Digital insurance brokers—old wine in new bottles? How digital brokers create value

This article analyzes digital brokers in the countries of the DACH region, Germany, Austria, and Switzerland, from a business model perspective. We argue that the potential to create new value for insurance customers has not yet been fully realized. Our analysis has identified two strategic action areas. The first concerns the exploitation of the wealth of customer data available. Those digital brokers who will succeed in generating new content and services using data analytics have the potential to take customer centricity and individuality to new bounds. The second centers around introducing aspects of community, such as connecting peers and enabling them to interact. The critical success factors are volume, a high degree of automation as well as leveraging the infrastructure and data to delivering new, value-adding content and services that go beyond traditional intermediation.     

Can small investors exploit the momentum effect?

This study uses UK data and investigates whether small investors can exploit the continuation effect in share prices. Individual traders are not in a financial position to buy and sell short hundreds of firms, as suggested by existing academic research, and thus this study uses extreme performance companies to implement the strategy. We find that strong momentum gains appear when extreme winners and losers are employed. These returns remain strong even after considering the transaction costs of implementing such strategies, including commissions, stamp duty, selling-short costs, and bid-ask spread. Overall, we show that a relatively large number of small investors can enjoy momentum gains, providing some evidence against stock market efficiency.     

Why Do the Swiss Rent?

At less than 34%, Switzerland has the lowest home ownership rate in Western Europe. This may seem odd given the economic strength of the country. We use household survey data for five Swiss cantons to explore some possible reasons for this. We estimate a tenure choice equation that allows us to analyze the impacts of a number of key variables on the ownership rate. We pay particular attention to the relative cost of owning and renting, which is a function of house prices, rents, and the user cost of owning. The latter is a function of income tax policy and expected house price inflation, among other things. We also measure mortgage underwriting criteria and consider rent control and other policies affecting rental housing. By simulating a number of hypothetical changes to taxation and other policies, underwriting criteria, and price levels, we assess the importance of these variables in explaining the ownership rate. We conclude that high house prices—relative to household incomes and wealth—and the tax on imputed rent are the most important causes of Switzerland’s low ownership rate.     

Monte Carlo theoretical trials of methods for assessing statistical significance for differences between adjusted odds ratios

Odds are generally defined as the number of successes divided by the number of failures in a given number of trials. An odds ratio is the ratio of one odds divided by another. Odds ratios can be adjusted to reflect associations with the outcome independently of the influence of associations with other variables. These are adjusted odds ratios. There are several well known methods for comparing odds ratios and testing for statistically significant differences between them. Analogous methods for adjusted odds ratios are not well known or well documented. One method for comparing adjusted odds ratios is explained by Hosmer and Lemeshow (Applied logistic regression, 2000). This method is used for the odds ratios for two variables from the same data set. The purpose of this analysis was to apply this method to a different situation: comparing odds ratios for the same variable from two different data sets. Monte Carlo trials were used to assess the performance of the method and these indicated the method performed well.     

Line by line,part by part: collaborative sketching for designing

While sketching has an established role in professional design, its benefits and role in design education are subjects that invite research and opinions. We investigated how undergraduates studying to become design educators and textile teachers used sketching to generate and develop design solutions in a collaborative setting. The students were given an authentic design assignment involving three detailed tasks, one of which was 2D visualisation by sketching. Adopting a micro-analytical approach, we analysed the video-recorded visualisation session to understand how teams used sketching to collaborate and to generate and develop design solutions. To that end, we set three research questions: (1) What ways of collaborative working are reflected in actions of sketching? (2) In what ways do sequences of collaborative sketching contribute to designing? (3) What kinds of collaborative sequences of sketching advance designing? Our analysis identified three collaborative ways of sketching (co-ordinated, collective and disclosed) and confirmed that sketching is an important facilitator of mutual appropriation, adaption and adoption. Next, we identified three ways of contributing to designing, as well as three functions and six capacities for advancing designing. Our analysis shows that sketching can lead to invaluable advances in designing, although each team had its own way of using and benefiting from sketching. We further consider that the teams’ diverse sketching processes and rich content owed, at least in part, to the task structure and imposed constraints. We continue to see sketching as an important design tool, one among many.