132 resultados para Global regulators

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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So-called sin industries are often related to harmfulness, unethical business, and unproductiveness. Nowadays, the alcohol, gambling, and tobacco industries are most often considered to be part of sin industries, which is also the context of this study. However, the definition of a sin industry is always related to time and culture. Despite the controversies of sin industries, there are studies that have shown that corporate social responsibility (CSR) engagement is even more important for sin industries than for normal industries and that CSR has a positive effect on firm value in sin industries. With CSR this study refers to an ideology where company takes mostly voluntary actions towards various groups of stakeholders and the environment. In other words, the company goes beyond the legal norms and regulations. In particular, the purpose of this thesis is to find out how companies, operating in the online gambling industry, communicate about their CSR actions to consumers at their web pages. The online environment is essential for this study as online gambling environment is a source of many controversies in comparison to the traditional gambling halls and casinos. These include, for example, greater accessibility, anonymity, and availability of the service. This study uses qualitative textual analysis as its approach, more precisely the discourse analysis. In addition, as this study focuses on large international companies and their actions, also case study approach will be presented. The cases studied are Mybet, Unibet, and Bwin.Party. In order to study the subject, elements from discourse analysis are combined with insights of essential CSR theories, and the specific characteristics of the online gambling industry. As a background for the framework, this study uses the framework of Du & Vieira (2012). After analyzing the discourses of CSR communication and CSR practices, it seems that all of the case companies still do not use all the potential that the online environment provides in terms of CSR or stakeholder communication. There are large differences between different communication tools used at different web pages (gambling pages vs. corporation pages) and between the firms’ CSR profiles. Moreover, there are large differences in the CSR practices used in the web pages of the case companies. The findings of this study are partially alarming as the case companies represent the largest companies in the industry. There are major varieties between the companies’ CSR communication and clear shortcomings in some parts of the online communication. Moreover, the trust of the consumer was broken in some places. If this is the standard that the biggest players in the industry have set with regards to CSR communication, it is probable that the smaller players are performing even worse. Moreover, the regulators are most likely concentrating on the larger companies, so the smaller companies might have fewer incentives and pressure to perform according to the regulations or exceeding the legislation. The conclusions of this thesis provide insights to managers, regulators, and scholars. Suggestions for future studies are provided as well.

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Selostus: Maatalous pohjoisilla äärialueilla: ilmastolliset rajoitukset ja ilmaston muutosten vaikutukset viljelyyn

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Selostus: Ilmaston lämpenemisen vaikutus perunaruttoon

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Selostus: Typpilannoituksen ja kasvunsääteiden vaikutukset kevätviljojen ja rypsin satoon sekä typen käyttöön

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Selostus: Aikaisen ja tavanomaisen kasvunsäädekäsittelyn vaikutus kevätviljojen kasvustoon ja satoon

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Vol.23, No. 5, pp. 1024-1037, 2007.

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Localization, which is the ability of a mobile robot to estimate its position within its environment, is a key capability for autonomous operation of any mobile robot. This thesis presents a system for indoor coarse and global localization of a mobile robot based on visual information. The system is based on image matching and uses SIFT features as natural landmarks. Features extracted from training images arestored in a database for use in localization later. During localization an image of the scene is captured using the on-board camera of the robot, features are extracted from the image and the best match is searched from the database. Feature matching is done using the k-d tree algorithm. Experimental results showed that localization accuracy increases with the number of training features used in the training database, while, on the other hand, increasing number of features tended to have a negative impact on the computational time. For some parts of the environment the error rate was relatively high due to a strong correlation of features taken from those places across the environment.