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In the world of internet marketing, search engine optimization is a popular term. Getting higher rankings on the search engine and thereby getting more views to advertiser’s site is basically what it is. However, those views will not mean a lot if they do not lead to sales or conversion. Search advertisers join an online auction in order to get a slot in the search engine results pages. This means, in Pay per Click online model, advertisers have to pay to the search engine for the number of clicks on the advertisement they posted. Therefore, predicting conversion likelihood for advertisers is highly crucial for the sake of the revenue. Besides, being able to understand and track the conversion rates not only allows advertisers to measure the performance of the web pages but also to identify areas for improvement. In this study, machine learning is used for predicting the conversion rate using search term queries in google shopping ads. The purpose is to analyse if a pattern on search term queries to predict conversion rate can be observed. Search term queries with a high probability of better conversion rate can be advertised more. While the bids on low-conversion segments can be lowered to reduce the costs. For this purpose, extracting features from the text to represent it in a way that can be understood by the machine like term frequency and paragraph vector are tested on machine learning and deep learning model. The results show that different patterns of search term queries do not lead to a predictable conversion rate in the specific use case. Thus, the search term itself is no indicator for good or bad conversion rate.
Hypothesis Extraction from Academic Papers Using Neural Networks for Ontology Theory Learning
(2019)
In this study, we investigated a new use case of deep learning. We applied deep learning to extract causes and effects from the hypotheses of the scientific papers. The research presents a variety of RNN models, including RNN models with CRF layer for labelling the sequences. We used such models as Bi-LSTM, LSTM, SimpleRNN and GRU. The experiments were conducted with GloVe vector representation and character level vector representation of words. Moreover, along with RNN models, we evaluated various hyperparameters and model setups to achieve the highest performance scores. In the end, we obtained promising results and shared our thoughts on the future prospects of the following studies.
The Efficient Market Hypothesis would lead one to believe that stock markets are perfectly efficient and that abnormal/ deviant average returns are not possible. However, the existence of calendar anomalies empirically shows how specific periods during a week, month and year can influence the average returns in the stock markets. Research from scholarly journals and books, industry-related news sources, and industry-experts shows the occurrence of various calendar anomalies in global markets that led to unbalanced average returns and confronted the fundaments of the Efficient Market
Hypothesis.
The role of branding in a marketing strategy against counterfeiting for high-fashion companies
(2019)
This thesis examines the effectiveness of the latest Transfer Learning techniques for Natural Language Processing applied to the classification of research methods used in scientific journals in the domain of Information Systems. The task of automated knowledge extraction from academic articles has seen ongoing progress in recent years. However, the combination of transfer and Deep Learning in order to assign research methods to scientific papers has not been addressed in the literature yet. The main contribution of this thesis is, therefore, an artifact that applies cutting-edge Transfer Learning techniques to a Deep Learning model by conducting several experiments and comparing their effectiveness. The prototype considers various ways of fine-tuning that are crucial to retain the knowledge transferred from pretrained models and avoid catastrophic forgetting. Additionally, this work discusses the literature with regard to the task-specific Theory Ontology Learning and the method-specific state of the art in Transfer Learning for Natural Language Processing. As a result, the artifact surpassed the performance of previously developed models for research method extraction, presented in the literature, without applying any custom feature engineering and only using around a thousand of labeled observations.
This thesis is based on a research regarding one of the most important profession in corporate world, namely Forensic Accountant, which recently its role is highly demanded. With the purposes to support the government and the corporate of detecting and preventing fraud from the inside of company, Forensic Accountant plays an important role in corporate crime world, especially accounting fraud.
This thesis aims to show the corporates and the government in Germany about how important the role and function of Forensic Accountant to help them by preventing, detecting, and even investigating accounting fraud that has been committed by the employees. From the rate of committed fraud in a global scale and national scale as a comparison, the efforts of anti-fraud that have been done so far by the company, an example of case study regarding accounting fraud, to the discussion of the possibility and effectiveness of Forensic Accountant in Germany will all be provided in this thesis.
