Design and regulation of balancing power auctions: an integrated market model approach

Journal of Regulatory Economics - We present an integrated market model which considers the dependencies between the wholesale market and the highly regulated balancing power markets. This fosters...     

The impact of trade agreements on world export prices

This paper uncovers new stylized facts on the relation between economic integration and world trade prices. Using free on board export price data for the universe of manufacturing products, we show that a country's membership in the WTO (World Trade Organization) or in a PTA (Preferential Trade Agreement) is associated with an increase in export prices of differentiated goods. For the WTO, this effect is captured by the countries that were subject to rigorous WTO accession procedures. We also exploit the importance of the depth of a PTA and of its different provisions. Whereas the effect of the depth per se is not significant, individual provisions evoke distinct effects on prices. In particular, we find that PTAs with provisions on investments are associated with higher export prices. The results are consistent with theoretical models that relate competition to the innovation behavior of firms.     

Multilevel dual approach for pricing American style derivatives

In this article we propose a novel approach to reduce the computational complexity of the dual method for pricing American options. We consider a sequence of martingales that converges to a given target martingale and decompose the original dual representation into a sum of representations that correspond to different levels of approximation to the target martingale. By next replacing in each representation true conditional expectations with their Monte Carlo estimates, we arrive at what one may call a multilevel dual Monte Carlo algorithm. The analysis of this algorithm reveals that the computational complexity of getting the corresponding target upper bound, due to the target martingale, can be significantly reduced. In particular, it turns out that using our new approach, we may construct a multilevel version of the well-known nested Monte Carlo algorithm of Andersen and Broadie (Manag. Sci. 50:1222–1234, 2004) that is, regarding complexity, virtually equivalent to a non-nested algorithm. The performance of this multilevel algorithm is illustrated by a numerical example.     

Examining the relationship between customer and entrepreneurial orientation on nascent firms’ marketing strategy

Is entrepreneurial marketing (EM) a ??one type fits all?? approach? Research suggests that EM is especially suitable for small firms. However, it is obvious that??despite their size??small firms show a myriad of different characteristics. In this paper, it is argued that different firm characteristics can be seen in different business orientations, namely customer orientation (CO) and entrepreneurial orientation (EO). In turn, different amounts of EO and CO lead to different forms of EM strategy. The Panel Study of Entrepreneurial Dynamics (PSED) serves as source to investigate relationships between EO, CO, and respective marketing strategies among nascent firms. The study suggests that innovativeness is strongly related to the importance of several marketing strategies, such as developing new or advanced product or process technologies. However, other strategies, such as lower prices or convenient location, are not related to either significant levels of CO or EO. The paper offers two main implications. Firstly, small business founders have to be aware of the fact that certain strategies cannot come ??out of nowhere??. This paper shows that running proactive marketing strategies that aim for ongoing innovativeness require the existence of an underlying EO. Secondly, there are different forms of ??small firm EM??; a finding that requires further research in the future.     

Organizational expatriates and self-initiated expatriates: who adjusts better to work and life in Japan?

Expatriates are often presented in the cross-cultural adjustment literature as a homogeneous, broad population. However, recent research that makes a distinction between organizational expatriates (OEs), those who are dispatched by their home companies to international posts, and self-initiated expatriates (SIEs), those who themselves make the decision to live and work abroad, has identified differences between the two groups. The present study compares the cross-cultural adjustment of these two groups of expatriates. Survey results of 179 expatriates in Japan show that SIEs are better adjusted to general aspects of their host country and interactions with host-country nationals than OEs. Suggestions for practice are provided.     

What you tweet is what we get?

