desired trade-off between the competing objectives. We apply our algorithm to several real case scenarios and we show that the efficiencies of the designs obtained present experimenters with several good options according to their objectives.     

Mitigating the effect of risk conditions on supply disruptions: the role of manufacturing postponement enablers

While previous published studies have evaluated the drivers of supply disruptions, only a few have empirically investigated the role of manufacturing postponement enablers as mitigating practices. This work explores the complex interaction between supply disruptions (i.e. supplier failure, purchase unavailability), risk conditions (i.e. antecedents that positively influence the probability and severity of supply disruptions) and manufacturing postponement enablers (i.e. product and process modularity). Specifically, we aim at understanding ‘when’ manufacturing postponement enablers should be adopted the most and ‘if’ their adoption can fully mitigate the effect risk conditions exert on supply disruptions’ probability and severity. To achieve our objective, we developed a conceptual model, and we tested it using survey data from 54 Italian manufacturing companies. The results show that supply market difficulty and technological uncertainty imply a higher probability and severity of disruptions associated with supplier failure and purchase unavailability. Most importantly, we provide evidence of the role played by product and process modularity in fully mitigating the effect of technological uncertainty on supply disruptions.     

Response improvement in complex experiments by co-information composite likelihood optimization

We propose an adaptive procedure for improving the response outcomes of complex combinatorial experiments. New experiment batches are chosen by minimizing the co-information composite likelihood (COIL) objective function, which is derived by coupling importance sampling and composite likelihood principles. We show convergence of the best experiment within each batch to the globally optimal experiment in finite time, and carry out simulations to assess the convergence behavior as the design space size increases. The procedure is tested as a new enzyme engineering protocol in an experiment with a design space size of order 10⁷.     

An Algorithm to Simulate VMA Processes Having a Spectrum with Fixed Condition Number

This article proposes an algorithm to generate vector moving average (VMA) processes with a variable spectrum having a fixed condition number across frequencies. This method is based on the theory of multivariate linear spectrum for VMA processes, and is developed in a two-step procedure. Specific examples are provided, and the precision of generated time series is discussed. Such an algorithm is a useful tool to assess the performance of selected multivariate spectral estimators, and it turns out to be particularly appropriated in the Kolmogorov asymptotic estimation framework.     

When Catholics turn right: the effects of the Islamic terrorism threat on the fragmented Catholic Italian voters

Italy, as well as most European countries, has been hit by a wave of anxiety arising from groups such as ISIS and Al Qaeda, whose effects on political attitudes are still under-examined. This article investigates the effect of the perceived threat of Islamic terrorism as a potential driver for a ‘right turn’ in the Catholic Italian electorate with open-ended interviews and an Internet-based experiment in which voters were randomly assigned to a terrorism threat manipulation and to a control condition (N?=?138). The results show that the Islamic terroristic threat significantly increased the support for centre-right leaders who promoted in-group identity and out-group hostility towards Muslims. Implications for the debate about the effects of perceived threat on political opinions and the relevance of the findings beyond the Italian case are discussed at the end of the article.