The interactive effects of organizational and leadership career management support on job satisfaction and turnover intention

In the organizational career management literature, scholars have focused on career management policies, with little attention given to practices that can vary within organizations. And despite its recognized importance, research on the role of leaders in the career management process is also scant. In this study, we investigate the effects of career management practices (OCPs) and leadership career support (LCS) on employee attitudes. Grounded on coping theory, we propose that career support received from line managers can be particularly consequential when OCPs are lacking. We analyze the moderating effects of LCS on the relationship between OCPs and both job satisfaction and turnover intention in a sample of employees from a large Brazilian organization, applying multiple regression analyses. Results showed that OCPs and LCS are positively related to job satisfaction and that OCPs are negatively related to turnover intention. In addition, we confirmed that LCS moderates the relationship between OCPs and both job satisfaction and turnover intention. Finally, we observed that the relationship between OCPs and turnover intention is mediated by job satisfaction. Theoretical and practical implications are discussed.     

Using clustering ensemble to identify banking business models

The business models of banks are often seen as the result of a variety of simultaneously determined managerial choices, such as those regarding the types of activities, funding sources, level of diversification, and size. Moreover, owing to the fuzziness of data and the possibility that some banks may combine features of different business models, the use of hard clustering methods has often led to poorly identified business models. In this paper we propose a framework to deal with these challenges based on an ensemble of three unsupervised clustering methods to identify banking business models: fuzzy c‐means (which allows us to handle fuzzy clustering), self‐organizing maps (which yield intuitive visual representations of the clusters), and partitioning around medoids (which circumvents the presence of data outliers). We set up our analysis in the context of the European banking sector, which has seen its regulators increasingly focused on examining the business models of supervised entities in the aftermath of the twin financial crises. In our empirical application, we find evidence of four distinct banking business models and further distinguish between banks with a clearly defined business model (core banks) and others (non‐core banks), as well as banks with a stable business model over time (persistent banks) and others (non‐persistent banks). Our proposed framework performs well under several robustness checks related with the sample, clustering methods, and variables used.     

Inequality and Income Distribution in Global Value Chains

Global value chains (GVCs), led by transnational corporations (TNCs), have reshaped the world division of labor over the past two decades. GVCs are pervasive in low technology manufacturing, such as textile and apparel, as well as in more advanced industries like automobiles, electronics, and machines. This hierarchical division of labor generates wild competition at the lower value-added stages of production, where low wages and low profit margins prevail for workers and contract manufacturers in developing countries. At the top of the hierarchy another kind of competition prevails, centered on the ability to monitor and control intellectual property rights related to innovation, finance, and marketing. We argue that GVCs have had crucial effects on income inequality and the appropriation of rents in modern capitalism.     

The relationship between high performance work systems and employee proactive behaviour: role breadth self‐efficacy and flexible role orientation as mediating mechanisms

Drawing on the contextual perspective, this study provides novel empirical evidence on how the organisational context (specifically, the firm's human resource strategy) has an effect on employee proactivity. We use matched data from managers and employees in 102 Spanish professional service firms to examine how high performance work systems contribute to enhance employee proactive behaviours through two motivational variables: role breadth self‐efficacy and flexible role orientation. Results of a multilevel study demonstrate that role breadth self‐efficacy mediates between HPWS and employee proactivity, but flexible role orientation does not mediate this relationship.     

An algorithm for panel ANOVA with grouped data

In this paper, we present an algorithm suitable for analysing the variance of panel data when some observations are either given in grouped form or are missed. The analysis is carried out from the perspective of ANOVA panel data models with general errors. The classification intervals of the grouped observations may vary from one to another, thus the missing observations are in fact a particular case of grouping. The proposed Algorithm (1) estimates the parameters of the panel data models; (2) evaluates the covariance matrices of the asymptotic distribution of the time-dependent parameters assuming that the number of time periods, T, is fixed and the number of individuals, N, tends to infinity and similarly, of the individual parameters when T → ∞ and N is fixed; and, finally, (3) uses these asymptotic covariance matrix estimations to analyse the variance of the panel data.     

Making use of Internet interactivity to propose a dynamic presentation of web questionnaires

Quality & Quantity - New methodologies that aim to collect data in innovative ways (e.g. big data) are putting pressure on the traditional surveys based on questionnaires. In order to obtain...