Business model diversification. Demand relatedness, entry sequencing, and curvilinearity in the diversification-performance relationship

This study integrates research on business model diversification (BMD) and demand-side theory to examine the relationship of BMD to performance and the sequencing of business model additions. We begin by explaining and demonstrating that the overall degree of BMD has an inverted U-shaped relationship with firm performance. We next highlight the particular role that demand relatedness plays in BMD. We first provide evidence that the inverted U-shaped relationship flattens in times of financial shocks, consistent with arguments that the benefits of BMD from consumers’ willingness-to-pay for simultaneous use of multiple business models may diminish during shocks. Second, we argue that firms tend to sequence the addition of new business models based on demand relatedness, and we provide evidence that the degree of demand relatedness between a core and a target business model enhances the likelihood of diversification into that target business model

Extreme events and predictability of catastrophic failure in composite materials and in the Earth

Despite all attempts to isolate and predict extreme earthquakes, these nearly always occur without obvious warning in real time: fully deterministic earthquake prediction is very much a ‘black swan’. On the other hand engineering-scale samples of rocks and other composite materials often show clear precursors to dynamic failure under controlled conditions in the laboratory, and successful evacuations have occurred before several volcanic eruptions. This may be because extreme earthquakes are not statistically special, being an emergent property of the process of dynamic rupture. Nevertheless, probabilistic forecasting of event rate above a given size, based on the tendency of earthquakes to cluster in space and time, can have significant skill compared to say random failure, even in real-time mode. We address several questions in this debate, using examples from the Earth (earthquakes, volcanoes) and the laboratory, including the following. How can we identify ‘characteristic’ events, i.e. beyond the power law, in model selection (do dragon-kings exist)? How do we discriminate quantitatively between stationary and non-stationary hazard models (is a dragon likely to come soon)? Does the system size (the size of the dragon’s domain) matter? Are there localising signals of imminent catastrophic failure we may not be able to access (is the dragon effectively invisible on approach)? We focus on the effect of sampling effects and statistical uncertainty in the identification of extreme events and their predictability, and highlight the strong influence of scaling in space and time as an outstanding issue to be addressed by quantitative studies, experimentation and models

Business model diversification. Demand relatedness, entry sequencing, and curvilinearity in the diversification-performance relationship

This study integrates research on business model diversification (BMD) and demand-side theory to examine the relationship of BMD to performance and the sequencing of business model additions. We begin by explaining and demonstrating that the overall degree of BMD has an inverted U-shaped relationship with firm performance. We next highlight the particular role that demand relatedness plays in BMD. We first provide evidence that the inverted U-shaped relationship flattens in times of financial shocks, consistent with arguments that the benefits of BMD from consumers’ willingness-to-pay for simultaneous use of multiple business models may diminish during shocks. Second, we argue that firms tend to sequence the addition of new business models based on demand relatedness, and we provide evidence that the degree of demand relatedness between a core and a target business model enhances the likelihood of diversification into that target business model

Optimal distinctiveness across revenue models: Performance effects of differentiation of paid and free products in a mobile app market

The optimal distinctiveness literature highlights a fundamental trade-off in product positioning within market categories: Products should be distinct to minimize competition, but similar to build legitimacy. Most recently, this research has focused on understanding sources of variance in the distinctiveness–performance relationship. We extend this literature with an examination of digital products and argue that the relationship depends on products' revenue models: We theorize the relationship is inverted U-shaped for paid products but U-shaped for free products, owing to heightened privacy concerns of free product customers. We further argue that this latter relationship becomes flatter for free products that provide greater monetization transparency by publishing a privacy statement or adopting a freemium revenue approach. Hypotheses are tested using a sample of 250,000-plus Apple App Store apps

Magnon-assisted transport and thermopower in ferromagnet-normal-metal tunnel junctions

Magnon-assisted transport across a tunnel junction between a ferromagnet and a normal (nonmagnetic) metal is studied theoretically. A finite temperature difference across the junction produces a nonequilibrium magnetization that drives a charge current, mediated by electrons via electron-magnon interactions, from the ferromagnet into the normal metal. The corresponding thermopower coefficient is large, Ssimilar to-(k(B)/e)(k(B)T/omega(M))P-3/2(Pi(+),Pi(-),Pi(N)) where P(Pi(+),Pi(-),Pi(N)), 0less than or equal toPless than or equal to1, represents the degree of spin polarization of the current response to a bias voltage, and depends on the relative sizes of the majority Pi(+) and the minority Pi(-) band Fermi surface in the ferromagnet and in the normal metal, Pi(N)