Visitors’ learning for environmental sustainability: Testing short- and long-term impacts of wildlife tourism experiences using structural equation modelling

Wildlife tourism experiences have the potential to positively impact tourists’ awareness, appreciation and actions in relation to the specific wildlife they encounter and the environment in general. This paper investigates the extent of such impact across multiple sites, and uses Structural Equation Modelling to identify factors that best predict positive long-term learning and environmental behaviour change outcomes. Three sets of variables were measured – visitors’ entering attributes (including pre-visit environmental orientation and motivation for the visit), salient aspects of the experience, and short- and long-term learning and environmental behaviour change outcomes. Although attributes such as pre-visit commitment and motivation to learn were among the best predictors of the long-term impact of the experience, there was evidence that aspects of the experience were also important. In particular, reflective engagement which involved cognitive and affective processing of the experience was found to be associated with short- and long-term environmental learning outcomes. The implications for wildlife tourism managers are discussed.     

Visitors’ acceptance of negative ecological impacts in national parks: comparing the explanatory power of psychographic scales in a Norwegian mountain setting

Even in protected areas, it is inevitable that any human use will produce some impact on natural resources. This study identifies visitors’ tolerance of potential negative ecological impacts from tourism activities and facilities in a Norwegian national park context, based on park visitors’ expressed degree of acceptance of negative effects on particular species of wildlife (wild reindeer and raptors) and on vegetation. Attitudes were analysed using psychographic scales, reflecting respondents’ nature orientations, their specific facility desires, their preferences in a wilderness setting and their concerns about human interaction with the natural environment. Fourteen research hypotheses were tested. Findings demonstrated that the psychographic scales explained more variation in attitudes than most social background and trip characteristics. Higher levels of education among visitors were strongly associated with increased ecological concern; age and gender were not. There was generally strong ecological awareness and eco-centrism among park visitors in general, with a small proportion of wilderness purists. Better trail conditions, signposting and interpretation were sought. But park visitors were also found to possess a complex mixture of needs and drivers. The study found significant potential for strategic alliances between tourism and conservation interests, and key value issues for park governance systems.     

Entry may increase network providers’ profit

In this paper the incentives for platform sponsors to open up their networks for independent rivals is analyzed. It is shown that open access may increase the platform sponsors’ profit levels and enhance quality improving investments. In addition, it is shown that a commitment to allow entry reduces the difference between ex ante and ex post compatibility incentives.     

Corporate Responsibility and the Collegial Field

This article is based on 21 interviews of informants actively engaged with corporate responsibility in Sweden. The article introduces a new concept—the “collegial field”—which is helpful in understanding the course of events. With systems that are more open to other organizations, horizontal groupings with common interests become more influential. Collegial fields can also be relevant for understanding other activities in organizations than corporate responsibility.     

Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model

We extend the class of dynamic factor yield curve models in order to include macroeconomic factors. Our work benefits from recent developments in the dynamic factor literature related to the extraction of the common factors from a large panel of macroeconomic series and the estimation of the parameters in the model. We include these factors in a dynamic factor model for the yield curve, in which we model the salient structure of the yield curve by imposing smoothness restrictions on the yield factor loadings via cubic spline functions. We carry out a likelihood-based analysis in which we jointly consider a factor model for the yield curve, a factor model for the macroeconomic series, and their dynamic interactions with the latent dynamic factors. We illustrate the methodology by forecasting the U.S. term structure of interest rates. For this empirical study, we use a monthly time series panel of unsmoothed Fama–Bliss zero yields for treasuries of different maturities between 1970 and 2009, which we combine with a macro panel of 110 series over the same sample period. We show that the relationship between the macroeconomic factors and the yield curve data has an intuitive interpretation, and that there is interdependence between the yield and macroeconomic factors. Finally, we perform an extensive out-of-sample forecasting study. Our main conclusion is that macroeconomic variables can lead to more accurate yield curve forecasts.     

The impact of coding time on the estimation of school effects

Multilevel growth curve models are becoming invaluable in educational research because they model changes in student outcomes efficiently. The coding of the time variable in these models plays a crucial role as illustrated in this study for the case of a three-level quadratic growth curve model. This paper shows clearly how the choice of a time coding affects school effects estimates and their interpretation. A new definition for school effects for growth curve models with random intercepts and slopes is proposed. This study recommends that the choice of a time coding should not only be based on the ease of interpretation and model convergence but also on its consequences on the student status and growth parameter estimates. The current application illustrates that in general the school effects for student growth in well-being and language achievement in secondary school, are greater for student growth than for student status.