European Neighboorhood Policy as a power instrument of the Euopean Union: the case Azerbaijan
(2019)
In order to contribute to our planet’s sustainability, a sustainable diet is inevitable. It turns out to be a challenge for consumers to identify the food products’ degree of sustainability. In this regard, quality labels can be a help. However, the latter contributes, inter alia, to consumer confusion. The latter occurs when the cognitive processing of product information is being disrupted, which can lead to postponing or abandoning the purchase decision. The present work determines the most relevant aspects of sustainability in the food context on the German market from a consumer’s perspective. Furthermore, it is being figured out, which requirements a quality label needs to meet when aiming to reduce consumer confusion.
The present thesis aims to give an overview on alternative forms of work and the current coworker in regard to gender, age, profession, and motivation to work in a coworking space. The growing number of coworking spaces available to an increasing number of workers explains and justifies the analysis of a current inventory. The economic and social changes influence the way people work. Younger generations and university graduates, in particular, are disproportionately engaged in non-standard employment relationships. This development in connection with the detachment of work and workplace opens up possibilities of alternative forms of work. Coworking spaces are only one example resulting from this change but will be the focus of this thesis.
The following research question is being asked: Coworkers, who are they and how are they using this alternative form of work? To answer the research question, a quantitative survey was conducted which addressed current coworking members.
The results showed that coworking spaces are mainly used by young academics who work as freelancers or self-employees. Coworking spaces constitute an alternative to home-office for various professional groups. Thereby, the alternative form of work is preferred over traditional offices. Considering the increasing number of atypical employment relationships, mobile workers, and coworking spaces it is most likely that these spaces will gain in importance and will impact the world of work in the future.
This thesis as well as the survey results are interesting for coworking space owners, for companies, and for politicians.
This paper aims to introduce a new topic for the economic policies associated with financial instability, both theoretically and through data analysis, discussing the roots of instability and the policy recommendations in the literature of Minsky and examining the role of National Development Banks (NDBs) in the economy. The purpose of the work is to acknowledge NDBs as Thwarting Institutions in a Minskyian sense. These special financial institutions have two sides of effects in the economy, one side related to their financial nature, through their capacity to provide finance to key sectors of the economy, and the other related to the real effects the financing of development projects implicate. Due to these influences, National Development Banks can be considered strong pillars to strengthen the economy, providing additional mechanisms for economic policies for stabilisation and recovery purposes, which is the definition of Thwarting Institution. The study case of the Brazilian National Bank for Economic and Social Development (BNDES) provided a detailed data analysis of the general performance of the bank between 2000-2018, its importance for the economy and especially the countercyclical role of the bank after the 2008s’ financial crisis. The last section will provide the analysis of financial stability in Brazil, showing important variables both from the financial and real side of the economy, in accordance with the Minskyian theory.
Cash, Less Cash and Cash-less: An Analysis of the Preferred Payment Methods in Germany and Sweden
(2019)
This paper focuses on the preferred payment methods in Sweden and in Germany. The current trends will be explored to find out which differences there are in regards to this matter and why. A cross-country analysis is made considering the costs, safety, and other important features of cash versus non-cash payment methods. Sweden is considered a country that is using less and less cash, almost on the way to becoming a cashless society. Germany on the other hand has stayed loyal to their Euro-banknotes and coins, with it being the most popular method at point-of-sales transactions. This is due to their different social norms, which have been shaped by their countries’ histories.
Is Germany going to follow in Sweden’s footsteps and turn away from cash?
No, not any time soon.
This paper will focus on inequality, especially on income inequality as an indicator for economic well-being. The purpose is to look at how income inequality is defined and measured, and the global development thereof and consequent drivers, and how a state can redistribute income, including through fiscal policies. A geographical focus will be drawn, as Germany and the United States will be examined in more detail. Also, a short examination of key differences between the two to-be-examined countries will be made to gain insights on how two advanced economies can show such distinct differences in inequality. In the end the author hopes to suggest policy relevant focuses in the hopes of decreasing income inequality in the future.
