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KU Leuven (2)


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dissertation (2)


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English (2)


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2022 (1)

2015 (1)

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Dissertation
Green Identity and Image Communication on Website in China : Analysis of Volkswagen's Think Blue Plan
Authors: --- --- ---
Year: 2015 Publisher: Leuven : KU Leuven. Faculteit Letteren

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Abstract

Corporate identity and image are known to affect the performance of a firm. Identity refers to how a firm presents itself to its stakeholders, and image is the impression of the firm in the minds of its stakeholders. Green identity and image are becoming more popular as the environmental crisis becomes more pronounced. Green identity and image can be communicated via the environmental initiatives and activities of a company. Effective communication of green image and identity has the ability to benefit the company via cost savings and risk reduction. A website is a primary way to communicate green identity and image. Communicating environmentally friendly features is based on two concepts according to the literature: the 'green' concept and the 'sustainability' concept. These two concepts can be explored via products, technologies, personal responsibility, emissions and the work environment. Previous studies have shown that communications deriving from the company will tend to frame the activities and efforts of a company as being good for the environment; these documents will avoid mentioning any bad influence that the company has on the environment. When communicating green identity and image, a company can raise suspicions by 'greenwashing,' which involves making claims that mislead stakeholders about the company's initiatives. This dissertation focuses on linguistic research. It will examine the framing texts, word use, and text about green corporation identity and image. The analysis will be largely based on Volkswagen's Chinese website in order to discuss how texts communicate green identity and image. This work will include a close reading of the Volkswagen website to examine the genre, the framing of the texts, and any potential greenwashing. Volkswagen has been promoting itself as an environmentally friendly company in several interviews and reports. The aim of this dissertation is to examine whether Volkswagen is really a green company or if it is simply greenwashing its communication text. Furthermore, this dissertation will investigate whether Volkswagen's website text is written in the genre and frames of the results of previous studies. This dissertation will employ AntConc software, a powerful linguistic analysis tool that is able to read Chinese. Word analysis, keywords lists, and the contexts of some key words will be furthermore investigated. We may conclude that Volkswagen China does communicate a green identity and image via products, technologies, personal dimension responsibility and emissions. Products and technologies account for the most percent, which means that the majority of text on the website is communicating these two terms. The term 'work environment' is not mentioned on Volkswagen's Chinese website. The text on the website emphasizes how the company benefits the environment; poor impacts on the environment are not mentioned. There is evidence of greenwashing on the website, but not all text is greenwashing. Text that is suspected to contain greenwashing has been mainly collected from joint venture's website of Volkswagen.

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Dissertation
The Herd Behaviour Index: An algorithmic realisation in R
Authors: --- --- ---
Year: 2022 Publisher: Leuven KU Leuven. Faculteit Economie en Bedrijfswetenschappen

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Abstract

This thesis provides an algorithm for calculating the Herd Behaviour Index (HIX), which is a model-free measure introduced by Dhaene et al. (2012), aiming at quantifying the degree of co-movement implied in the stock market. The algorithm is demonstrated through calculating the HIX for the Dow Jones Industrial Average (DJIA), namely the DJ-HIX, in January 2008. Different from the practice of Dhaene et al. (2012), it uses the minimal necessary information about the options of the DJIA and its constituents. The results show that, while the DJ-HIX computed by the algorithm are on average 10% higher than the results given by Dhaene et al. (2012), they follow almost the same trend. It is revealed that, by using different methodologies for determining the K-support, the results may deviate significantly. It is recommended to take further research on the issue to find an ideal criterion for the K-support determination.

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