Dynamic and Comparative Static Analysis of Imperfectly Competitive International Fishery

A dynamic system for change of fish stock is formulated assuming that two asymmetric rival countries harvest fish from a common fishing ground and sell it in an imperfectly competitive market. The existence of a unique stable steady state is examined based on the dynamic system. Comparative static analysis is conducted in relation to changes in national fishing management policies to explore, among other things, rent-shifting from one country to another.     

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).     

Approximate maximum likelihood estimation for stochastic differential equations with random effects in the drift and the diffusion

Consider N independent stochastic processes \((X_i(t), t\in [0,T])\), \(i=1,\ldots , N\), defined by a stochastic differential equation with random effects where the drift term depends linearly on a random vector \(\Phi _i\) and the diffusion coefficient depends on another linear random effect \(\Psi _i\). For these effects, we consider a joint parametric distribution. We propose and study two approximate likelihoods for estimating the parameters of this joint distribution based on discrete observations of the processes on a fixed time interval. Consistent and \(\sqrt{N}\)-asymptotically Gaussian estimators are obtained when both the number of individuals and the number of observations per individual tend to infinity. The estimation methods are investigated on simulated data and show good performances.     

Digitale Spaltung im Zeitalter der S?ttigung

Using Bourdieu??s Habitus-Capital theory and a representative dataset this study shows that social position influences internet use. The study is thus connected to the research about thedigital divide. A secondary analysis of the ACTA 2008 (n?=?7.623, representative of Germans between 14 and 64 years who use the internet) shows on the one hand that there are still gaps in internet usage (gender, generation, and education gap). On the other hand the results indicate acapital gap. Since the accumulation of capital in the internet is connected with education as well as economic status, there is a threat of a downward spiral: Those who have less capital (education, money) gather less internet knowledge. Since cultural capital influences a person??s social position, internet use enhances social inequality.     

The impact of advertising content on movie revenues

We analyze the contents of print ads in the motion picture industry (e.g., number of reviews quoted in the ad, the presence of a top reviewer, size of the ad, star, director, etc.). We find that external validation (a recommendation by a top reviewer) is more important to revenues than the informative content of the ad.     

Unobserved firm heterogeneity and the size-exports nexus: Evidence from German panel data

This paper starts from the stylized fact that firm size and exporting tends to be positively related. Using large sets of establishment panel data for three different industries from official statistics, evidence is presented that the familiar picture of an export/sales ratio that increases (at a decreasing rate) with firm size vanishes if unobserved firm heterogeneity is controlled for in a fixed-effects fractional logit regression model. This finding is well in line with the fact that many small firms are “hidden export champions.” JEL no. F10, D21, L60     

Coordination in retailer-carrier channels for long term planning

We study a retailer-carrier channel for the purpose of long term planning and coordination. Here, the term channel represents the business interaction between the retailer and the carrier. The retailer sells a particular item with price-dependent demand, whereas the carrier is responsible for transporting the item to the retailer's site. We characterize the profit functions of each channel member as well as the total channel profit. We consider two specific channel structures: (i) the centralized channel and (ii) the decentralized channel. Under the first channel structure, the goal is to set the retail price so as to maximize the total channel profit. Under the latter, the carrier and the retailer choose their own policy parameters, i.e., the freight rate for the carrier and the retail price for the retailer, so as to maximize their individual profits. We model the decentralized channel as a Stackelberg Game and propose a coordination mechanism between the retailer and the carrier in which the retailer signals a price multiplier to the carrier. We illustrate that this mechanism could provide win-win solutions for both parties and present analytical and numerical results on the efficiency of channel coordination. We demonstrate that coordination in retailer-carrier channels can be as promising as supplier-retailer channels. We also discuss the effects of retailer-carrier coordination on inventory levels.     

The role of the entrepreneurial team and the board of directors in the internationalization of academic spin-offs

This study addresses the roles of the entrepreneurial team and the board of directors in the internationalization of academic spin-off companies. The study is based on a quantitative analysis of 109 spin-offs from Norwegian academic institutions. The findings suggest that academic spin-offs are more likely to achieve both international strategic alliances and international sales with entrepreneurial teams having industrial experience that is both highly homogeneous (where each member has work experience in the same industry) and highly diverse (where each member has work experience in different industries) and board members that have diverse functional backgrounds. Firms that are less dependent on networking by board members to increase legitimacy and build relationships with potential foreign customers are more likely to achieve international sales.     

Assessing social support networks in cross-national comparative surveys: Measurement issues

In recent years many cross-national comparative surveys, such as Gender and Generation Programme, International Social Survey Programme, European Quality of Life Survey, or General Social Survey, have included assessment of social support networks. Generally, two approaches were used; the name generator approach and the role relation approach. As more cross-country surveys are conducted every year, it may seem reasonable to use such data sets, since they provide high quality comparisons across countries. However, one should pay close attention to the measurement instruments, as these may cause unintentional but systematic variability in the observed data. While the data from each survey can be of high quality ??per se??, we claim that results from these surveys are not comparable, owing to their different measurement approaches and survey instruments. In this paper we present data from several experiments which show that scientific findings from these surveys depend significantly on questionnaire design.     

Learning to trust strangers: an evolutionary perspective

What if living in a relatively trustworthy society was sufficient to blindly trust strangers? In this paper we interpret generalized trust as a learning process and analyse the trust game paradox in light of the replicator dynamics. Given that trust inevitably implies doubts about others, we assume incomplete information and study the dynamics of trust in buyer-supplier purchase transactions. Considering a world made of ??good?? and ??bad?? suppliers, we show that the trust game admits a unique evolutionarily stable strategy: buyers may trust strangers if it is not too risky to do so. Examining the situation where some players may play either as trustor or as trustee we show that this result is robust.