Sequential Statistical Testing Procedures as an Early Stopping for Binomial Bandit Experiments
(2019)
This study tries to provide an early stopping procedure on binomial bandits which is a type of multi-arm bandit experiment. In addition to that, it presents sequential statistical testing procedures which can be used as early stopping criteria for A/B experiment. The paper searches for the applicability of these procedures for binomial bandit case because multi-arm bandit experiment and A/B experiment are similar in the sense that rewards can be simulated as independent identical Bernoulli distribution.
It is often claimed that multi-armed bandit which use Thompson sampling requires dramatically less sample size than A/B testing while still controlling the type 1 and type 2 error rates on alpha and beta due to the concept of always switching to the better arm. However, it is also claimed that Bayesian procedures are not immune to peeking (early stopping) because of the structure of sequential testing.
The sequential statistical testing procedures reduce the required number of observations and allow the experiment to stop early when the collected data is good enough to make a conclusion. In this work, Wald’s SPRT and Max SPRT-I-AA (a modified version of Max SPRT) sequential statistical testing procedures are studied for the A/B testing, and their applicability to binomial bandit case is researched.
According to simulation results, Max SPRT-I-AA sequential statistical testing procedure perform well for the A/B test scenarios. The type 1 and type 2 error rates are remains on the acceptable level and the experiment time is reduced more than 50 %. However, for the binomial bandit case results are not so satisfactory and brings more questions about the applicability of Max SPRT-I-AA to multi-arm bandits because of the performance of upper boundary calculation.
The study examines the relationship between team development stages, team coaching and managerial coaching and its effect on the employees and team alignment. Previous researched has shown the influence of team development stages on the team growth and understanding of their identity role in the team. The understanding of the coaching process helps to recognize the outcome and the role of the coaching on the one hand the individual and on the other hand the team as a whole. Two case studies regarding the outcomes of team coaching clarified the issue with the indi-vidual in the organization and the business environment. The important contribution of this thesis is to highlight the affect and the mixture of team development, team coaching and managerial coaching on the team align-ment. Many research before showed the impact of team alignment to the success of the company or the organization. This thesis hypothesized that team coaching, managerial coaching and team development stages they all together play a role in the alignment of the team and increase the or-ganization success. A qualitative approach was pursed with experts inter-view in order to use their explicit and implicit knowledge. As predicted, the findings from the research revealed the influence of the three elements on the team alignment and the organizational success. The paper concluded that team coaching, managerial coaching and team development all to-gether are a powerful tool to create team alignment in the organization and influence the organization success.
The paper under consideration focuses on the network approach to internationalization. According to it, the choice of a country to which a firm internationalizes as well as the market entry mode are influenced by bilateral relations, i.e. firm’s networks. The aim of the given thesis is to explore the influence of bilateral relations on the internationalization process of the selected enterprises in the wind power industry.
As to the methodological framework, in line with the aim of the research paper under consideration the deductive approach has been applied. In order to answer the research questions and to meet the research objectives, the author decided to use the multiple-case study holistic design method, i.e. the research spreads over three world’s largest enterprises in wind power industry and focuses on every case in its totality.
The empirical part proves that bilateral relations do influence the internationalization path of the selected enterprises. Additionally, due to the fact that wind turbine producers under study are conglomerates, they are characterized by a relatively higher degree of resources commitment than non-conglomerate companies.
In this paper the concept of startups is explained in more detail, occasions for the valuation of these type of companies and the procedures for determining the company value presented. Two processes, the Multiples approach and the DCF method are applied to one example case. Finally, the results of both methods are compared and evaluated. For future work, there are also further possibilities for company valuation by young companies.
This paper focuses on the European stock market and the forces that determine the stock price movements on it. As a basis for the analysis, well known and used factor models’ methodology is applied for the investigation and explaining of the variance of the returns on the European stock market. An emphasis in the analysis is put on the description power of fundamental risk factors along with the momentum factor. As a result, five factors show abilities in explaining the returns in Europe. Particularly, the QMJ (Quality minus Junk), SMB (Small minus Big), PE (Price-to-Equity), ILLIQ (Illiquidity) and DE (Debt-to-Equity) show the greatest explanatory power among the overall 27 tested risk factors. Furthermore, a factor model constructed of the five aforementioned risk factors managed to achieve on average the greatest explanatory power when tested with six other famous factor models.