Characteristics and mobile Internet use intensity of consumers with different types of advanced handsets: An exploratory empirical study of iPhone,Android and other web-enabled mobile users in Germany

This work explores personal characteristics and mobile Internet (MI) use behaviors of consumers equipped with four distinct types of advanced handsets for accessing the Internet via cellular radio infrastructures of mobile network operators (MNO). Furthermore, it investigates the extent to which personal and mobile appliance characteristics explain variance in actual MI use intensity. Data on two demographic variables, three MNO relationship characteristics and actual MI use intensity (average monthly volume of mobile IP traffic generated by a subscriber in May and June 2011) of 9321 adult consumers with a flat MI pricing scheme are extracted from customer files of the German subsidiary of a large international MNO. 959, 2213, 2410 and 3739 of the sample members use an Apple iPhone 3, an Apple iPhone 4, a model running with Google’s Android operating system (OS) and other MI-enabled mobile OS/phone types, respectively. Compared to the adult population in Germany, persons at least 50 years of age are clearly underrepresented among MI adopters with the four studied device types. Differences between the four phone type groups with regard to gender, age, time from enrollment and MI use experience emerge as statistically significant, but they achieve only minor substantial relevance. MI use intensity is highly positively skewed: In each of the four appliance groups, a small number of users disproportionately add to the total MI traffic generated by the subjects. Consumers’ advanced OS/handset type strongly contributes towards explaining MI use intensity variance. iPhone subscribers generate more traffic than Android customers who in turn show a higher MI activity level than individuals running other web-enabled mobile models. Age is the only studied personal characteristic consistently showing a (negative) association with MI usage, which both is statistically and materially significant. Conclusions are drawn for MNO on MI marketing issues. Implications of study limitations for research on MI adoption and use behaviors on the MI are also outlined.     

InsurTech in the United States and Germany—What are the drivers behind the different business models?

Comparing the InsurTech ecosystems of the United States and Germany (Europe), there are significant regional differences in the choice of business models. While many InsurTechs in the United States have opted for the business model of a fully licensed insurer, this business model is much less common in Europe. In Europe, many InsurTechs seem to shy away from applying for a license as an insurer and limit themselves to the business model of a broker or a managing general agent. This paper analyzes the factors that influence an InsurTech's choice of business model when deciding whether or not to apply for an insurance license. It examines the impact of different local market environments on these decisions, as well as the role that access to venture capital plays in business model decisions and how regulators and their actions influence the decision-making process.     

OPTIMAL LIQUIDATION AND ADVERSE SELECTION IN DARK POOLS

We consider an investor who has access both to a traditional venue and a dark pool for liquidating a position in a single asset. While trade execution is certain on the traditional exchange, she faces linear price impact costs. On the other hand, dark pool orders suffer from adverse selection and trade execution is uncertain. Adverse selection decreases order sizes in the dark pool while it speeds up trading at the exchange. For small orders, it is optimal to avoid the dark pool completely. Adverse selection can prevent profitable round‐trip trading strategies that otherwise would arise if permanent price impact were included in the model.     

Wettbewerbsveränderungen im Kontext der Smart-Meter-Einführung in Deutschland

Triggered by the “Messstellenbetriebsgesetz” (metering point operations act), millions of electricity end-users and operators of decentralised energy production facilities face the re placement of their electricity meters by networked intelligent measurement systems (iMS; also better known as smart meters) in Germany in the coming years. Against the background of the legal context of iMS and an overview of their new capabilities, the present article discusses competitive effects of their launch on (1) companies that supply key iMS components to the electricity sector and (2) iMS operators. The analysis reveals that the increasing deployment of decentralised plants generating power from renewable sources, in conjunction with the digitalisation of electricity networks, paradoxically promote a decrease in the number of viable metering point operators. This leads to an increase in market concentration among iMS operation suppliers in favour of large scale utilities and financially strong players from outside the electricity industry which sell billing services covering various ancillary consumption costs of rental flats.     

OPTIMAL TRADE EXECUTION AND PRICE MANIPULATION IN ORDER BOOKS WITH TIME‐VARYING LIQUIDITY

In financial markets, liquidity is not constant over time but exhibits strong seasonal patterns. In this paper, we consider a limit order book model that allows for time‐dependent, deterministic depth and resilience of the book and determine optimal portfolio liquidation strategies. In a first model variant, we propose a trading‐dependent spread that increases when market orders are matched against the order book. In this model, no price manipulation occurs and the optimal strategy is of the wait region/buy region type often encountered in singular control problems. In a second model, we assume that there is no spread in the order book. Under this assumption, we find that price manipulation can occur, depending on the model parameters. Even in the absence of classical price manipulation, there may be transaction triggered price manipulation. In specific cases, we can state the optimal strategy in closed form.     

Optimal trade execution in order books with stochastic liquidity

In financial markets, liquidity changes randomly over time. We consider such random variations of the depth of the order book and evaluate their influence on optimal trade execution strategies. If the stochastic structure of liquidity changes satisfies certain conditions, then the unique optimal trading strategy exhibits a conventional structure with a single wait region and a single buy region, and profitable round‐trip strategies do not exist. In other cases, optimal strategies can feature multiple wait regions and optimal trade sizes that can be decreasing in the size of the position to be liquidated. Furthermore, round‐trip strategies can be profitable depending on bid–ask spread assumptions. We illustrate our findings with several examples including the Cox–Ingersoll–Ross model for the evolution of liquidity.     

Digital- und Medienpolitik in Parteiprogrammen zur Bundestagswahl 2021

Wirtschaftsdienst - Vier Parteien — Die Linke, SPD, Bündnis 90/Die Grünen und FDP — haben bis Ende April 2021 den Entwurf ihres Programms zur Bundestagswahl am 26. September...