Identification of research trends in the field of separation processes. Application of epidemiological model, citation analysis, text mining, and technical analysis of the financial markets

Choice of industrial development options and the relevant allocation of the research funds become more and more difficult because of the increasing R&D costs and pressure for shorter development period. Forecast of the research progress is based on the analysis of the publications activity in the field of interest as well as on the dynamics of its change. Moreover, allocation of funds is hindered by exponential growth in the number of publications and patents. Thematic clusters become more and more difficult to identify, and their evolution hard to follow. The existing approaches of research field structuring and identification of its development are very limited. They do not identify the thematic clusters with adequate precision while the identified trends are often ambiguous. Therefore, there is a clear need to develop methods and tools, which are able to identify developing fields of research. The main objective of this Thesis is to develop tools and methods helping in the identification of the promising research topics in the field of separation processes. Two structuring methods as well as three approaches for identification of the development trends have been proposed. The proposed methods have been applied to the analysis of the research on distillation and filtration. The results show that the developed methods are universal and could be used to study of the various fields of research. The identified thematic clusters and the forecasted trends of their development have been confirmed in almost all tested cases. It proves the universality of the proposed methods. The results allow for identification of the fast-growing scientific fields as well as the topics characterized by stagnant or diminishing research activity.

The Use of Data Envelopment Analysis as Equity Portfolio Selection Criterion in the Finnish Stock Market

This thesis examines the application of data envelopment analysis as an equity portfolio selection criterion in the Finnish stock market during period 2001-2011. A sample of publicly traded firms in the Helsinki Stock Exchange is examined in this thesis. The sample covers the majority of the publicly traded firms in the Helsinki Stock Exchange. Data envelopment analysis is used to determine the efficiency of firms using a set of input and output financial parameters. The set of financial parameters consist of asset utilization, liquidity, capital structure, growth, valuation and profitability measures. The firms are divided into artificial industry categories, because of the industry-specific nature of the input and output parameters. Comparable portfolios are formed inside the industry category according to the efficiency scores given by the DEA and the performance of the portfolios is evaluated with several measures. The empirical evidence of this thesis suggests that with certain limitations, data envelopment analysis can successfully be used as portfolio selection criterion in the Finnish stock market when the portfolios are rebalanced at annual frequency according to the efficiency scores given by the data envelopment analysis. However, when the portfolios were rebalanced every two or three years, the results are mixed and inconclusive.

Stock Price Reactions on M&A, Dividends and Game Releases. Evidence from Gaming Industry.

A rapidly growing gaming industry, which specializes on PC, console, online and other games, attracts attention of investors and analysts, who try to understand what drives changes of the gaming industry companies’ stock prices. This master thesis shows the evidence that, besides long-established types of events (M&A and dividend payments), the companies’ stock price changes depend on industry-specific events. I analyzed specific for gaming industry events - game releases with respect to its subdivisions: new games-sequels, games ratings and subdivision according to a developer of a game (self-developed by publisher or outsourced). The master thesis analyzes stock prices of 55 companies from gaming industry from all over the world. The research period covers 5 year, spreading from April 2008 to April 2013. Executed with an event study method, results of the research show that all the analyzed events types have significant influence on the stock prices of the gaming industry companies. The current master thesis suggests that acquisitions in the industry affect positively bidders’ and targets’ stock prices. Mergers events cause positive stock price reactions as well. But dividends payments and game releases events influence negatively on the stock prices. Game releases’ effect is up to -2.2% of cumulative average abnormal return (CAAR) drop during the first ten days after the game releases. Having researched different kinds of events and identified the direction of their impact, the current paper can be of high value for investors, seeking profits in the gaming industry, and other interested parties.

Information and appearance - design creating value for wearable technology items in B2C markets

The objective of the thesis is to study the role of design in adding value for wearable technology (WT) items in B2C markets by applying previous value creation literature to the subject. The thesis investigates value creation through types of value perceived by the customer being functional/instrumental, experiential/hedonic, symbolic/expressive and cost/sacrifice. The data was collected in face-to-face interviews with both consumers and industry experts. The results suggest that value perceived by both experts and consumers in every end-user category was elementarily functional, however, design was considered to bring most added value to WT in the categories of health and medicine, infotainment, and fashion. Also, WT ought to have same characteristics as regular clothing in order to attract mass markets. The results of the study suggest that companies should invest in design in order to gain long-term user engagement.

The role of network externalities in value creating process of the commercial web service for two-sided international markets

Network externalities and two-sided markets in the context of web services and value creation is not very well discussed topic in academic literature. The explosive rise of the Internet users has created a strong base for many successful web services and pushed many firms towards e-business and online service based business models. Thus the subject of this thesis, the role of network externalities in value creating process of the commer-cial web service for two-sided international markets is very current and interesting topic to examine. The objective of this Master’s Thesis is to advance the study of network externalities from the viewpoint of two-sided markets and network effects as well as describe the value creation & value co-creation process in commercial web service business models. The main proposition suggests that the larger network of customers and the bigger number of users the web service is able to attract, the more value and stronger positive net-work externalities the service is able to create for each customer group. The empirical research of this study was implemented for commercial web service, targeted to Russian consumers and Finnish business users. The findings suggest that the size of the network is highly related to the experi-enced value of the customers and the whole value creation process of commercial web targeted for two-sided international markets varies from the value creation for one-sided or pure domestic markets.

