Multidimensional scaling of consumer preferences for a public transportation system: An application of two approaches

Consumer attitudes toward a proposed new public transportation system were assessed through the application of two multidimensional scaling models to data on preference choices for system attributes. Carroll's vector model and Kruskal and Carmone's nonmetric unfolding model were compared on theoretical and empirical levels to determine their utility for exposing the latent structure of attitudes for a public project. While the unfolding model was attractive because of a theoretical property, the vector model was able to uncover latent dimensions for the attitudes which could be related via discriminant analysis to socio-economic and demographic characteristics of the respondents. The vector model also produced an outcome which was more closely related to a unidimensional analysis of these data. Therefore, even though both the vector and unfolding models produced plausible geometric representations of the attitudes which arc expected to aid urban transportation planners in designing systems, the vector model produced the more acceptable outcome.     

From unemployed to entrepreneur: The role of the absolute bequest motive

Using the British Household Panel Survey, this paper finds that inheritance has a concave effect on the hours worked by male entrepreneurs. Receiving an inheritance increases the labor supply of unemployed male entrepreneurs; however this effect becomes smaller for higher inheritances.     

How do central banks react to wealth composition and asset prices?

We assess the response of monetary policy to developments in asset markets in the euro area, the US and the UK. We estimate the reaction of monetary policy to wealth composition and asset prices using: (i) a linear framework based on a fully simultaneous system approach in a Bayesian environment; and (ii) a nonlinear specification that relies on a smooth transition regression model.     

Imperfect credibility and the zero lower bound

As the nominal interest rate cannot fall below zero, a central bank with imperfect credibility faces a significant challenge to stabilize the economy in a New Keynesian model during a large recession. We characterize the optimal monetary policy at the zero lower bound for the nominal interest rate if credibility is imperfect. Confronting monetary policy communication of the U.S. Federal Reserve and the Swedish Riksbank with such a framework, the credibility of both institutions is shown to have been low in the aftermath of the 2008 economic crisis.     

A systematic mapping study on enterprise architecture mining

Enterprise architecture allows companies to deal with digital transformation through the proactive presentation and alignment of business and IT in a holistic manner. One important challenge is EA modelling since it is time-consuming (thus expensive), error-prone, and biased owing to experts’ subjective opinions. This challenge might consequently be addressed through automatic EA modelling. We conducted a systematic mapping study to classify and evaluate the research concerning EA mining proposals developed specifically for TOGAF and Archimate. After analysing results, we concluded that the research field is not sufficiently mature and further research on EA mining is necessary.     

Can unpredictable risk exposure be priced?

We study the link between beta predictability and the price of risk. An investor who desires exposure to a certain risk factor needs to predict what next period’s beta will be. We use a simple model to show that an ambiguity averse agent’s demand is lower when betas are hard to predict, leading to a reduction in risk premiums. We test the implications for downside betas and VIX betas. We find that they have economically and statistically small prices of risk once we account for the fact that an investor cannot observe ex-post realized betas when determining asset demand.     

Household Determinants of the Adoption of Improved Cassava Varieties using DNA Fingerprinting to Identify Varieties in Farmer Fields: A Case Study in Colombia

We examine factors affecting the adoption of improved cassava varieties of 217 households in the Cauca Department in southwest Colombia. Using DNA fingerprinting through Single Nucleotide Polymorphisms (SNPs), we identified different cultivars in farmers fields. We also used this information to remove possible bias in the adoption model that could have resulted from a misclassification of improved varieties (IVs). As a result, we found that farmers substantially overestimate their use of IVs and there are important differences in the determinants of adoption between farmer self‐identification and DNA fingerprinting. This finding implies that the incorporation of DNA fingerprinting in IV adoption studies is important to ensure the accuracy of future agricultural economic research and the relevance of subsequent policy recommendations.     

Identifying cycling-inducing neighborhoods: A latent class approach

Understanding how spatial attributes of cities and neighborhoods induce cycling is relevant for urban planning and policy making. In this work, ordered logit and latent class models are specified and estimated to analyze how the built environment affects bicycle-commuting frequency. Data come from a survey to 1,487 people in the city of Santiago, Chile, including sociodemographic information, travel behavior patterns and place of residence and work. Using geographic information systems tools, the built environment was characterized with variables calculated for a 500-m-radius buffer around the residential and work locations of each individual. Two models are estimated, first an ordered logit model confirms that built environment variables effect on cycling is similar to what has been reported in the literature, with some new findings such as an increase in cycling when public transport accessibility is low and the role of built environment attributes at the destination. Second, a latent class ordered logit is used to identify two classes of neighborhood in term of their cycling patterns, as a function of their density, presence of cycling infrastructure and distance to the main activity center of the city. This result allows to map the class membership probabilities, potentially helping to identify neighborhoods that encourage cycling and providing relevant information for policy making and infrastructure decisions.     

Attracting potential blood donors: The role of personality and social marketing

Globally, society has been facing several and growing health problems, which increased the importance of efforts towards social change. In this context, using social marketing to create and implement programs that foster behavioural change has increased in the public health community. One of the health problems that society has been facing is the unceasing need for blood products, so the subject of blood donation became an important research topic in the area of social marketing, as social marketing strategies can contribute to solving this problem. It is essential to understand the factors that motivate individuals to donate blood, to enhance the recruitment and retention of blood donors. Our study aims at evaluating the key personality factors that influence blood donation behaviour to reach a higher understanding of what concerns this global issue. The method used to analyse the data is ANOVA. We conclude that the Personality of potential donors is significantly different from the non-donors' regarding Openness to Experience and Agreeableness. These results suggest that potential donors might perceive blood donation, as well as the associated barriers, differently from non-donors. Based on our findings, we suggest some perspectives for future research in this area.     

Propensity to firm creation: empirical research using structural equations

The identification of the entrepreneurs’ characteristics and the knowledge of the entrepreneurial profile of university students have been assuming a growing importance in the development of educational programs directed towards the entrepreneurship and start-up processes. This study aims to identify the factors that most contribute for the intention to start up a business. The research also tries to identify the profile of a potential entrepreneur student concerning several characteristics: personal attributes, family, demographic variables and motivations. Research findings include the idea that entrepreneurship education is the most relevant factor in what concerns the propensity to business creation. On the other side, personal characteristics have an important role in shaping motivation to start-up a business and perceived hurdles have a negative impact in the intention to start-up. The results may be relevant when developing an adequate educational program directed to the entrepreneurship education and start-up processes.