Twitter has a high presence in our modern society, media and science. Numbers of studies with Twitter data – not only in communication research – show that tweets are a popular data source for science. This popularity can be explained by the mostly free data and its technically high availability, as well as the distinct and open communication structure. Even though much research is based on Twitter data, it is only suitable for research to a limited extent. For example, some studies have already revealed that Twitter data has a low explanatory power when predicting election outcomes. Furthermore, the rise of automated communication by bots is an urgent problem of Twitter data analysis. Although critical aspects of Twitter data have already been discussed to some extent (mostly in final remarks of studies), comprehensive evaluations of data quality are relatively rare.To contribute to a deeper understanding of problems regarding the scientific use of Twitter data leading to a more deliberate und critical handling of this data, the study examines different aspects of data quality, usability and explanatory power. Based on previous research on data quality, it takes a critical look with the following four dimensions: availability and completeness, quality (regarding authenticity, reliability and interpretability), language as well as representativeness. Based on a small case study, this paper evaluates the scientific use of Twitter data by elaborating problems in data collection, analysis and interpretation. For this illustrative purpose, the author typically gathered data via Twitter’s Streaming APIs: 73,194 tweets collected between 20–24/02/2017 (each 8pm) with the Streaming APIs (POST statuses/filter) containing the search term “#merkel”.Concerning data availability and completeness, several aspects diminish data usability. Twitter provides two types of data gateways: Streaming APIs (for real-time data) and REST APIs (for historical data). Streaming APIs only have a free available Spritzer bandwidth, that is limited to only one percent of the overall (global) tweet volume at any given time. This limit is a prevalent problem when collecting Twitter data to major events like elections and sports. The REST APIs do not usually provide data older than seven days. Furthermore, Twitter gives no information about the total or search term-related tweet volume at any time.In addition to incomplete data, several quality related aspects complicate data gathering and analysis, like the lack of user specific and verified information (age, gender, location), inconsistent hashtag usage, missing conversational context or poor data/user authenticity. Geo data on Twitter is – if available at all – rarely correct and not useful for filtering relevant tweets. Searching and filtering relevant tweets by search terms can be deceptive, because not every tweet concerning a topic contains corresponding hashtags. Furthermore, it is difficult to find a perfect search term for broader and dynamically changing topics. Besides, the missing conversational context of tweets impedes interpretation of statements (especially with regard to irony or sarcasm). In addition, the rise of social bots diminishes dataset quality enormously. In the dataset generated for this work, only three of the top 30 accounts (by tweet count) could be directly identified as genuine. One fourth of all accounts in this dataset generated about 60% of all tweets. If the high-performing accounts predominantly consist of bots, the negative impact on data quality is immense.Another problem of Twitter analysis is Internet language. While Emojis can be misinterpreted, abbreviations, neologisms, mixed languages and a lack of grammar impede text analysis. In addition to low data quality in general, the quality of tweet content and its representativeness is crucial. This work compares user statistics with research articles on SCOPUS as well as media coverage of two selected, German quality newspapers. Twitter is – compared to its user count – enormously overrepresented in media and science. Only 16% of German adults (over 18 years) are monthly active (MAUs) and merely four percent are daily active users.Considering all presented problems, Twitter can be a good data source for research, but only to a limited extent. Researchers must consider that Twitter does not guarantee complete, reliable and representative data. Ignoring those critical points can mislead data analysis. While Twitter data can be suitable for specific case studies, like the usage and spread of selected hashtags or the twitter usage of specific politicians, you cannot use it for broader, nation-based surveys like the prediction of elections or the public opinion on a specific topic. Twitter has a low representativeness and is mostly an “elite medium” with an uncertain future (concerning the stagnating number of users and financial problems).     

Die Emotionskluft: Wie sich die Printmediennutzung und Gratifikationserwartungen in Einstellungsstrukturen niederschlagenThe emotion gap: How print media usage and expected gratifications influence attitude structures

Regarding formal, linguistic and content-related characteristics, tabloid newspapers have a relatively high potential to emotionally arouse readers, whereas broadsheets present news in a more factual style. In the present study it is argued that the usage of the different types of newspapers affects attitude structures. Specifically, it is assumed that the frequency of usage and expected gratifications during usage have an effect on the affective-cognitive attitude basis. Results of a survey (N = 505) support the hypotheses on the emotion gap: Heavy users of broadsheets base their attitudes on cognitions, regardless of their expected gratifications. For heavy users of tabloid newspapers, expected gratifications moderate the effect of usage on attitude bases: Information-oriented tabloid recipients hold cognition-based attitudes; entertainment-oriented tabloid recipients hold affect-based attitudes.