What Prevents Firms from Advancing in their Environmental Strategy?

The aim of this paper is to analyze the determinants of the strategic environmental behavior of firms and, more specifically, the external and internal barriers that limit and sometimes even prevent the environmental adaptation. The analysis focuses on a sample of industrial firms that have at least three workers and that are located in Aragón, a region situated in the northeast of Spain. In order to achieve this objective, first the theoretical literature on the topic is reviewed. Subsequently, from the firms which were sampled, the existence of an underlying structure among the totality of barriers is studied. Finally, this structure is analyzed in order to determine if it has any influence on the degree of proactivity of the firm’s environmental strategy.

Spatial Regression Analysis vs. Kriging Methods for Spatial Estimation

Due to the rapid development of Geographic Information Systems (GIS) in recent years, spatial data analysis has received considerable attention and played an important role in social science. Although many standard statistical techniques are attractive in traditional data analysis, they cannot be implemented uncritically for spatial data. Generally, most of the studies in spatial data analysis can be divided into two branches: the model-driven approach and the data-driven approach. The main aim of this paper is the comparison of both approaches. To carry out such a task, crime rate data in Columbus (Ohio), coming from a well-known database, have been used. The main aim of this paper is to illustrate how spatial effects can be viewed as spatial econometric models, which assess the limitations of standard techniques in a spatial context, suggesting alternative methods to deal with this problem. An application to the crime rate in Columbus (Ohio) has been carried out.

Returns from social capital in open source software networks

Open Source Software projects base their operation on a collaborative structure for knowledge exchange in the form of provision or reception of information, expertise and feedback on the creation of source code. Here, we address the direction of these knowledge flows among projects throughout social networks and their impact on project success. We identify the roles of membership or contribution that individuals play within projects. We found that connections through contributors who bring their knowledge to the project, improve project success, and that connection through members, who transfer their knowledge towards other projects, enhance project success. Finally, we found that ties through shared membership and contributions hamper project success. The analysis of knowledge flows and their impact on project success imply a translation of returns from investment in social capital, where investment takes the shape of knowledge flows and the returns mean the projects’ diffusion over the network.

An empirical approach to the organisational determinants of spin-off creation in European universities

Given the importance in recent years of the phenomenon of academic entrepreneurship in European universities, knowledge about determinants and performance of this technology transfer mechanism may have important managerial and policy implications. Applying the resource-based view at universities, we have tested the influence of five bundles of resources and capabilities on spin-off activity rates as well as on the performance of new spin-offs in a sample of seven European universities. These five bundles are: technology transfer policies and strategies; human capital; stock of technology; resources and capabilities of technology transfer offices; and support measures for academic entrepreneurship. Our results show that excellence of human capital and the presence of university-based financial support measures are strongly associated with both spin-off activity and performance. Another interesting finding is related to the availability of university-based non-economic support measures (training, counselling, etc.), which have no influence on spin-off activity but are significantly associated with performance of new spin-offs. We also discuss some interesting relationships between explanatory variables.     

Combining forecasts: An application to elections

We summarize the literature on the effectiveness of combining forecasts by assessing the conditions under which combining is most valuable. Using data on the six US presidential elections from 1992 to 2012, we report the reductions in error obtained by averaging forecasts within and across four election forecasting methods: poll projections, expert judgment, quantitative models, and the Iowa Electronic Markets. Across the six elections, the resulting combined forecasts were more accurate than any individual component method, on average. The gains in accuracy from combining increased with the numbers of forecasts used, especially when these forecasts were based on different methods and different data, and in situations involving high levels of uncertainty. Such combining yielded error reductions of between 16% and 59%, compared to the average errors of the individual forecasts. This improvement is substantially greater than the 12% reduction in error that had been reported previously for combining forecasts.     

INCENTIVES AND SOCIAL NORMS: A MOTIVATION‐BASED ECONOMIC ANALYSIS OF SOCIAL NORMS

Abstract It is now commonplace to regard social norms as a subject of growing interest in the economic literature (e.g. game theoretical approaches based on ‘other‐regarding’ individual preferences, the analysis of the impact of rewards or punishment on individuals’ behaviour through experimental economics as well as field experiments, the revival of the institutionalist tradition spurred on by the influential work of Douglas North and followed by many others and the growing influence of neuroeconomics). In this paper, we focus on the relationship between incentives and social norms and survey the literature that could constitute the foundations of a motivation‐based economic analysis of social norms. Our main findings are that (1) the interaction between incentives and social norms is far from obvious since taking social norms into account involves the introduction of supplementary motives, in addition to self‐interest, into the economic analytical framework; (2) the analysis of the interaction between incentives and social norms resists an approach exclusively in terms of crowding‐in and ‐out effects because it is sensitive to whether it concerns behaviours driven by honour or by social stigma; (3) as a result, it is difficult to precisely evaluate the policy implication of the interactions between incentives and social norms.     

Health effects on labour market exits and entries

This paper analyses the role of health on exits out of and entries into employment using data from the first twelve waves of the British Household Panel Survey (1991–2002). We use discrete-time duration models to estimate the effect of health on the hazard of becoming non-employed and on the hazard of becoming employed. The results show that general health, measured by a variable that captures health limitations and by a constructed latent health index, affects entries into and exits out of employment; the effects being higher for men than for women. The results are robust to different definitions of employment, and to the exclusion of older workers from the analysis.     

To post or not to post: social media sharing and sporting event performance

Social networks are becoming increasingly important for consumers, especially in the context of sport, where the service experience is highly intense. Few studies have combined subjective event performance variables and social network variables to analyze social network content sharing by sports practitioners. This article investigates the use of social networks in relation to sporting events. An empirical study examined the role of social network variables and sporting event performance variables in social media use. The sample consisted of 410 triathletes (72.2% male) aged between 18 and 66 years (mean 37.03 ± 8.62). Four analyses were performed using fuzzy‐set qualitative comparative analysis to examine the causes of sharing comments through social media, sharing photos and videos on social media, participant satisfaction, and word‐of‐mouth (WOM). The event's general image was a necessary condition in all cases. The combination of participants’ satisfaction and positive event image and the combination of social network use and positive event image lead to social network content sharing by athletes. The combination of positive event image and participant satisfaction leads to a positive WOM.