Issues in the analysis of co-authorship networks

Scientific collaboration is a complex phenomenon that improves the sharing of competences and the production of new scientific knowledge. Social Network Analysis is often used to describe the scientific collaboration patterns defined by co-authorship relationships. Different phases of the analysis of collaboration are related to: data collection, network boundary setting, relational data matrix definition, data analysis and interpretation of results. The aim of this paper is to point out some issues that arise in these different phases, highlighting: (i) the use of local archives versus international bibliographic databases; (ii) the use of different approaches for setting boundaries in a whole-network; (iii) the definition of a co-authorship data matrix (binary and weighted ties) and (iv) the analysis and the interpretation of network measures for co-authorship data. We discuss the different choices that can be made in these phases within an illustrative example on real data which is referred to scientific collaboration among researchers affiliated to an academic institution. In particular, we compare global and actor-level network measures computed from binary and weighted co-authorship networks in different disciplines.     

Employee reactions to voice and choice in the workplace: the influence of culture

The present study investigated the effect of culture on a much-prescribed management practice, that of employee participation in decision making. A survey was conducted among employees from two countries culturally distinct in the dimensions of power distance and individualism, namely Canada and the Philippines. Given eight decision-making scenarios that varied in terms of whether voice and/or choice was given to the employee and in terms of the importance of the outcomes, the respondents were asked about their perceptions of fairness of the procedures and outcomes, satisfaction with the procedures and outcomes, and preference for the decision-making procedures. Results show a highly significant country decision-making mode outcome importance interaction effect, but not in the directions expected. Overall, the Philippine sample registered more positive reactions to participation in decision making, although the Philippines' higher rank in power distance and lower rank in individualism than Canada seem to indicate otherwise. The results, together with a previous study conducted in high power distance-low individualism Mexico, forcefully suggest that employee participation in decision making may be successfully transferred.     

Does entrepreneurial activity matter for economic growth in developing countries? The role of the institutional environment

The discussion on which institutions determine entrepreneurial activity – and the role of institutions in the aggregated output for developing countries – is as yet unresolved. The extant literature about entrepreneurship recognizes new ventures as potential mechanisms for long-term development. Yet, there is a consensus on the lack of evidence, particularly for these countries. Drawing on institutional economics, this article explores the interrelationships among institutional environment, entrepreneurial activity, and economic growth. To this end, we use simultaneous-equation panel data models for a sample of 14 developing countries (78 observations) over the period of 2004–2012. The main findings suggest a causal chain running from institutions to opportunity entrepreneurship, which is linked to the economic growth of emerging economies. In particular, we find that institutional factors – such as the number of procedures to start a new business, private credit coverage ,, and access to communication– influence entrepreneurial activity driven by opportunity. Policy implications for developing countries could be derived in order to enhance their economic performance through entrepreneurial activity.

     

Model misspecification effects for biased samples

The model misspecification effects on the maximum likelihood estimator are studied when a biased sample is treated as a random one as well as when a random sample is treated as a biased one. The relation between the existence of a consistent estimator under model misspecification and the completeness of the distribution is also considered. The cases of the weight invariant distribution and the scale parameter distribution are examined and finally an example is presented to illustrate the results.