Customer value assessment in business markets

Understanding how firms create, communicate, and deliver value to customers is a key factor when firms seek to differentiate in increasingly competitive and commoditized business markets. As product and price have become less important differentiators in many industries, suppliers are increasingly seeking ways to differentiate themselves based on delivered customer value. Therefore, to gain a holistic understanding on what their offerings are worth to the customer, suppliers need to conduct customer value assessment, which quantifies the impact of a supplier´s offering to customers’ costs and returns. However, from a managerial perspective, customer value assessment is the single most critical challenge for firms in business markets. Consequently, developing holistic frameworks for customer value assessment is seen as one of the most important research priorities for marketing research. The purpose of this study is to explore the process of customer value assessment in business markets. Business markets represent a context where an increasing number of industrial firms are transitioning from basic product offerings towards service-based and solution-oriented hybrid offerings, which emphasize value co-creation and realization in the long term, thus making it difficult to quantify their monetary value. This study employs exploratory and qualitative research design by applying inductive and discovery-oriented grounded theory and multiple case research methods. The empirical data comprise interviews with 61 managers from 12 industrial firms, including seven best practice firms in customer value assessment. The findings of this study show that customer value assessment is essentially a crossfunctional process, which involves several organizational functions. The process begins well before and continues long after the actual delivery, often until the end of a supplier´s offering’s life-cycle. Furthermore, the findings shed light on alternative strategies that firms in business markets can adopt to implement the customer value assessment process. Overall, the findings contribute to customer value research, the sales and organizational management literature, the service marketing and solutions business literature, and suggest several managerial implications on how firms in business markets can adopt a holistic approach to assess value created for customers.

Insiders´ views as a predictor of stock performance : can insider trading be used to predict stock performance on the United States stock market?

This thesis studies the possibility of using information on insiders’ transactions to forecast future stock returns after the implementation of Sarbanes Oxley Act in July 2003. Insider transactions between July 2003 and August 2009 are analysed with regression tests to identify the relationships between insiders’ transactions and future stock returns. This analysis is complemented with rudimentary bootstrapping procedures to verify the robustness of the findings. The underlying assumption of the thesis is that insiders constantly receive pieces of information that indicate future performance of the company. They may not be allowed to trade on large and tangible pieces of information but they can trade on accumulation of smaller, intangible pieces of information. Based on the analysis in the thesis insiders’ profits were found not to differ from the returns from broad stock index. However, their individual transactions were found to be linked to future stock returns. The initial model was found to be unstable but some of the predictive power could be sacrificed to achieve greater stability. Even after sacrificing some predictive power the relationship was significant enough to allow external investors to achieve abnormal profits after transaction costs and taxes. The thesis does not go into great detail about timing of transactions. Delay in publishing insiders’ transactions is not taken into account in the calculations and the closed windows are not studied in detail. The potential effects of these phenomena are looked into and they do not cause great changes in the findings. Additionally the remuneration policy of an insider or a company is not taken into account even though it most likely affects the trading patterns of insiders. Even with the limitations the findings offer promising opportunities for investors to improve their investment processes by incorporating additional information from insiders’ transaction into their decisions. The findings also raise questions on how insider trading should be regulated. Insiders achieve greater returns than other investors based on superior information. On the other hand, more efficient information transfer could warrant more lenient regulation. The fact that insiders’ returns are dominated by the large investment stake they maintain all the time in their own companies also speaks for more leniency. As Sarbanes Oxley Act considerably modified the insider trading landscape, this analysis provides information that has not been available before. The thesis also constitutes a thorough analysis of insider trading phenomenon which has previously been somewhat separated into several studies.

Prediction of market switching and delisting events from OMX First North Nordic multilateral stock exchange

This thesis studies the predictability of market switching and delisting events from OMX First North Nordic multilateral stock exchange by using financial statement information and market information from 2007 to 2012. This study was conducted by using a three stage process. In first stage relevant theoretical framework and initial variable pool were constructed. Then, explanatory analysis of the initial variable pool was done in order to further limit and identify relevant variables. The explanatory analysis was conducted by using self-organizing map methodology. In the third stage, the predictive modeling was carried out with random forests and support vector machine methodologies. It was found that the explanatory analysis was able to identify relevant variables. The results indicate that the market switching and delisting events can be predicted in some extent. The empirical results also support the usability of financial statement and market information in the prediction of market switching and delisting events.

Stock Market reaction to the CSR announcements of American fast food companies

The purpose of this study is to examine whether Corporate Social Responsibility (CSR) announcements of the three biggest American fast food companies (McDonald’s, YUM! Brands and Wendy’s) have any effect on their stock returns as well as on the returns of the industry index (Dow Jones Restaurants and Bars). The time period under consideration starts on 1st of May 2001 and ends on 17th of October 2013. The stock market reaction is tested with an event study utilizing CAPM. The research employs the daily stock returns of the companies, the index and the benchmarks (NASDAQ and NYSE). The test of combined announcements did not reveal any significant effect on the index and McDonald’s. However the stock returns of Wendy’s and YUM! Brands reacted negatively. Moreover, the company level analyses showed that to their own CSR releases McDonald’s stock returns respond positively, YUM! Brands reacts negatively and Wendy’s does not have any reaction. Plus, it was found that the competitors of the announcing company tend to react negatively to all the events. Furthermore, the division of the events into sustainability categories showed statistically significant negative reaction from the Index, McDonald’s and YUM! Brands towards social announcements. At the same time only the index was positively affected by to the economic and environmental CSR news releases.