The MIMIC–CUB Model for the Prediction of the Economic Public Opinions in Europe

Social Indicators Research - To study the Europeans’ perception on the economic conditions, a model that combine Multiple Indicators Multiple Causes (MIMIC) and Combination of Uniform and...     

Innovation in Family Firms: A Systematic Literature Review and Guidance for Future Research

Through a systematic review of 118 peer‐reviewed journal articles published between 1961 and 2017, this article provides an integrative picture of the state of the art of the family firm innovation literature. Our aim is to widen existing understanding of innovation in family firms by building a theoretical bridge with studies in the mainstream innovation literature. Specifically, in identifying the main gaps in the literature and providing future research directions, our critical and dynamic picture of family‐specific determinants of innovation is intended to advance the debate on innovation in general, and family firms in particular.     

Governance Considerations for Seeker–Solver Relationships: A Knowledge‐Based Perspective in Crowdsourcing for Innovation Contests

The need to solve innovation problems and insource knowledge has led to an increasing number of organizations engaging in crowdsourcing activities and subsequently establishing working relationships with winning solution providers. Using a knowledge‐based view and the problem‐solving perspective, we develop a theoretical framework suggesting how specific innovation problem attributes (i.e. the decomposability, formulation and search space of the problem) influence the governance decision (unilateral vs. bilateral) of seekers to manage the relationship with winning solvers. We empirically analyse the framework using 582 challenges broadcast on the NineSigma crowdsourcing platform. Our results indicate that problem attributes – the formulation and search space of the problem – have a positive effect on seekers’ preference towards unilateral governance structures. However, we did not find any empirical confirmation of the effect that the decomposability of the innovation problem has on seekers’ preference towards unilateral governance structures. This study offers several contributions to the crowdsourcing literature, and also has important implications for managers of organizations aiming to insource knowledge through crowdsourcing for innovation contests.     

Subject-specific odds ratios in binomial GLMMs with continuous response

In a regression context, the dichotomization of a continuous outcome variable is often motivated by the need to express results in terms of the odds ratio, as a measure of association between the response and one or more risk factors. Starting from the recent work of Moser and Coombs (Stat Med 23:1843–1860, 2004) in this article we explore in a mixed model framework the possibility of obtaining odds ratio estimates from a regression linear model without the need of dichotomizing the response variable. It is shown that the odds ratio estimators derived from a linear mixed model outperform those from a binomial generalized linear mixed model, especially when the data exhibit high levels of heterogeneity.     

A New Relative Importance Index of Evaluation for Conjoint Analysis: Some Findings for CRM Assistant

Social Indicators Research - ELECTUS is an Italian multi-centre research project with the aim of reinforcing the relationship between the academic world and business. Through this project, it is...     

Economic Crisis and Migration

This article develops a perspective on African migrant integration, reflecting on the ‘visualization’ of migrant experience. It formulates some considerations on how integration of migrants can be captured, drawing on empirical material from street photography in modern-day Greece. The main research question concerns the role of visual images as sites for the construction and depiction of social difference. In that sense, their meaning goes beyond their content and they act as visual representations of discourses. The paper addresses this issue through a focus on local aspects of integration of sub-Saharan African migrants in the city centre of Athens. Specifically it looks at three themes related to discourses on migrant integration in today's economic crisis: (1) the physical and social environment of marginalization, (2) the migrant body and (3) the fear of the migrant. On the basis of the findings a synthesis is attempted of several parallel existing representations in discourses about African migration. The synthesis betrays the ongoing struggle between, on the one hand, the dominant structures that the state creates to deal with their presence and, on the other, the migrant strategies for adaptation and inclusion, which in turn sustain the mechanisms and form integration takes in this context.     

Maximum likelihood estimation in Dagum distribution with censored samples

In this work, we show that the Dagum distribution [3 Dagum, C. 1977. A new model of personal income distribution: Specification and estimation. Econ. Appl., XXX: 413–436.  [Google Scholar]] may be a competitive model for describing data which include censored observations in lifetime and reliability problems. Maximum likelihood estimates of the three parameters of the Dagum distribution are determined from samples with type I right and type II doubly censored data. We perform an empirical analysis using published censored data sets: in certain cases, the Dagum distribution fits the data better than other parametric distributions that are more commonly used in survival and reliability analysis. Graphical comparisons confirm that the Dagum model behaves better than a number of competitive distributions in describing the empirical hazard rate of the analyzed data. A probability plot to provide graphical check of the appropriateness of the Dagum model for right censored data is constructed, and the details are given in the appendix. Finally, a simulation study that shows the good performance of the maximum likelihood estimators of the Dagum shape parameters for finite type II doubly censored samples is carried out.     

Deriving Multidimensional Poverty Indicators: Methodological Issues and an Empirical Analysis for Italy

Theoretical and empirical studies have recently adopted a multidimensional concept of poverty. There is considerable debate about the most appropriate degree of multidimensionality to retain in the analysis. In this work we add to the received literature in two ways. First, we derive indicators of multiple deprivation by applying a particular multivariate statistical technique, the non-linear principal component analysis (NLPCA), which overcomes traditional limits of many of the mostly used methodologies for poverty measurement. Second, on the basis of the aforementioned indicators, we provide an accurate identification of the poor in Italy by analyzing deprivation both as a distinct phenomenon in different life domains and as a single multidimensional concept. The main determinants of poverty in Italy are then investigated by estimating logit regressions and an ordered probit model. Our empirical analysis is based on data from the Italian component of European Statistics on Income and Living Conditions (EU-SILC-2004).     

Decompositions by sources and by subpopulations of the Pietra index: two applications to professional football teams in Italy

In this paper two innovative procedures for the decomposition of the Pietra index are proposed. The first one allows the decomposition by sources, while the second one provides the decomposition by subpopulations. As special case of the latter procedure, the “classical” decomposition in two components (within and between) can be easily obtained. A remarkable feature of both the proposed procedures is that they permit the assessment of the contribution to the Pietra index at the smallest possible level: each source for the first one and each subpopulation for the second one. To highlight the usefulness of these procedures, two applications are provided regarding Italian professional football (soccer) teams.

     

Cellular automata and Riccati equation models for diffusion of innovations

Innovation diffusion represents a central topic both for researchers and for managers and policy makers. Traditionally, it has been examined using the successful Bass models (BM, GBM), based on an aggregate differential approach, which assures flexibility and reliable forecasts. More recently, the rising interest towards adoptions at the individual level has suggested the use of agent based models, like Cellular Automata models (CA), that are generally implemented through computer simulations. In this paper we present a link between a particular kind of CA and a separable non autonomous Riccati equation, whose general structure includes the Bass models as a special case. Through this link we propose an alternative to direct computer simulations, based on real data, and a new aggregate model, which simultaneously considers birth and death processes within the diffusion. The main results, referred to the closed form solution, the identification and the statistical analysis of our new model, may be both of theoretical and empirical interest. In particular, we examine two applied case studies, illustrating some forecasting improvements obtained.